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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
Ryan Daniel Budnick – ProQuest LLC, 2023
The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…
Descriptors: Grammar, Feedback (Response), Algorithms, Computational Linguistics
Danielle S. McNamara; Tracy Arner; Reese Butterfuss; Debshila Basu Mallick; Andrew S. Lan; Rod D. Roscoe; Henry L. Roediger; Richard G. Baraniuk – Grantee Submission, 2022
The learning sciences inherently involve interdisciplinary research with an overarching objective of advancing theories of learning and to inform the design and implementation of effective instructional methods and learning technologies. In these endeavors, learning sciences encompass diverse constructs, measures, processes, and outcomes…
Descriptors: Artificial Intelligence, Learning Processes, Learning Motivation, Educational Research
Alex Warstadt – ProQuest LLC, 2022
Data-driven learning uncontroversially plays a role in human language acquisition--how large a role is a matter of much debate. The success of artificial neural networks in NLP in recent years calls for a re-evaluation of our understanding of the possibilities for learning grammar from data alone. This dissertation argues the case for using…
Descriptors: Language Acquisition, Artificial Intelligence, Computational Linguistics, Ethics
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
Fabian Kieser; Peter Wulff; Jochen Kuhn; Stefan Küchemann – Physical Review Physics Education Research, 2023
Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for…
Descriptors: Physics, Science Instruction, Artificial Intelligence, Computer Software
Yiwen Li – Studies in Applied Linguistics & TESOL, 2024
In the realm of language acquisition, the integration of Artificial Intelligence (AI) presents a promising frontier. However, gaps exist in understanding the practical application of AI-driven tools, particularly in second language learning contexts. This study delves into the usability of ChatGPT, an advanced AI language model, within the domain…
Descriptors: Second Language Learning, Second Language Instruction, Teaching Methods, Learning Processes
Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
Panagiotis Panagiotidis – European Journal of Education (EJED), 2024
Efforts to utilize AI in education, and especially in language education, have their roots in the 60s with the appearance of the first rule-based systems. However, recent advances in Artificial Intelligence (AI) and more specifically the introduction of ChatGPT, have given a new perspective to language learning. The integration of AI, natural…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Second Language Learning
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Dye, Melody – ProQuest LLC, 2017
While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a…
Descriptors: Computational Linguistics, Natural Language Processing, Artificial Languages, Computer Software
Cronin, Anthony; Intepe, Gizem; Shearman, Donald; Sneyd, Alison – International Journal of Mathematical Education in Science and Technology, 2019
This paper explores analysis of feedback data collected from student consultations at two mathematics support centres at universities in Australia and Ireland. Unstructured text data was collected over six years and includes qualitative data on student queries collected during the consultations from mathematics and statistics related subjects.…
Descriptors: Natural Language Processing, Feedback (Response), Mathematics Instruction, Academic Support Services
Ellis, Nick C. – Language Learning, 2017
Usage-based approaches explore how we learn language from our experience of language. Related research thus involves the analysis of the usage from which learners learn and of learner usage as it develops. This program involves considerable data recording, transcription, and analysis, using a variety of corpus and computational techniques, many of…
Descriptors: Language Usage, Second Language Learning, Computational Linguistics, Longitudinal Studies
A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities
Mora, Higinio; Ferrández, Antonio; Gil, David; Peral, Jesús – International Review of Research in Open and Distributed Learning, 2017
Massive Open Online Courses and e-learning represent the future of the teaching-learning processes through the development of Information and Communication Technologies. They are the response to the new education needs of society. However, this future also presents many challenges such as the processing of online forums when a huge number of…
Descriptors: Electronic Learning, Online Courses, Teaching Methods, Learning Processes
Thompson, Kate; Kennedy-Clark, Shannon; Wheeler, Penny; Kelly, Nick – British Journal of Educational Technology, 2014
This paper describes a technique for locating indicators of success within the data collected from complex learning environments, proposing an application of e-research to access learner processes and measure and track group progress. The technique combines automated extraction of tense and modality via parts-of-speech tagging with a visualisation…
Descriptors: Data Collection, Educational Environment, Research, Electronic Equipment
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