Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning
Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning pe...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-12-01
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| Series: | Frontiers in Artificial Intelligence |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2021.780131/full |
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| author | Thomas Wilschut Thomas Wilschut Florian Sense Maarten van der Velde Maarten van der Velde Zafeirios Fountas Sarah C. Maaß Sarah C. Maaß Sarah C. Maaß Hedderik van Rijn Hedderik van Rijn |
| author_facet | Thomas Wilschut Thomas Wilschut Florian Sense Maarten van der Velde Maarten van der Velde Zafeirios Fountas Sarah C. Maaß Sarah C. Maaß Sarah C. Maaß Hedderik van Rijn Hedderik van Rijn |
| author_sort | Thomas Wilschut |
| collection | DOAJ |
| description | Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in word learning where spoken instead of typed input is used. Here we present a framework for speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes. We extend earlier findings demonstrating that a response-time based adaptive learning approach outperforms an accuracy-based, Leitner flashcard approach in learning efficiency (demonstrated by higher average accuracy and lower response times after a learning session). In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner’s pronunciations. We discuss the implications for our approach for the development of educationally relevant, adaptive speech-based learning applications. |
| first_indexed | 2024-12-19T02:31:32Z |
| format | Article |
| id | doaj.art-5c3fa4532c6a4cb89e3301638d862b05 |
| institution | Directory Open Access Journal |
| issn | 2624-8212 |
| language | English |
| last_indexed | 2024-12-19T02:31:32Z |
| publishDate | 2021-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj.art-5c3fa4532c6a4cb89e3301638d862b052022-12-21T20:39:36ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122021-12-01410.3389/frai.2021.780131780131Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based LearningThomas Wilschut0Thomas Wilschut1Florian Sense2Maarten van der Velde3Maarten van der Velde4Zafeirios Fountas5Sarah C. Maaß6Sarah C. Maaß7Sarah C. Maaß8Hedderik van Rijn9Hedderik van Rijn10Department of Experimental Psychology, University of Groningen, Groningen, NetherlandsDepartment of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, NetherlandsDepartment of Experimental Psychology, University of Groningen, Groningen, NetherlandsDepartment of Experimental Psychology, University of Groningen, Groningen, NetherlandsDepartment of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, NetherlandsEmotech Ltd, London, United KingdomDepartment of Experimental Psychology, University of Groningen, Groningen, NetherlandsDepartment of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, NetherlandsAging and Cognition Research Group, DZNE, Magdeburg, GermanyDepartment of Experimental Psychology, University of Groningen, Groningen, NetherlandsDepartment of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, NetherlandsMemorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in word learning where spoken instead of typed input is used. Here we present a framework for speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes. We extend earlier findings demonstrating that a response-time based adaptive learning approach outperforms an accuracy-based, Leitner flashcard approach in learning efficiency (demonstrated by higher average accuracy and lower response times after a learning session). In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner’s pronunciations. We discuss the implications for our approach for the development of educationally relevant, adaptive speech-based learning applications.https://www.frontiersin.org/articles/10.3389/frai.2021.780131/fulladaptive learningmemorypronunciationspeechreaction times (RT)ACT-R |
| spellingShingle | Thomas Wilschut Thomas Wilschut Florian Sense Maarten van der Velde Maarten van der Velde Zafeirios Fountas Sarah C. Maaß Sarah C. Maaß Sarah C. Maaß Hedderik van Rijn Hedderik van Rijn Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning Frontiers in Artificial Intelligence adaptive learning memory pronunciation speech reaction times (RT) ACT-R |
| title | Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning |
| title_full | Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning |
| title_fullStr | Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning |
| title_full_unstemmed | Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning |
| title_short | Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning |
| title_sort | benefits of adaptive learning transfer from typing based learning to speech based learning |
| topic | adaptive learning memory pronunciation speech reaction times (RT) ACT-R |
| url | https://www.frontiersin.org/articles/10.3389/frai.2021.780131/full |
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