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Suarez, Susan R. – ProQuest LLC, 2022
This action research study's primary purpose was to explore student and instructor experiences of chatbot use in online and hybrid undergraduate English composition courses. This qualitative study used structured and open-ended survey questions, interviews, and chat transcripts to collect data. The collaboration process among researcher and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Electronic Learning
Tansomboon, Charissa – ProQuest LLC, 2017
Students studying complex science topics can benefit from receiving immediate, personalized guidance. Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student…
Descriptors: Middle School Students, Secondary School Science, Science Education, Science Instruction
El-Arini, Khalid – ProQuest LLC, 2013
We live in an era of information overload. From online news to online shopping to scholarly research, we are inundated with a torrent of information on a daily basis. With our limited time, money and attention, we often struggle to extract actionable knowledge from this deluge of data. A common approach for addressing this challenge is…
Descriptors: Information Management, Electronic Learning, Data Collection, Privacy
Rajkumar, Rajakrishnan – ProQuest LLC, 2012
Natural Language Generation (NLG) is the process of generating natural language text from an input, which is a communicative goal and a database or knowledge base. Informally, the architecture of a standard NLG system consists of the following modules (Reiter and Dale, 2000): content determination, sentence planning (or microplanning) and surface…
Descriptors: Natural Language Processing, Linguistics, Language Processing, Models
Morris, Mitchell J. – ProQuest LLC, 2012
Quickly accessing the contents of a video is challenging for users, particularly for unstructured video, which contains no intentional shot boundaries, no chapters, and no apparent edited format. We approach this problem in the domain of lecture videos though the use of machine learning, to gather semantic information about the videos; and through…
Descriptors: Heuristics, Electronic Learning, Video Technology, Computer Interfaces