Factors Affecting Academic Self-Efficacy and Academic Self-handicapping Behaviors in Doctoral Students

Aim/Purpose: The purpose of this study was to determine to which degree age, race, and Socioeconomic Status (SES) influence academic self-efficacy and academic self-handicapping behaviors in doctoral. Background: Across all disciplines, more than 50% of students who begin a doctoral program do not persist to graduation. Although the issue of student retention and psychological factors have been proffered, much attention has not been placed on this relationship. Past researchers have focused primarily on academic-related, student-related, institutional, and financial factors. Methodology: A quantitative study was conducted, using the exploratory factor analysis. One-hundred and sixty-five participants, of legal age, who had completed at least one semester of a doctoral program, were involved in this current study. Contribution: The findings from this study increase the empirical evidence reported on the scarce literature on student retention and psychological factors in doctoral students. Findings: The factor analysis test did not show a statistically significance between the dependent variables -academic self-efficacy and academic self-handicapping- and any of the independent variables – gender, race, age, and socioeconomic status. Recommendations for Practitioners: Higher education leaders should make a proactive effort to understand the issue of student retention from a psychological perspective and make implementations to reduce these problems for doctoral students. Recommendation for Researchers: Future researchers should explore in-depth psychological variables that contribute to the high attrition rates in doctoral students. Impact on Society: A better understanding of the factors affecting the cognitive strategies and self-constructs of doctoral students could provide those working in academia with a better understanding of the problem and increase awareness at a societal level. Future Research: It is recommended that future research be carried using a mixed methods approach to offset the limitations found in the quantitative strand and gain thick, rich data from the qualitative strand.