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R., Akila Devi T.; Sathick, K. Javubar; Khan, A. Abdul Azeez; Raj, L. Arun – International Journal of Web-Based Learning and Teaching Technologies, 2021
Non-Factoid Question Answering (QA) is the next generation of textual QA systems, which gives passage level summaries for a natural language query, posted by the user. The main issue lies in the appropriateness of the generated summary. This paper proposes a framework for non-factoid QA system, which has three main components: (1) a deep neural…
Descriptors: Natural Language Processing, Artificial Intelligence, Classification, Responses
Marcel Mierwald – Journal of Educational Media, Memory and Society, 2024
Generative artificial intelligence (AI) offers new opportunities for history education, such as the ability to chat with historical figures. However, little is known about pupils' interaction with AI applications such as ChatGPT. A qualitative case study was conducted to explore how pupils (n = 21, year nine, fourteen years old) interacted with…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, History Instruction
Baral, Sami; Botelho, Anthony; Santhanam, Abhishek; Gurung, Ashish; Cheng, Li; Heffernan, Neil – International Educational Data Mining Society, 2023
Teachers often rely on the use of a range of open-ended problems to assess students' understanding of mathematical concepts. Beyond traditional conceptions of student open-ended work, commonly in the form of textual short-answer or essay responses, the use of figures, tables, number lines, graphs, and pictographs are other examples of open-ended…
Descriptors: Mathematics Instruction, Mathematical Concepts, Problem Solving, Test Format
McCarthy, Kathryn S.; Allen, Laura K.; Hinze, Scott R. – Grantee Submission, 2020
Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…
Descriptors: Reading Comprehension, Prediction, Responses, College Students
Katie Lai – College & Research Libraries, 2023
To explore whether artificial intelligence can be used to enhance library services, this study used ChatGPT to answer reference questions. An assessment rubric was used to evaluate how well ChatGPT handled different question types and difficulty levels. Overall ChatGPT's performance was fair, but it did poorly in information accuracy. It scored…
Descriptors: Artificial Intelligence, Technology Uses in Education, Library Services, Reference Services
Mazumder, Sahisnu – ProQuest LLC, 2021
Dialogue systems, commonly called as Chatbots, have gained escalating popularity in recent times due to their wide-spread applications in carrying out chit-chat conversations with users and accomplishing tasks as personal assistants. These systems are typically trained from manually-labeled data and/or written with handcrafted rules and often, use…
Descriptors: Computer Mediated Communication, Computer Software, Dialogs (Language), Information Seeking