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Download full textMorrison, Ryan – Online Submission, 2022
Large Language Models (LLM) -- powerful algorithms that can generate and transform text -- are set to disrupt language learning education and text-based assessments as they allow for automation of text that can meet certain outcomes of many traditional assessments such as essays. While there is no way to definitively identify text created by this…
Descriptors: Models, Mathematics, Automation, Natural Language Processing
Peer reviewedLu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
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
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Educational Data Mining Society, 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
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
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
