The Relationship between Self-Regulated Learning and PLE Management

2016 ◽  
pp. 253-280
Author(s):  
Cherng-Jyh Yen ◽  
Chih-Hsiung Tu ◽  
Laura E. Sujo-Montes ◽  
Shadow W. J. Armfield ◽  
Junn-Yih Chan
Keyword(s):  
Goal Setting ◽  
Time Management ◽  
Setting Time ◽  
Self Regulation ◽  
Sense Of Control ◽  
Personal Learning ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Task Strategies ◽  
And Task

Is Personal Learning Environment (PLE) a new concept for effective teaching and learning? Shouldn't learning always be personalized and individualized? How may digital technology enhance PLE? Web 2.0 technology integration requires a higher level of self-regulated learning skills to create a PLE. This study examined each of the four aspects of learner self-regulation in online learning (i.e., environment structuring, goal setting, time management, & task strategies) as the predictor for level of initiative and sense of control with regard to PLE widgets management in PLE. This study has concluded that goal setting, time management, and task strategies in self-regulated learning can predict level of initiative in organizing PLE. Furthermore, goal setting and task strategies can predict sense of control in PLE management. Based on the study results, PLE Guidelines are suggested to support educators and learners to build and to manage their PLE.

Learner Self-Regulation and Web 2.0 Tools Management in Personal Learning Environment

2013 ◽  
Vol 8 (1) ◽  
pp. 46-65 ◽  
Author(s):  
Cherng-Jyh Yen ◽  
Chih-Hsiung Tu ◽  
Laura E. Sujo-Montes ◽  
Shadow W. J. Armfield ◽  
Junn-Yih Chan
Keyword(s):  
Goal Setting ◽  
Time Management ◽  
Setting Time ◽  
Self Regulation ◽  
Sense Of Control ◽  
Personal Learning ◽  
Self Regulated Learning ◽  
Personal Learning Environment ◽  
Task Strategies ◽  
And Task

Web 2.0 technology integration requires a higher level of self-regulated learning skills to create a Personal Learning Environment (PLE). This study examined each of the four aspects of learner self-regulation in online learning (i.e., environment structuring, goal setting, time management, & task strategies) as the predictor for level of initiative and sense of control with regard to iGoogle gadgets management in PLE. This study has concluded that goal setting, time management, and task strategies in self-regulated learning can predict level of initiative in organizing PLE. Furthermore, goal setting and task strategies can predict sense of control in PLE management.

scholarly journals Profiles in self-regulated learning in the online learning environment

2010 ◽  
Vol 11 (1) ◽  
pp. 61 ◽  
Author(s):  
Lucy Barnard-Brak ◽  
Valerie Osland Paton ◽  
William Yun Lan
Keyword(s):  
Academic Outcomes ◽  
Time Management ◽  
Help Seeking ◽  
Latent Class ◽  
Setting Time ◽  
Future Research ◽  
Learning Behaviors ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Task Strategies

Individuals who are self-regulated in their learning appear to achieve more positive academic outcomes than individuals who do not exhibit self-regulated learning behaviors. We suggest that distinct profiles of self-regulated learning behaviors exist across learners. In turn, these profiles appear to be associated with significantly different academic outcomes. The purpose of the current study was to examine whether profiles for self-regulated learning skills and strategies exist among learners. To achieve this purpose, we conducted two studies using two different samples. We administered the Online Self-Regulated Learning Questionnaire (OLSQ), a 24-item scale with a 5-point Likert-type response format, to students enrolled in online degree programs at a large, public university located in the Southwestern United States. The OSLQ consists of six subscale constructs, including environment structuring, goal setting, time management, help seeking, task strategies, and self-evaluation. Latent class analyses were performed with participant subscale scores from the OSLQ. Our results indicate the presence of five, distinct profiles of self-regulated learning replicated across both study samples: super self-regulators, competent self-regulators, forethought-endorsing self-regulators, performance/reflection self-regulators, and non- or minimal self-regulators. Results also indicate that individuals differ significantly in their academic achievement according to their profile membership; for example, minimal and disorganized profiles of self-regulated learning are both associated with similar, poorer academic outcomes (e.g., lower GPAs). These profiles in self-regulated learning may be viewed as contributing to the development of theory by elucidating how exactly individuals are and are not self-regulated in their learning. The authors suggest future research directions.

