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Hsu, Hao-Hsuan; Huang, Nen-Fu – IEEE Transactions on Learning Technologies, 2022
This article introduces Xiao-Shih, the first intelligent question answering bot on Chinese-based massive open online courses (MOOCs). Question answering is critical for solving individual problems. However, instructors on MOOCs must respond to many questions, and learners must wait a long time for answers. To address this issue, Xiao-Shih…
Descriptors: Foreign Countries, Artificial Intelligence, Online Courses, Natural Language Processing
Xu, Jia; Wei, Tingting; Lv, Pin – International Educational Data Mining Society, 2022
In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…
Descriptors: Prediction, Programming, Natural Language Processing, Databases
Christopher Dann; Petrea Redmond; Melissa Fanshawe; Alice Brown; Seyum Getenet; Thanveer Shaik; Xiaohui Tao; Linda Galligan; Yan Li – Australasian Journal of Educational Technology, 2024
Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…
Descriptors: Artificial Intelligence, Learner Engagement, Feedback (Response), Decision Making
Zarcone, Alessandra; Demberg, Vera – Discourse Processes: A Multidisciplinary Journal, 2021
There is now a well-established literature showing that people anticipate upcoming concepts and words during language processing. Commonsense knowledge about typical event sequences and verbal selectional preferences can contribute to anticipating what will be mentioned next. We here investigate how temporal discourse connectives…
Descriptors: Natural Language Processing, Discourse Analysis, Form Classes (Languages), Word Order
Hunte, Melissa R.; McCormick, Samantha; Shah, Maitree; Lau, Clarissa; Jang, Eunice Eunhee – Assessment in Education: Principles, Policy & Practice, 2021
Children's oral language proficiency (OLP) is integral for developing literacy skills. Storytelling or retelling is often used by parents and educators to elicit children's OLP, yet it is less commonly used for assessment purposes. Leveraged by natural language processing and machine learning, this study examined the extent to which computational…
Descriptors: Scores, Natural Language Processing, Oral Language, Language Proficiency
Salas-Pilco, Sdenka Zobeida; Yang, Yuqin – International Journal of Educational Technology in Higher Education, 2022
Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is…
Descriptors: Artificial Intelligence, Higher Education, Foreign Countries, Technology Uses in Education
Rybinski, Krzysztof; Kopciuszewska, Elzbieta – Assessment & Evaluation in Higher Education, 2021
This article presents the first-ever big data study of the student evaluation of teaching (SET) using artificial intelligence (AI). We train natural language processing (NLP) models on 1.6 million student evaluations from the US and the UK. We address two research questions: (1) are these models able to predict student ratings from the student…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation of Teacher Performance, Natural Language Processing
Kim, Byungsoo; Yu, Hangyeol; Shin, Dongmin; Choi, Youngduck – International Educational Data Mining Society, 2021
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…
Descriptors: Academic Achievement, Intelligent Tutoring Systems, Prediction, Scores
Sinclair, Jeanne; Jang, Eunice Eunhee; Rudzicz, Frank – Journal of Educational Psychology, 2021
Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…
Descriptors: Prediction, Reading Comprehension, Natural Language Processing, Speech Communication
Chen, Zhaorui; Demmans, Carrie – International Educational Data Mining Society, 2020
Discussion forums are used to support socio-collaborative learning processes among students in online courses. However, complex forum structures and lengthy discourse require that students spend their limited time searching and filtering through posts to find those that are relevant to them rather than spending that time engaged in other…
Descriptors: Cooperative Learning, Computer Mediated Communication, Recordkeeping, Online Courses
Huang, Tao; Liang, Mengyi; Yang, Huali; Li, Zhi; Yu, Tao; Hu, Shengze – International Educational Data Mining Society, 2021
Influenced by COVID-19, online learning has become one of the most important forms of education in the world. In the era of intelligent education, knowledge tracing (KT) can provide excellent technical support for individualized teaching. For online learning, we come up with a new knowledge tracing method that integrates mathematical exercise…
Descriptors: Mathematics Instruction, Teaching Methods, Online Courses, Distance Education
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Zafra, Amelia; Ventura, Sebastian – International Working Group on Educational Data Mining, 2009
The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…
Descriptors: Foreign Countries, Programming, Academic Achievement, Grades (Scholastic)
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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