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Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
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
Ricardo Conejo Muñoz; Beatriz Barros Blanco; José del Campo-Ávila; José L. Triviño Rodriguez – IEEE Transactions on Learning Technologies, 2024
Automatic question generation and the assessment of procedural knowledge is still a challenging research topic. This article focuses on the case of it, the techniques of parsing grammars for compiler construction. There are two well-known techniques for parsing: top-down parsing with LL(1) and bottom-up with LR(1). Learning these techniques and…
Descriptors: Automation, Questioning Techniques, Knowledge Level, Language
Kangkang Li; Qian Yang; Xianmin Yang – IEEE Transactions on Learning Technologies, 2024
The student-generated question (SGQ) strategy is an effective instructional strategy for developing students' higher order cognitive and critical thinking. However, assessing the quality of SGQs is time consuming and domain experts intensive. Previous automatic evaluation work focused on surface-level features of questions. To overcome this…
Descriptors: Computer Simulation, Artificial Intelligence, Computer Assisted Testing, Automation
Ivan D. Mardini G.; Christian G. Quintero M.; César A. Viloria N.; Winston S. Percybrooks B.; Heydy S. Robles N.; Karen Villalba R. – Education and Information Technologies, 2024
Today reading comprehension is considered an essential skill in modern life, therefore, higher education students require more specific skills to understand, interpret and evaluate texts effectively. Short answer questions (SAQs) are one of the relevant and proper tools for assessing reading comprehension skills. Unlike multiple-choice questions,…
Descriptors: Reading Comprehension, Reading Tests, Learning Strategies, Grading
Dorottya Demszky; Jing Liu; Heather C. Hill; Shyamoli Sanghi; Ariel Chung – Annenberg Institute for School Reform at Brown University, 2023
While recent studies have demonstrated the potential of automated feedback to enhance teacher instruction in virtual settings, its efficacy in traditional classrooms remains unexplored. In collaboration with TeachFX, we conducted a pre-registered randomized controlled trial involving 523 Utah mathematics and science teachers to assess the impact…
Descriptors: Elementary Secondary Education, Mathematics Teachers, Science Teachers, Automation
Harrak, Fatima; Bouchet, François; Luengo, Vanda – International Educational Data Mining Society, 2019
Students' questions categorization is a challenging task as the available corpora are often limited in size (particularly with languages other than English) and require a costly preliminary manual annotation to train the classifiers. Ensemble learning can help improve machine learning results by combining several models, and is particularly…
Descriptors: Classification, Questioning Techniques, Artificial Intelligence, Documentation
Xizhe Wang; Yihua Zhong; Changqin Huang; Xiaodi Huang – IEEE Transactions on Learning Technologies, 2024
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This…
Descriptors: Reading Comprehension, Artificial Intelligence, Computer Software, Synchronous Communication
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
Chinkina, Maria; Ruiz, Simón; Meurers, Detmar – Research-publishing.net, 2017
We integrate insights from research in Second Language Acquisition (SLA) and Computational Linguistics (CL) to generate text-based questions. We discuss the generation of wh- questions as functionally-driven input enhancement facilitating the acquisition of particle verbs and report the results of two crowdsourcing studies. The first study shows…
Descriptors: Electronic Publishing, Collaborative Writing, Second Language Learning, Computational Linguistics
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction