Aptitude, Motivation, and Self-Regulation as Predictors of Achievement among Developmental College Students
Notice bibliographique
Résumé
Abstract The primary purpose of the present study was to examine the validity generalization of aptitude as a predictor of achievement for developmental college students. A second purpose was to investigate students' motivational beliefs and perceived self-regulated learning skills as predictors of achievement. Results indicated a weak correlation between aptitude and achievement, accounting for only .52% of the variance in achievement. As such, developmental educators may be using a criterion for admission that accounts for less than 1% of the variance in achievement. Together, aptitude, self-regulated learning, and motivational beliefs explained approximately 15.2% of the variance in achievement. Implications for education are discussed. An estimated 650,000 students, or approximately one-third of the freshmen entering U.S. colleges and universities each year, are required to enroll in at least one developmental course in Reading, English, or Mathematics designed to prepare students to cope with college-level coursework (Boylan, Bonham, & Bliss, 1994). Measures of students' aptitude (ACT or SAT scores), their previous performance (high school grade point averages or class rank), or a combination of these factors traditionally have served as the basis for making decisions concerning admission and/or placement in developmental courses. Numerous studies have reported correlations between aptitude and academic performance in college coursework. Various researchers have studied the predictive validity of standardized measures of aptitude such as the ACT and SAT in content-area courses (Stallworth-Clark, Scott, & Nist, 1996), in undergraduate pre-service teachers' programs (Neal, Schaer, & Ley, 1990), and among female intercollegiate student-athletes (Petrie & Stoever, 1997). In these studies, SAT and ACT scores are predictive of course grades and semester grade-point-averages (GPAs). Harackiewicz, Barron, Tauer, and Elliot (2002) also reported that both aptitude and high school GPA were significant predictors of academic performance in college. The predictive value of aptitude with regard to college achievement varies across studies. For example, Cote and Levine (2000) reported that IQ accounted for only 0 - 4% of the variance in academic achievement among Canadian university students. Likewise, Wolfe and Johnson (1995) found that prior performance (high school GPA) accounted for 19% of the variance in GPA among students enrolled in a college introductory psychology course, a motivational variable accounted for 9% of the variance while SAT scores accounted for only 5% of the variance. Other studies reported low to moderate correlations between measures of aptitude and academic performance. Britton and Tesser (1991) reported low correlations (r = .20) between college students' SAT scores and their cumulative GPA during their first two years of college. Further, Wentzel (1991) reported that student GPAs and SAT scores were only moderately correlated (r = .42) and that many of the students in the top 12% of their high school class did not score in the top 12% on the SAT. Moreover, Meeker, Fox, and Whitley (1994) tested the predictive value of 26 variables, including SAT scores, for college students' GPA in psychology. SAT scores (aptitude) were not significant predictors of GPA in psychology (the students' major), with Math SAT scores accounting for only 3.6% of the variance. In another study, measures of aptitude were found to be either unrelated or negatively related to achievement in college students, while motivation appeared to be more predictive of achievement (Cote & Levine, 2000). With regard to developmental college students, a second potential limitation of prior research on the predictive validity of aptitude is the nature of the sample. Because these studies have been conducted with the general college student population, the generalizability of findings to developmental college student populations may be questionable. …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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