Assessing Motivation To Individualize Reinforcement And Reinforcers For An Intelligent Tutor

Personalized learning with technology is in full demand across all context. Learning occurs through motivation therefore, personalizing motivation is key to enhancing learning rate and retention for the learner. Supplying the intelligent tutors with key information not will advance the familiarity of indi-vidual’s motivational factors and interest for individualizing motivation. Building this relationship stems from a streamlined Motivational Assessment Tool (MAT), aimed at assessing several motivation factors. The Motivation Assessment Tool is based on the interconnectedness of motivational factors with personality. The creation of the assessment allows the intelligent tutor to implement reinforcers that influence motivational level based off individual variances such as personality

Selection For Vigilance Assignments: A Review And Proposed New Direction

Vigilance or sustained attention is a critical aspect of operational tasks including air-traffic control, airport security, industrial quality control and inspection, and medical screening and monitoring. Consequently, the selection of personnel for assignments involving vigilance is a key ergonomic concern. As reviewed herein, traditional approaches to personnel selection for tasks requiring vigilance have concentrated on unidimensional measures involving sensory acuity, aptitude, sex, age and personality factors. These approaches have been ineffective. In this article, we suggest an alternative approach in which the selection issue is considered in terms of a theory-driven analysis of different types of vigilance tasks and multidimensional predictors. As an example of that approach, we made use of a resource model of vigilance and measures of cerebral blood flow velocity and subjective state obtained from a short battery of high-workload tasks to successfully predict individual performance on subsequent high-workload sensory and cognitive vigilance tasks. © 2011 Taylor & Francis