از مهم ترین پیش بینی کننده رفتار کمک طلبی آنلاین دانشجویان علوم کامپیوتر چه هستند؟
What are the most important predictors of computer science students' online help-seeking behaviors?
نویسندگان |
این بخش تنها برای اعضا قابل مشاهده است ورودعضویت |
اطلاعات مجله |
www.journals.elsevier.comcomputers-in-human-behavior |
سال انتشار |
September 2016 |
فرمت فایل |
PDF |
کد مقاله |
3239 |
پس از پرداخت آنلاین، فوراً لینک دانلود مقاله به شما نمایش داده می شود.
چکیده (انگلیسی):
This study investigates the most important predictors of computer science students’ online help-seeking behaviors. 203 computer science students from a large university in southeastern United States participated in the study. Online help-seeking behaviors explored in this study include online searching, asking teachers online for help, and asking peers online for help. Ten-fold cross validation was used to select the most significant predictors from eight potential factors, including prior knowledge of the learning subject, learning proficiency level, academic performance, epistemological belief, interests, problem difficulty, age and gender. Problem difficulty was selected as the most important predictor for all three types of online help seeking, while learning proficiency level, academic performance, and epistemological belief were selected as the most important predictors for both online searching and asking teachers online for help. Based on the selected factors and their relationships with online help seeking, the study provides guidance on targeted training for online help seeking in an era of mass higher education.
کلمات کلیدی مقاله (فارسی):
به دنبال کمک آنلاین. پیش بینی مهم است؛ جستجوی آنلاین. درخواست کمک آنلاین برای همسالان. اعتبار سنجی متقابل
کلمات کلیدی مقاله (انگلیسی):
Online help seeking; Important predictors; Online searching; Asking peers online for help; Cross-validation
پس از پرداخت آنلاین، فوراً لینک دانلود مقاله به شما نمایش داده می شود.