Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education

Programming has become increasingly important in our society. However, the learning process presents significant challenges, particularly for novice students of introductory courses. From the students’ perspective, programming concepts are often perceived as complex and challenging to und...

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Main Authors: Renato De Souza Garcia, Joao Emilio Antonio Villa, Andre Luiz Mendes Miranda, Gilleanes Thorwald Araujo Guedes, Ana Carolina Oran, Paulo Silas Severo De Souza, Ricardo Ferreira Vilela, Pedro Henrique Dias Valle, Williamson Silva
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/11126108/
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author Renato De Souza Garcia
Joao Emilio Antonio Villa
Andre Luiz Mendes Miranda
Gilleanes Thorwald Araujo Guedes
Ana Carolina Oran
Paulo Silas Severo De Souza
Ricardo Ferreira Vilela
Pedro Henrique Dias Valle
Williamson Silva
author_facet Renato De Souza Garcia
Joao Emilio Antonio Villa
Andre Luiz Mendes Miranda
Gilleanes Thorwald Araujo Guedes
Ana Carolina Oran
Paulo Silas Severo De Souza
Ricardo Ferreira Vilela
Pedro Henrique Dias Valle
Williamson Silva
author_sort Renato De Souza Garcia
collection DOAJ
description Programming has become increasingly important in our society. However, the learning process presents significant challenges, particularly for novice students of introductory courses. From the students’ perspective, programming concepts are often perceived as complex and challenging to understand. Chatbots have emerged as promising and effective pedagogical agents, offering continuous support and personalized feedback throughout the programming learning process. In this paper, we present CoderBot, a pedagogical agent grounded in Example-Based Learning designed to assist novice students in comprehending programming concepts using correct and erroneous practical examples. To evaluate the self-efficacy and acceptance of CoderBot in the classroom, we conducted an exploratory study involving 103 undergraduate students from several regions of our country, all of whom were enrolled in introductory programming courses. The quantitative findings highlight the ease of use associated with CoderBot, along with noticeable improvements in students’ understanding of programming concepts and increased levels of motivation and self-confidence. Moreover, the qualitative results indicate that CoderBot holds the potential to be an effective pedagogical agent for supporting programming instruction, particularly in terms of clarity, accessibility, and ongoing assistance. However, the findings also suggest the need for further expansion of the available examples and improvements in the clarity of responses to realize the tool’s educational potential fully. These results offer valuable insights into integrating chatbots within academic environments, underscoring the role such tools can play in enhancing the learning experience for programming students.
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spelling doaj-art-2e9d26a2d0b8498eabea71887997bc762025-08-25T23:11:54ZengIEEEIEEE Access2169-35362025-01-011314500714502210.1109/ACCESS.2025.359935711126108Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming EducationRenato De Souza Garcia0https://orcid.org/0009-0008-9811-6058Joao Emilio Antonio Villa1https://orcid.org/0009-0008-3156-8383Andre Luiz Mendes Miranda2Gilleanes Thorwald Araujo Guedes3https://orcid.org/0000-0001-5457-2600Ana Carolina Oran4https://orcid.org/0000-0002-6446-7510Paulo Silas Severo De Souza5https://orcid.org/0000-0003-4945-3329Ricardo Ferreira Vilela6https://orcid.org/0000-0001-5242-4938Pedro Henrique Dias Valle7https://orcid.org/0000-0002-6929-7557Williamson Silva8https://orcid.org/0000-0003-1849-2675Federal University of Pampa, Alegrete, BrazilFederal University of Pampa, Alegrete, BrazilFederal University of Pampa, Alegrete, BrazilFederal University of Pampa, Alegrete, BrazilFederal University of Amazonas, Manaus, BrazilFederal University of Pampa, Alegrete, BrazilState University of Campinas (UNICAMP), Campinas, BrazilUniversity of São Paulo, São Paulo, BrazilFederal University of Cariri, Juazeiro do Norte, BrazilProgramming has become increasingly important in our society. However, the learning process presents significant challenges, particularly for novice students of introductory courses. From the students’ perspective, programming concepts are often perceived as complex and challenging to understand. Chatbots have emerged as promising and effective pedagogical agents, offering continuous support and personalized feedback throughout the programming learning process. In this paper, we present CoderBot, a pedagogical agent grounded in Example-Based Learning designed to assist novice students in comprehending programming concepts using correct and erroneous practical examples. To evaluate the self-efficacy and acceptance of CoderBot in the classroom, we conducted an exploratory study involving 103 undergraduate students from several regions of our country, all of whom were enrolled in introductory programming courses. The quantitative findings highlight the ease of use associated with CoderBot, along with noticeable improvements in students’ understanding of programming concepts and increased levels of motivation and self-confidence. Moreover, the qualitative results indicate that CoderBot holds the potential to be an effective pedagogical agent for supporting programming instruction, particularly in terms of clarity, accessibility, and ongoing assistance. However, the findings also suggest the need for further expansion of the available examples and improvements in the clarity of responses to realize the tool’s educational potential fully. These results offer valuable insights into integrating chatbots within academic environments, underscoring the role such tools can play in enhancing the learning experience for programming students.https://ieeexplore.ieee.org/document/11126108/Programming educationpedagogical agentscoderbotexample-based learningempirical studyself-efficacy
spellingShingle Renato De Souza Garcia
Joao Emilio Antonio Villa
Andre Luiz Mendes Miranda
Gilleanes Thorwald Araujo Guedes
Ana Carolina Oran
Paulo Silas Severo De Souza
Ricardo Ferreira Vilela
Pedro Henrique Dias Valle
Williamson Silva
Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education
IEEE Access
Programming education
pedagogical agents
coderbot
example-based learning
empirical study
self-efficacy
title Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education
title_full Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education
title_fullStr Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education
title_full_unstemmed Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education
title_short Theory Inspires, but Examples Engage: A Mixed-Methods Analysis of Worked Examples From CoderBot in Programming Education
title_sort theory inspires but examples engage a mixed methods analysis of worked examples from coderbot in programming education
topic Programming education
pedagogical agents
coderbot
example-based learning
empirical study
self-efficacy
url https://ieeexplore.ieee.org/document/11126108/
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