How do Quality of Teaching, Assessment and Feedback Drive Undergraduate Course Satisfaction in UK Business Schools?

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univ[Dylan Sutherland of Durham University Business School, Philip Warwick of Durham University Business School, John Anderson of the University of Northern Iowa, and Mark Learmonth of Durham University Business School recently published an article in the Journal of Management Education. We are pleased to feature their article, “How do Quality of Teaching, Assessment and Feedback Drive Undergraduate Course Satisfaction in UK Business Schools? A Comparative Analysis with Non-Business School Courses using the UK National Student Survey,” and are excited to announce that the article will be free to access on our site for a limited time.  Below they reveal further insights regarding the inspiration behind the research, as well as additional information not included in the final publication.]

JME_72ppiRGB_powerpointOur research aimed to understand the most significant issues which contribute to student satisfaction. We also hoped to identify if there are any differences between students in business schools and those studying other subjects. We were motivated to look at this issue by the importance placed on student satisfaction by UK Higher Education System (many of the university and subject ranking tables place a significant weighting on student satisfaction scores).

We found that good teaching remains the most important driver of satisfaction, along with being well-organised (smooth running courses are very important to students). We also detected a noticeable tendency among business students to instrumentalism. That is, they focus on results and achieving those results, like a good job at the end of the course, rather than studying for the love of the subject. We think instrumentalism is different to adopting a strategic learning style, because of this emphasis on the end result. We finish the article by considering the implications of this work. With increasing tuition fees and the imperative of getting a good job at the end of the course, it seems likely that a wider range of students will adopt an instrumental approach in the future. Business students may be the forerunners.

 

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JOM 41(3)_Covers.inddIn the latest podcast from Journal of Management, Fred Oswald, Associate Editor of Journal of Management interviews Gerd Gigerenzer about his article co-authored with Julian N. Marewski entitled “Surrogate Science: The Idol of a Universal Method for Scientific Inference.” The article appeared in Journal of Management‘s Special Issue Bayesian Probability and Statistics in Management Research.

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gigerenzer_gerd_rgb_2006_webGerd Gigerenzer is Director at the Max Planck Institute for Human Development and Director of the Harding Center for Risk Literacy in Berlin. He is former Professor of Psychology at the University of Chicago and John M. Olin Distinguished Visiting Professor, School of Law at the University of Virginia. He is also Batten Fellow at the Darden Business School, University of Virginia, and Fellow of the Berlin-Brandenburg Academy of Sciences and the German Academy of Sciences. Awards for his work include the AAAS Prize for the best article in the behavioral sciences and the Association of American Publishers Prize for the best book in the social and behavioral sciences. His award-winning popular books have been translated into 18 languages.  Gigerenzer has trained U.S. federal judges, German physicians, and top managers in decision making and understanding risks and uncertainties.

FredOswaldFred Oswald currently serves the Rice University Department of Psychology as Chair, and he is a Professor in the Industrial/Organizational Psychology program. His published research addresses the reliability and validity of tests administered to applicants in organizational, education and military settings. Substantively, his work deals with defining, modeling and predicting societally relevant outcomes (e.g., job performance, academic performance, satisfaction, turnover) from psychological measures that are based on cognitive and motivational constructs (e.g., cognitive abilities, personality traits, situational judgment tests, job knowledge and skill, and biographical data). His statistical work in meta-analysis, structural equation modeling, and adverse impact also informs personnel selection issues and psychological testing in the research, practice and legal arenas.