Teaching with AI: A Systematic Review of Chatbots, Generative Tools, and Tutoring Systems in Programming Education

This review examines the role of artificial intelligence (AI) agents in programming education, focusing on how these tools are being integrated into educational practice and their impact on student learning outcomes. An analysis of 58 peer-reviewed studies published between 2022 and 2025 identified three primary categories of AI agents: chatbots, generative AI (GenAI), and intelligent tutoring systems (ITS), with GenAI being the most frequently studied. The studies report that the primary instructional objectives include providing enhanced programming support 94.83% of studies, delivering motivational and emotional benefits 18.96%, and increasing efficiency for educators 6.90%. Reported benefits include personalized feedback, improved learning outcomes, and time savings. The review also highlights challenges, such as implementation barriers documented in 93.10% of studies, overreliance resulting in superficial learning in 65.52%, and concerns regarding AI errors and academic integrity. These findings suggest the need for instructional frameworks that prioritize the development of prompt engineering skills and human oversight to address these issues. This review provides educators and curriculum designers with an evidence-based foundation for the practical and ethical integration of AI in programming education.

Authors

Institutions

Publication Details

Journal
International Journal of Learning Teaching and Educational Research
Published
2026-01-05
DOI
https://doi.org/10.26803/ijlter.25.1.1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Teaching with AI: A Systematic Review of Chatbots, Generative Tools, and Tutoring Systems in Programming Education

Abedallah Zaid Abualkishik, Said Elnaffar, Farzan Rashidi
International Journal of Learning Teaching and Educational Research
AI in Service Interactions
article

Teaching with AI: A Systematic Review of Chatbots, Generative Tools, and Tutoring Systems in Programming Education

Abedallah Zaid Abualkishik, Said Elnaffar, Farzan Rashidi
article en

Abstract

This review examines the role of artificial intelligence (AI) agents in programming education, focusing on how these tools are being integrated into educational practice and their impact on student learning outcomes. An analysis of 58 peer-reviewed studies published between 2022 and 2025 identified three primary categories of AI agents: chatbots, generative AI (GenAI), and intelligent tutoring systems (ITS), with GenAI being the most frequently studied. The studies report that the primary instructional objectives include providing enhanced programming support 94.83% of studies, delivering motivational and emotional benefits 18.96%, and increasing efficiency for educators 6.90%. Reported benefits include personalized feedback, improved learning outcomes, and time savings. The review also highlights challenges, such as implementation barriers documented in 93.10% of studies, overreliance resulting in superficial learning in 65.52%, and concerns regarding AI errors and academic integrity. These findings suggest the need for instructional frameworks that prioritize the development of prompt engineering skills and human oversight to address these issues. This review provides educators and curriculum designers with an evidence-based foundation for the practical and ethical integration of AI in programming education.

International Journal of Learning Teaching and Educational ResearchVol. 25(1)
Canadian University of Dubai (AE), Université Paris Cité (FR), American University in the Emirates (AE)
Directorate for STEM Education
Openalex Percentile: Top 99%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.