A Systematic Mapping Study on Chatbots in Programming Education
Resumo
Educational chatbots have gained prominence as support tools for teaching programming, particularly in introductory learning contexts. This paper presents a Systematic Mapping Study (SMS) that investigated how such agents have been developed and applied in programming education. From an initial set of 3,216 publications, 54 studies were selected and analyzed based on five research subquestions, addressing chatbot types, programming languages used, educational content covered, interaction models, and application contexts. The results reveal a predominance of chatbots designed for Python instruction, focusing on fundamental programming concepts, and employing a wide variety of pedagogical approaches and technological architectures. In addition to identifying trends and gaps in the literature, this study provides insights to inform the development of new educational tools for programming instruction.
Referências
Akçapınar, G. e Sidan, E. (2024). Ai chatbots in programming education: guiding success or encouraging plagiarism. Discover Artificial Intelligence, 4(87):1–18.
Alves, G., Rebouças, A., e Scaico, P. (2019). Coding dojo como prática de aprendizagem colaborativa para apoiar o ensino introdutório de programação: Um estudo de caso. Em Anais do XXVII Workshop sobre Educação em Computação, páginas 276–290. SBC.
Andersen-Kiel, N. e Linos, P. (2024). Using chatgpt in undergraduate computer science and software engineering courses: A students’ perspective. Em Proceedings of the 2024 IEEE Frontiers in Education Conference (FIE), páginas 1–9. IEEE.
Ardimansyah, M. e Widianto, M. (2021). Development of online learning media based on telegram chatbot (case studies: Programming courses). Em Journal of Physics: Conference Series, volume 1987, página 012006. IOP Publishing.
Arteaga Garcia, E. J., Nicolaci Pimentel, J. F., Feng, Z., Gerosa, M., Steinmacher, I., e Sarma, A. (2024). How to support ml end-user programmers through a conversational agent. Em Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, páginas 1–12.
Bilgin, T. T. e Yavuz, E. (2022). Integrating a dialogue tree based turkish chatbot into an open source python coding editor. Em 2022 3rd International Informatics and Software Engineering Conference (IISEC), páginas 1–5. IEEE.
Bobadilla, S., Glassey, R., Bergel, A., e Monperrus, M. (2023). Sobo: A feedback bot to nudge code quality in programming courses. IEEE Software, 41(2):68–76.
Bran, A. M. e Schwaller, P. (2024). Transformers and large language models for chemistry and drug discovery. Em Drug Development Supported by Informatics, páginas 143–163. Springer.
Callejo, P., Alario-Hoyos, C., e Delgado-Kloos, C. (2024). Evaluating chatgpt impact on the programming learning outcomes of students in a big data course. International Journal of Engineering Education, 40(4):863–872.
Carreira, G., Silva, L., Mendes, A. J., e Oliveira, H. G. (2022). Pyo, a chatbot assistant for introductory programming students. Em 2022 International Symposium on Computers in Education (SIIE), páginas 1–6. IEEE.
Chen, T., Xu, L., e Zhu, K. (2021). Fritzbot: A data-driven conversational agent for physical-computing system design. International Journal of Human-Computer Studies, 155:102699.
Clarizia, F., Colace, F., Lombardi, M., Pascale, F., e Santaniello, D. (2018). Chatbot: An education support system for student. Em International Symposium on Cyberspace Safety and Security, páginas 291–302. Springer.
Coronado, M., Iglesias, C. A., Carrera, Á., e Mardomingo, A. (2018). A cognitive assistant for learning java featuring social dialogue. International Journal of Human-Computer Studies, 117:55–67.
Cubillos, C., Mellado, R., Cabrera-Paniagua, D., e Urra, E. (2025). Generative artificial intelligence in computer programming: Does it enhance learning, motivation, and the learning environment? IEEE Access.
da Silva, C. A. G., Ramos, F. N., de Moraes, R. V., e dos Santos, E. L. (2024). Chatgpt: Challenges and benefits in software programming for higher education. Sustainability, 16(3):1245.
Ericsson, K. A., Krampe, R. T., e Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological review, 100(3):363.
Farah, J. C., Spaenlehauer, B., Ingram, S., Purohit, A. K., Holzer, A., e Gillet, D. (2023). Harnessing rule-based chatbots to support teaching python programming best practices. Em Proceedings of the International Conference on Educational Technology. Springer.
Fernandez, C., Sánchez-Soto, E., Aguilar Cisnero, J., e Juárez-Ramírez, R. (2024). Exploring the frontier of software engineering education with chatbots. Programming and Computer Software, 50(8):796–815.
Frankford, E., Sauerwein, C., Bassner, P., Krusche, S., e Breu, R. (2024). Ai-tutoring in software engineering education. Em Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training, páginas 309–319.
Gabriella, A., Gui, A., e Chanda, R. C. (2024). The use of chatbot and its impact on academic achievement. Em 2024 IEEE Symposium on Industrial Electronics & Applications (ISIEA), páginas 1–6. IEEE.
Groothuijsen, S., van den Beemt, A., Remmers, J. C., e van Meeuwen, L. W. (2024). Ai chatbots in programming education: students’ use in a scientific computing course and consequences for learning. Computers and Education: Artificial Intelligence, 7:100290.
Guo, P. J. (2018). Non-native english speakers learning computer programming: Barriers, desires, and design opportunities. Em Proceedings of the 2018 CHI conference on human factors in computing systems, páginas 1–14.
Gupta, R., Goyal, H., Kumar, D., Mehra, A., Sharma, S., Mittal, K., e Challa, J. S. (2025a). Sakshm ai: Advancing ai-assisted coding education for engineering students in india through socratic tutoring and comprehensive feedback. arXiv preprint arXiv:2503.12479.
Gupta, R. D., Hosain, M. T., Mridha, M., e Ahmed, S. U. (2025b). Multimodal programming in computer science with interactive assistance powered by large language model. Em International Conference on Human-Computer Interaction, páginas 59–69. Springer.
Haindl, P. e Weinberger, G. (2024a). Does chatgpt help novice programmers write better code? results from static code analysis. IEEE Access, 12:114146–114160.
Haindl, P. e Weinberger, G. (2024b). Students’ experiences of using chatgpt in an undergraduate programming course. IEEE Access, 12:43519–43530.
Hamzah, W. W., Ismail, I., Yusof, M. K., Saany, S. M., e Yacob, A. (2021). Using learning analytics to explore responses from student conversations with chatbot for education. International Journal of Engineering Pedagogy, 11(6):70–84.
Hien, H. T., Cuong, P.-N., Nam, L. N. H., Nhung, H. L. T. K., e Thang, L. D. (2018). Intelligent assistants in higher-education environments: the fit-ebot, a chatbot for administrative and learning support. Em Proceedings of the 9th International Symposium on Information and Communication Technology, páginas 69–76.
Hobert, S. (2019). Say hello to ‘coding tutor’! design and evaluation of a chatbot-based learning system supporting students to learn to program.
Ismail, M. e Ade-Ibijola, A. (2019). Lecturer’s apprentice: A chatbot for assisting novice programmers. Em 2019 international multidisciplinary information technology and engineering conference (IMITEC), páginas 1–8. IEEE.
Jury, B., Lorusso, A., Leinonen, J., Denny, P., e Luxton-Reilly, A. (2024). Evaluating llm-generated worked examples in an introductory programming course. Em Proceedings of the 26th Australasian computing education conference, páginas 77–86.
Kasinathan, V., Mustapha, A., Siow, S., e Hopman, M. (2018). Tictad: A chatterbot for learning visual c programming based on expert system,". Indonesian Journal of Electrical Engineering and Computer Science, 11(2):740–746.
Keuning, H., Jeuring, J., e Heeren, B. (2018). A systematic literature review of automated feedback generation for programming exercises. ACM Transactions on Computing Education (TOCE), 19(1):1–43.
Kiesler, N., Lohr, D., e Keuning, H. (2023). Exploring the potential of large language models to generate formative programming feedback. Em 2023 IEEE Frontiers in Education Conference (FIE), páginas 1–5. IEEE.
Kitchenham, B. e Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering.
Kitchenham, B., Madeyski, L., e Budgen, D. (2022). Segress: Software engineering guidelines for reporting secondary studies. IEEE Transactions on Software Engineering, 49(3):1273–1298.
