Rhode Island K-12Computer Science Education Standards
April 2018
Table of Contents
AcknowledgmentsOur Vision for Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Advisory Committee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Computer Science & Relevance to Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
Alignment with National Efforts / Organizations and Key Documents Referenced . . . . . . . 6
Process & Timeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Guiding Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Equity in Computer Science Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Computational Thinking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
Standards/Grade Bands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11
Implementation of Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Core Concepts & Sub-Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1. Computational Thinking & Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2. Computing Systems & Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3. Cybersecurity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4. Data & Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
5. Digital Literacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
6. Responsible Computing in Society . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Reading the Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
K-12 Computer Science Education Standards. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24
Appendices
Appendix A: K-12 Computer Science Education Standards (with descriptions) . . . . . . 39Appendix B: Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Appendix C: Glossary References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
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Acknowledgements
The development of the Computer Science Education Standards was a statewide collaboration withcontributions from a diverse group of Rhode Island stakeholders. I express my deepest appreciationto the Advisory Committee that gave up one Saturday a month for almost a year to review, evaluate,revise, and write the new standards. Their extraordinary dedication, enthusiasm, and thoughtful-ness made the standards a reality. Special thanks go to Chris Allen, Kathi Fisler, Tim Henry, JoeMazzone, Ilona Miko, and Vic Fay Wolfe for providing team leadership as we progressed. A veryheartfelt thank you to Kathi Fisler and Ilona Miko for going above and beyond their responsibilitiesby devoting extra time and effort through extensive review, editing, discussion, and support.
I acknowledge, with much appreciation, the Review Team that looked at the draft standards withfresh eyes, and provided insightful comments and suggestions. Members of the public also con-tributed time and attention to reviewing the draft standards, and I thank them for invaluable feed-back. I express my gratitude to the experts in the cybersecurity field and specialists indigital/media/instructional literacy who critiqued relevant sections of the standards.
A special note of thanks to Pat Yongpradit (Code.org), Peter McLaren (Next Generation Science Stan-dards Writing Team Member), John Bilotta (Rhode Island Society of Technology Educators), andTommy Gober and Kevin Nolten (Cyber Innovation Center) for their guidance, support, and encour-agement.
The development of the Computer Science Education Standards for Rhode Island would have beenimpossible without the support of the van Beuren Charitable Foundation, and especially senior pro-gram officer Deborah S. Linnell.
Last but not least, many thanks to CS4RI and the Rhode Island Department of Education (RIDE) forhelping us achieve our goal of developing comprehensive computer science education standards forRhode Island.
The excitement and eagerness with which everyone approached this project is testament to the beliefthat all Rhode Island students deserve the best education for future success.
Carol M. Giuriceo, Ph.D.Chair, Computer Science Education Standards Advisory CommitteeDirector, Rhode Island STEAM Center @ Rhode Island College
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Our Vision for Rhode Island
Our students, including those historically underrepresented, understand the value, influence, andrelevance of computer science education. We believe that increased use and mastery of compu-tational thinking through the grade levels builds human capacity, and allows students to becomeinformed users, as well as active creators, of technology. Students shall thoughtfully and ethicallyapproach personal and societal challenges and participate in finding solutions to local, regional, andglobal issues.
Our educators collaborate within communities of professional practice as computer science becomesthe multi-disciplinary bridge across school districts. We believe that an engaged citizenry emergesfrom a strong focus on essential life and career skills, problem-solving abilities, and lifelong commit-ment to learning, which positions Rhode Island as a leader in technology and a premier innovativecenter in the United States.
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Introduction
In January 2017, the Rhode Island STEAM Center organized and convened a statewide ComputerScience (CS) Education Advisory Committee, with funding from the van Beuren Charitable Founda-tion, with the goal of creating CS education standards for Rhode Island. The impetus for this workwas the current momentum surrounding the implementation of CS education in K-12 through theComputer Science for Rhode Island (CS4RI) initiative and the recent national emphasis on computerscience education.
In March 2017, the CS Education Standards Advisory Committee, composed of Rhode Islandersfrom across the state, met to begin work on developing and aligning with the nationally-recognizedK-12 Computer Science Framework (released October 2017), the Computer Science Teachers Associ-ation (CSTA) Computer Science Standards (draft standards November 2016; final standards releasedJuly 2017), and CS standards work in other states.
The Advisory Committee represented a broad range of expertise. We included elementary, middle,and high school teachers, district coordinators and administrators, higher education faculty, and in-dustry professionals. Some members had computer science expertise; others were pedagogy expertsand understood the value and use of academic standards. All served pro bono. Committee meetingsoccurred one Saturday a month through December 2017. During this time, we reviewed existingstandards, evaluated practices, and identified core concepts.
We chose to adapt rather than adopt, the CSTA K-12 Standards because we wanted to create stan-dards that retained the rigorous and collaborative work of the CSTA yet also related to the needs ofRhode Island. Our adaptations include:
• reorganizing the standards into concepts that we believe more accurately describe our focusand create logical progressions without too much overlap
• forming a new Digital Literacy concept focused on the use of computing devices, recogniz-ing its fit alongside the current Information Literacy standards (recently revised) and MediaLiteracy standards (in development)
• forming a new Cybersecurity concept and recognizing its increasing global relevance, as wellas Rhode Island’s growing and economically-relevant cybersecurity sector
Throughout the process, we focused on creating pathways that set realistic expectations for all stu-dents and can be implemented in a sustainable way in Rhode Island. They do not represent a com-prehensive list of all topics within computer science.
Most of all, we kept equity at the forefront of our discussions. We believe that increased use andmastery of computational thinking through the grade levels builds human capacity.
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Advisory Committee
• Chris Allen, NBCT, Fourth Grade Teacher, Greenbush Elementary School, West Warwick Pub-lic Schools
• Jenny Chan-Remka, Ed.D., Assistant Superintendent, Woonsocket Education Department
• Michelle Conary, Computer Literacy Instructor, Chariho Middle School, Chariho RegionalSchool District
• Jane L. Daly, Assistant Superintendent of Schools, Chariho Regional School District
• Vic Fay-Wolfe, Ph.D., Computer Science, University of Rhode Island
• Kathi Fisler, Ph.D., Research Professor, Computer Science, Brown University/Co-Director,Bootstrap
• Carol M. Giuriceo, Ph.D., Director, Rhode Island STEAM Center @ Rhode Island College
• Lenora E. Goodwin, Consulting Teacher, Teacher Retention and InductionNetwork (T.R.A.I.N.),Providence Public Schools
• Timothy Henry, Ph.D., Professor, IT Graduate Director, New England Institute of Technology
• Dominic Herard, Mathematics & Computer Science Teacher, Times Squared STEM Academy,Providence
• Verda Jones, Business & Technology Instructor, Shea Senior High School, Pawtucket SchoolDistrict
• Ramarao Koppaka, Staff Vice President, Principal Enterprise Architect, FM Global
• Linda Larsen, Director of Education Outreach & Workforce Development, Southeastern NewEngland Defense Industry Alliance (SENEDIA)
• Bryan Lucas, Computer Science/Literacy Teacher, Chariho Middle School, Chariho RegionalSchool District
• JoeMazzone, Secretary, CSTA-RI/Career and Technical Education Instructor, WilliamM.DaviesJr. Career and Technical High School, Lincoln
• Ilona Miko, Ph.D., MikoArtScience Consulting
• Ryan Mullen, Coordinator of Teaching & Learning, Warwick Public Schools
• Elizabeth (Liz) Patterson, Computer Science Teacher, Portsmouth High School, PortsmouthSchool Department
• Janet Prichard, Ph.D., Professor, Information Systems and Analytics, Bryant University
• Cmdr. Joseph E. Santos, Military Professor, U.S. Naval War College, Newport
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Advisory Committee
• Chris Allen, NBCT, Fourth Grade Teacher, Greenbush Elementary School, West Warwick Pub-lic Schools
• Jenny Chan-Remka, Ed.D., Assistant Superintendent, Woonsocket Education Department
• Michelle Conary, Computer Literacy Instructor, Chariho Middle School, Chariho RegionalSchool District
• Jane L. Daly, Assistant Superintendent of Schools, Chariho Regional School District
• Vic Fay-Wolfe, Ph.D., Computer Science, University of Rhode Island
• Kathi Fisler, Ph.D., Research Professor, Computer Science, Brown University/Co-Director,Bootstrap
• Carol M. Giuriceo, Ph.D., Director, Rhode Island STEAM Center @ Rhode Island College
• Lenora E. Goodwin, Consulting Teacher, Teacher Retention and InductionNetwork (T.R.A.I.N.),Providence Public Schools
• Timothy Henry, Ph.D., Professor, IT Graduate Director, New England Institute of Technology
• Dominic Herard, Mathematics & Computer Science Teacher, Times Squared STEM Academy,Providence
• Verda Jones, Business & Technology Instructor, Shea Senior High School, Pawtucket SchoolDistrict
• Ramarao Koppaka, Staff Vice President, Principal Enterprise Architect, FM Global
• Linda Larsen, Director of Education Outreach & Workforce Development, Southeastern NewEngland Defense Industry Alliance (SENEDIA)
• Bryan Lucas, Computer Science/Literacy Teacher, Chariho Middle School, Chariho RegionalSchool District
• JoeMazzone, Secretary, CSTA-RI/Career and Technical Education Instructor, WilliamM.DaviesJr. Career and Technical High School, Lincoln
• Ilona Miko, Ph.D., MikoArtScience Consulting
• Ryan Mullen, Coordinator of Teaching & Learning, Warwick Public Schools
• Elizabeth (Liz) Patterson, Computer Science Teacher, Portsmouth High School, PortsmouthSchool Department
• Janet Prichard, Ph.D., Professor, Information Systems and Analytics, Bryant University
• Cmdr. Joseph E. Santos, Military Professor, U.S. Naval War College, Newport
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ReviewersReview Team
• Amanda Bagley, Second Grade Education Teacher, Greenbush Elementary School, West War-wick Public Schools
• John Bilotta, Executive Director, Rhode Island Society of Technology Educators (RISTE)
• Joe Devine, Partner & CTO, Bridge Technical Talent, LLC
• Howard L. Dooley, Jr., Project Manager, Rhode Island Technology Enhanced Sciences and Com-puting (RITES +C), University of Rhode Island
• Donald Gregory, Education Specialist, Providence Public Library
• Linda A. Jzyk, Grant Specialist, Rhode Island College Foundation, Former Science and Tech-nology Specialist, Rhode Island Department of Education (RIDE)
• Tom Kowalczyk, Founder, KMRM,LLC
• Theresa Moore, President, T-Time Productions
• Diane Sanna, Assistant Superintendent, Bristol Warren Regional School District
• John Smithers, CEO, Tech Collective
• Holly Walsh, Digital Learning Specialist, Office of College and Career Readiness, Rhode IslandDepartment of Education (RIDE)
SpecialistsCybersecurity
• Jason Albuquerque, C/CISO,CGCIO, Chief Information Security Officer, Carousel Industries
• Brig Gen Kimberly A. Baumann, Ph.D., Assistant Adjutant General, Rhode Island NationalGuard
• Simon A. Cousins, Principal Client Specialist, FM Global
• Richard Siedzik, Director of Information Security and Planning/ISO, Bryant University
Digital Literacy
• Renee Hobbs, Ph.D., Professor, Department of Communication Studies; Co-Director, GraduateCertificate in Digital Literacy, Harrington School of Communication and Media, University ofRhode Island
• Mary H.Moen, Ph.D., Assistant Professor, Graduate School of Library and Information Studies,University of Rhode Island
• Zoey Wang, Graduate Assistant, Rhode Island STEAM Center @ Rhode Island College
Public Review: Their FeedbackAn open invitation was extended to teachers, principals, district administrators, superintendents,industry professionals, and other stakeholders to submit comments on the draft standards. Therefeedback provided valuable input that greatly enhanced the content of the standards.
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ReviewersReview Team
• Amanda Bagley, Second Grade Education Teacher, Greenbush Elementary School, West War-wick Public Schools
• John Bilotta, Executive Director, Rhode Island Society of Technology Educators (RISTE)
• Joe Devine, Partner & CTO, Bridge Technical Talent, LLC
• Howard L. Dooley, Jr., Project Manager, Rhode Island Technology Enhanced Sciences and Com-puting (RITES +C), University of Rhode Island
• Donald Gregory, Education Specialist, Providence Public Library
• Linda A. Jzyk, Grant Specialist, Rhode Island College Foundation, Former Science and Tech-nology Specialist, Rhode Island Department of Education (RIDE)
• Tom Kowalczyk, Founder, KMRM,LLC
• Theresa Moore, President, T-Time Productions
• Diane Sanna, Assistant Superintendent, Bristol Warren Regional School District
• John Smithers, CEO, Tech Collective
• Holly Walsh, Digital Learning Specialist, Office of College and Career Readiness, Rhode IslandDepartment of Education (RIDE)
SpecialistsCybersecurity
• Jason Albuquerque, C/CISO,CGCIO, Chief Information Security Officer, Carousel Industries
• Brig Gen Kimberly A. Baumann, Ph.D., Assistant Adjutant General, Rhode Island NationalGuard
• Simon A. Cousins, Principal Client Specialist, FM Global
• Richard Siedzik, Director of Information Security and Planning/ISO, Bryant University
Digital Literacy
• Renee Hobbs, Ph.D., Professor, Department of Communication Studies; Co-Director, GraduateCertificate in Digital Literacy, Harrington School of Communication and Media, University ofRhode Island
• Mary H.Moen, Ph.D., Assistant Professor, Graduate School of Library and Information Studies,University of Rhode Island
• Zoey (Xuezhao) Wang, Graduate Assistant, Rhode Island STEAM Center @ Rhode Island College
Public Review: Their FeedbackAn open invitation was extended to teachers, principals, district administrators, superintendents,industry professionals, and other stakeholders to submit comments on the draft standards. Therefeedback provided valuable input that greatly enhanced the content of the standards.
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Computer Science & Relevance to Rhode Island
In January 2016, the Metropolitan Policy Program at Brookings, along with Battelle TechnologyPartnership Practice (now TEConomy Partners, LLC) and with support from Monitor Deloitte, De-loitte Consulting LLP released Rhode Island Innovates: A Competitive Strategy for the Ocean State,a detailed economic assessment with recommendations for Rhode Island’s economic development.Brookings and its partners engaged in a six-month inquiry with private- and public-sector stake-holders across the state to assess Rhode Island’s present situation and competitive position, and toprovide an action plan for strategy development.
The report identified CS science as a core competency in Rhode Island with areas of focus in datasciences, robotics, cybersecurity, and algorithms. According to Brookings, a core competency “rep-resent[s] zones of endeavor where a place has the ability to grow. Core competencies indicate wherethere is a critical mass of expertise and creative activity across product development and processimprovements that has the potential to generate new intellectual property and startups . . . corecompetencies highlight where a state’s firms and research institutions have the capacity not only toadvance new research discoveries but also to apply them, mobilize talent, and create good jobs.” Thereport indicated that over 3,800 jobs posted online in 2013 in Rhode Island required knowledge ofat least one programming language.
Unfortunately, the Brookings inquiry also found that student engagement with CS was low, withmany of the state’s schools only offering a basic computer literacy class as a graduation requirement,rather than a more rigorous and comprehensive CS course. During the 2014-2015 academic year,only 72 Rhode Island students took the AP CS exam. Acknowledging the need for sustainable so-lutions, recommendations included incorporating CS into the PK-12 curriculum through changingtechnology graduation requirements and public/private partnerships that work to implement CScourses and professional development.
To meet this need, the Computer Science for Rhode Island initiative, or CS4RI was created to bringCS learning opportunities to all Rhode Island schools. National and local programs from Microsoft,Project Lead the Way, and Code.org, to the University of Rhode Island and Brown University, arecurrently serving as content providers, offering professional development and established curriculato schools across the state. The CS4RI initiative brings computer education to the forefront of thediscussion, as well as needed resources to jumpstart CS incorporation in K-12 education.
Conversations with educators during the first months of CS4RI implementation indicated that ed-ucators would welcome guidelines that assist in the development of computer science pathways.Identifying achievement outcomes for students in different grades would allow educators to feelconfident that they were teaching what students need to know. In January 2017, the Rhode IslandSTEAM Center @ Rhode Island College received funding from the van Beuren Charitable Founda-tion to develop Computer Science Education Standards for Rhode Island.
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Computer Science & Relevance to Rhode Island
In January 2016, the Metropolitan Policy Program at Brookings, along with Battelle TechnologyPartnership Practice (now TEConomy Partners, LLC) and with support from Monitor Deloitte, De-loitte Consulting LLP released Rhode Island Innovates: A Competitive Strategy for the Ocean State,a detailed economic assessment with recommendations for Rhode Island’s economic development.Brookings and its partners engaged in a six-month inquiry with private- and public-sector stake-holders across the state to assess Rhode Island’s present situation and competitive position, and toprovide an action plan for strategy development.
The report identified CS science as a core competency in Rhode Island with areas of focus in datasciences, robotics, cybersecurity, and algorithms. According to Brookings, a core competency “rep-resent[s] zones of endeavor where a place has the ability to grow. Core competencies indicate wherethere is a critical mass of expertise and creative activity across product development and processimprovements that has the potential to generate new intellectual property and startups . . . corecompetencies highlight where a state’s firms and research institutions have the capacity not only toadvance new research discoveries but also to apply them, mobilize talent, and create good jobs.” Thereport indicated that over 3,800 jobs posted online in 2013 in Rhode Island required knowledge ofat least one programming language.
Unfortunately, the Brookings inquiry also found that student engagement with CS was low, withmany of the state’s schools only offering a basic computer literacy class as a graduation requirement,rather than a more rigorous and comprehensive CS course. During the 2014-2015 academic year,only 72 Rhode Island students took the AP CS exam. Acknowledging the need for sustainable so-lutions, recommendations included incorporating CS into the PK-12 curriculum through changingtechnology graduation requirements and public/private partnerships that work to implement CScourses and professional development.
To meet this need, the Computer Science for Rhode Island initiative, or CS4RI was created to bringCS learning opportunities to all Rhode Island schools. National and local programs from Microsoft,Project Lead the Way, and Code.org, to the University of Rhode Island and Brown University, arecurrently serving as content providers, offering professional development and established curriculato schools across the state. The CS4RI initiative brings computer education to the forefront of thediscussion, as well as needed resources to jumpstart CS incorporation in K-12 education.
Conversations with educators during the first months of CS4RI implementation indicated that ed-ucators would welcome guidelines that assist in the development of computer science pathways.Identifying achievement outcomes for students in different grades would allow educators to feelconfident that they were teaching what students need to know. In January 2017, the Rhode IslandSTEAM Center @ Rhode Island College received funding from the van Beuren Charitable Founda-tion to develop Computer Science Education Standards for Rhode Island.
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Alignment with National Efforts
The Computer Science (CS) Education Standards process began at a critical time in K-12 computerscience education.
• In October 2016, the K-12 Computer Science (CS) Framework was released. The Framework,a national effort led by the Association for Computing Machinery (ACM), Code.org, ComputerScience Teachers Association (CSTA), Cyber Innovation Center (CIC), and the National Math +Science Initiative (Steering Committee) defined conceptual guidelines for states and districtsto create a K-12 pathway in CS. Participants in the development of the Framework includedwriters, advisors, and researchers who represented associations (such as the International So-ciety for Technology Education [ISTE]), industry (such as Microsoft, Google, Apple), states,school districts, higher education, and K-12.
• In July 2017, the Computer Science Teachers Association released their revised K-12 Com-puter Science Standards, which aligned with the K-12 CS Framework. These standards de-scribe learning objectives designed to provide the foundation for a complete computer sciencecurriculum at the K-12 level.
• Both the Framework and the CSTA Standards are based on current professional research andpractice in computer science education.
Organizations and Key Documents Referenced
K-12 Computer Science Framework
Our standards reflect the recommendations of the K-12 Computer Science Framework, led by theAssociation for Computing Machinery, Code.org, Computer Science Teachers Association, Cyber In-novation Center, and National Math and Science Initiative, in partnership with states and districts.The K-12 Compute Science Framework is endorsed by leading industry and educational organiza-tions, as well as K-12, higher education, and research leaders in the field of computer science educa-tion. To find more information, including a full list of supporters, visit k12cs.org.
2017 CSTA K-12 Computer Science Standards
The Advisory Committee used the 2017 CSTA K-12 Computer Science Standards as a foundationfor our standards but modifications were made to reflect the education environment in Rhode Is-land. The CSTA Standards are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. To find more information, visithttps://www.csteachers.org/page/standards.
2016 Massachusetts Digital Literacy and Computer Science (DLCS) Curriculum Framework
The Advisory Committee reviewed the 2016 Massachusetts Digital Literacy and Computer Science(DLCS) Curriculum Framework developed by the Massachusetts Department of Elementary andSecondary Education with a focus on the Digital Tools and Collaboration strand. To find moreinformation, visit http://www.doe.mass.edu/frameworks/dlcs.pdf.
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Alignment with National Efforts
The Computer Science (CS) Education Standards process began at a critical time in K-12 computerscience education.
• In October 2016, the K-12 Computer Science (CS) Framework was released. The Framework,a national effort led by the Association for Computing Machinery (ACM), Code.org, ComputerScience Teachers Association (CSTA), Cyber Innovation Center (CIC), and the National Math +Science Initiative (Steering Committee) defined conceptual guidelines for states and districtsto create a K-12 pathway in CS. Participants in the development of the Framework includedwriters, advisors, and researchers who represented associations (such as the International So-ciety for Technology Education [ISTE]), industry (such as Microsoft, Google, Apple), states,school districts, higher education, and K-12.
• In July 2017, the Computer Science Teachers Association released their revised K-12 Com-puter Science Standards, which aligned with the K-12 CS Framework. These standards de-scribe learning objectives designed to provide the foundation for a complete computer sciencecurriculum at the K-12 level.
• Both the Framework and the CSTA Standards are based on current professional research andpractice in computer science education.
Organizations and Key Documents Referenced
K-12 Computer Science Framework
Our standards reflect the recommendations of the K-12 Computer Science Framework, led by theAssociation for Computing Machinery, Code.org, Computer Science Teachers Association, Cyber In-novation Center, and National Math and Science Initiative, in partnership with states and districts.The K-12 Compute Science Framework is endorsed by leading industry and educational organiza-tions, as well as K-12, higher education, and research leaders in the field of computer science educa-tion. To find more information, including a full list of supporters, visit k12cs.org.
2017 CSTA K-12 Computer Science Standards
The Advisory Committee used the 2017 CSTA K-12 Computer Science Standards as a foundationfor our standards but modifications were made to reflect the education environment in Rhode Is-land. The CSTA Standards are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. To find more information, visithttps://www.csteachers.org/page/standards.
2016 Massachusetts Digital Literacy and Computer Science (DLCS) Curriculum Framework
The Advisory Committee reviewed the 2016 Massachusetts Digital Literacy and Computer Science(DLCS) Curriculum Framework developed by the Massachusetts Department of Elementary andSecondary Education with a focus on the Digital Tools and Collaboration strand. To find moreinformation, visit http://www.doe.mass.edu/frameworks/dlcs.pdf.
6
Alignment with National Efforts
The Computer Science (CS) Education Standards process began at a critical time in K-12 computerscience education.
• In October 2016, the K-12 Computer Science (CS) Framework was released. The Framework,a national effort led by the Association for Computing Machinery (ACM), Code.org, ComputerScience Teachers Association (CSTA), Cyber Innovation Center (CIC), and the National Math +Science Initiative (Steering Committee) defined conceptual guidelines for states and districtsto create a K-12 pathway in CS. Participants in the development of the Framework includedwriters, advisors, and researchers who represented associations (such as the International So-ciety for Technology Education [ISTE]), industry (such as Microsoft, Google, Apple), states,school districts, higher education, and K-12.
• In July 2017, the Computer Science Teachers Association released their revised K-12 Com-puter Science Standards, which aligned with the K-12 CS Framework. These standards de-scribe learning objectives designed to provide the foundation for a complete computer sciencecurriculum at the K-12 level.
• Both the Framework and the CSTA Standards are based on current professional research andpractice in computer science education.
Organizations and Key Documents Referenced
K-12 Computer Science Framework
Our standards reflect the recommendations of the K-12 Computer Science Framework, led by theAssociation for Computing Machinery, Code.org, Computer Science Teachers Association, Cyber In-novation Center, and National Math and Science Initiative, in partnership with states and districts.The K-12 Compute Science Framework is endorsed by leading industry and educational organiza-tions, as well as K-12, higher education, and research leaders in the field of computer science educa-tion. To find more information, including a full list of supporters, visit k12cs.org.
2017 CSTA K-12 Computer Science Standards
The Advisory Committee used the 2017 CSTA K-12 Computer Science Standards as a foundationfor our standards but modifications were made to reflect the education environment in Rhode Is-land. The CSTA Standards are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. To find more information, visithttps://www.csteachers.org/page/standards.
2016 Massachusetts Digital Literacy and Computer Science (DLCS) Curriculum Framework
The Advisory Committee reviewed the 2016 Massachusetts Digital Literacy and Computer Science(DLCS) Curriculum Framework developed by the Massachusetts Department of Elementary andSecondary Education with a focus on the Digital Tools and Collaboration strand. To find moreinformation, visit http://www.doe.mass.edu/frameworks/dlcs.pdf.
6
Alignment with National Efforts
The Computer Science (CS) Education Standards process began at a critical time in K-12 computerscience education.
• In October 2016, the K-12 Computer Science (CS) Framework was released. The Framework,a national effort led by the Association for Computing Machinery (ACM), Code.org, ComputerScience Teachers Association (CSTA), Cyber Innovation Center (CIC), and the National Math +Science Initiative (Steering Committee) defined conceptual guidelines for states and districtsto create a K-12 pathway in CS. Participants in the development of the Framework includedwriters, advisors, and researchers who represented associations (such as the International So-ciety for Technology Education [ISTE]), industry (such as Microsoft, Google, Apple), states,school districts, higher education, and K-12.
• In July 2017, the Computer Science Teachers Association released their revised K-12 Com-puter Science Standards, which aligned with the K-12 CS Framework. These standards de-scribe learning objectives designed to provide the foundation for a complete computer sciencecurriculum at the K-12 level.
• Both the Framework and the CSTA Standards are based on current professional research andpractice in computer science education.
Organizations and Key Documents Referenced
K-12 Computer Science Framework
Our standards reflect the recommendations of the K-12 Computer Science Framework, led by theAssociation for Computing Machinery, Code.org, Computer Science Teachers Association, Cyber In-novation Center, and National Math and Science Initiative, in partnership with states and districts.The K-12 Compute Science Framework is endorsed by leading industry and educational organiza-tions, as well as K-12, higher education, and research leaders in the field of computer science educa-tion. To find more information, including a full list of supporters, visit k12cs.org.
2017 CSTA K-12 Computer Science Standards
The Advisory Committee used the 2017 CSTA K-12 Computer Science Standards as a foundationfor our standards but modifications were made to reflect the education environment in Rhode Is-land. The CSTA Standards are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. To find more information, visithttps://www.csteachers.org/page/standards.
2016 Massachusetts Digital Literacy and Computer Science (DLCS) Curriculum Framework
The Advisory Committee reviewed the 2016 Massachusetts Digital Literacy and Computer Science(DLCS) Curriculum Framework developed by the Massachusetts Department of Elementary andSecondary Education with a focus on the Digital Tools and Collaboration strand. To find moreinformation, visit http://www.doe.mass.edu/frameworks/dlcs.pdf.