scholarly journals Self-Regulated Learning in the University of Tabuk: Gender Differences in Strategy and Outcomes

2021 ◽  
Vol 4 (1) ◽  
pp. 151-165
Author(s):  
Fakhralddin Abbas Mohammed Elfakki ◽  
Marai Mohammed Alamri ◽  
Islam Ashraful ◽  
Mustafa Elnimeiri ◽  
Ehab Frah
Keyword(s):  
Medical Students ◽  
Time Management ◽  
Help Seeking ◽  
Setting Time ◽  
Self Regulation ◽  
Learning Context ◽  
Self Regulated Learning ◽  
Self Evaluation ◽  
Regulated Learning ◽  
The University

Background Self-Regulated Learning (SRL) is defined as the adjustment of the individual's affective, meta-cognitive, and behavioral operations during learning to attain the desired level of academic achievement. It is an important skill for undergraduate students and its ignorance cause anxious behavior, a sense of potential failure, and avoidance of learning situations. Objective The objective of the study was to explore the pattern of SRL among medical students from a student perspective aiming to recognize the learning context and to provide recommendations for future support strategies. Methods This is a cross-sectional study that targeted a total coverage of medical students at the University of Tabuk, Saudi Arabia using a Self-Regulated Learning Questionnaire which composed of six constructs, namely: environment structuring, goal setting, time management, help-seeking, task strategies, and self-evaluation. An independent-samples test, ANOVA, and post-hoc analysis were conducted.   Results Females agreed on regular practice of the four domains namely: "environmental structuring, time management, help-seeking, and self-evaluation", mean scores: 3.7(SD=1.023), 3.42(SD=1.035), 3.68(SD=0.99), 3.54(SD=0.94) respectively. Conclusion This study identified a remarkable difference in SRL among undergraduate medical students. Females outperformed males in self-regulation; however, both genders in the second year have shown a low level in self-regulation in comparison to fifth year medical students. Rwanda J Med Health Sci 2021;4(1):151-165

scholarly journals Examining Procrastination among University Students through the Lens of the Self-Regulated Learning Model

2020 ◽  
Vol 10 (12) ◽  
pp. 184
Author(s):  
Pierpaolo Limone ◽  
Maria Sinatra ◽  
Flavio Ceglie ◽  
Lucia Monacis
Keyword(s):  
University Students ◽  
Learning Strategies ◽  
Time Management ◽  
Self Regulation ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Academic Settings ◽  
Account Due

Generally considered as a prevalent occurrence in academic settings, procrastination was analyzed in association with constructs such as self-efficacy, self-esteem, anxiety, stress, and fear of failure. This study investigated the role played by self-regulated learning strategies in predicting procrastination among university students. To this purpose, the relationships of procrastination with cognitive and metacognitive learning strategies and time management were explored in the entire sample, as well as in male and female groups. Gender differences were taken into account due to the mixed results that emerged in previous studies. This cross-sectional study involved 450 university students (M = 230; F = 220; Mage = 21.08, DS = 3.25) who completed a self-reported questionnaire including a sociodemographic section, the Tuckman Procrastination Scale, the Time Management Scale, and the Metacognitive Self-Regulation and Critical Thinking Scales. Descriptive and inferential analyses were applied to the data. The main findings indicated that temporal and metacognitive components play an important role in students’ academic achievement and that, compared to females, males procrastinate more due to poor time management skills and metacognitive strategies. Practical implications were suggested to help students to overcome their dilatory behavior.

scholarly journals Goal Setting and MOOC Completion

2019 ◽  
Vol 20 (3) ◽  
Author(s):  
Erwin Handoko ◽  
Susie L. Gronseth ◽  
Sara G. McNeil ◽  
Curtis J. Bonk ◽  
Bernard R. Robin
Keyword(s):  
Goal Orientation ◽  
Student Performance ◽  
Goal Setting ◽  
Time Management ◽  
Causal Attribution ◽  
Course Completion ◽  
Learning Context ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
And Performance

