Paper Number
ECIS2026-1409
Paper Type
CRP
Abstract
Digital transformation is redefining the competencies required for future work, highlighting the need for higher education to cultivate critical, ethical, and adaptive AI-related skills. This paper examines how an active-learning–based instructional model: AI-Integrated Competence Development (AICD) Model, can develop AI-interaction competences in an undergraduate business course. Generative AI tools were embedded throughout a semester-long Organizational Behavior course to support structured prompting, critical evaluation, reflective reasoning, and ethical decision-making. Using an explanatory mixed-methods design, we analyzed pre–post survey data from 123 students alongside qualitative responses. Findings show significant gains in AI literacy and prompt literacy, including improved conceptual understanding, strategic application, and ethical awareness. Qualitative evidence demonstrates that students engaged in iterative prompting, verification of AI outputs, and reflective comparison between AI-generated insights and theoretical framework. Results suggest that intentional, structured integration of AI within active learning environments can meaningfully support competence development and prepare students for AI-augmented professional contexts.
Recommended Citation
Papadimitriou, Antigoni and Pan, Zilong, "Developing Ai-Interaction Competences Through Active Learning In Business Education" (2026). ECIS 2026 Proceedings. 4.
https://aisel.aisnet.org/ecis2026/comp_mgmt/comp_mgmt/4
Developing Ai-Interaction Competences Through Active Learning In Business Education
Digital transformation is redefining the competencies required for future work, highlighting the need for higher education to cultivate critical, ethical, and adaptive AI-related skills. This paper examines how an active-learning–based instructional model: AI-Integrated Competence Development (AICD) Model, can develop AI-interaction competences in an undergraduate business course. Generative AI tools were embedded throughout a semester-long Organizational Behavior course to support structured prompting, critical evaluation, reflective reasoning, and ethical decision-making. Using an explanatory mixed-methods design, we analyzed pre–post survey data from 123 students alongside qualitative responses. Findings show significant gains in AI literacy and prompt literacy, including improved conceptual understanding, strategic application, and ethical awareness. Qualitative evidence demonstrates that students engaged in iterative prompting, verification of AI outputs, and reflective comparison between AI-generated insights and theoretical framework. Results suggest that intentional, structured integration of AI within active learning environments can meaningfully support competence development and prepare students for AI-augmented professional contexts.