Motivation and Among Working Faye George Mason SelfRegulation

Motivation and Among Working Faye George Mason

Self-Regulation College Students Huie University

Abstract Students make a difficult shift when transitioning to college, where they face increased demands for self-regulated learning and effective time-management, especially for students who balance both work and school. This study explores numerous aspects of motivation (goal orientation, self-efficacy, and life satisfaction), self-regulated learning (time -management, help-seeking, study strategies), academic selfhandicapping practices, work status, and academic performance among 592 first year college students. Surveys were completed by students at three time periods within their first two semesters. Results indicate that academic selfhandicapping was positively correlated with performanceavoidance goal orientations and negatively correlated with school satisfaction. Time studying was positively associated with school, and employed students used more learning strategies than unemployed students.

Introduction/Rationale n n n Nationally, 1 in 4 college freshmen (27%) do not return for their Sophomore year, and only about 50% eventually graduate Knowledge about the motivational predictors of successful student performance and retention can help colleges implement better assessment and intervention strategies for retaining students Studies on motivation and self-regulation in college students have typically a) involved homogenous Caucasian samples, b) not been longitudinal, c) not examined specifically students who work

Motivation = GOALS x EMOTIONS x PERSONAL AGENCY BELIEFS (Ford, 1992) n Goals: Desired outcomes ¨ ¨ ¨ Mastery- Developing competence Approach-performance- showing ability and performing well Approach-avoidance- concealing and preventing failure by not trying n n n Self-handicapping- conscious effort to avoid looking incompetent not only to others but also to themselves Emotions: Feelings toward the goal ¨ Life satisfaction: feelings toward life ¨ School satisfaction: feelings toward school Personal Agency Beliefs- personal and environmental confidence ¨ Self-efficacy: positive perception of one’s competence (Chemers et al. , 2001)

Self-Regulation n n Behaviors, cognitions, and motivations that allow goal attainment Time management: effective management of time Environment management ¨ Effort regulation ¨ n Learning Strategies: Effective strategies used to learn and understand material. Critical thinking ¨ Help seeking ¨ Metacognitive self-regulation ¨ n Self-regulated learning has adaptive outcomes (Schunk & Ertmer, 1999)

Method n Sample population characteristics ¨ ¨ ¨ ¨ n 62. 5% Female Age M = 18. 9 (range 16 -46) 62% White, 7% Black, 5% Hispanic, 17% Asian, 9% Other/Mixed 94% 1 st sem. Freshman, 4% 2 nd sem. , 2% Sophomore 54% working (M = 16. 5 hrs, SD = 9. 5, range = 1 -80 hrs) 79% English as native language 49% receive some formal financial aid Data collected within three time periods T 1 (Beginning of the first semester) N = 592 2. T 2 (End of the first semester) N = 243 (41%) 3. T 3 (End of the second semester) N = 96 (16%) 1.

Materials 1. Motivated Strategies for Learning Questionnaire (T 1, T 2, T 3) (MSLQ; Pintrich et al. , 1991) n n n 2. Learning Strategies Management of Learning Resources Academic Self-Regulation Extended Satisfaction with Life Scale (T 2 and T 3) (Alfonso et al. , 1996) § 3. general life, school life, and job satisfaction The Patterns for Adaptive Learning Scale (PALS; Midgley et al. 2000) T 1, T 2, T 3 3 Goal orientations § Academic Self-Efficacy § Academic Self-Handicapping §

Results Q 1: Are employed high academic achieving students particular different from those who are unemployed high academic achieving students? n A MANOVA (Multivariate Analysis of Variance) suggests: ¨ Employed and unemployed students are different on certain levels of self-regulation and motivation, F(9, 491) = 2. 61, p <. 01 (T 1) n ¨ Students with a high GPA and students with a low GPA are different on certain levels of motivation and self-regulation, F(9, 491) = 2. 66, p <. 01 (T 1) n ¨ See Table 1 See Table 2 Academically successful working students are significantly different from unemployed academically successful students on certain levels of motivation and self-regulation F(9, 183) = 4. 81, p <. 05 (T 1). n See Table 3

Table 1. Motivation and Self-Regulation as a Function of Working Status Working Non Working M (SD) Metacognitive Self. Regulation 4. 44 (. 81) 4. 32 (. 86) Time Management 4. 96 (. 84) 4. 96 (. 93) Effort Regulation 4. 83 (1. 06) 4. 86 (1. 13) Help Seeking 4. 52 (. 99) 4. 41 (1. 07) Use of Learning Strategies* 4. 62 (. 67) 4. 47 (. 68) Mastery Goal Orientation+ 4. 29 (. 75) 4. 23 (. 71) Performance Approach Goal Orientation+ 2. 68 (1. 14) 2. 85 (1. 12) Performance Avoidance Goal Orientation+ 2. 70 (1. 02) 3. 03 (. 99) Academic Self-Efficacy 4. 00 (. 74) 3. 95 (. 75) *p <. 05 +p <. 10

Table 2. Motivation and Self-Regulation as a Function of Academic Performance High GPA Low GPA M (SD) Metacognitive Self. Regulation 4. 45 (. 86) 4. 34 (. 82) Time Management* 5. 12 (. 93) 4. 87 (. 84) Effort Regulation* 5. 08 (1. 03) 4. 69 (1. 10) Help Seeking 4. 40 (1. 40) 4. 51 (1. 03) Use of Learning Strategies+ 4. 61 (. 71) 4. 51 (. 65) Mastery Goal Orientation+ 4. 34 (. 71) 4. 22 (. 74) Performance Approach Goal Orientation 2. 68 (1. 09) 2. 82 (1. 16) Performance Avoidance Goal Orientation 2. 97 (1. 01) 2. 96 (1. 01) Academic Self-Efficacy* 4. 06 (. 71) 3. 93 (. 76) *p <. 05 +p <. 10

