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An exploratory study of adult learners’ perceptions of online learning: Minority students in continuing education

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Abstract

The study was an investigation of online adult learners’ perceptions of interaction, satisfaction, and performance within an online course using the Blackboard platform. Interaction included learners’ interaction with the instructor, content, and the classmates. The effect of student background variables and course-related variables on interaction was explored. Participants were 167 minority students enrolled in six online undergraduate-level courses from a university in the southeastern United States. The majority of the students were African-American working adults. Results indicated that learner–content interaction and learner–instructor interaction were significant predictors for student satisfaction in online settings in which group activities were not provided. Internet self-efficacy was positively associated with three types of interaction. Student satisfaction was positively related to student performance. Learner–instructor interaction was influenced the most by student background variables (gender, age, hours spent online), and learner–learner interaction by course-related variables (course length, course type, and the number of discussion forums). While it had the strongest influence on student satisfaction, learner–content interaction was not affected by student- or course-related variables.

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References

  • Allen, M., Bourhis, J., Burrell, N., & Mabry, E. (2002). Comparing student satisfaction with distance education to traditional classrooms in higher education: A meta-analysis. American Journal of Distance Education, 16(2), 83–97. doi:10.1207/S15389286AJDE1602_3.

    Article  Google Scholar 

  • Allen, I. E., & Seaman, J. (2010). Class differences: Online education in the United States, 2010. Sloan Consortium. Retrieved January 1, 2016, from http://eric.ed.gov/?id=ED529952.

  • Allen, I. E., & Seaman, J. (2013). Changing course: Ten years of tracking online education in the United States. Sloan Consortium. Retrieved January 1, 2016, from http://eric.ed.gov/?id=ED541571.

  • An, H., Shin, S., & Lim, K. (2009). The effects of different instructor facilitation approaches on students’ interactions during asynchronous online discussions. Computers & Education, 53(3), 749–760. doi:10.1016/j.compedu.2009.04.015.

    Article  Google Scholar 

  • Anderson, T. (2003). Modes of interaction in distance education: Recent developments and research questions. In M. G. Moore & W. G. Anderson (Eds.), Handbook of distance education (pp. 129–144). New York: Routledge.

    Google Scholar 

  • Anderson, T., & Garrison, D. R. (1998). Learning in a networked world: New roles and responsibilities. In Distance learners in higher education: Institutional responses for quality outcomes. Madison, WI: Atwood. Retrieved January 1, 2016, from http://auspaceathabascau.applyforeasycredit.com/handle/2149/801.

  • Artino, A. R. (2007). Online military training: Using a social cognitive view of motivation and self-regulation to understand students’ satisfaction, perceived learning, and choice. Quarterly Review of Distance Education, 8(3), 191–202.

    Google Scholar 

  • Barker, C., Pistrang, N., & Elliott, R. (2005). Research methods in clinical psychology: An introduction for students and practitioners. Chichester, UK: Wiley.

    Google Scholar 

  • Battalio, J. (2007). Interaction online: A reevaluation. Quarterly Review of Distance Education, 8(4), 339–352.

    Google Scholar 

  • Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289. doi:10.3102/0034654309333844.

    Article  Google Scholar 

  • Biner, P. M., Bink, M. L., Huffman, M. L., & Dean, R. S. (1997). The impact of remote-site group size on student satisfaction and relative performance in interactive telecourses. American Journal of Distance Education, 11(1), 23–33. doi:10.1080/08923649709526949.

    Article  Google Scholar 

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

    Google Scholar 

  • Bray, E., Aoki, K., & Dlugosh, L. (2008). Predictors of learning satisfaction in Japanese online distance learners. The International Review of Research in Open and Distance Learning, 9(3). Retrieved January 1, 2016, from http://www.irrodl.org/index.php/irrodl/article/view/525.

  • Brookfield, S. (1987). Developing critical thinkers. Milton Keynes: Open University Press. Retrieved January 1, 2016, from http://stephenbrookfield.com/Dr._Stephen_D._Brookfield/Workshop_Materials_files/Developing_Critical_Thinkers.pdf.

  • Brown, E., Cristea, A., Stewart, C., & Brailsford, T. (2005). Patterns in authoring of adaptive educational hypermedia: A taxonomy of learning styles. Educational Technology & Society, 8(3), 77–90.

    Google Scholar 

  • Chang, S.-H. H., & Smith, R. A. (2008). Effectiveness of personal interaction in a learner-centered paradigm distance education class based on student satisfaction. Journal of Research on Technology in Education, 40(4), 407–426.

