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Raigul Zheldibayeva – Educational Process: International Journal, 2025
Background/purpose: Despite the rapid assimilation of generative artificial intelligence (GenAI) into education, and initial evidence suggesting its potential in language learning, rigorous empirical investigations into its efficacy for cultivating specific language skills remain limited. This study aimed to address this lacuna by examining the…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Nonmajors
McCord, Rachel; Jeldes, Isaac – Computer Science Education, 2019
Background and Context: Flipped classrooms are becoming more widely adopted across engineering higher education contexts. In degree programs where enrollment is increasing and undergraduate curricula are packed with content, pedagogies that allow more time for actively participate in classroom activities are being highly sought after to aid in…
Descriptors: Computer Software, Computer Science Education, Blended Learning, Intervention
Ha, Minsu; Nehm, Ross H.; Urban-Lurain, Mark; Merrill, John E. – CBE - Life Sciences Education, 2011
Our study explored the prospects and limitations of using machine-learning software to score introductory biology students' written explanations of evolutionary change. We investigated three research questions: 1) Do scoring models built using student responses at one university function effectively at another university? 2) How many human-scored…
Descriptors: Expertise, Nonmajors, Majors (Students), Computer Software
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