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Adding ‘Reinforcement’ to the Involvement Load Hypothesis Improves Students’ Productive Vocabulary Performance

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Blended Learning: Engaging Students in the New Normal Era (ICBL 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13357))

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Abstract

Hitherto, a proliferation of research using the Involvement load Hypothesis (ILH) has revealed that tasks with higher involvements loads (IL) might yield better results in students’ productive vocabulary performance. Paradoxically, some extant studies still witnessed a significant decrease of productive vocabulary knowledge gain in the delayed-test, albeit with the tasks containing high IL. The present study builds on such previous studies by investigating whether the provision of extra vocabulary knowledge (reinforcement) could bolster students’ productive vocabulary learning. Fifty-one undergraduate students from a Chinese University, divided into a control group (CG, n = 26) and an experimental group (EG, n = 25) participated in the present study. Two different WeChat Applets (Applet 0.0 and Applet 1.0) were designed. The design of Applet 0.0 was informed by the ILH. Applet 1.0 was also informed by ILH supplemented with vocabulary ‘use’ knowledge (i.e., grammatical functions (what part of speech this word is and what grammatical patterns this word can fit into?), collocations (what other words or types of words appear together with this word?) and limitations on use (in what situation would we use this word?)). Both groups were asked to write a paragraph every week while learning vocabulary with the different Applets (the CG used Applet 0.0 while the EG used Applet 1.0). Furthermore, a paragraph writing test served as pre-, post- and delayed-test. The results revealed a positive significant performance of EG over CG in terms of the post-test and delayed-test. It is concluded that reinforcement of extra vocabulary knowledge could bolster ILH and result in better delay productive vocabulary performance.

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Correspondence to Guoyuhui Huang .

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Huang, G., Hew, K.F. (2022). Adding ‘Reinforcement’ to the Involvement Load Hypothesis Improves Students’ Productive Vocabulary Performance. In: Li, R.C., Cheung, S.K.S., Ng, P.H.F., Wong, LP., Wang, F.L. (eds) Blended Learning: Engaging Students in the New Normal Era. ICBL 2022. Lecture Notes in Computer Science, vol 13357. Springer, Cham. https://doi.org/10.1007/978-3-031-08939-8_25

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  • DOI: https://doi.org/10.1007/978-3-031-08939-8_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08938-1

  • Online ISBN: 978-3-031-08939-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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