In this episode Charles welcomes Eric Surface, fellow I/O Psychologist and founder/CEO of ALPS Insights, a training analytics company that provides tools and advice to help companies extract value from their learning programs via actionable insights based on data. A big thank you to Science 4-Hire and author, Charles Handler.
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.
For many learning and development (L&D) professionals, training evaluation practices remain mired in the muck. What ends up being evaluated hasn’t changed much over the past two or three decades. We almost universally measure whether trainees liked the training, most of us measure if they learned something, and beyond that, evaluation is a mix of “We’d like to do that” and, “We’re not sure of what to make of the data we get.” Perhaps more critically, in one recent national survey, nearly two-thirds of L&D professionals did not see their learning evaluation efforts as effective in meeting their organization’s business goals.