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Student Class

2027

Student Affiliation

WISP Intern

First Advisor

Vasanta Lakshmi Kommineni

First Advisor Department

Department of Computer Science

Description

Generative AI tools like ChatGPT, Copilot, and Gemini have become essential to students’ learning in introductory coding classes like CS1. Yet, very little work has been done to create tutorials that utilize the potential of these tools. Traditional coding tutorials are not adaptable to a student’s learning style or understanding of a subject. AI-based tools combined with ma- chine learning algorithms used for adaptive testing can help students by creating a customized environment that adapts to an individual’s performance. The central goal of this project is to create an adaptive coding tutorial that uses generative AI tools to design increasingly challenging problems for a given topic. The tutorial also assists students by creating code samples when they make a mistake while learning.

Internally, the tutorial has two components. The first component communicates with the stu- dent and determines the learning level using adaptive learning algorithms. The second component uses the output of the adaptive learning algorithm to create coding problems suitable for the student’s learning level.

Publication Date

Spring 5-22-2024

Keywords

ChatGPT, Prompt Engineering, Coding, Tutorial, Beginner, Adaptive Testing, Generative AI, Machine Learning, Prompt Engine

Disciplines

Online and Distance Education | Other Computer Engineering

Prompt Engineering for Coding Tutorial

Restricted

Available to Dartmouth community via local IP address.

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