John Kendall Kruschke is an American psychologist and statistician known for his work in connectionist models of human learning,[1] and in Bayesian statistical analysis.
[5] Kruschke's popular textbook, Doing Bayesian Data Analysis,[2] was notable for its accessibility and unique scaffolding of concepts.
Kruschke gave a video-recorded plenary talk on this topic at the United States Conference on Teaching Statistics (USCOTS).
Kruschke's open-access Bayesian analysis reporting guidelines (BARG) [7] provide a step-by-step list with explanation.
[9] Liddell and Kruschke [10] showed that the common practice of treating ordinal data (such as subjective ratings) as if they were metric values can systematically lead to errors of interpretation, even inversions of means.
These models mathematically represent stimuli in a multi-dimensional space based on human perceived dimensions (such as color, size, etc.
An enhancement of the ALCOVE model, called RASHNL, provided a mathematically coherent mechanism for gradient descent with limited-capacity attention.
[17] Kruschke conducted an extensive series of novel learning experiments with human participants, and developed two connectionist models to account for the findings.
A series of experiments demonstrated that people tend to classify novel items, that are relatively close to an exceptional case, according to the rule more than would be predicted by exemplar-based models.
The effects of sequential or successive learning (such as highlighting, mentioned above) can be especially challenging for Bayesian models, which typically assume order-independence.
Kruschke attended the 1978 Summer Science Program at The Thacher School in Ojai CA, which focused on astrophysics and celestial mechanics.