Kosar, T., Ostojic, D., Liu, Y. D., e Mernik, M. (2024). Computer science education in chatgpt era: Experiences from an experiment in a programming course for novice programmers. Mathematics, 12(6):629.
Kuhrmann, M., Fernández, D. M., e Daneva, M. (2017). On the pragmatic design of literature studies in software engineering: an experience-based guideline. Empirical software engineering, 22:2852–2891.
Kumar, Y., Manikandan, A., Li, J. J., e Morreale, P. (2024). Preliminary results from integrating chatbots and low-code ai in computer science coursework. Em 2024 IEEE Integrated STEM Education Conference (ISEC), páginas 1–4. IEEE.
Kuo, Y.-C. e Chen, Y.-A. (2023). The impact of chatbots using concept maps on correction outcomes–a case study of programming courses. Education and Information Technologies, 28(7):7899–7925.
Lane, H. C. e VanLehn, K. (2003). Coached program planning: Dialogue-based support for novice program design. Em Proceedings of the 34th SIGCSE technical symposium on Computer science education, páginas 148–152.
Lee, J. S., Liu, F., e Cai, T. (2024). Code debugging with llm-generated explanations of programming error messages. Em 2024 IEEE 13th International Conference on Engineering Education (ICEED), páginas 1–5. IEEE.
Lepp, M. e Kaimre, J. (2025). Does generative ai help in learning programming: Students’ perceptions, reported use and relation to performance. Computers in Human Behavior Reports, 18:100642.
Lin, Y.-H. (2022). Chatbot script design for programming language learning. Em Proceedings of the 5th IEEE Eurasian Conference on Educational Innovation (ECEI). IEEE.
Liu, S., Yu, Z., Huang, F., Bulbulia, Y., Bergen, A., e Liut, M. (2024). Can small language models with retrieval-augmented generation replace large language models when learning computer science? Em Proceedings of the ACM Conference on Computing Education. ACM.
López-Pernas, S., Gordillo, A., Barra, E., e Quemada, J. (2019). Examining the use of an educational escape room for teaching programming in a higher education setting. IEEE Access, 7:31723–31737.
Luxton-Reilly, A. (2016). Learning to program is easy. Em Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education, páginas 284–289.
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., e Daradoumis, A. (2022). Educational ai chatbots for content and language integrated learning. Applied Sciences, 12(7):3239.
Mitchell, C. M., Boyer, K. E., e Lester, J. C. (2013). When to intervene: Toward a markov decision process dialogue policy for computer science tutoring. Em The First Workshop on AI-supported Education for Computer Science (AIEDCS 2013), página 40. Citeseer.
Modran, H., Ursutiu, D., Samoila, C., e Gherman Dolhăscu, E.-C. (2024). Developing a gpt chatbot model for students programming education. Em Advances in Intelligent Systems and Computing. Springer.
Nguyen, H. D., Tran, T.-V., Pham, X.-T., Huynh, A. T., Pham, V. T., e Nguyen, D. (2022). Design intelligent educational chatbot for information retrieval based on integrated knowledge bases. IAENG International Journal of Computer Science, 49(2):531–541.
Okonkwo, C. W. e Ade-Ibijola, A. (2020). Python-bot: A chatbot for teaching python programming. Engineering Letters, 29(1).
Okonkwo, C. W. e Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2:100033.
Okonkwo, C. W. e Ade-Ibijola, A. (2022). Revision-bot: A chatbot for studying past questions in introductory programming. IAENG International Journal of Computer Science, 49(3).
Palahan, S. (2025). Pythonpal: Enhancing online programming education through chatbot-driven personalized feedback. IEEE Transactions on Learning Technologies.
Penney, J., Pimentel, J. F., Steinmacher, I., e Gerosa, M. A. (2023). Anticipating user needs: Insights from design fiction on conversational agents for computational thinking. Em International Workshop on Chatbot Research and Design, páginas 204–219. Springer.
Petersen, K., Vakkalanka, S., e Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering: An update. Information and Software Technology, 64:1–18.
Pirzado, F. A., Ahmed, A., Mendoza-Urdiales, R. A., e Terashima-Marin, H. (2024). Navigating the pitfalls: Analyzing the behavior of llms as a coding assistant for computer science students-a systematic review of the literature. IEEE Access.
