University students' achievement goals and help-seeking strategies in an intelligent tutoring system
| Autor: | Vaessen, Bram, Prins, Frans, Jeuring, Johan, Leerstoel Brekelmans, Sub Mathematics Education, LS onderwijskwaliteit, Sub Softw.Techn. for Learning and Teach., Education and Learning: Development in Interaction |
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| Přispěvatelé: | RS-Research Line Learning (part of LIRS program), Department Computer Science, Leerstoel Brekelmans, Sub Mathematics Education, LS onderwijskwaliteit, Sub Softw.Techn. for Learning and Teach., Education and Learning: Development in Interaction |
| Rok vydání: | 2014 |
| Předmět: |
Knowledge management
General Computer Science Relation (database) Computer science business.industry Interactive learning environments Intelligent tutoring systems Learning strategies Logistic regression Machine learning computer.software_genre Click-through rate Markov model Intelligent tutoring system Help-seeking Education Help seeking behavior Artificial intelligence business Cluster analysis computer |
| Zdroj: | Vaessen, B, Prins, F & Jeuring, J T 2014, ' University students’ achievement goals and help-seeking strategies in an intelligent tutoring system ', Computers and Education, vol. 72, pp. 196-208 . https://doi.org/10.1016/j.compedu.2013.11.001 Computers and Education, 72, 196-208. Elsevier Computers & Education, 72, 196. Elsevier |
| ISSN: | 0360-1315 |
| Popis: | Help seeking behavior in an intelligent tutoring system was analyzed to identify help seeking strategies, and it was investigated whether the use of these strategies could be predicted by achievement goal scores. Discrete Markov Models and a k-means clustering algorithm were used to identify strategies, and logistic regression analyses (n?=?45) were used to analyze the relation between achievement goals and strategy use. Five strategies were identified, three of which were predicted by achievement goal scores. These strategies were labeled Little Help, Click Through Help, Direct Solution, Step By Step, and Quick Solution. The Click Through Help strategy was predicted by mastery avoidance goals, the Direct Solution strategy was negatively predicted by mastery avoidance goals and positively predicted by performance avoidance goals, and the Quick Solution strategy was negatively predicted by performance approach goals. Students' help-seeking behaviors in an intelligent tutoring system were analyzed.Five help-seeking strategies were identified.The use of three help-seeking strategies could be predicted by achievement goals. |
| Databáze: | OpenAIRE |
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