Unraveling the differential effects of motivational and skills, social, and self-management measures from traditional predictors of college outcomes.

Abstract

The authors report on a large-scale study examining the effects of self-reported psychosocial factors on 1st-year college outcomes. Using a sample of 14,464 students from 48 institutions, the authors constructed hierarchical regression models to measure the predictive validity of the Student Readiness Inventory, a measure of psychosocial factors. Controlling for institutional effects and traditional predictors, the authors tested the effects of motivational and skill, social, and self-management measures on academic performance and retention. Academic Discipline was incrementally predictive of academic performance (grade-point average) and retention. Social Activity and Emotional Control also helped predict academic performance and retention, whereas Commitment to College and Social Connection offered incremental prediction of retention. This study elaborates recent meta-analytic findings (S. Robbins et al., 2004), demonstrating the salience of a subset of motivational, social, and self-management factors. Future research questions include how measures of psychosocial factors can be used to aid students, the salience of these measures over the entire college experience and for predicting job performance, and the need for testing theoretical models for explaining postsecondary educational outcomes incorporating traditional, motivational, self-management, and social engagement factors.With the scheduled revamping of the Higher Education Act, the accountability of postsecondary institutions for student academic performance and dropout has received much attention in professional reports as well as popular and research literatures (is concern that college students are ill prepared to meet the hurdles they face upon entry into college. To counter these problems, researchers have suggested the tying of federal (Stedman, 2003) and state (Hearn & Holdsworth, 2002) funding to outcomes of higher education.In practice, prediction of college success has largely centered on high-stakes testing. In many 4-year colleges and universities, there are many more applicants than spots, and high school academic performance and standardized achievement test scores are heavily weighted in admission decisions. A significant debate is occurring over how these indicators should be used. It has been argued that certain groups are disadvantaged by standardized test scores

Overview and Evaluation of a Mentorship Program for University Students With ASD

“…With regard to postsecondary education in general, psychosocial factors including social activity and social connectedness have been shown to predict academic performance and retention (Robbins, Allen, Casillas, Peterson, & Le, 2006). Thus, the psychosocial impairments faced by individuals with ASD may place them at an even greater disadvantage than their typical peers.…”

Psychological correlates of university students' academic performance: A systematic review and meta-analysis.

“…In combination with the demographic (age, sex and socioeconomic status) and traditional constructs (SAT, ACT, high school GPA & intelligence) 50 constructs were considered. Measures of socioeconomic status typically assessed income and educational levels (e.g., Robbins, Allen, Casillas, Peterson & Le, 2006) while intelligence was measured using validated assessment instruments such as the revised Wechsler Adult Intelligence Scale (Wechsler, 1981). The following data were coded from each primary article where present: Correlations were reversed scored where necessary so that higher scores represented higher levels of the defined construct.…”

Impact de la motivation et des styles d’apprentissage sur la performance scolaire d’élèves-ingénieurs

“…Cet enjeu est tel que les chercheurs tentent de définir les déterminants de la performance scolaire depuis de nombreuses années en mobilisant des approches tant sociologiques, psychologiques, cognitives, organisationnelles, culturelles qu'économiques (Coulon, 2005 ;Duru-Bellat, 1995 ;Forquin, 1982aForquin, , 1982bGaland, Neuville et Frenay, 2005 ;Michaut, 2012 ;Mouw et Khanna, 1993 ;Richardson, Abraham et Bond, 2012). L'impact de très nombreux facteurs est ainsi étudié avec, de façon non exhaustive : la scolarité et les performances antérieures (Gruel, 2002 ;Mathiasen, 1984 ;Morlaix et Suchaut, 2012), les capacités intellectuelles et cognitives (Busato, Prins, Elshout et Hamaker, 2000 ;Lounsbury, Sundstrom, Loveland et Gibson, 2003 ;Romainville, 1997), les styles d'apprentissage (Boyle, Duffy et Dunleavy, 2003 ;Busato et al, 2000 ;Chamorro-Premuzic et Furnham, 2008 ;Duff, Boyle, Dunleavy et Ferguson, 2004 ;Komarraju, Karau, Schmeck et Avdic, 2011 ;Vermunt, 2005), la personnalité (Conard, 2006 ;Farsides et Woodfield, 2003 ;O'Connor et Paunonen, 2007 ;Poropat, 2009 ;Wolfe et Johnson, 1995), la motivation (Fortier, Vallerand et Guay, 1995 ;Lieury et Fenouillet, 2013 ;Pintrich et De Groot, 1990 ;Robbins, Allen, Casillas, Peterson et Le, 2006 ;Robbins, Lauver, Le, Davis, Langley et Carlstrom, 2004), l'engagement dans les études (Pirot et De Ketele, 2000), le sentiment d'efficacité personnelle (Chemers, Hu et Garcia, 2001 ;Multon, Brown et Lent, 1991 ;…”