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Abstract This study examined putative benefits of testing and production for learning new languages. Undergraduates (N= 156) were exposed to Turkish spoken dialogues under varying learning conditions (retrieval practice, comprehension, verbal repetition) in a computer‐assisted language learning session. Participants completed pre‐ and posttests of number‐ and case‐marking comprehension, a vocabulary test, and an explicit awareness questionnaire. Controlling for nonverbal ability and pretest scores, the retrieval‐practice group performed highest overall. For number/case marking, the comprehension and retrieval‐practice groups outperformed the verbal‐repetition group, suggesting benefits of either recognition‐ or recall‐based testing. For vocabulary, the verbal‐repetition and retrieval‐practice groups outperformed the comprehension group, indicating benefits of overt production. Case marking was easier to learn than number marking, suggesting advantages for learning word‐final inflections. Explicit awareness correlated with comprehension accuracy, yet some participants demonstrated above‐chance comprehension without showing awareness. Findings indicate the value of incorporating both practice tests and overt production in language pedagogy.
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Executable Examples for Programming Problem Comprehension
Flawed problem comprehension leads students to produce flawed implementations. However, testing alone is inadequate for checking comprehension: if a student develops both their tests and implementation with the same misunderstanding, running their tests against their implementation will not reveal the issue. As a solution, some pedagogies encourage the creation of input-output examples independent of testing-but seldom provide students with any mechanism to check that their examples are correct and thorough. We propose a mechanism that provides students with instant feedback on their examples, independent of their implementation progress. We assess the impact of such an interface on an introductory programming course and find several positive impacts, some more neutral outcomes, and no identified negative effects.
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- PAR ID:
- 10111823
- Date Published:
- Journal Name:
- ICER '19 Proceedings of the 2019 ACM Conference on International Computing Education Research
- Page Range / eLocation ID:
- 131 to 139
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3291279.3339416
