当前位置: X-MOL 学术Open Praxis › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Personalizing Feedback Using Voice Comments
Open Praxis Pub Date : 2018-12-28 , DOI: 10.5944/openpraxis.10.4.909
Kjrsten Keane , Daniel McCrea , Miriam Russell

While text-based feedback is normally used by college instructors to help students improve their written assignments, it is important to consider using voice comment tools for further personalization. New and easily-accessible technologies provide this option. Our study focused on surveying undergraduates who received voice comments on their written assignments. Students were queried on their preferences for feedback delivery and survey questions probed student responses both quantitatively and qualitatively. Two voice comment tools were used: Adobe Acrobat Reader and Kaizena voice comments. Results showed the majority (66.7%) of students surveyed preferred the addition of voice comment feedback over written comments alone. Appendices supply tool information, full data sets and extensive student commentary regarding their experience after receiving voice comments.

中文翻译:

使用语音评论个性化反馈

高校教师通常使用基于文本的反馈来帮助学生改善书面作业,但重要的是要考虑使用语音注释工具进行进一步的个性化设置。易于使用的新技术提供了此选项。我们的研究重点是调查那些收到书面作业语音评论的大学生。向学生询问他们对反馈的偏爱,并通过调查问题定量和定性地调查学生的回答。使用了两种语音注释工具:Adobe Acrobat Reader和Kaizena语音注释。结果显示,大部分接受调查的学生(66.7%)倾向于添加语音评论而不是书面评论。附录提供了工具信息,
更新日期:2018-12-28
down
wechat
bug