Each of us can recall an instructor who made learning engaging, relevant and impactful, inspiring us to apply what we learned. Unfortunately, each of us can also recall an instructor who failed in one or more these areas. Instructors are force multipliers, reaching hundreds — if not thousands— of learners, impacting both their learning experience and motivation to transfer. So, how can we improve instructor impact on learning?

During recent conference presentations and webinars focused on analytics, big data and evaluation, we noticed audience members asking, “What questions should I be asking [and answering with evaluation data and analytics]?” Speakers typically answer these questions one of two ways: either by recommending collecting specific types or “levels” of data, as if all relevant questions for all learning and development stakeholders should be immediately identified and addressed; or by recommending collecting and tagging as much data as possible so the data analysts figure it out, as if the important questions will only emerge from analyzing all the data after the fact.

Training evaluation should provide insights not only about the effectiveness of training but also about how it can be improved for learners and organizations. In this context, the term “insights” implies a deep understanding of learning, the training process and its outcomes as well as evaluation procedures – designing, measuring, collecting, integrating and analyzing data from both a formative and summative perspective.