AIL 602, Electronic Instructional Design, was the course that translated my growing theoretical vocabulary into a disciplined, systematic design practice. Taught by Dr. Feiya Luo, it advanced my degree goal of mastering the science of instructional design and my professional goal of producing evidence-based learning solutions rather than intuitive ones. Before this course I tended to jump from a perceived problem straight to a solution; AIL 602 taught me to slow down, analyze, and let evidence drive design, a shift that has reshaped how I approach every project since.
The needs-assessment assignment made this lesson concrete. I analyzed a scenario in which a university Media Resource Center experienced a 35% drop in patronage between 2015 and 2023. The director attributed the decline to low awareness, but the course pushed me to treat that as a hypothesis rather than a conclusion. I learned to design a structured needs analysis with clear objectives, identified target audiences, and triangulated evidence through surveys, focus groups, interviews, and observations. Crucially, I learned to distinguish instructional from non-instructional solutions, recognizing that some performance problems are solved not by training but by marketing, staffing, or stakeholder collaboration. This insight, that design extends beyond curriculum to systemic change, was genuinely new to me and now informs how I scope problems professionally.
The task-analysis assignment deepened the same competency. Building on a cause identified in the needs analysis, the underutilization of a “whisper booth” by music and communication graduate students, I designed an instructional video intervention and analyzed exactly what learners needed to know to use the facility. Examining how students’ prior audio-engineering coursework could scaffold new skills taught me to bridge existing competencies with new objectives rather than assuming a blank slate. In specifying the video, I applied cognitive load theory and the principle of brevity, drawing on research showing that learner engagement drops sharply for videos beyond six to nine minutes (Brame, 2016; Guo et al., 2014). That detail mattered: it moved my design decisions from preference to evidence, and it connects directly to my doctoral interest in simulation- and multimedia-based learning, where managing cognitive load is central.
Working with systematic models such as ADDIE, Dick and Carey, and Gagné’s Nine Events of Instruction gave me a repeatable, intentional process for planning instruction, and the accompanying design artifact, built and presented in Canva, strengthened my ability to communicate a design rationale to stakeholders. Collectively, AIL 602 positioned me to approach instructional design as an evidence-based discipline grounded in learning science. The analytic habits it instilled, beginning with the problem rather than the tool, are exactly what I will need for my dissertation and for future work designing technology integration programs for educators.
References
Brame, C. J. (2016). Effective educational videos: Principles and guidelines for maximizing student learning from video content. CBE—Life Sciences Education, 15(4), es6. https://doi.org/10.1187/cbe.16-03-0125
Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos. Proceedings of the First ACM Conference on Learning @ Scale, 41–50. https://doi.org/10.1145/2556325.2566239
