Understanding Satisfaction and Continuing Motivation in an Online Course:

1. Understanding Satisfaction and Continuing Motivation in an Online Course: An Extension of Social Cognitive, Control-Value Theory Anthony R. Artino, Jr. Department of Educational Psychology, Neag School of Education, University of Connecticut UCONN UCONN Abstract Method & Results Using social cognitive, control-value theory as a framework, this study examined how students’ cognitive appraisals (task value and self-efficacy) and negative achievement emotions (boredom and frustration) relate to their overall satisfaction with an online course and their continuing motivation to enroll in future courses. Service academy undergraduates (N = 481) completed a survey that assessed these constructs. Structural equation modeling revealed that task value, self-efficacy, boredom, and frustration were all statistically significant predictors of satisfaction, accounting for 64% of its variance. Task value and self-efficacy had direct effects on satisfaction, as well as indirect effects through boredom and frustration. Moreover, self-efficacy and boredom had both direct and indirect effects on continuing motivation; whereas task value and frustration had only indirect effects through satisfaction. The final model accounted for 41% of the variance in continuing motivation. Instructional implications are discussed. Participants A convenience sample of 481 undergraduates (sophomores and juniors) from a U.S. service academy; 398 men (83%) and 83 women (17%). Mean age 20.5 years (SD = 1.0; range 19-24). Instructional Materials A self-paced online course composed of four, 40-minute lessons. Each lesson included text, graphics, and video, as well as several interactive activities. • Instrumentation • Participants completed a 50-item survey; variables used in this study included the following: • Task Value: the extent to which students found the course interesting, useful, and important. • Self-Efficacy: students’ confidence in their ability to learn in a self-paced online format. • Boredom: students’ course-related boredom. • Frustration: students’ course-related frustration, annoyance, and irritation. • Satisfaction: students’ overall satisfaction with the online course. • Continuing Motivation: “Would you choose to enroll in another self-paced online course in the future? Please answer this question as if the choice were completely up to you.” Table 1 Descriptive Statistics, Cronbach’s Alphas, and Pearson Correlations for the Measured Variables (N = 471) Table 2 Effects of Cognitive Appraisals (Task Value and Self-Efficacy) and Negative Achievement Emotions (Boredom and Frustration) on Satisfaction (R2 = .64) and Continuing Motivation (R2 = .41) Background • Recent advances in Internet-based technologies have greatly expanded opportunities to learn and teach at a distance (Dabbagh & Bannan-Ritland, 2005; Hill et al., 2004). • Traditionally, online learning research has been dominated by comparison studies; that is, studies that compare online learning with that of conventional classroom instruction. • With few exceptions, results suggest that online learning can be as effective as traditional classroom instruction (e.g., Bernard et al., 2004; Sitzmann et al., 2006; Zhao et al., 2005). • That said, very little is known about the thoughts, feelings, and actions of students who succeed in highly autonomous online learning situations (Bernard et al., 2004). • Accordingly, several scholars (e.g., Bernard et al., 2004; Gibson, 2003; Gunawardena & McIsaac, 2004; Perraton, 2000; Saba, 2000) have called for a paradigm shift in online learning research, recommending a focus on within-group differences among learners. • Theoretical Framework • Using social cognitive, control-value theory (Pekrun, 2000, 2006) as a framework, this study focuses on the complex interplay among emotion, cognition, and motivation (Linnenbrink & Pintrich, 2004), in an effort to better understand how students function in online situations. • Control-value theory outlines hypothesized linkages between students’ cognitive appraisals (e.g., task value and self-efficacy), achievement emotions (e.g., enjoyment, hope, anxiety), and, ultimately, their learning, performance, and continuing motivation (Maehr, 1976). Note. All subscale variables were measured on a 7-point Likert-type agreement scale. Continuing motivation was measured on a 6-point Likert-type response scale ranging from 1 (definitely will not enroll) to 6 (definitely will enroll). Listwise deletion of cases with missing data was used for all statistical analyses. There were 471 cases with no missing values on the 24 survey items used in this study. All correlations are significant at the p < .001 level. Boredom R2 = .23 -.41 Note. Effects are reported as standardized regression coefficients. Total effects = direct effects + indirect effects. Task Value -.15 -.17 -.23 db 1 ds .50 ContinuingMotivationR2 = .41 Satisfaction R2 = .64 1 dc .41 .35 1 .57 Self-Efficacy .16 .12 df -.20 1 -.37 Purpose of the Study Frustration R2 = .21 -.18 Figure 1. Structural equation model of the linear relationships among students’ cognitive appraisals (task value and self-efficacy), negative achievement emotions (boredom and frustration), satisfaction with a self-paced online course, and continuing motivation to enroll in future online courses. Only latent variables, disturbances, and the continuing motivation variable are presented. All paths are significant at the p < .001 level. • The present study answers recent calls to move beyond between-group studies and to focus on the attributes, skills, behaviors, and attitudes that contribute to success in online learning environments (Bernard et al., 2004; Fletcher et al., 2007; Gunawardena & McIsaac, 2004). • Research Question How do students’ cognitive appraisals (task value and self-efficacy) and negative achievement emotions (boredom and frustration) relate to their overall satisfaction with a self-paced online course and their continuing motivation to enroll in future online courses? • Satisfaction was chosen as a key outcome because past research has shown it to be a powerful predictor of course attrition (Dabbagh & Bannan-Ritland, 2005; Moore & Kearsley, 2005). • Moreover, several studies have found satisfaction to be an important predictor of students’ continuing motivation to enroll in future online courses (Chiu et al., 2007; Roca et al., 2006). Discussion & Implications • Taken together, findings from this study support and extend Pekrun’s (2000, 2006) social cognitive, control-value theory. • In particular, results suggest that students who believed the online course was interesting, important, and useful (greater task value) and those who were confident they could learn the material presented online (greater self-efficacy) also reported less boredom and frustration, greater satisfaction, and greater likelihood of enrolling in future online courses. • Due to the correlational nature of this study, strong implications for online learning are somewhat difficult to draw. Nevertheless, results do offer online course developers and policy makers with some preliminary implications that require further empirical validation. • Preliminary Instructional Implications • Promote task value beliefs. Positively impact perceptions of task value by creating online courses that engage students in authentic learning activities (Artino & Stephens, 2006). • Promote self-efficacy for learning online. Enhance students’ self-efficacy beliefs by using prompt scaffolds that guide and encourage students to set challenging, proximal learning goals. Assess learning goals and provide timely/explicit feedback (Schunk & Ertmer, 2000). • Address boredom and frustration. Encourage adaptive outcomes by minimizing negative emotions. Do so by addressing value, efficacy, and other areas of the course where negative emotions are likely to be directed (i.e., the task and the technology; Wosnitza & Volet, 2005). Download the complete paper at www.artino.org.