JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN...

75
JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach

Transcript of JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN...

Page 1: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

JANE COOKLITERACY & TECHNOLOGY COACH

EASTCONN BETH MCCAFFERY

SCHOOL IMPROVEMENT COORDINATORLEARN

Data Driven Decision Making

and The Data Coach

Page 2: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Purpose

To highlight characteristics of high quality coaching practices and review the roles of a Data Coach

To review the coaching process and learn tools to use as a Data Coach to improve Data Driven Decision Making (DDDM)

To develop an action plan for implementing data coaching practices to support DDDM

Page 3: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Participants Will:

Identify the roles and responsibilities of a coach and effective models for coaching.

Apply coaching behaviors that influence best practices. (***triad activity from NSDC last day)

Examine the research based on coaching that supports DDDM.

Page 4: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Questions To Consider

What is an effective Data Coach? What is the theory behind data coaching? What do effective Data Coaches do? What tools can Data Coaches employ to help

educators use data to inform curriculum, instruction and assessment?

Page 5: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Why Data Coaches?

Data coaches assist Data Teams in using data and in applying the DDDM process to make high quality, informed decisions that will lead to increased student achievement.

Page 6: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

What are the characteristics of an effective Data Coach?Directions: • Individually write 5 characteristics that an effective coach

should possess. ***Develop Reflection Sheet for handout)• Share your response with another person.• Join another partner group to form a group of four• Select 5 distinct responses to the question.• Write each response on sentence strips.• Place responses on chart paper posted around the room

and have participants do an Affinity Diagram. ***Jane will post directions on Wiki

• Summarize the results gathered by the coaches.

Page 7: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

*** Start Here Effective Coaching

The gradual release of responsibility- from coach to teacher- is key to effective coaching.

Page 8: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Points To Ponder

The coach’s major role is to provide professional development and support to teachers to improve classroom instruction.

This typically involves organizing school wide professional development and then structuring in-class training, which includes demonstrations, modeling, support for teacher trials of new instruction, and coaching feedback.

(“Literacy Coaching For Change,” Association for Supervision and Curriculum Development. EDUCATIONAL LEADERSHIP MARCH 2005. Camille L. Z. Blachowicz, Connie Obrochta, and Ellen Fogelberg.

Page 9: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Text Rendering Protocol

Read through the text completely.

Note those passages that stand out for you.

Mark the sentence, the phrase, and the word that hold particular significance for you.

Page 10: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Text Rendering Protocol Cont’d

Each person shares a sentence from the document that he/she thinks/feels is particularly significant. Explain to the group why he/she marked the sentence.

Each person shares a phrase that he/she thinks/feels is particularly significant. Explain to the group why he/she marked the phrase.

Each person shares the word that he/she thinks/feels is particularly significant. Explain to the group why he/she marked the word.

Page 11: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Take A Look

Look at the sentences, phrases, and words that were chosen:

What do you notice? Any commonalities in the reflections about the text?

What came up for you during the conversations? What are your “take-aways” from this text?

Page 12: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

REFLECTION

Discuss what you heard and what it says about the document.

Share the words that emerged and any new insights about the document.

Page 13: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Coaching’s Big Four

Classroom ManagementContentInstructional PracticesAssessment for learning

Jim Knight

Page 14: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Isolation or Collaboration?

Collaborative lesson planning leads to: Consistent curricular focus Collegial support through conversations Common assessments Team problem solving Shared accountability Increased professionalism Decreased stress

Page 15: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Value of Collaboration Through Instructional Coaching

See what to avoid and/or include in our practices.

To inform lesson development and instruction. Self- assessment and self- awareness of

strengths and areas of growth. Insights into lesson development and effective

teaching strategies.

Page 16: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

NEEDS For Coaching Collaboration

Committed teacher and coach working together Time Agreed upon ground rules and structures Examine Lesson/ Unit plans together Protocols: the structure for conversation,

timeframe, guidelines, open and honest dialogue, build team culture and skills

Page 17: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Coaching Protocols

Observing Planning Monitoring Feedback Reflecting

Page 18: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Collaborate on lesson/ unit plans using template.

To inform instruction To ensure lessons incorporate ETS more

frequently Used by teacher and coach pre and post lesson Follow Norms Follow a Structure Helps us break down isolation

Collaborative Lesson Planning Protocol

Page 19: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Elements of Lesson Plans

Effective lesson plans: Offer ‘prompts’ or cues for focused thinking Allow linear and/or flexible options Feel like a ‘flight plan’ Consider multiple aspects of learning cycle

Page 20: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Pre-lesson Conference and Effective Teaching Strategies

Procedure/Lesson Overview (Specify the steps of the lesson)

Decide the stage of learning- Are you introducing new knowledge or do you want the students to practice, review, and apply knowledge already taught?

Page 21: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Note: Include at least one kinesthetic activity in your lesson plans for a unit.

Ensure that the lesson includes the following components of Effective Teaching Strategies based on the specific stage and purpose of learning within the lesson:

 

Page 22: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

What will I do to help students interact with new knowledge?

Page 23: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Anticipatory set Activate thinking Access prior knowledge Build background Make connections, scaffold Write

To Introduce New Knowledge:

Page 24: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

To practice, review, and apply knowledge

Develop ideas, new learning Read for information Write to clarify understanding Direct instruction Model Guided Practice Question Connect relevance, authenticity

Page 25: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Practice, Review, & Apply (cont’d)

Summarize Develop conclusions Elevate applications, thinking Produce evidence of understanding Solve problems, investigate Do something relevant with new information

Page 26: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Categories of Instructional Unit Activities

Select strategies based on the specific stage and purpose of learning:

Beginning of a unit.

During a unit.

End of a unit.

Page 27: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Beginning Stages of the Lesson Plan

Beginning: (Activate prior knowledge. Provide background information. How will students be hooked?)

Set Objectives Provide feedback Questions, cues, advanced organizers Cooperative Learning Identifying similarities and differences

Page 28: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Beginning of a Unit

A unit of instruction should begin with at least two activities:

1. Identifying clear learning goals.

2. Allowing students to identify and record their own learning goals.

Goals should be relatively specific BUT flexible enough to allow students to identify more specific personal learning goals.

Page 29: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

During a Unit

Once goals have been established, instructional strategies have great value throughout a unit of instruction.

Three broad categories: 1. Introducing new knowledge 2. practicing, reviewing, and applying

knowledge. 3. monitoring learning goals.

Page 30: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

During the Lesson

During: (What strategies and activities will be used to support the teaching objectives? How will students receive feedback on their progress?)

Nonlinguistic representation Note taking and summarizing Questions, cues, advanced organizers Cooperative Learning

Page 31: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

End of Unit

A unit of instruction should begin with a focus on learning goals ---AND it should end with that focus as well.

Page 32: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

End of Lesson

End: (Tie new knowledge to existing knowledge and future knowledge, Reflect, Evaluate)

Reinforce effort Provide recognition Summarize Evaluate Self-Assessment

Page 33: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Activities to provide focus at end of unit

Give students clear assessments of their progress on each learning goal.

Have students assess themselves on each learning goal and compare these assessments with those of the teacher.

Have students articulate what they have learned about the content and about themselves as learners.

Page 34: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Lesson Plan Checklist

(Include this here) NEED TO DEVELOP THIS or- Use TAKE THE

LEAD with copyright permission.(get copyright permission)

OR NANCY BOYLES GUIDELINES FOR COACHES AND ADMINISTRATORS– ask for copyright permission.

Page 35: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Stages of Instructional Coaching

Planning Conference Observation Modeling Co-teaching Gradual release Reflection

Page 36: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

STEPS FOR COACHING

Build relationships Help teachers request your service (JK tool) with an

identified need or area of concern. Pre- lesson Observation of classroom Feedback Model lesson Feedback Post modeled lesson Co-teach Feedback Reflection

Page 37: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Planning conference

The teacher and coach confer to:• Clarify learning goals• Anticipate the tasks or work the students will

complete to achieve the intended outcomes• Establish evidence of student achievement• Identify student or teacher behaviors the coach

should observe• Reach a common agreement on the role the

teacher and the coach will perform during the delivery of the lesson.

Page 38: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

In class support

The teacher and the coach collaborate in the delivery of the planned lesson through these activities:

Observation Demonstration lesson co-teaching Gradual release of responsibility from coach to

teacher

Page 39: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Observe The Classroom

Page 40: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Classroom Check-up Feedback Form

Time on Task Opportunities toRespond (OTR)

Ratio of Interactions Disruptions Daily Reality Scale

Teacher: ____________________

Conference date: ____/____/____

Goal area(s):_________________________________

Intervention(s): _______________________________________________________________________________________

_____________________________________________________________________________________________________

_____________________________________________________________________________________________________

_____________________________________________________________________________________________________

Page 41: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Debriefing/ Feedback

The teacher and the coach meet to discuss: Overall outcomes of the lesson Degree to which students have mastered the

learning outcomes Effective Teaching Strategies used by the

coach/teacher (depending on if observation, model lesson, & or co-teaching stage)

Instructional decisions the teacher made during the lesson

Page 42: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Feedback

Goal of feedback is to improve current situations without criticizing or offending.

