Strategic Decision-Making in Human-AI Workflow: Enhancing Online Course Design

The integration of Artificial Intelligence (AI) into teaching and learning is increasingly prevalent within today’s fast-evolving technological landscape. While AI’s computational capabilities boost productivity and reduce repetitive human effort, its role extends well beyond automation, also enhancing work quality and efficiency. Recent research emphasizes the continued importance of human judgment and decision-making in AI collaboration, particularly in contexts that demand adaptability, creativity, and ethical discernment (Akinnagbe, 2024).

Our team presentation adopts a human-centered approach to AI collaboration in online course design and delivery, using the “Evolution of Civilization” Massive Open Online Course (MOOC) as a case study. This global course also includes an optional blended-online-learning micro-module customized for students in the university’s UG Common Core CCGL 9042.

We examine the course’s human–AI collaboration workflow, focusing on decision points where human judgment guides interaction with AI support systems. Specifically, we explore how AI-based tools are used to develop learning activities—videos, images, infographics, interactive games, and other multimedia resources—with the aim of enhancing pedagogical practice and augmenting the student learning experience.

The presentation is organized around three main focuses:

• Multimedia integration: how AI-assisted production workflows for video, image, audio, and infographics enable contextual customization (historical scenarios, localized contexts, and cultural elements) and expand creative options for curating content to scaffold students’ understanding and mastery of abstract concepts—while introducing new quality‑management requirements for accuracy, authenticity, and socio‑ethical considerations.
• AI-assisted coding in game development: using smart, low‑code, and AI‑supported “vibe‑coding” platforms to create interactive games that concretize abstract economic and evolutionary concepts for personalized student learning. Game design requires balancing the ease of smart coding with its limitations, since complex gameplay analytics and deep game‑engine programming still demand domain experts.
• Classroom experience and feedback: observations from CCGL instructors and the design team, together with survey results capturing students’ self‑reported usability and perceived usefulness, providing insights into how engagement with AI‑assisted content supports learning.

Finally, we will review the advantages and constraints of human–AI collaboration in online course design and outline a framework to delineate where AI should be integrated in education.