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Showing 76 to 90 of 112 results Save | Export
Li, Chenglu; Xing, Wanli; Leite, Walter L. – Grantee Submission, 2021
There has been a long-standing issue of sparse discussion forums participation in online learning, which can impede students' help seeking practices. Researchers have examined AI techniques such as link prediction with network analysis to connect help seekers with help providers. However, little is known whether these AI systems will treat…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Online Courses
Patience Stevens; David Plaut – Grantee Submission, 2020
The statistical structure of a given language likely drives our sensitivity to words' morphological structure. The current work begins to investigate to what degree morphological processing effects observed in visual word recognition can be attributed to statistical regularities between orthography and semantics in English, without any prior…
Descriptors: Reading Processes, Word Recognition, Semantics, Written Language
Marilena Panaite; Mihai Dascalu; Amy Johnson; Renu Balyan; Jianmin Dai; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2018
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Algorithms, Decision Making
Chen, Zhanwen; Li, Shiyao; Rashedi, Roxanne; Zi, Xiaoman; Elrod-Erickson, Morgan; Hollis, Bryan; Maliakal, Angela; Shen, Xinyu; Zhao, Simeng; Kunda, Maithilee – Grantee Submission, 2020
Modern social intelligence includes the ability to watch videos and answer questions about social and theory-of-mind-related content, e.g., for a scene in "Harry Potter," "Is the father really upset about the boys flying the car?" Social visual question answering (social VQA) is emerging as a valuable methodology for studying…
Descriptors: Visual Stimuli, Questioning Techniques, Social Cognition, Video Technology
Chen, Su; Fang, Ying; Shi, Genghu; Sabatini, John; Greenberg, Daphne; Frijters, Jan; Graesser, Arthur C. – Grantee Submission, 2021
This paper describes a new automated disengagement tracking system (DTS) that detects learners' maladaptive behaviors, e.g. mind-wandering and impetuous responding, in an intelligent tutoring system (ITS), called AutoTutor. AutoTutor is a conversation-based intelligent tutoring system designed to help adult literacy learners improve their reading…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Attention, Adult Literacy
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
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…
Descriptors: Phrase Structure, Networks, Semantics, Feedback (Response)
Hu, Xiangen; Cai, Zhiqiang; Hampton, Andrew J.; Cockroft, Jody L.; Graesser, Arthur C.; Copland, Cameron; Folsom-Kovarik, Jeremiah T. – Grantee Submission, 2019
In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the "learners" interact with the learning "resources" in a given learning "environment" following preset steps of learning…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Metadata, Behavior Patterns
Chenglu Li; Wanli Xing; Walter Leite – Grantee Submission, 2022
A discussion forum is a valuable tool to support student learning in online contexts. However, interactions in online discussion forums are sparse, leading to other issues such as low engagement and dropping out. Recent educational studies have examined the affordances of conversational agents (CA) powered by artificial intelligence (AI) to…
Descriptors: Social Responsibility, Computer Mediated Communication, Group Discussion, Artificial Intelligence
Mongkhonvanit, Kritphong; Kanopka, Klint; Lang, David – Grantee Submission, 2019
MOOCs and online courses have notoriously high attrition [1]. One challenge is that it can be difficult to tell if students fail to complete because of disinterest or because of course difficulty. Utilizing a Deep Knowledge Tracing framework, we account for student engagement by including course interaction covariates. With these, we find that we…
Descriptors: Online Courses, Large Group Instruction, Knowledge Level, Learner Engagement
Dascalu, Maria-Dorinela; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle S.; Carabas, Mihai; Rebedea, Traian – Grantee Submission, 2021
The COVID-19 pandemic has changed the entire world, while the impact and usage of online learning environments has greatly increased. This paper presents a new version of the ReaderBench framework, grounded in Cohesion Network Analysis, which can be used to evaluate the online activity of students as a plug-in feature to Moodle. A Recurrent Neural…
Descriptors: COVID-19, Pandemics, Integrated Learning Systems, School Closing
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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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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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Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
Zhang, Zhiyong; Zhang, Danyang – Grantee Submission, 2021
Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These…
Descriptors: Statistics Education, Definitions, Course Descriptions, Computer Science Education
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