When it comes to training in data skills—whether it’s using PeopleSoft Query, BI Publisher, building dashboards, or interpreting datasets—one powerful strategy is to involve learners in the design of the learning experience itself. Adult learners arrive with a wealth of prior knowledge, responsibilities, and goals. Julie Dirksen’s Design for How People Learn emphasizes the importance of building on what learners already know, a principle rooted in constructivist theory. This mindset has transformed how I approach course design. Instead of starting with content, I [try to] start with curiosity: What do learners already understand? What problems are they trying to solve? What contexts do they work in? These questions help ensure that my training content is not only informative but also relevant, personal, and practical. Asking questions that consider what role your learners play in the design of your course is something that I touched upon in a Q&A thread back in March.
This learner-first approach became especially meaningful during the development of a self-paced online course in PeopleSoft Query. One colleague, a motivated learner juggling daily work and professional development, shared candidly about the challenge of retaining skills she didn’t use immediately. Her feedback pushed me to reexamine the course with fresh eyes. Were the scenarios realistic enough? Did learners have a chance to apply what they were learning in ways that mirrored their day-to-day work? We decided to collaborate: she would document real-world questions as they came up, and I would incorporate them into the course. One such question—how to query a list of courses taken by students in a specific academic plan and term—is now being developed into a hands-on exercise. By rooting the course content in actual user needs, we increase both its usefulness and the likelihood of long-term retention.
This practice echoes ideas from The New College Classroom by Davidson and Katopodis, who advocate for participatory learning and co-creating course content with students. While traditionally associated with academic settings, these ideas apply beautifully to workplace learning. For example, involving data training participants in brainstorming sessions or feedback loops can help surface common challenges—like interpreting enrollment trends, cleaning messy datasets, or presenting findings to non-technical stakeholders. From there, trainers can design learning modules that don’t just teach tools or theories, but actually solve problems learners face in their roles. These methods align with Vygotsky’s zone of proximal development: meeting learners just beyond their current ability, and guiding them toward growth with meaningful support.
Ultimately, data training is not just about imparting technical skills—it’s about empowering learners to think critically, solve real problems, and build confidence in their abilities. By treating learners as partners in course design, we show them that their time, insights, and feedback matter. This approach promotes learner autonomy, strengthens retention through real-world application, and fosters a culture of continuous improvement. Whether through surveys, working groups, or informal conversations, engaging learners in the design process can turn a one-way training experience into a dynamic, evolving collaboration—and one that benefits both the trainer and the trainees in lasting ways. So, what might change in your next training if you started by asking your learners what they need most?
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References
Dirksen, J. (2015). Design for How People Learn [Kindle version]. New Riders. [ https://a.co/d/gHIPUdx ]
Davidson, C. N., & Katopodis, C. (2022). The New College Classroom [Kindle version]. Harvard University Press. [ https://a.co/d/1uB9aq4 ]