Should be: Descriptive rather than Evaluative (visible) Specific instead of general Given only when requested Given as soon as possible to the situation Focused on realistic options change Positive with the intent to help the presenter

Page 43: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

WARMWARM COOLCOOL

SupportiveStrength orientedFocus on solutionsPromotes positive

learning

ImpersonalNeeds orientedFocus on the

problemProvides

constructive criticism

Warm V. Cool Feedback

Page 44: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Questions to Ask When Debriefing

What do you see? What is the focus on learning goals? What standard is being used and are the

procedures and assignments appropriate? How will the student achieve according to the

standard being addressed? What questions are being asked? Does the lesson end with the focused learning

goals?

Page 45: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Cont’d

What ETS do you see incorporated in the lesson? What needs do you see? What suggestions do you have for teaching this

standard? How can we support the teacher for future student

learning? Do you see any connections to what you may be

teaching in your content area? How can you work together to incorporate

collaboration on this lesson?

Page 46: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Cont’d

What did you learn about incorporating ETS in this lesson?

What did you learn about this teacher’s lesson from this session?

Page 47: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Reflection

The teacher and the coach independently and systematically reflect on how their collaborative work fosters the development of the student’s understanding.

Do this on ongoing basis to go back and re-examine goals so that the cycle can begin again in order to

Create continuity and sustainability.

Page 48: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Questions to Foster Reflection

A few simple questions can serve as a guide and a springboard for reflection and self-assessment:

What was I trying to accomplish? How did I go about completing the lesson and

solving problems I had along the way (process)? What did I do well (strengths)? What did I have difficulty with (weaknesses)? What have I learned/what would I do differently?

Page 49: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

1. SIMILARITIES AND DIFFERENCES2. SUMMARIZING AND NOTE TAKING

3. REINFORCING EFFORT AND PROVIDING RECOGNITION

4. HOMEWORK AND PRACTICE5. NONLINGUISTIC REPRESENTATION

6. COOPERATIVE LEARNING7. SETTING GOALS AND PROVIDING FEEDBACK

8. GENERATING AND TESTING HYPOTHESIS9. QUESTIONS, CUES, AND ADVANCED ORGANIZERS

10. NON-FICTION WRITING

Review of Effective Teaching Strategies

Page 50: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Classroom Instruction that Works

Marzano and Pickering’s Meta-analysis : - Results of over 35 years of educational

research to determine average effect of the most effective teaching strategies.

Page 51: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Figure 1.3Categories of Instructional Strategies That Affect Student Achievement

CategoryAvg.Effect

SizePercentile

GainNumber of

ESsStandard

Deviation (SD)Identifying similaritiesand differences

1.61 45 31 .31

Summarizing and notetaking

1.00 34 179 .50

Reinforcing effort andproviding recognition

.80 29 21 .35

Homework and practice .77 28 134 .36Nonlinguisticrepresentations

.75 27 246 .40

Cooperative learning .73 27 122 .40Setting objectives andproviding feedback

.61 23 408 .28

Generating and testinghypotheses

.61 23 63 .79

Questions, cues andadvance organizers

.59 22 1,251 .26

Note: We caution readers that is is impossible to derive the average effect sizes show in thisfigure from the effect-size information provided in the figures in Chapter 2-10, which list thesynthesis studies used in the analysis of the instructional strategy under discussion.

Classroom Instruction that Works, Marzano

Page 52: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

COGNITIVE STRATEGIESACADEMIC STRATEGIES

MOTIVATIONAL STRATEGIES

Categories of Strategies

Page 53: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Cognitive Strategies

Identifying Similarities/Differences

Nonlinguistic Representations

Generating and Testing Hypotheses

Page 54: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Processes Students Can Engage In To Identify Similarities & Differences

COMPARING: Identifying similarities & differences between or among things or ideas.

Comparison Matrix, Venn Diagram, Double Cluster

CLASSIFYING: Grouping things that are alike into categories based on their characteristics.

T-Chart, Tree or Column

CREATING ANALOGIES: Identifying relationships between pairs of concepts.

(Relationships between relationships) ___:___::___:___ CREATING METAPHORS: Identifying a general pattern in a

specific topic then finding another topic that is different, but has the same general pattern.

Page 55: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Nonlinguistic Representations

A variety of activities produce nonlinguistic representations.

Creating graphic representations. Generating mental pictures. Drawing pictures and pictographs. Engaging in kinesthetic activity.

Nonlinguistic representations should elaborate on knowledge.

Page 56: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Generating and Testing Hypotheses

Deductive thinking requires students to apply current knowledge to make a prediction about a future action or event.

Inductive thinking involves students in a process of drawing new conclusions based on information they know or have presented to them.

