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Download full textAkar, Sacide Guzin Mazman; Altun, Arif – Contemporary Educational Technology, 2017
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
Descriptors: Individual Differences, Learning Processes, Programming, Self Efficacy
Yildirim, Osman; Ozdener, Nesrin – International Journal of Technology in Education and Science, 2021
Computer games are effective instructional tools used in programming courses to increase students' motivation and engagement. This participatory action research aims to redesign the Object-Oriented Programming course in which the first author is both the instructor and researcher to make it more effective and efficient. In the first step of the…
Descriptors: Action Research, Programming, Computer Science Education, Computer Software
Zhu, Xiao-dong – International Education Studies, 2012
The evolution of object-oriented programming languages includes update of their own versions, update of development environments, and reform of new languages upon old languages. In this paper, the evolution analysis of object-oriented programming languages is presented in term of the characters and development. The notion of adaptive teaching upon…
Descriptors: Computer Science Education, Programming Languages, Programming, Computer Software
Gautam, Dipesh; Swiecki, Zachari; Shaffer, David W.; Graesser, Arthur C.; Rus, Vasile – International Educational Data Mining Society, 2017
Virtual internships are online simulations of professional practice where students play the role of interns at a fictional company. During virtual internships, participants complete activities and then submit write-ups in the form of short answers, digital notebook entries. Prior work used classifiers trained on participant data to automatically…
Descriptors: Computer Simulation, Internship Programs, Semantics, College Students
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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
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
Direct linkRupp, Andre A. – International Journal of Testing, 2003
Item response theory (IRT) has become one of the most popular scoring frameworks for measurement data. IRT models are used frequently in computerized adaptive testing, cognitively diagnostic assessment, and test equating. This article reviews two of the most popular software packages for IRT model estimation, BILOG-MG (Zimowski, Muraki, Mislevy, &…
Descriptors: Test Items, Adaptive Testing, Item Response Theory, Computer Software
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Braun, Henry I.; And Others – 1989
The use of constructed response items in large scale standardized testing has been hampered by the costs and difficulties associated with obtaining reliable scores. The advent of expert systems may signal the eventual removal of this impediment. This study investigated the accuracy with which expert systems could score a new, non-multiple choice…
Descriptors: Computer Science, Constructed Response, Expert Systems, High School Seniors
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Chung, Gregory K. W. K.; Baker, Eva L.; Brill, David G.; Sinha, Ravi; Saadat, Farzad; Bewley, William L. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2006
A critical first step in developing training systems is gathering quality information about a trainee's competency in a skill or knowledge domain. Such information includes an estimate of what the trainee knows prior to training, how much has been learned from training, how well the trainee may perform in future task situations, and whether to…
Descriptors: Distance Education, Skill Analysis, Knowledge Level, Prior Learning
