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Showing 1 to 15 of 24 results Save | Export
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Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
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Xue Wang; Gaoxiang Luo – Society for Research on Educational Effectiveness, 2024
Background: Despite the usefulness of systematic reviews and meta-analyses, they are time-consuming and labor-intensive (Michelson & Reuter, 2019). The technological advancements in recent years have led to the development of tools aimed at streamlining the processes of systematic reviews and meta-analyses. Innovations such as Paperfetcher…
Descriptors: Meta Analysis, Artificial Intelligence, Computational Linguistics, Computer Software
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C. H., Dhawaleswar Rao; Saha, Sujan Kumar – IEEE Transactions on Learning Technologies, 2023
Multiple-choice question (MCQ) plays a significant role in educational assessment. Automatic MCQ generation has been an active research area for years, and many systems have been developed for MCQ generation. Still, we could not find any system that generates accurate MCQs from school-level textbook contents that are useful in real examinations.…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Automation, Test Items
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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Shahzad, Areeba; Wali, Aamir – Education and Information Technologies, 2022
Checking essays written by students is a very time consuming task. Besides spellings and grammar, they also need to be evaluated on their semantic content such as cohesion, coherence, etc. In this study we focus on one such aspect of semantic content which is the topic of the essay. Putting it formally, given a prompt or essay-statement and an…
Descriptors: Computer Uses in Education, Essays, Writing Evaluation, Semantics
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Baral, Sami; Botelho, Anthony F.; Erickson, John A.; Benachamardi, Priyanka; Heffernan, Neil T. – International Educational Data Mining Society, 2021
Open-ended questions in mathematics are commonly used by teachers to monitor and assess students' deeper conceptual understanding of content. Student answers to these types of questions often exhibit a combination of language, drawn diagrams and tables, and mathematical formulas and expressions that supply teachers with insight into the processes…
Descriptors: Scoring, Automation, Mathematics Tests, Student Evaluation
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
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Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
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Vachharajani, Vinay; Pareek, Jyoti – International Journal of Distance Education Technologies, 2019
E-learning plays a significant role in educating large number of students. In the delivery of e-learning material, automatic e-assessment has been applied only to some extent in the case of free response answers in highly technical diagrams in domains like software engineering, electronics, etc., where there is a great scope of imagination and…
Descriptors: Automation, Visual Aids, Student Evaluation, Undergraduate Students
Danielle S. McNamara; Laura K. Allen; Scott A. Crossley; Mihai Dascalu; Cecile A. Perret – Grantee Submission, 2017
Language is of central importance to the field of education because it is a conduit for communicating and understanding information. Therefore, researchers in the field of learning analytics can benefit from methods developed to analyze language both accurately and efficiently. Natural language processing (NLP) techniques can provide such an…
Descriptors: Natural Language Processing, Learning Analytics, Educational Technology, Automation
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Santamaría Lancho, Miguel; Hernández, Mauro; Sánchez-Elvira Paniagua, Ángeles; Luzón Encabo, José María; de Jorge-Botana, Guillermo – Journal of Interactive Media in Education, 2018
Formative assessment and personalised feedback are commonly recognised as key factors both for improving students' performance and increasing their motivation and engagement (Gibbs and Simpson, 2005). Currently, in large and massive open online courses (MOOCs), technological solutions to give feedback are often limited to quizzes of different…
Descriptors: Online Courses, Formative Evaluation, Scoring, Feedback (Response)
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Pirnay-Dummer, Pablo – Technology, Knowledge and Learning, 2015
A local semantic trace is a certain quasi-propositional structure that can still be reconstructed from written content that is incomplete or does not follow a proper grammar. It can also retrace bits of knowledge from text containing only very few words, making the microstructure of these artifacts of knowledge externalization available for…
Descriptors: Semantics, Grammar, Speech, Knowledge Level
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Klein, Ariel; Badia, Toni – Journal of Creative Behavior, 2015
In this study we show how complex creative relations can arise from fairly frequent semantic relations observed in everyday language. By doing this, we reflect on some key cognitive aspects of linguistic and general creativity. In our experimentation, we automated the process of solving a battery of Remote Associates Test tasks. By applying…
Descriptors: Language Usage, Semantics, Natural Language Processing, Test Items
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Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Question generation is an emerging research area of artificial intelligence in education. Question authoring tools are important in educational technologies, e.g., intelligent tutoring systems, as well as in dialogue systems. Approaches to generate factual questions, i.e., questions that have concrete answers, mainly make use of the syntactical…
Descriptors: Chinese, Questioning Techniques, Automation, Natural Language Processing
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