How accurately can students evaluate the quality of self-generated examples of declarative concepts? Not well, and feedback does not help. (December 2016)

• Record Type: Journal Article
• Authors: Zamary, Amanda; Rawson, Katherine A.; Dunlosky, John
• Is Part Of: Learning and instruction. Volume 46(2016:Dec.)
• Page Start: 12
• Page End: 20
• Publication Date: 2016-12
• Subjects: Example generation -- Metacognition -- Monitoring -- Overconfidence -- Feedback; Learning -- Periodicals; Teaching -- Periodicals; Apprentissage -- Périodiques; Enseignement -- Périodiques; Learning; Teaching; Periodicals; Electronic journals; 370.1
• DOI: 10.1016/j.learninstruc.2016.08.002
• Languages: English
• ISSNs: 0959-4752

Abstract

Abstract: Students are commonly asked to learn declarative concepts in many courses. One strategy students report using involves generating concrete examples of abstract concepts. If students have difficulties evaluating the quality of their generated examples, then instructors will need to provide students with appropriate scaffolds or feedback to improve judgmentaccuracy. No prior research has investigated if students can accurately evaluate the quality of the examples they generate, which was the first aim of the current research. The second aim of this research was to investigate the extent to which providing feedback while students evaluate their generated examples can improve the accuracy of their example-quality judgments. In two experiments, students generated examples for declarative concepts from social psychology and then judged the quality of their examples. When making judgments, students received no feedback (in which they were only given the key term), full definition feedback (in which they were shown the definition of the declarative concept) or idea unit feedback (in which they first evaluated if they represented each idea unit of the definition within their example). Outcomes showed that students were overconfident when judging the quality of their examples, specifically for commission errors (i.e., examples that were entirely incorrect). Surprisingly, full definition and idea unit feedback did not help students improve the accuracy of their example-quality judgments. Thus, until scaffolds are discovered to reduce student overconfidence, instructors will need to assist in evaluating generated examples as students use this strategy to learn declarative concepts. Highlights: Students generated examples of concepts and then judged their quality. Students showed some accuracy in evaluating relative quality of examples. Students were more likely to assign full versus no credit for examples that were completely incorrect. Full definition feedback did not reduce overconfidence for examples that were completely incorrect. Idea unit feedback did not reduce overconfidence for examples that were completely incorrect.