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Hsiao, I-Han, Ed.; Sahebi, Shaghayegh, Ed.; Bouchet, Francois, Ed.; Vie, Jill-Jenn, Ed. – International Educational Data Mining Society, 2021
For this 14th iteration of the International Conference on Educational Data Mining (EDM 2021), the conference was held completely online. EDM is organized under the auspices of the International Educational Data Mining Society and was meant to happen in Paris, France. The official theme of this year's conference was Shifting Landscape of…
Descriptors: Blended Learning, Distance Education, Learning Analytics, Educational Technology
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
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
Yang, Xiaozhe – ECNU Review of Education, 2019
Purpose: This article summarizes recent developments in the use of artificial intelligence (AI) in Chinese education, paying particular attention to the different applications of AI at a number of different levels. The article reviews key government policies and guidelines and suggests a course for future development. Design/Approach/Methods: The…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Educational Policy
Gardner, Josh; Yang, Yuming; Baker, Ryan S.; Brooks, Christopher – International Educational Data Mining Society, 2019
Replication of machine learning experiments can be a useful tool to evaluate how both "modeling" and "experimental design" contribute to experimental results; however, existing replication efforts focus almost entirely on modeling alone. In this work, we conduct a three-part replication case study of a state-of-the-art LSTM…
Descriptors: Online Courses, Large Group Instruction, Prediction, Models
Morsy, Sara; Karypis, George – International Educational Data Mining Society, 2019
Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is…
Descriptors: Grades (Scholastic), Models, Prediction, Predictor Variables
Khashabi, Daniel – ProQuest LLC, 2019
"Natural language understanding" (NLU) of text is a fundamental challenge in AI, and it has received significant attention throughout the history of NLP research. This primary goal has been studied under different tasks, such as Question Answering (QA) and Textual Entailment (TE). In this thesis, we investigate the NLU problem through…
Descriptors: Natural Language Processing, Artificial Intelligence, Task Analysis, Questioning Techniques
Herzenberg, Stephen; Alic, John – Keystone Research Center, 2019
This is the first report of a Keystone Research Center project on the "Future of Work." The aim is to identify public policies that could help ensure that the application and diffusion of artificial intelligence (AI) over the next several decades fosters an economy in which Americans generally thrive. The project is motivated, in part,…
Descriptors: Artificial Intelligence, Public Policy, Economics, Technological Advancement
Luis F. Alvarez León – International Perspectives on Education and Society, 2019
A wave of technological change in the first decades of the twenty-first century is prefiguring a fundamental restructuring of society. Key among the driving forces behind such change are powerful technologies with the potential to exert major transformations on a range of human activities and, crucially, to do so without direct human intervention.…
Descriptors: Technology Uses in Education, Artificial Intelligence, Educational Practices, Technological Advancement
Aleksei Malakhov – International Perspectives on Education and Society, 2019
This chapter presents an overarching overview of how the rather recent technological phenomena, like data mining, machine learning, and artificial intelligence, are applied in the field of education. The author provides examples of how technological developments associated with the so-called Fourth Industrial Revolution are applied in education…
Descriptors: Information Retrieval, Data Analysis, Information Technology, Artificial Intelligence
Jones, Daniel Marc; Cheng, Liying; Tweedie, M. Gregory – Canadian Journal of Learning and Technology, 2022
This article reviews recent literature (2011-present) on the automated scoring (AS) of writing and speaking. Its purpose is to first survey the current research on automated scoring of language, then highlight how automated scoring impacts the present and future of assessment, teaching, and learning. The article begins by outlining the general…
Descriptors: Automation, Computer Assisted Testing, Scoring, Writing (Composition)
Marrone, Rebecca; Taddeo, Victoria; Hill, Gillian – Journal of Intelligence, 2022
Creativity is a core 21st-century skill taught globally in education systems. As Artificial Intelligence (AI) is being implemented in classrooms worldwide, a key question is proposed: how do students perceive AI and creativity? Twelve focus groups and eight one-on-one interviews were conducted with secondary school-aged students after they…
Descriptors: Creativity, Artificial Intelligence, 21st Century Skills, Student Attitudes
Ong, Nathan; Zhu, Jiaye; Mossé, Daniel – International Educational Data Mining Society, 2022
Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…
Descriptors: Prediction, Grades (Scholastic), Learning Analytics, Student Characteristics
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, Anaïs; Piech, Chris – International Educational Data Mining Society, 2022
How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…
Descriptors: Artificial Intelligence, Dialogs (Language), Bayesian Statistics, Decision Making

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