Do Trainings Really Transfer to the Workplace? A Longitudinal Perspective

By Tansu Baktıran

Companies invest billions every year in training their employees. But a crucial question remains: do these trainings actually make a lasting difference in the workplace?

Traditional evaluation methods—like the common “smile sheets” filled in right after a course—only tell us whether participants enjoyed the training. They don’t reveal whether employees remember the content, intend to use it, or actually apply it in their jobs weeks or months later.

This is where my research comes in. I study the transfer of training—the process of moving from learning in the classroom to real change in workplace behavior. More specifically, I look at how memory, intention, and action evolve over time after a training. By following participants across multiple points in time through Experience Sampling and digital diaries, I aim to capture not just if transfer happens, but how it unfolds.

And here’s the exciting part: new technologies are making this possible in ways never seen before. Speech-to-text lowers the barrier for participants to share their thoughts, while large language models (LLMs) can process and analyze rich qualitative feedback at scale. Together, these tools open new doors for more meaningful training evaluation.

In addition, I am exploring dynamic survey design with the ChatGPT API, where follow-up questions adapt based on earlier responses. This means surveys can feel more like a conversation than a form, encouraging participants to elaborate on their experiences in their own words. The aim is to lower barriers, improve engagement, and ultimately collect richer qualitative data.

How This Research Builds on Classic Theories

Baldwin & Blume’s Training Transfer Model

This model shows that transfer depends on the learner, the training design, and the work environment. My research extends it by adding a time-based view, showing whether knowledge and behaviors are generalized and maintained across weeks and months.

Kirkpatrick’s Four Levels

From Reaction to Learning, Behavior, and Results, Kirkpatrick’s framework is the backbone of training evaluation. By focusing on memory, intention, and action, I enrich the Learning and Behavior levels with longitudinal and qualitative data.

Ebbinghaus’ Forgetting Curve

We know that memory fades without reinforcement. But what about intention and action? My study applies the forgetting curve logic to see whether motivation and behavior also decay over time—and what can help sustain them.

Ajzen’s Theory of Planned Behavior

This theory shows that intention is the best predictor of behavior. I extend it by asking: does memory act as a driver of intention in training transfer? If employees forget, does their motivation to act fade too?

Brinkerhoff’s Success Case Method

Brinkerhoff highlights the conditions that make training successful—or not—through qualitative cases. My approach adds a mixed-methods lens, but also goes further: by using adaptive surveys, can we generate more detailed and relevant qualitative data from participants? This may strengthen the success-case logic, because the richer the stories and examples, the more powerful the insights into why training transfer succeeds or fails.

Why It Matters

For organizations, this research offers more than theory. It provides a new way to evaluate training investments, moving beyond one-time surveys to methods that truly reflect the reality of workplace learning. For researchers, it contributes to bridging classic theories with modern, tech-enabled methodologies.

In short, my goal is to help both practitioners and academics understand not just whether training works, but how learning survives, transforms, or disappears once the classroom door closes.