Despite providing advanced coursework online to learners around the world, massive open online courses (MOOCs) have had notoriously low completion rates. Self-regulated learning (SRL) frames strategies that students can use to enhance motivation and promote their engagement, persistence, and performance self-monitoring. Understanding which SRL subprocesses are most relevant to the MOOC learning context can guide course designers and instructors on how to incorporate key SRL aspects into the design and delivery of MOOCs. Through surveying 643 MOOC students using the Online Self-Regulated Learning Questionnaire (OSLQ), the present study sought to understand the differences in the use of SRL between those who completed their course and those who did not. MOOC completers were found to have significantly higher applications of one SRL specific subprocess, namely goal setting. Additional SRL subprocesses of task interest/values, causal attribution, time management, self-efficacy, and goal-orientation also emerged from an analysis of open-ended responses as key contributors to course completion. The findings from this study provide further support regarding the role of SRL in MOOC student performance and offer insight into learners’ perceptions on the importance of SRL subprocesses in reaching course completion.

scholarly journals Exploring self-regulated learning choices in a customisable learning pathway MOOC

2018 ◽  
Vol 34 (1) ◽  
Author(s):  
Matt Crosslin
Keyword(s):  
Course Design ◽  
Learning Experience ◽  
Qualitative Interviews ◽  
Self Regulation ◽  
Learning Preferences ◽  
Educational Process ◽  
Personal Learning ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
The Impact

Open online courses provide a unique opportunity to examine learner preferences in an environment that removes several pressures associated with traditional learning. This mixed methods study sought to examine the pathways that learners will create for themselves when given the choice between an instructor-directed modality and learner-directed modality. Study participants were first examined based on their levels of self-regulated learning. Follow-up qualitative interviews were conducted to examine the choices that participants made, the impact of the course design on those choices, and what role self-regulation played in the process. The resulting analysis revealed that participants desired an overall learning experience that was tailored to personal learning preferences, but that technical and design limitations can create barriers in the learning experience. The results from this research can help shape future instructional design efforts that wish to increase learner agency and choice in the educational process

Supporting Learning Self-Regulation through a PLE

2016 ◽  
pp. 1129-1156
Author(s):  
Iolanda Garcia ◽  
Begoña Gros ◽  
Ingrid Noguera
Keyword(s):  
Lifelong Learning ◽  
Time Management ◽  
Knowledge Society ◽  
Self Regulation ◽  
Self Directed Learning ◽  
Web Based ◽  
Virtual Spaces ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Directed Learning

In the knowledge society, autonomous and Self-Directed Learning (SDL) have become particularly important for professional development and lifelong learning. This kind of learning can take place in physical and virtual spaces that may belong to formal institutions but also to extended communities and networks. In virtual spaces, self-directed learning and self-regulation skills and capacities play an important role in learners' performance. For this reason, it is highly recommended to empower students to design and deploy educational spaces and projects able to fuse formal and informal contexts. The use of Personal Learning Environments (PLEs) can support learners to gain control over their experiences through Web-based tools and a task-orientated environment. It is known that time management is one relevant component of self-regulated learning. There are many Web-based tools that can be used to control time investment and promote planning but little research that takes into account time management in the design and use of PLEs. This chapter describes the results of the Just4me project1, aimed at designing and developing a PLE to support self-regulated learning dealing with time management as an important dimension in lifelong learning. From this perspective, this chapter contributes to the operationalization and analysis of the time factor in online learning regarding time management in self-regulated learning processes supported by PLEs.

