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The Assessment of Self-Regulated Learning: Where We Are Today

Centre for Information Technology in Education

Qiang Hao, Research AssistantFaculty of Education, The University of Hong Kong

Dr. Jingyan Lu, Assistant ProfessorFaculty of Education, The University of Hong Kong

• What is Self-Regulated Learning (SRL)?


Purpose

Purpose


Learning task selection


Purpose




Python

Purpose



Purpose



Purpose


1. Read it first.2. Read and code at

the same time.3. Read, code, and

apply solution to real life problems…


Purpose


1. Read it first.2. Read and code at

the same time.3. Read, code, and

apply solution to real life problems…

Learning strategy adoption


Purpose


1. Make Schedule2. No sleep at the wrong time3. No game playing at the wrong time4. Finish all the listed learning tasks…


Purpose


1. Make Schedule2. No sleep at the wrong time3. No game playing at the wrong time4. Finish all the listed learning tasks…


Self-Control

Purpose





Self-Control

Purpose





Self-Control

Self-evaluation

Self-reflection

Purpose



Purpose



Purpose



Purpose





Self-Control

Self-evaluation

Self-reflection

Purpose





Self-Control

Self-evaluation

Self-reflection

Assessment

Purpose

• The study aims at a systematic review of the development of technology-supported assessment of SRL.


Purpose

• The study aims at a systematic review of the development of technology-supported assessment of SRL.

• Widely-used methodologies

• Innovative methodologies


Widely-used methodologies



• Self-report surveys

1. Motivated Strategies for Learning Questionnaire (Pintrich, Smith, Garcia, & McKeachie, 1993)

2. Self-Regulated Learning Interview Scale ( Zimmerman & Martinez-Pons, 1989)

3. Microanalytic Methodology (Kitsantas & Zimmerman, 2002)









Motivation Learning Strategy





Motivation Learning Strategy

Scale: from “not at all” to “very true of me”











Problem-solving context









ForethoughtPerformanceSelf-reflection


Innovative methodologies



1. Trace Measure (Winne, Nesbit, Kumar, Hadwin, Lajoie, Azevedo, 2006)

2. Model Tracing (Aleven et al., 2010)

3. Computerization of self-evaluation measure (Hudesman, Carson, Flugman, Clay, & Isaac, 2011)







Take notesText highlightingInformation searchingCommunication with others









Human action Model





Human action Model

Help seeking







Mandatory Report

Comparison with actual performance







Reference

Aleven, V., Roll, I., McLaren, B. M., Koedinger, K. R. (2010). Automated, Unobtrusive, Action-by-Action Assessment of Self-Regulation during Learning with an Intelligent Tutoring System. Educational Psychologist, 45(4), 224-233.

Hudesman, J., Carson, M., Flugman, B., Clay, D. & Isaac, S. (2011). The Computerization of the Self-Regulated Learning Assessment System: A Demonstration Program in Developmental Mathematics. Retrieved from Internet: The 9th International Conference on Education and Information Systems, Technologies and Applications: www.iiis.org/CDs2011/CD2011SCI/EISTA_2011/PapersPdf/EA659WG.pdf

Kitsantas, A., & Zimmerman, B. J. (2002). Comparing self-regulatory processes among novice, non-expert, and expert volleyball players: A microanalytic study. Journal of Applied Sport Psychology, 14, 91–105.

Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MLSQ). Educational and Psychological Measurement, 53, 801–813.

Winne, P. H., Nesbit, J. C., Kumar, V., Hadwin, A. F., Lajoie, S. P., Azevedo, R., et al. (2006). Supporting self-regulated learning with gStudy software: The learning kit project. Technology, Instruction, Cognition and Learning, 3, 105–113.

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81, 329–339.


Thanks for your attention!

Qiang Hao: [email protected]


mailto:[email protected]

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