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Ustaog?lu, Mehmet Ali; Kukul, Volkan – Open Praxis, 2022
MOOCs can be considered as a powerful alternative in extraordinary situations where people cannot reach formal education. In recent years, the widespread use of the internet worldwide and especially the COVID-19 has increased the need of people for MOOCs. However, in order to increase the effectiveness of MOOCs, and to provide a better learning…
Descriptors: Students, MOOCs, Student Satisfaction, Electronic Publishing
Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
Rubenstein, Rheta N.; Thompson, Denisse R. – Mathematics Teaching in the Middle School, 2012
Mathematics is rich in visual representations. Such visual representations are the means by which mathematical patterns "are recorded and analyzed." With respect to "vocabulary" and "symbols," numerous educators have focused on issues inherent in the language of mathematics that influence students' success with mathematics communication.…
Descriptors: Student Attitudes, Symbols (Mathematics), Mathematics Instruction, Visual Stimuli
Faulkner, Robert; Davidson, Jane W.; McPherson, Gary E. – International Journal of Music Education, 2010
The use of data mining for the analysis of data collected in natural settings is increasingly recognized as a legitimate mode of enquiry. This rule-inductive paradigm is an effective means of discovering relationships within large datasets--especially in research that has limited experimental design--and for the subsequent formulation of…
Descriptors: Foreign Countries, Data Processing, Pattern Recognition, Data Analysis
Michalski, Greg V. – Association for Institutional Research (NJ1), 2011
Excessive college course withdrawals are costly to the student and the institution in terms of time to degree completion, available classroom space, and other resources. Although generally well quantified, detailed analysis of the reasons given by students for course withdrawal is less common. To address this, a text mining analysis was performed…
Descriptors: College Instruction, Courses, Withdrawal (Education), College Students
Morris, Phillip; Thrall, Grant – Association for Institutional Research (NJ1), 2010
Geographic analysis has been adopted by businesses, especially the retail sector, since the early 1990s (Thrall, 2002). Institutional research can receive the same benefits businesses have by adopting geographic analysis and technology. The commonalities between businesses and higher education institutions include the existence of trade areas, the…
Descriptors: Higher Education, Institutional Research, Business, College Administration
Baker, Ryan S. J. d., Ed.; Merceron, Agathe, Ed.; Pavlik, Philip I., Jr., Ed. – International Working Group on Educational Data Mining, 2010
The Third International Conference on Data Mining (EDM 2010) was held in Pittsburgh, PA, USA. It follows the second conference at the University of Cordoba, Spain, on July 1-3, 2009 and the first edition of the conference held in Montreal in 2008, and a series of workshops within the AAAI, AIED, EC-TEL, ICALT, ITS, and UM conferences. EDM 2011…
Descriptors: Information Retrieval, Pattern Recognition, Interdisciplinary Approach, Computer Science
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