grev 721 Poster session

1. An analysis of motivational beliefs, expectancies and goals and their impact on learners’
satisfaction in online learning environments in higher education
Online courses differ from traditional courses in the way students are required to be confident in performing technology-based activities.
Students with low level of confidence in online learning might not engage in learning activities, which lead to dissatisfaction in online
learning environments (Kuo, et. al., 2013). Moreover, students with low level of expectations may lead to decreasing level of learning
satisfaction in online learning (Hawkins, 2010). Similarly, goals that students set for themselves can predict students’ satisfaction in online
learning (Locke, and Latham, 2006). This paper proposes a method to examine self-efficacy beliefs, expectancies and goals, and their
relation to learner’ satisfaction in online learning environments in higher education.
Self-efficacy
•Research on Self-efficacy is on its infancy
•Predict student success
•Learners’ efficacy beliefs are directly
related to their academic performance
•People with high learning self efficacy
perform better, are more satisfied with
their performance and they are
committed to change and develop
•Technological tools in online learning
environments can be useful if learners
possess self-efficacy for regulating their
own learning, which leads to positive self-
efficacy for using online learning
Outcome expectancies and goal setting
•People with high outcome expectancy of
certain action result to specific outcomes,
which leads to high level of motivation to
perform successfully
•Outcome expectations can predict
performance motivation
•People who set themselves specific
difficult goals perform better than people
who have no goals at all or vague goals
like “do your best”.
Literature Review
Abstract
Emtinan Alqurashi, Instructional Technology and Leadership
Duquesne University
Methodology
•Participants: graduate students in the
school of education taking fully online
courses
•Setting: face-to-face & online
•Procedure: mixed method, online
survey and in-depth interviews.
•Phenomenology: investigates the way
people experience the world
•Structure online survey for quantitative
data and structures interviews a deeper
understanding of students’ perception
and experiences
Qualitative data analysis:
•Familiarizing yourself with your data
•Generating initial codes
•Searching for themes
•Reviewing themes
•Defining and naming themes
•Producing the report
Implementation
• No generalizations can be made if
there were a limited number of
participants
References
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. doi:10.1037/0033-295X.84.2.191
Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York: Academic Press.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.
Bandura, A. (2002). Growing primacy of human agency in adaptation and change in the electronic era. European Psychologist, 7(1), 2-16. doi:10.1027//1016-9040.7.1.2
Braun, V. and Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology. 3(2), 77-101.
Hawkins, G. W. (2010). Online learners' expectations and learning outcomes. ProQuest LLC, Retrieved from http://search.proquest.com/docview/288193817
Hodges, C. B. (2008). Self-efficacy in the context of online learning environments: A review of the literature and directions for research. Performance Improvement Quarterly, 20(3), 7-25.
Retrieved from http://search.proquest.com/docview/218576581?accountid=10610
Kuo, Y., Walker, A. E., Schroder, K. 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, 2035-50. doi:10.1016/j.iheduc.2013.10.001
Kuo, Y., Walker, A., Belland, B., & Schroder, K. (2013). A predictive study of student satisfaction in online education programs. The International Review Of Research In Open And Distributed
Learning, 14(1), 16-39. Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1338/2416
Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. The American Journal of Distance
Education, 15(2), 41–50.
Locke, E. A., & Latham, G. P. (1990). A theory of goal setting & task performance. Englewood Cliffs, NJ, US: Prentice-Hall, Inc.
Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist,57(9), 705-717. doi:10.1037/0003-
066X.57.9.705
Locke, E. A., & Latham, G. P. (2006). New Directions in Goal-Setting Theory. Current Directions in Psychological Science, 15(5), 265-268.
Locke, E. A., & Latham, G. P. (2013). New developments in goal setting and task performance. New York and London: Routledge.
Van, M. M. (1997). Researching lived experience: Human science for an action sensitive pedagogy. London, Ont: Althouse Press.
Pintrich, P., & Schunk, D. (2002). Motivation in education: Theory, research, and applications. Upper Saddle River, NJ: Merrill Prentice Hall.
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.
Ryan, G.W. & Bernard, H.R. (2000). "Data management and analysis methods." In Denzin, N.K. & Lincoln, Y.S., (Eds.) Handbook of qualitative research, second edition. London: Sage Publications.
Retrieved from http://nersp.nerdc.ufl.edu/~ufruss/documents/ryanandbernard.pdf
Schunk, D.H. (1991). Self-efficacy and academic motivation. Educational Psychologist, 26(3&4), 207-231. doi:10.1080/00461520.1991.9653133.
Shen, D., Cho, M., Tsai, C., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet And Higher Education, 1910-17.
doi:10.1016/j.iheduc.2013.04.001
Womble, J. C. (2008). E-learning: The relationship among learner satisfaction, self-efficacy, and usefulness. Dissertation Abstracts International, 69, 728.
Students satisfaction
• One of the pillars to assess the quality of online
learning
• Self-efficacy is considered as a major factor to
predict student’s satisfaction in online learning
environments
• if learner’s expectations in specific
domains decrease, their level of learning
satisfaction decrease as well
• self-efficacy was a significant predictor of
student’s satisfaction and their willingness
to take other online courses in the future.
Proposed Research Questions
How do students perceive their self-efficacy
in online learning environments in relation
to their satisfaction?
How do students’ outcome expectation of
the online course relate to their
satisfaction?
How do students’ goals in online learning
relate to their satisfaction?