    Article  Google Scholar 

  • Chejlyk, S. (2006). The effects of online course format and three components of student perceived interactions on overall course satisfaction. Capella University. http://www.editlib.org/p/117746/.

  • Clark, R. E. (2000). Evaluating distance education: Strategies and cautions. International Journal of Educational Policy, Research, and Practice: Reconceptualizing Childhood Studies, 1(1), 3–16.

    Google Scholar 

  • Dabbagh, N. (2007). The online learner: Characteristics and pedagogical implications. Contemporary Issues in Technology and Teacher Education, 7(3), 217–226.

    Google Scholar 

  • DeBourgh, G. A. (1999). Technology is the tool, teaching is the task: Student satisfaction in distance learning (Vol. 1999, pp. 131–137). Presented at the Society for Information Technology & Teacher Education International Conference. Retrieved January 1, 2016, from http://www.editlib.org/p/7521/.

  • Dennen, V. P., & Wieland, K. (2008). Does task type impact participation? Interaction levels and learner orientation in online discussion activities. Technology, Instruction, Cognition and Learning, 6, 105–124.

    Google Scholar 

  • Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication. doi:10.1111/j.1083-6101.2000.tb00110.x.

    Google Scholar 

  • Gangadharbatla, H. (2008). Facebook me: Collective self-esteem, need to belong, and Internet self-efficacy as predictors of the igeneration’s attitudes toward social networking sites. Journal of Interactive Advertising, 8(2), 5–15. doi:10.1080/15252019.2008.10722138.

    Article  Google Scholar 

  • Garrison, D. R., & Shale, D. (1990). A new framework and perspective. Education at a distance: From issues to practice (pp. 123–133). Kreiger: Malabar, FL.

    Google Scholar 

  • Graham, R., & Smith, D. T. (2010). Dividing lines: An empirical examination of technology use and Internet activity among African-Americans. Information, Communication & Society, 13(6), 892–908. doi:10.1080/13691180903514344.

    Article  Google Scholar 

  • Havice, P. A., Foxx, K. W., Davis, T. T., & Havice, W. L. (2010). The impact of rich media presentations on a distributed learning environment. Quarterly Review of Distance Education, 11(1), 53.

    Google Scholar 

  • Hirumi, A. (2012). The design and sequencing of online and blended learning interactions: A framework for grounded design. Canadian Learning Journal, 16(2), 21–25.

    Google Scholar 

  • Johnson, S. D., Aragon, S. R., & Shaik, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of Interactive Learning Research, 11(1), 29–49.

    Google Scholar 

  • Ke, F., & Kwak, D. (2013). Online learning across ethnicity and age: A study on learning interaction participation, perception, and learning satisfaction. Computers & Education, 61, 43–51. doi:10.1016/j.compedu.2012.09.003.

    Article  Google Scholar 

  • Ke, F., & Xie, K. (2009). Toward deep learning for adult students in online courses. The Internet and Higher Education, 12, 136–145. doi:10.1016/j.iheduc.2009.08.001.

    Article  Google Scholar 

  • Keeler, L. C. (2006). Student satisfaction and types of interaction in distance education courses. Dissertation Abstracts International, 67(09) (UMI No. 3233345).

  • Keller, J. M. (1983). Motivational design of instruction. In C. M. Reigeluth (Ed.), Instructional-design theories and models: An overview of their current status. Hillsdale, NJ: Psychology Press.

    Google Scholar 

  • Kuo, Y. C. (2014). Accelerated online learning: Perceptions of interaction and learning outcomes among African American students. American Journal of Distance Education. doi:10.1080/08923647.2014.959334.

    Google Scholar 

  • Kuo, Y. C., Chen, Y. S., & Kuo, Y. T. (2015). Interaction among online adult learners with the use of technologies. Journal of Technologies in Education, 11(1), 1–10.

    Google Scholar 

  • Kuo, Y. C., Walker, A., Belland, B. R., & Schroder, K. E. E. (2013). A predictive study of student satisfaction in online education programs. The International Review of Research in Open and Distance Learning, 14(1), 16–39.

    Google Scholar 

  • Kuo, Y. C., Walker, A., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35–50. doi:10.1016/j.iheduc.2013.10.001.

    Article  Google Scholar 

  • Liang, J.-C., & Tsai, C.-C. (2008). Internet self-efficacy and preferences toward constructivist internet-based learning environments: A study of pre-school teachers in Taiwan. Educational Technology & Society, 11(1), 226–237.

