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本科神经科学课堂中利用交互式计算机图形进行学习。

Learning with interactive computer graphics in the undergraduate neuroscience classroom.

作者信息

Pani John R, Chariker Julia H, Naaz Farah, Mattingly William, Roberts Joshua, Sephton Sandra E

机构信息

Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY, 40292, USA,

出版信息

Adv Health Sci Educ Theory Pract. 2014 Oct;19(4):507-28. doi: 10.1007/s10459-013-9483-3. Epub 2014 Jan 22.

Abstract

Instruction of neuroanatomy depends on graphical representation and extended self-study. As a consequence, computer-based learning environments that incorporate interactive graphics should facilitate instruction in this area. The present study evaluated such a system in the undergraduate neuroscience classroom. The system used the method of adaptive exploration, in which exploration in a high fidelity graphical environment is integrated with immediate testing and feedback in repeated cycles of learning. The results of this study were that students considered the graphical learning environment to be superior to typical classroom materials used for learning neuroanatomy. Students managed the frequency and duration of study, test, and feedback in an efficient and adaptive manner. For example, the number of tests taken before reaching a minimum test performance of 90 % correct closely approximated the values seen in more regimented experimental studies. There was a wide range of student opinion regarding the choice between a simpler and a more graphically compelling program for learning sectional anatomy. Course outcomes were predicted by individual differences in the use of the software that reflected general work habits of the students, such as the amount of time committed to testing. The results of this introduction into the classroom are highly encouraging for development of computer-based instruction in biomedical disciplines.

摘要

神经解剖学教学依赖于图形展示和拓展性自主学习。因此,包含交互式图形的计算机辅助学习环境应能促进该领域的教学。本研究在本科神经科学课堂中对这样一个系统进行了评估。该系统采用了自适应探索方法,即在高保真图形环境中的探索与即时测试及重复学习周期中的反馈相结合。本研究的结果是,学生们认为图形化学习环境优于用于学习神经解剖学的典型课堂材料。学生们以高效且自适应的方式管理学习、测试和反馈的频率及时长。例如,在达到至少90%正确的最低测试成绩之前所进行的测试次数,与在更严格的实验研究中所观察到的值非常接近。对于在用于学习断层解剖学的更简单程序和图形更引人注目的程序之间进行选择,学生们的意见存在很大差异。通过反映学生一般学习习惯(如用于测试的时间量)的软件使用上的个体差异,可以预测课程成果。将此引入课堂的结果对于生物医学学科基于计算机的教学发展极具鼓舞作用。

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