First-Year College Students' Time Use and Self-Regulation

Study Overview and Objectives

• The study investigated the relations between first-year college students' ($N = 589$) time use, academic self-regulation, and grade point average ($GPA$) across three time points during their first year of university.

• Researchers examined how students manage their time as a critical component of academic performance and self-regulated learning ($SRL$).

• The study specifically addressed how students plan for and actually spend time on academics, socializing, leisure, and work obligations, and how these patterns evolve between the first and second semesters.

• Primary Research Questions included:

  • How do students plan to, and actually spend time over their first and second semesters?

  • To what extent is time use associated with academic self-regulation and target/actual $GPA$?

  • How accurate are students with their time use and goal-setting, and do they revise these after the first semester?

  • How do managing and changing time use relate to self-regulation and $GPA$?

Theoretical Framework: Self-Regulated Learning (SRL)

• $SRL$ is described by Zimmerman ($2008$) as occurring in three distinct phases:

  • Forethought Phase: Students set goals and establish expectations for their learning.

  • Performance Phase: Students implement learning strategies and monitor their progress/learning.

  • Self-Reflection Phase: Students use self-monitored outcomes to evaluate strategy effectiveness, encouraging adjustments in the forethought phase for future tasks.

• Cognitive Strategies: Strategic learners use organized study techniques, monitor knowledge gaps, and maintain reliable study environments. High awareness and monitoring lead to higher academic delay-of-gratification and performance (Bembenutty, $2007$).

• Goal-Setting: Set standards for performance (Locke \& Latham, $2002$). Students with higher academic goals typically exhibit higher motivation and believe in their capability to self-regulate (Wolters, $2003$).

• Procrastination: Viewed as a failure of self-regulation. It can be minimized by increasing self-efficacy and metacognitive strategy use. Research indicates that students with high $GPAs$ understand short-range planning and maintain a time-oriented attitude (Britton \& Tesser, $1991$).

Methodology and Participant Demographics

• Participants: $589$ first-semester undergraduates at a large public, mid-Atlantic university.

  • Classifications: $535$ first-semester freshmen, $25$ transfer freshmen, $10$ transfer sophomores, $1$ transfer junior, and $18$ non-indicated.

  • Age: Average age of $18$ years.

  • Gender: $63\%$ female, $37\%$ male.

  • Ethnicity: $65\%$ White, $18\%$ Asian, $7\%$ Black, $6\%$ Hispanic, and $4\%$ "Other."

  • Background: $85\%$ native to the US; $75\%$ spoke English as a first language; average family income of $US\$70,000$ per year; approximately $1/3$ were first-generation college students.

  • Enrollment: $97\%$ full-time; $92\%$ had no prior college experience; $61\%$ lived on campus.

• Procedures: Data collected at three intervals:

  • Time 1 (T1): 2 weeks into the fall semester.

  • Time 2 (T2): End of the fall semester.

  • Time 3 (T3): Follow-up at the end of the second semester.

• Measures:

  • Motivated Strategies for Learning Questionnaire (MSLQ): Assessed $SRL$ (academic activities and metacognitive strategies). Subscales: Time and environment ($8$ items, $\alpha = .71$); metacognitive planning/monitoring ($12$ items, $\alpha = .74$).

  • Time Use Scale: Students reported planned and actual hours in a week on a scale from $1$ to $8$ ($1 = none$, 2 = <1 hr, $3 = 1-2 hr$, $4 = 3-5 hr$, $5 = 6-10 hr$, $6 = 11-15 hr$, $7 = 16-20 hr$, 8 = >20 hr).

  • Time Use Composites:

    1. Academic Activities: Studying/homework and meeting with instructors.

    2. Passive Leisure Activities: Watching TV and playing videogames.

    3. Socializing Activities: Socializing with friends and partying.

    4. Obligatory Activities: Exercise, working for pay, volunteering, student clubs, and household/child care.

Detailed Results: Time Use Patterns

• Planned Time Use Distribution (T1):

  • Obligations: $16.26$ hours per week ($SD = 10.07$).

  • Socializing: $12.56$ hours per week ($SD = 8.59$).

  • Academic: $10.78$ hours per week ($SD = 6.21$).

  • Passive Leisure: $5.21$ hours per week ($SD = 5.92$).

• Actual Time Use Distribution (T2 - First Semester):

  • Obligations: $14.61$ hours per week ($SD = 10.88$).

