Theses and Dissertations

ORCID

https://orcid.org/0009-0004-3162-8578

Advisor

Bethel, Cindy L.

Committee Member

Jankun-Kelly, T.J.

Committee Member

Rahimi, Sharam

Committee Member

Xu, Jianzhong

Date of Degree

12-12-2025

Original embargo terms

Immediate Worldwide Access

Document Type

Dissertation - Open Access

Major

Computer Science

Degree Name

Doctor of Philosophy (Ph.D.)

College

James Worth Bagley College of Engineering

Department

Department of Computer Science and Engineering

Abstract

Given the rapid advancement of Computer Science (CS) and Artificial Intelligence (AI), introducing these disciplines early and effectively in education is essential. Many middle school students, however, struggle to understand these subjects when taught with traditional, abstract, and screen-based methods, which often fail to engage students or build deep conceptual understanding. This study argues that tangible, hands-on learning tools and interactive activities make AI and CS concepts more accessible, concrete, and engaging for students. The findings show that, compared to traditional lectures, hands-on activities lead to substantially improved comprehension, retention, and enjoyment. While the sample size poses limitations, the evidence supports that interactive methods foster collaboration, critical thinking, and curiosity—skills essential for mastering AI and CS. The results show that game-based, interactive learning approaches clarify technical AI concepts and promote responsible use of AI. Expanding these methods, along with teacher training and institutional support, can further enhance students’ understanding, critical thinking, and preparedness for emerging technologies. This research highlights the importance of hands-on, interactive learning in AI and CS education, offering practical guidance for curriculum design and teacher preparation based on the proven benefits of these approaches.

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