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Emerson, Andrew; RodrÃguez, Fernando J.; Mott, Bradford; Smith, Andy; Min, Wookhee; Boyer, Kristy Elizabeth; Smith, Cody; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2019
Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…
Descriptors: Programming, Computer Science Education, Feedback (Response), Prediction
Liao, Soohyun Nam; Zingaro, Daniel; Thai, Kevin; Alvarado, Christine; Griswold, William G.; Porter, Leo – ACM Transactions on Computing Education, 2019
As enrollments and class sizes in postsecondary institutions have increased, instructors have sought automated and lightweight means to identify students who are at risk of performing poorly in a course. This identification must be performed early enough in the term to allow instructors to assist those students before they fall irreparably behind.…
Descriptors: Prediction, Low Achievement, Tests, Scores
Paassen, Benjamin; Hammer, Barbara; Price, Thomas William; Barnes, Tiffany; Gross, Sebastian; Pinkwart, Niels – Journal of Educational Data Mining, 2018
Intelligent tutoring systems can support students in solving multi-step tasks by providing hints regarding what to do next. However, engineering such next-step hints manually or via an expert model becomes infeasible if the space of possible states is too large. Therefore, several approaches have emerged to infer next-step hints automatically,…
Descriptors: Intelligent Tutoring Systems, Cues, Educational Technology, Technology Uses in Education
Gitinabard, Niki; Xu, Yiqiao; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – IEEE Transactions on Learning Technologies, 2019
Blended courses that mix in-person instruction with online platforms are increasingly common in secondary education. These platforms record a rich amount of data on students' study habits and social interactions. Prior research has shown that these metrics are correlated with students performance in face-to-face classes. However, predictive models…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Prediction
Tekin, Ahmet – Eurasian Journal of Educational Research, 2014
Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…
Descriptors: Foreign Countries, Prediction, Grade Point Average, Undergraduate Students
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

Fennell, Joseph P.; And Others – 1977
This report summarizes the findings of a one man-month study of the current status and future direction of instructional computing in the Montgomery County, Maryland, Public Schools including computer assisted instruction, computer managed instruction, computer assisted problem solving, and data processing education. The report is presented in six…
Descriptors: Computer Assisted Instruction, Computer Managed Instruction, Computer Science Education, Costs
Buterbaugh, James G. – 1980
Included in this thorough overview of the probable future developments in videodisc technology and its role as an educational medium are (1) a review of current educational technology literature on videodiscs, which summarizes a U.S. Navy Delphi Study of videodisc technology use through 1986, discusses a National Institute of Education (NIE) study…
Descriptors: Computer Science, Delphi Technique, Educational Media, Educational Technology
Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John – International Working Group on Educational Data Mining, 2011
The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…
Descriptors: Academic Achievement, Logical Thinking, Profiles, Tutoring
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers