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The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically, the study will attempt to answer the questions of whether students’ scores on the MUSIC model predict or explain effort, academic performance, course rating, and instructor rating. A Bayesian approach to linear regression is used to determine and understand the impact of the MUSIC model components on the aforementioned output measures.

Many ranking algorithms rank a set of alternatives based on their performance in a set of pairwise comparisons. In this study, a special scenario is observed in which the objective is to rate and rank a set of groups in a traditional recruiting situation, in which the groups extend offers to the set of individuals, and the individuals will select one of their available offers. The new ranking method, Crowd-Ranking, uses collective wisdom and decision-making in conjunction with Markov chains to create competitive matches between alternatives and ultimately provide a ranking of the alternatives. First, the method is evaluated by its performance in a perfect season scenario. Next, it is applied to the case of NCAA football recruiting in the power conferences (ACC, Big Ten, Big 12, Pac 12 and SEC) in the Football Bowl Subdivision. For the Big Ten conference, the method performs significantly better than popular existing services at predicting future team performance based on past recruiting rankings. For a comprehensive national ranking of the power conferences, there is no statistically significant difference between Crowd-Ranking and the other methods.

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published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User