Comparing online and blended learner's self-regulated learning strategies and academic performance

Highlights

• Few studies have online learner's and blended learners SRL strategy use & grade.

• Online and blended learners differed in their SRL strategies use.

• Individual predictive value of SRL strategies differed for online/blended learners.

• Overall predictors of grade were equivalent for online and blended learners.

• Time management/elaboration/rehearsal strategies key for predicting grade.

Abstract

The existing literature suggests that self-regulated learning (SRL) strategies are relevant to student grade performance in both online and blended contexts, although few, if any, studies have compared them. However, due to challenges unique to each group, the variety of SRL strategies that are implicated, and their effect size for predicting performance may differ across contexts. One hundred and forty online students and 466 blended learning students completed the Motivated Strategies for Learning Questionnaire. The results show that online students utilised SRL strategies more often than blended learning students, with the exception of peer learning and help seeking. Despite some differences in individual predictive value across enrolment status, the key SRL predictors of academic performance were largely equivalent between online and blended learning students. Findings highlight the relative importance of using time management and elaboration strategies, while avoiding rehearsal strategies, in relation to academic subject grade for both study modes.

Introduction

The transition from primary and secondary to tertiary education is typically characterized by a reduction in structured class time per week, less direct contact with one's teachers, and greater reliance upon self-regulated learning. Within this higher education context, it is well established that the strategies students employ to self-regulate their learning impact their academic performance (Richardson et al., 2012). It is also clear that students differ in the strategies they employ to self-regulate their learning (Barnard-Brak et al., 2010), as well as the frequency with which they utilise these strategies (Dörrenbächer & Perels, 2016). While these individual differences likely reflect the strategies learners have been taught previously and/or found to be helpful, strategy utilisation preferences may also reflect the constraints of one's learning environment. The present study explores this latter possibility by evaluating whether students in a wholly online study mode versus those in a blended learning environment differ in their use of various self-regulated learning strategies and/or the predictive value of these strategies for academic performance.

To be described as a self-regulated learner, the learner must be motivated, meta-cognitively involved, and an active agent in his or her own learning process (Zimmerman, 1986). Self-regulated learners plan, set goals, and engage in strategies to achieve those goals. Through evaluation and reflection, these strategies are monitored and modified to enhance one's progression towards goal achievement. Self-regulated learners are motivated, persistent, manage their time effectively, and seek assistance when necessary (Pintrich, Smith, Garcia & McKeachie, 1993). Although there are several different self-regulated learning (SRL) models, each from different theoretical perspectives, they all feature common characteristics—that is (a) a cyclical process, (b) comprised of cognition, metacognition, motivation, and emotion, and (c) a set of skills that can be developed and learned (Panadero & Alonso-Tapia, 2014).

Pintrich's (2004) model of SRL comprises the most comprehensive set of self-regulatory strategies, which can be measured using the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich, Smith, Garcia & McKeachie, 1991). Pintrich et al. (1991) identified three categories of SRL strategies that learners can apply to regulate their learning: (1) cognitive, (2) metacognitive, and (3) resource management strategies. According to Pintrich et al., cognitive strategies are a combination of basic and complex strategies for retaining information, and include strategies such as rehearsal (e.g. rote learning), elaboration (e.g. connect prior knowledge with new material), organisation (e.g. outlining and note taking), and critical thinking (e.g. synthesizing and evaluating). Metacognitive strategies are those that help to regulate and control cognition in order to accomplish a goal, and include strategies such as goal setting, planning, self-monitoring, and self-regulation. Resource management strategies, on the other hand, help learners to control external resources, and include time and environment management (e.g. planning), effort regulation (e.g. maintain focus), and peer learning (e.g. using peers to collaborative understand) and help seeking (e.g. asking for assistance). Despite the apparent breadth in the number of learning strategies available to a student, permissibility of these various strategies may be somewhat constrained by the way course content is delivered and accessed.

Traditionally, on-campus instructional approaches typically featured content taught in a classroom at a prescribed time by a teacher, that was supplemented with prescribed readings and assessment tasks (writing assignments, exams, quizzes, etc.) (Allen & Seaman, 2013). With the development and integration of online learning technologies, however, blended learning is quickly becoming the norm in the higher education sector (Masi & Winer, 2005). Although it may be defined in a variety of ways (e.g., see Driscoll & Carliner, 2005), blended learning in the present study is defined as the adoption of educational web-based technology (e.g., a learning management system) for online learning, which is used in combination with face-to-face, located instruction from teaching practitioners.

Growing in popularity too is online learning (Allen et al., 2016), defined here as educational instruction that occurs using web-based technology, which may be engaged in completely asynchronously or with components of synchronous learning, and with no located face-to-face class time. Online learning is thought to have several advantages over traditional face-to-face and blended education, including flexibility and accessibility to study anywhere, at any time, without requiring one's physical presence at a campus location (Means et al., 2009, Van Doorn and Van Doorn, 2014). While online learning can often include synchronous interactions and communication with instructors and peers, as well as deadlines and structure, it also provides for asynchronous learning in which space and time are not barriers (Means et al., 2009). This affords online learners the ability to live great distances from campus locations, and juggle their studies with other priorities such as work or family. These benefits are often obtained at a cost, as the online mode may also result in reduced opportunities for student-to-teacher and student-to-student interactions and communication, and as time is not typically structured around fixed instruction, online learners may need to provide their own structure around learning, determine for themselves when and how to engage with course content, manage their time efficiently, and persist in study despite competing life demands (Kizilcec et al., 2017, Moore and Kearsley, 2005).

