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2026 ASEE Annual Conference & Exposition

Enhancing Self-Directed Learning with GenAI: A Freshman-Level Engineering Case Study

Presented at Tips and tricks for faculty to leverage AI in the classroom

The transition from structured, teacher-led high school learning to the self-directed learning demands of college is a major challenge for many first-year students, particularly in large freshman courses where faculty–student interaction may be limited. This challenge is further intensified by the rapid rise of generative artificial intelligence (GenAI), which brings both opportunities and concerns for higher education. To promote responsible GenAI use and better understand how first-time-in-college (FTIC) students employ these tools, this study developed a custom AI chatbot (I2CE; a pseudonym used to preserve anonymity) as a self-study assistant for an Introduction to Civil Engineering course. The two-credit course meets weekly for three hours over 10 weeks and covers four modules: (1) an overview of the civil engineering profession; (2) lifecycle of construction projects; (3) essential soft skills for engineers; and (4) professional ethics.
This study aims at examining GenAI usage and student perceptions in a class of 82 freshmen. Data were collected from students using a two-tier survey strategy: pre-course and post-course surveys and weekly “pulse” surveys administered from Weeks 4–10. Response counts were stable across stages (pre: 77; weekly range: 67–82; post: 82). Surveys captured familiarity with GenAI, perceived usefulness, engagement, perceived effectiveness of GenAI-supported activities, usage frequency, and intention to continue using AI chatbots for learning.
Results indicate consistent increases in familiarity, perceived usefulness, and engagement from pre- to post-course. Descriptive cross-tabulations show that higher perceived usefulness aligns with stronger intention to continue use, and higher engagement aligns with more frequent use. Weekly pulse results indicate consistently high perceived effectiveness, with modest fluctuations associated with topic demands. This study contributes longitudinal classroom evidence and a practical evaluation approach for understanding how guided, course-grounded GenAI chatbots can scaffold freshmen’s self-directed learning.

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The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026