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The Effects of Emotionally Sound Web-Based Instruction on Performance, Engagement and Retention

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Intelligent Computing and Optimization (ICO 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1072))

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Abstract

This study was designed to investigate the effectiveness of emotionally sound web-based instruction on performance, engagement and retention in learning English grammar. The sample consisted of Form Two students from a secondary school in the Northern region of the Peninsular Malaysia. The data were collected using Post-Test 1, Retention Questionnaire (Post-Test 2) and E-Learning Engagement Instrument (ELEI). The research design for this study is Quasi-experimental with pre-test and post-test design. The data was analyzed by using an independent sample t-test and ANCOVA. On balance, results indicate that the emotionally sound web-based instruction have positive impact on learning. The results revealed that students in WBIe performed better than students in WBIwe based on their academic performance and retention level in English grammar. In terms engagement level, students in both WBIe and WBIwe have a similar score.

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Author information

Authors and Affiliations

  1. Department of Computing, School of Engineering, Computing and Built Environment, KDU Penang University College, 10400, George Town, Penang, Malaysia

    Rasslenda-Rass Rasalingam

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  1. Rasslenda-Rass Rasalingam
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Correspondence to Rasslenda-Rass Rasalingam .

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Editors and Affiliations

  1. Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Tronoh, Perak, Malaysia

    Pandian Vasant

  2. Computer Science, FEI, VSB-TU Ostrava, Ostrava, Czech Republic

    Ivan Zelinka

  3. Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland

    Gerhard-Wilhelm Weber

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Rasalingam, RR. (2020). The Effects of Emotionally Sound Web-Based Instruction on Performance, Engagement and Retention. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2019. Advances in Intelligent Systems and Computing, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-33585-4_33

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