Prather, J., Reeves, B. N., Leinonen, J., MacNeil, S., Randrianasolo, A. S., Becker, B. A., Kimmel, B., Wright, J., e Briggs, B. (2024). The widening gap: The benefits and harms of generative ai for novice programmers. Em Proceedings of the ACM Conference on International Computing Education Research V.1 (ICER ’24), páginas 469–486, Melbourne, VIC, Australia. ACM.
Renkl, A. (2014). Toward an instructionally oriented theory of example-based learning. Cognitive science, 38(1):1–37.
Robins, A. V. (2019). 12 novice programmers and introductory programming. The Cambridge handbook of computing education research, página 327.
Ruan, S., Jiang, L., Xu, J., Tham, B. J.-K., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., e Landay, J. A. (2019). Quizbot: A dialogue-based adaptive learning system for factual knowledge. Em Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, páginas 1–13.
Scholl, A., Schiffner, D., e Kiesler, N. (2025). Students’ use of chatgpt in an introductory programming course: A deep dive into chat protocols and the student perspective. eleed, Issue 16:1–20.
Smutny, P. e Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the facebook messenger. Computers & Education, 151:103862.
Sweller, J., Ayres, P., e Kalyuga, S. (2011). Cognitive Load Theory. Springer.
Sweller, J., Van Merrienboer, J. J., e Paas, F. G. (1998). Cognitive architecture and instructional design. Educational psychology review, páginas 251–296.
Tayeb, A., Alahmadi, M., Tajik, E., e Haiduc, S. (2024). Investigating developers’ preferences for learning and issue resolution resources in the chatgpt era. arXiv preprint arXiv:2410.08411.
Troussas, C., Krouska, A., Papakostas, C., Mylonas, P., e Sgouropoulou, C. (2024). Assessing the impact of integrating chatgpt as an advice generator in educational software. Em 2024 9th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), páginas 127–133. IEEE.
Vadaparty, A., Geng, F., Smith IV, D. H., Benario, J. G., Zingaro, D., e Porter, L. (2025). Achievement goals in cs1-llm. Em Proceedings of the 27th Australasian Computing Education Conference, páginas 144–153.
Van Merrienboer, J. J. e Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational psychology review, 17:147–177.
Verleger, M. e Pembridge, J. (2018). A pilot study integrating an ai-driven chatbot in an introductory programming course. Em 2018 IEEE frontiers in education conference (FIE), páginas 1–4. IEEE.
Vintila, F. (2024). Avert (authorship verification and evaluation through responsive testing): an llm-based procedure that interactively verifies code authorship and evaluates student understanding. Em Proceedings of the 21st International Conference on Information Technology Based Higher Education and Training (ITHET). IEEE.
Wei, S., Luo, Y., Chen, S., Huang, T., e Xiang, Y. (2023). Deep research and analysis of chatgpt based on multiple testing experiments. Em 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), páginas 123–131. IEEE.
Wijaya, O. C. e Purwarianti, A. (2024). An interactive question-answering system using large language model and retrieval-augmented generation in an intelligent tutoring system on the programming domain. Em Proceedings of the 2024 International Conference on Advanced Informatics: Concept, Theory and Application (ICAICTA). IEEE.
Winkler, R., Hobert, S., Salovaara, A., Söllner, M., e Leimeister, J. M. (2020). Sara, the lecturer: Improving learning in online education with a scaffolding-based conversational agent. Em Proceedings of the 2020 CHI conference on human factors in computing systems, páginas 1–14.
Xiao, R., Hou, X., Kumar, H., Moore, S., Stamper, J., e Liut, M. (2024). A preliminary analysis of students’ help requests with an llm-powered chatbot when completing cs1 assignments. Em Proceedings of the 8th Educational Data Mining in Computer Science Education Workshop (CSEDM’24), Atlanta, GA. CEUR-WS, CEUR Workshop Proceedings.
Xue, Y., Chen, H., Bai, G. R., Tairas, R., e Huang, Y. (2024). Does chatgpt help with introductory programming? an experiment of students using chatgpt in cs1. Em Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training, páginas 331–341.
Zabala, E. e Narman, H. S. (2024). Development and evaluation of an ai-enhanced python programming education system. Em Proceedings of the 15th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference. IEEE.
