Unpacking the Influence of Online Students’ Perceived Course Satisfaction/Dissatisfaction on their Performance
Concurrent Session 3
To what extent do online students’ perceive their course satisfaction and dissatisfaction influence their course performance? Presenters will answer this question based on findings from a dissertation study and references such as Keller’s ARCS Model and Herzberg’s two-factor theory. They will recommend strategies that could potentially improve online students performance.
To what extent do online students perceive that their satisfying and dissatisfying online course experiences influenced their online course performance? Answering this question bears significance, given the escalating number of higher education online courses and programs, in which student satisfaction is underscored as a quality indicator (Allen, Seaman, Poulin, & Straut, 2016; Quality Matters, 2014). The significance of including students’ voices for informing enhancements to online course design and development continues to gain researchers’ attention in this fastest growing course modality in higher education (Clinefelter & Aslanian, 2016; Jacobi, 2016; Shattuck, 2015). Unlike their counterparts in traditional face-to-face classes, students in the online environment are usually more mature and challenged to be self-directed in their learning that requires high levels of motivation and confidence in order to succeed (Katt & Condly, 2009; Kauffman, 2015). Employing the Keller’s ARCS Model (Milman & Wessmiller, 2016) and Herzberg’s two-factor theory (Herzberg, Mausner, & Snyderman, 1959), the current presentation intents to unpack online master’s students’ perception of the influence of their satisfying and dissatisfying online course experiences on their online course performance. Based on findings from a doctoral dissertation that examined such influence on online students’ course performance, the presenters will recommend instructional strategies that could lead to satisfying online learning experiences that could potentially increase online students’ course performance.
Practice appears to be ahead of research as online courses and program rapidly increase to match student demand (Clinefelter & Aslanian, 2016; Jacobi, 2016; Shattuck, 2015), but research on key factors influencing both online students’ satisfaction and dissatisfaction (Chyung & Virgilio, 2013; Katt & Condly, 2009) and, by extension, their performance is needed. To this end, only a few studies can be found that applied Herzberg’s et al. (1959) two-factor theory (of satisfaction and dissatisfaction) to higher education for understanding the factors that influence both students’ satisfaction and dissatisfaction in these learning environments (Chyung & Vachon, 2005; Danielson, 1998; DeShields, Kara, & Kaynak, 2005; Katt & Condly, 2009). A sole study from among the latter, Chyung and Vachon (2005), explored factors leading to students’ satisfaction and dissatisfaction with their online learning experiences, but did not probe how such satisfaction or dissatisfaction influenced students’ course performance. The need for further research on how online students’ course satisfaction influence their performance is critical as it is a quality indicator that impacts online course retention or attrition as well as students’ decision to continue with a particular institution (DeShields, Kara & Kaynak, 2005; Harrison, Gemmell, & Reed, 2014; Keller, 2010).
Building on Herzberg’s et al. (1959) two-factor workplace-based theory, Katt and Condly (2009) attempted to determine what factors motivated or demotivated students in the classroom and whether similar patterns existed between the workplace and the classroom. Katt and Condly’s (2009) study results resonated with Herzberg’s theory regarding hygienic factors or dissatisfiers (e.g., poor class management and unfair class policies) affecting students’ dissatisfaction. Similarly, students’ satisfiers (e.g., professor care and achievement) also aligned with the theory for factors affecting students’ satisfaction in their classes. Katt and Condly concluded that student motivation can be influenced by factors stimulating their psychological growth to include recognizing students’ success and giving them challenging but achievable assignments. Thus, the researchers confirmed Herzberg’s et al. two-factor theory that satisfiers and dissatisfiers operate on two different continua. Conventional research tends to view satisfaction and dissatisfaction as opposites ends of one continuum which is not necessarily the case. As such, it is imperative that online practitioners examine student satisfaction and dissatisfaction separately because the absence of one does not automatically result in the presence of the other. The dissertation findings that will be discussed in the current presentation, used Herzberg’s et al. two-factor theory as a lens to understand how students’ perceived course satisfaction and dissatisfaction influence their performance in online courses.
In addition, Keller (2010) supported Herzberg’s et al. (1959) workplace-based theory in acknowledging the intrinsic and extrinsic nature of the human being in using the ARCS model (Attention, Relevance, Confidence and Satisfaction) for exploring how online instruction can be more motivationally appealing. Keller pointed out that when attention, relevance, and confidence are addressed for online learners, they will be intrinsically satisfied. In contrast, if these first three factors of the ARCS model are left unattended, students will become demotivated. The latter responses reflect the innate intrinsic and extrinsic tendencies of the human being as theorized by Herzberg et al. (1959). Moreover, “satisfaction”, the fourth category in the ARCS model, can be achieved by specifically managing students’ intrinsic and extrinsic learning outcomes (Keller & Suzuki, 2004). For example, students’ feelings of intrinsic satisfaction will depend on their instructors recognizing them personally and providing opportunities for application of skills and knowledge learned (Keller, 2008). In like manner, students will also perceive their coursework to be adequate and consistent with course learning outcomes and fair grading of their course work.
Excerpt of Research Methods and Findings
The presenters will report findings from a dissertation study that revealed the top 10 satisfying and dissatisfying factors that online students perceive influenced their course performance. The students were 624 master’s students from a large Midwestern university who had taken at least one online course. The online course that the students reported on were not necessarily master’s-level courses.
