Towards a deeper understanding of believing and achieving in educational settings : reciprocity and calibration of self-efficacy and academic performance
Background: Academic self-efficacy, and its relationship with academic outcomes, has been the subject of extensive research and many systematic reviews over the past several decades. These analyses consistently point to self-efficacy as one of the strongest positive correlates of academic performance, reflecting the traditional focus on the benefits of a strong sense of self-efficacy on educational behaviours and performance. However, questions about the nature of the relationship between self-efficacy and performance remain, including the issue of reciprocity in the relationship and the relative impact of performance on subsequent self-efficacy beliefs, and the issue of how accurate people's self-efficacy beliefs are and how this influences performance. Research questions: In this context, the overall aim of the present thesis is to explore the complexities in the relationship between self-efficacy and academic performance, moving beyond the notion of believe and you will achieve‚ÄövÑvp. To this end, this thesis addresses the following research questions. Firstly, what is the impact of academic performance on self-efficacy and vice versa: is the relationship between the two reciprocal, or is one variable a stronger antecedent of the other? And is the relationship moderated by other participant and methodological variables? Secondly, how accurate are students' self-efficacy beliefs and how does this accuracy (or inaccuracy) predict future academic performance outcomes? And is it possible to identify person and environmental characteristics which differentiate miscalibrated students from their peers? Studies: Studies 1 and 2 addressed the question of reciprocity in the self-efficacy/ performance relationship by means of a systematic review with meta-analysis of panel data. Pooled correlations were fit to a cross-lagged path model which provided support for reciprocal effects. Moderator analyses indicated that the strength of cross-lagged effects varied as a function of participant age, the lag time between measurements, the degree of match between self-efficacy and performance operationalisations, and the type of scale used to measure self-efficacy. Overall, reciprocity held in most circumstances, providing support for reciprocal determinism as per self-efficacy theory, and highlighting the positive influence of self-efficacy on academic performance and vice versa. A key finding was that reciprocity was evident in adult samples, but not in children (in whom performance predicted self-efficacy, but not vice versa). Also, the order of measurement of the variables at each measurement point moderated the reciprocal relationship. When performance was measured prior to self-efficacy at time 1, self-efficacy was a stronger predictor of performance at time 2 than the reverse. When self-efficacy was measured first at time 1, performance was a stronger predictor of self-efficacy at time 2 than the reverse. Study 3 focused on calibration of self-efficacy and academic performance in university students, operationalised as the deviation of self-efficacy beliefs from performance outcomes measured on the same scale. Participants' self-efficacy beliefs with regard to their performance could be accurate (calibrated), or inaccurate (miscalibrated), and miscalibration was further categorised as either over- or under-efficaciousness. Miscalibration was prevalent, with under-efficaciousness evident at task-level (written assignments and exams) and over-efficaciousness pronounced at subject-level (overall grades). Low achievers tended to be over-efficacious, while the reverse was true for high achievers. The strongest subsequent performance outcomes on similar tasks were predicted by under-efficaciousness, rather than accuracy or over-efficaciousness. These findings suggest that over-efficacious students may be at risk of negative academic outcomes. Findings were more consistent with discrepancy-reduction processes than with the idea of self-efficacy as a self-fulfilling prophecy. Study 4 investigated whether it is possible to identify over-efficacious students (identified in study 3 as being at risk of poor academic performance) based on personal and environmental variables. Self-efficacy calibration was assessed at multiple time points over an academic semester. At different points in the semester, over-efficacious students tended to be younger, lower in cognitive ability and agreeabless, higher in self-esteem, and from higher SES backgrounds. Over-efficaciousness may, thus, be maintained by both cognitive and motivated processes. These findings may be of benefit in targeting interventions to enhance students' calibration levels, and they may also inform future research and theory development. Conclusions: Overall, the findings of this thesis present a picture of the relationship between self-efficacy and academic performance as complex and nuanced. Reciprocity between the two variables is evident, but varies in magnitude and directional strength with different participants and research approaches. Calibration in adult learners appears to be poor overall, and the direction of miscalibration predicts future performance. Both personal and contextual variables differentiate over-efficacious students from their peers. Future research and theory development, and applications of self-efficacy theory to learning environments, would benefit from increased focus on the issues of reciprocity and calibration, which point to the need for updated conceptualisations of adult learners' self-efficacy beliefs, as well as to the importance of regular cycles of performance and accurate feedback for students of all ages.
Copyright 2017 the author Chapter 2 appears to be the equivalent of a pre-print version of an article published as: Talsma, K. L., Schuz, B., Schwarzer, R., Norris, K., 2018. I believe, therefore I achieve (and vice versa): A meta-analytic cross-lagged panel analysis of self-efficacy and academic performance, Learning and individual differences, 61, 136-160