Evaluating Students Acceptance of AI Chatbot to Enhance Virtual Collaborative Learning in Malaysia

The pandemic COVID-19 has created a crisis in tertiary education sectors worldwide with significant impacts in Malaysia. It gives the challenge to students to cope with their new learning setup. However, with the help of technology such as AI chatbot, students can receive instant assistance in seeki...

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Bibliographic Details
Published in:International Journal of Sustainable Development and Planning
Main Author: Yahaya S.N.; Bakar M.H.; Jabar J.; Abdullah M.M.; Segaran Y.
Format: Article
Language:English
Published: International Information and Engineering Technology Association 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192253739&doi=10.18280%2fijsdp.190119&partnerID=40&md5=a3692886cc4a52abe8bd5c7ecee28346
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Summary:The pandemic COVID-19 has created a crisis in tertiary education sectors worldwide with significant impacts in Malaysia. It gives the challenge to students to cope with their new learning setup. However, with the help of technology such as AI chatbot, students can receive instant assistance in seeking and accessing information and limit the disruptions during online classes. Furthermore, the advancements in AI technology have led to improvements in natural language processing, enabling chatbots to engage in more natural interactions and provide better visual and audio representations. Therefore, the purpose of this study is to examine students’ acceptance on the effectiveness of AI chatbots to solve virtual class issues. The factors involved in this process were identified and include perceived ease of use, perceived usefulness, and perceived security. A total of 376 responses were taken into this study, and the data were analyzed using SPSS software. The results indicated that higher education authorities should focus on the effectiveness of AI chatbot by its perceived ease of use which has the highest significance value followed by perceived usefulness and perceived security as the less significance value. Findings were proved by testing through Pearson correlation coefficient and multiple linear regression. University authorities should provide students with basic techniques for learning, as well as sufficient understanding and teaching about the system's capabilities, which can help students' confidence in and willingness to adopt the technology. Copyright: ©2024 The authors.
ISSN:17437601
DOI:10.18280/ijsdp.190119