Repairing Errors with Elaborative Feedback in Computerised Learning Environments
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| Title: | Repairing Errors with Elaborative Feedback in Computerised Learning Environments |
|---|---|
| Language: | English |
| Authors: | Tomás Martínez (ORCID |
| Source: | Journal of Computer Assisted Learning. 2026 42(2). |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Error Correction, Feedback (Response), Computer Uses in Education, Multiple Choice Tests, Automation, Performance, Learning Processes, Student Needs, Problem Solving, Computer Assisted Testing, Instructional Effectiveness |
| DOI: | 10.1002/jcal.70199 |
| ISSN: | 0266-4909 1365-2729 |
| Abstract: | Background: Although automatic elaborative feedback (EF) is effective for teaching conceptual learning in science, there is insufficient evidence on how to adapt it in computer-based question-answering activities. Objectives: This study aims to examine how we can make automatic EF more effective and tailored according to the knowledge revision process proposed in studies with refutative texts. Methods: Students were required to read a science text and then answer a series of inferential multiple-choice questions. After each answer, students received corrective feedback (right/wrong) plus automatic EF, according to their experimental condition, and then had a second attempt to answer. Three types of EFs were compared: one focused on elaborating the correct answer (EF[subscript Explicative]), another focused on correcting incorrect ideas (EF[subscript Refutative]), and another contained a neutral message (NF[subscript Control]). Two studies were conducted, one without text access while responding after EF, and the other with access to the text. Results and Conclusions: The results of both studies show that EF[subscript Explicative] is more difficult to process than EF[subscript Refutative], although the effects on performance on a second response attempt varied between studies. When the text was unavailable, EF[subscript Refutative] produced a significantly higher proportion of correct responses than EF[subscript Explicative], and both groups performed better than NF[subscript Control]. Nevertheless, when the text was available, these results were partially attenuated. After discovering errors in their learning process, learners tend to initiate a revision of their knowledge. Feedback that is congruent with this revision process was found to increase efficiency. |
| Abstractor: | As Provided |
| Notes: | https://osf.io/wk28s |
| Entry Date: | 2026 |
| Accession Number: | EJ1500517 |
| Database: | ERIC |
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