Zhang, H., Kitchenham, B., e Pfahl, D. (2010). Software process simulation modeling: an extended systematic review. Em International Conference on Software Process, páginas 309–320. Springer.
Alves, G., Rebouças, A., e Scaico, P. (2019). Coding dojo como prática de aprendizagem colaborativa para apoiar o ensino introdutório de programação: Um estudo de caso. Em Anais do XXVII Workshop sobre Educação em Computação, páginas 276–290. SBC.
Andersen-Kiel, N. e Linos, P. (2024). Using chatgpt in undergraduate computer science and software engineering courses: A students’ perspective. Em Proceedings of the 2024 IEEE Frontiers in Education Conference (FIE), páginas 1–9. IEEE.
Ardimansyah, M. e Widianto, M. (2021). Development of online learning media based on telegram chatbot (case studies: Programming courses). Em Journal of Physics: Conference Series, volume 1987, página 012006. IOP Publishing.
Arteaga Garcia, E. J., Nicolaci Pimentel, J. F., Feng, Z., Gerosa, M., Steinmacher, I., e Sarma, A. (2024). How to support ml end-user programmers through a conversational agent. Em Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, páginas 1–12.
Bilgin, T. T. e Yavuz, E. (2022). Integrating a dialogue tree based turkish chatbot into an open source python coding editor. Em 2022 3rd International Informatics and Software Engineering Conference (IISEC), páginas 1–5. IEEE.
Bobadilla, S., Glassey, R., Bergel, A., e Monperrus, M. (2023). Sobo: A feedback bot to nudge code quality in programming courses. IEEE Software, 41(2):68–76.
Bran, A. M. e Schwaller, P. (2024). Transformers and large language models for chemistry and drug discovery. Em Drug Development Supported by Informatics, páginas 143–163. Springer.
Callejo, P., Alario-Hoyos, C., e Delgado-Kloos, C. (2024). Evaluating chatgpt impact on the programming learning outcomes of students in a big data course. International Journal of Engineering Education, 40(4):863–872.
Carreira, G., Silva, L., Mendes, A. J., e Oliveira, H. G. (2022). Pyo, a chatbot assistant for introductory programming students. Em 2022 International Symposium on Computers in Education (SIIE), páginas 1–6. IEEE.
Chen, T., Xu, L., e Zhu, K. (2021). Fritzbot: A data-driven conversational agent for physical-computing system design. International Journal of Human-Computer Studies, 155:102699.
Clarizia, F., Colace, F., Lombardi, M., Pascale, F., e Santaniello, D. (2018). Chatbot: An education support system for student. Em International Symposium on Cyberspace Safety and Security, páginas 291–302. Springer.
Coronado, M., Iglesias, C. A., Carrera, Á., e Mardomingo, A. (2018). A cognitive assistant for learning java featuring social dialogue. International Journal of Human-Computer Studies, 117:55–67.
Cubillos, C., Mellado, R., Cabrera-Paniagua, D., e Urra, E. (2025). Generative artificial intelligence in computer programming: Does it enhance learning, motivation, and the learning environment? IEEE Access.
da Silva, C. A. G., Ramos, F. N., de Moraes, R. V., e dos Santos, E. L. (2024). Chatgpt: Challenges and benefits in software programming for higher education. Sustainability, 16(3):1245.
Ericsson, K. A., Krampe, R. T., e Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological review, 100(3):363.
Farah, J. C., Spaenlehauer, B., Ingram, S., Purohit, A. K., Holzer, A., e Gillet, D. (2023). Harnessing rule-based chatbots to support teaching python programming best practices. Em Proceedings of the International Conference on Educational Technology. Springer.
Fernandez, C., Sánchez-Soto, E., Aguilar Cisnero, J., e Juárez-Ramírez, R. (2024). Exploring the frontier of software engineering education with chatbots. Programming and Computer Software, 50(8):796–815.
Frankford, E., Sauerwein, C., Bassner, P., Krusche, S., e Breu, R. (2024). Ai-tutoring in software engineering education. Em Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training, páginas 309–319.
Gabriella, A., Gui, A., e Chanda, R. C. (2024). The use of chatbot and its impact on academic achievement. Em 2024 IEEE Symposium on Industrial Electronics & Applications (ISIEA), páginas 1–6. IEEE.
