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Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
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
Stone, Deborah – Creative Computing, 1980
Discussed is computer use at High Valley, a small private tutorial school in rural Dutchess County, New York. (MP)
Descriptors: Computer Oriented Programs, Computer Science Education, Computers, Individualized Instruction
Pannwitt, Barbara – Curriculum Report, 1983
The first of a three-part series on computer-assisted instruction (CAI), this report describes 11 exemplary programs across the country that involve the use of microcomputers for instruction in computer science, mathematics, and science at the elementary and secondary levels. At the head of each description are the name and address of the school…
Descriptors: Autoinstructional Aids, Business Education, Computer Assisted Instruction, Computer Literacy