Contents and Skills of Data Mining Courses in Analytics Programs

Autor/inn/en	Radovilsky, Zinovy; Hegde, Vishwanath
Titel	Contents and Skills of Data Mining Courses in Analytics Programs
Quelle	In: Journal of Information Systems Education, 33 (2022) 2, S.182-194 (15 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1055-3096
Schlagwörter	Data Analysis; Statistics Education; Graduate Students; Barriers; Interdisciplinary Approach; Teaching Methods; Instructional Design; Comparative Analysis; Job Skills; Masters Programs; Undergraduate Study; Undergraduate Students; Educational Improvement; Specialization; Web Sites; Job Applicants; Databases; Programming Languages; Course Descriptions; Curriculum Design + Suchen Sie Ihr Suchwort? Auswertung; Graduate Study; Student; Students; Aufbaustudium; Graduiertenstudium; Hauptstudium; Studentin; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Teaching method; Lehrmethode; Unterrichtsmethode; Lesson concept; Lessonplan; Unterrichtsentwurf; Produktive Fertigkeit; Magister course; Magisterstudiengang; Grundstudium; Teaching improvement; Unterrichtsentwicklung; Arbeitsteilige Spezialisierung; Web-Design; Bewerber; Datenbank; Kursstrukturplan; Lehrplangestaltung
Abstract	Data Mining (DM) is one of the most offered courses in data analytics education. However, the design and delivery of DM courses present a number of challenges and issues that stem from the DM's interdisciplinary nature and the industry expectations to generate a broader range of skills from the analytics programs. In this research, we identified and compared frequencies of the contents and skills of DM course syllabi in various data analytics programs. We also identified and systemized DM contents and skills in the analytics job market and compared them with the contents and skills from DM syllabi. Based on these analyses and comparisons, we developed four different templates of the DM contents and skills for a DM course at various levels of the analytics education that include: specialized graduate analytics program (MS), general graduate program (MBA), specialized undergraduate analytics program (BS), and general undergraduate program (BSBA). These templates may be specifically useful for educators to design new or improve existing DM courses in data analytics curricula. (As Provided).
Anmerkungen	Journal of Information Systems Education. e-mail: editor@jise.org; Web site: http://www.jise.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01