A Comparative Study on Linguistic Theories for Modeling EFL Learners: Facilitating Personalized Vocabulary Learning via Task Recommendations

Autor/inn/en	Zou, Di; Wang, Minhong; Xie, Haoran; Cheng, Gary; Wang, Fu Lee; Lee, Lap-Kei
Titel	A Comparative Study on Linguistic Theories for Modeling EFL Learners: Facilitating Personalized Vocabulary Learning via Task Recommendations
Quelle	In: Interactive Learning Environments, 29 (2021) 2, S.270-282 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Zou, Di) ORCID (Wang, Minhong) ORCID (Xie, Haoran) ORCID (Cheng, Gary) ORCID (Wang, Fu Lee) ORCID (Lee, Lap-Kei)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2020.1789178
Schlagwörter	Linguistic Theory; Vocabulary Development; Second Language Learning; Second Language Instruction; English (Second Language); Learning Processes; Electronic Learning; Comparative Analysis; Individualized Instruction; Teaching Methods; Check Lists; Language Tests; Foreign Countries; Pretests Posttests; College Students; Task Analysis; Instructional Effectiveness; Models; Evaluation Methods; Integrated Learning Systems; China; International English Language Testing System + Suchen Sie Ihr Suchwort? Linguistische Theorie; Wortschatzarbeit; Zweitsprachenerwerb; Fremdsprachenunterricht; English as second language; English; Second Language; Englisch als Zweitsprache; Learning process; Lernprozess; Individualisierender Unterricht; Teaching method; Lehrmethode; Unterrichtsmethode; Checkliste; Language test; Sprachtest; Ausland; Collegestudent; Aufgabenanalyse; Unterrichtserfolg; Analogiemodell; Language tests; Englisch
Abstract	Personalized learning has become an important and powerful paradigm catering for various needs, styles, preferences, and modes of learning. Several methods including task recommendations and path planning have recently emerged to effectively implement personalized learning using e-learning systems. The literature shows that the use of task recommendations in e-learning systems is a very effective way to facilitate personalized vocabulary learning. One of the key research issues regarding these personalized vocabulary learning systems is how to model the learning logs of each learner. Specifically, how to measure the learning effectiveness of each learned tasks has become a core issue for establishing personalized learning systems. Three theories, Spaced Learning (SL), Technique Feature Analysis (TFA), and Involvement Load Hypothesis (ILH), are commonly applied for achieving this purpose. In this study, we compared the effectiveness of these three linguistic theories for modeling EFL learners' personalized vocabulary learning via task recommendations. By conducting experimental studies among different groups of participants, our findings revealed that the ILH and TFA were more suitable than SL for facilitating personalized vocabulary learning. It is therefore suggested that future personalized vocabulary learning systems ought to be designed and developed based on comprehensive theoretical frameworks such as the ILH and TFA. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01