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Ammar, Salwa; Kim, Min Jung; Masoumi, Amir H.; Tomoiaga, Alin – Decision Sciences Journal of Innovative Education, 2023
Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the…
Descriptors: Business, Data Analysis, Business Administration Education, Intercollegiate Cooperation
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Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis
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Sankaran, Siva; Sankaran, Kris; Bui, Tung – Decision Sciences Journal of Innovative Education, 2023
Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators…
Descriptors: Data Analysis, Programming Languages, Student Attitudes, Computer Science Education