|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|348235||618170||2015||16 صفحه PDF||سفارش دهید||دانلود رایگان|
این مقاله ISI می تواند منبع ارزشمندی برای تولید محتوا باشد.
- تولید محتوا برای سایت و وبلاگ
- تولید محتوا برای کتاب
- تولید محتوا برای نشریات و روزنامه ها
پایگاه «دانشیاری» آمادگی دارد با همکاری مجموعه «شهر محتوا» با استفاده از این مقاله علمی، برای شما به زبان فارسی، تولید محتوا نماید.
• Students' knowledge and regulation of attention in online learning are investigated.
• Five online learning profiles are derived from knowledge and regulation of attention.
• Profiles differ in ISE, search strategies, achievement, and time spent on Internet.
• Both knowledge and regulation are required to ensure performance in learning.
• Suggestions are made to foster attention by understanding and regulating attention.
The Internet has become a major platform for learning in higher education. Besides rich informational resources, however, the Internet offers an abundance of distractors that challenge students' attention. This study investigated university students' perceived attention state and use of regulatory strategies using the Online Learning Motivated Attention and Regulatory Strategies scale (OL-MARS). Participants were 230 undergraduate and graduate students recruited from two universities located in central and northern Taiwan. The exploratory factor analysis revealed four subscales in the OL-MARS, including perceived attention discontinuity, social media notification, behavioral strategies, and mental strategies. Results showed that mental and behavioral strategies were positively associated with criterion variables, including Internet self-efficacy, online search strategies, and final course grades, but negatively correlated with time spent on the Internet and social media. Whereas, perceived attention discontinuity and social media notification mostly had a modest correlational relationship with these validating variables in an opposite direction. Cluster analysis identified five types of profiles: the Motivated Strategic, the Unaware, the Hanging On, the Non-Responsive and the Self-Disciplined. Group membership exhibited mean differences in Internet self-efficacy, online search strategies, final course grades, and time spent on the Internet and social media. The study results validated the constructs in meta-attention for theory development, provided the OL-MARS scale as an effective meta-attention measurement tool to assess university students’ knowledge of attention and regulation of attention, and proposed the specific intervention and attention regulation training for each profile group.
Journal: Computers & Education - Volume 89, November 2015, Pages 75–90