For this reason, blended learning, if done well, may combine the benefits afforded by online technologies, with structure and social aspects of face-to-face time, to give an overall richer experience (Van Doorn & Van Doorn, 2014). A blended learning environment provides flexibility, but orientates students to a specific time and location each week to attend on-campus classes. It also allows students to customise their learning, while teaching staff are still able play a pivotal role in providing structure, organisation, scaffolding, and time management to the learning experience for students (Aldhafeeri, 2015, Artino and Jones, 2012). Several indirect lines of evidence, when viewed together, suggest that the self-regulation strategies employed and their impact on performance may differ across study mode.

A recent, large meta-analysis by Richardson et al. (2012), which compared the findings of 126 studies of SRL strategies used by students in higher education settings found that the strategies of effort regulation, time management, metacognition, elaboration, critical thinking, help seeking, and concentration significantly predicted student's grades; weighted mean correlations (r) ranged from 0.15 to 0.32. In particular, effort regulation, time management, elaboration and metacognition were found across studies to have the highest correlation with GPA. However, this meta-analysis did not differentiate on the basis of traditional versus blended learning formats.

In comparison, relatively few studies (n = 12) have been conducted focusing on the SRL strategy use of online-only learners, and their relationship with academic success in the last 10 years (Broadbent & Poon, 2015). Puzziferro (2008) found, from 815 online liberal arts students, that those who scored higher on the subscales of effort regulation and time management received higher final grades. However, none of the other SRL strategies employed (rehearsal, elaboration, organisation, critical thinking, metacognition, peer learning, or help seeking) were found to be significantly related to grade. Similarly, Carson's (2011) large study of 4909 first year online students also found that effort regulation and time management, as well as metacognition had a small positive correlation with grade. Indeed, a meta-analytic review by Broadbent and Poon (2015) found that only four learning strategies were significantly associated with online learner's grades: metacognition, time management, effort regulation, and critical thinking. Their weighted mean correlations (ranged from 0.05 to 0.14), were weaker than those found by Richardson et al. (2012). Broadbent and Poon (2015) concluded that although SRL strategy use in more traditional settings appear to generalise to online learning environments, the effects of SRL strategies may be “dampened in the online learning environment” and “we should not assume that online learning in itself fosters SRL strategies use or development (p. 12)”.

However, none of the studies from the Broadbent and Poon (2015) meta-analysis directly compared online learners with blended learners. One study, by Klingsieck, Fries, Horz, and Hofer (2012), compared a distance education sample with a ‘traditional university’ sample, but no information was given about whether the traditional students studied with any online components. The authors found significant negative correlations between elaboration and rehearsal with grade, and a significant positive correlation between metacognition and grade for online learners. No comparison to the traditional students could be made, as these data were not reported by the authors.

While little to no work has been done comparing the influence of SRL strategies on academic performance across study mode, Means et al. (2009) conducted a meta-analysis of 56 experimental studies to compare the effect sizes of traditional, blended, and online educational settings. Online and blended learning students outperformed students in more traditional settings (with larger effects for blended vs traditional learners), but did not significantly differ from each other. Perhaps, no differences occurred because blended and online learning attracts different types of learners (Bernard et al., 2014), each of which are attracted to the learning context that suits their needs and learning styles. It is likely that the type of learner who chooses to study in a blended study mode does so because they like structure, and the social presence associated with study context, while online learners are likely to be attracted to the high level of flexibility and independence. Possibly too, learners who choose to engage in online learning may already employ numerous self-regulated learning strategies and thus feel comfortable learning in a more autonomous environment. As such, differences between these groups may instead be observed in the learning strategies they employ and/or the impact of various learning strategies on their learning outcomes rather than directly observable differences in performance. However, as there are few studies comparing the SRL strategy use of blended and online learners in relation to grade, this is of course speculative.

In summary, the existing literature suggests that SRL strategies are relevant to student performance in both online and blended learning contexts, and the variety of SRL strategies that are implicated and their effect size for predicting performance may differ across context due to characteristics and student challenges unique to each. Despite this, explicit tests of differences in the relative contributions of SRL strategies across online and blended learning contexts have seldom been previously undertaken, if at all. Such knowledge would provide greater insights into the key drivers of performance that are generalizable across these two learning contexts, as well as identify potential SRL strategies that may be more important for one context than the other. In turn, these insights may be leveraged to produce more effective study resources for students, and enhance SRL interventions tailored to their learning context.

The aims of the current study were threefold: (1) to assess differences in perceived frequency of use of self-regulated learning strategies in two different learning modes (blended learning vs. online learning); (2) to examine the relationships between SRL strategies and subject grade for both groups; and (3) to explore whether contributions of the SRL strategies for subject grade differed across the two groups. It was predicted that (1) because of the increased autonomy of the online environment, online learners will utilise more self-regulated learning strategies than blended learners; (2) in line with the findings of Broadbent and Poon (2015) and Richardson et al. (2012), there will be a dampened effect of strategy use on subject grade for online learners compared to blended learners; although (3) in line with the findings of Means et al. (2009) where blended and online learners performed academically similar, it is predicted that when viewed altogether the contributions of the SRL strategies will contribute to final subject grade equivalently across blended and online learners.