Teachers should ask students to clearly explain their hypotheses and their conclusions. Research has shown the power of asking students to explain, in a variety of communication modes, their predictions and results

Page 57: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Academic Strategies

Summarizing and Note Taking

Homework and Practice

Cues, Questions and Advance Organizers (Activating Prior Knowledge)

Page 58: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Summarizing

To effectively summarize, students must delete some information, substitute some information and keep some information. (KEEP, DELETE, SUBSTITUTE)

To effectively delete, substitute, and keep information, students must analyze the information at a fairly deep level.

Being aware of the explicit structure of information is an aid to summarizing information.

Page 59: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Summarizing (cont’d) Use summary frames to highlight the important elements of specific

patterns commonly found in text and to help front load student thinking.

Summary frames are beneficial to teachers because it gives them an opportunity to have class participation that is specific to key information students gather as they move through the text.

There are six summary frames: Narrative, Topic-Restriction-Illustration, Definition, Argumentation,

Problem/Solution, Conversation

Page 60: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Note Taking

Verbatim is the least effective way to take notes.

Notes should be considered a work in progress.

Notes should be used as study guides for tests.

The more notes that are taken, the better.

Page 61: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Homework

Less homework should be assigned to younger students than to older students. ( suggestion-10 minutes per grade level)

Parent involvement in homework should be kept to a minimum.

The purpose of homework should be identified and articulated and should not be new skill.

If homework is assigned, it should be commented on.

Page 62: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Practice

Mastering a skill requires a fair amount of focused practice. (24 repetitions equal 80% mastery of a skill)

While practicing, students should adapt and shape what they have learned.

Page 63: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Cues and Questions

Cues and questions should focus on what is important as opposed to what is unusual.

"Higher level" questions produce deeper learning than lower level questions.

"Waiting" briefly before accepting responses from students increases the depth of student answers.

Questions are effective learning tools even when asked before a learning experience.

Page 64: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Advance Organizers

Advance Organizers should focus on what is important as opposed to what is unusual.

"Higher level" advance organizers produce deeper learning than the "lower level" advance organizers.

Advance Organizers are most useful with information that is not well organized.

Different types of advanced organizers produce different results.

Page 65: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Motivational Strategies

Reinforcing Effort and Providing Recognition

Cooperative Learning

Setting Objectives and Providing Feedback

Page 66: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Reinforcing Effort

People generally attribute success at any given task to one of four causes: ability, effort, other people and luck.

Not all students realize the importance of believing in effort.

Students can learn to change their beliefs to an emphasis on effort.

Without HOPE there will be no EFFORT

Page 67: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Providing Recognition

Rewards do not necessarily have a negative effect on intrinsic motivation.

Reward is most effective when it is contingent on the attainment of some standard of performance.

Abstract symbolic recognition is more effective than tangible rewards.

Page 68: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Cooperative Learning

Organizing groups based on ability should be done sparingly.

Cooperative groups should be kept small in size.

Cooperative learning should be applied consistently and systematically, but not overused.

Five Defining Elements-

Page 69: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Five Defining Elements of Cooperative Learning

1. Positive interdependence: a sense of sink or swim together.

2. Face-to-face interaction: helping each other learn, applauding success and efforts.

3. Individual and group accountability: each of us has to contribute to the group achieving its goals.

4. Interpersonal and small group skills: communication, trust, leadership, decision making, and conflict resolution.

5. Group processing : reflecting on how well the team is functioning and how to function even better.

Page 70: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Setting Objectives Instructional goals/objectives narrow what

students focus on. Instructional goals/objectives should not be too

specific. Students should be encouraged to personalize the

teacher's goals.

Page 71: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Providing Feedback

Feedback should be "corrective" in nature by explaining to students what they are doing correctly and incorrectly.

Feedback should be specific to a criterion. Feedback should be timely. Students can effectively provide some of their own

feedback.

Page 72: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Questions, Cues

These strategies help students access what they already know about a topic

Activation of prior knowledge is critical to all types of learning and learners

Prior knowledge influences new learning

Page 73: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Reflection

What worked well? What did we learn? Did our conversations lead us closer to our

goals? How? Did we focus on the lesson or on other issues? Did we do what we set out to do? How can we improve on this to make coaching

collaborating on lesson plans more significant part of our work?

Page 74: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

Your Feedback

Please take the time to complete the feedback form provided.

Make sure you have signed the CALI sign- in sheet before you leave (if you have not done so already).

Page 75: JANE COOK LITERACY & TECHNOLOGY COACH EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR LEARN Data Driven Decision Making and The Data Coach.

This power point was adapted from Robert Marzano.