A motivation perspective on achievement appraisals, emotions, and performance in an online learning environment
Introduction
Life course transitions such as moving to another city, starting a new job, getting married, having a first child, retiring, and age-onset disabilities entail motivation challenges and setbacks. Many are minor, several occur concurrently, and some are substantial and precipitous (e.g., Chipperfield et al., 2019; Hamm, Heckhausen, Shane, Infurna, & Lachman, 2019; Hamm, Heckhausen, Shane, & Lachman, 2020; Hamm, Perry et al., 2020). School-to-college transitions typify one salient shift that creates formidable hurdles for students due to unaccustomed demands comprised of increased personal responsibility, frequent academic failure, new financial needs, unstable social networks, and critical career choices (Perry, 2003; Perry, Hall, & Ruthig, 2005; Perry, Hladkyj et al., 2005). Compounding these complexities are worldwide initiatives by postsecondary institutions to convert academic programs to remote delivery platforms in response to the COVID-19 pandemic. Though the debate is ongoing, online courses appear to have higher attrition rates than conventional face-to-face courses (e.g., Cochran, Campbell, Baker, & Leeds, 2014; Lee & Choi, 2011), exceeding 90% for MOOCs in some cases (Daniels et al., 2015; Onah, Sinclair, & Boyatt, 2014).
Our study draws on Control-value theory (CVT) to identify theory-derived patterns of cognitions and emotions students exhibit in online learning environments during the transition to college. CVT focuses on the interplay of academic control and value appraisals and emotions that influence motivation and performance in diverse achievement settings (Pekrun, 2006, 2019, Pekrun & Perry, 2014). CVT aligns with expectancy-value theory traditions that hypothesized cognitive and affective processes as precursors to motivation and performance over the decades (cf., Eccles & Wigfield, 2020; Gendolla & Wright, 2016, 2018; Koenka, 2020; Weiner, 2010). Within this context, we assessed the co-occurrence of CVT-related appraisals (control, value) and emotions (boredom, anxiety, enjoyment) to form multifaceted motivation profiles that predict achievement perceptions and performance in a two-semester online learning course.
Section snippets
Control-value theory and achievement appraisals and emotions
CVT posits that perceived control and value appraisals are linked to emotions that contribute to motivation and performance in achievement settings (Pekrun, 2006, 2019; Pekrun & Perry, 2013, 2014; Pekrun, Goetz, Titz, & Perry, 2002; Pekrun, Frenzel, Goetz, & Perry, 2007). Control beliefs arise from individuals’ subjective estimates concerning the degree to which they can influence or predict outcomes and events throughout the lifespan (e.g., Chipperfield et al., 2016; Morling & Evered, 2006;
Cognitive appraisals and emotions
Students can experience different cognitions and emotions in achievement settings that are interwoven closely in time as they complete their academic tasks. Robinson et al. (2017) provide some support for this using cluster analysis whereby affective profiles related to engagement and performance, though they did not include control and value appraisals in their analysis. Although CVT posits a process whereby appraisals are antecedent to emotion, it specifies that cognitive appraisals do not
Participants and procedure
Participants (N = 327) were recruited from a two-semester, online introductory psychology course at a large mid-western research-1 Canadian university and received course credit for participation. Most were native English speakers (82%), between the ages of 17 and 20 (80%), in their first year of university (67%), and female (60%). The study design involved a four-phase protocol that spanned the two semesters.1 In the third
Rationale for analyses
We employed Latent Profile Analysis (LPA) to identify student motivation profiles at the beginning of Semester 1 in a two-semester, introductory psychology course. LPA is a type of mixture modelling that estimates the optimal number of latent (unobserved) subgroups based on responses to multiple indicator variables (Muthén & Muthén, 2007; Nylund, Asparouhov, & Muthén, 2007). As a person-centered approach, LPA identifies subgroups of individuals who are similar to each other on the indicator
Discussion
School-to-college transitions entail unexpected academic and personal setbacks marked by unfamiliar pedagogical practices and newly emerging online learning environments. Our study documents real-time snapshots of multifaceted motivation profiles formed by patterns of cognitions and emotions consistent with CVT. These profiles predicted achievement perceptions (perceived success, expected performance) and performance on six tests in a two-semester online course. The three latent profiles
Declaration of Competing Interest
The authors declare no competing interests.
Acknowledgments
This study was supported by research grants to: Raymond P. Perry from the Social Sciences and Humanities Research Council of Canada (Insight #435-2017-0804) and Royal Society of Canada:, Judith G. Chipperfield from the Social Sciences and Humanities Research Council of Canada (Insight #410-2016-0970); and postdoctoral fellowships to Jeremy M. Hamm from the Social Sciences and Humanities Research Council of Canada, the Canadian Institutes of Health Research, and the Fonds de recherche Santé.
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