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Manik R. Reddy; Nils G. Walter; Yulia V. Sevryugina – Journal of Chemical Education, 2024
The effective and responsible educational application of ChatGPT and other generative artificial intelligence (GenAI) tools constitutes an active area of exploration. This study describes and assesses the implementation of a structured, GenAI-assisted scientific essay writing assignment in nucleic acid biochemistry. Briefly, students created,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing Assignments, Biochemistry
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Lucas Kohnke; Mark B. Ulla – Knowledge Management & E-Learning, 2024
This study explored the perspectives of English instructors from Thai higher education institutions, with a focus on teachers' familiarity with generative artificial intelligence (GenAI) and its potential impact on teachers' professional roles and responsibilities. The results suggested that GenAI tools may allow English instructors to transition…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, English (Second Language)
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Irfan, Rabia; Khan, Sharifullah; Abbas, Muhammad Azeem; Shah, Asad Ali – Information Research: An International Electronic Journal, 2019
Introduction. Taxonomy is an effective mean of managing and accessing a large amount of digital information. Various techniques have been developed to generate taxonomy automatically. The purpose of this study is threefold: (i) review methods and approaches adopted during taxonomy generation, (ii) identify the factors influencing the choice of a…
Descriptors: Literature Reviews, Taxonomy, Semantics, Natural Language Processing
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Kolb, John; Farrar, Scott; Pardos, Zachary A. – International Educational Data Mining Society, 2019
Misconceptions have been an important area of study in STEM education towards improving our understanding of learners' construction of knowledge. The advent of largescale tutoring systems has given rise to an abundance of data in the form of learner question-answer logs in which signatures of misconceptions can be mined. In this work, we explore…
Descriptors: Misconceptions, Expertise, Mathematics Teachers, Semantics
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Odden, Tor Ole B.; Marin, Alessandro; Rudolph, John L. – Science Education, 2021
For well over a century, the journal "Science Education" has been publishing articles about the teaching and learning of science. These articles represent more than just a repository of past work: they have the potential to offer insights into both the history of science education as well as well as the dynamics of field-specific change.…
Descriptors: Science Education, Periodicals, Literature Reviews, Natural Language Processing
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McFarland, Daniel A.; Khanna, Saurabh; Domingue, Benjamin W.; Pardos, Zachary A. – AERA Open, 2021
This AERA Open special topic concerns the large emerging research area of education data science (EDS). In a narrow sense, EDS applies statistics and computational techniques to educational phenomena and questions. In a broader sense, it is an umbrella for a fleet of new computational techniques being used to identify new forms of data, measures,…
Descriptors: Learning Analytics, Statistics, Computation, Measurement
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Meddeb, Ons; Maraoui, Mohsen; Zrigui, Mounir – International Journal of Web-Based Learning and Teaching Technologies, 2021
The advancement of technologies has modernized learning within smart campuses and has emerged new context through communication between mobile devices. Although there is a revolutionary way to deliver long-term education, a great diversity of learners may have different levels of expertise and cannot be treated in a consistent manner.…
Descriptors: Educational Technology, Semitic Languages, Natural Language Processing, Internet
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Haering, Marlo; Bano, Muneera; Zowghi, Didar; Kearney, Matthew; Maalej, Walid – IEEE Transactions on Learning Technologies, 2021
With the vast number of apps and the complexity of their features, it is becoming challenging for teachers to select a suitable learning app for their courses. Several evaluation frameworks have been proposed in the literature to assist teachers with this selection. The iPAC framework is a well-established mobile learning framework highlighting…
Descriptors: Automation, Courseware, Computer Software Evaluation, Computer Software Selection
Allen, Laura K.; Creer, Sarah D.; Poulos, Mary Cati – Grantee Submission, 2021
Research in discourse processing has provided us with a strong foundation for understanding the characteristics of text and discourse, as well as their influence on our processing and representation of texts. However, recent advances in computational techniques have allowed researchers to examine discourse processes in new ways. The purpose of the…
Descriptors: Natural Language Processing, Computation, Discourse Analysis, Computer Science
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Odden, Tor Ole B.; Marin, Alessandro; Caballero, Marcos D. – Physical Review Physics Education Research, 2020
We have used an unsupervised machine learning method called latent Dirichlet allocation (LDA) to thematically analyze all papers published in the Physics Education Research Conference Proceedings between 2001 and 2018. By looking at co-occurrences of words across the data corpus, this technique has allowed us to identify ten distinct themes or…
Descriptors: Physics, Science Education, Educational Research, Conferences (Gatherings)
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Davidovitch, Nitza; Eckhaus, Eyal – Journal of Education and Learning, 2020
The current study is an exploratory study designed to examine the traits that are considered essential or important for research students, from the perspective of student advisors. The study addresses the broad question of whether and how academic faculty members select research students when seeking to maximize their own research outputs and…
Descriptors: Student Characteristics, Student Motivation, Research, College Faculty
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Lippert, Anne; Shubeck, Keith; Morgan, Brent; Hampton, Andrew; Graesser, Arthur – Technology, Knowledge and Learning, 2020
This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Natural Language Processing, Educational Technology
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Rao, Dhawaleswar; Saha, Sujan Kumar – IEEE Transactions on Learning Technologies, 2020
Automatic multiple choice question (MCQ) generation from a text is a popular research area. MCQs are widely accepted for large-scale assessment in various domains and applications. However, manual generation of MCQs is expensive and time-consuming. Therefore, researchers have been attracted toward automatic MCQ generation since the late 90's.…
Descriptors: Multiple Choice Tests, Test Construction, Automation, Computer Software
Lippert, Anne; Shubeck, Keith; Morgan, Brent; Hampton, Andrew; Graesser, Arthur – Grantee Submission, 2020
This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Natural Language Processing, Educational Technology
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Zhao Wanli; Tang Youjun; Ma Xiaomei – SAGE Open, 2025
Deeper learning (DL) is firmly rooted in learning science and computer science. However, a dearth of review studies has probed its trajectory in DL in foreign languages (DLFL). Utilizing SSCI from the Web of Science Core Collection, we employ Citespace and Vosviewer to analyze the scientific knowledge graph of DLFL literature. Our analysis…
Descriptors: Bibliometrics, Second Language Learning, Computer Science, Educational Research
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