Paper
26 June 2024 A framework for the application of AI in higher education in association with APPETD and Swiss Institute for Management and Innovation
W. Goosen, P. Mugumo
Author Affiliations +
Proceedings Volume 13188, International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024); 1318808 (2024) https://doi.org/10.1117/12.3030740
Event: International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024), 2024, Kuala Lumpur, Malaysia
Abstract
This study aimed to create a Framework for utilizing AI in Education to assist in policy development and application by examining the use of AI technology in higher education institutions. Both quantitative and qualitative research methods were used to gather data from students, academic staff, and stakeholders from various educational institutions in South Africa. Based on the findings, the study suggests an AI Education Policy Framework customized to fit the South African context, divided into four dimensions. The Pedagogical dimensions use AI to improve Research, Curriculum Development, and Teaching methods. The Governance dimension deals with Student Support Services and administration issues, including privacy and security, ensuring that AI technologies are used responsibly and ethically. Operationally, matters concerning infrastructure and training aim to provide resources and support for effective AI implementation. The study promotes understanding of the implications of AI in Education, emphasizing the importance of stakeholders' awareness and encouraging appropriate actions, a balanced approach to AI implementation in Education. Methodology - A Conceptual Framework for AI use in Higher Education is supported by a literature review, a survey of educator needs, and the researcher's experience in higher Education. Using Grounded Theory, Concepts and Categories that inform the themes supporting the proposed framework have been identified. The resulting framework ensures that AI technologies are used effectively in the context of higher Education while addressing the specific needs of educators and students. Findings - The study indicates the need for a framework that will serve as a guide for the ethical use of AI in Education. This framework should enable unlocking of AI's immense potential while ensuring alignment with ethical values. The guidance should include AI's use in research, curriculum development, instruction, and student administration. Adhering to this framework will enable higher education institutions to use AI responsibly and effectively, thereby improving overall quality of Education. Guidelines are crucial in ensuring that AI is utilized relatively and safely. Collaboration can help uphold ethical principles while enhancing the use of this Technology. Recommendations - Based on the study, the AI Framework should guide various aspects such as Research, Curriculum Development, Instruction, Student support, and administration in the education sector. AI can unlock new opportunities, industries, and jobs. The study highlights the significance of structure and skills in successfully implementing AI. Additionally, it stresses the need for capacity building and equipping the education sector to ensure optimal utilization of AI, which in turn can enhance learning outcomes and student success.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
W. Goosen and P. Mugumo "A framework for the application of AI in higher education in association with APPETD and Swiss Institute for Management and Innovation", Proc. SPIE 13188, International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024), 1318808 (26 June 2024); https://doi.org/10.1117/12.3030740
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Artificial intelligence

Machine learning

Analytical research

Evolutionary algorithms

Industry

Data privacy

Analytics

Back to Top