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Process & Timeline
The Computer Science (CS) Education Standards Committeemetmonthly for day-long sessions fromMarch 2017 to December 2017. Smaller committees convened more frequently during January andFebruary 2018 for targeted discussions. Our process included reviewing the K-12 CS Frameworkand existing CS standards in other states. The Committee identified working Core Concepts andSub-Concepts after the initial review. Smaller working groups with members representing differentsectors formed to focus on specific concepts. Review of the CSTA CS K-12 Standards began. As workprogressed, the Committee decided to combine two of the existing Concepts into one and add twonew Concepts. The Committee followed a similar process with the Sub-Concepts.
Other stakeholders also helped to inform the standards. Although the Committee used existingstandards in cybersecurity and digital literacy as starting points, we reached out to cybersecurityexperts who offered suggestions and recommendations so the standards were comprehensive butnot overly technical. Additionally, the Committee was aware of the overlap among digital literacy,media literacy, and instructional literacy, and met with specialists to discuss how to include digitalliteracy in the CS standards without duplication.
The Review Team, composed of Rhode Islanders from across the state, served as the reviewers forthe draft standards. They evaluated the draft standards using a checklist developed by the K-12 CSFramework developers. Criteria included focus/manageability, equity, coherence/progression, clar-ity/accessibility, and measurability, among others.
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Our Guiding Principles
The following Guiding Principles helped establish our aspirational visionand informed the development of K-12 Computer Science education
standards for Rhode Island.
Broaden Participation &Equity
All students regardless of age, race, ethnicity, gender, socioeconomicstatus, special needs, English proficiency, or any other demographicwill have the opportunity to participate in computer science.Thecontent and practices of the standards will be accessible to all.
Stimulate Learning &Curiosity
The standards at all grade levels will connect to appropriate real worldchallenges as a means to motivate and empower, promote individualgrowth, and spark a desire for life-long learning.
Build Connections AcrossDisciplines
Computer science will complement other disciplines and build upon and developstudent knowledge.,The standards will connect with practices andconcepts from the Common Core State Standards (CCSS) and the NextGeneration Science Standards (NGSS) to promote learning acrossdisciplines.
EncourageWorkforce/Economic
Development
Students will have the skills, practices, and knowledge to participate in aworld that is increasingly influenced and shaped by technologicaladvancements.,The standards will help to prepare students who canadapt and prosper under constantly changing conditions.
Support TeachersThe standards will identify focused learning progressions and multi-tierteaching approaches that meet the needs of all learners.
Inform with CurrentResearch
The standards will be based on current professional research and practicein computer science education and pedagogy.
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Equity in Computer Science Education
The Rhode Island Computer Science Education Standards Advisory Committee believes that equityand broadening participation must be at the forefront of the computer science initiative to ensurethat all Rhode lsland students benefit. We strongly agree with the position identified in the K-12Computer Science Framework (2016) which states:
When equity exists, there are appropriate supports based on individ-ual students’ needs so that all have the opportunity to achieve similarlevels of success. Inherent in this goal is a comprehensive expectationof academic success that is accessible by and applies to every student.. . . equity, inclusion, and diversity are critical factors in all aspects ofcomputer science.(pp.23, 26)1
We constantly returned to this issue throughout the development of the standards. We worked toensure equity is embedded in the standards themselves, the descriptions, and the accompanyingsuggested activities. Additionally, standards can be met without computing devices or with alimited amount of available hardware so implementation is possible for all schools.
1. K-12 Computer Science Framework. (2016). Retrieved from http://www.k12cs.org
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Equity in Computer Science Education
The Rhode Island Computer Science Education Standards Advisory Committee believes that equityand broadening participation must be at the forefront of the computer science initiative to ensurethat all Rhode lsland students benefit. We strongly agree with the position identified in the K-12Computer Science Framework (2016) which states:
When equity exists, there are appropriate supports based on individ-ual students’ needs so that all have the opportunity to achieve similarlevels of success. Inherent in this goal is a comprehensive expectationof academic success that is accessible by and applies to every student.. . . equity, inclusion, and diversity are critical factors in all aspects ofcomputer science.(pp.23, 26)1
We constantly returned to this issue throughout the development of the standards. We worked toensure equity is embedded in the standards themselves, the descriptions, and the accompanyingsuggested activities. Additionally, standards can be met without computing devices or with alimited amount of available hardware so implementation is possible for all schools.
1. K-12 Computer Science Framework. (2016). Retrieved from http://www.k12cs.org
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Computational Thinking
Computational thinking involves solving problems, designing systems, andunderstanding human behavior, by drawing on the concepts fundamental tocomputer science. . . . This kind of thinking will be part of the skill set of, notonly other scientists, but of everyone else. Ubiquitous computing is to todayas computational thinking is to tomorrow. Ubiquitous computing wasyesterday’s dream that become today’s reality; computational thinking istomorrow’s reality.
– Jeannette Wing, March 2006Communications of the ACM, 49(3), 33-35.
Computational thinking is central to the standards and a necessary skill for participation in today’ssociety. It can be applied broadly to solving complex problems in other disciplines and can betaught across the K-12 curriculum.1
1. Computational Thinking for a Computational World. (2017). Retrieved fromhttp://digitalpromise.org/wp-content/uploads/2017/12/dp-comp-thinking-v1r5.pdf
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Computational Thinking
Computational thinking involves solving problems, designing systems, andunderstanding human behavior, by drawing on the concepts fundamental tocomputer science. . . . This kind of thinking will be part of the skill set of, notonly other scientists, but of everyone else. Ubiquitous computing is to todayas computational thinking is to tomorrow. Ubiquitous computing wasyesterday’s dream that become today’s reality; computational thinking istomorrow’s reality.
– Jeannette Wing, March 2006Communications of the ACM, 49(3), 33-35.
Computational thinking is central to the standards and a necessary skill for participation in today’ssociety. It can be applied broadly to solving complex problems in other disciplines and can betaught across the K-12 curriculum.1
1. Computational Thinking for a Computational World. (2017). Retrieved fromhttp://digitalpromise.org/wp-content/uploads/2017/12/dp-comp-thinking-v1r5.pdf
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Standards
Standards represent pathways that are realistic expectations for all students. They identify theknowledge, practices, and skills in computer science that all students should know and be able todo at each level in their education. They serve as specific performance measures and are used asreference points for planning and teaching, including but not limited to, the development ofcurriculum frameworks, curricula, lesson plans, instruction, professional development, andassessment.
The standards are written to be aspirational – they represent the concepts and practices that allstudents need to master. They are designed to inform, encourage, and drive a sustainable computerscience education program, and were developed to be cognitively appropriate for each grade band.Careful attention was paid to word choice in the standards to ensure measurability.
Grade Bands
The decision to adopt and use the grade bands identified in the CSTA K-12 Standards document –K-2, 3-5, 6-8, 9-12 – allows for increased flexibility for implementation in schools. Although theCSTA separated grades 9-12 into two levels – 9-10, 11-12 – with the 11-12 level designed forstudents enrolled in more rigorous courses, we decided that it was appropriate to extend the 9-10level to 9-12 at this time since our goal focused on standards for ALL students.
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Implementation of Standards
The Computer Science (CS) Education Standards are designed for all students K-12 in Rhode Islandregardless of career aspirations. They represent the knowledge and skills that all students need toeffectively participate and be productive in today’s society.
At this time, adoption of the CS Education Standards by school districts is not mandatory.However, the response to the CS4RI initiative in connecting content providers with local schools toreduce barriers and provide quality CS education and professional development has beenoverwhelmingly positive at all grade levels.
CS4RI will support implementation of the CS Education Standards in school districts through afour-pronged approach:
1. All curricula and professional development offered by CS content providers in the CS4RImatrix will be aligned with the new Rhode Island standards. The new Memorandums ofUnderstanding include this requirement.
2. The SCRIPT – School CSforALL Resource & Implementation Planning Tool – will be offered inSummer 2018 to all school districts to serve as a framework and platform to guide districtstaff in the creation of implementation plans based on the needs and goals of individualdistricts.
3. CS4RI will be working closely with the Computer Science Teachers Association – RhodeIsland to provide resources and support through communities of practice.
4. CS4RI will be developing additional resources and supplementary materials to support CSEducation Standards adoption in K-12 education.
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Core Concepts and Sub-Concepts
The Core Concepts represent specific areas of disciplinary importance in computer science. TheSub-Concepts represent specific ideas within each concept.
Computational Thinking & Programming
• Algorithms• Variables• Data Structures & Data Types• Control Structures• Modularity• Computational Design
Computing Systems & Networks
• Human-Computer Interaction• Hardware & Software• Troubleshooting• Networks & the Internet
Cybersecurity• Risks• Safeguards• Response
Data & Analysis• Collection, Visualization, & Transformation• Inference & Models• Storage
Digital Literacy• Creation & Use• Searching Digital Information• Understanding Software Tools
Responsible Computing in Society• Culture• Safety, Law, & Ethics• Social Interactions
Each Core Concept and Sub-Concept is described in more detail on the following pages. Thedescriptions were adopted from the K-12 CS Framework. Certain changes and additions were madewhen necessary.
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Computational Thinking & Programming
Overview: Computational thinking involves problem solving that requires the logical analysis ofdata. It serves as a fundamental skill for all students, and can be applied to complex problemsacross disciplines. These skills empower people to communicate with the world in new ways andsolve compelling problems. Creating meaningful and efficient programs involves choosing whichinformation to use and how to process and store it, breaking apart large problems into smallerones, recombining existing solutions, and analyzing different solutions.
Algorithms
An algorithm is a sequence of steps designed to accomplish a specifictask. Algorithms are translated into programs, or code, to provideinstructions for computing devices, and are designed to be carriedout by both humans and computers. In early grades, students learnabout age-appropriate algorithms from the real world. As theyprogress, students learn about the development, combination, anddecomposition of algorithms, as well as the evaluation of competingalgorithms.
Variables
Computer programs store and manipulate data using variables. In early grades,students learn that different types of data, such as words, numbers,or pictures, can be used in different ways. As they progress,students learn about variables, and ways to organize largecollections of data into data structures of increasing complexity.
Data Structure &Data Types
Data structures store and organize data within a computer program. Datatypes classify data by attributes. In early grades, students learnto model and identify real-world examples of data. As they progress,they organize and create programs to process those data.
ControlStructures
Control structures specify the order in which instructions are executedwithin an algorithm or program. In early grades, students learnabout sequential execution and simple control structures. As theyprogress, students expand their understanding to combinations ofstructures that support complex execution.
Modularity
Modularity involves breaking down tasks into simpler tasks, and combining simpletasks to create something more complex. In early grades, studentslearn that algorithms and programs can be designed by breaking tasksinto smaller parts and recombining existing solutions. As theyprogress, students learn about recognizing patterns to make use ofgeneral, reusable solutions for commonly occurring scenarios, andclearly describing tasks in ways that are widely usable.
Computational Design
Programs are developed through a design process that is often repeated untilthe programmer is satisfied with the solution. In early grades,students learn how and why people develop programs. As theyprogress, students learn about the tradeoffs in program designassociated with complex decision, which involve user constraints,efficiency, ethics and testing.
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Computing Systems & Networks
Overview: People interact with a wide variety of computing devices that collect, store, analyze, andact upon information in ways that can affect human capabilities, both positively and negatively.The physical components (hardware) and instructions (software) that make up a computing systemcommunicate and process information in digital form. An understanding of hardware and softwareis useful when troubleshooting a computing system that does not work as intended.
Additionally, computing devices typically do not operate in isolation. Networks connect computingdevices to share information and resources and are an increasingly integral part of computing.Networks and communication systems provide greater connectivity in the computing world byproviding fast, secure communication, and facilitating innovation.
Human-ComputerInteraction
Many everyday objects contain computational components that both sense andact on the world. In early grades, students learn features andapplications of common computing devices. As they progress, studentslearn about connected systems and how the interaction between humansand devices influences design decisions.
Hardware& Software
Computing systems use hardware and software to communicate and processinformation in digital form. In early grades, students learn howsystems use both hardware and software to represent and processinformation. As they progress, students gain a deeper understandingof the interaction between hardware and software at multiple levelswithin computing systems.
Troubleshooting
When computing systems do not work as intended, troubleshooting strategieshelp people solve the problem. In early grades, students learn thatidentifying the problem is the first step to fixing it. As theyprogress, students learn systematic problem-solving processes and howto develop their own troubleshooting strategies, based on a deeperunderstanding of how computing systems work.
Networks& the Internet
Computing devices communicate with each other across networks to shareinformation. In early grades, students learn that computers connectthem to other people, places, and systems around the world. As theyprogress, students gain a deeper understanding of how information issent and received across different types of networks.
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Cybersecurity
Overview: Cybersecurity includes practices, processes, technologies, and other protective measuresthat are designed to protect against unwanted, unauthorized, or illegal access to or use of data,through onsite or remote devices, programs, and/or networks. As more information becomesdigitized, both proactive and adaptive approaches to securing data become essential to meet thefrequent and continually-evolving cybersecurity risks.
Risks
Being online or connected to a network has become part of a daily routine in personal,school and work environments. Students have ubiquitous access to information butare also exposed to common threats, scams, and fraud. In the early grades, studentslearn to identify and detect activity that may be monitoring and compromising theirinformation. As they progress, students learn about social engineering, privacyconcerns, and personal responsibility.
Safeguards
Transmitting information securely across networks requires appropriate protection thatwill mitigate or contain the impact, or even prevent the cybersecurity event.Safeguards include limiting access, using targeted processes and procedures,maintaining security software, and continuous monitoring of activity. In early grades,students learn how to protect their personal information. As they progress, studentslearn increasingly complex ways and tools used to protect information sent acrossnetworks and the trade-offs when selecting and implementing cybersecurity strategies.
Response
Implementing appropriate measures in response to a cybersecurity event requiresan awareness of and a suitable reaction to the threat. Responses include pre-eventplanning, adoption and maintenance, threat containment, structure reporting andcommunications protocols, root cause analysis, and continuous process improvement.In the early grades, students learn when to report suspicious activity. As they progress,students learn how to take appropriate action on both personal and organizational levels.
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Data & Analysis
Overview: Computing systems exist to process data. The amount of digital data generated in theworld is rapidly expanding, so the need to process data effectively is increasingly important. Dataare collected, analyzed and stored to better understand our social structures, geography, health andenvironment, and to make more accurate predictions about them.
Collection, Visualization, &Transformation
Data are collected with both computational and non-computational toolsand processes. In early grades, students learn how data about themselvesand their environment are collected and used. As they progress, studentslearn the effects of collecting data with computational and automatedtools. Data are transformed throughout the process of collection, digitalrepresentation, and analysis. In early grades, students learn howtransformations can be used to simplify data. As they progress, studentslearn about more complex operations to discover patterns and trends,and communicate those to others.
Inference & Models
Data science is one example where computer science serves many fields.Computer science and other sciences use data to make inferences, theories,or predictions based upon data collected from users or simulations. In earlygrades, students learn about the use of data to make simple predictions.As they progress, students learn how models and simulations can be usedto examine theories and understand systems, and how predictions andinferences are affected by more complex and larger data sets.
Storage
Core functions of computers are storing, representing, and retrieving data.In early grades, students learn how data are stored on computers. As theyprogress, students learn how to evaluate different storage methods,including the tradeoffs associated with those methods.
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Digital Literacy
Overview: Digital literacy refers to the ability to leverage software technology to create, share, andmodify artifacts, as well as search over digital information. This literacy includes understandingthe benefits and implications of software tool use while accessing digital information andcollaborating on digital artifacts. Digital literacy is a multifaceted concept that extends beyondskills-based activities and incorporates both cognitive and technical skills.
Creation & Use
Software tools are used to create and edit artifacts as well as locateand retrieve information. In early grades, students learn how toperform common operations using local, networked, or online tools.As they progress, students learn how to collaborate using softwaretools, and make informed decisions according to purpose and need.
Searching Digital Information
Locating, retrieving, and organizing relevant information includesbeing able to search for information in different ways. In earlygrades, students conduct basic and multi-criteria searches to findinformation in digital resources. As they progress, students learn toexpand to multiple formats and databases, and synthesize searchresults to answer a complex question or solve a problem.
Understanding Software Tools
Humans interact with software tools to perform tasks. In early grades,students begin by understanding what software can do and how toexplain this to others. As they progress, they learn about howsoftware tools perform computations to incorporate multiplefunctions, and how software can be customized depending on who isusing it.
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Responsible Computing in Society
Overview: Computing affects many aspects of our world in both positive and negative ways, and atlocal and global scales. Individuals and communities influence computing through both theirbehaviors and cultural and social interactions, and in turn, computing influences new culturalpractices. An informed and responsible person should understand the social implications ofcomputing technology, including its impact on equity and access to computing.
Culture
Computing influences culture—including belief systems, language,relationships, technology, and institutions—and culture shapes howpeople engage with and access computing. In early grades, studentslearn how computing can be helpful and harmful. As they progress,students learn about tradeoffs associated with computing and potentialfuture impacts of computing on global societies.
Safety, Law, & Ethics
Legal and ethical considerations of using computing devices influencebehaviors that can affect the safety and security of individuals. In earlygrades, students learn the fundamentals of digital citizenship andappropriate use of digital media. As they progress, students learn aboutthe legal and ethical issues that shape computing practices.
Social Interactions
Computing can support new ways of connecting people, communicatinginformation, and expressing ideas. In early grades, students learn thatcomputing can connect people and support interpersonal communication.As they progress, students learn how the social nature of computingaffects institutions and careers in various sectors.
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Practices
We adopted the practices that the K-12 CS Framework developed, and that are used in the CSTAK-12 Standards. These practices describe the behavior and ways of thinking thatcomputationally-literate students use to engage in Core Concepts.
The Advisory Committee added an eighth practice – Using Technology Appropriately – whichdescribes the necessary behavior and ways of thinking that support the Cybersecurity and DigitalLiteracy Core Concepts.
Practice 1Fostering an InclusiveComputing Culture
Overview: Building an inclusive and diverse computing culture requiresstrategies for incorporating perspectives from people of different genders,ethnicities, and abilities. Incorporating these perspectives involvesunderstanding the personal, ethical, social, economic, and cultural contextsin which people operate. Considering the needs of diverse users duringthe design process is essential to producing inclusive computational products.
1.1 Include the unique perspectives of others and reflect on one’s ownperspectives when designing and developing computational products.
1.2 Address,the needs of diverse users during the design process to produceartifacts with broad accessibility and usability.
1.3 Employ self- and peer-advocacy to address bias in interactions, productdesign, and development methods.
Practice 2Collaborating Around
Computing
Overview: Collaborative computing is the process of performing acomputational task by working in pairs and on teams. Because it involvesasking for the contributions and feedback of others, effective collaborationcan lead to better outcomes than working independently. Collaborationrequires individuals to navigate and incorporate diverse perspectives,conflicting ideas, disparate skills, and distinct personalities. Students shoulduse collaborative tools to effectively work together and to create complexartifacts.
2.1 Cultivate working relationships with individuals possessing diverseperspectives, skills, and personalities.
2.2 Create team norms, expectations, and equitable workloads to increaseefficiency and effectiveness.
2.3 Solicit and incorporate feedback from, and provide constructive feedbackto team members and other stakeholders.
2.4 Evaluate and select technological tools that can be used to collaborate ona project.
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Practice 3Recognizing & DefiningComputational Problems
Overview: The ability to recognize appropriate and worthwhileopportunities to apply computation is a skill that develops overtime and is central to computing. Solving a problem with acomputational approach requires defining the problem, breaking itdown into parts, and evaluating each part to determine whether acomputational solution is appropriate.
3.1 Identify complex, interdisciplinary, real-world problems that canbe solved computationally.
3.2 Decompose complex real-world problems into manageablesub-problems that could integrate existing solutions or procedures.
3.3 Evaluate whether it is appropriate and feasible to solve a problemcomputationally.
Practice 4Developing & Using
Abstractions
Overview: Abstractions are formed by identifying patterns andextracting common features from specific examples to creategeneralizations. Using generalized solutions and parts of solutionsdesigned for broad reuse simplifies the development process bymanaging complexity.
4.1 Extract common features from a set of interrelated processesor complex phenomena.
4.2 Evaluate existing technological functionalities and incorporatethem into new designs.
4.3 Create modules and develop points of interaction that canapply to multiple situations and reduce complexity.
4.4 Model phenomena and processes and simulate systemsto understand and evaluate potential outcomes.
Practice 5Creating Computational
Artifacts
Overview: The process of developing computational artifactsembraces both creative expression and the exploration of ideas tocreate prototypes and solve computational problems. Studentscreate artifacts that are personally relevant or beneficial to theircommunity and beyond. Computational artifacts can be created bycombining and modifying existing artifacts or by developing newartifacts. Examples of computational artifacts include programs,simulations, visualizations, digital animations, robotic systems, andapps.
5.1 Plan the development of a computational artifact using an iterativeprocess that includes reflection on and modification of the plan, takinginto account key features, time and resource constraints, and userexpectations.
5.2 Create a computational artifact for practical intent, personalexpression, or to address a societal issue.
5.3 Modify an existing artifact to improve or customize it.
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Practice 6Testing & Refining
Computational Artifacts
Overview: Testing and refinement is the deliberate and iterative processof improving a computational artifact. This process includes debugging(identifying and fixing errors) and comparing actual outcomes tointended outcomes. Students also respond to the changing needs andexpectations of end users and improve the performance, reliability,usability, and accessibility of artifacts.
6.1 Systematically test computational artifacts by considering allscenarios and using test cases.
6.2 Identify and fix errors using a systematic process.
6.3 Evaluate and refine a computational artifact multiple times toenhance its performance, reliability, usability, and accessibility.
Practice 7Communicating About
Computing
Overview: Communication involves personal expression and exchangingideas with others. In computer science, students communicate withdiverse audiences about the use and effects of computation and theappropriateness of computational choices. Students write clear comments,document their work, and communicate their ideas through multipleforms of media. Clear communication includes using precise language andcarefully considering possible audiences.
7.1 Select, organize, and interpret large data sets from multiple sources tosupport a claim.
7.2 Describe, justify, and document computational processes and solutionsusing appropriate terminology consistent with the intended audience andpurpose.
7.3 Articulate ideas responsibly by observing intellectual property rightsand giving appropriate attribution.
Practice 8Using TechnologyAppropriately
Overview: Today’s technology-focused society requires more than just anunderstanding of how to use technology, but a working knowledge of whatis appropriate, responsible, and safe behavior in a digital world. Incomputer science, understanding extends to the use of: hardware andsoftware; applications such as email; the Internet and smallerhome/school/business networks; and the use of onsite and offsite storage.Additionally, appropriate use includes onsite and remote access.
8.1 Follow certain protocols when using technology.
8.2 Identify and address risks and/or unintended consequences associatedwith technological tools by considering all scenarios.
8.3 Evaluate technological tools systematically through the use of selectcriteria based on the requirements of the task and the capacity of the system.
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Con
trol
Stru
ctur
esCreatingCom
putation
alArtifacts
9-12
3-CT-C-1
Createan
djustifytheselectionof
specificcontrol
stru
ctur
eswhe
ntrad
eoffs
invo
lvecode
orga
nization
,read
ability,an
dpr
ogram
performan
cean
dexplain
thebe
nefits
anddraw
back
sof
choicesmad
e.
Com
putation
alThink
ing
&Program
ming
Con
trol
Stru
ctur
esCreatingCom
putation
alArtifacts
K-2
1A-C
T-M-1
Decom
pose
atask
into
aseto
fsm
allertasks.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
26 3-5
1B-C
T-M-1
Con
tinu
ally
decompo
sepr
oblemsinto
smaller
subtasks
untile
achsu
btaskisaman
ageableseto
fba
sicop
erations
.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
3-5
1B-C
T-M-2
Createcompu
tation
alartifactsby
incorp
orating
existing
mod
ules
into
one’sow
nworkto
solve
apr
oblem.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
•Develop
ing&
Using
Abstraction
s
•CreatingCom
putation
alArtifacts
6-8
2-CT-M-1
Decom
pose
compu
tation
alpr
oblemsto
facilitate
the
design
andim
plem
entation
ofpr
ograms.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
•Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
•CreatingCom
putation
alArtifacts
6-8
2-CT-M-2
Createpr
oced
ures
withpa
rametersto
orga
nize
code
andmak
eiteasier
toreus
e.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
Develop
ing&
Using
Abstraction
s
9-12
3-CT-M-1
Iden
tify
existing
compu
tation
alartifactsthat
can
beus
edforthesu
btasks
ofade
compo
sedpr
oblem.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
9-12
3-CT-M-2
Createcompu
tation
alartifactsby
incorp
oratingpr
e-de
fine
dpr
oced
ures,self-de
fine
dpr
oced
ures
and
external
artifacts.
Com
putation
alThink
ing
&Program
ming
Mod
ularity
CreatingCom
putation
alArtifacts
K-2
1A-C
T-CD-1
Develop
aplan
that
describe
swha
tacompu
tation
alartifact
shou
ldlook
like
andho
witshou
ldpe
rform.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
•CreatingCom
putation
alArtifacts
•Com
mun
icatingAbo
utCom
puting
27K-2
1A-C
T-CD-2
Iden
tify
atask
that
includ
essequ
encesan
dsimple
loop
s
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Testing&
Refi
ning
Com
putation
alArtifacts
3-5
1B-C
T-CD-1
Use
aniterativepr
ocessto
plan
thede
velopm
ent
ofacompu
tation
alartifact
byinclud
ingothe
rs’
perspe
ctives
andcons
ideringus
erpr
eferen
ces.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
•Fo
steringAnInclus
ive
Com
puting
Culture
•CreatingCom
putation
alArtifacts
3-5
1B-C
T-CD-2
Deb
ugerrors
inan
algo
rithm
orpr
ogram
that
includ
essequ
encesan
dsimpleloop
s.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Testing&
Refi
ning
Com
putation
alArtifacts
3-5
1B-C
T-CD-3
Describestep
stake
nan
dch
oicesmad
edu
ring
the
processof
creating
acompu
tation
alartifact.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Com
mun
icatingAbo
utCom
puting
6-8
2-CT-CD-1
Seek
andincorp
oratefeed
back
from
team
mem
bers
andus
ersto
refine
asolution
that
meets
user
need
s.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
•Fo
steringAnInclus
ive
Com
puting
Culture
•Collabo
rating
Aroun
dCom
puting
6-8
2-CT-CD-2
Test
andde
bugapr
ogram
toen
sure
itru
nsas
intend
ed.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Testing&
Refi
ning
Com
putation
alArtifacts
6-8
2-CT-CD-3
Describech
oicesmad
edu
ring
developm
ento
fcompu
tation
alartifacts.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Com
mun
icatingAbo
utCom
puting
9-12
3-CT-CD-1
System
atically
design
andim
plem
entc
ompu
tation
alartifactsfortargeted
audien
cesby
incorp
orating
feed
back
from
users.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
CreatingCom
putation
alArtifacts
28 9-12
3-CT-CD-2
System
atically
test
andrefine
prog
ramsus
inga
rang
eof
test
cases.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Testing&
Refi
ning
Com
putation
alArtifacts
9-12
3-CT-CD-3
Docum
entc
ompu
tation
alartifactsin
orde
rto
mak
ethem
easier
tofollow
,test,an
dde
bug.