Table 3. Motivation and Self-Regulation as a Function of Employment Status (Just Hi GPA Group) Employed Students Unemployed Students M (SD) M Metacognitive Self. Regulation 4. 53 (. 81) 4. 37 (. 91) Time Management 4. 99 (1. 13) 4. 44 (. 79) Effort Regulation 5. 08 (. 95) 5. 09 (1. 11) Help Seeking* 4. 57 (. 97) 4. 24 (1. 08) Use of Learning Strategies* 4. 74 (. 71) 4. 49 (. 69) Mastery Goal Orientation 4. 40 (. 75) 4. 28 (. 68) Performance Approach Goal Orientation 2. 55 (1. 08) 2. 79 (1. 10) Performance Avoidance Goal Orientation+ 2. 82 (1. 01) 3. 10 (. 99) Academic Self-Efficacy 4. 05 (. 72) 4. 07 (. 70) *p <. 05 +p <. 10 (SD)

Results Q 2: To what extent are amount of time spent at work and amount of time spent studying related with life satisfaction and academic performance? GPA Life Sat. School Sat. Job Sat. Work. Hrs (T 1) -. 13* -. 09 -. 10 -. 30* Study. Hrs (T 1) . 15* . 07 . 09 -. 02 Work. Hrs (T 2) -. 37* -. 16 -. 04 -. 25* Study. Hrs (T 2) . 21* . 10 . 16* -. 11 * p <. 05 n n Correlations between work hours, study hours, and life satisfaction indicate that work and study time are significantly associated with GPA. Results indicate that the higher amount of time put into work the lower GPA and satisfaction becomes.

Table 4. (Q 3) What motivational and self-regulatory factors are associated with academic self-handicapping? Academic Self-Handicapping (T 1) (T 2) GPA (T 2) -. 13* -. 24* Metacognitive self-regulation -. 10* -. 10 Time management -. 40* -. 43* Effort regulation -. 45* -. 56* Help seeking -. 03 -. 09 Learning strategies used -. 14* -. 11+ Mastery goal Orientation -. 17* -. 11+ Performance-approach goal orientation . 39* . 54* Performance avoidance goal orientation . 43* . 60* Academic self-efficacy -. 10* . 02* Life satisfaction N/A -. 04 Job satisfaction N/A -. 16 School satisfaction N/A -. 21* * p <. 05

Results Q 4: What is the strongest predictor (goals, emotions, selfefficacy, self-regulation, and employment) of academic performance? n n Regression analyses reveal that self-regulation predicts academic performance above and beyond the motivation and life satisfaction variables. Multiple hierarchical regression Model 1 = Motivational Variables n Three goal orientations, academic self efficacy ¨ Model 2 = Self-regulatory Variables n Time management, learning strategies ¨ Model 3 = Life satisfaction ¨ R R Square F p Model 1 . 24 . 06 3. 29 . 01 Model 2 . 41 . 17 8. 67 . 00 Model 3 . 18 . 03 8. 14 . 01

Results Q 5: Are employed students more likely to engage in self-handicapping than nonworking students? n Two independent samples t-test q n Correlations between hours worked with academic self handicapping q n Results indicate that working students do not engage in more self handicapping (M = 2. 40, SD =. 99, NS) than non working students (M = 2. 43, SD = 1. 03, NS) Results revealed that number of hours worked is NOT associated with academic self handicapping (r =. 01) These results show us that employed students are not more likely to engage in academic self-handicapping than nonworking students

Longitudinal Analyses n Students who practice self-handicapping methods are more performance oriented in Time 2, than Time 1 ¨ The longer a student practices academic self-handicapping strategies, the more importance they will place on their appearance Academic Self-Handicapping (T 1) (T 2) GPA (T 2) -. 13* -. 24* Time management -. 40* -. 43* Effort regulation -. 45* -. 56* Performance-approach goal orientation . 39* . 54* Performance avoidance goal orientation . 43* . 60* *p <. 05 +p <. 10

n Self-regulation is an even stronger predictor of GPA at Longitudinal the end of the semester than it is at the beginning of the semester ¨ As Analyses cont’ self-regulated students are getting better grades, the nonself regulated students may be getting even worse grades over time– making the predictive value of selfregulation stronger Time 1 R R 2 F p M 1 . 15 . 04 2. 91 . 02 M 2 . 24 . 06 6. 30 . 00 M 3 . 18 . 03 8. 14 . 01 R R 2 F p M 1 . 24 . 06 3. 29 . 01 M 2 . 41 . 17 8. 67 . 00 M 3 . 18 . 03 8. 14 . 01 Time 2

Discussion/Implications n n These findings generally indicate that the more hours students work, the poorer they do in school This information may also suggest that universities need to develop special courses or seminars to teach students how to balance work and school life, or helpful self-regulating strategies Universities may also take this information to thoroughly train professors to emphasize a mastery classroom environment to help students be better self-regulators as well as improve motivation Properly implementing this information to improve college careers may significantly decrease the college drop out rate

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Dr. Adam Winsler Dr. Linda Chrosniak Dr. Anastasia Kitsantas