Groothuijsen, S., van den Beemt, A., Remmers, J. C., e van Meeuwen, L. W. (2024). Ai chatbots in programming education: students’ use in a scientific computing course and consequences for learning. Computers and Education: Artificial Intelligence, 7:100290.
Guo, P. J. (2018). Non-native english speakers learning computer programming: Barriers, desires, and design opportunities. Em Proceedings of the 2018 CHI conference on human factors in computing systems, páginas 1–14.
Gupta, R., Goyal, H., Kumar, D., Mehra, A., Sharma, S., Mittal, K., e Challa, J. S. (2025a). Sakshm ai: Advancing ai-assisted coding education for engineering students in india through socratic tutoring and comprehensive feedback. arXiv preprint arXiv:2503.12479.
Gupta, R. D., Hosain, M. T., Mridha, M., e Ahmed, S. U. (2025b). Multimodal programming in computer science with interactive assistance powered by large language model. Em International Conference on Human-Computer Interaction, páginas 59–69. Springer.
Haindl, P. e Weinberger, G. (2024a). Does chatgpt help novice programmers write better code? results from static code analysis. IEEE Access, 12:114146–114160.
Haindl, P. e Weinberger, G. (2024b). Students’ experiences of using chatgpt in an undergraduate programming course. IEEE Access, 12:43519–43530.
Hamzah, W. W., Ismail, I., Yusof, M. K., Saany, S. M., e Yacob, A. (2021). Using learning analytics to explore responses from student conversations with chatbot for education. International Journal of Engineering Pedagogy, 11(6):70–84.
Hien, H. T., Cuong, P.-N., Nam, L. N. H., Nhung, H. L. T. K., e Thang, L. D. (2018). Intelligent assistants in higher-education environments: the fit-ebot, a chatbot for administrative and learning support. Em Proceedings of the 9th International Symposium on Information and Communication Technology, páginas 69–76.
Hobert, S. (2019). Say hello to ‘coding tutor’! design and evaluation of a chatbot-based learning system supporting students to learn to program.
Ismail, M. e Ade-Ibijola, A. (2019). Lecturer’s apprentice: A chatbot for assisting novice programmers. Em 2019 international multidisciplinary information technology and engineering conference (IMITEC), páginas 1–8. IEEE.
Jury, B., Lorusso, A., Leinonen, J., Denny, P., e Luxton-Reilly, A. (2024). Evaluating llm-generated worked examples in an introductory programming course. Em Proceedings of the 26th Australasian computing education conference, páginas 77–86.
Kasinathan, V., Mustapha, A., Siow, S., e Hopman, M. (2018). Tictad: A chatterbot for learning visual c programming based on expert system,". Indonesian Journal of Electrical Engineering and Computer Science, 11(2):740–746.
Keuning, H., Jeuring, J., e Heeren, B. (2018). A systematic literature review of automated feedback generation for programming exercises. ACM Transactions on Computing Education (TOCE), 19(1):1–43.
Kiesler, N., Lohr, D., e Keuning, H. (2023). Exploring the potential of large language models to generate formative programming feedback. Em 2023 IEEE Frontiers in Education Conference (FIE), páginas 1–5. IEEE.
Kitchenham, B. e Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering.
Kitchenham, B., Madeyski, L., e Budgen, D. (2022). Segress: Software engineering guidelines for reporting secondary studies. IEEE Transactions on Software Engineering, 49(3):1273–1298.
Kosar, T., Ostojic, D., Liu, Y. D., e Mernik, M. (2024). Computer science education in chatgpt era: Experiences from an experiment in a programming course for novice programmers. Mathematics, 12(6):629.
Kuhrmann, M., Fernández, D. M., e Daneva, M. (2017). On the pragmatic design of literature studies in software engineering: an experience-based guideline. Empirical software engineering, 22:2852–2891.
Kumar, Y., Manikandan, A., Li, J. J., e Morreale, P. (2024). Preliminary results from integrating chatbots and low-code ai in computer science coursework. Em 2024 IEEE Integrated STEM Education Conference (ISEC), páginas 1–4. IEEE.
