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Exploring Factors That Influence Computer Science Introductory Course Students To Persist In The Major

机译:探索影响计算机科学入门课程学生坚持专业的因素

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This paper describes an exploratory study to identify which environmental and student factors best predict intention to persist in the computer science major. The findings can be used to make decisions about initiatives for increasing retention. Eight indices of student characteristics and perceptions were developed using the research-based Student Experience of the Major Survey: student-student interaction; student-faculty interaction; collaborative learning opportunities; pace/workload/prior experience with programming; teaching assistants; classroom climate/pedagogy; meaningful assignments; and racism/sexism. A linear regression revealed that student-student interaction was the most powerful predictor of students' intention to persist in the major beyond the introductory course. Other factors predicting intention to persist were pace/workload/prior experience and male gender. The findings suggest that computer science departments interested in increasing retention of students set structured expectations for student-student interaction in ways that integrate peer involvement as a mainstream activity rather than making it optional or extracurricular. They also suggest departments find ways to manage programming experience gaps in CS1.
机译:本文介绍了一项探索性研究,以确定哪些环境因素和学生因素最能预测计算机科学专业的持续学习意图。研究结果可用于制定有关增加保留率的计划的决策。使用基于调查的主要调查学生经验,开发出八个学生特征和知觉的指标:学生与学生的互动;师生互动;合作学习机会;进度/工作量/编程经验;教学助理;课堂气氛/教学法;有意义的任务;和种族主义/性别歧视。线性回归显示,学生与学生的互动是学生在入门课程之外继续攻读专业的最有力预测指标。预测坚持意愿的其他因素是步调/工作量/以前的经历和男性。研究结果表明,对增加学生保留率感兴趣的计算机科学系通过将同伴参与作为主流活动,而不是使其成为可选活动或课外活动,为学生与学生的互动树立了结构化的期望。他们还建议部门找到解决CS1中编程经验差距的方法。

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