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<p>This research analyses the challenges and opportunities of AI in competency-based learning, with a focus on higher education teachers. The databases Scopus, Lancaster One-Search, Google Scholar, IEEE Explore, and ERIC were utilised to obtain the relevant literature for the study, resulting in the selection of twenty-four studies for final analysis. These papers were studied to determine the challenges and opportunities of AI in competency-based learning for higher education teachers. The information obtained was documented in a table, with column headers for challenges, opportunities, and the respective year of publication. This research encompassed studies from different geographical locations such as Hong Kong, the Kingdom of Saudi Arabia, and Romania. Utilising AI for competency-based learning provides a personalised learning environment for the users. AI assists the teachers in analysing the students’ skills and knowledge, and accordingly, teachers could provide a personalised learning environment for students. The use of AI eases the teacher’s work by providing support in grading, offering feedback, generating lesson plans, and managing other administrative responsibilities. Along with these opportunities, the study also identifies the key challenges of using AI for competency-based learning. The study reveals that the major challenges in utilising AI for competency-based learning are the unavailability of the technical know-how of effective utilisation of AI, as well as the accuracy of AI-generated information. Moreover, AI-generated data would not be able to address the issue of ethical concerns. It is important to consider how AI can contribute to improving students’ skills, especially in the context of competency-based learning, where skill-based study is most important. Future research needs to focus on addressing this gap by exploring how AI can contribute to enhancing students’ academic skills within competency-based learning frameworks in higher education. The findings of this research will contribute to the understanding of the utilisation of AI in competency-based learning. Moreover, it will provide insight to higher education teachers, management, curriculum designers, and policymakers, aiding them in making decisions about integrating AI into teaching and learning.</p>

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Analysing the challenges and opportunities of AI in competency-based learning for higher education teachers: a systematic literature review

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  • 出版模式：

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  • 发表日期：

    2026年7月13日

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  • Silishi Noushad

摘要

This research analyses the challenges and opportunities of AI in competency-based learning, with a focus on higher education teachers. The databases Scopus, Lancaster One-Search, Google Scholar, IEEE Explore, and ERIC were utilised to obtain the relevant literature for the study, resulting in the selection of twenty-four studies for final analysis. These papers were studied to determine the challenges and opportunities of AI in competency-based learning for higher education teachers. The information obtained was documented in a table, with column headers for challenges, opportunities, and the respective year of publication. This research encompassed studies from different geographical locations such as Hong Kong, the Kingdom of Saudi Arabia, and Romania. Utilising AI for competency-based learning provides a personalised learning environment for the users. AI assists the teachers in analysing the students’ skills and knowledge, and accordingly, teachers could provide a personalised learning environment for students. The use of AI eases the teacher’s work by providing support in grading, offering feedback, generating lesson plans, and managing other administrative responsibilities. Along with these opportunities, the study also identifies the key challenges of using AI for competency-based learning. The study reveals that the major challenges in utilising AI for competency-based learning are the unavailability of the technical know-how of effective utilisation of AI, as well as the accuracy of AI-generated information. Moreover, AI-generated data would not be able to address the issue of ethical concerns. It is important to consider how AI can contribute to improving students’ skills, especially in the context of competency-based learning, where skill-based study is most important. Future research needs to focus on addressing this gap by exploring how AI can contribute to enhancing students’ academic skills within competency-based learning frameworks in higher education. The findings of this research will contribute to the understanding of the utilisation of AI in competency-based learning. Moreover, it will provide insight to higher education teachers, management, curriculum designers, and policymakers, aiding them in making decisions about integrating AI into teaching and learning.