AI-Assisted learning: intelligent tutoring system for the introduction to programming course
This thesis presents the development of an AI-powered intelligent tutoring system to address challenges in the Introduction to Programming course at Universidad de los Andes. Using the Lean Startup methodology, we developed a virtual assistant that connects to the Senecode database to provide person...
- Autores:
-
Osorio Cárdenas, Daniel
Guatibonza Briceño, Pablo Alejandro
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2025
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/75502
- Acceso en línea:
- https://hdl.handle.net/1992/75502
- Palabra clave:
- Intelligent tutoring system
Chatbot
Artificial intelligence
AI
Education
Programming
AI agents
Agents
Retrieval-Augmented Generation
Inteligencia artificial
IA
Educación
Programación
LangGraph
RAG
Ingeniería
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
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AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
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AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
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AI-Assisted learning: intelligent tutoring system for the introduction to programming course Intelligent tutoring system Chatbot Artificial intelligence AI Education Programming AI agents Agents Retrieval-Augmented Generation Inteligencia artificial IA Educación Programación LangGraph RAG Ingeniería |
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AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
| title_full |
AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
| title_fullStr |
AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
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AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
| title_sort |
AI-Assisted learning: intelligent tutoring system for the introduction to programming course |
| dc.creator.fl_str_mv |
Osorio Cárdenas, Daniel Guatibonza Briceño, Pablo Alejandro |
| dc.contributor.advisor.none.fl_str_mv |
Manrique Piramanrique, Rubén Francisco |
| dc.contributor.author.none.fl_str_mv |
Osorio Cárdenas, Daniel Guatibonza Briceño, Pablo Alejandro |
| dc.subject.keyword.eng.fl_str_mv |
Intelligent tutoring system Chatbot Artificial intelligence AI Education Programming AI agents Agents Retrieval-Augmented Generation |
| topic |
Intelligent tutoring system Chatbot Artificial intelligence AI Education Programming AI agents Agents Retrieval-Augmented Generation Inteligencia artificial IA Educación Programación LangGraph RAG Ingeniería |
| dc.subject.keyword.spa.fl_str_mv |
Inteligencia artificial IA Educación Programación |
| dc.subject.keyword.none.fl_str_mv |
LangGraph RAG |
| dc.subject.themes.spa.fl_str_mv |
Ingeniería |
| description |
This thesis presents the development of an AI-powered intelligent tutoring system to address challenges in the Introduction to Programming course at Universidad de los Andes. Using the Lean Startup methodology, we developed a virtual assistant that connects to the Senecode database to provide personalized support to students. Senecode is an online platform where students in the course can practice coding exercises in Python and receive automated feedback. The system included a feedback agent to evaluate the student’s code and a RAG agent to guide the students through relevant topics. We evaluated the system’s impact on student learning outcomes and engagement through iterative testing and refinement based on user feedback. |
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2025-01-20T19:41:46Z |
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2025-01-20 |
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Trabajo de grado - Pregrado |
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Helen Crompton and Diane Burke. 2023. Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1):22. Paul Denny, Stephen MacNeil, Jaromir Savelka, Leo Porter, and Andrew Luxton-Reilly. 2024. Desirable Characteristics for AI Teaching Assistants in Programming Education. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1, pages 408–414, Milan Italy. ACM. Rida Indah Fariani, Kasiyah Junus, and Harry Budi Santoso. 2023. A Systematic Literature Review on Personalised Learning in the Higher Education Context. Technology, Knowledge and Learning, 28(2):449–476. Enkelejda Kasneci, Kathrin Sessler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, Stephan Krusche, Gitta Kutyniok, Tilman Michaeli, Claudia Nerdel, Jürgen Pfeffer, Oleksandra Poquet, Michael Sailer, Albrecht Schmidt, Tina Seidel, Matthias Stadler, Jochen Weller, Jochen Kuhn, and Gjergji Kasneci. 2023. ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103:102274. Sophia Krause-Levy, Rachel S. Lim, Ismael Villegas Molina, Yingjun Cao, and Leo Porter. 2022. An Exploration of Student-Tutor Interactions in Computing. In Proceedings of the 27th ACM Conference on Innovation and Technology in Computer Science Education Vol. 1, ITiCSE ’22, pages 435–441, New York, NY, USA. Association for Computing Machinery. Lazar Krstić, Veljko Aleksić, and Marija Krstić. 2022. Artificial Intelligence in Education: A Review. In Proceedings TIE 2022, pages 223–228. University of Kragujevac, Faculty of Technical Sciences Čačak. Mohammad Amin Kuhail, Nazik Alturki, Salwa Alramlawi, and Kholood Alhejori. 