Facilitating Student Success in Introductory Chemistry with Feedback in an Online Platform

Sam Van Horne, Maura Curran, Anna Smith, John VanBuren, David Zahrieh, Russell Larsen, Ross Miller

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Instructional technologists and faculty in post-secondary institutions have increasingly adopted learning analytics interventions such as dashboards that provide real-time feedback to students to support student’ ability to regulate their learning. But analyses of the effectiveness of such interventions can be confounded by measures of students’ prior learning as well as their baseline level of self-regulated learning. For this research study, we sought to examine whether the frequency of accessing a dashboard was associated with learning outcomes after matching subjects on confounding variables. And because prior research has suggested that measures of prior learning are associated with students’ likelihood to use learning analytics interventions, we sought to adequately control for learners’ likelihood to access the feedback by using a propensity score matching with a non-binary treatment variable. We administered the Motivated Strategies for Learning Questionnaire and also collected demographic information for a propensity score matching process. Users’ frequency of accessing the intervention was categorized as High, Moderate, or Low/No usage. After matching users on characteristics associated with dashboard usage (gender, high school GPA, and the “Test Anxiety” and “Self Efficacy” factors) we found that both the “High” and “Moderate” users achieved significantly higher course grades than the “Low/No” users. The results suggest learners benefited from regularly accessing the feedback, but extreme amounts of usage were not necessary to achieve a positive effect. We discuss the implications for recommending how students use learning analytics interventions without excessively accessing feedback.

Original languageEnglish (US)
Pages (from-to)21-40
Number of pages20
JournalTechnology, Knowledge and Learning
Volume23
Issue number1
DOIs
StatePublished - Apr 1 2018

Keywords

  • Feedback
  • Learning analytics
  • Motivation
  • Propensity score matching
  • Self-regulated learners

ASJC Scopus subject areas

  • Mathematics (miscellaneous)
  • Education
  • Human-Computer Interaction
  • Computer Science Applications

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