Forgetting of Foreign-Language Skills: A Corpus-Based Analysis of Online Tutoring Software
| Autor: | Michael C. Mozer, Karl Ridgeway, Anita R. Bowles |
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| Rok vydání: | 2015 |
| Předmět: |
020205 medical informatics
Computer science Cognitive Neuroscience media_common.quotation_subject Foreign language Online tutoring Aptitude Experimental and Cognitive Psychology Multilingualism 02 engineering and technology Machine learning computer.software_genre 050105 experimental psychology Artificial Intelligence Memory 0202 electrical engineering electronic engineering information engineering Humans Learning 0501 psychology and cognitive sciences media_common Language Forgetting business.industry 05 social sciences Variance (accounting) Models Theoretical Test (assessment) Artificial intelligence Computational linguistics business computer Software Cognitive psychology |
| Zdroj: | Cognitive science. 41(4) |
| ISSN: | 1551-6709 |
| Popis: | We explore the nature of forgetting in a corpus of 125,000 students learning Spanish using the Rosetta Stone® foreign-language instruction software across 48 lessons. Students are tested on a lesson after its initial study and are then retested after a variable time lag. We observe forgetting consistent with power function decay at a rate that varies across lessons but not across students. We find that lessons which are better learned initially are forgotten more slowly, a correlation which likely reflects a latent cause such as the quality or difficulty of the lesson. We obtain improved predictive accuracy of the forgetting model by augmenting it with features that encode characteristics of a student's initial study of the lesson and the activities the student engaged in between the initial and delayed tests. The augmented model can predict 23.9% of the variance in an individual's score on the delayed test. We analyze which features best explain individual performance. |
| Databáze: | OpenAIRE |
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