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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
Geden, Michael; Emerson, Andrew; Carpenter, Dan; Rowe, Jonathan; Azevedo, Roger; Lester, James – International Journal of Artificial Intelligence in Education, 2021
Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…
Descriptors: Game Based Learning, Middle School Students, Microbiology, Secondary School Science
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
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Crossley, Scott; Kyle, Kristopher; Davenport, Jodi; McNamara, Danielle S. – International Educational Data Mining Society, 2016
This study introduces the Constructed Response Analysis Tool (CRAT), a freely available tool to automatically assess student responses in online tutoring systems. The study tests CRAT on a dataset of chemistry responses collected in the ChemVLab+. The findings indicate that CRAT can differentiate and classify student responses based on semantic…
Descriptors: Intelligent Tutoring Systems, Chemistry, Natural Language Processing, High School Students
Zehner, Fabian; Goldhammer, Frank; Lubaway, Emily; Sälzer, Christine – Education Inquiry, 2019
In 2015, the "Programme for International Student Assessment" (PISA) introduced multiple changes in its study design, the most extensive being the transition from paper- to computer-based assessment. We investigated the differences between German students' text responses to eight reading items from the paper-based study in 2012 to text…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
Jackson, G. Tanner; Castellano, Katherine E.; Brockway, Debra; Lehman, Blair – Journal of Research on Technology in Education, 2018
Open-ended, short-answer questions, referred to as constructed responses (CR), allow students to express knowledge and skills through their own words. While CRs can reduce the likelihood of guessing correct answers, they also enable students to provide errant responses due to a lack of knowledge or a misunderstanding of the question.…
Descriptors: Responses, Cognitive Processes, Alternative Assessment, Prompting
Zehner, Fabian; Sälzer, Christine; Goldhammer, Frank – Educational and Psychological Measurement, 2016
Automatic coding of short text responses opens new doors in assessment. We implemented and integrated baseline methods of natural language processing and statistical modelling by means of software components that are available under open licenses. The accuracy of automatic text coding is demonstrated by using data collected in the "Programme…
Descriptors: Educational Assessment, Coding, Automation, Responses
Quixal, Martí; Meurers, Detmar – CALICO Journal, 2016
The paper tackles a central question in the field of Intelligent Computer-Assisted Language Learning (ICALL): How can language learning tasks be conceptualized and made explicit in a way that supports the pedagogical goals of current Foreign Language Teaching and Learning and at the same time provides an explicit characterization of the Natural…
Descriptors: Computer Assisted Instruction, Educational Technology, Second Language Instruction, Natural Language Processing
Bejar, Isaac I.; VanWinkle, Waverely; Madnani, Nitin; Lewis, William; Steier, Michael – ETS Research Report Series, 2013
The paper applies a natural language computational tool to study a potential construct-irrelevant response strategy, namely the use of "shell language." Although the study is motivated by the impending increase in the volume of scoring of students responses from assessments to be developed in response to the Race to the Top initiative,…
Descriptors: Responses, Language Usage, Natural Language Processing, Computational Linguistics
Moffitt, Kevin Christopher – ProQuest LLC, 2011
The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…
Descriptors: Cues, Verbs, Natural Language Processing, Discriminant Analysis