Further Exploring Differences in Business Undergraduate Perceived Outcomes by Preferred Classroom Learning Environment
ARTICLE
Gary Blau, Sherry Jarrell, Michael McCloskey, Wayne Williams, Alan Kerzner, Tyra Ford
Journal of Education and Learning Volume 7, Number 5, ISSN 1927-5250
Abstract
The purpose of this study was to compare business undergraduate online/hybrid course perceptions across three different preferred classroom learning environments (CLE): online, hybrid, or face-to-face (F2F). Six different perception-based outcomes were measured: easy to use technology, peer-perceived favorability of online/hybrid courses (peer-PFoOC); instructor-perceived favorability of online/hybrid courses (instructor-PFoOC); intent to recommend online/hybrid courses; institutional commitment; and persistence towards graduation. Undergraduates who were simultaneously taking at least one online or hybrid class and F2F course, i.e., mixed course delivery format, voluntarily completed an online survey. In the fall of 2017, a complete-data sample of n = 242 respondents was obtained and in the spring of 2018 the complete-data sample was n = 237. Consistent results across both samples were found for the outcomes. Undergraduates who preferred either online or hybrid CLE had significantly higher peer-PFoOC, instructor-PFoOC, and intent to recommend online/hybrid courses than students preferring an F2F environment. There were no differences between these three CLE preference groups in perceived easy to use technology, institutional commitment or persistence. As universities increase their online and hybrid course offerings monitoring student perceived outcomes between F2F and online/hybrid course sections will continue to be important.
Citation
Blau, G., Jarrell, S., McCloskey, M., Williams, W., Kerzner, A. & Ford, T. (2018). Further Exploring Differences in Business Undergraduate Perceived Outcomes by Preferred Classroom Learning Environment. Journal of Education and Learning, 7(5), 20-30. Retrieved August 7, 2024 from https://www.learntechlib.org/p/190705/.
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Keywords
- blended learning
- Business Administration Education
- Classroom Environment
- Comparative Analysis
- Correlation
- Differences
- Graduation
- multivariate analysis
- online courses
- Online Surveys
- Outcomes of Education
- Statistical Analysis
- Synchronous Communication
- Technology Uses in Education
- undergraduate students
References
View References & Citations Map- Alavi, M. (1994). Computer-mediated collaborative learning: An empirical evaluation. MIS Quarterly, 18(2), 159-174.
- Arbaugh, J.B. (2005). Is there an optimal design for online MBA courses? Academy of Management& Education, 4(2), 135-149.
- Arbaugh, J.B. (2014). What might online delivery teach us about blended management education? Prior perspectives and future directions. Journal of Management Education, 38, 784-817.
- Beck, H.P., & Milligan, M. (2014). Factors influencing the institutional commitment of online students. Internet and Higher Education, 20, 51-56. Https://doi.org/10.1016/J.iheduc.2013.09.002
- Blau, G., & Drennan, R. (2017). Exploring difference in business undergraduate perceptions by preferred classroom delivery mode. Online Learning, 21(3), 222-234. Https://doi.org/10.24059/olj.v21i3.973
- Blau, G., Mittal, N., Schirmer, M., & Ozkan, B. (2017). Differences in business undergraduate perceptions by preferred classroom learning environment. Journal of Education for Business, 92(6), 280-287.
- Britt, M. (2015). How to better engage online students with online strategies. College Student Journal, 49(3), 399-404.
- Cavanaugh, J., & Jaquemin, S.J. (2015). A large sample comparison of grade based student learning outcomes in online versus face-to-face courses. Online Learning, 19(2), 25-32. Https://doi.org/10.24059/olj.v19i2.454
- Comer, D.R., Lengaghan, J.A., & Sengupta, K. (2015). Factors that affect students’ capacity to fulfill the role of online learner. Journal of Education for Business, 90, 145-155.
- Daymont, T., Blau, G., & Campbell, D. (2011). Deciding between traditional and online formats: Exploring the role of learning advantages, flexibility and compensatory adaptation. Journal of Behavioral and Applied Management, 11, 156-179.
- Hart Research Associates. (2015). Falling short? College learning and career success. Washington, DC: Association of American Colleges& Universities. Retrieved from https://www.aacu.org/leap/public-opinion-research/2015-survey-results
- Haughton, J., & Kelly, A. (2015). Student performance in an introductory business statistics course: Does delivery mode matter? Journal of Education for Business, 90, 31-43.
- Johnson, D., & Palmer, C.C. (2015). Comparing student assessments and perceptions of online and face-to-face versions of an introductory linguistics course. Online Learning, 19(2), 33-42.
- Nulty, D.D. (2008). The adequacy of response rates to online and paper surveys: What can be done? Assessment& Evaluation in Higher Education, 33(3), 301-314.
- Nunnally, J.C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw Hill.
- Podsakoff, P., Mackenzie, S., Lee, J., & Podsakoff, N. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903.
- Reason, R. (2009). An examination of persistence research through the lens of a comprehensive conceptual framework. Journal of College Student Development, 50(6), 659-682.
- Rindfuss, R.R., Choe, M.K., Tsuya, N.O., Bumpass, L.L., & Tamaki, E. (2015). Do low survey response rates bias results? Evidence from Japan. Demographic Research, 32(26), 797-828.
- Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences (2nd ed.). Mahwah, NJ: Lawrence Erlbaum.
- Wang, Q., Lit Woo, H., Lang Quek, C., Yang, Y., & Liu, M. (2012). Using Facebook group as a learning management system. British Journal of Educational Technology, 43(3), 428-438.
- Yu, T., & Richardson, J.C. (2015). An exploratory factor analysis and reliability analysis of the Student Online Learning Readiness (SOLR) instrument. Online Learning, 19(5), 120-141.
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