Relationships Between Minority Students Online Learning Experiences and Academic Performance

Alex Kumi Yeboah, Patriann Smith

Abstract


The study investigated the relationship between minority students’ use of technology, social media, the number of online courses, program of study, satisfaction, and academic performance. Participants in the study were a diverse student body regarding age, gender, and educational level, and functioned at both undergraduate and graduate levels. Analysis of variance (ANOVA) and Chi-square tests were used to find the relationship between participants’ online learning experiences and academic performance. Results showed that satisfaction and use of social media had no relationship with the academic performance of participants. However, a relationship existed between the use of technology, the number of courses in online, program of study, and academic performance. Categories that emerged from the open-ended questions were flexibility and time convenience, self-confidence, lack of support, self-regulated learning skills, and language and linguistic differences. The authors concluded that varying factors such as cultural, language, personal, and efficacy skills facilitated the academic performance of minority students in an online learning environment. This study reiterates the importance of establishing multicultural presence in an online course and suggests best pedagogical methods for teaching minority students in an online course.

Keywords


Minority students, satisfaction, social media, use of technology, academic performance, self-regulated learning, and self-confidence.

Full Text:

PDF

References


Allen, I. E., & Seaman, J. (2008). Class differences: Online education in the United States, 2010. Needham, MA: Babson Survey Research Group.

Allen, I. E., & Seaman, J. (2014). Class differences: Online education in the United States. Needham, MA: Babson Survey Research Group. Retrieved February 4, 2015 https://www.sloan c.org/publications/survey/pdf/sizing_opportunity.pdf

Arbaugh, J. B. (2002). Managing the on-line classroom: a study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13, 203–223.

Arbaugh, J. B., & Duray, R. (2002). Technological and structural characteristics, student learning and satisfaction with web-based courses–An exploratory study of two on-line MBA programs. Management Learning, 33(3), 331-347.

Artino, A.R. (2008). Promoting academic motivation and self-regulation: Practical guidelines for online instructors. TechTrends, 52(3), 37-45.

Artino, A.R., & Stephens, J. M. (2009). Academic motivation and self-regulation: A comparative analysis of undergraduate and graduate students learning online. Internet and Higher Education, 12, 146-151.

Astin, A. W. (1993). What matters in college? Four critical years revisited. San Francisco, CA: Jossey-Bass.

Azevedo, R. (2005). Using hypermedia as a metacognitive tool for enhancing student

learning. The role of self-regulated learning. Educational Psychologist, 40 (4), 199-209.

Azevedo, R., Cromley, J. G., & Seibert, D. (2004). Does adaptive scaffolding facilitate

students’ ability to regulate their learning with hypermedia. Contemporary Educational Psychology, 29, 344-370.

Barnard-Brak, L., Paton, V. O., & Lan, W. Y. (2010). Self-regulation across time of first-generation online learners. Research in Learning Technology, 18(1), 61-70.

Battalio, J. (2007). Interaction online: A re-evaluation. Quarterly Review of Distance Education, 8(4), 339-352.

Bollinger, D. U., & Martindale, T. (2004). Key factors for determining student satisfaction in online courses. International Journal on E-Learning, 3(1), 61-67.

Bork, R. H., & Rucks-Ahidiana, Z. (2013). Role ambiguity in online courses: An analysis of student and instructor expectations. (CCRC Working Paper No.64). New York: Columbia University, Teachers College, Community College Research Center.

Bothma, F., & Monteith, J. (2004). Self-regulated learning as a prerequisite for successful distance learning. South Africa Journal of Education, 24(2), 141-147.

Brown, B. W., & Liedholm, C. E. (2002). Can web courses replace the classroom in principles of microeconomics. The American Economic Review, 92(2), 444-448.

Chavous, T. M., Debra, H. B., Schmeelk-Cone, K., Caldwell, C. H., Kohn-Wood, L. L., & Zimmerman, M. A. (2003). Racial identity and academic attainment among African American adolescents. Child Development, 74(4), 1076.

Coates, D., Humphreys, B. R., Kane, J., & Vachris, M. A. (2004). “No significant distance” between face-to-face and online instruction: Evidence from principles of economics. Economics of Education Review, 23, 533-546.

Corbeil, J. R. (2003). Online technologies, self-efficacy, self-directed learning readiness, and locus of control of learners in a graduate-level web-based distance education program. (Unpublished doctoral dissertation). University of Houston, Houston, TX.

