What Self-Regulated Learning Skills Matter and How Can a Learner Acquire Them?

• In Event: Cognitive, Metacognitive, and Motivational Interventions Supporting Student Success in STEM: What Works, When, for Whom?

Abstract

Background/Aims
Undergraduate STEM lecture courses enroll hundreds who must master declarative, conceptual, and applied learning objectives in complex active learning environments. Active learning designs require that students be able to engage in self-regulated learning (SRL; Winne & Hadwin, 1998). Undergraduates struggle with SRL (Perez et al., 2014), and many universities provide courses, workshops, and digital trainings to scaffold SRL skill development and enactment (Hattie, et al., 1996; Theobald, 2021). Recently, brief digital learning supports have shown considerable promise for delivering timely, brief, independent opportunities to develop undergraduates’ SRL skills (Broadbent & Poon, 2015), and some have been shown to improve course performance in STEM settings (e.g., Bernacki, et al., 2020).

In this paper, we expanded upon this evidence and examined how two designs of a digital skill training scaffolded students’ SRL skills and how skill mastery demonstrated at the end of training modules predicted performance on future course exams in biology. Iterative redesign efforts across two studies allowed us to explore context-dependent, differential treatment effects.

Method
In Study 1, undergraduate (N=49) anatomy and physiology students from a southwestern US university with Minority Serving Institution status completed SRL-training activities. Responses were scored for quality and summed to reflect mastery of cognitive strategies, metacognitive processes involved in SRL, and behavioral and environmental regulation strategies. Training was administered after exam 1, and performance on training items was scored by two raters (ICC=.938) and analyzed in relation to unit and final exam scores (alphas >.75).

In Study 2, students enrolled in a biology course at the same university (N=62) completed the same modules on the same topic, but those modules were redesigned according to principles of Multimedia Learning Theory (Mayer, 2021) to lessen students' cognitive load by splitting content across audio and visual information channels, as well as to lessen time cost and improve completion rates (Figure 1). Two raters scored training performances (ICC=.841) and instructors scored exams (50 multiple choice items on unit exams, 95 on final exam; alphas >.89). Modules were assigned before exams.

Results
In Study 1, path analyses indicated that students’ knowledge of cognitive strategies and behavioral and environmental regulation predicted exam grades (Figure 2, middle).

In Study 2, knowledge of behavioral and environmental regulation strategies again predicted biology exam performance, whereas knowledge of cognitive strategies was a positive but statistically nonsignificant predictor of exam performance (Figure 2, bottom). Compared to the reading-intensive design administered in Study 1, which had a completion rate of ~ 50% and completion times of ~120 minutes, Study 2 completion rates increased to ~70%, and time-to-completion of training decreased to 60-90 minutes.

Significance
Digital skill trainings continue to show promise as an effective tool to scaffold STEM learning in higher education. Iterative redesign efforts guided by learning skill training frameworks (Hattie & Donoghue, 2016) and multimedia learning theory (Mayer, 2021) showed that efficacy of training can be maintained while the time and effort cost to students is lessened, thus broadening the training's accessibility and impact in diverse student populations.

Authors

• Matthew L. Bernacki, University of North Carolina - Chapel Hill
  Presenting Author

• MeganClaire Cogliano, University of Nevada - Las Vegas
  Non-Presenting Author

• Shelbi Laura Kuhlmann, University of North Carolina - Chapel Hill
  Non-Presenting Author

• Jonathan C. Hilpert, University of Nevada - Las Vegas
  Non-Presenting Author

• Christy Strong, University of Nevada - Las Vegas
  Non-Presenting Author