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首页> 外文期刊>Community College Journal of Research and Practice >Academic Performance, Age, Gender, and Ethnicity in Online Courses Delivered by Two-Year Colleges
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Academic Performance, Age, Gender, and Ethnicity in Online Courses Delivered by Two-Year Colleges

机译：两年制大学开设的在线课程中的学习成绩，年龄，性别和种族

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This study investigated the effects the demographic variables age, gender, and ethnicity and their interactions had on academic performance in online courses delivered by public two-year colleges in Kentucky. The study controlled for previous academic performance measured by cumulative grade point average (GPA). The study used a random sample (NÂ =Â 320) of all students who had enrolled in at least one online course delivered by the institutions of the Kentucky Community and Technical College System in the spring 2008 semester. A linear hierarchical multiple regression acting as ANCOVA served as the main analysis, with the order entry as follows: cumulative GPA; independent variables (age, gender, ethnicity); interaction vectors; and product vectors. Final course grade served as the dependent variable. The results of the analysis indicated that only cumulative GPA was a significant predictor, explaining approximately 40% of the variance of the final grade. Although differences in final grades were present among the variables age and ethnicity, these differences disappeared when controlling for cumulative GPA. Significance of the results and recommendations for future research are discussed.View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/10668921003744876
机译：这项研究调查了人口变量的年龄，性别和种族及其相互作用对肯塔基州公立两年制大学开设的在线课程的学习成绩的影响。该研究控制了以前的学习成绩，该成绩由累积平均绩点（GPA）衡量。该研究使用了一个随机样本（N = 320），该样本是所有至少参加了2008年春季学期由肯塔基州社区和技术学院系统的机构提供的在线课程的学生的。主要的分析是线性分层多元回归（ANCOVA），顺序输入如下：累积GPA；独立变量（年龄，性别，种族）；相互作用载体和乘积向量。最终课程成绩作为因变量。分析结果表明，只有累积GPA才是重要的预测指标，可以解释最终成绩的40％左右。尽管年龄和种族变量之间存在最终成绩差异，但在控制累积GPA时，这些差异消失了。讨论了结果的重要性和对未来研究的建议。 ，google，更多“，pubid：” ra-4dff56cd6bb1830b“};添加到候选列表链接永久链接http://dx.doi.org/10.1080/10668921003744876

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