Promoting College Student Self-Regulation in Online Learning Environments

Wandler, J. Brad; Imbriale, William John

doi:10.24059/olj.v21i2.881

Cited by 92 publications

(80 citation statements)

References 21 publications

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“…Accordingly, students who have adopted more supportive online learning behaviors are more confident about understanding the subject matter and expect they will perform well and receive good grades at the end of the semester. According to Wandler and Imbriale (2017), self-regulated learners are likely to manage their time to complete tasks in a timely fashion without procrastination. They can also flexibly adapt or change their physical surroundings, if needed, to make them more conducive to completing their tasks.…”

Section: Discussionmentioning

confidence: 99%

How College Students’ Achievement Goal Orientations Predict Their Expected Online Learning Outcome: The Mediation Roles of Self-Regulated Learning Strategies and Supportive Online Learning Behaviors

Yeh

Kwok

Chien

et al. 2019

OLJ

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The purpose of this study was to examine the underlying mechanism between goal orientations and academic expectation for online learners. We simultaneously studied the structural relationships among 2×2 achievement goal orientations, self-regulated learning (SRL) strategies, supportive online learning behaviors, and expected academic outcome in various online courses with 93 respondents (70 undergraduate and 23 graduate students). Specifically, we tested the mediation effects of both SRL strategies and supportive online learning behaviors on the relationship between achievement goal orientations and students' academic expectations. The results showed that two of the achievement goal orientations-mastery-approach (MAP) goals and mastery-avoidance (MAV) goals-predicted the adoption of SRL strategies and supportive online learning behaviors, which, in turn, predicted students' expected academic outcome for their online course. Specifically, students with higher MAP goals were more likely to adopt different types of SRL strategies and supportive online learning behaviors to facilitate their learning experience, which further enhanced their expectation for their academic outcome. By contrast, students with higher MAV goals were less likely to adopt SRL strategies and supportive online learning behaviors, which, in turn, led to lower grade expectations. . (2019).How college students' achievement goal orientations predict their expected online learning outcome: The mediation roles of self-regulated learning strategies and supportive online learning behaviors. Online Learning, 23(4), 23-41.

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Section: Discussionmentioning

confidence: 99%

How College Students’ Achievement Goal Orientations Predict Their Expected Online Learning Outcome: The Mediation Roles of Self-Regulated Learning Strategies and Supportive Online Learning Behaviors

Yeh

Kwok

Chien

et al. 2019

OLJ

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“…However, this study focuses on instructional design elements that may increase the attention span of learners who are already watching the online video lectures. Therefore, external mechanisms such as those suggested by Wandler and Imbriale (2017) and Romero et al, (2016), are beyond the scope of the current study.…”

Section: Theoretical Background and The Research Questionsmentioning

confidence: 99%

“…Wandler and Imbriale (2017) propose that online instructors should promote the use of self-regulated learning strategies by students, including scaffolding time expectations, by dividing large assignments to sub assignments with several due dates. Romero, Cerezo, Espino, and Bermudez (2016) suggest using smartwatches for students to decrease procrastination behaviors in MOOCs.…”

Section: Theoretical Background and The Research Questionsmentioning

confidence: 99%

A Learning Analytics Approach for Evaluating the Impact of Interactivity in Online Video Lectures on the Attention Span of Students