Com
putation
alThink
ing
&Program
ming
Com
putation
alDesign
Com
mun
icatingAbo
utCom
puting
K-2
1A-C
SN-H
-1Iden
tify
theinpu
tsan
dou
tputsof
acompu
ter
system
.
Com
puting
System
s&Networks
Hum
an-C
ompu
ter
Interfaces
Com
mun
icatingAbo
utCom
puting
3-5
1B-C
SN-H
-1Describeho
wpe
ople
interact
withtheva
riou
spa
rts
ofcompu
ting
system
sto
accomplishtasks.
Com
puting
System
s&Networks
Hum
an-C
ompu
ter
Interfaces
Com
mun
icatingAbo
utCom
puting
6-8
2-CSN
-H-1
Iden
tify
impr
ovem
ents
tothede
sign
ofcompu
ting
devices,ba
sedon
anan
alysisof
how
usersinteract
withthede
vices.
Com
puting
System
s&Networks
Hum
an-C
ompu
ter
Interfaces
FosteringAnInclus
ive
Com
puting
Culture
9-12
3-CSN
-H-1
Ana
lyze
acompu
ting
system
andexplainho
wab
stractions
simplifytheun
derlying
implem
entation
detailsem
bedd
edin
everyd
ayob
jects
.
Com
puting
System
s&Networks
Hum
an-C
ompu
ter
Interfaces
Develop
ing&
Using
Abstraction
s
K-2
1A-C
SN-H
S-1
Use
appr
opriateterm
inolog
yin
iden
tifyingan
dde
scribing
thefunc
tion
ofcommon
physical
compo
nentsof
compu
ting
system
s(hardw
are).
Com
puting
System
s&Networks
Hardw
arean
dSo
ftware
Com
mun
icatingAbo
utCom
puting
3-5
1B-C
SN-H
S-1
Mod
elho
wcompu
terha
rdwarean
dsoftwarework
together
asasystem
toaccomplishtasks.
Com
puting
System
s&Networks
Hardw
arean
dSo
ftware
Develop
ing&
Using
Abstraction
s
296-8
2-CSN
-HS-1
Designpr
ojects
that
combine
hardwarean
dsoftware
compo
nentsto
collecta
ndus
eda
tato
perform
afunc
tion
.
Com
puting
System
s&Networks
Hardw
arean
dSo
ftware
CreatingCom
putation
alArtifacts
9-12
3-CSN
-HS-1
Com
pare
levelsof
abstractionan
dinteractions
betw
eenap
plicationsoftware,system
software,an
dha
rdwarelayers.
Com
puting
System
s&Networks
Hardw
arean
dSo
ftware
Develop
ing&
Using
Abstraction
s
K-2
1A-C
SN-T-1
Describeba
sicha
rdwarean
dsoftwarepr
oblems
usingap
prop
riateterm
inolog
y.
Com
puting
System
s&Networks
Trou
blesho
oting
•Te
sting&
Refi
ning
Com
putation
alArtifacts
•Com
mun
icatingAbo
utCom
puting
3-5
1B-C
SN-T-1
Determinepo
tentialsolutions
tosolvesimple
hardwarean
dsoftwarepr
oblemsus
ingcommon
trou
blesho
otingstrategies.
Com
puting
System
s&Networks
Trou
blesho
oting
Testing&
Refi
ning
Com
putation
alArtifacts
6-8
2-CSN
-T-1
Iden
tify
andfixpr
oblemswithcompu
ting
devices
andtheircompo
nentsus
ingasystem
atic
trou
blesho
otingmetho
dor
guide.
Com
puting
System
s&Networks
Trou
blesho
oting
Testing&
Refi
ning
Com
putation
alArtifacts
9-12
3-CSN
-T-1
Develop
andcommun
icatetrou
blesho
oting
strategies
othe
rscanus
eto
iden
tify
andfixerrors.
Com
puting
System
s&Networks
Trou
blesho
oting
Testing&
Refi
ning
Com
putation
alArtifacts
K-2
1A-C
SN-N
-1DescribetheInternet
asaplaceto
sharean
dfind
inform
ation.
Com
puting
System
s&Networks
Networks
andthe
Internet
Com
mun
icatingAbo
utCom
puting
30 3-5
1B-C
SN-N
-1
Mod
elho
winform
ationisbrok
endo
wninto
smallerpieces
ofda
ta,trans
mittedas
pack
ets
throug
hmultiplede
vicesov
erne
tworks
andthe
Internet,a
ndreassembled
atthede
stination.
Com
puting
System
s&Networks
Networks
andthe
Internet
Develop
ing&
Using
Abstraction
s
6-8
2-CSN
-N-1
Mod
eltherole
ofpr
otocolsin
tran
smitting
data
across
netw
orks
andtheInternet.
Com
puting
System
s&Networks
Networks
andthe
Internet
Develop
ing&
Using
Abstraction
s
9-12
3-CSN
-N-1
Iden
tify
theva
riou
selem
ents
ofane
tworkan
dde
scribe
how
they
func
tion
andinteract
totran
sfer
inform
ation.
Com
puting
System
s&Networks
Networks
andthe
Internet
Com
mun
icatingAbo
utCom
puting
K-2
1A-C
Y-R-1
Keeploginan
dpe
rson
alinform
ationpr
ivate,an
dlogoff
ofde
vicesap
prop
riately.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
3-5
1B-C
Y-R-1
Describetherisksof
sharingpe
rson
alinform
ation,
onweb
sitesor
othe
rpu
blic
foru
ms.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
3-5
1B-C
Y-R-2
Describewayspe
rson
alinform
ationcanbe
obtained
digitally.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
3-5
1B-C
Y-R-3
Describetherisksof
othe
rsus
ingon
e’spe
rson
alresour
cesor
devices.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
6-8
2-CY-R-1
Describetrad
eoffs
betw
eenallowinginform
ationto
bepu
blic
andke
epinginform
ationpr
ivatean
dsecu
re.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
316-8
2-CY-R-2
Describesocial
engine
eringattack
san
dthepo
tential
risksassociated
withthem
.Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
6-8
2-CY-R-3
Describerisksof
usingfree
andop
enservices.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
9-12
3-CY-R-1
Explainthepr
ivacyconc
erns
relatedto
thecollection
andgene
ration
ofda
tathroug
hau
tomated
processes
that
may
notb
eev
iden
ttous
ers.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
9-12
3-CY-R-2
Ana
lyze
anexisting
orpr
oposed
applicationto
iden
tify
thepo
tentialw
aysitcouldbe
used
toob
tain
sens
itiveinform
ation.
Cyb
ersecu
rity
Risks
•Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
•Using
Tech
nology
App
ropr
iately
9-12
3-CY-R-3
Explainho
wthedigitalsecur
ityof
anorga
nization
may
beaff
ectedby
theaction
sof
itsem
ploy
ees.
Cyb
ersecu
rity
Risks
Using
Tech
nology
App
ropr
iately
K-2
1A-C
Y-S-1
Recog
nize
basicdigitalsecur
ityfeatur
es.
Cyb
ersecu
rity
Safegu
ards
Using
Tech
nology
App
ropr
iately
3-5
1B-C
Y-S-1
Explainindividu
alaction
sthat
protectp
ersona
lelectron
icinform
ationan
dde
vices.
Cyb
ersecu
rity
Safegu
ards
Using
Tech
nology
App
ropr
iately
6-8
2-CY-S-1
Explainph
ysical
anddigitalsecur
itymeasu
resthat
protecte
lectronicinform
ation.
Cyb
ersecu
rity
Safegu
ards
Using
Tech
nology
App
ropr
iately
6-8
2-CY-S-2
Dem
onstrate
how
multiplemetho
dsof
encryp
tion
prov
idesecu
retran
smission
ofinform
ation.
Cyb
ersecu
rity
Safegu
ards
Using
Tech
nology
App
ropr
iately
32 9-12
3-CY-S-1
Recom
men
dsecu
rity
measu
resto
addressva
riou
sscen
ariosba
sedon
factorssu
chas
efficien
cy,
feasibility,an
dethicalimpa
cts.
Cyb
ersecu
rity
Safegu
ards
Using
Tech
nology
App
ropr
iately
9-12
3-CY-S-2
Explaintrad
eoffs
whe
nselectingan
dim
plem
enting
cybe
rsecur
ityrecommen
dation
s.Cyb
ersecu
rity
Safegu
ards
Using
Tech
nology
App
ropr
iately
K-2
1A-C
Y-RP-1
Iden
tify
situations
withph
ysical
anddigitala
rtifacts
applications
andde
vicesthat
shou
ldbe
repo
rted
toaresp
onsiblead
ult.
Cyb
ersecu
rity
Respo
nse
Using
Tech
nology
App
ropr
iately
3-5
1B-C
Y-RP-1
Iden
tify
andde
scribe
unus
uald
ataor
beha
viorsof
applications
andde
vicesthat
shou
ldbe
repo
rted
toaresp
onsiblead
ult.
Cyb
ersecu
rity
Respo
nse
Using
Tech
nology
App
ropr
iately
6-8
2-CY-RP-1
Describewhich
action
sto
take
andno
ttotake
whe
nan
applicationor
device
repo
rtsapr
oblem
orbe
havesun
expe
cted
ly.
Cyb
ersecu
rity
Respo
nse
Using
Tech
nology
App
ropr
iately
9-12
3-CY-RP-1
Describetheap
prop
riateaction
sto
take
inresp
onse
tode
tected
secu
rity
breach
es.
Cyb
ersecu
rity
Respo
nse
Using
Tech
nology
App
ropr
iately
K-2
1A-D
A-C
VT-1
Collect
andpr
esen
tthe
sameda
tain
multipleform
ats.
Data&Ana
lysis
Collection,
Visua
lization
,Tran
sformation
•Develop
ing&
Using
Abstraction
s
•Com
mun
icatingAbo
utCom
puting
333-5
1B-D
A-C
VT-1
Organ
izean
dpr
esen
tcollected
data
tohigh
ligh
trelation
shipsan
dsu
pporta
claim.
Data&Ana
lysis
Collection,
Visua
lization
,Tran
sformation
Develop
ing&
Using
Abstraction
s
Com
mun
icatingAbo
utCom
puting
6-8
2-DA-C
VT-1
Collect
data
usingcompu
tation
altoolsor
online
sour
cesan
dtran
sform
theda
tato
mak
eitmore
useful
andreliab
le.
Data&Ana
lysis
Collection,
Visua
lization
,Tran
sformation
Testing&
Refi
ning
Com
putation
alArtifacts
9-12
3-DA-C
VT-1
Select
appr
opriateda
ta-collectiontoolsan
dpr
esen
tation
tech
niqu
esfordiffe
rent
type
sof
data.
Data&Ana
lysis
Collection,
Visua
lization
,Tran
sformation
•Develop
ing&
Using
Abstraction
•Com
mun
icatingAbo
utCom
puting
K-2
1A-D
A-IM-1
Iden
tify
andde
scribe
patterns
inda
tapr
esen
tation
s,su
chas
charts
orgrap
hs,tomak
epr
ediction
s.Data&Ana
lysis
Inferenc
esan
dMod
els
Develop
ing&
Using
Abstraction
s
3-5
1B-D
A-IM-1
Use
data
tohigh
ligh
torpr
oposecaus
e-an
d-eff
ect
relation
ships,pr
edicto
utcomes,o
rcommun
icate
anidea.
Data&Ana
lysis
Inferenc
esan
dMod
els
•CreatingCom
putation
alArtifacts
•Com
mun
icatingAbo
utCom
puting
6-8
2-DA-IM-1
Createan
drefine
compu
tation
almod
elsba
sedon
gene
ratedor
gathered
data.
Data&Ana
lysis
Inferenc
esan
dMod
els
•Develop
ing&
Using
Abstraction
•CreatingCom
putation
alArtifacts
•Te
sting&
Refi
ning
Com
putation
alArtifacts
34 6-8
2-DA-IM-2
Discu
sspo
tentialv
isible
biases
that
couldexistin
ada
taseta
ndho
wthesebiases
couldaff
ect
analysisconc
lusion
s.Data&Ana
lysis
Inferenc
esan
dMod
els
•Fo
steringAnInclus
ive
Com
puting
Culture
•Com
mun
icatingAbo
utCom
puting
9-12
3-DA-IM-1
Createcompu
tation
almod
elsthat
repr
esen
tthe
relation
shipsam
ongdiffe
rent
elem
ents
ofda
tacollectedfrom
aph
enom
enon
orpr
ocess.
Data&Ana
lysis
Inferenc
esan
dMod
els
•Develop
ing&
Using
Abstraction
•CreatingCom
putation
alArtifacts
9-12
3-DA-IM-2
Discu
sspo
tentialh
idde
nbiases
that
couldbe
introd
uced
while
collecting
ada
taseta
ndho
wthesebiases
couldaff
ecta
nalysisconc
lusion
s.Data&Ana
lysis
Inferenc
esan
dMod
els
•Fo
steringAnInclus
ive
Com
puting
Culture
•Com
mun
icatingAbo
utCom
puting
9-12
3-DA-IM-3
Evalua
tetheab
ilityof
mod
elsan
dsimulations
totest
andsu
pportthe
refine
men
tofhy
potheses.
Data&Ana
lysis
Inferenc
esan
dMod
els
•Develop
ing&
Using
Abstraction
•Te
sting&
Refi
ning
Com
putation
alArtifacts
K-2
1A-D
A-ST-1
Iden
tify
data
asinform
ationthat
isstored
bysoftware.
Data&Ana
lysis
Storag
eDevelop
ing&
Using
Abstraction
s
3-5
1B-D
A-ST-1
Store,copy
,search,
retrieve,m
odify,an
dde
lete
data
usingacompu
ting
device.
Data&Ana
lysis
Storag
e
•Collabo
rating
Aroun
dCom
puting
•Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
6-8
2-DA-ST-1
Store,retrieve,a
ndshareda
tato
collab
orate,us
ing
aclou
d-ba
sedsystem
.Data&Ana
lysis
Storag
e
•Collabo
rating
Aroun
dCom
puting
•CreatingCom
putation
alArtifacts
356-8
2-DA-ST-2
Describeva
riou
slow-level
data
tran
sformations
and
iden
tify
which
resu
ltin
aloss
ofinform
ation
Data&Ana
lysis
Storag
eDevelop
ing&
Using
Abstraction
s
9-12
3-DA-ST-1
Explaintrad
eoffs
betw
eenstoringda
talocallyor
incentral,clou
d-ba
sedsystem
s.Data&Ana
lysis
Storag
e
•Collabo
rating
Aroun
dCom
puting
•CreatingCom
putation
alArtifacts
9-12
3-DA-ST-2
Tran
slateda
taforva
riou
sreal-w
orld
phen
omen
a,su
chas
characters,n
umbe
rs,a
ndim
ages,intobits.
Data&Ana
lysis
Storag
eDevelop
ing&
Using
Abstraction
s
K-2
1A-D
L-CU-1
Use
softwaretoolsto
create
simpledigitala
rtifacts
Digital
Literacy
Creationan
dUse
Using
Tech
nology
App
ropr
iately
3-5
1B-D
L-CU-1
Use
softwaretoolsto
create
andsharemultimed
iaartifacts
Digital
Literacy
Creationan
dUse
Using
Tech
nology
App
ropr
iately
6-8
2-DL-CU-1
Use
softwaretoolsto
create
artifactsthat
enga
geus
ersov
ertime
Digital
Literacy
Creationan
dUse
Using
Tech
nology
App
ropr
iately
9-12
3-DL-CU-1
Select
appr
opriatesoftwaretoolsor
resour
ces
tocreate
acomplex
artifact
orsolveapr
oblem.
Digital
Literacy
Creationan
dUse
Using
Tech
nology
App
ropr
iately
K-2
1A-D
L-SD
I-1
Con
duct
basicdigitalsearche
s.Digital
Literacy
Search
ingDigital
Inform
ation
Using
Tech
nology
App
ropr
iately
3-5
1B-D
L-SD
I-1
Con
duct
andrefine
multi-criteriasearch
esov
erdigital
inform
ation.
Digital
Literacy
Search
ingDigital
Inform
ation
Using
Tech
nology
App
ropr
iately
6-8
2-DL-SD
I-1
Con
duct
search
esov
ermultipletype
sof
digital
inform
ation.
Digital
Literacy
Search
ingDigital
Inform
ation
Using
Tech
nology
App
ropr
iately
36 9-12
3-DL-SD
I-1
Decom
pose
acomplex
prob
lem
into
multiplequ
estion
s,iden
tify
which
canbe
explored
throug
hdigitalsou
rces,
andsynthe
size
queryresu
ltsus
ingava
rietyof
software
tools.
Digital
Literacy
Search
ingDigital
Inform
ation
Using
Tech
nology
App
ropr
iately
K-2
1A-D
L-US-1
Describeba
sicdiffe
renc
esbe
tweenhu
man
san
dcompu
ters
forpe
rformingcompu
tation
altasks.
Digital
Literacy
Und
erstan
ding
Software
Tools
Using
Tech
nology
App
ropr
iately
3-5
1B-D
L-US-1
Describethediffe
rent
high
-level
tasksthat
arecommon
tosoftwaretoolsthat
stud
ents
use.
Digital
Literacy
Und
erstan
ding
Software
Tools
Using
Tech
nology
App
ropr
iately
6-8
2-DL-US-1
Describethediffe
rent
form
atsof
softwarecompo
nentsthat
supp
ortc
ommon
tasksin
softwaretools.
Digital
Literacy
Und
erstan
ding
Software
Tools
Using
Tech
nology
App
ropr
iately
9-12
3-DL-US-1
Describediffe
rent
kind
sof
compu
tation
sthat
software
toolspe
rform
totailo
rasystem
toindividu
alus
ers.
Digital
Literacy
Und
erstan
ding
Software
Tools
Using
Tech
nology
App
ropr
iately
K-2
1A-R
C-C
U-1
Com
pare
andcontrast
how
individu
alslive
andwork
before
andaftertheim
plem
entation
orad
option
ofne
wcompu
ting
tech
nology.
Respo
nsible
Com
puting
&So
ciety
Culture
Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
3-5
1B-R
C-C
U-1
Com
pare
andcontrast
compu
ting
tech
nologies
that
have
chan
gedtheworld,a
ndexpr
essho
wthose
tech
nologies
influ
ence,a
ndareinflu
encedby,
cultural
practices.
Respo
nsible
Com
puting
&So
ciety
Culture
Recog
nizing
&Defi
ning
Com
putation
alPr
oblems
3-5
1B-R
C-C
U-2
Iden
tify
waysto
impr
ovetheaccessibilityan
dus
ability
oftech
nology
prod
ucts
forthediversene
edsan
dwan
tsof
users.
Respo
nsible
Com
puting
&So
ciety
Culture
FosteringAnInclus
ive
Com
puting
Culture
376-8
2-RC-C
U-1
Com
pare
andcontrast
trad
eoffs
associated
with
compu
ting
tech
nologies
that
affectp
eople’severyd
ayactivities
andcareer
option
s.
Respo
nsible
Com
puting
&So
ciety
Culture
Com
mun
icatingAbo
utCom
puting
6-8
2-RC-C
U-2
Discu
ssissu
esof
bias
andaccessibilityin
thede
sign
ofexisting
tech
nologies.
Respo
nsible
Com
puting
&So
ciety
Culture
FosteringAnInclus
ive
Com
puting
Culture
9-12
3-RC-C
U-1
Evalua
tethewayscompu
ting
impa
ctspe
rson
al,ethical,
social,econo
mic,a
ndcu
ltural
practices.
Respo
nsible
Com
puting
&So
ciety
Culture
FosteringAnInclus
ive
Com
puting
Culture
9-12
3-RC-C
U-2
Designan
dan
alyz
ecompu
tation
alartifactsto
redu
cebias
andeq
uity
deficits.
Respo
nsible
Com
puting
&So
ciety
Culture
FosteringAnInclus
ive
Com
puting
Culture
Testing&
Refi
ning
Com
putation
alArtifacts
9-12
3-RC-C
U-3
Evalua
tetheim
pact
ofeq
uity,a
ccess,an
dinflu
ence
onthedistribu
tion
ofcompu
ting
resour
cesin
aglob
alsociety.
Respo
nsible
Com
puting
&So
ciety
Culture
FosteringAnInclus
ive
Com
puting
Culture
K-2
1A-R
C-SLE
-1Discu
ssow
nershipan
dattributionof
digitala
rtifacts.
Respo
nsible
Com
puting
&So
ciety
Safety,L
aw&
Ethics
Com
mun
icatingAbo
utCom
puting
3-5
1B-R
C-SLE
-1Incorp
oratepu
blic
domainor
creative
common
smed
iainto
adigitala
rtifact,an
drefrainfrom
copy
ingor
usingmaterialc
reated
byothe
rswitho
utpe
rmission
.
Respo
nsible
Com
puting
&So
ciety
Safety,L
aw&
Ethics
Com
mun
icatingAbo
utCom
puting
6-8
2-RC-SLE
-1Discu
ssho
wlawscontrolu
sean
daccess
tointellectual
prop
erty,a
ndman
date
broa
daccess
toinform
ationtech
nologies.
Respo
nsible
Com
puting
&So
ciety
Safety,L
aw&
Ethics
Com
mun
icatingAbo
utCom
puting
38 9-12
3-RC-SLE
-1Ev
alua
tetheim
pact
ofintellectual
prop
erty
laws
ontheus
eof
digitalinformation
Respo
nsible
Com
puting
&So
ciety
Safety,L
aw&
Ethics
Com
mun
icatingAbo
utCom
puting
9-12
3-RC-SLE
-2Ev
alua
tethesocial
andecon
omic
implications
ofpr
ivacyan
dfree
speech
inthecontexto
fsafety,
law,o
rethics.
Respo
nsible
Com
puting
&So
ciety
Safety,L
aw&
Ethics
Com
mun
icatingAbo
utCom
puting
K-2
1A-R
C-SI-1
Workresp
ectfully
andresp
onsiblywithothe
rson
line
.
Respo
nsible
Com
puting
&So
ciety
Social
Interactions
Collabo
rating
Aroun
dCom
puting
3-5
1B-R
C-SI-1
Seek
diversepe
rspe
ctives
forthepu
rposeof
impr
ovingcompu
tation
alartifacts.
Respo
nsible
Com
puting
&So
ciety
Social
Interactions
FosteringAnInclus
ive
Com
puting
Culture
6-8
2-RC-SI-1
Collabo
rate
andstrategize
withman
yon
line
contribu
tors
whe
ncreating
acompu
tation
alor
digitala
rtifact.
Respo
nsible
Com
puting
&So
ciety
Social
Interactions
•Collabo
rating
Aroun
dCom
puting
•CreatingCom
putation
alArtifacts
9-12
3-RC-SI-1
Use
toolsan
dmetho
dsforcollab
orationon
apr
ojecttoincrease
conn
ectivity
betw
eenpe
ople
indiffe
rent
cultur
esan
dcareer
fields
.
Respo
nsible
Com
puting
&So
ciety
Social
Interactions
Collabo
rating
Aroun
dCom
puting
39App
endi
x A
40 DataStructures&DataTypes
Mod
elre
al-w
orld
obje
ctsa
nd/o
rpr
oces
sest
hat
can
bere
pres
ente
dby
vari
oust
ypes
ofda
ta.
Stud
ents
shou
ldbe
able
tore
pres
entp
hysi
cal
obje
ctsa
ndth
eira
ttrib
utes
asw
ritte
nda
ta.
Fore
xam
ple,
stude
ntsc
ould
use
thum
bsup
/dow
nas
repr
esen
tatio
nsof
yes/
no,u
sear
rows
whe
nw
ritin
gal
gori
thm
sto
repr
esen
tdire
ctio
n,or
enco
dean
dde
code
word
susi
ngnu
mbe
rs,
pict
ogra
phs,
orot
hers
ymbo
lsto
repr
esen
tlet
ters
orwo
rds.
Prac
tice(
s):4
.4
Iden
tify
real
-wor
ldex
ampl
esof
data
stru
ctur
esan
dda
taty
pes.
Dat
astr
uctu
resh
old
mul
tiple
piec
esof
data
abou
ton
eth
ing.
Exam
ples
ofda
tastr
uctu
resa
rea
listo
fpl
anet
sand
thei
rdia
met
ers,
ora
phon
eco
ntac
twith
the
first
nam
e,la
stna
me,
and
phon
enu
mbe
rofa
pers
on.E
ach
piec
eof
data
hasa
data
type
,suc
has
adi
amet
erbe
ing
anu
mbe
r,an
da
nam
ebe
ing
astr
ing
ofch
arac
ters
.Stu
dent
ssho
uld
beab
leto
desc
ribe
how
data
isgr
oupe
dfo
ran
asso
ciat
ion
with
anen
tity
inei
ther
the
real
world
orin
aco
mpu
tatio
nala
rtifa
ct,a
ndth
ety
peof
that
data
.Fo
rexa
mpl
e,stu
dent
scou
ldde
scri
beth
eda
tastr
uctu
resa
ndda
taty
pesi
nan
onlin
ega
me
that
hass
ever
alch
arac
ters
.
Prac
tices
(s):
3.1
Org
aniz
eda
tain
toan
appr
opri
ate
data
stru
ctur
ein
apr
ogra
m.
Stud
ents
shou
ldbe
able
toid
entif
yth
eco
mpo
nent
sof
data
ina
give
nco
mpu
tatio
nalp
robl
em,d
eter
min
eth
ety
peof
each
com
pone
nt,a
ndpr
opos
ea
struc
tura
lor
gani
zatio
nfo
rtho
seda
ta.F
orex
ampl
e,stu
dent
sco
uld
repr
esen
tcha
ract
ersi
na
gam
ew
itha
data
type
that
hasa
nam
e,pi
ctur
e,an
dpo
sitio
n,an
dco
uld
repr
esen
tthe
colle
ctio
nof
char
acte
rson
the
scre
enas
apr
ogra
mlis
toft
hatd
ata
type
.
Prac
tice(
s):5
.1
Cre
ate
apr
ogra
mth
atpr
oces
sesa
colle
ctio
nof
data
.
Prog
ram
softe
npr
oces
scol
lect
ions
ofda
ta,s
uch
asth
eco
llect
ion
ofso
ngtit
lesi
na
play
list,
ora
colle
ctio
nof
alls
prite
son
the
scre
en.S
tude
ntss
houl
dbe
able
toor
gani
zem
ultip
leda
taite
mso
fthe
sam
ety
pein
toa
prog
ram
data
struc
ture
(suc
has
alis
tora
rray
)and
wri
tea
prog
ram
that
com
pute
sare
sult
abou
ttha
tco
llect
ion.
Fore
xam
ple,
stude
ntsc
ould
chec
kto
see
ifan
ytw
osp
rite
sin
apr
ogra
mlis
tora
rray
ofsp
rite
sha
veco
llide
don
the
scre
en.
Prac
tice(
s):5
.2
ControlStructures
Dev
elop
simpl
epr
ogra
msw
ithse
quen
cesa
ndsim
ple
repe
titio
ns.
Prog
ram
min
gco
ntro
lstr
uctu
ress
peci
fyth
eor
der
inw
hich
instr
uctio
nsar
eex
ecut
edw
ithin
apr
ogra
m.S
eque
nces
are
the
orde
rofi
nstr
uctio
nsin
apr
ogra
m.F
orex
ampl
e,if
dial
ogue
isno
tse
quen
ced
corr
ectly
whe
npr
ogra
mm
ing
asi
mpl
ean
imat
edsto
ry,t
hesto
ryw
illno
tmak
ese
nse.