Beyond Grades in Online Learning: Adaptive Profiles of Academic Self-Regulation Among Naval Academy Undergraduates

2009 ◽  
Vol 20 (4) ◽  
pp. 568-601 ◽  
Author(s):  
Anthony R. Artino ◽  
Jason M. Stephens
Keyword(s):  
Academic Success ◽  
Self Efficacy ◽  
Self Regulation ◽  
Task Value ◽  
Naval Academy ◽  
Motivational Beliefs ◽  
Achievement Emotions ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
And Task

Educational psychologists have long known that students who are motivated to learn tend to experience greater academic success than their unmotivated counterparts. Using a social cognitive view of self-regulated learning as a theoretical framework, this study explored how motivational beliefs and negative achievement emotions are differentially configured among students in a self-paced online course. Additionally, this study examined how these different motivation-emotion configurations relate to various measures of academic success. Naval Academy undergraduates completed a survey that assessed their motivational beliefs (self-efficacy and task value); negative achievement emotions (boredom and frustration); and a collection of outcomes that included their use of self-regulated learning strategies (elaboration and metacognition), course satisfaction, continuing motivation, and final course grade. Students differed vastly in their configurations of course-related motivations and emotions. Moreover, students with more adaptive profiles (i.e., high motivational beliefs/low negative achievement emotions) exhibited higher mean scores on all five outcomes than their less-adaptive counterparts. Taken together, these findings suggest that online educators and instructional designers should take steps to account for motivational and emotional differences among students and attempt to create curricula and adopt instructional practices that promote self-efficacy and task value beliefs and mitigate feelings of boredom and frustration.

Supporting Learning Self-Regulation through a PLE

2018 ◽  
pp. 1018-1046
Author(s):  
Iolanda Garcia ◽  
Begoña Gros ◽  
Ingrid Noguera
Keyword(s):  
Lifelong Learning ◽  
Time Management ◽  
Knowledge Society ◽  
Self Regulation ◽  
Self Directed Learning ◽  
Web Based ◽  
Virtual Spaces ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Directed Learning

In the knowledge society, autonomous and Self-Directed Learning (SDL) have become particularly important for professional development and lifelong learning. This kind of learning can take place in physical and virtual spaces that may belong to formal institutions but also to extended communities and networks. In virtual spaces, self-directed learning and self-regulation skills and capacities play an important role in learners' performance. For this reason, it is highly recommended to empower students to design and deploy educational spaces and projects able to fuse formal and informal contexts. The use of Personal Learning Environments (PLEs) can support learners to gain control over their experiences through Web-based tools and a task-orientated environment. It is known that time management is one relevant component of self-regulated learning. There are many Web-based tools that can be used to control time investment and promote planning but little research that takes into account time management in the design and use of PLEs. This chapter describes the results of the Just4me project1, aimed at designing and developing a PLE to support self-regulated learning dealing with time management as an important dimension in lifelong learning. From this perspective, this chapter contributes to the operationalization and analysis of the time factor in online learning regarding time management in self-regulated learning processes supported by PLEs.

scholarly journals Online learning in the time of the COVID-19 crisis: Implications for the self-regulated learning of university design students

2021 ◽  
pp. 146978742110512
Author(s):  
Tsai-Yun Mou
Keyword(s):  
Online Learning ◽  
Undergraduate Students ◽  
Time Management ◽  
Setting Time ◽  
Upward Trend ◽  
Self Monitoring ◽  
Self Regulated Learning ◽  
Self Evaluation ◽  
Regulated Learning ◽  
Design Students

This study investigated the intervention of a weekly learning diary on design students’ self-regulated learning in an online learning environment. A total of 54 undergraduate students from an intermediate and an advanced course respectively participated in this study. In a 7-week period of online learning, the students had to complete a course project on their own. Synchronous online learning with the Microsoft Teams program was adopted for students to have real-time learning as well as recordings for after-class reviewing. The results revealed that the structured weekly diary was helpful for the students’ goal setting, time management, self-monitoring, and self-evaluation. Students with clear strategies of time management mostly had better performance. The students had an upward trend of self-monitoring and self-evaluation. Regarding their self-efficacy, the freshman class did not change greatly over time but the senior class steadily built up confidence in online learning and self-regulated learning. Nevertheless, the process and experiences of online self-regulated learning with the intervention of the learning diary influenced the design students to a certain degree.

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