Enhancing Programming Education with an Active Learning Plan and Artificial Intelligence Integration - Portella Cleves, Jorge Enrique; Rodríguez Hernández, Ariel Adolfo (Revista FI-UPTC, 2024)
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.