Ifth
eco
mm
ands
topr
ogra
ma
robo
tare
noti
nth
eco
rrec
tord
er,t
hero
botw
illno
tcom
plet
eth
ede
sire
dta
sk.R
epet
ition
cons
truc
ts(w
hich
vary
acro
ssla
ngua
gesb
utin
clud
elo
ops)
allo
wfo
rper
form
ing
oper
atio
nsm
ultip
letim
es.F
orex
ampl
e,stu
dent
scou
ldm
odel
repe
titio
nsfo
rha
ndwa
shin
gby
chan
ting
"rub
your
hand
s,ru
byo
urha
nds..
..rub
your
hand
s,"th
enre
plac
ing
that
with
"rub
your
hand
sten
times
."
Prac
tice(
s):5
.2
Cre
ate
prog
ram
stha
tcom
bine
sequ
ence
s,re
petit
ions
,con
ditio
nals,
and/
orev
ents
.
Con
trols
truc
ture
sspe
cify
the
orde
rin
whi
chin
struc
tions
are
exec
uted
with
ina
prog
ram
and
can
beco
mbi
ned
tosu
ppor
tthe
crea
tion
ofm
ore
com
plex
prog
ram
s.Ev
ents
allo
wpo
rtio
nsof
apr
ogra
mto
run
base
don
asp
ecifi
cin
tera
ctio
nw
ithth
epr
ogra
m,s
uch
asth
eus
ercl
icki
ngth
em
ouse
.Stu
dent
ssho
uld
beab
leto
crea
tea
prog
ram
usin
gev
ents
,con
ditio
nals
,an
dre
petit
ions
.For
exam
ple,
stude
ntsc
ould
wri
tea
prog
ram
toex
plai
nth
ewa
terc
ycle
and
whe
na
spec
ific
com
pone
ntis
clic
ked
(eve
nt),
the
prog
ram
woul
dsh
owin
form
atio
nab
outt
hatp
arto
fthe
wate
rcyc
le.C
ondi
tiona
lsal
low
fort
heex
ecut
ion
ofa
port
ion
ofco
dein
apr
ogra
mw
hen
ace
rtai
nco
nditi
onis
true
.Fo
rexa
mpl
e,stu
dent
scou
ldw
rite
am
ath
gam
eth
atas
ksa
mul
tiplic
atio
nqu
estio
nan
dth
enus
esa
cond
ition
alto
chec
kw
heth
eror
nott
hean
swer
that
wase
nter
edis
corr
ect.
Anex
ampl
eof
aco
mbi
ned
prog
ram
woul
dbe
am
ath
quiz
prog
ram
that
loop
sthr
ough
mul
tiple
ques
tions
each
with
aco
nditi
onal
toch
eck
fort
heri
ghta
nswe
r.
Prac
tice(
s):5
.2
Des
ign
prog
ram
stha
tcom
bine
cont
rol
stru
ctur
es,i
nclu
ding
nest
edre
petit
ions
and
com
poun
dco
nditi
onal
s.
Con
trols
truc
ture
scan
beco
mbi
ned
inm
any
ways
.Ne
sted
repe
titio
nsco
nsist
ofop
erat
ions
that
are
repe
ated
with
inot
herr
epea
ted
oper
atio
ns.
Com
poun
dco
nditi
onal
scom
bine
two
orm
ore
cond
ition
sin
alo
gica
lrel
atio
nshi
p(e
.g.,
usin
gAN
D,O
R,an
dN
OT)
,and
nesti
ngco
nditi
onal
sw
ithin
one
anot
hera
llows
the
resu
ltof
one
cond
ition
alto
lead
toan
othe
r.Fo
rexa
mpl
e,w
hen
prog
ram
min
gan
inte
ract
ive
story
,stu
dent
scou
ldre
peat
edly
chec
kw
heth
era
char
acte
rhas
ake
yan
dis
touc
hing
the
door
befo
reun
lock
ing
the
door
.
Prac
tice(
s):5
.1,5
.2
Cre
ate
and
just
ifyth
ese
lect
ion
ofsp
ecifi
cco
ntro
lst
ruct
ures
whe
ntr
adeo
ffsin
volv
eco
deor
gani
zatio
n,re
adab
ility
,and
prog
ram
perf
orm
ance
and
expl
ain
the
bene
fitsa
nddr
awba
ckso
fcho
ices
mad
e.
Apr
ogra
mm
erha
scho
ices
abou
twha
tcon
trol
struc
ture
sto
use.
Stud
ents
shou
ldbe
able
toch
oose
good
cont
rols
truc
ture
sand
desc
ribe
why
they
chos
eth
em.R
eada
bilit
yre
fers
toho
wcl
eart
hepr
ogra
mis
toot
herp
rogr
amm
ers.
The
disc
ussi
onof
perf
orm
ance
islim
ited
toa
theo
retic
alun
ders
tand
ing
ofex
ecut
ion
time
and
stora
gere
quire
men
ts;a
quan
titat
ive
anal
ysis
isno
texp
ecte
d.Fo
rex
ampl
e,th
estu
dent
scou
ldex
plai
nw
hyus
ing
are
petit
ion
cons
truc
tisp
refe
rabl
eto
wri
ting
(nea
rly)
iden
tical
code
mul
tiple
times
.Ano
ther
exam
ple
isth
atstu
dent
scou
ldpr
ogra
mw
ithse
ries
ofif-
else
state
men
tsfo
raco
mpl
exco
nditi
on,a
ndde
scri
beho
wth
isdi
ffers
inex
ecut
ion
and
read
abili
tyth
ana
sim
ilars
erie
sofi
fsta
tem
ents
(with
out"
else
"cl
ause
s)fo
rtha
tcom
plex
cond
ition
.
Prac
tice(
s):5
.2
2
41
Dec
ompo
sea
task
into
ase
tofs
mal
ler
task
s.
Dec
ompo
sitio
nis
the
acto
fbre
akin
gdo
wn
task
sin
tosi
mpl
erta
sks.
Stud
ents
shou
ldbe
able
tolis
tste
psfo
rapa
rtic
ular
task
.For
exam
ple,
stude
nts
coul
dde
scri
beth
eta
sksn
eede
dto
getr
eady
togo
hom
efro
msc
hool
.
Prac
tice(
s):3
.2
Con
tinua
llyde
com
pose
prob
lem
sint
osm
alle
rsu
btas
ksun
tilea
chsu
btas
kis
am
anag
eabl
ese
tof
basic
oper
atio
ns.
Stud
ents
shou
ldbr
eak
prob
lem
sint
ohi
erar
chie
sof
subt
asks
,eac
hof
whi
chin
turn
deco
mpo
sesi
nto
othe
rsub
task
sori
ndiv
idua
lste
ps.F
orex
ampl
e,stu
dent
scou
ldpl
ana
part
yby
sepa
ratin
gth
eta
skin
tosu
btas
kssu
chas
invi
ting
gues
ts,g
ettin
gpa
rty
favo
rs,p
lann
ing
gam
es,a
ndpr
epar
ing
food
.Th
ein
vitin
ggu
ests
ubta
skco
uld
bebr
oken
into
itsow
nsu
btas
ksof
dete
rmin
ing
agu
estl
ist,w
ritin
gin
vita
tions
,and
send
ing
invi
tatio
ns-w
here
each
ofth
ese
subt
asks
isa
man
agea
ble
seto
fba
sic
oper
atio
nsa
pers
onkn
owsh
owto
dosu
chas
wri
tean
dse
ndan
emai
lwith
the
invi
tatio
n.
Prac
tice(
s):3
.2
Dec
ompo
seco
mpu
tatio
nalp
robl
emst
ofa
cilit
ate
the
desig
nan
dim
plem
enta
tion
ofpr
ogra
ms.
Dec
ompo
sitio
nfa
cilit
ates
aspe
ctso
fpro
gram
deve
lopm
entb
yal
low
ing
stude
ntst
ofo
cuso
non
epi
ece
ata
time
(e.g
.,ge
tting
inpu
tfro
mth
eus
er,
proc
essi
ngth
eda
ta,a
nddi
spla
ying
the
resu
ltto
the
user
).D
ecom
posi
tion
also
enab
lesd
iffer
ent
stude
ntst
owo
rkon
diffe
rent
part
satt
hesa
me
time.
Stud
ents
shou
ldbe
able
tode
com
pose
aco
mpu
tatio
nalp
robl
emin
tosu
btas
ksth
atfa
cilit
ate
the
use
ofap
prop
riat
epr
ogra
mm
ing
lang
uage
cons
truc
tsth
atre
flect
the
subt
asks
ofth
epr
oble
mso
lutio
n.Fo
rexa
mpl
e,stu
dent
scou
ldm
atch
subt
asks
inth
eirp
robl
emde
com
posi
tion
topr
oced
ures
that
they
will
prog
ram
ina
prog
ram
min
gla
ngua
ge.
Prac
tice(
s):3
.3,5
.1
Iden
tify
exist
ing
com
puta
tiona
lart
ifact
stha
tcan
beus
edfo
rth
esu
btas
ksof
ade
com
pose
dpr
oble
m.
Stud
ents
shou
ldbe
able
tota
kea
prob
lem
that
they
deco
mpo
sed
tosu
btas
ksan
did
entif
yex
istin
gco
mpu
tatio
nals
olut
ions
toth
esu
btas
k.Fo
rexa
mpl
e,stu
dent
scou
ldfin
da
libra
ryof
proc
edur
esto
doda
tavi
sual
izat
ion
and
use
thos
epr
oced
ures
todi
spla
yda
tain
thei
rpro
gram
.
Prac
tice(
s):3
.2
Modularity
No
K-1
2st
anda
rd.
Cre
ate
com
puta
tiona
lart
ifact
sby
inco
rpor
atin
gex
istin
gm
odul
esin
toon
e’so
wn
work
toso
lve
apr
oble
m.
Stud
ents
shou
ldbe
able
toco
mbi
neex
istin
gco
mpu
tatio
nala
rtifa
ctsi
nto
thei
row
nco
mpu
tatio
nala
rtifa
ct.F
orex
ampl
e,stu
dent
sco
uld
com
bine
pict
ures
and
text
into
am
eme
pict
ure
orcr
eate
apr
ogra
mus
ing
the
exist
ing
instr
uctio
nsan
dbu
ilt-in
func
tions
ofa
prog
ram
min
gla
ngua
ge/e
nviro
nmen
t.
Prac
tice(
s):4
.2,5
.3
Cre
ate
proc
edur
esw
ithpa
ram
eter
sto
orga
nize
code
and
mak
eit
easie
rto
reus
e.
Proc
edur
esan
d/or
func
tions
can
beus
edm
ultip
letim
esw
ithin
apr
ogra
mto
repe
atgr
oups
ofin
struc
tions
.Stu
dent
ssho
uld
beab
leto
nam
eth
epr
oced
ures
appr
opri
atel
yto
mat
chth
eirf
unct
ion
and
beab
leto
defin
epa
ram
eter
stha
tcre
ate
diffe
rent
outp
utsf
ora
wid
era
nge
ofin
puts
.For
exam
ple,
all
stude
ntco
uld
crea
tea
proc
edur
eto
draw
circ
les
ofdi
ffere
ntsi
zesb
yad
ding
ara
dius
para
met
er.
Prac
tice(
s):4
.1,4
.3
Cre
ate
com
puta
tiona
lart
ifact
sby
inco
rpor
atin
gpr
e-de
fined
proc
edur
es,s
elf-d
efine
dpr
oced
ures
and
exte
rnal
artif
acts
.
Com
puta
tiona
lart
ifact
scan
becr
eate
dby
com
bini
ngan
dm
odify
ing
exist
ing
exte
rnal
artif
acts
orby
deve
lopi
ngne
war
tifac
ts.I
nter
actin
gm
odul
es,e
ach
with
asp
ecifi
cro
lebu
tcoo
rdin
ated
fora
com
mon
over
allp
urpo
se,a
llow
forb
ette
rman
agem
ento
fco
mpl
exta
sks.
Stud
ents
shou
ldbe
able
iden
tify
exist
ing
exte
rnal
mod
ules
that
they
can
use,
crea
tem
odul
esth
atdo
n’th
ave
ago
odex
istin
gso
lutio
n,an
dco
mbi
neth
ese
mod
ules
tocr
eate
aco
mpu
tatio
nala
rtifa
ct.F
orex
ampl
e,stu
dent
sco
uld
crea
tean
orig
inal
web
site
and
use
open
-sou
rce
Java
Scri
ptlib
rari
esto
expa
ndits
func
tiona
lity.
Asan
othe
rexa
mpl
e,stu
dent
sco
uld
crea
teth
eiro
wn
mod
ules
tocl
ean
and
proc
esss
peci
ficda
ta,a
ndth
enus
eex
istin
gm
odul
esfro
man
exte
rnal
libra
ryto
disp
lay
Prac
tice(
s):5
.2,5
.3
3
42
Dev
elop
apl
anth
atde
scri
besw
hata
com
puta
tiona
lart
ifact
shou
ldlo
oklik
ean
dho
wit
shou
ldpe
rfor
m.
Cre
atin
ga
plan
forw
hata
nar
tifac
tsho
uld
like
and
docl
arifi
esth
este
psth
atw
illbe
need
edto
crea
teit
and
can
beus
edto
chec
kif
itis
corr
ect.
Stud
ents
shou
ldbe
able
tolo
okco
mpl
ete
apl
anni
ngpr
oces
swith
the
teac
her’
sass
istan
ce.F
orex
ampl
e,stu
dent
sco
uld
crea
tea
plan
ning
docu
men
tsuc
has
asto
rym
ap,a
story
boar
d,or
ase
quen
tial
grap
hic
orga
nize
rto
illus
trate
the
prog
ram
.
Prac
tice(
s):5
.1,7
.2
Use
anite
rativ
epr
oces
sto
plan
the
deve
lopm
ento
faco
mpu
tatio
nala
rtifa
ctby
incl
udin
got
hers
’per
spec
tives
and
cons
ider
ing
user
pref
eren
ces.
Plan
ning
isan
impo
rtan
tpar
toft
heite
rativ
epr
oces
sofp
rogr
amde
velo
pmen
t.St
uden
tssh
ould
beab
leto
outli
neke
yfe
atur
es,t
ime
and
reso
urce
cons
train
ts,a
ndus
erex
pect
atio
ns.
Fore
xam
ple,
stude
ntsc
ould
docu
men
tapl
anus
ing
story
boar
ds,fl
owch
arts
,pse
udoc
ode,
orus
er-in
terf
ace
sket
ches
.
Prac
tice(
s):1
.1,5
.1
Seek
and
inco
rpor
ate
feed
back
from
team
mem
bers
and
user
sto
refin
ea
solu
tion
that
mee
tsus
erne
eds.
Dev
elop
men
ttea
mse
mpl
oyus
er-c
ente
red
desi
gnto
crea
teso
lutio
ns(e
.g.,
prog
ram
sand
devi
ces)
that
supp
ortt
hene
edso
fend
user
s,su
chas
anap
plic
atio
nth
atal
lows
peop
lew
ithsp
eech
diffi
culti
esto
trans
late
hard
-to-u
nder
stand
pron
unci
atio
nin
toun
ders
tand
able
lang
uage
.Fo
rexa
mpl
e,stu
dent
scou
ldbe
gin
tose
ekdi
vers
epe
rspe
ctiv
esth
roug
hout
the
desi
gnpr
oces
sto
impr
ove
thei
rcom
puta
tiona
lart
ifact
sby
focu
sing
onus
abili
ty,a
cces
sibi
lity,
age-
appr
opri
ate
cont
ent,
resp
ectfu
llan
guag
e,us
erpe
rspe
ctiv
e,pr
onou
nus
e,co
lorc
ontra
st,an
dea
seof
use.
Prac
tice(
s):1
.1,2
.3
Syst
emat
ical
lyde
sign
and
impl
emen
tcom
puta
tiona
lar
tifac
tsfo
rta
rget
edau
dien
cesb
yin
corp
orat
ing
feed
back
from
user
s.
Stud
ents
shou
ldbe
able
tofo
llow
asy
stem
atic
proc
ess
that
incl
udes
feed
back
from
broa
dau
dien
ceso
nth
eir
com
puta
tiona
lart
ifact
.For
exam
ple,
stude
ntsc
ould
crea
tea
user
satis
fact
ion
surv
ey,i
dent
ifydi
strib
utio
nm
etho
dsth
atco
uld
yiel
dfe
edba
ckfro
ma
dive
rse
audi
ence
onth
eus
abili
tyan
deff
ectiv
enes
soft
heir
webs
itean
ddo
cum
entt
hepr
oces
sofi
ncor
pora
ting
feed
back
.
Prac
tice(
s):5
.1
ComputationalDesign
Iden
tify
ata
skth
atin
clud
esse
quen
cesa
ndsim
ple
loop
s.
Stud
ents
shou
ldbe
able
toim
plem
enta
sim
ple
algo
rith
m,d
eter
min
eif
itis
inco
rrec
t,an
dfix
erro
rs.F
orex
ampl
eon
estu
dent
coul
ddi
rect
anot
hers
tude
ntfro
ma
start
loca
tion
toan
end
loca
tion
byho
ldin
gup
arro
ws.I
fthe
seco
ndstu
dent
fails
toge
tto
the
end
loca
tion,
the
dire
ctin
gstu
dent
shou
ldde
term
ine
whe
reth
em
istak
eoc
curr
ed,a
ndco
rrec
tthe
mist
ake.
Prac
tice(
s):6
.2
Deb
uger
rors
inan
algo
rith
mor
prog
ram
that
incl
udes
sequ
ence
sand
simpl
elo
ops.
Algo
rith
mso
rpro
gram
smay
nota
lway
swor
kco
rrec
tly.S
tude
ntss
houl
dbe
able
tous
eva
riou
sstr
ateg
ies,
such
asfo
llow
ing
the
algo
rith
min
aste
p-by
-ste
pm
anne
r,ch
angi
ngth
ese
quen
ceof
the
steps
,and
/oru
sing
tria
land
erro
rto
fixpr
oble
msi
nal
gori
thm
sand
prog
ram
s.Fo
rex
ampl
e,stu
dent
scou
ldch
eck
thei
rons
cree
nch
arac
ters
tose
eif
they
are
colli
ding
beca
use
ofto
om
any
repe
titio
ns.
Prac
tice(
s):6
.2
Test
and
debu
ga
prog
ram
toen
sure
itru
nsas
inte
nded
.
Aspr
ogra
msa
rede
velo
ped,
they
shou
ldbe
cont
inuo
usly
teste
dto
ensu
reth
eyru
nas
inte
nded
.If
not,
erro
rssh
ould
beid
entifi
edan
dfix
ed.
Stud
ents
shou
ldal
sobe
able
tosu
cces
sful
lyde
bug
sim
ple
erro
rsin
prog
ram
scre
ated
byot
hers
.For
exam
ple,
stude
ntsc
ould
revi
ewpr
ogra
ms
inte
ntio
nally
crea
ted
with
erro
rsto
iden
tify
the
prob
lem
and
dete
rmin
eth
efix
.
Prac
tice(
s):6
.1,6
.2
Syst
emat
ical
lyte
stan
dre
fine
prog
ram
susin
ga
rang
eof
test
case
s.
Test
case
sand
use
case
sare
crea
ted
and
anal
yzed
tobe
tterm
eett
hene
edso
fuse
rsan
dto
eval
uate
whe
ther
prog
ram
sfun
ctio
nas
inte
nded
.Stu
dent
ssho
uld
beab
leto
reco
gniz
eth
atte
sting
isa
delib
erat
epr
oces
sth
atis
itera
tive,
syste
mat
ic,a
ndpr
oact
ive.
For
exam
ple,
stude
ntsc
ould
begi
nto
test
prog
ram
sby
cons
ider
ing
pote
ntia
lerr
ors,
such
asw
hatw
illha
ppen
ifa
user
ente
rsin
valid
inpu
ts(e
.g.,
nega
tive
num
bers
and
0in
stead
ofpo
sitiv
enu
mbe
rs).
Prac
tice(
s):6
.1
4
43ComputationalDesign
No
K-1
2st
anda
rd.y
yyyy
yyyy
yyyy
yyyy
yyyi
Des
crib
est
epst
aken
and
choi
cesm
ade
duri
ngth
epr
oces
sofc
reat
ing
aco
mpu
tatio
nal
artif
act.
Stud
ents
shou
ldbe
able
tota
lkor
wri
te,u
sing
appr
opri
ate
term
inol
ogy,
abou
tthe
goal
sand
expe
cted
outc
omes
ofth
eco
mpu
tatio
nala
rtifa
cts
that
they
crea
tean
dth
ech
oice
stha
tthe
ym
ade.
Fore
xam
ple,
stude
ntsc
ould
desc
ribe
thei
rwor
kus
ing
ano
tebo
okof
desi
gns,
codi
ngjo
urna
ls,
disc
ussi
onsw
itha
teac
her,
clas
spre
sent
atio
ns,o
rbl
ogs.
Prac
tice(
s):7
.2
Des
crib
ech
oice
smad
edu
ring
deve
lopm
ento
fco
mpu
tatio
nala
rtifa
cts.
Peop
leco
mm
unic
ate
abou
tthe
irco
deto
help
othe
rsun
ders
tand
and
use
thei
rpro
gram
s.St
uden
tssh
ould
beab
leto
expl
ain
thei
rdes
ign
choi
cest
ode
mon
strat
ean
unde
rsta
ndin
gof
thei
rwo
rk.F
orex
ampl
e,stu
dent
scou
ldin
clud
eth
ese
expl
anat
ions
asin
-line
code
com
men
tsfo
rco
llabo
rato
rsan
das
sess
ors,
oras
part
ofa
sum
mat
ive
pres
enta
tion,
such
asa
code
walk
-thr
ough
orco
ding
jour
nal.
Prac
tice(
s):7
.2
Doc
umen
tcom
puta
tiona
lart
ifact
sin
orde
rto
mak
eth
emea
sier
tofo
llow,
test
,and
debu
g.
Doc
umen
tatio
nal
lows
crea
tors
and
othe
rsto
mor
eea
sily
use
and
unde
rsta
nda
prog
ram
.Stu
dent
ssho
uld
prov
ide
docu
men
tatio
nfo
rend
user
stha
texp
lain
thei
rart
ifact
s,ho
wth
eyar
eus
ed,a
ndw
hyth
eyac
tthe
way
they
do.
Fore
xam
ple,
stude
ntsc
ould
prov
ide
apr
ojec
tove
rvie
w,de
sign
ratio
nale
and
clea
ruse
rins
truc
tions
.The
ysh
ould
com
mun
icat
eth
eirp
roce
ssus
ing
desi
gndo
cum
ents
,flo
wcha
rts,
and
pres
enta
tions
.
Prac
tice(
s):7
.2
5
44
CO
MPU
TIN
GSY
STEM
SA
ND
NET
WO
RK
SG
rade
sK-2
Gra
des3
-5G
rade
s6-8
Gra
des9
-12
Human-ComputerInteraction
Iden
tify
the
inpu
tsan
dou
tput
sofa
com
pute
rsy
stem
.
Ther
ear
em
any
ways
toex
chan
gein
form
atio
nw
itha
com
pute
r.St
uden
tssh
ould
beab
leto
iden
tify
the
com
pone
nts
ofa
com
pute
rsys
tem
that
help
peop
lein
puti
nfor
mat
ion
and
the
part
stha
tpr
oduc
ea
desi
red
outp
ut.F
orex
ampl
e,stu
dent
scou
ldus
ea
digi
talk
eybo
ard
toin
putl
ette
rsan
dsy
mbo
lsor
pres
spla
yon
avi
deo
play
erto
start
avi
deo,
ordr
aga
digi
talo
bjec
tfro
mon
elo
catio
nto
anot
her.
Prac
tice(
s):7
.2
Des
crib
eho
wpe
ople
inte
ract
with
the
vari
ousp
arts
ofco
mpu
ting
syst
ems
toac
com
plish
task
s.
Com
putin
gde
vice
softe
nde
pend
onhu
man
inte
ract
ions
totr
igge
rpar
ticul
arac
tions
.Ake
yboa
rdin
puto
ram
ouse
clic
km
ayca
use
ach
ange
inin
form
atio
ndi
spla
yed
ona
scre
en.
Stud
ents
shou
ldun
ders
tand
that
com
pute
rsar
epr
ogra
mm
edto
prod
uce
cert
ain
outp
utsb
ased
onpa
rtic
ular
inpu
ts,a
ndsh
ould
beab
leto
desc
ribe
how
peop
lean
dde
vice
sint
erac
t,us
ing
appr
opri
ate
term
inol
ogy.
Fore
xam
ple,
stude
ntsc
ould
desc
ribe
allo
fthe
actio
nsne
eded
topl
ayth
eirf
avor
itevi
deo
gam
eor
tous
eth
eirf
avor
iteap
p.
Prac
tice(
s):7
.2
Iden
tify
impr
ovem
ents
toth
ede
sign
ofco
mpu
ting
devi
ces,
base
don
anan
alys
isof
how
user
sint
erac
twith
the
devi
ces.
The
study
ofhu
man
–com
pute
rint
erac
tion
(HC
I)ca
nim
prov
eth
ede
sign
ofbo
thha
rdwa
rean
dso
ftwar
eof
devi
ces.
Fore
xam
ple,
anas
sisti
vede
vice
may
incl
ude
am
icro
phon
e(h
ardw
are
sens
or)
that
conv
erts
spok
enwo
rdst
ow
ritte
nte
xt.
Stud
ents
shou
ldbe
able
toun
ders
tand
that
devi
ces
can
bede
sign
edfo
rava
riet
yof
purp
oses
,inc
ludi
ngac
cess
ibili
ty,e
rgon
omic
s,an
dle
arna
bilit
y.Fo
rex
ampl
e,stu
dent
scou
ldm
ake
reco
mm
enda
tions
fori
mpr
ovem
ents
toex
istin
gde
vice
s(e.
g.,a
lapt
op,s
mar
tpho
ne,o
rtab
let),
softw
are
(app
licat
ions
),or
they
coul
dde
sign
thei
row
nco
mpo
nent
orso
ftwar
ein
terf
ace
(e.g
.,cr
eate
thei
row
nco
ntro
llers
).
Prac
tice(
s):1
.1
Ana
lyze
aco
mpu
ting
syst
eman
dex
plai
nho
wab
stra
ctio
nssim
plify
the
unde
rlyi
ngim
plem
enta
tion
deta
ilsem
bedd
edin
ever
yday
obje
cts.
Com
putin
gde
vice
sare
ofte
nin
tegr
ated
with
othe
rsy
stem
s,in
clud
ing
biol
ogic
al,m
echa
nica
l,an
dso
cial
syste
ms.
Exam
ples
are:
am
edic
alde
vice
can
beem
bedd
edin
side
ape
rson
tom
onito
rand
regu
late
;an
assi
stive
liste
ning
devi
ceca
nfil
tero
utce
rtai
nfre
quen
cies
and
ampl
ifyot
hers
;am
onito
ring
devi
cein
side
am
otor
vehi
cle
can
track
ape
rson
’sdr
ivin
gpa
ttern
sand
habi
ts;a
nda
faci
alre
cogn
ition
devi
ceca
nbe
inte
grat
edin
toa
secu
rity
syste
mto
iden
tify
ape
rson
.St
uden
tssh
ould
beab
leto
desc
ribe
(but
notc
reat
e)an
inte
grat
edor
embe
dded
syste
ms.
