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A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
Carvalho, Floran; Henriet, Julien; Greffier, Francoise; Betbeder, Marie-Laure; Leon-Henri, Dana – Journal of Education and e-Learning Research, 2023
This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…
Descriptors: Learning Processes, Algorithms, Artificial Intelligence, Programming Languages
Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Sebastian Hobert; Florian Berens – Educational Technology Research and Development, 2024
Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Learning Processes, Teaching Methods
Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
Unger, Layla; Yim, Hyungwook; Savic, Olivera; Dennis, Simon; Sloutsky, Vladimir M. – Developmental Science, 2023
Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…
Descriptors: Natural Language Processing, Language Usage, Vocabulary Development, Linguistic Input
Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Aras Bozkurt; Ramesh C. Sharma – Asian Journal of Distance Education, 2024
This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of…
Descriptors: Algorithms, Artificial Intelligence, Man Machine Systems, Technology Uses in Education
Williams, John N. – Language Learning, 2020
Over the past decades, research employing artificial grammar, sequence learning, and statistical learning paradigms has flourished, not least because these methods appear to offer a window, albeit with a restricted view, on implicit learning processes underlying natural language learning. But these paradigms usually provide relatively little…
Descriptors: Learning Processes, Grammar, Sequential Learning, Natural Language Processing
William Cain – TechTrends: Linking Research and Practice to Improve Learning, 2024
This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Prompting
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
Thanh Pham; Binh Nguyen; Son Ha; Thanh Nguyen Ngoc – Australasian Journal of Educational Technology, 2023
This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that…
Descriptors: Artificial Intelligence, Engineering Education, Universities, Foreign Countries
Mohammad Amini Farsani; Hamid R. Jamali – Studies in Second Language Learning and Teaching, 2023
The current study draws on synthetic techniques and bibliometric analysis to explore the patterns of scientific collaboration in light of methodological orientations. We examined 3,992 applied linguistics (AL) articles published in 18 top-tier journals from 2009 to 2018 and analyzed their methodological orientations and scientific collaboration.…
Descriptors: Applied Linguistics, Periodicals, International Cooperation, Language Research
Carme Grimalt-Álvaro; Mireia Usart – Journal of Computing in Higher Education, 2024
Sentiment Analysis (SA), a technique based on applying artificial intelligence to analyze textual data in natural language, can help to characterize interactions between students and teachers and improve learning through timely, personalized feedback, but its use in education is still scarce. This systematic literature review explores how SA has…
Descriptors: Formative Evaluation, Higher Education, Artificial Intelligence, Natural Language Processing