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Zhu, Yongjun – ProQuest LLC, 2017
In the big data era, we have witnessed the explosion of scholarly literature. This explosion has imposed challenges to the retrieval of bibliographic information. Retrieval of intended bibliographic information has become challenging due to the overwhelming search results returned by bibliographic information retrieval systems for given input…
Descriptors: Bibliographies, Graphs, Information Retrieval, User Needs (Information)
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Keezhatta, Muhammed Salim – Arab World English Journal, 2019
Natural Language Processing (NLP) platforms have recently reported a higher adoption rate of Artificial Intelligence (AI) applications. The purpose of this research is to examine the relationship between NLP and AI in the application of linguistic tasks related to morphology, parsing, and semantics. To achieve this objective, a theoretical…
Descriptors: Models, Correlation, Natural Language Processing, Artificial Intelligence
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Lundqvist, Karsten Ø.; Liyanagunawardena, Tharindu; Starkey, Louise – International Review of Research in Open and Distributed Learning, 2020
Many course designers trying to evaluate the experience of participants in a MOOC will find it difficult to track and analyse the online actions and interactions of students because there may be thousands of learners enrolled in courses that sometimes last only a few weeks. This study explores the use of automated sentiment analysis in assessing…
Descriptors: Feedback (Response), Online Courses, Student Experience, Peer Relationship
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Kappagantula, Sri Rama Kartheek; Adamo-Villani, Nicoletta; Wu, Meng-Lin; Popescu, Voicu – IEEE Transactions on Learning Technologies, 2020
We present a system that automatically generates deictic gestures for animated pedagogical agents (APAs). The system takes audio and text as input, which define what the APA has to say, and generates animated gestures based on a set of rules. The automatically generated gestures point to the exact locations of elements on a whiteboard nearby the…
Descriptors: Animation, Nonverbal Communication, Lecture Method, Video Technology
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Akpinar, Nil-Jana; Ramdas, Aaditya; Acar, Umut – International Educational Data Mining Society, 2020
Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…
Descriptors: Learning Strategies, Blended Learning, Learning Analytics, Student Behavior
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Bosch, Nigel; Crues, R. Wes; Shaik, Najmuddin; Paquette, Luc – Grantee Submission, 2020
Online courses often include discussion forums, which provide a rich source of data to better understand and improve students' learning experiences. However, forum messages frequently contain private information that prevents researchers from analyzing these data. We present a method for discovering and redacting private information including…
Descriptors: Privacy, Discussion Groups, Asynchronous Communication, Methods
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Degraeuwe, Jasper; Goethals, Patrick – Research-publishing.net, 2022
This paper presents a reflection on the design of an Intelligent Computer-Assisted Language Learning (ICALL) 'ecosystem', integrated into an online learning environment for Spanish as a Foreign Language (SFL). The innovative dimension of the ecosystem lies in its triple focus: apart from enabling users to create and use intelligent language…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Spanish
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Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis – International Journal of Artificial Intelligence in Education, 2017
Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Natural Language Processing, Logical Thinking
Sharp, Rebecca Reynolds – ProQuest LLC, 2017
We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…
Descriptors: Computation, Natural Language Processing, Inferences, Questioning Techniques
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Ipek, Ziyaeddin Halid; Gözüm, Ali Ibrahim Can; Papadakis, Stamatios; Kallogiannakis, Michail – Educational Process: International Journal, 2023
Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Educational Benefits
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L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…
Descriptors: Validity, Automation, Scoring, Writing Assignments
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Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning
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Gerard, Libby; Kidron, Ady; Linn, Marcia C. – International Journal of Computer-Supported Collaborative Learning, 2019
This paper illustrates how the combination of teacher and computer guidance can strengthen collaborative revision and identifies opportunities for teacher guidance in a computer-supported collaborative learning environment. We took advantage of natural language processing tools embedded in an online, collaborative environment to automatically…
Descriptors: Computer Assisted Testing, Student Evaluation, Science Tests, Scoring
Cai, Zhiqiang; Siebert-Evenstone, Amanda; Eagan, Brendan; Shaffer, David Williamson; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Coding is a process of assigning meaning to a given piece of evidence. Evidence may be found in a variety of data types, including documents, research interviews, posts from social media, conversations from learning platforms, or any source of data that may provide insights for the questions under qualitative study. In this study, we focus on text…
Descriptors: Semantics, Computational Linguistics, Evidence, Coding
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Huang, Eddie; Valdiviejas, Hannah; Bosch, Nigel – Grantee Submission, 2019
Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the…
Descriptors: Metacognition, Mathematics, Language Usage, Writing (Composition)
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