Students' self‐report and observed learning orientations in blended university course design: How are they related to each other and to academic performance?

This study examines the extent to which the learning orientations identified by student self‐reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first‐year engineering undergraduates, who were enrolled in...

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Publicado en:Journal of Computer Assisted Learning Vol. 36; no. 6; pp. 969 - 981
Autores principales: Han, Feifei, Pardo, Abelardo, Ellis, Robert A.
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell Dec2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2020
      vid: 36
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1111/jcal.12453
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        atl: Students' self‐report and observed learning orientations in blended university course design: How are they related to each other and to academic performance?
      aug:
        au:
          Han, Feifei
          Pardo, Abelardo
          Ellis, Robert A.
        affil: Office of Pro‐Vice‐Chancellor (Arts, Education and Law), Griffith University, Brisbane Queensland,, Australia
      sug:
        subj:
          Student Attitudes
          Self Report
          Learning
          Course Evaluation
          Academic Performance
          Human
          Funding Source
          Cluster Analysis
          One-Way Analysis of Variance
          Students, College
          Adolescence
          Adult
          Australia
          Learning Environment
          Adolescent: 13-18 years
          Adult: 19-44 years
      ab: This study examines the extent to which the learning orientations identified by student self‐reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first‐year engineering undergraduates, who were enrolled in a blended course. Using students' self‐report on a questionnaire about their approaches to learning and perceptions of the blended learning environment, 'understanding' and 'reproducing' learning orientations were identified. Using observations of student activity online, a Hidden Markov Model (HMM) and agglomerative sequence clustering detected four qualitatively different patterns of online learning orientations. Cross‐tabulations showed significant and logical associations amongst the learning orientations derived by the self‐report and observational methods. Significant differences were also consistently found in the students' academic performance across the mid‐term and final assessments based on their learning orientations detected by both self‐report and observational methods, results which have important implications for learning research. Lay Description: What is currently known about the subject matter: Learning analytics research uses observational data to investigate learning.Students Approaches to Learning research uses self‐report data to examine learning experiences.Little research combines observational and self‐report data to investigate variations in learning outcomes. What this paper adds: This study uses both observational and self‐report data to investigate learning orientations.The learning orientations predicted mid‐ and final‐ assessment marks.Significant associations were found between learning orientations identified by observational and self‐report data. Implications for practitioners: Combining data sources enables teachers to better understand students' learning orientations.Interventions can be designed based on an understanding of different learning orientations to improve learning.The approach used in this study is transferrable to other similar research.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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