Kuo, Y.-C. e Chen, Y.-A. (2023). The impact of chatbots using concept maps on correction outcomes–a case study of programming courses. Education and Information Technologies, 28(7):7899–7925.
Lane, H. C. e VanLehn, K. (2003). Coached program planning: Dialogue-based support for novice program design. Em Proceedings of the 34th SIGCSE technical symposium on Computer science education, páginas 148–152.
Lee, J. S., Liu, F., e Cai, T. (2024). Code debugging with llm-generated explanations of programming error messages. Em 2024 IEEE 13th International Conference on Engineering Education (ICEED), páginas 1–5. IEEE.
Lepp, M. e Kaimre, J. (2025). Does generative ai help in learning programming: Students’ perceptions, reported use and relation to performance. Computers in Human Behavior Reports, 18:100642.
Lin, Y.-H. (2022). Chatbot script design for programming language learning. Em Proceedings of the 5th IEEE Eurasian Conference on Educational Innovation (ECEI). IEEE.
Liu, S., Yu, Z., Huang, F., Bulbulia, Y., Bergen, A., e Liut, M. (2024). Can small language models with retrieval-augmented generation replace large language models when learning computer science? Em Proceedings of the ACM Conference on Computing Education. ACM.
López-Pernas, S., Gordillo, A., Barra, E., e Quemada, J. (2019). Examining the use of an educational escape room for teaching programming in a higher education setting. IEEE Access, 7:31723–31737.
Luxton-Reilly, A. (2016). Learning to program is easy. Em Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education, páginas 284–289.
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., e Daradoumis, A. (2022). Educational ai chatbots for content and language integrated learning. Applied Sciences, 12(7):3239.
Mitchell, C. M., Boyer, K. E., e Lester, J. C. (2013). When to intervene: Toward a markov decision process dialogue policy for computer science tutoring. Em The First Workshop on AI-supported Education for Computer Science (AIEDCS 2013), página 40. Citeseer.
Modran, H., Ursutiu, D., Samoila, C., e Gherman Dolhăscu, E.-C. (2024). Developing a gpt chatbot model for students programming education. Em Advances in Intelligent Systems and Computing. Springer.
Nguyen, H. D., Tran, T.-V., Pham, X.-T., Huynh, A. T., Pham, V. T., e Nguyen, D. (2022). Design intelligent educational chatbot for information retrieval based on integrated knowledge bases. IAENG International Journal of Computer Science, 49(2):531–541.
Okonkwo, C. W. e Ade-Ibijola, A. (2020). Python-bot: A chatbot for teaching python programming. Engineering Letters, 29(1).
Okonkwo, C. W. e Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2:100033.
Okonkwo, C. W. e Ade-Ibijola, A. (2022). Revision-bot: A chatbot for studying past questions in introductory programming. IAENG International Journal of Computer Science, 49(3).
Palahan, S. (2025). Pythonpal: Enhancing online programming education through chatbot-driven personalized feedback. IEEE Transactions on Learning Technologies.
Penney, J., Pimentel, J. F., Steinmacher, I., e Gerosa, M. A. (2023). Anticipating user needs: Insights from design fiction on conversational agents for computational thinking. Em International Workshop on Chatbot Research and Design, páginas 204–219. Springer.
Petersen, K., Vakkalanka, S., e Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering: An update. Information and Software Technology, 64:1–18.
Pirzado, F. A., Ahmed, A., Mendoza-Urdiales, R. A., e Terashima-Marin, H. (2024). Navigating the pitfalls: Analyzing the behavior of llms as a coding assistant for computer science students-a systematic review of the literature. IEEE Access.
Prather, J., Reeves, B. N., Leinonen, J., MacNeil, S., Randrianasolo, A. S., Becker, B. A., Kimmel, B., Wright, J., e Briggs, B. (2024). The widening gap: The benefits and harms of generative ai for novice programmers. Em Proceedings of the ACM Conference on International Computing Education Research V.1 (ICER ’24), páginas 469–486, Melbourne, VIC, Australia. ACM.
Renkl, A. (2014). Toward an instructionally oriented theory of example-based learning. Cognitive science, 38(1):1–37.
Robins, A. V. (2019). 12 novice programmers and introductory programming. The Cambridge handbook of computing education research, página 327.
