Running head: MOTIVATION AND SELF-REGULATION IN ONLINE LEARNING Using Social Cognitive Theory to Predict Students' Use of Self-Regulated Learning Strategies in Online Courses

Effective use of self-regulated learning (SRL) strategies may be particularly important for students participating in online education (Schunk & Zimmerman, 1998). The objective of this study was to investigate how different motivational components of social cognitive theory (Bandura, 1986) relate to students' use of cognitive and metacognitive learning strategies in online courses. University students (n = 96) completed a survey that assessed their task value and self-efficacy, as well as outcome variables that included their use of three SRL strategies. Pearson correlations indicate that task value and self-efficacy were significantly related to students’ use of elaboration, critical thinking, and metacognitive learning strategies. Additionally, results from regression analyses reveal that task value and self-efficacy were significant positive predictors of students’ use of various learning strategies. These findings support and extend prior research in traditional classrooms indicating that students’ motivational beliefs about a learning task are related to their use of SRL strategies. Educational implications and suggestions for future research are discussed. DRAFT Motivation and Self-Regulation in Online Learning 3 Using Social Cognitive Theory to Predict Students' Use of Self-Regulated Learning Strategies in Online Courses Interest in academic self-regulation has increased considerably in recent years as investigators and practitioners attempt to understand how students become masters of their own learning processes (Schunk & Zimmerman, 1998). Self-regulated learning (SRL) has been defined as, “an active, constructive process whereby learners set goals for their learning and then attempt to monitor, regulate, and control their cognition, motivation, and behavior, guided and constrained by their goals and the contextual features of the environment” (Pintrich, 2000, p. 453). Self-regulated learners are generally characterized as active participants who efficiently control their own learning experiences in many different ways, including organizing and rehearsing information to be learned, and holding positive beliefs about their capabilities, the value of learning, and the factors that influence learning (Schunk & Zimmerman, 1994, 1998). Recently, several scholars have suggested that SRL skills may be particularly important for students participating in online education (Bandura, 1997; Dillon & Greene, 2003; Hartley & Bendixen, 2001; Hill & Hannafin, 1997). For example, in their edited volume regarding the instructional implications of academic self-regulation, Schunk and Zimmerman (1998) concluded that effective SRL strategies may be critical in distance learning situations due to the high degree of student autonomy resulting from the instructor’s physical absence. The authors recommended that future research on self-regulation investigate the specific strategies that allow for effective and efficient distance learning. The present study is the first in a line of research designed to address the recommendations made by Schunk and Zimmerman (1998). Specifically, this study explores the linkages between students’ motivation and self-regulation in online learning courses, seeking to DRAFT Motivation and Self-Regulation in Online Learning 4 determine if the pattern of relationships are consistent with those that have been found in traditional academic settings. In short, the present investigation marks a critical first step in extending the robust literature on SRL in classroom settings to online learning environments. Review of the Literature Self-regulated learning refers to “learning that occurs largely from the influence of student’s self-generated thoughts, feelings, strategies, and behaviors, which are oriented toward the attainment of goals” (Schunk & Zimmerman, 1998, p. viii). Academic self-regulation has been studied in traditional classrooms as a means of understanding how successful students adapt their cognition, motivation, and behavior to improve learning. In general, investigators have consistently found moderate to strong positive relations between students use of SRL strategies and academic achievement (Pintrich, 1999; Pintrich & De Groot, 1990; Pintrich & Garcia, 1991). For example, in a study of 173 seventh graders, Pintrich and De Groot (1990) found that higher levels of self-regulation were correlated with higher levels of achievement, as measured by final course grades, essays and reports, and in-class seatwork. Although there are various conceptualizations of academic self-regulation (for a review, see Boekaerts, Pintrich, & Zeidner, 2000), several researchers have found social cognitive models of SRL to be particularly useful in analyzing student success in online education (Lynch, 2003; Miltiadou & Savenye, 2003; Niemi, Nevgi, & Virtanen, 2003; Whipp & Chiarelli, 2004). This may be so because social cognitive models highlight important motivational factors and learning strategies that appear to benefit students in these highly autonomous learning situations. Furthermore, a number of investigators have recently emphasized the importance of social and environmental factors on student success in online education (Gunawardena & Zittle, 1997; Richardson & Swan, 2003). Thus, a social cognitive perspective on self-regulation, which DRAFT Motivation and Self-Regulation in Online Learning 5 addresses the interrelationship between the learner, the learners’ behavior, and the social environment (Bandura, 1997), lends itself well to an understanding of how successful learners function in online situations. While most SRL theorists acknowledge the influence of motivation on self-regulation, Pintrich’s (2000, 2003) model of SRL stresses the importance of motivation in all phases of selfregulation. Pintrich and his colleagues have demonstrated that effective and less effective selfregulated learners differ in several motivational processes. For example, their research suggests that learners’ task value (i.e., the extent to which they find a task interesting, important, and/or valuable) relates positively to their use of SRL strategies. Similarly, Schunk (2005) concluded, “Students with greater personal interest in a topic and those who view the activity as important or useful are more likely to use adaptive self-regulatory strategies” (p. 87). Existing research (Pintrich & De Groot, 1990; Schunk, 2005) has also suggested positive relations between students’ academic self-efficacy and their use of SRL strategies. In an early study of middle school students, Pintrich and De Groot (1990) found that students’ self-efficacy beliefs were positively related to their cognitive engagement and academic performance. In part, their results indicated that students who believed they were capable of learning were more likely to report use of SRL strategies and to persist longer at difficult academic tasks. More recently, in a review of past research, Schunk (2005) indicated that highly self-regulated learners tend to report higher levels of academic self-efficacy than do students with poorer self-regulatory skills. Taken together, much of the research on SRL supports the hypothesized linkages between motivation, self-regulation, and academic success. The objective of the present study was to determine if the relations between motivation and self-regulation that have consistently been found in traditional academic settings extend to online learning environments. Specifically, DRAFT Motivation and Self-Regulation in Online Learning 6 the following research question was addressed: Are students’ perceived task value and selfefficacy associated with their self-reported use of cognitive and metacognitive learning strategies in online courses? Consistent with findings in traditional classrooms, it was hypothesized that both students’ perceived task value and self-efficacy would be positively related with their selfreported use of critical thinking, elaboration, and metacognitive self-regulation in online courses.