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Mishra, Swaroop – ProQuest LLC, 2023
Humans have the remarkable ability to solve different tasks by simply reading textual instructions that define the tasks and looking at a few examples. Natural Language Processing (NLP) models built with the conventional machine learning paradigm, however, often struggle to generalize across tasks (e.g., a question-answering system cannot solve…
Descriptors: Natural Language Processing, Models, Readability, Mathematical Logic
DeKita G. Moon Rembert – ProQuest LLC, 2021
Many students may find math word problems uninteresting; therefore, lacking the motivation to solve them. The content in most math word problems in use today is outdated, deliberately generic, and does not fully engage students. The development of technologies that personalize math word problems seeks to improve the engagement of students.…
Descriptors: Word Problems (Mathematics), Student Interests, Learner Engagement, Educational Technology
Allen, Laura – ProQuest LLC, 2017
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the writing literature. Research suggests that higher quality writing is…
Descriptors: Writing Skills, Reader Text Relationship, Natural Language Processing, Linguistic Performance
Product and Process Perspectives: an Empirical Study of Explicitation in Chinese-English Translation
Fan, Zhewei – ProQuest LLC, 2012
Product-and process-oriented, this dissertation focuses on both the explicitness in translated texts and the implementation of explicitation in Chinese-English translation. In doing so, it provides a new cognitive framework for understanding explicitation as a strategic process. A specially designed study of the translation process facilitates the…
Descriptors: English, Chinese, Translation, Language Research