Assessing novice programmers' perception of ChatGPT:performance, risk, decision-making, and intentions

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Miranda, John Paul P., Yambao, Jaymark A.
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918280894087168
author Miranda, John Paul P.
Yambao, Jaymark A.
author_facet Miranda, John Paul P.
Yambao, Jaymark A.
contents This study explores the novice programmers' intention to use chat generative pretrained transformer (ChatGPT) for programming tasks with emphasis on performance expectancy (PE), risk-reward appraisal (RRA), and decision-making (DM). Utilizing partial least squares structural equation modeling (PLS-SEM) and a sample of 413 novice programmers, the analysis demonstrates that higher PE of ChatGPT is positively correlated with improved DM in programming tasks. Novice programmers view ChatGPT as a tool that enhances their learning and skill development. Additionally, novice programmers that have a favorable RRA of ChatGPT tend to make more confident and effective decisions, acknowledging potential risks but recognizing that benefits such as quick problem-solving and learning new techniques outweigh these risks. Moreover, a positive perception of ChatGPT's role in DM significantly increases the inclination to use the tool for programming tasks. These results highlight the critical roles of perceived capabilities, risk assessment, and positive DM experiences in promoting the adoption of artificial intelligence (AI) tools in programming education.
format Preprint
id arxiv_https___arxiv_org_abs_2601_06044
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Assessing novice programmers' perception of ChatGPT:performance, risk, decision-making, and intentions
Miranda, John Paul P.
Yambao, Jaymark A.
Computers and Society
Human-Computer Interaction
This study explores the novice programmers' intention to use chat generative pretrained transformer (ChatGPT) for programming tasks with emphasis on performance expectancy (PE), risk-reward appraisal (RRA), and decision-making (DM). Utilizing partial least squares structural equation modeling (PLS-SEM) and a sample of 413 novice programmers, the analysis demonstrates that higher PE of ChatGPT is positively correlated with improved DM in programming tasks. Novice programmers view ChatGPT as a tool that enhances their learning and skill development. Additionally, novice programmers that have a favorable RRA of ChatGPT tend to make more confident and effective decisions, acknowledging potential risks but recognizing that benefits such as quick problem-solving and learning new techniques outweigh these risks. Moreover, a positive perception of ChatGPT's role in DM significantly increases the inclination to use the tool for programming tasks. These results highlight the critical roles of perceived capabilities, risk assessment, and positive DM experiences in promoting the adoption of artificial intelligence (AI) tools in programming education.
title Assessing novice programmers' perception of ChatGPT:performance, risk, decision-making, and intentions
topic Computers and Society
Human-Computer Interaction
url https://arxiv.org/abs/2601.06044