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Tiahrt, Thomas; Hanus, Bartlomiej; Porter, Jason C. – Decision Sciences Journal of Innovative Education, 2022
Firms desire graduates capable of executing current and future business practices, many of which revolve around data. To meet those needs, we shifted the orientation of our required information systems course from technology to data. Instead of a survey of information systems, students learn the data acquisition-preparation-mining-presentation…
Descriptors: Information Systems, Information Science Education, Computer Software, Undergraduate Students
Albert, Jim; Hu, Jingchen – Journal of Statistics Education, 2020
Bayesian statistics has gained great momentum since the computational developments of the 1990s. Gradually, advances in Bayesian methodology and software have made Bayesian techniques much more accessible to applied statisticians and, in turn, have potentially transformed Bayesian education at the undergraduate level. This article provides an…
Descriptors: Bayesian Statistics, Computation, Statistics Education, Undergraduate Students
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
Hu, Jingchen – Journal of Statistics Education, 2020
We propose a semester-long Bayesian statistics course for undergraduate students with calculus and probability background. We cultivate students' Bayesian thinking with Bayesian methods applied to real data problems. We leverage modern Bayesian computing techniques not only for implementing Bayesian methods, but also to deepen students'…
Descriptors: Bayesian Statistics, Statistics Education, Undergraduate Students, Computation
Simonson, Michael, Ed. – Association for Educational Communications and Technology, 2015
For the thirty-eighth time, the Research and Theory Division of the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Indianapolis, Indiana. The Proceedings of AECT's Convention are published in two…
Descriptors: Information Technology, Educational Technology, Student Attitudes, Online Courses
Kaburlasos, Vassilis G.; Marinagi, Catherine C.; Tsoukalas, Vassilis Th. – Computers & Education, 2008
This work presents innovative cybernetics (feedback) techniques based on Bayesian statistics for drawing questions from an Item Bank towards personalized multi-student improvement. A novel software tool, namely "Module for Adaptive Assessment of Students" (or, "MAAS" for short), implements the proposed (feedback) techniques. In conclusion, a pilot…
Descriptors: Feedback (Response), Student Improvement, Computer Science, Bayesian Statistics