What are the most important predictors of computer science students' online help-seeking behaviors?

被引：37
|
作者：
Hao, Qiang [1 ,2 ]
Wright, Ewan [3 ]
Barnes, Brad [4 ]
Branch, Robert Maribe [1 ]
机构：
[1] Univ Georgia, Learning Design & Technol, 850 Coll Stn Rd, Athens, GA 30602 USA
[2] Univ Georgia, Comp Sci, 850 Coll Stn Rd, Athens, GA 30602 USA
[3] Univ Hong Kong, Policy Adm & Social Sci Educ, 401 Runme Shaw Bldg,Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China
[4] Univ Georgia, Comp Sci, Boyd Grad Studies Res Ctr 415, Athens, GA 30602 USA
来源：
COMPUTERS IN HUMAN BEHAVIOR | 2016年 / 62卷
关键词：
Online help seeking; Important predictors; Online searching; Asking peers online for help; Cross-validation; UNIVERSITY-STUDENTS; SELF-REGULATION; GRADUATE-STUDENTS; ACHIEVEMENT; INFORMATION; STRATEGIES; MOTIVATION; NOVICE; SCHOOL; GOALS;
D O I：
10.1016/j.chb.2016.04.016
中图分类号：
B84 [心理学];
学科分类号：
04 ; 0402 ;
摘要：
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. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码：467 / 474
页数：8
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