Toward deep learning for adult students in online courses

被引:104
|
作者
Ke, Fengfeng [1 ]
Xie, Kui [2 ]
机构
[1] Univ New Mexico, Coll Educ, Albuquerque, NM 87131 USA
[2] Mississippi State Univ, Mississippi State, MS 39762 USA
来源
INTERNET AND HIGHER EDUCATION | 2009年 / 12卷 / 3-4期
关键词
Online learning; Adult students; Online course design; Deep learning; Content analysis; HIGHER-EDUCATION; AGE;
D O I
10.1016/j.iheduc.2009.08.001
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Adult students have become the new majority in online distance education. Research in online distance education, however, is still predominantly based on the historical perspective of the traditional student profile. This study examines adult students' learning engagement in online courses and explores the impact of online course design models and the type of online discussion on adult students' self-perceived and observable learning performance. The study findings inform that age itself does not predict adult students' learning satisfaction and performance. instead, an integrated course model promotes learning satisfaction, while a Content+Support course model reinforces knowledge-constructive online interactions. The study findings also indicate disadvantages of close-ended discussion tasks in supporting students' online learning success. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:136 / 145
页数:10
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