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Gooding, Constance L.; Lyford, Alex; Giaimo, Genie N. – Teaching Statistics: An International Journal for Teachers, 2022
Instructors at postsecondary institutions have designed a myriad of data science classes to keep up with the rise of big data. Businesses and companies have become increasingly interested in hiring people with strong data acquisition, management, and communication skills. Since data science as a field of study is relatively new, though it has deep…
Descriptors: Statistics Education, Undergraduate Students, Course Descriptions, Writing Instruction
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
Neelima Bhatnagar; Victoria Causer; Michael J. Lucci; Michael Pry; Dorothy M. Zilic – Information Systems Education Journal, 2024
Data analytics is a rapidly growing field that plays a crucial role in extracting valuable insights from large volumes of data. A data analytics practicum course provides students with hands-on experience in applying data analytics techniques and tools to real-world scenarios. This practicum is intended to serve as a bridge between the student's…
Descriptors: Statistics Education, Data Analysis, Practicums, Education Work Relationship
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
Hundhausen, C. D.; Conrad, P. T.; Carter, A. S.; Adesope, O. – Computer Science Education, 2022
Background and Context: Assessing team members' indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a…
Descriptors: Computer Software, Computer Science Education, Correlation, Engineering Education
Hong, Moo Sun; Sun, Weike; Anthony, Brian W.; Braatz, Richard D. – Chemical Engineering Education, 2022
This article describes experiences with teaching process data analytics and machine learning, including in: (1) a joint undergraduate/graduate course for students in chemical and mechanical engineering and engineering management; and (2) an undergraduate chemical engineering concentration in process data analytics. The article also describes…
Descriptors: Teaching Methods, Graduate Students, Undergraduate Students, Chemical Engineering
Linwan Wu; Allyssa Andrews – Journal of Advertising Education, 2024
Programmatic advertising has come to dominate the landscape of digital media planning. To prepare ad majors for their future careers in the industry, it is essential to teach students programmatic buying and provide them with hands-on experience. In this article, the authors present their approach of integrating teaching programmatic buying into a…
Descriptors: Advertising, Professional Education, Teaching Methods, Purchasing
Del Toro, Israel; Dickson, Kimberly; Hakes, Alyssa S.; Newman, Shannon L. – American Biology Teacher, 2022
Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…
Descriptors: Undergraduate Students, Biology, Statistics Education, Data Analysis
Son, Ji Y.; Blake, Adam B.; Fries, Laura; Stigler, James W. – Journal of Statistics and Data Science Education, 2021
Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help…
Descriptors: Statistics Education, Introductory Courses, Teaching Methods, Data Analysis
Zhang, Limin; Chen, Fang; Wei, Wei – Journal of Information Systems Education, 2020
The current data-centric business environment has seen an increasing demand for business students with knowledge and skills in the area of business analytics. This article presents the design and implementation of a foundation business analytics (BA) course for undergraduate business students who aspire to become data-literate professionals or…
Descriptors: Teaching Methods, Data Analysis, Business Administration Education, Computer Software
Koutsoukis, Nikitas-Spiros; Fakiolas, Efstathios; Katsis, Athanassios; Papadimitriou, Pyrros – Policy Futures in Education, 2022
The purpose of this article is to describe a multidisciplinary approach implemented in teaching public policy analysis at university level. The approach fuses (a) contextual policy analysis with (b) bivariate and multivariate analysis techniques and (c) data analytics skills to improve the learners' competence to conduct "decisional"…
Descriptors: Interdisciplinary Approach, Policy Analysis, Teaching Methods, Public Policy
Adams, Bryan; Baller, Daniel; Jonas, Bryan; Joseph, Anny-Claude; Cummiskey, Kevin – Journal of Statistics and Data Science Education, 2021
Since the publishing of Nolan and Temple Lang's "Computing in the Statistics Curriculum" in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop…
Descriptors: Multivariate Analysis, Statistics Education, Teaching Methods, Thinking Skills
Bertrand Schneider; Joseph Reilly; Iulian Radu – Journal for STEM Education Research, 2020
In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…
Descriptors: Learning Analytics, Classroom Techniques, Multimedia Materials, Graduate Students
Hudiburgh, Lynette M.; Garbinsky, Diana – Journal of Statistics Education, 2020
Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data…
Descriptors: Statistics Education, Data Analysis, Visualization, Teaching Methods
Nurse, Anne M.; Staiger, Trish – Teaching Sociology, 2019
Data reproducibility is becoming increasingly important in the social sciences, but it has yet to be incorporated into many undergraduate sociology programs. This note describes a service-learning activity that can be added to an introductory statistics course. Students partner with a nonprofit and analyze quantitative data to answer questions…
Descriptors: Teaching Methods, Sociology, Undergraduate Students, Service Learning