Specifically, the presenters will highlight the online students’ responses to two dissertation survey questions (2 and 6). It is important to note that survey questions 1 and 5 asked students to share satisfying and dissatisfying experiences in their online courses (respectively). Survey question 2 asked students to indicate whether or not the satisfying experience (that they reported for question 1) affected the way they performed in the online course. They were also prompted to provide examples if they indicated yes. If they answered no to question 2, they were prompted to explain why. Similarly, question 6 asked students to indicate whether or not the dissatisfying experience (that they reported for question 5) influenced the way they performed in the online course. They were also prompted to provide examples is they indicated yes. If they indicated no, they were asked to explain why.
The students’ qualitative responses to the two survey questions were categorized using the content analysis technique, and frequencies were generated for each category. This presentation will highlight the top 10 satisfying and dissatisfying factors that students reported influenced their performance and relate them to established research such as Herzberg’s et al. (1959) two-factor theory of satisfaction and dissatisfaction and Kellers ARCS (Attention, Relevance, Confidence and Satisfaction) model.
For example, the top two factor that student indicated influence their performance was instructor feedback, which is the presence or absence of constructive criticism from an instructor that is related to students’ coursework. An example of students’ responses to survey question 1 is:
When our professor takes time to grade and gives us specific feedback on assignments instead of just a grade without feedback. We just did an extensive research paper and the professor took the time to make specific remarks on the paper and cited various examples. This made me feel like the class is genuine and worthwhile.
An example of a student’s response to survey question 2 (follow-up to question 1) regarding the influence of the satisfying experience on the student course performance is:
“I felt the need to work harder and to make sure to be more detail oriented”
The aforementioned quotes show the influence of instructor feedback on online students’ course performance. This finding is in line with that of Chyung and Vachom’s (2005) study. They found that personal feedback from the instructor was number 7 among the top 17 satisfying experiences that students reported.
During the presentation, the presenters will do the following:
- Reveal the top 10 satisfying and dissatisfying experiences that online students perceive influence their course performance. Direct quotes from students will be highlighted. Also, relevant theories (e.g. Herzberg et al. 1959 two-factor theory and ARCS model) will be discussed in relation to the findings.
- Recommend instructional strategies that could potentially improve online students’ course experience and performance.
- Discuss implications for future research.
- Offer opportunities for participants to interact, ask questions, or share insights throughout the presentation.
The presenters will ask engaging questions throughout the presentation (e.g. Have you ever felt satisfied or dissatisfied in an online/blended course? How did your feelings affect your performance in the course?). The presenters will also provide opportunities for audience interaction. For example, using the ‘Think-Pair-Share’ technique, participants will be asked to share relevant instructional strategies that could lead to satisfying online learning experiences and potentially improve online students’ performance. The audience will also receive the opportunity to ask questions and share additional insights.
In sum, the presenters will reveal the top satisfying and dissatisfying factors that online students perceive influenced their online course performance. They will also explain how these factors relate to established research. This presentation will inform strategies that online practitioners can use to improve students’ experiences in the online learning environment which could lead to improved course performance.
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Chyung, S. Y. (2005). Analyze motivation-hygiene factors to improve satisfaction levels of your online training program. Retrieved from http://www.achc.org.co/hospital360/contextos/Institucional/Crisis_Profesionales/Factores_de_motivacion.pdf
Chyung, S.Y., & Vachon, M. (2005). An investigation of the profiles of satisfying and dissatisfying factors in e-learning. Performance Improvement Quarterly, 18(2), 97–113
Clinefelter, D. L., & Aslanian, C. B. (2016). Online college students 2016: A comprehensive data on demands and preferences. Louisville: The Learning House, Inc.
Danielson, C. (1998). Is satisfying college students the same as decreasing their dissatisfaction? A paper presented at the annual forum of the Association for Institution and Research. Retrieved from http://www.eric.ed.gov/PDFS/ED422812.pdf
DeShields, O.W., Kara, A., & Kaynak, E. (2005). Determinants of business student satisfaction and retention in higher education: Applying Herzberg’s two-factor theory, The International Journal of Educational Management,19(2), 128-39.
Harrison, R., Gemmell, I., & Reed, K., (2014). Student Satisfaction with a web-based dissertation course: Findings from an international distance learning master’s programme in public health, The International Review of Research in Open and Distance Learning (15)1, 182-202.
Herzberg, F., Mausner, B., & Snyderman, B. (1959). The motivation to work. New York: Wiley.
Jacobi, L. (2016). The trifecta approach and more: Student perspectives on strategies for successful online lectures. Inquiry in Education, 8(2) article 3, 1-15. Retrieved from http://digitalcommons.nl.edu/cgi/viewcontent.cgi?article=1132&context=ie.
Katt, J., & Condly, S. (2009). A preliminary study of classroom motivators and de-motivators from a motivation-hygiene perspective. Communication Education, 58(2), 213-234.
Keller, J. M. & Suzuki, K. (2004). Learner motivation and e-learning design: A multinationally validated process, Journal of Educational Media 29(3), 229–39.
Keller, J.M. (2008). First principles of motivation to learn and e3-learning. Distance Education, 29(2), 175-185.
Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach. New York: Springer.
Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in learning technology, 23(1), 26507
Milman, B. M., & Wessmiller, J. (2016). Ends and means: Motivating the online learner using Keller’s ARCS model. Distance Learning, 13(2), 67-71.
Quality Matters. (2017). Course design rubric standards. Retrieved from https://www.qualitymatters.org/qa-resources/rubric-standards/higher-ed-rubric
Shattuck, K. (2015). Research inputs and outputs of quality matters: Update to 2012 and 2014 versions of what we’re learning from QM-focused research. Quality Matters: Annapolis. Retrieved from https://www.qualitymatters.org/sites/default/files/research-docs-pdfs/QM-Research-What-We're-Learning-2015update.pdf