Geri

Winer

Zaks

2017

IJELL

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Aim/PurposeAs online video lectures rapidly gain popularity in formal and informal learning environments, one of their main challenges is student retention. This study investigates the influence of adding interactivity to online video lectures on students' attention span. BackgroundInteractivity is perceived as increasing the attention span of learners and improving the quality of learning. However, interactivity may be regarded as an interruption, which distracts students. Furthermore, adding interactive elements to online video lectures requires additional investment of various resources. Therefore, it is important to investigate the impact of adding interactivity to online video lectures on the attention span of learners. Methodology This study employed a learning analytics approach, obtained data from Google Analytics, and analyzed data of two Massive Open Online Courses (MOOCs) that were developed by the Open University of Israel in order to make English for academic purposes (EAP) courses freely accessible. ContributionThe paper provides important insights, based on quantitative empirical research, on the following: integrating interactive elements in online videos; the impact of video length; and differences between two groups of advanced and basic learners. Furthermore, it demonstrates how learning analytics may be used for improving instructional design. Evaluating the Impact of Interactivity in Online Video Lectures 216 FindingsThe findings suggest that interactivity may increase the attention span of learners, as measured by the average online video lecture viewing completion percentage, before and after the addition of interactivity. The impact is significantly stronger for the more advanced course. However, when the lecture is longer than about 15 minutes, the completion percentages decrease, even after adding interactive elements. Recommendations for PractitionersAdding interactivity to online video lectures and controlling their length is expected to increase the attention span of learners. Recommendation for ResearchersLearning analytics is a powerful quantitative methodology for identifying ways to improve learning processes. Impact on Society Providing practical insights on mechanisms for increasing the attention span of learners is expected to improve social inclusion. Future ResearchDiscovering further best practices to improve the effectiveness of online video lectures for diverse learners.

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“…Self-Regulated Learning (SRL) strategies enable a self-regulated learner to actively engage self-regulated processes (Perry and Rahim, 2011). In order to be successful, e-learners must rely on their individual abilities to direct their learning, by employing SRL Strategies (Wandler and Imbriale, 2017;Muuro et al, 2016). All students are self-regulated learners to some degree, but not all students are necessarily strong selfregulated learners (Zimmerman and Schunk, 2011).…”

Section: Srl Strategiesmentioning

confidence: 99%

“…There has been a steady increase in e-learning enrollment for undergraduate students in Higher Education Institutions (HEIs) in Africa (Wandler and Imbriale, 2017) due to an increase in internet access in the past decade (Greenland and Moore, 2014). In contrast, Higher e-learning institutions in sub-Saharan Africa have experienced high drop-out rates due to factors such as (i) Lack of direct interaction between instructors and learners, (ii) the difficulty for instructors to monitor student progress (Lodge et al, 2018), hence e-learners may experience a sense of isolation, (iii) lack of ability to self-regulate (Lee and Choi, 2011), which may in part be due to students not recognizing the effort and organization required to succeed in e-learning courses and (iv) limited self-regulatory skills (Cho and Shen, 2013).…”

Section: Introductionmentioning

confidence: 99%

Proposed Self-Regulation Model for Collaborative E-Learning Systems in Kenyan Public Universities

Akinyi

Oboko

2020

American Journal of Engineering and Applied Sciences

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Integration of technology in learning such as Electronic-learning has become an indispensable segment of higher education in Sub-Saharan Africa. This has opened up opportunities that improve teaching and learning. There is need for intervening in e-learning environments towards developing Self-regulated learning support, which can lead to improvement in performance and learner retention. SRL provides students with capability to acquire and update complex and systemic concepts and make judgements about their progress as they do so. Lack of ability to self-regulate is a major reason for dropout rates and poor performance in E-learning courses, due in part to students not recognizing the effort and organization required to succeed in online courses and the difficulty for instructors to monitor student progress. This study was carried out in order to develop an SRL model for collaborative e-learning based on SRL theories to determine the SRL strategies to model. The study proposes an SRL model based on Social Cognitive Theory of SRL as an intervention for reducing drop-out rates and improving performance of elearning environments in Kenyan Public Universities.

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Promoting College Student Self-Regulation in Online Learning Environments

Cited by 92 publications

References 21 publications

How College Students’ Achievement Goal Orientations Predict Their Expected Online Learning Outcome: The Mediation Roles of Self-Regulated Learning Strategies and Supportive Online Learning Behaviors

How College Students’ Achievement Goal Orientations Predict Their Expected Online Learning Outcome: The Mediation Roles of Self-Regulated Learning Strategies and Supportive Online Learning Behaviors

A Learning Analytics Approach for Evaluating the Impact of Interactivity in Online Video Lectures on the Attention Span of Students

Proposed Self-Regulation Model for Collaborative E-Learning Systems in Kenyan Public Universities

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