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Abstract
Two practice strategies are generally considered to be effective for acquiring problem-solving skills: worked-examples and retrieval practice. To better understand which strategy works under which conditions, we integrated two existing perspectives into one model. In that model, the optimal practice strategy depends on both the complexity of the learning task and the interval between the final practice opportunity and the test (i.e., retention interval). To test the model, we conducted a multi-classroom experiment with a 2 (Task Complexity: simple vs. complex) x 2 (Practice Strategy: worked-examples vs. retrieval practice) x 2 (Retention Interval: 5 minutes vs. 1 week) between-subjects design (N = 170). We performed a Bayesian 2 x 2 x 2 ANCOVA on participants’ problem-solving performance. Although the data provided evidence that prior mathematical knowledge and task complexity affect participants’ problem-solving performance, no evidence was found for the hypothesized interaction effects. Further analyses on the effect of practice strategy on problem-solving performance will be presented at the conference.
Original language | English |
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Publication status | Published - 23 Aug 2023 |
Event | 20th Biennial EARLI Conference: Education as a hope in uncertain times - Thessaloniki , Greece Duration: 22 Aug 2023 → 26 Aug 2023 Conference number: 20 https://www.earli.org/events/earli2023 |
Conference
Conference | 20th Biennial EARLI Conference |
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Abbreviated title | EARLI 2023 |
Country/Territory | Greece |
City | Thessaloniki |
Period | 22/08/23 → 26/08/23 |
Internet address |
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Dive into the research topics of 'Worked-Examples and Retrieval Practice in Primary School Students’ Mathematical Problem-Solving'. Together they form a unique fingerprint.Activities
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Understanding and Optimizing Effects of Retrieval Practice in Education
Obergassel, N. (Chair), Ruitenburg, S. (Chair), Camp, G. (Organiser) & Roelle, J. (Organiser)
23 Aug 2023Activity: Attending or organising an event types › Organising an event › Academic