Fore
xam
ple,
stude
nts
coul
dse
lect
anem
bedd
edde
vice
such
asa
cars
tere
o,id
entif
yth
ety
peso
fdat
a(r
adio
statio
npr
eset
s,vo
lum
ele
vel)
and
proc
edur
es(in
crea
sevo
lum
e,sto
re/re
call
save
dsta
tion,
mut
ebu
tton)
,and
expl
ain
how
the
impl
emen
tatio
nde
tails
are
hidd
enfro
mth
eus
er.
Prac
tice(
s):4
.1
Hardware&Software
Use
appr
opri
ate
term
inol
ogy
inid
entif
ying
and
desc
ribi
ngth
efu
nctio
nof
com
mon
phys
ical
com
pone
ntso
fcom
putin
gsy
stem
s(h
ardw
are)
.
Aco
mpu
ting
syste
mis
com
pose
dof
hard
ware
and
softw
are.
Har
dwar
eco
nsist
sofp
hysi
cal
com
pone
nts.
Stud
ents
shou
ldbe
able
toid
entif
yan
dde
scri
beth
efu
nctio
nof
exte
rnal
hard
ware
,su
chas
desk
top
com
pute
rs,l
apto
pco
mpu
ters
,tab
let
devi
ces,
mon
itors
,key
boar
ds,m
ice,
and
prin
ters
.Fo
rexa
mpl
e,stu
dent
scou
ldla
bela
ndm
atch
com
pone
ntsw
ithth
eird
escr
iptio
ns.
Prac
tice(
s):7
.2
Mod
elho
wco
mpu
ter
hard
war
ean
dso
ftwar
ew
ork
toge
ther
asa
syst
emto
acco
mpl
ishta
sks.
Both
hard
ware
and
softw
are
are
need
edto
acco
mpl
ish
task
swith
aco
mpu
ter.
Stud
ents
shou
ldre
cogn
ize
the
basi
cel
emen
tsof
aco
mpu
ters
yste
m,
incl
udin
gin
put,
outp
ut,p
roce
ssor
,sen
sors
,and
stora
ge.F
orex
ampl
e,stu
dent
scou
lddr
awa
mod
el(o
npa
pero
rdig
itally
),pr
ogra
man
anim
atio
nof
the
mod
el,o
rdes
crib
eit
thro
ugh
body
mov
emen
tsor
role
play
ing.
Prac
tice(
s):4
.4
Des
ign
proj
ects
that
com
bine
hard
war
ean
dso
ftwar
eco
mpo
nent
sto
colle
ctan
dus
eda
tato
perf
orm
afu
nctio
n.
Col
lect
ing
and
exch
angi
ngda
tain
volv
esin
put,
outp
ut,s
tora
ge,a
ndpr
oces
sing
.Stu
dent
ssho
uld
beab
leto
sele
ctth
eha
rdwa
rean
dso
ftwar
eco
mpo
nent
sfor
thei
rpro
ject
desi
gnsb
yco
nsid
erin
gfa
ctor
ssuc
has
func
tiona
lity,
cost,
size
,spe
ed,a
cces
sibi
lity,
and
aesth
etic
s.Fo
rex
ampl
e,stu
dent
scou
ldde
sign
am
obile
appl
icat
ion
that
incl
udes
acce
lero
met
er,G
PS,
and
spee
chre
cogn
ition
Prac
tice(
s):5
.1
Com
pare
leve
lsof
abst
ract
ion
and
inte
ract
ions
betw
een
appl
icat
ion
softw
are,
syst
emso
ftwar
e,an
dha
rdw
are
laye
rs.
Atits
mos
tbas
icle
vel,
aco
mpu
teri
scom
pose
dof
phys
ical
hard
ware
and
elec
tric
alim
puls
esw
ithm
ultip
lela
yers
ofso
ftwar
ebu
iltup
onth
eha
rdwa
re.S
yste
mso
ftwar
em
anag
esa
com
putin
gde
vice
’sre
sour
cess
oth
atso
ftwar
eca
nin
tera
ctw
ithha
rdwa
re.F
orex
ampl
e,te
xt-e
ditin
gso
ftwar
ein
tera
ctsw
ithth
eop
erat
ing
syste
mto
rece
ive
inpu
tfro
mth
eke
yboa
rd,c
onve
rtth
ein
putt
obi
tsfo
rsto
rage
,and
inte
rpre
tthe
bits
asre
adab
lete
xtto
disp
lay
onth
em
onito
r.St
uden
tssh
ould
beab
leto
reco
gniz
eth
atsy
stem
softw
are
isus
edon
man
ydi
ffere
ntty
peso
fdev
ices
,suc
has
smar
tTVs
,as
sisti
vede
vice
s,vi
rtua
lcom
pone
nts,
clou
dco
mpo
nent
s,an
ddr
ones
.For
exam
ple,
stude
ntsc
ould
expl
ain
the
prog
ress
ion
from
volta
geto
bina
rysi
gnal
tolo
gic
gate
sto
adde
rsan
dso
on.
Prac
tice(
s):4
.1
6
45
Troubleshooting
Des
crib
eba
sicha
rdw
are
and
softw
are
prob
lem
sus
ing
appr
opri
ate
term
inol
ogy.
Prob
lem
swith
com
putin
gsy
stem
shav
edi
ffere
ntca
uses
.Stu
dent
ssho
uld
beab
leto
com
mun
icat
ea
prob
lem
with
appr
opri
ate
term
inol
ogy,
alth
ough
they
dono
tnee
dto
unde
rsta
ndth
eca
uses
.For
exam
ple,
stude
ntsc
ould
notif
ya
teac
herw
hen
anap
plic
atio
nor
prog
ram
isno
twor
king
asex
pect
ed,
such
asw
hen
ade
vice
will
nott
urn
onor
ther
eis
noso
und.
Prac
tice(
s):6
.2,7
.2
Det
erm
ine
pote
ntia
lsol
utio
nsto
solv
esim
ple
hard
war
ean
dso
ftwar
epr
oble
ms
usin
gco
mm
ontr
oubl
esho
otin
gst
rate
gies
.
Alth
ough
com
putin
gsy
stem
smay
vary
,com
mon
troub
lesh
ootin
gstr
ateg
iesc
anbe
used
onal
lof
them
.Stu
dent
ssho
uld
beab
leto
iden
tify
solu
tions
toba
sic
prob
lem
s,su
chas
the
devi
ceno
tre
spon
ding
,no
powe
r,no
netw
ork
conn
ectio
n,ap
plic
atio
ncr
ashi
ng,n
oso
und,
orpa
sswo
rden
try
notw
orki
ng.F
orex
ampl
e,w
hen
erro
rsoc
cur,
stude
ntsc
ould
use
vari
ouss
trate
gies
,suc
has
rebo
otin
gth
ede
vice
,che
ckin
gfo
rpow
er,c
heck
ing
netw
ork
avai
labi
lity,
clos
ing
and
reop
enin
gan
appl
icat
ion,
mak
ing
sure
spea
kers
are
turn
edon
orhe
adph
ones
are
plug
ged
in,a
ndm
akin
gsu
reth
atth
eca
pslo
ckke
yis
noto
n,in
anat
tem
ptto
solv
eth
ese
prob
lem
s.
Prac
tice(
s):6
.2
Iden
tify
and
fixpr
oble
msw
ithco
mpu
ting
devi
ces
and
thei
rco
mpo
nent
susin
ga
syst
emat
ictr
oubl
esho
otin
gm
etho
dor
guid
e.
Sinc
ea
com
putin
gde
vice
may
inte
ract
with
inte
rcon
nect
edde
vice
swith
ina
syste
m,p
robl
ems
may
notb
edu
eto
the
spec
ific
com
putin
gde
vice
itsel
fbut
tode
vice
scon
nect
edto
it.St
uden
tssh
ould
beab
leto
use
astr
uctu
red
proc
ess–
sim
ilart
oth
ech
eckl
istus
edby
airc
raft
pilo
ts–
totro
uble
shoo
tpr
oble
msw
ithco
mpu
ting
syste
ms,
and
ensu
reth
atpo
tent
ials
olut
ions
are
noto
verlo
oked
.For
exam
ple,
stude
ntsc
ould
follo
wa
troub
lesh
ootin
gflo
wdi
agra
m,
mak
ech
ange
sto
softw
are
tose
eif
hard
ware
will
work
,che
ckco
nnec
tions
and
setti
ngs,
orch
ange
work
ing
com
pone
nts.
Prac
tice(
s):6
.2
Dev
elop
and
com
mun
icat
etr
oubl
esho
otin
gst
rate
gies
othe
rsca
nus
eto
iden
tify
and
fixer
rors
.
Trou
bles
hoot
ing
com
plex
prob
lem
sinv
olve
sth
eus
eof
mul
tiple
sour
cesw
hen
rese
arch
ing,
eval
uatin
g,an
dim
plem
entin
gpo
tent
ials
olut
ions
.Tr
oubl
esho
otin
gal
sore
lieso
nex
peri
ence
,suc
has
whe
npe
ople
reco
gniz
eth
ata
prob
lem
issi
mila
rto
one
they
have
seen
befo
reor
adap
tso
lutio
nsth
atha
vewo
rked
inth
epa
st.St
uden
tssh
ould
beab
leto
iden
tify
com
plex
troub
lesh
ootin
gstr
ateg
ies,
whi
chin
clud
ere
solv
ing
conn
ectiv
itypr
oble
ms,
adju
sting
syste
mco
nfigu
ratio
nsan
dse
tting
s,en
suri
ngha
rdwa
rean
dso
ftwar
eco
mpa
tibili
ty,a
ndtra
nsfe
rrin
gda
tafro
mon
ede
vice
toan
othe
r.Fo
rexa
mpl
e,stu
dent
scou
ldcr
eate
aflo
wcha
rt,
ajo
bai
dfo
rahe
lpde
skem
ploy
ee,o
ran
expe
rtsy
stem
(art
ifici
alin
telli
genc
e).
Prac
tice(
s):6
.2
Networks&theInternet
Des
crib
eth
eIn
tern
etis
apl
ace
tosh
are
and
find
info
rmat
ion.
The
Inte
rnet
trans
mits
info
rmat
ion
betw
een
com
pute
rs.S
tude
ntss
houl
dun
ders
tand
that
info
rmat
ion
acce
ssed
onth
eIn
tern
etca
nbe
store
dan
dsh
ared
onco
mpu
ters
arou
ndth
ewo
rld.S
tude
nts
shou
ldbe
able
toid
entif
yth
eva
lue
ofa
netw
ork
like
the
Inte
rnet
tofin
din
form
atio
nan
dac
cess
othe
rse
rvic
es.F
orex
ampl
e,stu
dent
scou
ldlo
okfo
rin
form
atio
nth
atco
mes
from
are
mot
elo
catio
n.
Prac
tice(
s):7
.2
Mod
elho
win
form
atio
nis
brok
endo
wn
into
smal
ler
piec
esof
data
,tra
nsm
itted
aspa
cket
sth
roug
hm
ultip
lede
vice
sove
rne
twor
ksan
dth
eIn
tern
et,a
ndre
asse
mbl
edat
the
dest
inat
ion.
Dat
aar
ese
ntan
dre
ceiv
edov
erph
ysic
alca
bles
and
wire
sorw
irele
sspa
ths.
They
are
brok
endo
wn
into
smal
lerp
iece
s(pa
cket
s)w
hich
are
sent
inde
pend
ently
and
reas
sem
bled
atth
ede
stina
tion.
Stud
ents
shou
ldbe
able
tore
cogn
ize
diffe
rent
type
sofn
etwo
rksf
orsp
ecifi
cpu
rpos
es(i.
e.th
esc
hool
’slo
caln
etwo
rkve
rsus
the
Inte
rnet
).Fo
rexa
mpl
e,stu
dent
scou
ldde
mon
strat
eth
eiru
nder
stand
ing
ofth
isflo
wof
data
bydr
awin
ga
mod
elof
the
way
pack
etsa
retra
nsm
itted
,pro
gram
min
gan
anim
atio
nto
show
how
pack
etsa
retra
nsm
itted
,ord
emon
strat
ing
this
thro
ugh
body
mov
emen
tsor
role
play
ing
activ
ities
.
Prac
tice(
s):4
.4
Mod
elth
ero
leof
prot
ocol
sin
tran
smitt
ing
data
acro
ssne
twor
ksan
dth
eIn
tern
et.
Prot
ocol
sare
rule
stha
tdefi
neho
wm
essa
ges
betw
een
com
pute
rsar
ese
nt.S
tude
ntss
houl
dun
ders
tand
the
purp
ose
ofpr
otoc
olsa
ndho
wth
eyen
able
secu
rean
der
rorle
ssco
mm
unic
atio
nas
well
asm
odel
prot
ocol
stha
tena
ble
the
faste
stpa
th,d
eal
with
mis
sing
info
rmat
ion,
and
deliv
erse
nsiti
veda
tase
cure
ly.F
orex
ampl
e,stu
dent
scou
ldde
vise
apl
anfo
rres
endi
nglo
stin
form
atio
nor
fori
nter
pret
ing
api
ctur
eth
atha
smis
sing
piec
es.
Prac
tice(
s):4
.4
Iden
tify
the
vari
ouse
lem
ents
ofa
netw
ork
and
desc
ribe
how
they
func
tion
and
inte
ract
totr
ansf
erin
form
atio
n.
Larg
e-sc
ale
coor
dina
tion
occu
rsam
ong
man
ydi
ffere
ntm
achi
nesa
cros
smul
tiple
path
seve
rytim
ea
web
page
isop
ened
oran
imag
eis
view
edon
line.
Stud
ents
shou
ldbe
able
toex
plai
nth
epa
thof
com
mun
icat
ion
from
thei
rde
vice
toa
webs
itean
dba
ckus
ing
the
netw
ork
topo
logy
(ser
vers
,rou
ters
,sw
itche
s,D
NS,
ISP,
etc.
).Fo
rexa
mpl
e,stu
dent
scou
ldus
eon
line
netw
ork
sim
ulat
orst
oex
peri
men
twith
thes
efa
ctor
s.ex
peri
men
twith
thes
efa
ctor
s.
Prac
tice(
s):7
.2
7
46
CY
BER
SEC
UR
ITY
Gra
desK
-2G
rade
s3-5
Gra
des6
-8G
rade
s9-1
2
Kee
plo
gin
and
pers
onal
info
rmat
ion
priv
ate,
and
log
offof
devi
cesa
ppro
pria
tely
.
Com
putin
gte
chno
logy
can
help
orhu
rtpe
ople
.St
uden
tssh
ould
reco
gniz
ean
dav
oid
harm
ful
beha
vior
s,su
chas
shar
ing
priv
ate
info
rmat
ion
and
stayi
nglo
gged
onpu
blic
devi
ces.
Fore
xam
ple,
stude
ntsc
ould
iden
tify
wha
tinf
orm
atio
nm
ight
bepr
ivat
eab
outa
phot
ogra
ph,a
ndde
mon
strat
eth
atth
eykn
owho
wto
log
outo
fany
acco
unts
they
use
forc
lass
room
work
.
Prac
tice(
s):8
.1
Des
crib
eth
eri
skso
fsha
ring
pers
onal
info
rmat
ion,
onw
ebsit
esor
othe
rpu
blic
foru
ms.
Secu
rity
atta
ckso
ften
start
with
info
rmat
ion
that
ispu
blic
lyav
aila
ble
onlin
e.St
uden
tssh
ould
beab
leto
reco
gniz
eth
atsh
arin
gin
form
atio
nab
outf
amily
mem
bers
and
frie
ndsc
anpu
tthe
mat
risk
.For
exam
ple,
stude
ntsc
ould
crea
tea
listo
fpot
entia
lri
skso
fsha
ring
pers
ona
info
rmat
ion
inre
allif
e,w
here
pers
onal
info
rmat
ion
incl
udes
iden
tifyi
ngin
form
atio
nsu
chas
birt
hdat
esas
well
asin
form
atio
nab
outc
urre
ntlo
catio
ns.
Prac
tice(
s):8
.2
Des
crib
etr
adeo
ffsbe
twee
nal
low
ing
info
rmat
ion
tobe
publ
ican
dke
epin
gin
form
atio
npr
ivat
ean
dse
cure
.
Shar
ing
info
rmat
ion
onlin
eca
nhe
lpes
tabl
ish,
mai
ntai
n,an
dstr
engt
hen
conn
ectio
nsbe
twee
npe
ople
.Ita
llows
artis
tsan
dde
sign
ers,
for
exam
ple,
todi
spla
yth
eirw
ork
and
reac
ha
broa
dau
dien
ce.P
eopl
em
ustd
ecid
ew
hich
info
rmat
ion
tosh
are
and
whi
chto
prot
ect.
Stud
ents
shou
ldre
cogn
ize
that
diffe
rent
situ
atio
nsre
quire
diffe
rent
safe
guar
dsan
dth
atno
teve
ryon
ew
illag
ree
onw
hatt
osh
are.
Fore
xam
ple,
stude
ntsc
ould
listt
hepr
osan
dco
nsof
shar
ing
pict
ures
and
info
rmat
ion
abou
tthe
irac
tiviti
eson
soci
alm
edia
ora
scho
oldi
rect
ory.
Prac
tice(
s):8
.2
Expl
ain
the
priv
acy
conc
erns
rela
ted
toth
eco
llect
ion
and
gene
ratio
nof
data
thro
ugh
auto
mat
edpr
oces
sest
hatm
ayno
tbe
evid
ent
tous
ers.
Dat
aca
nbe
colle
cted
and
aggr
egat
edac
ross
mill
ions
ofpe
ople
,eve
nw
hen
they
are
nota
ctiv
ely
enga
ging
with
orph
ysic
ally
near
the
data
colle
ctio
nde
vice
s.St
uden
tssh
ould
beab
leto
iden
tify
priv
acy
conc
erns
rela
ted
toth
eau
tom
ated
and
non-
evid
entc
olle
ctio
nan
dre
cogn
ize
that
alli
nfor
mat
ion
will
bepa
rtof
big
data
.For
exam
ple,
stude
ntsc
ould
anal
yze
the
bene
fits
and
cons
eque
nces
ofso
cial
med
iasi
tesm
inin
gan
acco
unte
ven
whe
nth
eus
eris
noto
nlin
e.O
ther
exam
ples
incl
ude
surv
eilla
nce
vide
ous
edin
asto
reto
track
custo
mer
sfor
secu
rity
,ori
nfor
mat
ion
abou
tpu
rcha
sing
habi
ts,o
rthe
mon
itori
ngof
road
traffi
cto
chan
gesi
gnal
sin
real
-tim
eto
impr
ove
road
effici
ency
with
outd
rive
rsbe
ing
awar
e.
Prac
tice(
s):8
.3
Risks No
K-2
stan
dard
.
Des
crib
ew
aysp
erso
nali
nfor
mat
ion
can
beob
tain
eddi
gita
lly.
Web
site
suse
vari
ousm
etho
dsto
gath
erin
form
atio
nab
outi
ndiv
idua
ls,f
amili
es,o
rfri
ends
.Inf
orm
atio
nm
aysu
rviv
eon
line
even
afte
rthe
owne
rdel
etes
it.St
uden
tssh
ould
beab
leto
reco
gniz
ewa
ysth
atda
taar
ega
ther
edon
line.
Fore
xam
ple,
stude
ntsc
ould
list
ways
webs
itesg
athe
rdat
asu
chas
byas
king
ques
tions
,sel
ling
prod
ucts
and
track
ing
peop
le’s
webs
itevi
sits
.
Prac
tice(
s):8
.2
Des
crib
eso
cial
engi
neer
ing
atta
cksa
ndth
epo
tent
ialr
isksa
ssoc
iate
dw
ithth
em.
Soci
alen
gine
erin
gis
base
don
"tri
ckin
g"pe
ople
into
reve
alin
gse
nsiti
vein
form
atio
n.It
can
beth
wart
edby
bein
gwa
ryof
atta
cks,
such
asph
ishi
ngan
dsp
oofin
g.St
uden
tssh
ould
beab
leto
reco
gniz
eth
atat
tack
scan
com
eth
roug
hlin
ksin
emai
l,ad
son
webs
ites,
and
ques
tions
from
othe
rpeo
ple.
Fore
xam
ple,
stude
ntsc
ould
desc
ribe
apo
tent
ialp
hish
ing
atta
ck.
Prac
tice(
s):8
.2
Ana
lyze
anex
istin
gor
prop
osed
appl
icat
ion
toid
entif
yth
epo
tent
ialw
aysi
tcou
ldbe
used
toob
tain
sens
itive
info
rmat
ion.
Appl
icat
ions
gath
eran
dsto
rein
form
atio
nab
outu
sers
and
thei
rbeh
avio
rs.T
heri
sksa
nap
plic
atio
npo
ses
depe
ndso
nw
hati
nfor
mat
ion
itga
ther
s,w
here
that
info
rmat
ion
issto
red,
and
who
can
acce
ssth
atin
form
atio
n.Ri
sksm
ayco
ncer
nre
puta
tiona
l,fin
anci
al,o
rleg
alis
sues
.Stu
dent
ssho
uld
beab
leto
diffe
rent
iate
betw
een
met
hods
and
devi
cesf
orco
llect
ing
data
byth
eam
ount
ofsto
rage
requ
ired,
leve
lofd
etai
lcol
lect
ed,a
ndsa
mpl
ing
rate
s.
Prac
tice(
s):3
.1,8
.2,8
.3
8
47Risks
No
K-2
stan
dard
.
Des
crib
eth
eri
skso
foth
ersu
sing
one’
spe
rson
alre
sour
ceso
rde
vice
s.
Whe
nac
cess
toa
smar
tpho
ne,n
etwo
rk,o
racc
ount
issh
ared
,inf
orm
atio
nab
outt
he"o
wne
r"ca
nbe
expo
sed.
Stud
ents
shou
ldbe
able
todi
scus
spot
entia
lco
nseq
uenc
esto
givi
ngfr
iend
sand
acqu
aint
ance
sac
cess
toth
eird
evic
esor
acco
unts
.For
exam
ple,
stude
ntsc
ould
listi
napp
ropr
iate
actio
nsth
atso
meo
neco
uld
take
ifth
eyha
dac
cess
toa
digi
talf
olde
rcon
tain
ing
anot
hers
tude
nt’s
clas
swor
k.
Prac
tice(
s):8
.1,8
.2
Des
crib
eri
skso
fusin
gfr
eean
dop
ense
rvic
es.
Free
serv
ices
ofte
nca
rry
less
secu
rity
than
paid
serv
ices
.Stu
dent
ssho
uld
beab
leto
iden
tify
situ
atio
nsin
whi
chth
eym
ight
beus
ing
free
serv
ices
and
the
corr
espo
ndin
gri
sks.
Exam
ples
incl
ude
usin
gth
eri
skof
info
rmat
ion
thef
tove
rop
enne
twor
ksin
resta
uran
ts,a
ndth
eri
skof
mal
ware
insta
llatio
nfro
msi
tesf
orstr
eam
ing
licen
sed
ente
rtai
nmen
t(e.
g.,m
ovie
sors
port
ing
even
ts).
Addi
tiona
lly,c
erta
insm
artp
hone
orla
ptop
appl
icat
ions
may
requ
estp
erm
issi
onst
hat
may
com
prom
ise
pers
onal
info
rmat
ion.
For
exam
ple,
stude
ntsc
ould
iden
tify
cert
ain
phon
eor
lapt
opap
plic
atio
nsth
atre
ques
tper
mis
sion
sth
atm
ayco
mpr
omis
epe
rson
alin
form
atio
n.
Prac
tice(
s):8
.2
Expl
ain
how
the
digi
tals
ecur
ityof
anor
gani
zatio
nm
aybe
affec
ted
byth
eac
tions
ofits
empl
oyee
s.
Org
aniz
atio
nssto
rese
nsiti
ve,c
onfid
entia
land
prop
riet
ary
info
rmat
ion
inth
eirc
ompu
ting
syste
ms.
Empl
oyee
shav
ea
resp
onsi
bilit
yto
help
prot
ectt
hese
syste
msa
ndth
eird
ata.
Stud
ents
shou
ldun
ders
tand
how
anem
ploy
eeis
anin
tegr
alpa
rtof
anor
gani
zatio
n’sd
igita
lsec
urity
and
how
anin
divi
dual
’sdi
gita
lina
ttent
iven
essc
anha
vese
riou
sco
nseq
uenc
es.F
orex
ampl
e,stu
dent
scou
ldid
entif
yan
dde
scri
bece
rtai
nco
ntex
tsw
ithin
indu
stry,
mili
tary
,hea
lthca
re,e
nerg
y,an
dgo
vern
men
tor
gani
zatio
nsw
here
cons
eque
nces
woul
dbe
seri
ous.
Prac
tice(
s):8
.1
Safeguards
Rec
ogni
zeba
sicdi
gita
lsec
urity
feat
ures
.
Dev
ices
and
softw
are
use
seve
ralm
echa
nism
sto
safe
guar
dda
ta.F
orex
ampl
e,de
vice
shav
epa
ssco
des.
Softw
are
tool
shav
epa
sswo
rd-p
rote
cted
acco
unts
soth
aton
eus
erca
nnot
see
anot
heru
ser’
sda
ta.W
ebsi
tesd
ispl
aya
lock
icon
whe
nth
eyar
eus
ing
cert
ain
com
mon
secu
rity
mea
sure
s.St
uden
tssh
ould
beab
leto
reco
gniz
ew
heth
era
devi
ceor
softw
are
tool
offer
sbas
icda
tapr
otec
tion
base
don
pass
word
s,ac
coun
ts,a
ndpa
dloc
kic
ons.
For
exam
ple,
stude
ntsc
ould
crea
tepa
sswo
rdst
hat
incl
ude
num
bers
,upp
er&
lowe
rcas
ele
tters
&sp
ecia
lsym
bols
.
Prac
tice(
s):8
.1
Expl
ain
indi
vidu
alac
tions
that
prot
ectp
erso
nal
elec
tron
icin
form
atio
nan
dde
vice
s.
Just
aswe
prot
ecto
urpe
rson
alpr
oper
tyoffl
ine,
weal
sone
edto
prot
ecto
urde
vice
sand
the
info
rmat
ion
store
don
them
.Inf
orm
atio
nca
nbe
prot
ecte
dus
ing
vari
ouss
ecur
itym
easu
res.
Thes
em
easu
resc
anbe
phys
ical
and/
ordi
gita
l.D
igita
lpr
otec
tion
shou
ldbe
base
don
stron
gpe
rson
alau
then
ticat
ion
(e.g
.,pa
sswo
rds)
.Stu
dent
ssho
uld
beab
leto
iden
tify
thes
em
easu
resa
ndde
scri
beho
wto
use
them
.For
exam
ple,
stude
ntsc
ould
desc
ribe
wha
tmak
esa
pass
word
stron
gan
dho
wto
safe
guar
dth
eirp
assw
ords
,des
crib
ew
hata
nti-
viru
ssof
twar
edo
esan
dho
wto
keep
itup
date
d,an
dw
heth
erva
riou
sapp
licat
ions
that
they
use
back
upda
taau
tom
atic
ally
inth
ecl
oud.
Prac
tice(
s):8
.1
Expl
ain
phys
ical
and
digi
tals
ecur
itym
easu
res
that
prot
ecte
lect
roni
cin
form
atio
n.
