Achievement and motivation

Learner motivation has been one of the central constructs with a perennial scholarly interest in the Educational Psychology literature (Wentzel & Miele, 2016). This is not surprising considering the role that academic motivation plays in giving rise to learning engagement and fostering academic competence (Elliot et al., 2017). Furthermore, the malleability of motivation through theory-based interventions as well as systematically designed modifications of contextual factors (e.g. school climate, instructional practice) has rendered student motivation as a psychological construct that educational psychologists and educators alike would direct their attention to and spend their resources on (Liem & McInerney, 2020). Originating from the Latin word “movere” which means “to move,” many scholars have defined motivation to psychological (and physiological) forces that energise, direct, and sustain students’ behaviours towards the attainment of goals (Schunk et al., 2014), while some others simply refer it to the psychology of wanting (Baumeister, 2016). All of them, however, agree that motivated students are more likely to engage in their learning, persist in the face of challenges, spend longer time on-task, and put forth more effort expenditure than their less motivated peers (Elliot et al., 2017; Schunk et al., 2014; Wentzel & Miele, 2016). The present issue comprises seven empirical papers that, I believe, significantly contribute to the academic motivation literature and advance our understanding of the role of motivation in empowering learning and building competence. Based on a social-cognitive theory (Bandura, 1986), the preponderance of these studies represented motivation as sociocontextually shaped motivational beliefs including achievement goals, self-efficacy or selfconcept, and school valuing, among others. Achievement goal theory has been one of the “big” theories of motivation that has evolved and continued to grow in the past four decades (Elliot & Hulleman, 2017; Liem & McInerney, 2018). However, the theory is not free from debates, one of which is with regard to the dimensionality of its key constructs. This was a reason why Strunk et al. (2021) focussed their attention on mastery-avoidance goals. They conducted a metaanalytic onfirmatory factor analyses (MA-CFA) on responses to two widely used achievement goal measures: the Achievement Goal Questionnaire-Revised (AGQ-R) and the Patterns of Adaptive Learning Scales (PALS). Their finding showed that CFA models fit the data better without mastery-avoidance goals. Rather controversially, Strunk et al. concluded by calling for researchers to consider excluding mastery-avoidance goals in their research. Considering popular day-to-day expressions (e.g. “Thank God It’s Friday,” “Motivation Monday”), Sotak et al. (2021) examined changes in the weekly patterns of undegraduates’ motivation. To this end, they collected data over 56 consecutive days to allow them to detect motivational cycles and fit trigonometric functions to the data via spectral analysis. Their findings indicated that motivation followed a cosine function with a weekly cycle, in which motivation began to increase on Sunday and was relatively high early-week, dropped on Friday, and was lowest on Saturday. Not only do these findings advance our