Commitment Contracts

We review the theoretical and empirical literature on commitment devices.A commitment device is any arrangement, entered into by an individual, with the aim of making it easier to fulfill his or her own future plans. We argue that there is growing empirical evidence supporting the proposition that people demand commitment devices and that these devices can change behavior. We highlight the importance of further research exploring soft commitment – those involving only psychological costs – and the welfare consequences of hard commitments – those involving actual costs – especially in the presence of bounded rationality.consumer/household economics, institutional and behavioral economics

Modeling the NCAA Tournament Through Bayesian Logistic Regression

Many rating systems exist that order the Division I teams in Men\u27s College Basketball that compete in the NCAA Tournament, such as seeding teams on an S-curve, and the Pomeroy and Sagarin ratings, simplifying the process of choosing winners to a comparison of two numbers. Rather than creating a rating system, we analyze each matchup by using the difference between the teams\u27 individual regular season statistics as the independent variables. We use an MCMC approach and logistic regression along with several model selection techniques to arrive at models for predicting the winner of each game. When given the 63 actual games in the 2012 tournament, eight of our models performed as well as Pomeroy\u27s rating system and four did as well as Sagarin\u27s rating system when given the 63 actual games. Not allowing the models to fix their mistakes resulted in only one model outperforming both Pomeroy and Sagarin\u27s systems

The Influence of Question Sequencing Using Formative Assessment in Introductory Statistics

Formative assessment has long been used to gauge students’ understanding of course material prior to taking an exam. With the advent of more advanced technology, only recently have instructors been able to combine formative assessment with a student response system to allow students to respond to questions in real time during class. Previous studies show mixed findings on the relationship between the use of student response systems and student learning. For example, some studies show that those students who used a student response system performed better on exams or in the course when compared to those who did not, while others found no significant difference. In addition, the influence of testing students formatively multiple times before a summative assessment has been of little focus. A quasi-experimental design was used in this study to test students on 112 concepts in introductory statistics at three time points: during class using a student response system, during an online quiz about one week later, and on an exam at the end of the unit. Each concept was associated with one of four course units and was assigned a level of cognitive demand. The primary goal of the study was to determine if the sequences of correct and incorrect responses that students provided on two formative assessments influenced their ability to answer a corresponding summative assessment question correctly using a logistic regression model and Monte Carlo simulation. Also, a series of loglinear models was used to determine if the sequence of responses, unit of the course, and level of cognitive demand were independent. The results of this study indicate that students who answered both formative assessments correctly performed the best on the exam, followed by those who answered only the quiz question correctly. However, students who answered only the student response system question correctly fared no better on the exam than those who missed both formative assessments. Students who completed more sequences were more likely to overachieve their predicted exam results. Moreover, the results showed that students’ sequences of responses, the course unit, and the level of cognitive demand were not independent. Students tended to overachieve on less cognitively demanding sequences requiring descriptive statistics and on strategic thinking exam questions requiring inference, but underachieved in the probability unit and on more challenging descriptive statistics questions. This study provided insight on the influence of that repeated practice on exam performance, suggesting that working independently after learning a concept is more beneficial to student learning than using a student response system in class. This study also demonstrated how statistics education can effectively use formative assessment in the classroom and test higher-order thinking using multiple-choice questions. University instructors may find the results useful in reevaluating the use of active learning in their classroom

Addressing Students’ Mental Health Needs in Faculty-Led Study Abroad Courses

The increased enrollment of students with mental health needs in U.S. higher education, paired with increasing emphasis on study abroad participation has led campus mental health professionals to consider how their services might extend to serve students with mental health needs who are studying abroad. When it comes to faculty led courses, instructors can play a key role in providing on-the-ground support for students experiencing mental health challenges. The findings from this study provide key insights that college mental health professionals can use to better understand and support these instructors as they serve on the front lines of addressing students’ mental health needs while they are away from campus. In particular, our findings point to key ways that college mental health professionals can partner with education abroad offices to provide effective pre-departure training and in-country support for faculty instructors