2023. Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28(1):973–1018. Lasha Labadze, Maya Grigolia, and Lela Machaidze. 2023. Role of AI chatbots in education: systematic literature review. International Journal of Educational Technology in Higher Education, 20(1):56. Mark Liffiton, Brad Sheese, Jaromir Savelka, and Paul Denny. 2023. CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes. ArXiv:2308.06921 [cs]. Dani Mahaini. 2024. Generative AI in Computer Science Education: A Study on Academic Performance. Publisher: University of Twente. Chinedu Wilfred Okonkwo and Abejide Ade-Ibijola. 2021. Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2:100033. Maciej Pankiewicz and Ryan Baker. 2023. Large Language Models (GPT) for automating feedback on programming assignments. Olga Petrovska, Lee Clift, Faron Moller, and Rebecca Pearsall. 2024. Incorporating Generative AI into Software Development Education. In Proceedings of the 8th Conference on Computing Education Practice, pages 37–40, Durham United Kingdom. ACM. José Quiroga Pérez, Thanasis Daradoumis, and Joan Manuel Marquès Puig. 2020. Rediscovering the use of chatbots in education: A systematic literature review. Computer Applications in Engineering Education, 28(6):1549–1565. _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/cae.22326. Eric Ries. 2011. The Lean Startup, 1st edition. Penguin Random House LLC. Brad Sheese, Mark Liffiton, Jaromir Savelka, and Paul Denny. 2024. Patterns of Student Help-Seeking When Using a Large Language Model-Powered Programming Assistant. In Proceedings of the 26th Australasian Computing Education Conference, pages 49–57. ArXiv:2310.16984 [cs]. Borsci Simone, Malizia Alessio, Schmettow Martin, van der Velde Frank, Tariverdiyeva Gunay, Balaji Divyaa, and Alan Chamberlain. 2022. The Chatbot Usability Scale: the Design and Pilot of a Usability Scale for Interaction with AI-Based Conversational Agents. Personal and Ubiquitous Computing, 26(1):95–119. Num Pages: 95-119 Place: London, Netherlands Publisher: Springer Nature B.V. Aaron J. Smith, Kristy Elizabeth Boyer, Jeffrey Forbes, Sarah Heckman, and Ketan Mayer-Patel. 2017. My Digital Hand: A Tool for Scaling Up One-to-One Peer Teaching in Support of Computer Science Learning. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE ’17, pages 549–554, New York, NY, USA. Association for Computing Machinery. Fati Tahiru. 2021. AI in Education: A Systematic Literature Review. Journal of Cases on Information Technology (JCIT), 23(1):1–20. Publisher: IGI Global Scientific Publishing. Sebastian Wollny, Jan Schneider, Daniele Di Mitri, Joshua Weidlich, Marc Rittberger, and Hendrik Drachsler. 2021. Are We There Yet? - A Systematic Literature Review on Chatbots in Education. Frontiers in Artificial Intelligence, 4. Publisher: Frontiers. Zhiyi Xu. 2024. AI in education: Enhancing learning experiences and student outcomes. Applied and Computational Engineering, 51:104–111. Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, and Zhen-Hua Ling. 2024. Corrective Retrieval Augmented Generation. ArXiv:2401.15884. Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023. ReAct: Synergizing Reasoning and Acting in Language Models. ArXiv:2210.03629 [cs]. |
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Manrique Piramanrique, Rubén Franciscovirtual::22226-1Osorio Cárdenas, DanielGuatibonza Briceño, Pablo Alejandro2025-01-20T19:41:46Z2025-01-20T19:41:46Z2025-01-20https://hdl.handle.net/1992/75502instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/This thesis presents the development of an AI-powered intelligent tutoring system to address challenges in the Introduction to Programming course at Universidad de los Andes. Using the Lean Startup methodology, we developed a virtual assistant that connects to the Senecode database to provide personalized support to students. Senecode is an online platform where students in the course can practice coding exercises in Python and receive automated feedback. The system included a feedback agent to evaluate the student’s code and a RAG agent to guide the students through relevant topics. We evaluated the system’s impact on student learning outcomes and engagement through iterative testing and refinement based on user feedback.Esta tesis presenta el desarrollo de un sistema de tutoría inteligente impulsado por IA para abordar los desafíos en el curso de Introducción a la Programación de la Universidad de los Andes. Utilizando la metodología Lean Startup, desarrollamos un asistente virtual que se conecta a la base de datos de Senecode para proporcionar soporte personalizado a los estudiantes. Senecode es una plataforma en línea donde los estudiantes del curso pueden practicar ejercicios de programación en Python y recibir retroalimentación automatizada. El sistema incluye un agente de retroalimentación para evaluar el código del estudiante y un agente RAG para guiar a los estudiantes a través de temas relevantes. Evaluamos el impacto del sistema en los resultados de aprendizaje y la participación de los estudiantes mediante pruebas iterativas y refinamientos basados en la retroalimentación de los usuarios.Pregrado16 páginasapplication/pdfengUniversidad de los AndesIngeniería de Sistemas y ComputaciónFacultad de IngenieríaDepartamento de Ingeniería de Sistemas y ComputaciónAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2AI-Assisted learning: intelligent tutoring system for the introduction to programming courseTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPIntelligent tutoring systemChatbotArtificial intelligenceAIEducationProgrammingAI agentsAgentsRetrieval-Augmented GenerationInteligencia artificialIAEducaciónProgramaciónLangGraphRAGIngenieríaHelen Crompton and Diane Burke. 