The effectiveness of undergraduate career courses has been demonstrated for multiple variables, including career certainty, maturity, decision‐making skills, and reduction of dysfunctional career thoughts. Although such studies used the career course as an intervention, most failed to include a comparison course, nor were grounded in career theory. This study used a comparison group of 152 undergraduates enrolled in career development courses and 50 students enrolled in undergraduate human relations courses. Pre‐ and posttest comparisons indicated that the career course yielded significant improvements in career decision state, cognitive information processing (CIP) skills, career decision‐making stage, knowledge of next steps, and anxiety about current career concern, but the human relations course did not. The CIP‐based career course is supported as a valid career intervention, and individuals may benefit from targeted interventions depending on their CASVE cycle position. Future research might compare different career theory–based or atheoretical career courses on career development outcomes.
The purpose of this study was to explore adaptation through the manipulation of perceived task difficulty and self-efficacy to challenge the concepts postulated by the two-perception probabilistic concept of the adaptation phenomenon (TPPCA) conceptual framework. Twenty-four randomized performers completed a handgrip and putting task, at three difficulty levels, to assess their self-efficacy and perceived task difficulty interactions on motivations, affect, and performances. The TPPCA was partially confirmed in both tasks. Specifically, as the task difficulty level increased, arousal increased, pleasantness decreased, and the performance declined. There was no solid support that motivational adaptations were congruent with the TPPCA. The findings pertaining to the human adaptation state represent a first step in encouraging future inquiries in this domain. The findings clarify the notion of perceived task difficulty and self-efficacy discrepancy, which then provokes cognitive appraisals and emotional resources to produce an adaptation response.
Maddox et al. [9,10] establish Bayesian methods for estimating home-team in-game win probability for college and NBA basketball. This paper introduces a Bayesian approach for estimating in-game hometeam win probability for Division-I FBS college (American) football that uses expected number of remaining possessions and expected score as two predictors. Models for estimating these are presented and compared. These, along with other predictors are introduced into two Bayesian approaches for the final estimate of in-game home-team win probability. To illustrate utility, methods are applied to the 2021 Big XII Conference Football Championship game between Baylor and Oklahoma State.
Two new Bayesian methods for estimating and predicting in-game home team win probabilities in Division I NCAA men’s college basketball are proposed. The first method has a prior that adjusts as a function of lead differential and time elapsed. The second is an adjusted version of the first, where the adjustment is a linear combination of the Bayesian estimator with a time-weighted pregame win probability. The proposed methods are compared to existing methods, showing the new methods are competitive with or outperform existing methods for both estimation and prediction. The utility is illustrated via an application to the 2012/2013 through the 2019/2020 NCAA Division I Men’s Basketball seasons.
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