Abstract

This study investigated how computer agents’ language style affects summary writing in an Intelligent Tutoring System, called CSAL AutoTutor. Participants interacted with two computer agents in one of three language styles: (1) a formal language style, (2) an informal language style, and (3) a mixed language style. Primary results indicated that participants improved the quality of summary writing, spent less time writing summaries, and had lower syntactic complexity but more non-narrative summaries on posttest than pretest. However, this difference was not affected by the discourse formality that agents used during instruction. Results also showed participants rated peer summaries more accurately for cause/effect texts in the formal and mixed conditions, but generated summaries with lower referential cohesion in the informal condition on posttest than pretest.

摘要

这项研究调查了计算机代理的语言风格如何影响称为CSAL AutoTutor的智能辅导系统中的摘要写作。参与者以两种语言风格中的一种与两个计算机代理进行交互：（1）正式语言风格；（2）非正式语言风格；（3）混合语言语言风格。初步结果表明，参与者提高了总结写作的质量，花了更少的时间来编写总结，语法复杂度更低，但与前测相比，后测的非叙事总结更多。但是，这种差异不受代理在教学过程中所使用的话语形式的影响。结果还显示，参与者在正式和混合条件下对因果关系文本的同行总结进行了更准确的评分，但在非正式条件下的后继测试结果比预测试的参考凝聚力低。