Eom, S. B., Wen, H. J., & Ashill, N. (2006). The determinants of students’ perceived

learning outcomes and satisfaction in university online education: An empirical investigation. Decision Sciences Journal of Innovative Education, 4(2), 215-235.

Fredericksen, E., Pickett, A., Pelz, W., Shea, P., & Swan, K. (2000). Student satisfaction and perceived learning with online courses: principles and examples from the SUNY Learning Network. Journal of Asynchronous Learning Networks, 14(2).

Green, K. (2007). The 2007 campus computing survey. Retrieved January 17, 2015 from http://www.campuscomputing.net/sites/www.campuscomputing.net/files/2007-CCP_0.pdf.

Goodfellow, R., & Hewling, A. (2005). Reconceptualizing culture in virtual learning environments: from an ‘essentialist’ to a ‘negotiated’ perspective. E-Learning, 2(4), 355 -367.

Guglielmino, L. M., & Guglielmino, P. J. (2002). Learner characteristics affecting success in electronic distance learning. In H.B. Long & Associates, Twenty-First Century Advances in Self-Directed Leaning. Boynton Beach, FL: Motorola University Press

Gunawardena, C., Wilson, P., & Nolla, A. (2003). Culture and online education. In M. Morre, & W. Anderson (Eds.), Handbook of distance education (pp. 753-775). Mahwah, NJ: Lawrence Erlbaum.

Hannafin, M. J., & Land, S. M. (1997). The foundations and assumptions of technology enhanced student-centered learning environments. Instructional Science, 25, 167-202.

Hawkins, B. L., & Rudy, J. A. (2008). EDUCAUSE core data service fiscal year 2007 summary report. Retrieved January 10, 2015 from http://net.educause.edu/ir/library/pdf/PUB8005.pdf.

Hiltz, S. R., & Shea, P. (2005). The student in the online classroom. In S. R. Hiltz & R. Goldman (Eds.), Learning together online: Research on asynchronous learning networks (pp. 145-168). Mahwah, NJ: Erlbaum.

Hodges, C. B., & Kim, C. (2010). Email, self-regulation, self-efficacy, and achievement in a college online mathematics course. Educational Computing Research, 43(2), 207-223.

Hong, K. S. (2002). Relationships between students’ and instructional variables with satisfaction and learning from a Web-based course. Internet and Higher Education, 5, 267–281.

Ibarra, R. (2000). Studying Latinos in a “virtual” university: Reframing diversity and academic culture change. Occasional Paper No. 68. Latino Studies Series. East Lansing, MI: Julian Samora Research Institute, Retrieved March 3, 2015, from ERIC database.

Jiang, M., & Ting, E. (1998). Course design, instruction, and students’ online behaviors: A study of instructional variables and student perceptions of online learning. In Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA, April 13–17, 1988

Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: a research paradigm whose time has come. Educational Researcher, 33(7), 14-26.

Jonassen, D. H., Davidson, M., Collins, M., Campbell, J., & Haag, B. B. (1995). Constructivism and computer-mediated communication in distance education. American Journal of Distance Education, 9(2), 7-25.

Jonassen, D. H., & Land, S. M. (2000). Theoretical foundations of learning environments. Mahwah, NJ: Lawrence Erlbaum Associates.

Jung, I., Choi, S., Lim, C., & Leem, J. (2002). Effects of different types of interaction on learning achievement, satisfaction and participation in web-based instruction. Innovations in Education & Teaching International, 39(2), 153–162.

Kanuka, H., & Nocente, N. (2003). Exploring the effects of personality type on perceived satisfaction with web-based learning in continuing professional development. Decision Education, 24(2), 227-245.

Ke, F. (2010). Examining online teaching, cognitive, and social presence for adult students. Computers & Education, 55(2), 808-820.

Ke, F., & Carr-Chellman, A. (2006). Solitary learner in online collaborative learning: a disappointing experience. Quarterly Review of Distance Education, 7(3), 249-265.

King, F. B., Harner, M., & Brown, S. W. (2000). Self-regulatory behavior influences in distance learning. International Journal of Instructional Media, 27(2), 147-156.

Kearsley, G. (2002). Is online learning for everybody. Educational Technology, 42(1), 41-44.

Moore, M. G., & Kearsley, G. (2005). Distance education: A systems view (2nd ed.). Belmont, CA: Wadsworth.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Washington, DC: US Department of Education.

Matuga, J.M. (2009). Self-regulation, goal orientation, and academic achievement of secondary students in online university courses. Educational Technology & Society, 12(3), 4-11.

