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Chatbot adoption model in determining student career path development: pilot study


Citation

Ahmed, Mohamed Hassan and Abdullah, Rusli and Jusoh, Yusmadi Yah and Azmi Murad, Masrah Azrifah (2025) Chatbot adoption model in determining student career path development: pilot study. International Journal on Informatics Visualization, 9 (1). pp. 387-395. ISSN 2549-9904

Abstract

A career decision is incredibly essential in one's life. It shapes one's future role in society, influences professional development, and can lead to success and fulfillment. Making a sound and consistent career decision based on skills and interests is critical for personal and professional development. Since generative AI is an emerging and revolutionizing technology industry in the market, which is very good in generating contents, providing consultancies and answering questions in humanly fashion, integrating AI chatbots into the career planning process can help students to get more accurate and personalized advice for their future career. This pilot study emphasized the student’s adoption of chatbot technology for career selecting processes utilizing the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model with four additional constructs which influence the student’s career selection, namely: Perceived Student’s External Factors (PEF), Perceived Student’s Interest (PSN), Perceived Career Opportunities (PCO) and Perceived Self-Efficacy (PSF). An online survey was conducted, and 37 responses were received and analyzed. The measurement model produced a promising result, and the discriminant validity, construct reliability and validity of the model were confirmed with a Cronbach’s alpha (α) above 0.70 threshold and AVE over 0.5 cut-off for most of the constructs including the four above mentioned latent variables. However, the Price Value (PPV) and Facilitating Conditions (PFC) UTAUT2 constructs produced alpha (á) of 0.680 and 0.611 respectively which is still adequate since their AVE is above the 0.5 threshold. Consequently, their interpretation and conclusions should be approached with caution.


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Additional Metadata

Item Type: Article
Subject: Computer Science (all)
Subject: Statistics, Probability and Uncertainty
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.62527/joiv.9.1.3798
Publisher: Politeknik Negeri Padang
Keywords: Chatbots; Chatgpt; Determinants; Large language models; Structural equation modeling (sem)
Sustainable Development Goals (SDGs): SDG 4: Quality Education, SDG 9: Industry, Innovation and Infrastructure, SDG 8: Decent Work and Economic Growth
Depositing User: Ms. Siti Radziah Mohamed@mahmod
Date Deposited: 22 Apr 2026 01:14
Last Modified: 22 Apr 2026 01:14
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.62527/joiv.9.1.3798
URI: http://psasir.upm.edu.my/id/eprint/123512
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