How patterns of students dashboard use are related to their achievement and self-regulatory engagement

Fatemeh Salehian Kia, Stephanie D. Teasley, Marek Hatala, Stuart A. Karabenick, Matthew Kay

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

2 Scopus citations

Abstract

The aim of student-facing dashboards is to support learning by providing students with actionable information and promoting selfregulated learning. We created a new dashboard design aligned with SRL theory, called MyLA, to better understand how students use a learning analytics tool. We conducted sequence analysis on students' interactions with three different visualizations in the dashboard, implemented in a LMS, for a large number of students (860) in ten courses representing different disciplines. To evaluate different students' experiences with the dashboard, we computed chi-squared tests of independence on dashboard users (52%) to find frequent patterns that discriminate students by their differences in academic achievement and self-regulated learning behaviors. The results revealed discriminating patterns in dashboard use among different levels of academic achievement and self-regulated learning, particularly for low achieving students and high self-regulated learners. Our findings highlight the importance of differences in students' experience with a student-facing dashboard, and emphasize that one size does not fit all in the design of learning analytics tools.

Original languageEnglish (US)
Title of host publicationLAK 2020 Conference Proceedings - Celebrating 10 years of LAK
Subtitle of host publicationShaping the Future of the Field - 10th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages340-349
Number of pages10
ISBN (Electronic)9781450377126
DOIs
StatePublished - Mar 23 2020
Externally publishedYes
Event10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020 - Frankfurt, Germany
Duration: Mar 23 2020Mar 27 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020
CountryGermany
CityFrankfurt
Period3/23/203/27/20

Keywords

  • Academic achievement
  • Self-regulated learning
  • Sequential pattern mining
  • Student-facing dashboard

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'How patterns of students dashboard use are related to their achievement and self-regulatory engagement'. Together they form a unique fingerprint.

Cite this