Enhancing Programming Education with an Active Learning Plan and Artificial Intelligence Integration
Artificial Intelligence (Al) is transforming higher education, bringing challenges and opportunities. Thus, instilling skills to leverage Al effectively and equip students for the future workforce is crucial. This requires a shift from traditional pedagogical methods toward active learning emphasizi...
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| Veröffentlicht in: | Revista FI-UPTC Jg. 33; H. 67; S. 1 - 16 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Tunja
Universidad Pedagogica y Tecnologica de Colombia
01.01.2024
Universidad Pedagógica y Tecnológica de Colombia |
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| ISSN: | 0121-1129, 2357-5328, 2357-5328 |
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| Abstract | Artificial Intelligence (Al) is transforming higher education, bringing challenges and opportunities. Thus, instilling skills to leverage Al effectively and equip students for the future workforce is crucial. This requires a shift from traditional pedagogical methods toward active learning emphasizing problem-solving, collaborative work, and the integration of Al tools. The proposed Active Learning Plan (ALP) addresses these imperatives. This plan encompasses research, problem-solving, pseudocode validation using Al tools such as ChatGPT, thorough code documentation, group collaboration, and evaluation. The ALP delves into the interplay between Al and higher education, and it challenges students to derive manual solutions, draft pseudocode, document it, and subsequently validate it through ChatGPT. Moreover, it fosters collaboration by encouraging the formation of groups of five to craft questionnaires on the core topic, which are later used for learning assessment. It is paramount for students to reflect on their experience, pinpointing strengths, weaknesses, and areas for improvement. The adopted methodology emphasizes problem-solving and collaboration and allows students to engage with cutting-edge technologies, acquiring pivotal skills. The assessment of this approach was based on the Cronbach's alpha coefficient, yielding a value of 1.99016, indicating significant internal consistency. Upon analyzing the outcomes, 74% surpassed the score of 4.1, 18% passed, and only 8% failed to meet the minimum requirement. The deployment of this ALP proves to be an efficient instrument in readying students for an everevolving job market. |
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| AbstractList | Artificial Intelligence (AI) is transforming higher education, bringing challenges and opportunities. Thus, instilling skills to leverage AI effectively and equip students for the future workforce is crucial. This requires a shift from traditional pedagogical methods toward active learning emphasizing problem-solving, collaborative work, and the integration of AI tools. The proposed Active Learning Plan (ALP) addresses these imperatives. This plan encompasses research, problem-solving, pseudocode validation using AI tools such as ChatGPT, thorough code documentation, group collaboration, and evaluation. The ALP delves into the interplay between AI and higher education, and it challenges students to derive manual solutions, draft pseudocode, document it, and subsequently validate it through ChatGPT. Moreover, it fosters collaboration by encouraging the formation of groups of five to craft questionnaires on the core topic, which are later used for learning assessment. It is paramount for students to reflect on their experience, pinpointing strengths, weaknesses, and areas for improvement. The adopted methodology emphasizes problem-solving and collaboration and allows students to engage with cutting-edge technologies, acquiring pivotal skills. The assessment of this approach was based on the Cronbach's alpha coefficient, yielding a value of 1.99016, indicating significant internal consistency. Upon analyzing the outcomes, 74% surpassed the score of 4.1, 18% passed, and only 8% failed to meet the minimum requirement. The deployment of this ALP proves to be an efficient instrument in readying students for an ever-evolving job market. Artificial Intelligence (Al) is transforming higher education, bringing challenges and opportunities. Thus, instilling skills to leverage Al effectively and equip students for the future workforce is crucial. This requires a shift from traditional pedagogical methods toward active learning emphasizing problem-solving, collaborative work, and the integration of Al tools. The proposed Active Learning Plan (ALP) addresses these imperatives. This plan encompasses research, problem-solving, pseudocode validation using Al tools such as ChatGPT, thorough code documentation, group collaboration, and evaluation. The ALP delves into the interplay between Al and higher education, and it challenges students to