A Longitudinal Analysis of High School Students’ Profiles of Academic Buoyancy in Math and English

• In Event: Considering the Whole Student: The Use of Person-Centered Approaches to Characterize and Study Motivation

Abstract

Building on research on academic buoyancy, the purpose of this presentation is twofold. First, we examine how profiles of academic buoyancy change over the course of an academic year in the domains of English and mathematics. Second, we investigate how these profiles ultimately impact students’ achievement in those domains.

The construct of academic buoyancy emerges from research on academic resilience, and describes those students who, despite setbacks, manage to succeed academically. In contrast to academic resilience research, which examines the acute and chronic adversities experienced by a small cohort of students (Luthar, 2003), research on academic buoyancy focuses instead on the everyday academic struggles and challenges that most students confront in school, such as dealing with competing deadlines and exam pressures (Martin, 2007). Academic buoyancy is most commonly operationalized in terms of motivational, affective, and cognitive variables. More specifically, Martin (2007) suggests that students who are capable and mastery-oriented; who are planful and use appropriate cognitive and metacognitive strategies; and who have low levels of failure avoidance and anxiety are most likely to be academically buoyant.

Participants included 153 9th and 10th grade female high school students attending an urban, private, high school in the metropolitan New York City area. Students completed a web-based survey four times during the 2009-2010 academic year. Measures were adapted from established instruments (e.g., PALS, MSLQ, see Zusho & Barnett, 2011) and included indices of motivation (i.e., mastery goals, task-value, expectancy-for success, performance-avoidance goals), affect (i.e., anxiety), and self-regulation (i.e., rehearsal, organization, metacognitive self-regulation, academic procrastination). At each administration, students were asked to complete the measures twice, once in reference to their English class and once in reference to their mathematics class.

Profiles were created using a two-step cluster analytic procedure. The aforementioned nine variables were first submitted to Ward’s method separately by wave and by subject domain. K-Means was then used to confirm the number of clusters. In general, the same four-group cluster solution was found across waves and subject domain, with the exception of the final wave, where a three-group cluster solution emerged. Overall, the groups varied in terms of their levels of academic buoyancy: (1) one group, which could be considered to be the academically buoyant, had high levels of adaptive cognitive and motivational scales (i.e., cognitive and metacognitive strategy-use, mastery goals, expectancy-for-success, task-value) and low levels of maladaptive scales (i.e., performance-avoidance, anxiety, and procrastination); (2) another group had moderate levels of adaptive motivation and cognitive engagement and low levels of maladaptive motivation, procrastination, and affect; (3) another group had moderate levels of both adaptive and maladaptive scales; (4) finally, one group had low levels of adaptive scales, and high levels of maladaptive scales. Follow up ANOVAs further revealed a main effect of the cluster solutions on grades at Waves 2, 3, and 4. Overall, students considered to be the most academically buoyant obtained the highest grades. Taken together, the findings highlight the possible advantages of using person-centered analyses to investigate the additive impact of motivational, cognitive, and affective variables on achievement.

Authors

• Peggy Ann Barnett, Fordham University

• Karen Elizabeth Clayton, Touro College of Osteopathic Medicine

• Akane Zusho, Fordham University