Info
rmat
ion
that
issto
red
onlin
eis
vuln
erab
leto
unwa
nted
acce
ss.P
hysi
cals
ecur
itym
easu
rest
opr
otec
tdat
ain
clud
eke
epin
gpa
sswo
rdsh
idde
n,lo
ckin
gdo
ors,
mak
ing
back
upco
pies
onex
tern
alsto
rage
devi
ces,
and
eras
ing
asto
rage
devi
cebe
fore
itis
reus
ed.D
igita
lsec
urity
mea
sure
sinc
lude
secu
rero
uter
adm
inpa
sswo
rds,
usin
gtw
o-fa
ctor
auth
entic
atio
n,fir
ewal
lsth
atlim
itac
cess
topr
ivat
ene
twor
ks,i
nsta
lling
softw
are
upda
tes,
usin
g(a
ndno
tdis
ablin
g)m
alwa
rede
tect
ors,
and
the
use
ofa
prot
ocol
such
asH
TTPS
toen
sure
secu
reda
tatra
nsm
issi
on.S
tude
ntss
houl
dbe
able
todi
ffere
ntia
tebe
twee
nph
ysic
alan
ddi
gita
lsec
urity
mea
sure
s.Fo
rexa
mpl
e,stu
dent
scou
ldcr
eate
alis
tofs
ecur
itym
easu
resf
orth
esc
hool
and
disc
ussw
ithth
eon
site
ITpr
ofes
sion
al.
Prac
tice(
s):8
.2,8
.3
Rec
omm
end
secu
rity
mea
sure
sto
addr
essv
ario
ussc
enar
iosb
ased
onfa
ctor
ssuc
heffi
cien
cy,
feas
ibili
ty,a
ndet
hica
lim
pact
s.
Secu
rity
mea
sure
smay
incl
ude
phys
ical
secu
rity
toke
ns,t
wo-fa
ctor
auth
entic
atio
n,an
dbi
omet
ric
veri
ficat
ion.
Pote
ntia
lsec
urity
prob
lem
s,su
chas
deni
al-o
f-ser
vice
atta
cks,
rans
omwa
re,v
irus
es,
worm
s,sp
ywar
e,an
dph
ishi
ng,e
xem
plify
why
sens
itive
data
shou
ldbe
secu
rely
store
dan
dtra
nsm
itted
.The
timel
yan
dre
liabl
eac
cess
toda
taan
din
form
atio
nse
rvic
esby
auth
oriz
edus
ers,
refe
rred
toas
avai
labi
lity,
isen
sure
dth
roug
had
equa
teba
ndw
idth
,bac
kups
,and
othe
rmea
sure
s.St
uden
tssh
ould
syste
mat
ical
lyev
alua
tean
dco
ntin
ually
re-a
sses
sthe
feas
ibili
tyof
usin
gco
mpu
tatio
nalt
ools
toso
lve
give
nse
curi
typr
oble
mso
rsub
prob
lem
s.Fo
rexa
mpl
e,stu
dent
sco
uld
use
aco
st-be
nefit
anal
ysis
toev
alua
te(e
vent
ually
incl
udin
gm
ore
fact
orsi
nth
eir
eval
uatio
ns)s
uch
asho
weffi
cien
cyaff
ects
feas
ibili
tyor
whe
ther
apr
opos
edap
proa
chra
ises
ethi
cal
conc
erns
.
Prac
tice(
s):8
.3
9
48
Safeguards
No
K-2
stan
dard
No
3-5
stan
dard
.
Dem
onst
rate
how
mul
tiple
met
hods
ofen
cryp
tion
prov
ide
secu
retr
ansm
issio
nof
info
rmat
ion.
Encr
yptio
nca
nbe
assi
mpl
eas
lette
rsub
stitu
tion
oras
com
plic
ated
asm
oder
nm
etho
dsus
edto
secu
rene
twor
ksan
dth
eIn
tern
et.S
tude
ntss
houl
den
code
and
deco
dem
essa
gesu
sing
ava
riet
yof
encr
yptio
nm
etho
ds,a
ndsh
ould
unde
rsta
ndth
edi
ffere
ntle
vels
ofco
mpl
exity
used
tohi
deor
secu
rein
form
atio
n.Fo
rexa
mpl
e,stu
dent
scou
ldse
cure
mes
sage
susi
ngm
etho
dssu
chas
Cae
sarc
iphe
rsor
stega
nogr
aphy
(i.e.
,hid
ing
mes
sage
sins
ide
api
ctur
eor
othe
rdat
a).T
hey
can
also
mod
elm
ore
com
plic
ated
met
hods
,suc
has
publ
icke
yen
cryp
tion,
thro
ugh
unpl
ugge
dac
tiviti
es.
Prac
tice(
s):8
.2
Expl
ain
trad
eoffs
whe
nse
lect
ing
and
impl
emen
ting
cybe
rsec
urity
reco
mm
enda
tions
.
Netw
ork
secu
rity
depe
ndso
na
com
bina
tion
ofha
rdwa
re,s
oftw
are,
and
prac
tices
that
cont
rola
cces
sto
data
and
syste
ms.
The
need
sofu
sers
and
the
sens
itivi
tyof
data
dete
rmin
eth
ele
velo
fsec
urity
impl
emen
ted.
Ever
yse
curi
tym
easu
rein
volv
estra
deoff
sbet
ween
the
acce
ssib
ility
and
secu
rity
ofth
esy
stem
.Stu
dent
ssho
uld
beab
leto
desc
ribe
,ju
stify
,and
docu
men
tcho
ices
they
mak
eus
ing
term
inol
ogy
appr
opri
ate
fort
hein
tend
edau
dien
cean
dpu
rpos
e.Fo
rexa
mpl
e,stu
dent
scou
ldde
bate
issu
esfro
mth
epe
rspe
ctiv
eof
dive
rse
audi
ence
s,in
clud
ing
indi
vidu
als,
corp
orat
ions
,pri
vacy
advo
cate
s,se
curi
tyex
pert
s,an
dgo
vern
men
t.
Prac
tice(
s):8
.3
Response
Iden
tify
situa
tions
appl
icat
ions
and
devi
cest
hat
shou
ldbe
repo
rted
toa
resp
onsib
lead
ult.
Losi
nga
devi
ceor
acci
dent
ally
shar
ing
apa
sswo
rdex
pose
speo
ple
and
thei
racc
ount
sto
info
rmat
ion
thef
t.St
uden
tssh
ould
unde
rsta
ndw
hich
kind
sofl
osse
sto
repo
rtto
apa
rent
,tea
cher
,or
othe
rtru
sted
adul
t.(I
nstr
uctio
nssh
ould
follo
wan
yap
prop
riat
edi
stric
tors
choo
lpol
icie
stha
tare
inte
nded
fory
oung
stude
nts.)
Prac
tice(
s):8
.1
Iden
tify
and
desc
ribe
unus
uald
ata
orbe
havi
ors
ofap
plic
atio
nsan
dde
vice
stha
tsho
uld
bere
port
edto
are
spon
sible
adul
t.
Dev
ices
orap
plic
atio
nsca
nbe
have
inun
expe
cted
ways
whe
na
secu
rity
inci
dent
occu
rs.A
nun
usua
lsc
reen
mig
htop
enas
king
fora
pass
word
,pho
nenu
mbe
r,or
perm
issi
onto
insta
llan
othe
rpro
gram
.Em
aila
ttach
men
tsca
nco
ntai
nm
alic
ious
softw
are.
Stud
ents
shou
ldbe
able
tore
cogn
ize
sim
ple
form
sof
unus
ualb
ehav
iori
nco
mm
onap
plic
atio
ns,
incl
udin
gda
taor
links
that
mig
htco
nstit
ute
ari
sk,a
ndun
ders
tand
whi
chbe
havi
orst
ore
port
toa
pare
nt,t
each
er,o
roth
ertr
uste
dad
ult.
(Ins
truc
tions
shou
ldfo
llow
any
appr
opri
ate
distr
ict
orsc
hool
polic
iest
hata
rein
tend
edfo
ryou
ngstu
dent
s.)Fo
rexa
mpl
e,stu
dent
scou
ldre
view
sam
ple
emai
lmes
sage
sand
iden
tify
feat
ures
ofea
chth
atsu
gges
tsus
pici
ousb
ehav
ior.
Prac
tice(
s):8
.1
Des
crib
ew
hich
actio
nsto
take
and
nott
ota
kew
hen
anap
plic
atio
nor
devi
cere
port
sapr
oble
mor
beha
vesu
nexp
ecte
dly.
Use
rsca
nta
kede
fens
ive
actio
nsw
hen
devi
ces,
appl
icat
ions
,oro
nlin
eac
quai
ntan
cesb
ehav
ein
unex
pect
edwa
ys.D
isco
nnec
ting
ade
vice
from
ane
twor
k,ch
angi
ngpa
sswo
rds,
and
rem
ovin
gor
bloc
king
peop
leon
soci
alm
edia
appl
icat
ions
are
each
appr
opri
ate
inso
me
situ
atio
ns.S
tude
nts
shou
ldbe
able
tore
cogn
ize
basi
csi
tuat
ions
inw
hich
tota
keor
nott
ake
vari
ousd
efen
sive
actio
ns.F
orex
ampl
e,stu
dent
scou
ldde
scri
bebe
nefit
sand
risk
sto
each
actio
n(s
uch
asth
elo
ssof
fore
nsic
data
ifa
devi
ceis
com
plet
ely
turn
edoff
,ort
hatr
eque
ststo
chan
gepa
sswo
rdss
houl
don
lybe
follo
wed
whe
nth
eyco
me
from
anap
prop
riat
eau
thor
ity).
Stud
ents
shou
ldbe
able
tode
scri
bebo
thba
sic
form
sofs
ocia
leng
inee
ring
atta
cksa
ndho
wto
deci
dew
hich
links
ordo
cum
ents
toop
en.
Prac
tice(
s):8
.2
Des
crib
eth
eap
prop
riat
eac
tions
tota
kein
resp
onse
tode
tect
edse
curi
tybr
each
es.
Empl
oyee
smay
obse
rve
activ
itysu
chas
mal
ware
scan
s,m
odifi
catio
nsto
docu
men
ts,o
runu
sual
acce
ssto
docu
men
tsby
othe
rem
ploy
eesw
hen
anor
gani
zatio
nsu
ffers
ase
curi
tybr
each
.Bre
ache
sal
sooc
curo
na
pers
onal
leve
lwith
cred
itca
rds
orso
cial
med
iaac
coun
ts.S
tude
ntss
houl
dbe
able
tore
cogn
ize
diffe
rent
kind
sofb
reac
hest
hatt
hey
mig
htde
tect
asem
ploy
eeso
rin
thei
rper
sona
lliv
es.F
orex
ampl
e,stu
dent
scou
lddi
scus
ssam
ple
orga
niza
tiona
lres
pons
epr
otoc
ols,
sam
ple
state
and
fede
ralp
olic
ieso
nda
talo
ssan
din
cide
nce
resp
onse
,and
expl
ain
thei
rres
pons
ibili
tiest
oor
gani
zatio
nsin
resp
ondi
ngto
brea
ches
.In
term
sof
pers
onal
info
rmat
ion,
stude
ntsc
ould
disc
uss
wha
tsor
tsof
info
rmat
ion
indi
vidu
alss
houl
dga
ther
inad
vanc
eas
evid
ence
ofda
tath
eft,
loss
,or
fabr
icat
ion
and
iden
tify
the
appr
opri
ate
peop
le(s
uch
asba
nks,
the
polic
e,or
acqu
aint
ance
s)to
who
mto
repo
rtin
cide
nts.
Prac
tice(
s):8
.3
10
49
DATA
&A
NA
LYSI
SG
rade
sK-2
Gra
des3
-5G
rade
s6-8
Gra
des9
-12
Collection,Visualization,&Transformation
Col
lect
and
pres
entt
hesa
me
data
inm
ultip
lefo
rmat
s.
The
colle
ctio
nan
dus
eof
data
abou
tthe
world
arou
ndus
isa
rout
ine
part
oflif
ean
din
fluen
ces
how
peop
leliv
e.D
iffer
entp
rese
ntat
ions
ofda
tahi
ghlig
htdi
ffere
ntas
pect
soft
heda
ta.S
tude
nts
shou
ldbe
able
toco
llect
and
tally
sim
ple
data
,th
enpr
esen
titt
woor
mor
ewa
ysus
ing
diffe
rent
repr
esen
tatio
ns.F
orex
ampl
e,stu
dent
scou
ldco
untt
henu
mbe
rofb
lock
sby
colo
r,or
surv
eycl
assm
ates
onth
eirf
avor
itefo
ods,
then
pres
ent
thes
eda
taw
itha
barg
raph
and
pict
ogra
ph.
Prac
tice(
s):4
.4,7
.2
Org
aniz
ean
dpr
esen
tcol
lect
edda
tato
high
light
rela
tions
hips
and
supp
orta
clai
m.
Raw
data
are
sets
ofob
serv
atio
nsth
atha
velit
tlem
eani
ngon
thei
row
n.D
ata
are
ofte
nso
rted
orgr
oupe
dto
focu
son
part
icul
arqu
estio
ns.
Org
aniz
ing
data
can
mak
ein
terp
retin
gan
dco
mm
unic
atin
gth
emto
othe
rsea
sier
.Stu
dent
ssh
ould
sort
the
sam
eda
tase
tin
mul
tiple
ways
,pr
esen
ting
each
inan
appr
opri
ate
form
at.F
orex
ampl
e,a
data
seto
fspo
rtst
eam
scou
ldbe
sort
edby
win
s,po
ints
scor
ed,o
rpoi
ntsa
llowe
d,w
itha
barg
raph
pres
ente
dfo
reac
hso
rtin
g.
Prac
tice(
s):4
.1,7
.1
Col
lect
data
usin
gco
mpu
tatio
nalt
ools
oron
line
sour
cesa
ndtr
ansf
orm
the
data
tom
ake
itm
ore
usef
ulan
dre
liabl
e.
Fora
naly
sist
obe
relia
ble,
data
need
tobe
ina
cons
isten
tfor
mat
,fre
eof
criti
cale
rror
sorn
oise
,and
orga
nize
dto
mak
eke
ytre
ndsv
isib
le.S
tude
ntss
houl
dbe
able
toco
llect
data
from
devi
ceso
ronl
ine
sour
ces
and
iden
tify
nois
e,er
rors
,ori
ncon
siste
ncie
stha
tco
uld
exist
inth
ese
data
.For
exam
ple,
anau
dio
sens
orm
eant
tore
cord
appl
ause
volu
me
may
colle
ctex
trane
ouss
ound
duri
ngth
efir
stfe
wse
cond
sof
posi
tioni
ngth
ese
nsor
,and
thes
epa
rtso
frec
orde
dso
und
data
shou
ldbe
excl
uded
inan
alys
is.S
tude
nts
coul
ddo
wnl
oad
asp
read
shee
tcon
tain
ing
teac
her-
craf
ted
data
setf
rom
awe
bsite
and
chec
kfo
rm
issi
ngor
dupl
icat
een
trie
s.
Prac
tice(
s):6
.2,6
.3
Sele
ctap
prop
riat
eda
ta-c
olle
ctio
nto
olsa
ndpr
esen
tatio
nte
chni
ques
for
diffe
rent
type
sof
data
.
Diff
eren
tkin
dsof
data
are
best
colle
cted
and
pres
ente
dus
ing
diffe
rent
met
hods
and
form
ats.
Stud
ents
shou
ldbe
able
todi
sting
uish
betw
een
disc
rete
and
dyna
mic
even
ts,c
hoos
eap
prop
riat
em
etho
dsor
tool
sfor
gath
erin
gea
chty
peof
data
,an
dch
oose
appr
opri
ate
repr
esen
tatio
nsfo
rag
greg
atin
gor
pres
entin
gsu
chda
ta.F
orex
ampl
e,a
tally
coun
terc
ould
beus
edto
com
pare
the
num
bero
fpeo
ple
atte
ndin
ga
conc
erto
ndi
ffere
ntda
ys,w
ithda
tapr
esen
ted
ina
barc
hart
,whe
reas
alig
htse
nsor
coul
dbe
used
tode
tect
chan
gein
illum
inat
ion
duri
ngth
eco
urse
ofa
clou
dyve
rsus
sunn
yda
y,w
ithda
tapl
otte
das
two
trend
sal
ong
the
sam
etim
eax
is.
Prac
tice(
s):4
.1,7
.2
InferenceandModels
Iden
tify
and
desc
ribe
patte
rnsi
nda
ta,
pres
enta
tions
such
asch
arts
orgr
aphs
,to
mak
epr
edic
tions
Dat
aca
nbe
used
tom
ake
infe
renc
esor
pred
ictio
nsab
outt
hewo
rld.S
tude
ntss
houl
dbe
able
toin
terp
rets
impl
egr
aphs
orch
arts
.Fo
rexa
mpl
e,stu
dent
scou
ldan
alyz
ea
char
tre
pres
entin
gw
hatc
lass
mat
esat
efo
rbre
akfa
stfo
rse
vera
lday
s,th
enm
ake
apr
edic
tion
abou
thow
man
ystu
dent
will
eata
part
icul
arbr
eakf
ast
onan
othe
rday
.
Prac
tice(
s):4
.1
Use
data
tohi
ghlig
htor
prop
ose
caus
e-an
d-eff
ect
rela
tions
hips
,pre
dict
outc
omes
,or
com
mun
icat
ean
idea
.
The
accu
racy
ofda
taan
alys
isis
rela
ted
toho
wre
alist
ical
lyda
taar
ere
pres
ente
d.In
fere
nces
orpr
edic
tions
base
don
data
are
less
likel
yto
beac
cura
teif
data
are
nots
uffici
ent,
orif
the
data
are
inco
rrec
tin
som
ewa
y.St
uden
tssh
ould
beab
leto
refe
rto
data
whe
nfo
rmin
ghy
poth
eses
and
com
mun
icat
ing
anid
ea.T
hey
shou
ldre
cogn
ize
whe
nda
taar
ein
suffi
cien
tqua
ntity
,orr
elev
ant.
Fore
xam
ple,
stude
ntsc
ould
reco
rdth
ete
mpe
ratu
reat
noon
each
day
asa
basi
sto
show
that
tem
pera
ture
sar
ehi
gher
ince
rtai
nm
onth
soft
heye
ar,b
utth
ese
data
woul
dbe
insu
ffici
entm
easu
rem
ents
ifon
lyta
ken
once
am
onth
.Dat
aab
outp
reci
pita
tion
woul
dno
tbe
rele
vant
toth
ispr
edic
tion
abou
ttem
pera
ture
.
Prac
tice(
s):5
.1,7
.1
Cre
ate
and
refin
eco
mpu
tatio
nalm
odel
sbas
edon
gene
rate
dor
gath
ered
data
.
Aco
mpu
tatio
nalm
odel
may
bea
prog
ram
med
sim
ulat
ion
ofev
ents
ora
mat
hem
atic
alre
pres
enta
tion
ofho
wdi
ffere
ntob
ject
srel
ate.
Stud
ents
shou
ldbe
able
tocr
eate
and
refin
ea
mod
elby
cons
ider
ing
whi
chda
tapo
ints
are
rele
vant
,how
data
poin
tsre
late
toea
chot
her,
and
ifth
eda
taar
eac
cura
te.M
odel
sca
nbe
crea
ted
insi
mul
atio
nto
ols,
spre
adsh
eets
,or
onpa
per.
Fore
xam
ple,
stude
ntsm
aym
ake
apr
edic
tion
abou
thow
fara
ball
will
trave
lbas
edon
ata
ble
ofda
tare
late
dto
the
heig
htan
dan
gle
ofa
track
.The
stude
nts
coul
dth
ente
stan
dre
fine
thei
rmod
elby
com
pari
ngpr
edic
ted
vers
usac
tual
resu
ltsan
dco
nsid
erin
gw
heth
erot
herf
acto
rsar
ere
leva
nt(e
.g.,
size
and
mas
soft
heba
ll).
Prac
tice(
s):4
.4,5
.3,6
.1
Cre
ate
com
puta
tiona
lmod
elst
hatr
epre
sent
the
rela
tions
hips
amon
gdi
ffere
ntel
emen
tsof
data
colle
cted
from
aph
enom
enon
orpr
oces
s.
Com
puta
tiona
lmod
elsm
ake
pred
ictio
nsab
out
proc
esse
sorp
heno
men
aba
sed
onse
lect
edda
taan
dfe
atur
es.T
heam
ount
,qua
lity,
and
dive
rsity
ofda
taan
dth
efe
atur
esch
osen
can
affec
tthe
qual
ityof
am
odel
and
ther
efor
eou
rabi
lity
toun
ders
tand
asy
stem
.Pre
dict
ions
orin
fere
nces
are
teste
dto
valid
ate
mod
els.
Stud
ents
shou
ldm
odel
phen
omen
aas
syste
ms,
with
rule
sgo
vern
ing
the
inte
ract
ions
with
inth
esy
stem
,th
enan
alyz
ean
dev
alua
teth
ese
mod
elsa
gain
stre
al-w
orld
obse
rvat
ions
.For
exam
ple,
stude
nts
coul
dcr
eate
asi
mpl
epr
oduc
er–c
onsu
mer
ecos
yste
mm
odel
,ora
traffi
c-pa
ttern
pred
ictio
nm
odel
,usi
nga
prog
ram
min
gor
sim
ulat
ion
tool
.
Prac
tice(
s):4
.4,5
.1,5
.2
11
50
No
K-2
stan
dard
.yyy
yyyy
yyyy
yyyy
yyyy
yyyy
yyy
No
3-5
stan
dard
.yyy
yyyy
yyyy
yyyy
yyyy
yyyy
yyyy
y
Disc
ussp
oten
tialv
isibl
ebi
ases
that
coul
dex
istin
ada
tase
tand
how
thes
ebi
ases
coul
daff
ect
anal
ysis
conc
lusio
ns.
Dat
aset
smay
notb
ere
pres
enta
tive
ofth
epo
pula
tion
they
are
bein
gus
edto
study
.Stu
dent
ssho
uld
iden
tify
pote
ntia
lbia
sesi
nth
eco
mpo
nent
sofa
data
seta
nddi
scus
swhe
ther
thos
ebi
ases
coul
dad
vers
ely
affec
tsp
ecifi
cco
nclu
sion
sdra
wn
from
the
data
set.
For
exam
ple,
stude
ntsc
ould
anal
yze
surv
eyda
tato
see
ifke
ypo
pula
tions
are
unde
rrep
rese
nted
.
Prac
tice(
s):1
.3,7
.1
Disc
ussp
oten
tialh
idde
nbi
ases
that
coul
dbe
intr
oduc
edw
hile
colle
ctin
ga
data
seta
ndho
wth
ese
bias
esco
uld
affec
tana
lysis
conc
lusio
ns.
Dat
aset
smay
have
hidd
enbi
ases
base
don
how
they
were
colle
cted
.Stu
dent
ssho
uld
iden
tify
pote
ntia
lbia
sest
hata
reno
tdire
ctly
refle
cted
inth
eda
tase
t,bu
ttha
tcou
ldex
istba
sed
onho
wth
eda
tawe
reco
llect
ed.S
tude
ntss
houl
dal
sodi
scus
sw
heth
erth
ose
bias
esco
uld
adve
rsel
yaff
ects
peci
ficco
nclu
sion
sdra
wn
from
the
data
set.
Fore
xam
ple,
stude
ntsc
ould
anal
yze
data
abou
tpub
licwo
rks
fund
ing
foro
nene
ighb
orho
odan
ddi
scus
swhe
ther
the
anal
ysis
shou
ldpr
edic
tfun
ding
fora
noth
erne
ighb
orho
odin
the
sam
eci
ty.
Prac
tice:
1.1,
1.3,
7.1
Inferences&Models No
K-2
stan
dard
.N
o3-
5st
anda
rd.
No
6-8
stan
dard
.
Eval
uate
the
abili
tyof
mod
elsa
ndsim
ulat
ions
tote
stan
dsu
ppor
tthe
refin
emen
tofh
ypot
hese
s.
Mod
elsm
ustb
eev
alua
ted
tode
term
ine
whe
ther
they
are
appr
opri
ate
and
relia
ble.
Am
odel
may
omit
info
rmat
ion
that
ises
sent
ialt
oan
swer
ing
aqu
estio
n,or
yiel
dre
sults
that
seem
inco
nsist
ent
with
expe
ctat
ions
orda
tafro
mot
hers
ourc
es.
Stud
ents
shou
ldle
arn
how
tote
stm
odel
son
data
forw
hich
resu
ltsar
ekn
own,
artic
ulat
equ
estio
nsth
eyco
uld
ask
tova
lidat
ea
mod
el,g
ive
deta
iled
expl
anat
ions
ofw
here
am
odel
mig
htbe
inac
cura
te,
and
mak
esu
gges
tions
onho
wto
mod
ifyex
istin
gm
odel
sto
impr
ove
thei
rrel
iabi
lity.
Fore
xam
ple,
stude
ntsc
ould
anal
yze
the
accu
racy
ofa
weat
her
mod
elif
pred
ictio
nsof
patte
rnso
frai
nar
ein
cons
isten
twith
rece
nthi
stori
cald
ata.
Inco
nsist
enci
esw
ithre
alda
taco
uld
beus
edto
mod
ifyth
em
odel
,orr
efine
ahy
poth
esis
abou
tw
hyra
inda
tais
inco
nsist
entw
ithre
cent
histo
rica
lda
ta.
Prac
tice(
s):4
.4,6
.3
12
51
Iden
tify
data
asin
form
atio
nth
atis
stor
edby
softw
are.
Alli
nfor
mat
ion
store
dan
dpr
oces
sed
bya
com
putin
gde
vice
isre
ferr
edto
asda
ta.D
ata
can
exist
indi
ffere
ntfo
rms,
such
asim
ages
,tex
tdo
cum
ents
,aud
iofil
es,v
ideo
files
,sof
twar
epr
ogra
ms,
orap
plic
atio
ns.S
tori
ngda
tadi
gita
llym
akes
itea
sier
tocr
eate
and
shar
eco
pies
ofth
eda
ta.S
tude
ntss
houl
dbe
able
toid
entif
yw
hat
kind
sofi
nfor
mat
ion
issto
red
byva
riou
sso
ftwar
eto
olst
hatt
hey
use
and
give
exam
ples
ofw
hen
they
mig
htwa
ntto
shar
eda
taw
ithot
hers
.For
exam
ple,
ado
cum
ents
tore
stex
tand
pict
ures
,whi
lesh
arin
gth
edo
cum
entl
ets
teac
hers
mar
kco
mm
ents
onit.
Prac
tice(
s):4
.2
Stor
e,co
py,s
earc
h,re
trie
ve,m
odify
,and
dele
teda
taus
ing
aco
mpu
ting
devi
ce.
Dat
aca
nbe
store
d,co
pied
,sea
rche
d,re
trie
ved,
mod
ified
,and
dele
ted,
and
can
besto
red
eith
eron
loca
lorr
emot
ede
vice
s.St
uden
tssh
ould
beab
leto
perf
orm
each
ofth
ese
oper
atio
nsw
ithin
the
rele
vant
softw
are
appl
icat
ions
that
they
use,
and
unde
rsta
ndw
hen
adi
gita
ltoo
lism
anip
ulat
ing
data
.St
uden
tssh
ould
also
unde
rsta
ndth
atth
eirp
rivi
lege
sto
man
ipul
ate
data
may
depe
ndon
who
owns
the
data
.For
exam
ple,
stude
ntsc
anta
lkab
outh
owth
eyca
rry
outt
hese
oper
atio
nson
emai
lort
extm
essa
ges,
and
who
isal
lowe
dto
exec
ute
thes
eop
erat
ions
onth
eiro
wn
acco
unts
.