derive manual solutions, draft pseudocode, document it, and subsequently validate it through ChatGPT. Moreover, it fosters collaboration by encouraging the formation of groups of five to craft questionnaires on the core topic, which are later used for learning assessment. It is paramount for students to reflect on their experience, pinpointing strengths, weaknesses, and areas for improvement. The adopted methodology emphasizes problem-solving and collaboration and allows students to engage with cutting-edge technologies, acquiring pivotal skills. The assessment of this approach was based on the Cronbach's alpha coefficient, yielding a value of 1.99016, indicating significant internal consistency. Upon analyzing the outcomes, 74% surpassed the score of 4.1, 18% passed, and only 8% failed to meet the minimum requirement. The deployment of this ALP proves to be an efficient instrument in readying students for an everevolving job market. Artificial Intelligence (AI) is transforming higher education, bringing challenges and opportunities. Thus, instilling skills to leverage AI effectively and equip students for the future workforce is crucial. This requires a shift from traditional pedagogical methods toward active learning emphasizing problem-solving, collaborative work, and the integration of AI tools. The proposed Active Learning Plan (ALP) addresses these imperatives. This plan encompasses research, problem-solving, pseudocode validation using AI tools such as ChatGPT, thorough code documentation, group collaboration, and evaluation. The ALP delves into the interplay between AI and higher education, and it challenges students to derive manual solutions, draft pseudocode, document it, and subsequently validate it through ChatGPT. Moreover, it fosters collaboration by encouraging the formation of groups of five to craft questionnaires on the core topic, which are later used for learning assessment. It is paramount for students to reflect on their experience, pinpointing strengths, weaknesses, and areas for improvement. The adopted methodology emphasizes problem-solving and collaboration and allows students to engage with cutting-edge technologies, acquiring pivotal skills. The assessment of this approach was based on the Cronbach's alpha coefficient, yielding a value of 1.99016, indicating significant internal consistency. Upon analyzing the outcomes, 74% surpassed the score of 4.1, 18% passed, and only 8% failed to meet the minimum requirement. The deployment of this ALP proves to be an efficient instrument in readying students for an ever-evolving job market. La Inteligencia Artificial (IA) está transformando la educación superior, trayendo consigo desafíos y oportunidades. Para equipar a los estudiantes para el mundo laboral del futuro, es esencial inculcar habilidades para utilizar eficazmente la IA. Esto demanda un giro desde los métodos pedagógicos convencionales hacia un aprendizaje activo que priorice la resolución de problemas, el trabajo colaborativo y la incorporación de herramientas de IA. Un Plan de Aprendizaje Activo (PAA) propuesto aborda estos requisitos. Este plan abarca investigación, solución de problemas, validación de pseudocódigo con herramientas de IA como ChatGPT, documentación detallada del código, colaboración grupal y evaluación. El PAA se sumerge en la relación entre IA y educación superior. Desafía a los alumnos a encontrar soluciones manuales, redactar pseudocódigo, documentarlo y luego validarlo mediante ChatGPT. Además, promueve la colaboración, alentando la formación de grupos de cinco para desarrollar cuestionarios sobre el tema central, utilizados posteriormente para medir el aprendizaje. Es esencial que los estudiantes reflexionen sobre su experiencia, reconociendo fortalezas, debilidades y áreas de mejora. La metodología adoptada no solo se centra en la resolución de problemas y la colaboración, sino que también permite a los estudiantes interactuar con tecnologías vanguardistas, adquiriendo habilidades vitales. La evaluación de este enfoque se basó en el coeficiente alfa de Cronbach, arrojando un valor de 1.99016, señalando una notable consistencia interna. Al analizar los resultados, el 74% superó la puntuación de 4.1, el 18% aprobó, mientras que solo el 8% no alcanzó el mínimo requerido. La implementación de este PAA demuestra ser una herramienta efectiva para preparar a los estudiantes para un mundo laboral en evolución constante |
| Author | Rodriguez-Hernandez, Ariel-Adolfo Portella-Cleves, Jorge-Enrique |
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| SubjectTerms | Active learning active programming learning Artificial intelligence Artificial intelligence and programming Chatbots Collaboration Collaborative work Cooperation Education Higher education Hybrid learning learning and artificial intelligence Problem solving Programming learning Skills Students |
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