英语视听说课程教学的思考

本文从教学安排、学生自身、教师三方面对当前英语视听说课程教学中存在的几个问题进行思考，旨在提高学生的听力水平，提高教学质量。     

试论如何提高大学英语听力教学的效果

本文针对目前大学英语听力教学效果不佳的现状,提出英语教师应该弥补平时教室教学中的一些缺陷,并以听力理解的一些基本理论为基础,科学有效的开展语音室教学,从而提高学生的听力理解能力。     

高职院校写作教学浅议

根据高职院语课写作教学要求与培养目标,针对写作教学中存在的种种认识误区,要提倡“积累—领悟—创新”的写作教学。     

大学一年级新生英语学习的困难及对策

作通过调查认为大学一年级新生英语学习的困难主要集中在词汇、听力和口语上。章分析了造成这三方面困难的原因，并提出了相应的教学对策。     

听力课DFI 教学法

根据英语听力理解在认知、语言等方面的固有特点,提出了针对英语专业低年级英语听力的DFI(Differentiation Facilitation Integration,即分层教学)听力教学法,即针对不同听力水平的学生设计不同的任务,教师给予听力策略上的指导和训练,综合听力、口语两项技能的英语听力综合教学法,同时具体介绍了该教学法的设计和实践过程。     

面向垂直领域的阅读理解数据增强方法

阅读理解问答系统是利用语义理解等自然语言处理技术,根据输入问题,对非结构化文档数据进行分析,生成一个答案,具有很高的研究和应用价值。在垂直领域应用过程中,阅读理解问答数据标注成本高且用户问题表达复杂多样,使得阅读理解问答系统准确率低、鲁棒性差。针对这一问题,该文提出一种面向垂直领域的阅读理解问答数据的增强方法,基于真实用户问题,构造阅读理解训练数据,一方面降低标注成本,另一方面增加训练数据多样性,提升模型的准确率和鲁棒性。该文用汽车领域数据对本方法进行实验验证,其结果表明,该方法对垂直领域中阅读理解模型的准确率和鲁棒性均得到有效提升。     

The segmented presentation of visually structured texts: Effects on text comprehension

The effects of a segmented presentation applied to a visually structured text were examined in the context of the explosion of small-screen devices. Empirical research investigating the influence of text signaling on text processing suggests that the text visual structure may influence comprehension by facilitating the construction of a coherent text representation. Undergraduate students were asked to read a text under different segmented conditions varying on the type of information provided about the text visual structure and on the segmentation unit. When the segmented presentation did not supply any information or when it only offered local information about the text visual structure, text comprehension depended on the segmentation unit. When the segmentation unit did not fit the text visual structure, an erroneous text representation was constructed, whereas the compatible segmentation unit led to a correct text comprehension. When the segmented presentation rendered the global text visual structure, the segmentation unit had no effect on comprehension and more readers constructed a correct and close text representation. Thus, the text visual structure seems to play a role in text comprehension and this role has to be taken into account for text segmented presentation.     

The effects of the number of links and navigation support on cognitive load and learning with hypertext: The mediating role of reading order

Problems in learning with hypertext systems have been claimed to be caused by high levels of disorientation and cognitive load. This was recognized by DeStefano and LeFevre [DeStefano, D., & LeFevre, J. -A., (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23(3), 1616–1641.] who predicted an increase of cognitive load and impairment of learning for hypertexts with a higher number of links per page. From a practical perspective, several navigation support techniques, such as providing link suggestions, have been proposed for guiding learners and reducing cognitive overload. In an experiment, we tested DeStefano and LeFevre’s predictions as well as the usefulness of link suggestions. Participants used different versions of a hypertext, either with 3-links or 8-links per page, presenting link suggestions or not. We tested their cognitive load and learning outcomes. Results showed that there was a benefit of using link suggestions for learning, but no effect of number of links on learning was found. Moreover, the effects of our manipulations on cognitive load were mediated by the reading order that participants selected. Implications for research and the design of navigation support systems are discussed.     

基于框架语义的高考语文阅读理解答案句抽取

高考语文阅读理解问答相对普通阅读理解问答难度更大,问句抽象表述的理解需要更深层的语言分析技术,答案候选句抽取更注重与问句的关联分析,答案候选句排序更注重答案句之间的语义相关性。为此,该文提出借助框架语义匹配和框架语义关系抽取答案候选句,在排序时引入流形排序模型,通过答案句之间的框架语义相关度将排序分数进行传播,最终选取分数较高的Top-4作为答案句。在北京近12年高考语文阅读理解问答题上的准确率与召回率分别达到了53.65%与79.06%。     

基于视频描述和阅读理解的视频问答研究

针对大多数视频问答(VideoQA)模型将视频和问题嵌入到同一空间进行答案推理所面临的多模态交互困难、视频语义特征保留能力差等问题,提出了一种视频描述机制来获得视频语义特征的文本表示,从而避免了多模态的交互.提出方法将视频特征通过描述机制得到相应的视频描述文本,并将描述文本特征与问题特征进行阅读理解式的交互与分析,最后推理出问题的答案.在MSVD-QA以及MSRVTT-QA数据集上的测试结果显示,提出问答模型的回答准确率较现有模型均有不同程度的提升,说明所提方法能更好地完成视频问答任务.