Using analytics to transform the library agenda
Dr Linda Corrin@lindacorrin
DEFINITION
the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs
Society for Learning Analytics Research
Long P. & Siemens G. (2011) Penetrating the fog: analytics in learning and education. EDUCAUSE Review 46, 31–40. Available at: http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and-education
Micro
Meso
Macro
Buckingham Shum, S., Knight, S., & Littleton, K. (2012). Learning analytics. In UNESCO Institute for Information Technologies in Education. Policy Brief.
PossibilitiesLearning analytics
Personalised learning
Understanding the learning process
Information about the students’ context
Pedagogical and assessment improvements
Understanding student motivation and attitude
Academic analytics
IT service provision
Curriculum mapping
Review of teaching structures
Student support services
Student retention
Drachsler, H., & Greller, W. (2012). The pulse of learning analytics. Understandings and expectations from the stakeholders. In S. Buckingham Shum, D. Gasevic, & R. Ferguson (Eds.), 2nd International Conference Learning Analytics & Knowledge (pp. 120-129). April, 29-May, 02, 2012, Vancouver, BC, Canada.
Libraries and Student Success
Positive impact on grades a
Positive impact on retention b
Positive impact on grades and retention c
a. Jantti, M., & Cox, B. (2013). Measuring the value of library resources and student academic performance through relational datasets. Evidence Based Library and Information Practice, 8(2), 163-171.
b. Haddow, G. (2013). Academic library use and student retention: A quantitative analysis. Library & Information Science Research, 35(2), 127-136.c. Soria, K. M., Fransen, J., & Nackerud, S. (2014). Stacks, serials, search engines, and students' success: First-year undergraduate students' library use, academic
achievement, and retention. The Journal of Academic Librarianship, 40(1), 84-91.
LA Implementation in Australia
1. Conceptualisation
2. Capacity & culture
3. Leadership
4. Rapid innovation cycle
5. Ethics
What do libraries want/need to know?
How can learning analytics help answer these questions?
QUESTION:
Image source: https://edtechdigest.wordpress.com/2012/05/10/learning-analytics-the-future-is-now/
1. Performance
2. Effort
3. Prior academic history
4. Student characteristics
Current Research
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Current Research
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Focus Groups
Student engagement
The learning experience
Quality of teaching and curriculum
Administrative functions associated with L&T
Student performance‘At risk’ studentsAttendanceAccess to learning resourcesParticipation in communicationPerformance in assessment
Corrin, L., Kennedy, G., & Mulder, R. (2013). Enhancing learning analytics by understanding the needs of teachers. In H. Carter, M. Gosper & J. Hedberg (Eds.), Electric Dreams. Proceedings ascilite 2013 Sydney. (pp. 201-205).
Focus Groups
Student engagement
The learning experience
Quality of teaching and curriculum
Administrative functions associated with L&T
Student performance += ? (ideal student)
Corrin, L., Kennedy, G., & Mulder, R. (2013). Enhancing learning analytics by understanding the needs of teachers. In H. Carter, M. Gosper & J. Hedberg (Eds.), Electric Dreams. Proceedings ascilite 2013 Sydney. (pp. 201-205).
Focus Groups
Student engagement
The learning experience
Quality of teaching and curriculum
Administrative functions associated with L&T
Student performance
Feedback
Corrin, L., Kennedy, G., & Mulder, R. (2013). Enhancing learning analytics by understanding the needs of teachers. In H. Carter, M. Gosper & J. Hedberg (Eds.), Electric Dreams. Proceedings ascilite 2013 Sydney. (pp. 201-205).
Focus Groups
Student engagement
The learning experience
Quality of teaching and curriculum
Administrative functions associated with learning & teaching
Student performance
Greater understanding of how students develop knowledge Track prior knowledge and it’s development through learning activities Data?
Focus Groups
Student engagement
The learning experience
Quality of teaching and curriculum
Administrative functions associated with learning & teaching
Student performance
Automated textual analysis of messages sent to student support services Assessment (formative and summative) to identify areas for review Access to support resources
Focus Groups
Student engagement
The learning experience
Quality of teaching and curriculum
Administrative functions associated with learning & teaching
Student performance
Assessment of consistency of student placements Enrolment and profiling of tutorial groups Tracking safety requirements for field trips Guidance for students on future subject selection
Interviews
Interviews with 12 teaching academics (UoM, Macquarie, UniSA)
1. Fairly basic analytics requests
2. Focus on engagement analytics
3. Limited use of technological tools (blended)
4. Concerns over ability to interpret data
Kennedy, G., Corrin, L., Lockyer, L., Dawson, S., Williams, D., Mulder, R., Khamis, S., & Copeland, S. (2014). Completing the loop: returning learning analytics to teachers. In B. Hegarty, J. McDonald, & S.-K. Loke (Eds.), Rhetoric and Reality: Critical perspectives on educational technology. Proceedings ascilite Dunedin 2014 (pp. 436-440).
Loop
Loop
Loop
Learning Design
“Learning design provides a semantic
structure for analytics” Mor, Ferguson & Wasson, 2015
“a documentation of pedagogical intent”
Lockyer, Heathcote & Dawson, 2013
Interaction with resources
Hadwin, A. F., Nesbit, J. C., Jamieson-Noel, D., Code, J., & Winne, P. H. (2007). Examining trace data to explore self-regulated learning. Metacognition and Learning, 2(2-3), 107-124.
GIVING THE DATA TO STUDENTS…
Student Perspectives“I just log into the [LMS] to download learning materials
and print them. I do not think my online learning behaviours such as log-ins would reflect my general
efforts for learning and learning outcomes”
Park, Y., & Jo, I. H. (2015). Development of the Learning Analytics Dashboard to Support Students' Learning Performance. Journal of Universal Computer Science, 21(1), 110-133.
Plan learning schedule
Manage learning processes
Set learning goals
Get an objective and accurate perspective
Do not want such data to impact final score and grade
Student Dashboards
Corrin, L., & de Barba, P. (2014). Exploring students’ interpretation of feedback delivered through learning analytics dashboards. In B. Hegarty, J. McDonald, & S.-K. Loke (Eds.), Rhetoric and Reality: Critical perspectives on educational technology. Proceedings ascilite Dunedin 2014 (pp. 629-633).
JISC Student Learning Analytics App
Source: Sclater, N. (2015) What do students want from a learning analytics app?. http://analytics.jiscinvolve.org/wp/2015/04/29/what-do-students-want-from-a-learning-analytics-app/
Situation Theory Question Data Representation Timing
Situation Theory Question Data Representation Timing
Planning for Libraries
melbourne-cshe.unimelb.edu.au© Melbourne Centre for the Study of Higher Education, The University of Melbourne
2016
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