Ruan, S., Jiang, L., Xu, J., Tham, B. J.-K., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., e Landay, J. A. (2019). Quizbot: A dialogue-based adaptive learning system for factual knowledge. Em Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, páginas 1–13.
Scholl, A., Schiffner, D., e Kiesler, N. (2025). Students’ use of chatgpt in an introductory programming course: A deep dive into chat protocols and the student perspective. eleed, Issue 16:1–20.
Smutny, P. e Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the facebook messenger. Computers & Education, 151:103862.
Sweller, J., Ayres, P., e Kalyuga, S. (2011). Cognitive Load Theory. Springer.
Sweller, J., Van Merrienboer, J. J., e Paas, F. G. (1998). Cognitive architecture and instructional design. Educational psychology review, páginas 251–296.
Tayeb, A., Alahmadi, M., Tajik, E., e Haiduc, S. (2024). Investigating developers’ preferences for learning and issue resolution resources in the chatgpt era. arXiv preprint arXiv:2410.08411.
Troussas, C., Krouska, A., Papakostas, C., Mylonas, P., e Sgouropoulou, C. (2024). Assessing the impact of integrating chatgpt as an advice generator in educational software. Em 2024 9th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), páginas 127–133. IEEE.
Vadaparty, A., Geng, F., Smith IV, D. H., Benario, J. G., Zingaro, D., e Porter, L. (2025). Achievement goals in cs1-llm. Em Proceedings of the 27th Australasian Computing Education Conference, páginas 144–153.
Van Merrienboer, J. J. e Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational psychology review, 17:147–177.
Verleger, M. e Pembridge, J. (2018). A pilot study integrating an ai-driven chatbot in an introductory programming course. Em 2018 IEEE frontiers in education conference (FIE), páginas 1–4. IEEE.
Vintila, F. (2024). Avert (authorship verification and evaluation through responsive testing): an llm-based procedure that interactively verifies code authorship and evaluates student understanding. Em Proceedings of the 21st International Conference on Information Technology Based Higher Education and Training (ITHET). IEEE.
Wei, S., Luo, Y., Chen, S., Huang, T., e Xiang, Y. (2023). Deep research and analysis of chatgpt based on multiple testing experiments. Em 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), páginas 123–131. IEEE.
Wijaya, O. C. e Purwarianti, A. (2024). An interactive question-answering system using large language model and retrieval-augmented generation in an intelligent tutoring system on the programming domain. Em Proceedings of the 2024 International Conference on Advanced Informatics: Concept, Theory and Application (ICAICTA). IEEE.
Winkler, R., Hobert, S., Salovaara, A., Söllner, M., e Leimeister, J. M. (2020). Sara, the lecturer: Improving learning in online education with a scaffolding-based conversational agent. Em Proceedings of the 2020 CHI conference on human factors in computing systems, páginas 1–14.
Xiao, R., Hou, X., Kumar, H., Moore, S., Stamper, J., e Liut, M. (2024). A preliminary analysis of students’ help requests with an llm-powered chatbot when completing cs1 assignments. Em Proceedings of the 8th Educational Data Mining in Computer Science Education Workshop (CSEDM’24), Atlanta, GA. CEUR-WS, CEUR Workshop Proceedings.
Xue, Y., Chen, H., Bai, G. R., Tairas, R., e Huang, Y. (2024). Does chatgpt help with introductory programming? an experiment of students using chatgpt in cs1. Em Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training, páginas 331–341.
Zabala, E. e Narman, H. S. (2024). Development and evaluation of an ai-enhanced python programming education system. Em Proceedings of the 15th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference. IEEE.
Zhang, H., Kitchenham, B., e Pfahl, D. (2010). Software process simulation modeling: an extended systematic review. Em International Conference on Software Process, páginas 309–320. Springer.
Publicado
24/11/2025
Como Citar
GARCIA, Marcelino; GARCIA, Renato; PARIZOTTO, Arthur; MENDES, Andre; VALLE, Pedro; VILELA, Ricardo; BALANCIERI, Renato; SILVA, Williamson.
A Systematic Mapping Study on Chatbots in Programming Education. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 36. , 2025, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 378-395.
DOI: https://doi.org/10.5753/sbie.2025.12323.
