Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 4 |
| Since 2007 (last 20 years) | 9 |
Descriptor
| Data Processing | 12 |
| Predictor Variables | 12 |
| Foreign Countries | 6 |
| Data Analysis | 5 |
| Academic Achievement | 4 |
| Models | 4 |
| College Students | 3 |
| Online Courses | 3 |
| Prediction | 3 |
| Best Practices | 2 |
| Data Collection | 2 |
| More ▼ | |
Source
Author
| Cocea, M. | 1 |
| Conijn, Rianne | 1 |
| Cotton, Dan | 1 |
| Davidson, Jane W. | 1 |
| Delen, Dursun | 1 |
| Drakopoulou, Konstantina | 1 |
| Faulkner, Robert | 1 |
| Guru, Ashu | 1 |
| Kantor, Paul B. | 1 |
| Kleingeld, Ad | 1 |
| Lee, In Heok | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 12 |
| Reports - Research | 8 |
| Reports - Descriptive | 2 |
| Reports - Evaluative | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 5 |
| Postsecondary Education | 3 |
| Adult Education | 1 |
| Elementary Secondary Education | 1 |
| Secondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Livieris, Ioannis E.; Drakopoulou, Konstantina; Tampakas, Vassilis T.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Journal of Educational Computing Research, 2019
Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…
Descriptors: Secondary School Students, Academic Achievement, Teaching Methods, Student Behavior
Weiand, Augusto; Manssour, Isabel Harb; Silveira, Milene Selbach – International Journal of Distance Education Technologies, 2019
With technological advances, distance education has been frequently discussed in recent years. The learning environments used in this course usually generates a great deal of data because of the large number of students and the various tasks involving their interaction. In order to facilitate the analysis of the data, the authors researched to…
Descriptors: Foreign Countries, Distance Education, Online Courses, Visualization
Turner, David A. – Compare: A Journal of Comparative and International Education, 2017
In his proposal for comparative education, Marc Antoinne Jullien de Paris argues that the comparative method offers a viable alternative to the experimental method. In an experiment, the scientist can manipulate the variables in such a way that he or she can see any possible combination of variables at will. In comparative education, or in…
Descriptors: Comparative Education, Comparative Analysis, Research Methodology, Predictor Variables
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Yukselturk, Erman; Ozekes, Serhat; Turel, Yalin Kilic – European Journal of Open, Distance and E-Learning, 2014
This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies…
Descriptors: Online Courses, Distance Education, Dropout Characteristics, Prediction
Lee, In Heok – Career and Technical Education Research, 2012
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…
Descriptors: Vocational Education, Data Collection, Maximum Likelihood Statistics, Educational Research
Delen, Dursun – Journal of College Student Retention: Research, Theory & Practice, 2012
Affecting university rankings, school reputation, and financial well-being, student retention has become one of the most important measures of success for higher education institutions. From the institutional perspective, improving student retention starts with a thorough understanding of the causes behind the attrition. Such an understanding is…
Descriptors: Higher Education, Student Attrition, School Holding Power, Prediction
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
Cocea, M.; Weibelzahl, S. – IEEE Transactions on Learning Technologies, 2011
Learning environments aim to deliver efficacious instruction, but rarely take into consideration the motivational factors involved in the learning process. However, motivational aspects like engagement play an important role in effective learning-engaged learners gain more. E-Learning systems could be improved by tracking students' disengagement…
Descriptors: Prediction, Electronic Learning, Online Courses, Delivery Systems
Kantor, Paul B.; Ng, Kwong Bor – Proceedings of the ASIS Annual Meeting, 1998
Categorizes different theoretical justifications of data fusion into two approaches, examines their implications, analyzes some unsuccessful data fusion experiments, and proposes two conditions for effective data fusion. Results indicate that the efficacy and inter-scheme dissimilarity are good predictors for effectiveness of data fusion.…
Descriptors: Data Processing, Evaluation Criteria, Information Processing, Information Retrieval
Schacht, Walter H.; Guru, Ashu; Reece, Patrick E.; Volesky, Jerry D.; Cotton, Dan – Journal of Natural Resources and Life Sciences Education, 2005
A focus of grazing management courses is the cause-effect relationships between grazing livestock distribution and environmental and management variables. A learning module for the classroom was developed to enable students to actively study livestock distribution by analyzing recently collected data from an on-ranch situation. Data were collected…
Descriptors: Learning Modules, Intervals, Computer Software, Student Evaluation
Redman, John C.; Middleton, James W. – 1973
In 1965 the Court of Appeals of Kentucky ruled that all property should be assessed at 100 percent of fair market value. In compliance with the court decision, the county assessors began reassessing properties in January 1966. A great controversy arose over the new assessment procedures and problems. This study evaluates the results of the 1966…
Descriptors: Case Studies, Computer Programs, Data Processing, Legislation

Peer reviewed
Direct link
