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Sharma, Harsh; Mathur, Rohan; Chintala, Tejas; Dhanalakshmi, Samiappan; Senthil, Ramalingam – Education and Information Technologies, 2023
Examination assessments undertaken by educational institutions are pivotal since it is one of the fundamental steps to determining students' understanding and achievements for a distinct subject or course. Questions must be framed on the topics to meet the learning objectives and assess the student's capability in a particular subject. The…
Descriptors: Taxonomy, Student Evaluation, Test Items, Questioning Techniques
Gal Sasson Lazovsky; Tuval Raz; Yoed N. Kenett – Journal of Creative Behavior, 2025
As artificial intelligence and natural language processing methods rapidly develop, communication plays a pivotal role in every-day interactions. In this theoretical paper, we explore the overlap and commonalities between question-asking and prompt engineering. While seemingly distinct, these processes share a common foundation in essential skills…
Descriptors: Creativity, Questioning Techniques, Inquiry, Artificial Intelligence
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
Alberto Testoni; Raffaella Bernardi; Azzurra Ruggeri – Cognitive Science, 2023
In recent years, a multitude of datasets of human-human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on…
Descriptors: Questioning Techniques, Cognitive Science, Natural Language Processing, Data Use
Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Yun-Fang Tu – Educational Technology & Society, 2024
With the rapid development of generative artificial intelligence (GAI), the performance and usability of related tools, such as ChatGPT, have significantly improved. The advancement has fostered researchers to increasingly focus on students' perceptions and application of the roles, functionalities, and interaction patterns of these tools in…
Descriptors: Artificial Intelligence, Interaction, Undergraduate Students, Student Attitudes
Dabae Lee; Taekwon Son; Sheunghyun Yeo – Journal of Computer Assisted Learning, 2025
Background: Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain. Objectives: The primary objective of this study is to examine whether…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Preservice Teachers
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
Razvan Paroiu; Stefan Ruseti; Mihai Dascalu; Stefan Trausan-Matu; Danielle S. McNamara – Grantee Submission, 2023
The exponential growth of scientific publications increases the effort required to identify relevant articles. Moreover, the scale of studies is a frequent barrier to research as the majority of studies are low or medium-scaled and do not generalize well while lacking statistical power. As such, we introduce an automated method that supports the…
Descriptors: Science Education, Educational Research, Scientific and Technical Information, Journal Articles
Kurdi, Ghader; Leo, Jared; Parsia, Bijan; Sattler, Uli; Al-Emari, Salam – International Journal of Artificial Intelligence in Education, 2020
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing)…
Descriptors: Computer Assisted Testing, Adaptive Testing, Natural Language Processing, Questioning Techniques
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
Silva, Valtemir A.; Bittencourt, Ig Ibert; Maldonado, Jose C. – IEEE Transactions on Learning Technologies, 2019
Question classification is a key point in many applications, such as Question Answering (QA, e.g., Yahoo! Answers), Information Retrieval (IR, e.g., Google search engine), and E-learning systems (e.g., Bloom's tax. classifiers). This paper aims to carry out a systematic review of the literature on automatic question classifiers and the technology…
Descriptors: Questioning Techniques, Classification, Man Machine Systems, Information Retrieval
González-Castro, Nuria; Muñoz-Merino, Pedro J.; Alario-Hoyos, Carlos; Delgado Kloos, Carlos – Australasian Journal of Educational Technology, 2021
Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that…
Descriptors: Online Courses, Learning Modules, Computer Science Education, Programming
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
Kelly, Sean; Olney, Andrew M.; Donnelly, Patrick; Nystrand, Martin; D'Mello, Sidney K. – Educational Researcher, 2018
Analyzing the quality of classroom talk is central to educational research and improvement efforts. In particular, the presence of authentic teacher questions, where answers are not predetermined by the teacher, helps constitute and serves as a marker of productive classroom discourse. Further, authentic questions can be cultivated to improve…
Descriptors: Middle School Students, Natural Language Processing, Artificial Intelligence, Teaching Methods
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