Do instrumentation tools capture self-regulated learning?

Joep Van Der Graaf, Lyn Lim, Yizhou Fan, Jonathan Kilgour, Johanna Moore, Maria Bannert, Dragan Gasevic, Inge Molenaar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations

Abstract

Researchers have been struggling with the measurement of Self-Regulated Learning (SRL) for decades. Instrumentation tools have been proposed to help capture SRL processes that are difficult to capture. The aim of the present study was to improve measurement of SRL by embedding instrumentation tools in a learning environment and validating the measurement of SRL with these instrumentation tools using think aloud. Synchronizing log data and concurrent think aloud data helped identify which SRL processes were captured by particular instrumentation tools. One tool was associated with a single SRL process: the timer co-occurred with monitoring. Other tools co-occurred with a number of SRL processes, i.e., the highlighter and note taker captured superficial writing down, organizing, and monitoring, whereas the search and planner tools revealed planning and monitoring. When specific learner actions with the tool were analyzed, a clearer picture emerged of the relation between the highlighter and note taker and SRL processes. By aligning log data with think aloud data, we showed that instrumentation tool use indeed reflects SRL processes. The main contribution is that this paper is the first to show that SRL processes that are difficult to measure by trace data can indeed be captured by instrumentation tools such as high cognition and metacognition. Future challenges are to collect and process log data real time with learning analytic techniques to measure ongoing SRL processes and support learners during learning with personalized SRL scaffolds.

Original languageEnglish
Title of host publicationLAK 2021 Conference Proceedings - The Impact we Make
Subtitle of host publicationThe Contributions of Learning Analytics to Learning, 11th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages438-448
Number of pages11
ISBN (Electronic)9781450389358
DOIs
StatePublished - 12 Apr 2021
Event11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021 - Virtual, Online, United States
Duration: 12 Apr 202116 Apr 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021
Country/TerritoryUnited States
CityVirtual, Online
Period12/04/2116/04/21

Keywords

  • Instrumentation tools
  • Self-regulated learning

Fingerprint

Dive into the research topics of 'Do instrumentation tools capture self-regulated learning?'. Together they form a unique fingerprint.

Cite this