Write-and-learn: Promoting meaningful learning through concept map-based formative feedback on writing assignments

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

1 Scopus citations

Abstract

A primary goal of higher education is to promote meaningful learning: the delivery of core academic content to students in innovative ways that allow them to learn and then apply what they have learned. As a pedagogical strategy, Writing-to-Learn (WTL) intends to use writing to improve students' understanding of course content and concepts. To improve students' meaningful learning of conceptual knowledge in WTL activities, the project proposes to develop the Write-and-Learn system to generate automated formative feedback by taking advantage of the concept maps constructed from instructors' lecture notes and individual students' writing assignments. The proposed research aims to provide insights into how to apply concept maps into WTL activities to generate effective formative feedback on the acquisition and development of conceptual knowledge, and explore how and to what extent concept map-based formative feedback can be utilized to scaffold and promote meaningful learning in WTL activities.

Original languageEnglish (US)
Title of host publicationLAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference
Subtitle of host publicationUnderstanding, Informing and Improving Learning with Data
PublisherAssociation for Computing Machinery
Pages552-553
Number of pages2
ISBN (Electronic)9781450348706
DOIs
StatePublished - Mar 13 2017
Event7th International Conference on Learning Analytics and Knowledge, LAK 2017 - Vancouver, Canada
Duration: Mar 13 2017Mar 17 2017

Publication series

NameACM International Conference Proceeding Series

Other

Other7th International Conference on Learning Analytics and Knowledge, LAK 2017
Country/TerritoryCanada
CityVancouver
Period3/13/173/17/17

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Keywords

  • Automated formative feedback
  • Concept mapping
  • Natural language processing
  • Writing-to-Learn

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