Spacing, Feedback, and Testing Boost Vocabulary Learning in a Web Application
| Autor: | Angelo Belardi, Salome Pedrett, Nicolas Rothen, Thomas P. Reber |
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| Rok vydání: | 2020 |
| Předmět: |
Vocabulary
media_common.quotation_subject online learning Distance education Context (language use) computer.software_genre language learning Multimodality memory CALL (Computer Assisted Language Learning) Psychology Web application General Psychology Original Research media_common business.industry web application Language acquisition vocabulary learning BF1-990 distance education distance learning Principles of learning Corrective feedback Artificial intelligence business computer Natural language processing |
| Zdroj: | Frontiers in Psychology, Vol 12 (2021) Frontiers in Psychology |
| DOI: | 10.31234/osf.io/yqsrx |
| Popis: | Information and communication technology (ICT) becomes more prevalent in education but its general efficacy and that of specific learning applications are not fully established yet. One way to further improve learning applications could be to use insights from fundamental memory research. We here assess whether four established learning principles (spacing, corrective feedback, testing, and multimodality) can be translated into an applied ICT context to facilitate vocabulary learning in a self-developed web application. Effects on the amount of newly learned vocabulary were assessed in a mixed factorial design (3×2×2×2) with the independent variables Spacing (between-subjects; one, two, or four sessions), Feedback (within-subjects; with or without), Testing (within-subjects, 70 or 30% retrieval trials), and Multimodality (within-subjects; unimodal or multimodal). Data from 79 participants revealed significant main effects for Spacing [F(2,76) = 8.51, p = 0.0005, ηp2=0.18] and Feedback [F(1,76) = 21.38, p < 0.0001, ηp2=0.22], and a significant interaction between Feedback and Testing [F(1,76) = 14.12, p = 0.0003, ηp2=0.16]. Optimal Spacing and the presence of corrective Feedback in combination with Testing together boost learning by 29% as compared to non-optimal realizations (massed learning, testing with the lack of corrective feedback). Our findings indicate that established learning principles derived from basic memory research can successfully be implemented in web applications to optimize vocabulary learning. |
| Databáze: | OpenAIRE |
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