    Google Scholar 

  • Liao, P.-W., & Hsieh, J. Y. (2011). What influences Internet-based learning? Social Behavior and Personality: An International Journal, 39(7), 887–896. doi:10.2224/sbp.2011.39.7.887.

    Article  Google Scholar 

  • 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. US Department of Education. http://eric.ed.gov/?id=ED505824.

  • Moore, M. G. (1989). Editorial: Three types of interaction. American Journal of Distance Education, 3(2), 1–7. doi:10.1080/08923648909526659.

    Article  Google Scholar 

  • Moore, M. G., & Kearsley, G. (1996). Distance education: A systems view. Distance Education, 17, 412.

    Article  Google Scholar 

  • Pike, G. R. (1993). The relationship between perceived learning and satisfaction with college: An alternative view. Research in Higher Education, 34(1), 23–40. doi:10.1007/BF00991861.

    Article  Google Scholar 

  • Reinhart, J., & Schneider, P. (2001). Student satisfaction, self-efficacy, and the perception of the two-way audio/video distance learning environment: A preliminary examination. Quarterly Review of Distance Education, 2(4), 357–365.

    Google Scholar 

  • Robles, F. M. R. (2006). Learner characteristic, interaction and support service variables as predictors of satisfaction in Web-based distance education. ProQuest. Dissertation Abstracts International, 67(07) (3224964).

  • Rovai, A. P., & Baker, J. D. (2005). Gender differences in online learning: Sense of community, perceived learning, and interpersonal interactions. Quarterly Review of Distance Education, 6(1), 31–44.

    Google Scholar 

  • Salmon, G. (2000). E-moderating: The key to teaching and learning online. London: Kogan Page.

    Book  Google Scholar 

  • Shi, J., Chen, Z., & Tian, M. (2010). Internet self-efficacy, the need for cognition, and sensation seeking as predictors of problematic use of the Internet. Cyberpsychology, Behavior, and Social Networking, 14(4), 231–234. doi:10.1089/cyber.2009.0462.

    Article  Google Scholar 

  • Stevens, J. P. (2012). Applied multivariate statistics for the social sciences (5th ed.). New York: Routledge.

    Google Scholar 

  • Swan, K. (2003). Learning effectiveness online: What the research tells us. In J. Bourne & J. C. Moore (Eds.), Elements of quality online education, practice and direction (Vol. 4, pp. 13–47). Needham, MA: Sloan Center for Online Education. Retrieved January 1, 2016, from http://cguevara.commons.gc.cuny.edu/files/2009/09/learning-effectiveness.pdf.

  • Tsai, C.-C. (2012). The development of epistemic relativism versus social relativism via online peer assessment, and their relations with epistemological beliefs and Internet self-efficacy. Educational Technology & Society, 15(2), 309–316.

    Google Scholar 

  • US Census Bureau. (2010). Computer and Internet use in the United States: 2010. Retrieved January 1, 2016, from http://www.census.gov/hhes/computer/publications/2010.html.

  • Wagner, E. D. (1994). In support of a functional definition of interaction. American Journal of Distance Education, 8(2), 6–29. doi:10.1080/08923649409526852.

    Article  Google Scholar 

  • Wanstreet, C. E. (2006). Interaction in online learning environments: A review of the literature. Quarterly Review of Distance Education, 7(4), 399–411.

    Google Scholar 

  • Woo, Y., & Reeves, T. C. (2007). Meaningful interaction in web-based learning: A social constructivist interpretation. The Internet and Higher Education, 10(1), 15–25. doi:10.1016/j.iheduc.2006.10.005.

    Article  Google Scholar 

  • Yalcinalp, S., & Gulbahar, Y. (2010). Ontology and taxonomy design and development for personalised web-based learning systems. British Journal of Educational Technology, 41(6), 883–896. doi:10.1111/j.1467-8535.2009.01049.x.

    Article  Google Scholar 

  • Yukselturk, E., & Yildirim, Z. (2008). Investigation of interaction, online support, course structure and flexibility as the contributing factors to students’ satisfaction in an online certificate program. Educational Technology & Society, 11(4), 51–65.

    Google Scholar 

  • Zhu, E. (2006). Interaction and cognitive engagement: An analysis of four asynchronous online discussions. Instructional Science, 34(6), 451–480. doi:10.1007/s11251-006-0004-0.

    Article  Google Scholar 

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Kuo, YC., Belland, B.R. An exploratory study of adult learners’ perceptions of online learning: Minority students in continuing education. Education Tech Research Dev 64, 661–680 (2016). https://doi.org/10.1007/s11423-016-9442-9

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