  • Socializing: $13.49$ hours per week ($SD = 9.16$).

  • Academic: $10.53$ hours per week ($SD = 6.52$).

  • Passive Leisure: $5.57$ hours per week ($SD = 6.07$).

• Changes Over Time:

  • Students planned to spend significantly more time on academics in the second semester ($M = 13.58$, $d = 0.22$) compared to the first ($M = 10.78$).

  • Students planned more time for obligations in the second semester ($M = 19.26$, $d = 0.29$) vs. first ($M = 16.26$).

  • Actual socializing time decreased significantly from the first ($M = 13.49$) to the second semester ($M = 7.65$, $d = 0.72$).

Relations Between Time Use, Self-Regulation, and Performance

• Self-Regulation (MSLQ) Correlations:

  • Planned academic time (T1) correlated positively with time/environment management ($r = .12$, p < .05) and metacognitive $SRL$ ($r = .23$, p < .01).

  • Actual academic time (T2) correlated with time/environment management ($r = .22$, p < .01) and metacognitive $SRL$ ($r = .21$, p < .01).

  • Metacognitive $SRL$ was negatively correlated with actual passive leisure ($r = -.15$, p < .05).

• GPA Relationships:

  • Planned Academic Time (T1): Correlated with first-semester actual $GPA$ ($r = .16$, p < .01) and second-semester target $GPA$ ($r = .21$, p < .01).

  • Actual Academic Time (T2): Correlated with second-semester target $GPA$ ($r = .23$, p < .01) and actual second-semester $GPA$ ($r = .17$, p < .01).

  • Setting a higher target $GPA$ was also related to planning more time in obligations ($r = .10$, p < .05).

Time Use Accuracy and Goal Achievement Analysis

• Accuracy Measures: Calculated as the absolute difference between planned and actual hours. All areas showed significant inaccuracy (deviation from zero):

  • Obligations Accuracy: $M = 7.83$, $SD = 7.63$ ($t(214) = 15.06$).

  • Socializing Accuracy: $M = 5.47$, $SD = 4.82$ ($t(229) = 17.20$).

  • Academic Accuracy: $M = 5.37$, $SD = 4.46$ ($t(229) = 18.23$).

  • Passive Leisure Accuracy: $M = 3.38$, $SD = 4.06$ ($t(226) = 12.53$).

• Performance Comparison Groups:

  • Worse than expected: $66\%$ of students did not achieve their first-semester target $GPA$.

  • Same as expected: $21\%$ of students achieved within $0.10$ points of their target.

  • Better than expected: $13\%$ of students exceeded their target.

• Behavioral Responses to Feedback:

  • Those who failed to meet target $GPAs$ did not plan to spend more time on academics in the second semester. Instead, they tended to lower their second-semester target $GPA$ ($r = -.19$) and increased planned obligations ($M = 20.37$ vs. $16.73$ for those meeting targets).

  • Students who surpassed their targets planned to socialize more ($M = 15.75$, $SD = 10.10$, $d = 0.64$) and engage in more leisure ($M = 7.42$, $d = 0.45$) in the second semester compared to peers.

Discussion and Practical Implications

• Inadequate Study Time: Students planned only about $2.5$ hours of study per course per week, far below instructor recommendations (often $3$ hours of study for every $1$ hour in class).

• Self-Regulatory Gap: The findings suggest that first-year students struggle with $SRL$ capacity. When faced with underperformance, they tend to reduce expectations rather than adjust behavioral effort (increasing academic time).

• Campus-Centered vs. Work-Centered: Following Astin ($1999$) and Nonis et al. ($2006$), students on campus with a structured schedule often exhibit higher $SRL$; paradoxically, a busy schedule (high obligations) may help students prioritize goals.

• Administrative Recommendations:

  • Orientation Courses (e.g., University 100): Should intensify curriculum regarding time management, planning, and goal-setting beyond the first few weeks.

  • Middle-Year Intervention: Advisors should meet with students midway through the first year to assist with revising goals based on actual performance feedback.

  • Micro-level Measures: Future research and interventions should utilize daily diaries or hour-by-hour tracking to improve students' self-monitoring sensitivity.

  • Modeling Strategy: Instructors should model the process of planning, performing, and reflecting on academic tasks to demonstrate how long specific processes (like writing a paper) actually take.