Growth goal setting in high school: A large-scale study of perceived instructional support, personal background attributes, and engagement outcomes.

Abstract

The present investigation examined the role of teachers' instructional support (student reports of relevance, organization and clarity, feedback-feedforward) in predicting students' growth goal setting and, in turn, the roles of instructional support and growth goal setting in predicting students' academic engagement (perseverance, aspirations, school attendance, homework behavior). Also examined was the question of whether the relationship between students' background attributes and engagement is moderated by their growth goal setting (e.g., whether growth goal setting attenuates negative effects of low socioeconomic status). The sample comprised N = 61,879 students in grades 7-10 from schools across New South Wales, Australia. The results of structural equation modeling showed that perceived instructional relevance and feedback-feedforward from teachers positively predicted students' growth goal setting; that growth goal setting predicted gains in students' perseverance, aspirations, and homework behavior; and that growth goal setting significantly mediated the relationship between perceived instructional support and engagement. Additionally, growth goal setting appeared to significantly bolster some outcomes for low achieving students and students from low socioeconomic backgrounds. These findings add to the growing body of literature about the positive role of growth goal setting in students' outcomes and provide direction for educational practice. Educational Impact and Implications StatementThis study investigated growth goal setting among a large statewide sample of high school students. Growth goal setting refers to the pursuit of specific, challenging, and competitively self-referenced targets that match or exceed a previous best effort or performance. Findings demonstrated that perceived instructional support (student reports of teachers' feedback-feedforward and instructional relevance) was associated with students' growth goal setting and that students' growth goal setting was associated with significant gains in their academic engagement (perseverance, aspirations, and homework behavior). Importantly also, growth goal setting reduced the potential negative effects of low socioeconomic status and low prior achievement on some engagement outcomes. These findings provide important direction for enhancing students' growth goal setting and engagement. Accordingly, practical suggestions for enhancing instructional support and growth goal setting are provided.

University Students’ Motivation and Engagement During the COVID-19 Pandemic: The Roles of Lockdown, Isolation, and Remote and Hybrid Learning

“…To reduce fear of failure, educators can make it clear to students that mistakes, poor performance, and failure provide useful information on how to improve and do not imply a lack of self-worth (Covington, 2000). Educators might also look to shape students' perceptions of success so that success is seen more in terms of personal improvement than outperforming others (Martin, Burns, et al, 2021). By instilling more positive constructions of failure and poor performance, and also framing success in more achievable ways, students are less inclined towards problematic failure dynamics in the forms of self-handicapping and disengagement (Martin & Marsh, 2003).…”

Personal agency among students from low socio-economic backgrounds: An examination of student profiles, perceived teaching support, and achievement

“…The five intra-and inter-personal agency factors are predictors of students' academic development (e.g., Bostwick et al, 2022), and are particularly relevant for students from low-SES backgrounds who may not have the contextual privileges or supports that students from other backgrounds often have (Kraus et al, 2012;Sirin, 2005). Indeed, students from low-SES backgrounds often report lower levels of the adaptive factors and higher levels of conduct problems (King et al, 2022;Martin et al, 2022)-often due to their experiences in a contextual environment that is less well resourced and supportive. However, this is not necessarily the case for all subpopulations of students from low-SES backgrounds, which is important to examine.…”

“…Although personal agency beliefs and behaviors can combine in various patterns (or profiles) for different types of students (Burns et al, 2022), only limited research has considered these or related agency factors by way of profiles. The bulk of past research examining these or related agency factors among students from low-SES backgrounds has involved variable-centered examinations (e.g., King et al, 2022;Martin et al, 2022). Variable-centered analyses (e.g., by way of structural equation modelling process models; e.g., Martin et al, 2022) focus on identifying how variables are interrelated among a population as a whole and have revealed, for example, that school belonging is an important personal academic agency factor associated with positive outcomes among students from low-SES backgrounds (Bostwick et al, 2022).…”

“…Students from low-SES backgrounds generally report lower levels of personal agency, and academic achievement, than students from mid-to-high SES backgrounds (King et al, 2022;Martin et al, 2022). However, students from low-SES backgrounds are not a homogenous group-there are also many who demonstrate academic outcomes as strong as students from mid-to-high SES backgrounds (Cutmore et al, 2018).…”

“…However, students from low-SES backgrounds are not a homogenous group-there are also many who demonstrate academic outcomes as strong as students from mid-to-high SES backgrounds (Cutmore et al, 2018). Prior research examining personal agency beliefs and behaviors among students from low-SES backgrounds has largely assumed subpopulation homogeneity, testing how these factors are associated with other variables in the sample as a whole (i.e., variable-centered examinations; e.g., King et al, 2022;Martin et al, 2022). Another approach is to allow for subpopulation heterogeneity by considering personal agency factors not as separate albeit associated predictor variables, but as indicator sets with potentially different combinations for various types of students-that is via student profiles (i.e., personcentered examinations).…”