Examining the relationship between calibration and reflection in an online discussion environment

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Calibration plays a critical role for groups to regulate future learning behaviors. There is a wealth of research on self-assessment, calibration, and metacognitive learning (e.g., Azevedo, 2009; Zimmerman, 2002), but there is a lack of research on calibration at the group level. To accurately calibrate, an accurate understanding of the assessment criteria plays an important role, and reflective activities in groups on self-assessment could provide opportunities for learners to take time thinking about their performance and correcting each other’s understanding of the criteria. This study aims to examine the relationship between learner calibration, at the group and individual levels, with their patterns of discourse in the self-reflective discussions that indicated learner understanding of the assessed items. Results show that high calibration accuracy groups had more accurate understanding of the items, while incorrect understanding in medium and low calibration accuracy groups were either ignored or agreed upon, rather than challenged.

Original languageEnglish (US)
Title of host publication14th International Conference of the Learning Sciences
Subtitle of host publicationThe Interdisciplinarity of the Learning Sciences, ICLS 2020 - Conference Proceedings
EditorsMelissa Gresalfi, Ilana Seidel Horn
PublisherInternational Society of the Learning Sciences (ISLS)
Pages1293-1300
Number of pages8
ISBN (Electronic)9781732467279
StatePublished - 2020
Event14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 - Nashville, United States
Duration: Jun 19 2020Jun 23 2020

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume3
ISSN (Print)1573-4552

Conference

Conference14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020
CountryUnited States
CityNashville
Period6/19/206/23/20

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Education

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