1 Self-Regulation and Ability Predictors of Academic Success during College Anastasia Kitsantas, Faye Huie, and Adam Winsler George Mason University

2 Abstract The purpose of this study was to examine the role of prior academic ability, self- regulatory processes, and motivational beliefs in predicting academic success over the first and second year of college with 243 incoming first-year students. Participants were asked to complete the Motivated Strategies for Learning Questionnaire, which includes learning strategies scales (e.g., metacognitive self-regulation and time management), and motivation scales (e.g., task value, self-efficacy, and test anxiety) at the end of their first semester. Cumulative high school GPA, and SAT verbal and math scores were assessed as prior ability variables, and college GPA was obtained from college records and the end of the first and second year of college. We hypothesized that prior ability, self- regulation, and motivational beliefs would each contribute unique variance in predicting later academic achievement. Partial support of the hypothesis was found. Prior ability indices were the most potent predictors of student achievement during the freshman and sophomore year with verbal SAT scores being a better predictor of college performance than math SAT scores. In regard to student self-regulated strategies and motivational beliefs, only time management strategies and self-efficacy contributed additional variance in students’ academic performance above and beyond prior ability measures. Time management strategies remained a strong predictor throughout the first two years of college studies, whereas self-efficacy significantly predicted achievement only during the first semester. The results suggest that college administrators and professors should train students to manage and plan their time efficiently. A social cognitive perspective is used to discuss the findings of the present study.

3 Introduction/Rationale Nationally, 1 in 4 college freshmen (27%) do not return for their sophomore year, and only about 50% eventually graduate Knowledge about self-regulation, motivation, and prior academic ability predictors of successful student performance and retention can help colleges implement better assessment and Design intervention strategies for students

4 Self-Regulation Behaviors, cognitions, and motivations that promote successful goal attainment (Zimmerman, 1989) a) setting goals involving specific tasks b) utilizing technique-oriented strategies Time management c) displaying high levels of self-efficacy and intrinsic interest d) self-monitoring and self-reflecting on performance outcomes Metacognitive Self-Regulation Effort Management

5 Motivation Interaction of emotions and agency beliefs that allow an individual to feel confident in his/her ability to accomplish certain tasks (Bandura, 1986) a) relevance of and personal interest to the task Task Value b) personal competency beliefs to accomplish task Self-Efficacy c) physiological or behavioral response in anticipating negative outcomes on an exam Test Anxiety

6 Hypothesis It was hypothesized that: (a) Prior academic measures high school GPA and SAT scores (b) Self-regulation metacognitive self-regulation, effort management, and time management strategies and (c) Motivational beliefs test anxiety, task value, and self-efficacy would contribute unique variance in predicting students’ GPA across the first and third year.

7 Method/Participants Sample population characteristics 63.8% female Age M = 18 (range 17-47) 4% White; 7% Black; 4% Hispanic; 15% Asian; 9% Other/Mixed 94% first semester freshman, 4% first year, and 1% sophomores 99% full-time students 79% English as native language

8 Methods/Measures 1. Motivated Strategies for Learning Questionnaire (T1, T2, T3) (MSLQ; Pintrich et al., 1991) Learning Strategies Management of Learning Resources Academic Self-Regulation Self-Efficacy 2.Prior ability and academic performance High school SAT and GPA scores College credits taken and completed College GPA at the end of their first year and third year were obtained directly from institutional records Data Collected at the end of the first semester (N = 243)

9 Results: Table 1. Motivation and Self-Regulation as a Function of Academic Performance Variable M SD End of Semester 2 Cumulative GPA End of Semester 5 Cumulative GPA Earned Credits SAT Math Score SAT Verbal Score Final Cumulative HS GPA MSLQ Learning Strategies Scales a. Metacognitive Self-Regulation b. Time and Study Environment c. Effort Management MSLQ Motivation Scales a. Test Anxiety b. Task Value c. Self-Efficacy

10 Results: Table 2. Correlations between Motivation, Self- Regulation, and Academic Performance Variable123456a6b6c7a7b 1. End of Semester 2 Cumulative GPA End of Semester 5 Cumulative GPA.91** SAT Verbal Score.45**.44** SAT Math Score.34**.35**.47** Final Cumulative HS GPA.52**.55**.33**.38**1.00 MSLQ Learning Strategy Scales 6a. Metacognitive Self-Regulation.21** b. Time and Study Environment.35**.32** *.37**1.00 6c. Effort Management.36**.32**.14*.04.30*.31**.57**1.00 MSLQ Motivation Scales 7a. Test Anxiety-.21**-.19**-.25**-.30**-.18**.20** **1.00 7b. Task Value.29**.30**.14*.08.23**.54**.38**.42** c. Self-Efficacy.29**.23**.03.25**.45**.31**.40**.15*.61**

11 Results: Table 3. Three Regressions with end of semester 2 GPA as the outcome variable VariablesR2R2 R 2 Change FSig F Change BetatP Model 1: Past Performance ** a. Cumulative High School GPA ** b. SAT Verbal ** c. SAT Math Model 2: Learning Strategies ** a. Cumulative High School GPA ** b. SAT Verbal ** c. SAT Math d. Metacognitive Self-Regulation * e. Time and Study Environment ** Model 3: Motivation ** a. Cumulative High School GPA ** b. SAT Verbal ** c. SAT Math d. Metacognitive Self-Regulation e. Time and Study Environment ** f. Test Anxiety g. Task Value h. Self-Efficacy *

12 Results: Table 4. Three Regressions with end of semester 5 GPA as the outcome variable VariablesR2R2 R 2 ChangeFSig F ChangeBetatp Model 1: Past Performance ** a. Cumulative High School GPA ** b. SAT Verbal ** c. SAT Math Model 2: Learning Strategies ** a. Cumulative High School GPA ** b. SAT Verbal ** c. SAT Math d. Metacognitive Self-Regulation e. Time and Study Environment ** Model 3: Motivation ** a. Cumulative High School GPA ** b. SAT Verbal ** c. SAT Math d. Metacognitive Self-Regulation e. Time and Study Environment ** f. Test Anxiety g. Task Value h. Self-Efficacy

13 Results Prior academic measures (high school GPA, SAT scores), time management strategies, and motivational beliefs (test anxiety, task value, and self-efficacy) contributed unique variance in predicting students’ GPA across the first and third year. The prior ability, self-regulation, and motivation variables accounted for 48% of the variance in first year GPA Time management (beta =.23) The prior ability, self-regulation, and motivation variables accounted for 46% of the variance in third year GPA Time management (beta =.21) Self-efficacy was a significant predictor of first year GPA, but not third year GPA Verbal SAT scores are a better predictor of college GPA than Math SAT scores

14 Discussion/Implications Universities need to provide students with seminars or workshops to teach them how to manage their time more effectively College administrators and instructors should focus on instilling a healthy sense of self-efficacy during the first year Educators teaching introductory courses must be aware of transition difficulties and prepare their first year students to study effectively on their own Properly implementing this information to improve college careers may significantly decrease the college drop out rate