Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning

Danny Kostons, Tamara Van Gog, Fred Paas

    Research output: Contribution to journalArticleAcademicpeer-review


    For self-regulated learning to be effective, students need to be able to accurately assess their own performance on a learning task and use this assessment for the selection of a new learning task. Evidence suggests, however, that students have difficulties with accurate self-assessment and task selection, which may explain the poor learning outcomes often found with self-regulated learning. In experiment 1, the hypothesis was investigated and confirmed that observing a human model engaging in self-assessment, task selection, or both could be effective for secondary education students’ (N = 80) acquisition of selfassessment and task-selection skills. Experiment 2 investigated and confirmed the hypothesis that secondary education students’ (N = 90) acquisition of self-assessment and task-selection skills, either through examples or through practice, would enhance the effectiveness of self-regulated learning. It can be concluded that self-assessment and task-selection skills indeed play an important role in selfregulated learning and that training these skills can significantly increase the amount of knowledge students can gain from self-regulated learning in which they choose their own learning tasks.
    Original languageEnglish
    Pages (from-to)121-132
    Number of pages12
    JournalLearning and Instruction
    Issue number2
    Early online date15 Sep 2011
    Publication statusPublished - Apr 2012


    • Self-regulated learning
    • Self-assessment
    • Task selection
    • Example-based learning


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