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.

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.

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 Cultivating Self-Regulated Learning in Flipped EFL Courses: A Model for Course Design

2021 ◽  
Vol 23 (2) ◽  
pp. 20-36
Author(s):  
Ünal Çakıroğlu ◽  
Mücahit Öztürk
Keyword(s):  
Foreign Language ◽  
Learning Strategies ◽  
Time Management ◽  
Help Seeking ◽  
Flipped Classroom ◽  
Course Design ◽  
Testing Time ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Student Centred Learning

AbstractConsiderable effort has been invested in innovative learning practices in English Foreign Language courses (EFL) in universities. Flipped classroom model transforms passive listeners into active learners in school and home activities pace. Flipped classroom model and the foreign language teaching methods are student-centred learning environments in which students should have a certain level of self-regulated learning skills. The study suggest a model for flipped classroom implementations with regard to self-regulated learning strategies in order to keep students more active in the EFL courses. Students were allowed to apply goal setting and planning, rehearsing, help seeking, monitoring, testing, time management, organising, regulating and note taking strategies within the model in online and face to face sessions. We hope the suggested model can contribute to improve listening, reading, writing and speaking skills of students in EFL courses.

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 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.

scholarly journals Systematic literature review on self-regulated learning in massive open online courses

2019 ◽  
Vol 35 (1) ◽  
Author(s):  
Daeyeoul Lee ◽  
Sunnie Lee Watson ◽  
William R Watson
Keyword(s):  
Goal Setting ◽  
Help Seeking ◽  
Online Courses ◽  
The Body ◽  
Massive Open Online Courses ◽  
Future Research ◽  
Massive Open Online ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Regulation Strategies

Despite arguments about the importance of self-regulated learning (SRL) in massive open online courses (MOOCs) (Terras & Ramsay, 2015), understanding of the topic is limited. This study offers a systematic review of empirical research on SRL in MOOCs. It revealed that the body of literature on SRL in MOOCs has grown from 2014 to 2016. The content analysis findings show that SRL was a factor positively influencing learning in MOOCs. SRL strategies were identified, including motivational regulation strategies, specifically self-efficacy, task value, and goal setting. Particular cognitive regulation strategies were not identified, and goal setting was found as a metacognitive regulation strategy. Regarding behavioural and contextual regulation strategies, help seeking, time management, and effort regulation were identified. In addition, several MOOC designs and SRL interventions that consider unique characteristics of MOOCs were proposed to promote SRL. Implications of these findings and future research are discussed.

Adaptation and Validation of a Chinese Online Self-Regulated Learning Questionnaire

2021 ◽  
pp. 073428292110599
Author(s):  
Kit-Ling Lau
Keyword(s):  
Secondary Students ◽  
Time Management ◽  
Help Seeking ◽  
Factor Model ◽  
Self Regulated Learning ◽  
Self Evaluation ◽  
Measurement Models ◽  
Regulatory Strategies ◽  
Monitoring Strategies ◽  
Regulated Learning

This study aimed to adapt and validate a Chinese version of the online self-regulated learning questionnaire (COSLQ) with Chinese junior secondary students in Hong Kong. A total of 716 students from six schools participated voluntarily in the study. Overall, the findings of this study supported the COSLQ’s psychometric quality. The COSLQ subscales all demonstrated high internal consistency. Different measurement models were tested using confirmatory factor analysis. The results indicated that a 7-factor model best fit the data, suggesting that the participants could distinguish seven types of online self-regulatory strategies: goal setting, environment structuring, time management, effort regulation, cognitive/monitoring strategies, help seeking, and self-evaluation.

scholarly journals Self-Regulated Learning in Flipped Classrooms: A Systematic Literature Review

2020 ◽  
Vol 10 (11) ◽  
pp. 848-853
Author(s):  
Rasheed Abubakar Rasheed ◽  
◽  
Amirrudin Kamsin ◽  
Nor Aniza Abdullah ◽  
Habeebah Adamu Kakudi ◽  
...  
Keyword(s):  
Help Seeking ◽  
Instructional Strategy ◽  
Flipped Classroom ◽  
Self Regulation ◽  
Future Research ◽  
Online Help ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Flipped Classrooms ◽  
Regulation Strategies

The flipped classroom is considered an instructional strategy and a type of blended learning instruction that focused on active learning and student engagement. Over the years, flipped classroom studies have focused more on the advantages and challenges of flipped instruction and its effectiveness, but little is known about the state of self-regulation in flipped classrooms. This study investigates the self-regulation strategies as well as the supports proposed for self-regulated learning in flipped classrooms. Findings show that relatively few studies have focused on self-regulated learning in flipped classrooms compared to the overall research and publication productivity in flipped classrooms. Also, the existing solutions and supports have only focused on either self-regulation or online help-seeking, but have not focused on other specific types of self-regulation strategies. Our study proposed some future research recommendations in flipped classrooms.

scholarly journals Does Mode of Access Make a Difference? Mobile Learning and online student engagement

2021 ◽  
Vol 25 (3) ◽  
Author(s):  
Sarah Nichter
Keyword(s):  
Student Engagement ◽  
Student Success ◽  
Mobile Learning ◽  
Time Management ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Research Questions ◽  
Task Strategies ◽  
Device Use ◽  
Management Behaviors

Even though student use of mobile devices for educational purposes has increased in recent years, the research on the possible impact on student success or engagement has been minimal. This study investigated the impact of mobile device use on student engagement and student success in online courses. The theory of Self-Regulated Learning (SRL) was a foundation for understanding and measuring engagement behaviors of online students. The Online Self-Regulated Learning Questionnaire (OSLQ) was the basis of the survey instrument. Participants were categorized into three groups of mobile device use (low, moderate, high). These three groups were used for comparison in each of the research questions. The research questions ask what impacts mobile learning has on student engagement, as measured with SRL; what impact mobile learning has on the SRL constructs of environment structuring, task management, and time management; and what associations mobile learning might have with student success and persistence. The ANOVA showed that mobile learning had a moderate impact on engagement for students in the high group. Students in each group engaged in environment structuring behaviors more than task strategies or time management behaviors. Students in the moderate and high groups engaged in task strategies more than the low group. Students in the high group engaged in time management behaviors more than the other groups.  The Crosstab analysis did not show an association between levels of mobile learning and course grade or persistence. These findings have positive implications for online pedagogy and course design.              Keywords: Mobile Learning; online learning; student engagement; Self-Regulated Learning; student success

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