AI in Coding: How can code generation models support developing computational thinking skills?

The use of code generation models in programming support activities

Bachelor Thesis (2023)
Author(s)

R. Mulder (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Efthimia Aivaloglou – Mentor (TU Delft - Web Information Systems)

X. Zhang – Mentor (TU Delft - Web Information Systems)

T.J. Viering – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Rick Mulder
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Rick Mulder
Graduation Date
28-06-2023
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Using AI to support programming has recently gained a lot of popularity. Researchers have been developing tools to support programming activities using GPT models such as ChatGPT and Codex In this paper, we present the most common pro-gramming activities that these models can support. We show that they have a varying range of success
across solving Code Generation, Code Explana-tion,and Data Visualisation problems, but are often able to solve around 50% of problems on the first try. Multiple tries can raise these averages to 75%. Additionally, specialized tools using GPT models have seen promising results regarding Data Visuali-sation, Software Vulnerability Detection, and Gen-
eral Programming Support. This shows a promis-ing trend, and can mean we will all be pair pro-gramming with AI in the near-future.

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