Cognitive Science is interested in being able to develop methodologies for analyzing human learning and performance data. Intelligent tutoring systems need good c ognitive models that can predict student performance. Cognitive models of human processing are also useful in tutoring because well-designed curriculums need to understand the common components of knowledge that students need to be ab...

Many users have acquired a sophisticated understanding of searching the Web in specific domains. For example, we often hear of users who can get amazing deals for electronic products on the Web. What knowledge do such users have, and how does it affect their search behavior? To address this question, we observed information retrieval experts in the domains of healthcare and online shopping, whi...

Studies of reaction time in Parkinson's disease (PD) have suggested a selective deficit in simple reaction time (SRT), compared with choice reaction time (CRT). This finding has been interpreted as a deficit in motor preprogramming but could involve other factors, such as attentional focussing and stimulus predictability. Moreover, not all studies show the same selective deficit, possibly becau...

BACKGROUND Music-syntactic irregularities often co-occur with the processing of physical irregularities. In this study we constructed chord-sequences such that perceived differences in the cognitive processing between regular and irregular chords could not be due to the sensory processing of acoustic factors like pitch repetition or pitch commonality (the major component of 'sensory dissonance'...

The learning component of a cognitive-based language model (LEAP) designed to easily integrate into agent systems is presented. Building on the Interlaced Micro-Patterns (IMP) theory and the Alchemy/Goal Mind environment, the LEAP research improves agent-to-human and agent-to-agent communication by incorporating aspects of human language development within the framework of general cognition. Us...

Prior experience with a cognitive task is often associated with higher performance on a second assessment, and these experience effects can complicate the interpretation of cognitive change. The current study was designed to investigate experience effects by obtaining measures of cognitive performance separated by days and by years. The analyses were based on data from 2017 adults with two long...

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cogni...