Prac
tice(
s):2
.4,3
.2
Stor
e,re
trie
ve,a
ndsh
are
data
toco
llabo
rate
,usin
ga
clou
d-ba
sed
syst
em.
Clo
ud-b
ased
appl
icat
ions
enab
lem
ultip
lepe
ople
toup
date
data
from
mul
tiple
loca
tions
.Thi
sena
bles
back
upsy
stem
sto
prot
ectd
ata
aswe
llas
colla
bora
tion
ondo
cum
ents
and
proc
esse
s.St
uden
tssh
ould
crea
tean
dm
odify
info
rmat
ion
usin
gcl
oud-
base
dsy
stem
s.Fo
rex
ampl
e,stu
dent
scou
ldco
ntri
bute
toa
data
setr
ecor
ded
ina
shar
edsp
read
shee
t,ta
kean
onlin
ecl
assf
orce
rtifi
catio
n,or
cont
ribu
tere
gion
alim
ages
toa
natio
nal
data
base
ofim
ages
.
Prac
tice(
s):2
.4,5
.3
Expl
ain
trad
eoffs
betw
een
stor
ing
data
loca
llyor
ince
ntra
l,cl
oud-
base
dsy
stem
s.
Loca
land
clou
d-ba
sed
stora
geof
data
have
diffe
rent
affor
danc
esw
ithre
spec
tto
acce
ssib
ility
,cos
t,sp
eed,
secu
rity
,and
inte
grity
.St
uden
tssh
ould
beab
leto
disc
usst
hese
trade
offs
inth
eco
ntex
tofd
ecis
ions
abou
tman
agin
gsp
ecifi
cfo
rmso
fdat
a.Fo
rexa
mpl
e,stu
dent
sco
uld
disc
ussb
enefi
tsan
dlim
itatio
nsto
both
loca
land
clou
d-ba
sed
stora
geof
med
ical
reco
rds
bya
doct
or’s
office
.
Prac
tice(
s):2
.4,5
.1
Storage
No
K-2
stan
dard
.N
o3-
5st
anda
rd.
Des
crib
eva
riou
slow
-leve
ldat
atr
ansf
orm
atio
nsan
did
entif
yw
hich
resu
ltin
alo
ssof
info
rmat
ion
Dat
are
pres
enta
tions
occu
ratm
ultip
lele
vels
ofab
strac
tion,
from
the
phys
ical
stora
geof
bits
toth
ear
rang
emen
tofi
nfor
mat
ion
into
orga
nize
dfo
rmat
s(e.
g.ta
bles
).So
me
data
repr
esen
tatio
nsco
mpr
essd
ata
tosa
vesp
ace,
whi
chre
sults
ina
loss
ofin
form
atio
n.St
uden
tssh
ould
beab
leto
repr
esen
tthe
sam
eda
tain
mul
tiple
ways
,dis
cuss
ing
whe
ther
each
repr
esen
tatio
nlo
ses
any
info
rmat
ion.
Fore
xam
ple,
stude
ntsc
ould
repr
esen
tthe
sam
eco
loru
sing
both
RGB
valu
es,
hex
code
s,an
dgr
eysc
ale
valu
es,d
iscu
ssin
gpo
tent
iall
oss
ofhu
e.St
uden
tsco
uld
expe
rim
entw
ithdi
ffere
ntau
dio-
com
pres
sion
form
ats,
liste
ning
forw
hen
they
can
dete
ctdi
ffere
nces
inso
und
qual
ity.
Prac
tice:
4.1,
4.3
Tran
slate
data
for
vari
ousr
eal-w
orld
phen
omen
a,su
chas
char
acte
rs,n
umbe
rs,a
ndim
ages
,int
obi
ts.
Com
pute
rsul
timat
ely
store
data
asse
quen
ceso
fbi
nary
digi
ts(b
its)o
f0sa
nd1s
.Let
ter
char
acte
rs,n
umbe
rs,a
ndim
ages
can
bere
pres
ente
das
num
bers
,whi
chin
turn
can
beco
nver
ted
tobi
ts.S
tude
ntss
houl
dun
ders
tand
why
com
pute
rsus
ebi
t-lev
elre
pres
enta
tions
,and
shou
ldbe
able
toco
nver
tmul
tiple
type
sof
basi
cda
tain
tobi
t-lev
elfo
rm.F
orex
ampl
e,stu
dent
scou
ldtra
nsla
tea
4-di
gitn
umbe
rint
obi
ts,a
two-
word
phra
sein
toAS
CII
orU
nico
de,
and
seve
rali
mag
epi
xels
into
sequ
ence
sof
hexa
deci
mal
colo
rcod
es
Prac
tice(
s):4
.1
13
52
DIG
ITA
LLI
TER
ACY
Gra
desK
-2G
rade
s3-5
Gra
des6
-8G
rade
s9-1
2
Creation&Use
Use
softw
are
tool
sto
crea
tesim
ple
digi
tala
rtifa
cts.
Peop
lepe
rfor
mm
any
com
mon
oper
atio
nsw
hen
crea
ting
artif
acts
with
softw
are
tool
s.St
uden
tssh
ould
beab
leto
oper
ate
and
inte
ract
with
softw
are
tool
sto
crea
tean
artif
act.
Fore
xam
ple,
stude
ntsc
ould
wri
tea
text
docu
men
ttha
tinc
lude
san
imag
e.
Prac
tice(
s):8
.1
Use
softw
are
tool
sto
crea
tean
dsh
are
mul
timed
iaar
tifac
ts.
Whe
ncr
eatin
gdi
gita
lart
ifact
s,pe
ople
use
loca
l,ne
twor
ked
and
onlin
eto
ols.
Stud
ents
shou
ldbe
able
tocr
eate
,man
ipul
ate,
and
publ
ish
mul
timed
iaar
tifac
tsus
ing
softw
are
tool
sfro
mm
ultip
leen
viro
nmen
ts.F
orex
ampl
e,stu
dent
smig
htcr
eate
avi
deo
with
alo
cal
tool
,the
nup
load
the
vide
oto
anon
line
fold
eror
blog
fors
hari
ngw
ithfr
iend
sand
fam
ily.
Prac
tice(
s):8
.1
Use
softw
are
tool
sto
crea
tear
tifac
tsth
aten
gage
user
sove
rtim
e
Man
yar
tifac
tsar
em
eant
tobe
view
edei
ther
inm
ultip
lesta
ges(
like
slid
esho
ws)o
rove
rmul
tiple
visi
ts(li
kebl
ogs)
.Stu
dent
ssho
uld
unde
rsta
ndho
wdi
ffere
ntki
ndso
fart
ifact
scan
enga
geus
ers
over
time,
and
crea
teap
prop
riat
ear
tifac
tsth
atdo
so.
Stud
ents
shou
ldal
sode
scri
bech
alle
nges
inke
epin
gsu
char
tifac
tsup
toda
te.F
orex
ampl
e,stu
dent
sco
uld
crea
tea
mul
timed
iasl
ides
how
show
ing
the
histo
ryof
alo
cali
ssue
,orc
reat
ea
blog
with
upda
teso
na
topi
cof
inte
rest,
deba
ting
polic
ies
foru
pdat
ing
olde
rblo
gpo
stsin
the
pres
ence
ofpe
rmal
inks
..
Prac
tice(
s):8
.1
Sele
ctap
prop
riat
eso
ftwar
eto
ols
orre
sour
cest
ocr
eate
aco
mpl
exar
tifac
tor
solv
ea
prob
lem
.
Peop
leus
em
ultip
leki
ndso
fsof
twar
eto
olsw
hen
crea
ting
inte
ract
ive
artif
acts
orso
lvin
gpr
oble
ms.
Stud
ents
shou
ldse
lect
softw
are
tool
s,ar
tifac
tsty
les,
and
reso
urce
sbas
edon
thei
reffi
cien
cyan
deff
ectiv
enes
sfor
agi
ven
purp
ose,
proj
ecto
ras
sign
men
t,an
dbe
able
toju
stify
thei
rcho
ices
.Fo
rexa
mpl
e,stu
dent
smig
htco
mbi
neda
tafro
mci
tizen
scie
nce
data
base
s,ne
wsar
chiv
esan
dim
age
data
base
sto
crea
tea
webs
iteth
atpr
esen
tspr
esen
tsdy
nam
ical
ly-u
pdat
ing
info
rmat
ion.
Prac
tice(
s):8
.1,8
.3
SearchingDigitalInformation
Con
duct
basic
digi
tals
earc
hes.
Dig
itald
ata
repo
sito
ries
ofte
npr
ovid
ewa
ysfo
rus
erst
ose
arch
fori
nfor
mat
ion
that
inte
rests
them
.St
uden
tssh
ould
beab
leto
cond
uctb
asic
keyw
ord
sear
ches
tofin
din
form
atio
nin
digi
talr
esou
rces
.Fo
rexa
mpl
e,stu
dent
scou
ldse
arch
forb
ooks
onsp
ecifi
cto
pics
ina
libra
ryca
talo
gor
onth
eIn
tern
et.
Prac
tice(
s):8
.1
Con
duct
and
refin
em
ulti-
crite
ria
sear
ches
over
digi
tali
nfor
mat
ion.
Que
ries
over
digi
tali
nfor
mat
ion
ofte
nco
nsid
erm
ultip
leco
nstra
ints
.Stu
dent
ssho
uld
beab
leto
perf
orm
sear
ches
that
invo
lve
mul
tiple
crite
ria,
whe
ther
thro
ugh
sear
chto
olsw
ithse
para
tefie
lds
orby
usin
g"a
nd"
or"o
r"op
erat
ions
with
inqu
erie
s.St
uden
tssh
ould
also
beab
leto
refin
ere
sults
ofon
equ
ery
with
addi
tiona
lcon
strai
nts.
For
exam
ple,
stude
ntsc
ould
sear
chfo
rloc
alev
ents
that
occu
rwith
ina
spec
ific
date
rang
ein
awe
bsite
with
loca
leve
ntlis
tings
,the
nre
stric
tthe
resu
ltsto
mus
icco
ncer
ts.
Prac
tice(
s):8
.1
Con
duct
sear
ches
over
mul
tiple
type
sofd
igita
lin
form
atio
n.
Dig
itali
nfor
mat
ion
com
esin
form
soth
erth
ante
xtua
ldoc
umen
ts.S
tude
ntss
houl
dbe
able
tose
arch
foro
ther
form
sofd
ata,
such
asim
ages
orau
dio
files
,pay
ing
atte
ntio
nto
Cop
yrig
htan
dFa
irU
seon
disc
over
edre
sour
ces.
Fore
xam
ple,
stude
ntsc
ould
sear
chfo
rgra
phic
sin
asp
ecifi
cfil
efo
rmat
toin
clud
ein
apr
esen
tatio
n,w
hile
esta
blis
hing
that
the
licen
sing
onth
egr
aphi
cal
lows
such
use.
Prac
tice(
s):8
.1,8
.2
Dec
ompo
sea
com
plex
prob
lem
into
mul
tiple
ques
tions
,ide
ntify
whi
chca
nbe
expl
ored
thro
ugh
digi
tals
ourc
es,a
ndsy
nthe
size
quer
yre
sults
usin
ga
vari
ety
ofso
ftwar
eto
ols.
Real
istic
prob
lem
sare
answ
ered
byco
mbi
ning
the
resu
ltsof
seve
ralm
ore
focu
sed
ques
tions
,so
me
ofw
hich
can
bean
swer
edth
roug
hdi
gita
lin
form
atio
n.St
uden
tssh
ould
beab
leto
brea
kdo
wn
apr
oble
min
tofo
cuse
dqu
estio
ns,q
uery
digi
tals
ourc
esw
hen
appr
opri
ate,
synt
hesi
zere
sults
into
anan
swer
toth
eor
igin
alpr
oble
m,
whi
lepr
oper
lyid
entif
ying
and
citin
gso
urce
s.Fo
rexa
mpl
e,stu
dent
scou
ldas
kho
wwe
athe
rm
ight
affec
tcri
me
statis
ticsf
ora
chos
enci
tyor
regi
on,s
earc
hfo
rgeo
-tagg
edcr
ime
inci
dent
data
and
weat
herd
ata,
then
synt
hesi
zeth
eda
tato
find
and
pres
enta
nan
swer
toan
info
rmat
ion
prob
lem
.
Prac
tice(
s):8
.1,8
.3
14
53UnderstandingSoftwareTools
No
K-2
stan
dard
.yyy
yyyy
yyyy
yyyy
yyyy
yyyy
yyyy
Des
crib
eth
edi
ffere
nthi
gh-le
velt
asks
that
are
com
mon
toso
ftwar
eto
olst
hats
tude
ntsu
se.
Man
yso
ftwar
eto
olsa
rebu
iltar
ound
aco
mm
onco
llect
ion
ofta
sks,
such
asga
ther
ing
inpu
tfro
mus
ers,
stori
ngda
ta,p
rese
ntin
gda
ta,p
rote
ctin
gda
ta,
perf
orm
ing
som
eco
mpu
tatio
nov
erda
ta,o
rco
nnec
ting
toot
herr
esou
rces
orse
rvic
esto
perf
orm
aco
mpu
tatio
n.St
uden
tssh
ould
beab
leto
desc
ribe
thes
eta
sksa
ndth
eira
ssoc
iate
dda
tafo
ratl
east
two
diffe
rent
kind
sofs
oftw
are
that
they
use
ona
regu
lar
basi
s.Fo
rexa
mpl
e,stu
dent
scou
ldde
scri
beth
eda
tam
anag
edby
anon
line
docu
men
t-edi
ting
prog
ram
and
how
the
prog
ram
cont
rols
acce
ssto
docu
men
ts.
Stud
ents
coul
dex
plai
nho
wa
softw
are
tool
work
sto
othe
rs,s
uch
asth
em
eani
ngbe
hind
com
mon
icon
ssu
chas
the
gear
whe
elor
apa
dloc
kin
abr
owse
rsea
rch
field
orop
erat
ing
syste
m.
Prac
tice(
s):8
.1,8
.3
Des
crib
eth
edi
ffere
ntfo
rmat
sofs
oftw
are
com
pone
ntst
hats
uppo
rtco
mm
onta
sksi
nso
ftwar
eto
ols
Softw
are
tool
sare
built
outo
fsta
ndar
dco
mpo
nent
ssu
chas
data
base
s,fil
esy
stem
s,ne
twor
kco
nnec
tions
and
sens
ors.
Stud
ents
shou
ldbe
able
toex
plai
nw
hatv
ario
usco
mpo
nent
sdo
inge
nera
l,an
dho
wth
ese
com
pone
ntsa
reus
edin
spec
ific
softw
are
syste
mst
hata
rere
leva
ntto
the
stude
nt.
Fore
xam
ple,
stude
ntss
houl
dbe
able
toex
plai
nth
ata
phot
o-sh
arin
gwe
bsite
hasa
data
base
with
info
rmat
ion
onus
ers,
afil
esy
stem
ofph
otog
raph
s,an
dus
esth
ene
twor
kto
trans
fer
phot
osta
ken
ona
user
’ssm
artp
hone
toth
eap
plic
atio
n.
Prac
tice(
s):8
.1,8
.3
Des
crib
edi
ffere
ntki
ndso
fcom
puta
tions
that
softw
are
tool
sper
form
tota
ilor
asy
stem
toin
divi
dual
user
s.
Dat
ais
atth
ehe
arto
fsof
twar
eto
ols:
tool
sm
anag
eda
ta,b
utal
sous
eda
taan
dco
mpu
tatio
nsov
erda
tato
alte
rhow
diffe
rent
user
sexp
erie
nce
asy
stem
.Stu
dent
ssho
uld
beab
leto
expl
ain
how
softw
are
tool
suse
data
tocu
stom
ize
softw
are
toin
divi
dual
user
s.Fo
rex
ampl
e,stu
dent
smig
htex
plai
nw
hatu
ser
data
and
sear
ches
are
used
tode
term
ine
whi
chad
vert
isem
ents
are
disp
laye
don
ane
wsor
ente
rtai
nmen
tweb
site
,and
why
diffe
rent
user
sse
edi
ffere
ntad
vert
isem
ents
orse
arch
resu
ltsfo
rthe
sam
ese
arch
.
Prac
tice(
s):8
.1,8
.3
15
54
RES
PON
SIBL
EC
OM
PUTI
NG
INSO
CIE
TYG
rade
sK-2
Gra
des3
-5G
rade
s6-8
Gra
des9
-12
Com
pare
and
cont
rast
how
indi
vidu
alsl
ive
and
work
befo
rean
daf
ter
the
impl
emen
tatio
nor
adop
tion
ofne
wco
mpu
ting
tech
nolo
gy.
Com
putin
gte
chno
logy
hasp
ositi
vely
and
nega
tivel
ych
ange
dth
ewa
ype
ople
live
and
work
.In
the
past,
ifstu
dent
swan
ted
tore
adab
outa
topi
c,th
eyne
eded
acce
ssto
alib
rary
oran
yre
posi
tory
tofin
dre
sour
ces.
Toda
y,stu
dent
scan
find
info
rmat
ion
onth
eIn
tern
etab
outa
topi
cor
they
can
dow
nloa
de-
book
sabo
utit
dire
ctly
toa
devi
ce.S
tude
ntss
houl
dbe
able
tode
scri
beth
ety
peof
info
rmat
ion
foun
don
the
Inte
rnet
.Fo
rexa
mpl
e,stu
dent
scou
ldgo
toth
elib
rary
and
with
teac
hero
rlib
rari
anas
sista
nce,
find
book
son
apa
rtic
ular
topi
can
dth
enfin
dan
dco
mpa
resi
mila
rin
form
atio
non
line.
Prac
tice(
s):3
.1
Com
pare
and
cont
rast
com
putin
gte
chno
logi
esth
atha
vech
ange
dth
ewo
rld,
and
expr
essh
owth
ose
tech
nolo
gies
influ
ence
,and
are
influ
ence
dby
,cul
tura
lpra
ctic
es.
New
com
putin
gte
chno
logy
iscr
eate
dan
dex
istin
gte
chno
logi
esar
em
odifi
edfo
rman
yre
ason
s,su
chas
incr
ease
dbe
nefit
s(e.
g.,I
nter
nets
earc
hre
com
men
datio
ns),
decr
ease
dri
sks(
e.g.
,aut
onom
ous
vehi
cles
),an
dso
cial
effici
enci
es(s
mar
tpho
neap
plic
atio
ns).
With
guid
ance
from
thei
rtea
cher
,stu
dent
ssho
uld
beab
leto
disc
usst
opic
stha
trel
ate
toth
ehi
story
ofte
chno
logy
and
the
chan
gesa
roun
dth
emth
atar
edr
iven
byte
chno
logy
.For
exam
ple,
stude
nts
coul
ddi
scus
scur
rent
even
tsth
ataff
ectt
hem
such
asro
botic
s,w
irele
ssIn
tern
et,m
obile
com
putin
gde
vice
s,G
PSsy
stem
s,we
arab
leco
mpu
ting,
orho
wso
cial
med
iaha
sinfl
uenc
edso
cial
and
polit
ical
mov
emen
ts,c
hang
edor
affec
ted
the
prac
tices
ofcu
ltura
ltra
ditio
nsan
dcu
stom
s.
Prac
tice(
s):3
.1
Com
pare
and
cont
rast
trad
eoffs
asso
ciat
edw
ithco
mpu
ting
tech
nolo
gies
that
affec
tpe
ople
’sev
eryd
ayac
tiviti
esan
dca
reer
optio
ns.
Adva
ncem
ents
inco
mpu
tert
echn
olog
yar
ene
ither
entir
ely
posi
tive
norn
egat
ive.
How
ever
,the
ways
that
peop
leus
eco
mpu
ting
tech
nolo
gies
have
trade
offs.
Stud
ents
shou
ldco
nsid
ercu
ltura
lim
pact
s,in
clud
ing
priv
acy,
free
spee
ch,c
omm
unic
atio
n,an
dau
tom
atio
n.Fo
rexa
mpl
e,stu
dent
scou
ldid
entif
ytra
deoff
sw
ithdr
iver
less
cars
-the
yca
nin
crea
seco
nven
ienc
ean
dre
duce
acci
dent
s,bu
tthe
yar
eal
sosu
scep
tible
toha
ckin
g.
Prac
tice(
s):7
.2
Eval
uate
the
way
scom
putin
gim
pact
sper
sona
l,et
hica
l,so
cial
,eco
nom
ic,a
ndcu
ltura
lpra
ctic
es.
Com
putin
gm
aych
ange
(impr
ove
orha
rm)o
rm
aint
ain
soci
etal
prac
tices
.Min
imal
expo
sure
toco
mpu
ting,
limite
dac
cess
toed
ucat
ion,
and
lack
oftra
inin
gop
port
uniti
esm
agni
fysy
stem
icpr
oble
msi
nso
ciet
y.St
uden
tssh
ould
beab
leto
eval
uate
the
acce
ssib
ility
ofa
prod
uctt
oa
broa
dgr
oup
ofen
dus
ers,
such
aspe
ople
who
lack
ubiq
uito
usac
cess
toth
eIn
tern
etor
who
have
disa
bilit
ies.
Fore
xam
ple,
stude
ntsc
ould
iden
tify
pote
ntia
lbia
sdur
ing
the
deve
lopm
enta
ndde
sign
proc
esst
om
axim
ize
acce
ssib
ility
inwe
bsite
ordi
gita
lpro
duct
impl
emen
tatio
n.
Prac
tice(
s):1
.2
Culture
No
K-2
stan
dard
.
Iden
tify
way
sto
impr
ove
the
acce
ssib
ility
and
usab
ility
ofte
chno
logy
prod
ucts
for
the
dive
rse
need
sand
wan
tsof
user
s.
The
deve
lopm
enta
ndm
odifi
catio
nof
com
putin
gte
chno
logy
are
driv
enby
peop
le’s
need
sand
want
san
dca
naff
ectg
roup
sdiff
eren
tly.S
tude
ntss
houl
dbe
able
toid
entif
yth
ene
edsa
ndwa
ntso
fdiv
erse
end
user
sand
purp
osef
ully
cons
ider
pote
ntia
lpe
rspe
ctiv
esof
user
swith
diffe
rent
back
grou
nds,
abili
tyle
vels
,poi
ntso
fvie
w,an
ddi
sabi
litie
s.Fo
rex
ampl
e,stu
dent
scou
ldco
nsid
erus
ing
both
spee
chan
dte
xtw
hen
they
conv
eyin
form
atio
nin
aga
me.
They
coul
dal
sova
ryth
eop
tions
orsty
lesi
npr
ogra
mst
hey
crea
te,k
now
ing
that
note
very
one
shar
esth
eiro
wn
taste
s.
Prac
tice(
s):1
.2
Disc
ussi
ssue
sofb
iasa
ndac
cess
ibili
tyin
the
desig
nof
exist
ing
tech
nolo
gies
.
Stud
ents
shou
ldte
stan
ddi
scus
sthe
usab
ility
ofva
riou
stec
hnol
ogy
tool
s(e.
g.,a
pplic
atio
ns,
gam
es,a
ndde
vice
s)w
ithth
ete
ache
r’s
guid
ance
.Fac
ialr
ecog
nitio
nso
ftwar
e,fo
rex
ampl
e,th
atwo
rksb
ette
rfor
light
ersk
into
nes
wasl
ikel
yde
velo
ped
with
aho
mog
eneo
uste
sting
grou
pan
dco
uld
beim
prov
edby
sam
plin
ga
mor
edi
vers
epo
pula
tion.
Stud
ents
shou
ldbe
able
tore
cogn
ize
that
incr
easi
ngus
abili
tybe
nefit
soth
ersi
nad
ditio
nto
the
targ
eted
grou
p.Fo
rexa
mpl
e,stu
dent
scou
lddi
scus
sthe
diffe
rent
type
sofu
sers
who
woul
dbe
nefit
from
bein
gab
leto
adju
stfo
ntsi
zesa
ndco
lorc
ontra
stra
tios.
Prac
tice(
s):1
.2
Des
ign
and
anal
yze
com
puta
tiona
lart
ifact
sto
redu
cebi
asan
deq
uity
defic
its.
Bias
esin
clud
ein
corr
ecta
ssum
ptio
nsde
velo
pers
have
mad
eab
outt
heir
user
base
.Equ
ityde
ficits
incl
ude
min
imal
expo
sure
toco
mpu
ting,
acce
ssto
educ
atio
n,an
dtra
inin
gop
port
uniti
es.S
tude
nts
shou
ldbe
gin
toid
entif
ypo
tent
ialb
iasd
urin
gth
ede
sign
proc
esst
om
axim
ize
acce
ssib
ility
inpr
oduc
tdes
ign
and
beco
me
awar
eof
prof
essi
onal
lyac
cept
edac
cess
ibili
tysta
ndar
dsto
eval
uate
com
puta
tiona
lart
ifact
sfor
acce
ssib
ility
.
Prac
tice(
s):1
.2,6
.3
16
55Culture
No
K-2
stan
dard
.N
o3-
5st
anda
rd.
No
6-8
stan
dard
.
Eval
uate
the
impa
ctof
equi
ty,a
cces
s,an
din
fluen
ceon
the
dist
ribu
tion
ofco
mpu
ting
reso
urce
sin
agl
obal
soci
ety.
Reso
urce
s,su
chas
com
pute
rs,m
obile
devi
cesa
ndne
twor
kco
nnec
tivity
requ
irem
oney
toac
quire
and
train
ing
tous
eeff
ectiv
ely.
The
lack
offin
anci
alre
sour
cesa
nded
ucat
orss
kille
din
com
putin
gin
man
yre
gion
soft
hewo
rld,s
uch
asin
nerc
ities
and
rura
lare
as,p
lace
sind
ivid
uals
ata
disa
dvan
tage
ina
soci
ety
that
valu
este
chno
logy
.St
uden
tssh
ould
beab
leto
disc
usst
hewa
ysth
isdi
gita
ldiv
ide
plac
esin
divi
dual
sata
disa
dvan
tage
.Fo
rexa
mpl
e,stu
dent
scou
ldre
sear
chho
wbe
tter
acce
ssto
info
rmat
ion
and/
orre
sour
cesa
ffect
sapo
pula
tion.
Prac
tice(
s):1
.2
Safety,Law,&Ethics
Disc
usso
wne
rshi
pan
dat
trib
utio
nof
digi
tal
artif
acts
.
Mos
tdig
itala
rtifa
ctsh
ave
owne
rs.S
tude
nts
shou
ldun
ders
tand
the
impo
rtan
ceof
givi
ngcr
edit
tom
edia
crea
tors
/ow
ners
whe
nus
ing
thei
rwo
rk.F
orex
ampl
e,stu
dent
scou
ldcr
eate
ate
xtdo
cum
entw
ithdi
gita
lim
ages
and
iden
tify
the
onlin
eso
urce
ofth
eiri
mag
es.
Prac
tice(
s):7
.3
Inco
rpor
ate
publ
icdo
mai
nor
crea
tive
com
mon
sm
edia
into
adi
gita
lart
ifact
,and
refr
ain
from
copy
ing
orus
ing
mat
eria
lcre
ated
byot
hers
with
outp
erm
issio
n.
