1. ZHAW digitalcollection
  2. School of Management and Law
  3. Publikationen
  4. Publikationen School of Management and Law
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dc.contributor.authorFazlija, Bledar-
dc.contributor.authorIbrahim, Mohamed-
dc.date.accessioned2023-07-20T14:23:44Z-
dc.date.available2023-07-20T14:23:44Z-
dc.date.issued2022-
dc.identifier.isbn978-3-031-11646-9de_CH
dc.identifier.isbn978-3-031-11647-6de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/28308-
dc.description.abstractThere is a variety of metacognitive information that can be used to model learning success, such as judgements of learning (JOLs) and feeling of difficulty (FOD). The latter is not widely used, and part of this study is to collect FODs through crowed annotation and demonstrate its potential as a predictor of learning success. While objective features related to task difficulty provide valuable information for the modeling task, we show evidence that FOD can provide similar insight. We examine and compare the use of objective and subjective features as predictors for learning success in second language word pair learning. The results indicate that metacognitive information is transferable across different groups of subjects. They also show that crowed annotation is a useful method for enriching datasets with FODs and potentially other metacognitive information.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesLecture Notes in Computer Sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectMetacognitionde_CH
dc.subjectMachine learningde_CH
dc.subjectTransfer learningde_CH
dc.subjectWord difficultyde_CH
dc.subjectCrowed annotationde_CH
dc.subjectFeeling of difficultyde_CH
dc.subjectJudgment of learningde_CH
dc.subject.ddc410.285: Computerlinguistikde_CH
dc.titleUsing metacognitive information and objective features to predict word pair learning successde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitut für Wealth & Asset Management (IWA)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-031-11647-6_39de_CH
zhaw.conference.details23rd International Conference on Artificial Intelligence in Education (AIED), Durham, United Kingdom, 27-31 July 2022de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end226de_CH
zhaw.pages.start222de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number13356de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsArtificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortiumde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Fazlija, B., & Ibrahim, M. (2022). Using metacognitive information and objective features to predict word pair learning success [Conference paper]. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, 222–226. https://doi.org/10.1007/978-3-031-11647-6_39
Fazlija, B. and Ibrahim, M. (2022) ‘Using metacognitive information and objective features to predict word pair learning success’, in Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. Cham: Springer, pp. 222–226. Available at: https://doi.org/10.1007/978-3-031-11647-6_39.
B. Fazlija and M. Ibrahim, “Using metacognitive information and objective features to predict word pair learning success,” in Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, 2022, pp. 222–226. doi: 10.1007/978-3-031-11647-6_39.
FAZLIJA, Bledar und Mohamed IBRAHIM, 2022. Using metacognitive information and objective features to predict word pair learning success. In: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. Conference paper. Cham: Springer. 2022. S. 222–226. ISBN 978-3-031-11646-9
Fazlija, Bledar, and Mohamed Ibrahim. 2022. “Using Metacognitive Information and Objective Features to Predict Word Pair Learning Success.” Conference paper. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, 222–26. Cham: Springer. https://doi.org/10.1007/978-3-031-11647-6_39.
Fazlija, Bledar, and Mohamed Ibrahim. “Using Metacognitive Information and Objective Features to Predict Word Pair Learning Success.” Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, Springer, 2022, pp. 222–26, https://doi.org/10.1007/978-3-031-11647-6_39.


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