The tech world is buzzing with news of a breakthrough from Utah State University researchers. The USU team has developed a novel model that promises to revolutionize IT training and system adoption. Their work addresses a familiar agony: the collective groan from an office as a new software update looms, threatening to scramble familiar routines and efficiencies.
A new study, penned by USU's very own Kelly J. Fadel, Robert J. Mills, and Reagan R. Siggard, sheds light on why the shift to new IT systems often feels like a migration across an uncharted digital wasteland. Their research, presented at the Hawaii International Conference on System Sciences (HICSS) in 2025, posits that the rub isn't the technology itself, but the way in which users mentally bridge the old and new. According to USU Today, users frequently fall back on their mental models of old systems when faced with new software.
This pivot point forms the core of the Systems Analogical Learning Theory (SALT), which suggests that the similarity between old and new IT systems heavily influences how easily users adapt. The researchers divide these similarities into categories that affect learning, for example, when design and logic are consistent, users transition seamlessly. However, if it's just the surface features that are alike, users might incorrectly apply their old knowledge. SALT outlines four learning pathways that range from immediate "literal similarity" matchups to more laborious "de novo" learning scenarios, where no prior analogies apply.