Ethi
calc
ompl
icat
ions
aris
efro
mth
eop
port
uniti
espr
ovid
edby
com
putin
g.Th
eea
seof
send
ing
and
rece
ivin
gco
pies
ofm
edia
onth
eIn
tern
et,s
uch
asvi
deo,
phot
os,a
ndm
usic
,cre
ates
the
oppo
rtun
ityfo
runa
utho
rize
dus
e,su
chas
onlin
epi
racy
,and
disr
egar
dof
copy
righ
ts.S
tude
ntss
houl
dco
nsid
erth
elic
ense
son
com
puta
tiona
lart
ifact
stha
tthe
yw
ish
tous
e.Fo
rexa
mpl
e,th
elic
ense
ona
dow
nloa
ded
imag
eor
audi
ofil
em
ayha
vere
stric
tions
that
proh
ibit
mod
ifica
tion,
requ
ireat
trib
utio
n,fo
rbid
com
mer
cial
use,
orpr
ohib
itus
een
tirel
y.
Prac
tice(
s):7
.3
Disc
ussh
owla
wsc
ontr
olus
ean
dac
cess
toin
telle
ctua
lpro
pert
y,an
dm
anda
tebr
oad
acce
ssto
info
rmat
ion
tech
nolo
gies
.
Cop
yrig
htla
wsan
dlic
ensi
ngpr
otec
tow
ners
ofin
telle
ctua
lpro
pert
y.Ad
ditio
nally
,law
shel
pen
sure
that
peop
lew
ithva
riou
sdis
abili
tiesc
anac
cess
com
putin
gte
chno
logi
es.S
tude
ntss
houl
dbe
able
toex
plai
nth
epo
tent
ialc
onse
quen
ceso
fvio
latin
gin
telle
ctua
lpro
pert
yla
wsor
licen
sing
agre
emen
ts,a
ndse
ndin
gin
appr
opri
ate
cont
ent.
Fore
xam
ple,
stude
nts
coul
ddi
scus
show
crea
tive
com
mon
slic
ense
sfor
imag
es,
restr
ictio
nson
taki
ngph
otos
inm
useu
ms,
orho
wla
wsdr
ive
scho
olpo
licie
son
appr
opri
ate
cont
ents
hari
ngbe
twee
nstu
dent
s.
Prac
tice(
s):7
.3
Eval
uate
the
impa
ctof
inte
llect
ualp
rope
rty
law
son
the
use
ofdi
gita
linf
orm
atio
n.
Inte
llect
ualp
rope
rty
laws
can
have
mix
edeff
ects
.Th
eyar
em
eant
topr
otec
tcre
atio
nan
din
vent
ion,
butc
anal
sore
stric
tacc
essa
ndus
age
ofdi
gita
lob
ject
stha
tper
mit
leve
ragi
ngan
inve
ntio
nfo
rw
ider
use.
The
sam
eto
olst
hata
reus
edto
enfo
rce
copy
righ
tlaw
scan
beus
edto
cens
orm
edia
.For
exam
ple,
laws
enac
ted
tore
duce
onlin
epi
racy
can
restr
ictfi
lesh
arin
gin
ways
that
limit
publ
icac
cess
toin
form
atio
n.St
uden
tssh
ould
beaw
are
ofin
telle
ctua
lpro
pert
yla
wsan
dth
eiri
mpa
cton
usin
gor
publ
ishi
ngdi
gita
lart
ifact
s,as
well
asco
mm
erci
alen
deav
ors.
Fore
xam
ple,
stude
ntsc
ould
rese
arch
and
expl
ain
how
mus
icstr
eam
ing
appl
icat
ions
com
pens
ate
artis
ts,o
rhow
pate
ntsa
rem
eant
topr
otec
tthe
inte
rests
ofin
nova
tors
,yet
can
beab
used
inlit
igat
ion
focu
sed
onfin
anci
alga
in.
Prac
tice(
s):7
.3
17
56 Safety,Law,&Ethics
No
K-2
stan
dard
.N
o3-
5st
anda
rd.
No
6-8
stan
dard
.
Eval
uate
the
soci
alan
dec
onom
icim
plic
atio
nsof
priv
acy
and
free
spee
chin
the
cont
exto
fsaf
ety,
law,
oret
hics
.
Laws
gove
rnm
any
aspe
ctso
fcom
putin
g,su
chas
priv
acy,
data
,pro
pert
y,in
form
atio
nac
cess
,and
digi
tali
dent
ity.I
nter
natio
nald
iffer
ence
sin
laws
and
ethi
csha
veim
plic
atio
nsfo
rcom
putin
g.St
uden
tssh
ould
unde
rsta
ndho
wpr
ivac
yla
wsim
pact
educ
atio
n,wo
rkpl
ace
and
recr
eatio
n.Fo
rex
ampl
e,stu
dent
scou
ldre
view
case
studi
esor
curr
ente
vent
swhi
chpr
esen
tan
ethi
cald
ilem
ma
whe
nan
indi
vidu
al’s
righ
tto
priv
acy
isat
odds
with
the
safe
ty,s
ecur
ity,o
rwel
l-bei
ngof
aco
mm
unity
.
Prac
tice(
s):7
.3
SocialInteractions
Wor
kre
spec
tfully
and
resp
onsib
lyw
ithot
hers
onlin
e.
Onl
ine
com
mun
icat
ion
faci
litat
espo
sitiv
ein
tera
ctio
ns,s
uch
assh
arin
gid
easw
ithm
any
peop
le,b
utth
epu
blic
and
anon
ymou
snat
ure
ofon
line
com
mun
icat
ion
also
allo
wsin
timid
atin
gan
din
appr
opri
ate
beha
vior
inth
efo
rmof
cybe
rbul
lyin
g.St
uden
tssh
ould
beab
leto
prov
ide
feed
back
toot
hers
onth
eirw
ork
ina
kind
and
resp
ectfu
lman
nera
ndte
llan
adul
tifo
ther
sare
shar
ing
thin
gsth
eysh
ould
nots
hare
orar
etre
atin
got
hers
inan
unki
ndor
disr
espe
ctfu
lman
ner.
For
exam
ple,
asstu
dent
ssha
reth
eirw
ork
inbl
ogso
rot
hero
nlin
eco
llabo
rativ
esp
aces
(suc
has
the
loca
lsch
oold
epar
tmen
tdom
ain)
,the
yw
illav
oid
shar
ing
info
rmat
ion
that
isin
appr
opri
ate
orwo
uld
viol
ate
thei
rsor
anot
her’
spri
vacy
.
Prac
tice(
s):2
.1
Seek
dive
rse
pers
pect
ives
for
the
purp
ose
ofim
prov
ing
com
puta
tiona
lart
ifact
s.
Com
putin
gfa
cilit
ates
colla
bora
tion
and
shar
ing
ofid
eas.
Stud
ents
shou
ldbe
nefit
from
dive
rse
pers
pect
ives
faci
litat
edby
digi
talc
olla
bora
tion.
Fore
xam
ple,
stude
ntsc
ould
dom
utua
lrev
iews
ofea
chot
her’
spro
ject
s,or
seek
feed
back
from
othe
rstu
dent
grou
psou
tsid
eth
eirc
lass
room
(at
anot
herg
rade
leve
l,or
inan
othe
rsch
ool).
Spec
ifica
lly,a
ndw
ithgu
idan
cefro
mth
eir
teac
her,
stude
ntsc
ould
use
vide
oco
nfer
enci
ngto
olso
roth
eron
line
colla
bora
tive
spac
es,s
uch
asbl
ogs,
wik
is,f
orum
s,or
webs
iteco
mm
ents
,to
gath
erfe
edba
ckfro
min
divi
dual
sand
grou
psab
out
prog
ram
min
gpr
ojec
tsor
othe
rdig
italo
bjec
tsth
eycr
eate
.
Prac
tice(
s):1
.1
Col
labo
rate
and
stra
tegi
zew
ithm
any
onlin
eco
ntri
buto
rsw
hen
crea
ting
aco
mpu
tatio
nalo
rdi
gita
lart
ifact
.
Cro
wds
ourc
ing
isga
ther
ing
serv
ices
,ide
as,o
rcon
tent
from
ala
rge
grou
pof
peop
le,e
spec
ially
from
anon
line
com
mun
ity.I
tcan
bedo
neat
the
loca
llev
el(e
.g.,
clas
sroo
mor
scho
ol)o
rglo
ball
evel
(e.g
.,ag
e-ap
prop
riat
eon
line
com
mun
ities
fora
rtifa
ctcr
eato
rs).
Stud
ents
shou
ldde
velo
pan
unde
rsta
ndin
gof
solic
iting
feed
back
from
aw
ider
audi
ence
.For
exam
ple,
agr
oup
ofstu
dent
scou
ldco
llect
and
com
bine
imag
esor
anim
atio
nsfro
mth
eir
com
mun
ityan
dcr
eate
adi
gita
lmos
aic.
They
coul
dal
soso
licit
feed
back
from
man
ype
ople
bysh
arin
gth
eir
digi
tala
rtifa
ctsw
ithsp
ecifi
con
line
com
mun
ities
and
elec
troni
csu
rvey
s,th
enm
ake
impr
ovem
ents
.
Prac
tice(
s):2
.4,5
.2
Use
tool
sand
met
hods
for
colla
bora
tion
ona
proj
ectt
oin
crea
seco
nnec
tivity
betw
een
peop
lein
diffe
rent
cultu
resa
ndca
reer
field
s.
Hum
anso
cial
struc
ture
stha
tsup
port
educ
atio
n,wo
rkan
dco
mm
uniti
esha
vebe
enaff
ecte
dby
the
ease
ofco
mm
unic
atio
nfa
cilit
ated
byco
mpu
ting.
The
incr
ease
dco
nnec
tivity
betw
een
peop
lein
diffe
rent
cultu
resa
ndin
diffe
rent
care
erfie
ldsh
asim
pact
edth
eva
riet
yan
dty
peso
fcar
eers
that
are
poss
ible
.Stu
dent
ssho
uld
beab
leto
expl
ore
diffe
rent
colla
bora
tive
tool
sand
met
hods
used
toso
licit
inpu
tfro
mte
amm
embe
rs,c
lass
mat
es,a
ndot
hers
,suc
has
part
icip
atio
nin
onlin
efo
rum
sor
com
pilin
gsu
rvey
data
from
loca
lcom
mun
ities
.Fo
rexa
mpl
e,stu
dent
scou
ldco
mpa
rewa
ysdi
ffere
ntso
cial
med
iato
olsc
ould
help
ate
amto
rese
arch
exam
ples
and
solic
itin
putt
hath
elps
solv
ea
com
mun
itypr
oble
m.
Prac
tice(
s):2
.4
18
57
Appendix B- Glossary
The glossary includes definitions of terms used in the statements in the standards. Unlessindicated, these definitions were adopted directly from the K-12 Computer Science Framework. Asnoted in the Framework, these terms are defined for readers of the framework and are notnecessarily intended to be the definitions or terms that are presented to students.
*denotes revision of definition by Rhode Island Computer Science EducationStandards Committee
**denotes addition of definition by Rhode Island Computer Science EducationStandards Committee
Term Definition
abstraction
(Process): The process of reducing complexity by focusing on the mainidea. By hiding details irrelevant to the question at hand and bringingtogether related and useful details, abstraction reduces complexityand allows one to focus on the problem.
(Product): A new representation of a thing, a system, or a problem thathelpfully reframes a problem by hiding details irrelevant to thequestion at hand.[MDESE, 2016]
accessibility
The design of products, devices, services, or environments for peoplewho experience disabilities. Accessibility standards that are generallyaccepted by professional groups include the Web Content AccessibilityGuidelines (WCAG) 2.0 and Accessible Rich Internet Applications(ARIA) standards. [Wikipedia]
algorithm A step-by-step process to complete a task.
analog
The defining characteristic of data that is represented in a continuous,physical way. Whereas digital data is a set of individual symbols,analog data is stored in physical media, such as the surface grooveson a vinyl record, the magnetic tape of a VCR cassette, or othernon-digital media. [Techopedia]
appA type of application software designed to run on a mobile device,such as a smartphone or tablet computer. Also known as a mobileapplication. [Techopedia]
57
58
application **A combination of software components or programs that enableusers to perform tasks, such as interact with digital artifacts,databases, and other users.
artifact *Something made by a human. See computational artifact forthe definition used in computer science.
audience Expected end users of a computational artifact or system.
authenticationThe verification of the identity of a person or process.[FOLDOC]
automate;automation
Automate: To link disparate systems and software so that theybecome self-acting or self-regulation [Ross, 2016]
Automation: The process of automating.
BooleanA type of data or expression with two possible values: trueand false. [FOLDOC]
bug
An error in a software program. It may cause a program tounexpectedly quit or behave in an unintended manner.[Tech Terms]
The process of finding and correcting errors (bugs) is calleddebugging. [Wikipedia]
codeAny set of instructions expressed in a programming language.[MDESE, 2016]
commentA programmer-readable annotation in the code of a computerprogram added to make the code easier to understand. Commentsare generally ignored by machines. [Wikipedia]
complexityThe minimum amount of resources such as memory, time, ormessages, needed to solve a problem or execute an algorithm.[NIST/DADS]
componentAn element of a larger group. Usually, a component provides aparticular service or group of related services. [Tech Terms,TechTarget]
computational Relating to computers or computing methods.
58
59
computationalartifact *
An artifact that performs computation over digital information.
computationalthinking *
The human ability to solve problems, design systems, andunderstand human behavior, by drawing on the conceptsfundamental to computer science. [Lee,2006]
computerA machine or device that performs processes, calculations,and operations based on instructions provided by a softwareor hardware program. [Techopedia]
computerscience
The study of computers and algorithmic processes, includingtheir principles, their hardware and software designs, theirimplementation, and their impact on society. [ACM, 2006]
computingAny goal-oriented activity requiring, benefiting from, orcreating algorithmic processes. [MDESE, 2016]
computingdevice
A physical device that uses hardware and software to receive,process, and output information. Computers, mobile phones,and computer chips inside appliances are all examples ofcomputing devices.
computingsystem
A collection of one or more computers or computing devices,together with their hardware and software, integrated forthe purpose of accomplishing shared tasks. Although acomputing system can be limited to a single computer orcomputing device, it more commonly refers to a collection ofmultiple connected computers, computing devices, and hardware.
conditional
A feature of a programming language that performs differentcomputations or actions depending on whether a programmer-specified Boolean condition evaluates to true or false.[MDESE, 2016]
(A conditional could refer to a conditional statement, conditionalexpression, or conditionalconstruct.)
configuration
(Process): Defining the options that are provided when installingor modifying hardware and software or the process of creatingthe configuration (product). [TechTarget]
(Product): The specific hardware and software details that tellexactly what the system is made up of, especially in terms ofdevices attached, capacity, or capability. [TechTarget]
59
60
connectionA physical or wireless attachment between multiple computingsystems, computers, or computing devices.
connectivityA program or device’s ability to link with other programs anddevices. [Webopedia]
control;control structure
Control: (in general) The power to direct the course of actions.
(In programming): The use of elements of programming codeto direct which actions take place and the order in which theytake place.
Control structure: A programming (code) structure thatimplements control. Conditionals and loops are examples ofcontrol structures.
culture;cultural practices
Culture: A human institution manifested in the learnedbehavior of people, including their specific belief systems,language(s), social relations, technologies, institutions,organizations, and systems for using and developingresources. [NCSS, 2013]
Cultural practices: The displays and behaviors of a culture.
cybersecurityThe protection against access to, or alteration of, computingresources through the use of technology, processes, andtraining. [TechTarget]
data
Information that is collected and used for reference or analysis.Data can be digital or non-digital and can be in many forms,including numbers, text, show of hands, images, sounds, or video.[CAS, 2013; Tech Terms]
data structureA particular way to store and organize data within a computerprogram to suit a specific purpose so that it can be accessedand worked with in appropriate ways. [TechTarget]
data type
A classification of data that is distinguished by its attributesand the types of operations that can be performed on it. Somecommon data types are integer, string, Boolean (true or false),and floating-point.
debuggingThe process of finding and correcting errors (bugs) in programs.[MDESE, 2016]
60
61
decompose;decomposition
Decompose: To break down into components.
Decomposition: Breaking down a problem or system intocomponents. [MDESE, 2016]
deviceA unit of physical hardware that provides one or more computingfunctions within a computing system. It can provide input to thecomputer, accept output, or both. [Techopedia]
digitalA characteristic of electronic technology that uses discrete values,generally 0 and 1, to generate, store, and process data. [Techopedia]
digitalartifact **
An artifact that is stored in a digital format.
digitalcitizenship
The norms of appropriate, responsible behavior with regard tothe use of technology. [MDESE, 2016]
digitalcollaboration**
Any activity that involves the sharing or modifying of artifactsby multiple users.
efficiency
A measure of the amount of resources an algorithm uses to findan answer. It is usually expressed in terms of the theoreticalcomputations, the memory used, the number of messagespassed, the number of disk accesses, etc. [NIST/DADS]
encapsulationThe technique of combining data and the procedures that act on itto create a type. [FOLDOC]
encryptionThe conversion of electronic data into another form, calledciphertext, which cannot be easily understood by anyone exceptauthorized parties. [TechTarget]
end user (or user)A person for whom a hardware or software product is designed(as distinguished from the developers). [TechTarget]
event
Any identifiable occurrence that has significance for systemhardware or software. User-generated events include keystrokesand mouse clicks; system-generated events include programloading and errors. [TechTarget]
event handler A procedure that specifies what should happen when a specificevent occurs.
61
62
execute;execution
Execute: To carry out (or “run”) an instruction or set ofinstructions (program, app, etc.).
Execution: The process of executing an instruction or setof instructions. [FOLDOC]
hardwareThe physical components that make up a computing system,computer, or computing device. [MDESE, 2016]
hierarchyAn organizational structure in which items are ranked accordingto levels of importance. [TechTarget]
human–computerinteraction (HCI)
The study of how people interact with computers and to whatextent computing systems are or are not developed for successfulinteraction with human beings. [TechTarget]
identifierThe user-defined, unique name of a program element (such as avariable or procedure) in code. An identifier name should indicatethe meaning and usage of the element being named. [Techopedia]
implementationThe process of expressing the design of a solution in a programminglanguage (code) that can be made to run on a computing device.
inference A conclusion reached on the basis of evidence and reasoning. [Oxford]
input The signals or instructions sent to a computer. [Techopedia]
integrityThe overall completeness, accuracy, and consistency of data.[Techopedia]
InternetThe global collection of computer networks and their connections,all using shared protocols to communicate. [CAS, 2013]
iterativeInvolving the repeating of a process with the aim of approaching adesired goal, target, or result. [MDESE, 2016]
loopA programming structure that repeats a sequence of instructions as longas a specific condition is true. [Tech Terms]
memory Temporary storage used by computing devices. [MDESE, 2016]
62
63
model
A representation of some part of a problem or a system.[MDESE, 2016]
Note: This definition differs from that used in science.
modularity
The characteristic of a software/web application that has been divided(decomposed) into smaller modules. An application might have severalprocedures that are called from inside its main procedure. Existingprocedures could be reused by recombining them in a new application.[Techopedia]
moduleA software component or part of a program that contains oneor more procedures. One or more independently developed modulesmake up a program. [Techopedia]
networkA group of computing devices (personal computers, phones, servers,switches, routers, etc.) connected by cables or wireless media for theexchange of information and resources.
operationAn action, resulting from a single instruction, changes the stateof data. [Free Dictionary]
operating system **Software that enables a user to interact with and organize filesand applications in a single machine: distinct from application.
packet The unit of data sent over a network. [Tech Terms]
parameterA special kind of variable used in a procedure to refer to oneof the pieces of data received as input by the procedure.[MDESE, 2016]
procedure
An independent code module that fulfills some concrete taskand is referenced within a larger body of program code. Thefundamental role of a procedure is to offer a single point ofreference for some small goal or task that the developer orprogrammer can trigger by invoking the procedure itself.[Techopedia]
In this framework, procedure is used as a general term thatmay refer to an actual procedure or a method, function, ormodule of any other name by which modules are known inother programming languages.
processA series of actions or steps taken to achieve a particularoutcome. [Oxford]
63
64
Program*;programming
Program (n): A set of instructions that can be executedby a computer
Program (v): To produce a program by programming.
Programming: The craft of analyzing problems anddesigning, writing, testing, and maintaining programsto solve them. [MDESE, 2016]
protocol
The special set of rules used by endpoints in atelecommunication connection when they communicate. Protocolsspecify interactions between the communicating entities.[TechTarget]
prototypeAn early approximation of a final product or informationsystem, often built for demonstration purposes. [TechTarget,Techopedia]
redundancyA system design in which a component is duplicated, so ifit fails, there will be a backup. [TechTarget]
reliabilityAn attribute of any system that consistently produces the sameresults, preferably meeting or exceeding its requirements.[FOLDOC]
remix
The process of creating something new from something old.Originally, a process that involved music, remixing involvescreating a new version of a program by recombining andmodifying parts of existing programs, and often adding newpieces, to form new solutions. [Kafai & Burke, 2014]
routerA device or software that determines the path that datapackets travel from source to destination. [TechTarget]
scalabilityThe capability of a network to handle a growing amountof work or its potential to be enlarged to accommodatethat growth. [Wikipedia]
security See the definition for cybersecurity.
simulate;simulation
Simulate: To imitate the operation of a real-world process orsystem.
Simulation: Imitation of the operation of a real-world processor system. [MDESE, 2016]
64
65
softwarePrograms that run on a computing system, computer, or othercomputing device.
softwaretool **
Software that enables creation of digital artifacts, storage ofdata, and data formatting.
storage
(Place): A place, usually a device, into which data can beentered, in which the data can be held, and from which thedata can be retrieved at a later time. [FOLDOC]
(Process): A process through which digital data is savedwithin a data storage device by means of computing technology.Storage is a mechanism that enables a computer to retain data,either temporarily or permanently. [Techopedia]
string
A sequence of letters, numbers, and/or other symbols. A stringmight represent, for example, a name, address, or song title.Some functions commonly associated with strings are length,concatenation, and substring. [TechTarget]
structureA general term used in the framework to discuss the conceptof encapsulation without specifying a particular programmingmethodology.
switchA high-speed device that receives incoming data packets andredirects them to their destination on a local area network(LAN). [Techopedia]
systemA collection of elements or components that work together fora common purpose. [TechTarget] See also the definition forcomputing system.
testcase
A set of conditions or variables under which a tester willdetermine whether the system being tested satisfies requirementsor works correctly. [STF]
topology
The physical and logical configuration of a network; thearrangement of a network, including its nodes and connectinglinks. A logical topology is the way devices appear connected tothe user. A physical topology is the way they are actuallyinterconnected with wires and cables. [PCMag]
troubleshootingA systematic approach to problem solving that is often used tofind and resolve a problem, error, or fault within software or acomputing system. [Techopedia, TechTarget]
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user **Anyone interacting with a digital artifact, software tool, programor application.
variable
A symbolic name that is used to keep track of a value that canchange while a program is running. Variables are not just usedfor numbers; they can also hold text, including whole sentences(strings) or logical values (true or false). A variable has a datatype and is associated with a data storage location; its value isnormally changed during the course of program execution.[CAS, 2013; Techopedia]
Note: This definition differs from that used in math.
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Appendix C- Resources
Below are the resources used by the K-12 Computer Science Framework. As noted in theFramework, some definitions came directly from the sources listed in the glossary, while otherswere excerpted or adapted to include content relevant to the framework.
ACM, 2006
A Model Curriculum for K–12 Computer Science
Tucker, A., McCowan, D., Deek, F., Stephenson, C., Jones, J., &Verno, A. (2006). A model curriculum for K–12 computer science: Reportof the ACM K–12 task force curriculum commit- tee (2nd ed.).New York, NY: Association for Computing Machinery.
CAS, 2013
Computing At School’s Computing in the National Curriculum:A Guide for Primary Teachers
Computing At School. (2013). Computing in the national curriculum:A guide for primary teachers. Belford, UK: Newnorth Print.Retrieved from http://www.computingatschool.org.uk/ data/uploads/CASPrimaryComputing.pdf
College Board, 2016
College Board Advanced Placement® Computer Science Principles
College Board. (2016). AP Computer Science Principles course andexam description. New York, NY: College Board. Retrieved fromhttps://secure-media.collegeboard.org/digitalServices/ pdf/ap/ap-computer-science-principles-course-and- exam-description.pdf
FOLDOC
Free On-Line Dictionary of Computing
Free on-line dictionary of computing. (n.d.).Retrieved from http://foldoc.org
Free Dictionary
The Free Dictionary
The free dictionary. (n.d.). Retrieved fromhttp://www.thefreedictionary.com
Kafai & Burke, 2014
Connected Code: Why Children Need to Learn Programming
Kafai, Y., & Burke, Q. (2014). Connected code: Whychildren need to learn programming. Cambridge, MA: MIT Press.
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Lee, 2016
Reclaiming the Roots of CT
Lee, I. (2016). Reclaiming the roots of CT. CSTA Voice:The Voice of K–12 Computer Science Education and ItsEducators, 12(1), 3–4. Retrieved from http://www.csteachers.org/resource/ resmgr/Voice/csta_voice_03_2016.pdf
MDESE, 2016
Massachusetts Digital Literacy and Computer Science (DL&CS)Standards
Massachusetts Department of Elementary and SecondaryEducation. (2016, June). 2016 Massachusetts digital literacy andcomputer science (DLCS) curriculum framework. Malden, MA:Author. Retrieved from http://www.doe.mass.edu/frameworks/dlcs.pdf
NCSS, 2013
College, Career & Civic Life (C3) Framework for Social StudiesState Standards
National Council for the Social Studies. (2013). The college, career,and civic life (C3) framework for social studies state standards:Guidance for enhancing the rigor of K–12 civics, economics,geography, and history. Silver Spring, MD: Author. Retrieved fromhttp://www.socialstudies.org/ system/files/c3/C3-Framework-for-Social-Studies.pdf
NIST/DADS
National Institute of Science and Technology Dictionary ofAlgorithms and Data Structures
Pieterse, V., & Black, P. E. (Eds.). (n.d). Dictionary of algorithmsand data structures. Retrieved from https://xlinux.nist.gov/dads//
Oxford
Oxford Dictionaries
Oxford dictionaries. (n.d.). Retrieved fromhttp://www.oxforddictionaries.com/us
PCmag
PCmag.com Encyclopedia
PCmag.com encyclopedia. (n.d.). Retrieved from http://www.pcmag.com/encyclopedia/ term/46301/logical-vs-physical-topology
Ross, 2016
What Is Automation
Ross, B. (2016, May 10). What is automation and howcan it improve customer service? Information Age. Retrievedfrom http://www.information-age. com/industry/soft- ware/123461408/what-automation-and- how-can-it-improve-customer-service
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STF
Software Testing Fundamentals
Software testing fundamentals. (n.d).Retrieved from http://softwaretestingfundamentals.com
Tech TermsTech Terms
Tech terms computer dictionary. (n.d.). Retrieved fromhttp://www.techterms.com
Techopedia
Techopedia
Techopedia technology dictionary. (n.d.). Retrieved fromhttps://www.techopedia.com/ dictionary
TechTarget
TechTarget Network
TechTarget network. (n.d.). Retrieved from http://www.techtarget.com/network
WebopediaWebopedia
Webopedia. (n.d.). Retrieved from http://www.webopedia.com
Wikipedia
Wikipedia
Wikipedia: The free encyclopedia. (n.d.). Retrieved fromhttps://www.wikipedia.org/
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