Description
CSCI 340 – Data Structures and Algorithm Analysis is one of the highest-enrollment required courses in the Computer Science department, serving sophomore and junior students each semester across multiple sections. It is a required gateway course for all CS majors and a critical checkpoint for professional readiness. While AI tools have made it increasingly easy for students to complete programming assignments without developing genuine understanding, students also have varied academic backgrounds and preparation prior to this course that makes it challenging to adequately assess student learning.
In response, Dr. Zhang developed a web-based adaptive learning and assessment system, built on large language model inference. The system functions as an AI-powered mastery platform: after each major topic is covered in lecture, students complete an AI-driven Adaptive Learning Session drawn from a question bank spanning multiple formats, including a new question type introduced by this redesign: code reading, where students analyze, trace, or debug code rather than simply produce it. The system continuously diagnoses each student's knowledge gaps and routes them to questions targeting exactly what they have not yet mastered, with students earning full credit through demonstrated mastery rather than mere submission.
Tags
AI Learning Tool Assessment Design Code Generation Critical Thinking Disciplinary SkillsLearning Objectives
- Read code by analyzing, tracing, or debugging code.
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