A Blended Model: Simultaneously Teaching a Quantitative Course Traditionally, Online, and Remotely

Autor/inn/en	Lightner, Constance A.; Lightner-Laws, Carin A.
Titel	A Blended Model: Simultaneously Teaching a Quantitative Course Traditionally, Online, and Remotely
Quelle	In: Interactive Learning Environments, 24 (2016) 1, S.224-238 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2013.841262
Schlagwörter	College Students; Business Schools; Blended Learning; Distance Education; Online Courses; Achievement Gap; Models; Nontraditional Students; Nontraditional Education; Methods Courses; Conventional Instruction; Delivery Systems; Multiple Regression Analysis; Television; Interactive Video; Synchronous Communication; Asynchronous Communication; Hypothesis Testing; Educational Technology; Student Needs + Suchen Sie Ihr Suchwort? Collegestudent; Distance study; Distance learning; Fernunterricht; Online course; Online-Kurs; Analogiemodell; Non-traditional education; Alternative Erziehung; Methodisch-didaktische Anleitung; Auslieferung; Fernsehen; Fernsehtechnik; Interaktives Video; Hypothesenprüfung; Hypothesentest; Unterrichtsmedien
Abstract	As universities seek to bolster enrollment through distance education, faculty are tasked with maintaining comparable teaching/learning standards in traditional, blended, and online courses. Research has shown that there is an achievement gap between students taking courses exclusively offered online versus those enrolled in face-to-face classes. In an effort to mitigate these observed differences, the School of Business faculty at the research institution investigated various course models to meet the needs of a diverse, non-traditional, and multifaceted student population. Ultimately, a blended course model for statistics and quantitative method courses was developed that allowed students to choose between online, remote (via interactive television), and traditional course delivery modes each week. This model is more flexible and agile than existing blended courses that have more static components. Multiple regression analysis, ?[superscript 2], and t-tests are used to demonstrate the efficacy of our model in maintaining student performance standards. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01