One of the dirty little secrets in the assessment business is the way that assessments are validated. There are no formal systematic approaches for the validation of tests that are easy for tests users, not versed in statistics, to follow.
A recent study published in PLoS ONE conducted a reanalysis of a meta-analysis on Positive Psychology Interventions (PPI’s). A meta-analysis is, in simple terms, a statistical means of combining data from a lot of studies, and is an analysis of analysis. The results of a meta-analysis are often more robust than single studies as they combine data from multiple sources.
I think the claims to measurement in our discipline are on shaky ground to put in politely. As such, I often think that we should be focussed more on the evaluation of usefulness rather than infinitesimally small gains in measurement accuracy.
The International Journal of Selection and Assessment recently included a feature article on the gamification of assessment. While the research methodology in the article was sound, I could not help but think that the article in many ways symbolised what is wrong with much of the assessment literature that emphasises psychometric properties as opposed to practical utility.
Over the past six years, I have had more injuries, than at any other time in my life. I have also had to cross train harder, simply to be able to make it to training each week. The irony is that I have loved every minute of my judo journey and would not change one aspect of the past six years.
While the failure to replicate findings from the psychological literature has been a common critique of psychology in the recent press, one area of psychology which does appear to replicate is that of trait-based prediction, a finding that is especially relevant for I/O Psychology.
Turnitin, the plagiarism detector that most Universities has been sold. Having used Turnitin for years now, I have found the software to be improving continually, and the software regularly picks most aspects of plagiarism relatively fast.
This week, scientists from around the world have made a call to stop the over-reliance on the use of statistical significance testing as a means of establishing what constitutes good science. The problem it seems is that the general public, and many researchers, don’t seem to understand the significance of