خودتنظیمی آنلاین دانش آموزان بزرگسال
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خودتنظیمی آنلاین دانش آموزان بزرگسال

عنوان فارسی مقاله: تجزیه و تحلیل پروفایل پنهان از خودتنظیمی آنلاین دانش آموزان بزرگسال در محیط های آموزشی ترکیبی
عنوان انگلیسی مقاله: A latent profile analysis of adult students’ online self-regulation in blended learning environments
مجله/کنفرانس: نقش کامپیوتر در رفتار انسان – Computers in Human Behavior
رشته های تحصیلی مرتبط: مدیریت، علوم تربیتی
گرایش های تحصیلی مرتبط: مدیریت دانش، تکنولوژی آموزشی
کلمات کلیدی فارسی: انگیزه پیشرفت، آموزش بزرگسالان، یادگیری ترکیبی، تجزیه و تحلیل پروفایل پنهان، یادگیری خودتنظیم آنلاین
کلمات کلیدی انگلیسی: Achievement motivation، Adult education، Blended learning، Latent profile analysis، Online self-regulated learning
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.chb.2019.05.021
دانشگاه: Department of Educational Sciences, Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 5.876 در سال 2018
شاخص H_index: 137 در سال 2019
شاخص SJR: 1.711 در سال 2018
شناسه ISSN: 0747-5632
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 11
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: دارد
کد محصول: E13641
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1. Introduction


2. Theoretical background


3. Present research


4. Methods


5. Results


6. Discussion


7. Conclusion


Acknowledgements


References

نمونه متن انگلیسی مقاله

Abstract


Self-regulated learning (SRL) is crucial for academic success; therefore support, to enhance and maintain SRL skills is important. In blended adult education, the heterogeneity of adults creates diversity in SRL abilities, which makes it necessary to provide tailored support. Conducting latent profile analyses for a sample of 213 blended adult students, we identified three profiles, namely high, low, and moderate SRL profiles which prove differences in SRL strategy use and imply tailored SRL support. Through multivariate analysis of variance (MANOVA) and multinomial logistic regression, we further explore the differences in SRL between the profiles and the extent to which the students’ personal background characteristics and achievement motivations predict their profile membership. The three profiles differ significantly in terms of the scores of all SRL subscales. Furthermore, only achievement motivation – more specifically, attainment and utility value – predicts profile membership. These results inform educational practice about opportunities for supporting and enhancing SRL skills. Anticipating attainment and utility value, time management, and collaboration with peers are all recommended. More specifically, teachers can, for example, use authentic tasks and examples during the learning process or be a role model regarding online interaction and information sharing.


Introduction


Blended learning environments combine face-to-face and online learning activities that are meant to complement each other (Boelens, Van Laer, De Wever, & Elen, 2015). These environments allow students considerable autonomy, which requires self-regulated learning (SRL) for individuals to succeed (Peverly, Brobst, Graham, & Shaw, 2003). Although blended learning environments are autonomous, tailored support for adult students in developing and maintaining their SRL skills should be provided. Since adult students are heterogeneous regarding their previous life, work, and educational experiences, they are diverse in their SRL skills (Barnard-Brak, Lan, & Paton, 2010), which makes a one-size-fits-all approach insufficient for supporting adult students. Optimisation and personalisation of the support of students is crucial for their learning (Authors, 2018b). To adjust the support they provide, teachers should have a clear perspective on students’ current SRL. However, creating a rich assessment of adult students’ SRL in blended learning environments is challenging because (1) existing research on the SRL of adult students in blended learning environments and how to support it is lacking, (2) research on SRL of students in contexts other than blended adult education is not generalisable to blended adult education due to the context specificity of SRL, and (3) in blended learning environments, teachers have limited time to observe their students individually. While blended learning environments allow for the individualisation of education and support, it can become challenging to provide individualised SRL support for each student considering the teachers’ time and effort required to do so. The current study consequently examines how to support teachers in gaining information about their students’ individual SRL needs in order to provide personalised support at an achievable level.

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