Advancing Knowledge Management in Business Education at HBCUs: A Framework for Active Learning, AI Integration, and Knowledge Sharing

Knowledge management has become increasingly important in business education as universities prepare students to create, organize, share, and apply knowledge in data-driven and AI-enhanced professional environments. However, existing KM approaches in business curricula often lack structured integration of generative AI and active learning, particularly in the context of Historically Black Colleges and Universities (HBCUs). This extended abstract proposes a knowledge management–based pedagogical framework that integrates active learning, AI-assisted knowledge construction, and collaborative knowledge sharing to enhance student engagement and learning outcomes in HBCU business education.

The proposed framework is grounded in the view that effective business education requires more than delivering course content. It requires a structured learning environment in which students actively construct knowledge, apply concepts to real-world problems, collaborate with peers, use digital and AI tools responsibly, and reflect on their learning processes. In this framework, knowledge management is understood as a teaching and learning process involving knowledge creation, sharing, application, and evaluation. These processes can be supported through active learning strategies, case studies, project-based assignments, business analytics tools, generative AI, and collaborative digital platforms. The framework is organized as a four-stage cycle consisting of AI-assisted knowledge creation, collaborative knowledge sharing, applied problem-solving, and reflective evaluation.

This study builds on two related scholarly contributions. First, Gao et al. (2024) examined the interplay between AI and human logic in mathematical problem-solving, emphasizing the importance of combining AI-generated support with human reasoning, verification, and critical thinking. This perspective informs business education by highlighting that students must learn not only how to use AI tools but also how to evaluate, interpret, and responsibly apply AI-assisted outputs. Second, Gao and Gao (2026) developed the knowledge management mesosystem model for enhancing business education through active learning, AI integration, and knowledge sharing. The present framework extends this work by emphasizing its application to HBCU business education and by highlighting the role of knowledge management in student-centered, technology-enhanced learning and incorporating human–AI collaboration and AI literacy as core elements of the learning process.

The implications of this framework are significant for business curriculum design, faculty development, student engagement, and institutional innovation. By integrating knowledge management principles into business courses, instructors can help students become active knowledge creators rather than passive recipients of information. Students can develop stronger communication, collaboration, analytical reasoning, AI literacy, and problem-solving skills. For HBCUs, this approach may also support undergraduate research, interdisciplinary collaboration, and broader participation in AI-driven business fields. The framework will be implemented and evaluated in business courses at HBCUs using project-based learning activities and AI-supported assignments.

In conclusion, this extended abstract presents a theory-informed framework for advancing knowledge management in business education at HBCUs. By integrating active learning, AI, and knowledge sharing, the proposed approach can help prepare business students for modern workplaces where knowledge, technology, and human judgment are deeply interconnected.

References Gao, S., Gao, W., Malomo, O., Allagan, J., Su, J., Eyob, E., & Challa, C. (2024). Exploring the interplay between AI and human logic in mathematical problem-solving. Online Journal of Applied Knowledge Management, 12(1), 73–93. https://doi.org/10.36965/OJAKM.2024.12(1)73-93

Gao, S., & Gao, W. (2026). Enhancing business education with the knowledge management mesosystem model: A framework for active learning, AI integration, and knowledge sharing. In M. Russ & M. D. Lytras (Eds.), AI-driven knowledge management processes, Volume 1: Strategies for the modern business landscape. Emerald Publishing Limited. https://doi.org/10.1108/978-1-80592-391-620261010