INTEGRATING ARTIFICIAL INTELLIGENCE (AI) TOOLS INTO TEACHING MATHEMATICAL ECONOMICS IN TERTIARY EDUCATION
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https://doi.org/10.46827/ejoe.v9i1.5683##semicolon##
artificial intelligence in education##common.commaListSeparator## mathematical economics pedagogy##common.commaListSeparator## AI-driven learning tools##common.commaListSeparator## interactive learning in economics##common.commaListSeparator## higher education technology integrationAbstrakt
This paper examines the integration of artificial intelligence (AI) tools, specifically conversational agents like ChatGPT, in teaching mathematical economics in tertiary education. Recognizing the inherent challenges in mathematical economics—ranging from complex theoretical constructs to advanced quantitative methods—this study explores AI's potential to enhance student comprehension, engagement, and problem-solving skills. Drawing from existing literature on AI applications in education and learning sciences, this conceptual paper evaluates AI's role in delivering real-time support, facilitating interactive problem-solving, and offering personalized feedback, thereby addressing diverse student needs. Key areas of focus include AI-driven question-and-answer capabilities, scenario-based learning simulations, and guided problem-solving models that can reinforce theoretical knowledge through practical application. The paper further identifies potential challenges, including student overreliance on AI tools, possible misunderstandings in AI-generated solutions, and ethical concerns related to data privacy and academic integrity. By proposing a blended learning model, this paper suggests best practices for using AI as a supportive, non-replacement instructional tool. These best practices encompass educator training, responsible AI implementation, and fostering a balanced, interactive classroom environment. The findings contribute to a growing discourse on the responsible and effective use of AI in higher education, with implications for policy and practice in curriculum design, educational technology, and teaching strategies. Future research directions include empirical studies on AI’s impact on learning outcomes in mathematical economics, exploring how these tools can further enhance both student engagement and academic performance.##submission.citations##
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