Evaluating the Impact of Self-regulated Learning Programming for Students on Academic Probation

Symposium presented at the annual meeting of the American Educational Research Association, New York, NY.

In this contribution to the symposium, we will pursue two goals related to understanding the impact of the University Learning Center (ULC) on student success. First, we will describe the ULC’s interventions, their connection to self-regulated learning, and the students they serve. Second, we will evaluate the impact of one form of the intervention for students on academic probation.

Self-regulated learning (SRL) serves as the framework for the ULC’s interventions and research. Self-regulated learners are active participants in their learning and utilize strategies to exert control over themselves and their academic tasks (Pintrich & Zusho, 2007). Because of the connection between SRL and positive outcomes (Dent & Koenka, 2016), researchers have utilized SRL as a basis for interventions (Dorrenbacher & Perels, 2016; Hofer, Yu, & Pintrich, 1998). However, little research has evaluated SRL interventions specifically for students known to be at risk of leaving the university.

The ULC offers three types of programming rooted in SRL: a learning-to-learn course, workshops, and academic coaching. In our presentation, we will share data evaluating the impact of these interventions with particular focus on the learning-to-learn course. As with similar courses (Hofer, Yu, & Pintrich, 1998), assignments were designed to develop students’ procedural knowledge and skills related to motivation and SRL.

During the first week of the course, students (Nparticipants = 305) reported their academic probation status (n = 48): a designation that typically occurs when their GPA falls below 2.00. During week two of the semester, students completed self-report surveys including self-efficacy for SRL (Zimmerman et al., 1992), time management (Macan, 1994), and procrastination (Tuckman, 1991). During week seven, students reported their environmental management (Wolters & Benzon, 2013) and motivational regulation (Kim, Brady, & Wolters, 2017). Follow-up survey measuring self-efficacy for SRL, environmental management, and motivational regulation were completed by students during week 13.

We conducted an independent sample t-test to determine differences in motivational beliefs and strategies based on probation status. Scores on three scales were significantly different for students who were or were not on academic probation: self-efficacy for SRL, time management, and procrastination (Table 1; see PDF).

Our presentation will discuss the impact of the learning-to-learn course and its relative impact based on probation status. Repeated measures ANOVA will compare changes in motivational beliefs and strategies. We also will report qualitative analyses of students’ self-reflections about changes in their motivational beliefs and strategies.

Consistent with the view that weaknesses in motivational beliefs and learning strategies contribute to the academic difficulties associated with academic probation (Isaak, Graves, & Mayers, 2007), our findings indicate that these students had lower self-efficacy beliefs, utilized fewer time management strategies, and procrastinated more frequently than their peers. Additional findings provide insight on the ways SRL training can provide particular benefits to those on probation through improvements in SRL skills and motivational beliefs.