2026 ASEE Annual Conference & Exposition

From the Alphabet to AI-Algorithms: Co-Learning and Co-Construction of Knowledge with AI.
The proposed paper will explore the parallel pedagogical impacts of Artificial Intelligence (AI) and those historically wrought by the invention of the alphabet and the technology of writing. It argues that just as writing externalized human thought and transformed how societies transmitted knowledge, AI now externalizes cognition, transforming how learning, reasoning, and problem-solving occur in educational settings. Grounded in media ecology and hermeneutic inquiry, the paper examines how autonomous digital tools, particularly MathWorks Simulink, Simscape, and MATLAB GPT, function as pedagogical agents that shape co-learning, knowledge construction, and applications in engineering education [1].

Walter Ong’s classic observation that “writing is a technology that restructures thought” [2] provides a historical framework for understanding AI’s contemporary transformation of cognition and pedagogy. The invention of the alphabet not only revolutionized communication but also reorganized memory, reasoning, and social structure by creating new external supports for thought. Similarly, AI-assisted environments, especially those involving intelligent systems capable of interpretation, dialogue, and adaptive feedback, extend human cognition into hybrid learning ecologies that merge human and machine intelligences [3], [4].

In the context of engineering education, this study investigates how Simulink and MATLAB GPT act as autonomous pedagogical collaborators rather than passive instructional tools [5]. Simulink enables learners to visualize system behaviors dynamically, supporting interpretive, iterative understanding of abstract concepts. Meanwhile, MATLAB GPT, through its conversational code generation and debugging assistance, introduces a dialogical mode of learning akin to the Socratic method, allowing students to test and refine their conceptual models in real time [1]. Together, these tools illustrate the hermeneutic cycles of interpretation and re-interpretation that underline co-learning and construction of knowledge with intelligent agents [6], [7].

Hermeneutics, as a theory of understanding and interpretation, [8] plays a crucial role in analyzing these interactions. Learners engage in continuous cycles of inquiry, posing questions, testing hypotheses, and refining models, while the AI system provides feedback that itself carries interpretive assumptions embedded in algorithmic reasoning. This recursive relationship mirrors Hans-Georg Gadamer’s concept of the “fusion of horizons” [9], where meaning emerges through dialogue between differing perspectives, in this case, human learners and computational agents.

The paper will conclude that AI in engineering education is not merely a technological augmentation but a transformation of epistemic relations: where understanding becomes distributed, interpretation recursive, and knowledge construction increasingly collaborative. By situating this discussion within the broader historical arc from orality to literacy to AI-based cognition, the paper proposes a new hermeneutic model for digital-age engineering pedagogy.

References
[1] MathWorks, “MATLAB Copilot and Simulink for Learning Engineering Systems,” MathWorks Education Portal, 2024. [Online]. Available: https://www.mathworks.com/education.html
[2] W. J. Ong, Orality and Literacy: The Technologizing of the Word, London, U.K.: Methuen, 1982.
[3] S. Papert, Mindstorms: Children, Computers, and Powerful Ideas, New York, NY: Basic Books, 1980.
[4] A. Hogan, The Semantic Web: History, Applications, and Future Directions, San Rafael, CA: Morgan & Claypool, 2020.
[5] T. Malone, Superminds: The Surprising Power of People and Computers Thinking Together (p. 328). Little, Brown and Company. Kindle Edition.
[6] C. Dede, J. Richards, and B. Saxberg, Learning Engineering for Online Education, New York, NY: Routledge, 2018.
[7] C. Dede, J. Richards, and B. Saxberg, The 60-Year Curriculum: New Models for Lifelong Learning in the Digital Economy, Routledge, 2019.
[8] Zimmermann, J. (2015). Hermeneutics: A Very Short Introduction. Oxford: Oxford University Press.
[9] H.-G. Gadamer, Truth and Method, 2nd Rev. Ed., New York, NY: Continuum, 1989.