Bret Beheim — senior researcher at the Max Planck Institute for Evolutionary Anthropology — posted a great GIF animation of the response to his research survey. He calls the figure citation gates, relating the year of scientific publication to the likelihood that the research materials are published open-source or accessible.
To generate the visualization, Bret used R’s base plotting functionality combined with Thomas Lin Pedersen‘s R package tweenrto animate it.
Bret shared his R code for the above GIF of his citation gateson GitHub. With the open source code, this amazing visual display inspired others to make similar GIFs for their own projects. For example, Anne-Wil Kruijt’s dance of the confidence intervals:
Applied to a Human Resource Management context, we could use this similar animation setup to explore, for instance, recruitment, selection, or talent management processes.
Unfortunately, I couldn’t get the below figure to animate properly yet, but I am working on it (damn ggplot2 facets). It’s a quick simulation of how this type of visualization could help to get insights into the recruitment and selection process for open vacancies.
The figure shows how nearly 200 applicants — sorted by their age — go through several selection barriers. A closer look demonstrates that some applicants actually skip the screening and assessment steps and join via a fast lane in the first interview round, which could happen, for instance, when there are known or preferred internal candidates. When animated, such insights would become more clearly visible.
Ashley Hughes, Stephanie Zajac, Jacqueline Spencer, and Eduardo Salas wrote a recent research note for the International Journal of Training and Development. The research note is build around an evidence-based checklist of actionable insights for practitioners that will help to enhance the effectiveness of training interventions. These actionable insights would help to prevent ‘transfer problem’, meaning that trained skills are not being used on the job.
For the full details and scientific evidence behind each suggested action, I suggest you access the research note. Nevertheless, here’s my summary of their main advice on improving training transfer before, during, and after training implementation:
Conduct a training needs analysis to align the training’s content and participants with the organizational objectives
Involved stakeholders should be aware of training, understand its importance, and — obviously — be prepared for the training program. The scholars provide seven specific actions here, including the setting of personal training goals, and aligning resources and rewards with the training.
Training attendance should be framed as an opportunity, and the training’s anticipated benefits could be emphasized (e.g. improvement of work processes or on-the-job performance).
A climate which encourages learning should be created, with dedicated time (and opportunities) for post‐training learning and a sense of accountability for using trained knowledge, skills, and abilities.
Piloting the training with a single department or subset of trainees is highly encouraged. This is one way that greatly helps to assess whether the training design is appropriate in terms of content and delivery.
Error‐encouragement framing can influence a trainee’s learning orientation and thus errors made during training should be framed as growth opportunities.
Use of the trained skills should be supported and planned. For instance, participants could be given a small workload reduction to provide opportunities to apply the learned knowledge and skills once they return to their position.
Management and training participants should be held accountable for their use of skills on the job.
Think about using just‐in‐time or refresher training and coaching, if needed.
Assess training effectiveness criteria including training transfer using metrics and analytics. Specifically, the scholars propose that the criteria measured in the training evaluation should correspond to the training needs identified through the training needs analysis that was conducted before the training.
Training evaluation criteria should consider the scope and timeframe of the training. Take into account that distal outcomes such as ROI may take longer to realize.