ARTIFICIAL INTELLIGENCE-AIDED INSTRUCTION AND RESEARCH GENERATION: TERTIARY EDUCATION POLICY CONSIDERATIONSAND AI OPTIMIZATION PLAN

Abstract

The use of Artificial Intelligence (AI) in many aspects of human lives, particularly in tertiary education i.e. teaching and research, has been prevalent in the 21st century. This research utilized mixed method that explored the level of AI integration in the teaching and learning as well as its usage in research generation using 64 tertiary education faculty members. Data revealed that teachers’ AI integration in instruction is partially integrated, with higher use of AI as a means to prepare students in the future AI application, however, there is a minimal AI integration in the areas of curriculum planning, assessment, and learning enhancement.

Contrary to the results in using AI in teaching, respondents have manifested a high level of dependence in AI in research output generation particularly in synthesizing ideas, review of literature, and statistical treatment of data but they have shown moderate to partial reliance in the areas of data analytics, prediction, and hypothesizing in research. 

The result of correlational analysis using Spearman’s rho (ρ = 0.30) shows low positive relationship between AI Research Dependence and Instructional Integration.  This proves that the higher utilization of AI in research is associated to slightly higher integration of AI in instructions but limitations, such as systemic, pedagogical, and policy-related challenges must be taken into considerations.

Further, the results of qualitative analysis from seven (7) participants have provided multidimensional insights on AI Integration.  Identified key themes include: the need to have a holistic capacity building, ethics in the use of AI, comprehensive institutional policy and frameworks, teachers’ mindset, measurable AI initiatives, and interdisciplinary collaboration have surfaced. 

Results of this study recognized the strong potential and limitations of AI adoption in tertiary education.  Although AI competence in research can support instruction integration, it is not enough to guarantee significant and inclusive application in instructions.  Data provided strong evidence for: developing inclusive professional enhancement programs in the use of AI, policy framework, and comprehensive approaches that will resolve identified challenges.