Nicol, D. (2009). Assessment for learner self-regulation: Enhancing achievement in the first year using learning technologies. Assessment & Evaluation in Higher Education, 34(3), 335-352.

Okwumabua, T. M., Walker, K. M., Hu, X., & Watson, A. (2011). An exploration of African American students' attitudes toward online learning. Urban Education, 46, 241-250.

Paraskeva, Mysirlaki, & Choustoulakis (2009). Designing collaborative learning environments using educational scenarios based on self-regulation. International Journal of Advanced Corporate Learning, 2(1), 42-49.

Peterson, S. (2011). Self-regulation and online course satisfaction in high school. Dissertation Abstracts International, 71(10A) (UMI No. 3466080).

Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: a research framework and a preliminary assessment of effectiveness in basic IT skill training. MIS Quarterly, 25(4), 401-426.

Public Agenda. (2013). Not yet sold: What employers and community college students think about online education. New York: Author.

Puzziferro,M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. American Journal of Distance Education, 22(2), 72-89.

Quintana, C., Zhang, M., & Krajcik, J. (2005). Scaffolded software environments for supporting metacognitive aspects of online inquiry. Educational Psychologist, 40, 235-244.

Rovai, A. P., Ponton, M. K., Wighting, M. J., & Baker, J. D. (2007). A comparative analysis of student motivation in traditional classroom and E-learning courses. International. Journal on E-Learning, 6(3), 413-432.

Shapiro, A. (2000). The effect of interactive overviews on the development of conceptual structure in novices learning from hypermedia. Journal of Educational Multimedia & Hypermedia, 9, 57–78.

Shea, P., & Bidjerano, T. (2010). Learning presence: Towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments. Computers & Education, 55, 1721-1731.

Sher, A. (2009). Assessing the relationship of student–instructor and student–student interaction to student learning and satisfaction in web-based online learning environment. Journal of Interactive Online Learning, 8(2), 102–120.

Stokes, S. P. (2001). Satisfaction of college students with the digital learning environment. Do Learners’ temperaments make a difference. Internet and High Education, 4, 31–44.

Smith, D., & Ayers, D. (2006). Culturally responsive pedagogy and online learning: implications for the globalized community college. Community College Journal of Research & Practice, 30(5/6), 401-415.

Sun, P., Tsai, R. J., Finger, G., Chen, Y., & Yeh, D. (2008). What drives a successful e-learning: An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50 (4), 1183-1202.

Swan, K., Shea, P., Fredericksen, E., Pickett, A., Pelz, W., & Maher, G. (2000). Building knowledge building communities: consistencies, contact and communication in the virtual classroom. Journal of Educational Computing Research, 23(4), 359-383.

Swan, K. (2001). Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education, 22(2),

–331.

Thurmond, V. A. (2003). Examination of interaction variables as predictors of students' satisfaction and willingness to enroll in future web-based courses while controlling for student characteristics. Retrieved February 6, 2015 from. http://www.bookpump.com/dps/pdf-b/ 1121814b.pdf

Thurmond, V. A., & Wambach, K. (2004). Understanding interactions in distance education: A review of the literature. International Journal of Instructional Technology and Distance Learning, 1(1), 9-26.

Williams, M. (1996). Learner control and instructional technologies. In D. Jonassen (Ed.), Handbook of research on educational communications and technology (pp. 957–983). NY: Scholastic.

Wang, M. (2007). Designing online courses that effectively engage learners from diverse cultural backgrounds. British Journal of Educational Technology, 38(2), 294-311, Retrieved January 30, 2015, from ERIC database.

Wong, F., & Trinidad, S. (2004). Using ICT in web-based distance learning to reduce the cultural distance. Journal of Interactive Online Learning, 3, 1-13.

Xu, D. & Jaggars, S.S. (2011). Online and Hybrid Course Enrollment and Performance in Washington State Community and Technical Colleges (CCRC Working Paper No. 31). New York: Community College Research Center, Teachers College, Columbia University. Retrieved on January 3, 2015 from http://ccrc.tc.columbia.edu/Publication.asp?UID=872

Xu, D., & Jaggars, S. S. (2013). The impact of online learning on students’ course outcomes: Evidence from a large community and technical college system. Economics of Education Review, 37, 46-57.

Yen, H. J., & Liu, S. (2009). Learner autonomy as a predictor of course success and final grades in community college online courses. Journal of Educational Computing Research, 41(3), 347-367.

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329–339.

Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). San Diego: Academic Press.




DOI: http://dx.doi.org/10.24059/olj.v20i4.577