2023. Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1):22.Paul Denny, Stephen MacNeil, Jaromir Savelka, Leo Porter, and Andrew Luxton-Reilly. 2024. Desirable Characteristics for AI Teaching Assistants in Programming Education. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1, pages 408–414, Milan Italy. ACM.Rida Indah Fariani, Kasiyah Junus, and Harry Budi Santoso. 2023. A Systematic Literature Review on Personalised Learning in the Higher Education Context. Technology, Knowledge and Learning, 28(2):449–476.Enkelejda Kasneci, Kathrin Sessler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, Stephan Krusche, Gitta Kutyniok, Tilman Michaeli, Claudia Nerdel, Jürgen Pfeffer, Oleksandra Poquet, Michael Sailer, Albrecht Schmidt, Tina Seidel, Matthias Stadler, Jochen Weller, Jochen Kuhn, and Gjergji Kasneci. 2023. ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103:102274.Sophia Krause-Levy, Rachel S. Lim, Ismael Villegas Molina, Yingjun Cao, and Leo Porter. 2022. An Exploration of Student-Tutor Interactions in Computing. In Proceedings of the 27th ACM Conference on Innovation and Technology in Computer Science Education Vol. 1, ITiCSE ’22, pages 435–441, New York, NY, USA. Association for Computing Machinery.Lazar Krstić, Veljko Aleksić, and Marija Krstić. 2022. Artificial Intelligence in Education: A Review. In Proceedings TIE 2022, pages 223–228. University of Kragujevac, Faculty of Technical Sciences Čačak.Mohammad Amin Kuhail, Nazik Alturki, Salwa Alramlawi, and Kholood Alhejori. 2023. Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28(1):973–1018.Lasha Labadze, Maya Grigolia, and Lela Machaidze. 2023. Role of AI chatbots in education: systematic literature review. International Journal of Educational Technology in Higher Education, 20(1):56.Mark Liffiton, Brad Sheese, Jaromir Savelka, and Paul Denny. 2023. CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes. ArXiv:2308.06921 [cs].Dani Mahaini. 2024. Generative AI in Computer Science Education: A Study on Academic Performance. Publisher: University of Twente.Chinedu Wilfred Okonkwo and Abejide Ade-Ibijola. 2021. Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2:100033.Maciej Pankiewicz and Ryan Baker. 2023. Large Language Models (GPT) for automating feedback on programming assignments.Olga Petrovska, Lee Clift, Faron Moller, and Rebecca Pearsall. 2024. Incorporating Generative AI into Software Development Education. In Proceedings of the 8th Conference on Computing Education Practice, pages 37–40, Durham United Kingdom. ACM.José Quiroga Pérez, Thanasis Daradoumis, and Joan Manuel Marquès Puig. 2020. Rediscovering the use of chatbots in education: A systematic literature review. Computer Applications in Engineering Education, 28(6):1549–1565. _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/cae.22326.Eric Ries. 2011. The Lean Startup, 1st edition. Penguin Random House LLC.Brad Sheese, Mark Liffiton, Jaromir Savelka, and Paul Denny. 2024. Patterns of Student Help-Seeking When Using a Large Language Model-Powered Programming Assistant. In Proceedings of the 26th Australasian Computing Education Conference, pages 49–57. ArXiv:2310.16984 [cs].Borsci Simone, Malizia Alessio, Schmettow Martin, van der Velde Frank, Tariverdiyeva Gunay, Balaji Divyaa, and Alan Chamberlain. 2022. The Chatbot Usability Scale: the Design and Pilot of a Usability Scale for Interaction with AI-Based Conversational Agents. Personal and Ubiquitous Computing, 26(1):95–119. Num Pages: 95-119 Place: London, Netherlands Publisher: Springer Nature B.V.Aaron J. Smith, Kristy Elizabeth Boyer, Jeffrey Forbes, Sarah Heckman, and Ketan Mayer-Patel. 2017. My Digital Hand: A Tool for Scaling Up One-to-One Peer Teaching in Support of Computer Science Learning. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE ’17, pages 549–554, New York, NY, USA. Association for Computing Machinery.Fati Tahiru. 2021. AI in Education: A Systematic Literature Review. Journal of Cases on Information Technology (JCIT), 23(1):1–20. Publisher: IGI Global Scientific Publishing.Sebastian Wollny, Jan Schneider, Daniele Di Mitri, Joshua Weidlich, Marc Rittberger, and Hendrik Drachsler. 2021. Are We There Yet? - A Systematic Literature Review on Chatbots in Education. Frontiers in Artificial Intelligence, 4. Publisher: Frontiers.Zhiyi Xu. 2024. AI in education: Enhancing learning experiences and student outcomes. Applied and Computational Engineering, 51:104–111.Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, and Zhen-Hua Ling. 2024. Corrective Retrieval Augmented Generation. ArXiv:2401.15884.Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023. ReAct: Synergizing Reasoning and Acting in Language Models. 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