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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
Avci, Esat; Coskuntuncel, Orkun – Pegem Journal of Education and Instruction, 2019
The purpose of this research is to examine the views of middle school mathematics teachers about the usability of VUstat and TinkerPlots software in data processing learning in the Curriculum of Mathematics Teaching in Middle School (5th, 6th, 7th and 8th grades). In the study, the phenomenology design from qualitative research patterns was…
Descriptors: Middle School Teachers, Mathematics Teachers, Teacher Attitudes, Computer Uses in Education
Dun, Yijie; Wang, Na; Wang, Min; Hao, Tianyong – International Journal of Distance Education Technologies, 2017
In a question-answering system, learner generated content including asked and answered questions is a meaningful resource to capture learning interests. This paper proposes an approach based on question topic mining for revealing learners' concerned topics in real community question-answering systems. The authors' approach firstly preprocesses all…
Descriptors: Natural Language Processing, Information Retrieval, Data Processing, Pattern Recognition
Klingler, Severin; Wampfler, Rafael; Käser, Tanja; Solenthaler, Barbara; Gross, Markus – International Educational Data Mining Society, 2017
Gathering labeled data in educational data mining (EDM) is a time and cost intensive task. However, the amount of available training data directly influences the quality of predictive models. Unlabeled data, on the other hand, is readily available in high volumes from intelligent tutoring systems and massive open online courses. In this paper, we…
Descriptors: Classification, Artificial Intelligence, Networks, Learning Disabilities
Scaltritti, Michele; Longcamp, Marieke; Alario, F. -Xavier – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
The selection and ordering of response units (phonemes, letters, keystrokes) represents a transversal issue across different modalities of language production. Here, the issue of serial order was investigated with respect to typewriting. Following seminal investigations in the spoken modality, we conducted an experiment where participants typed as…
Descriptors: Office Occupations, Serial Ordering, Word Order, Psychomotor Skills
Liu, Ran; Stamper, John; Davenport, Jodi – Journal of Learning Analytics, 2018
Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Learning, Data Analysis, Student Development
Singh, Archana – Education and Information Technologies, 2017
The youth power to speak their mind, recommendations and opinions about various issues on social media cannot be ignored. There is a generated by students on social media websites like, facebook, Orkut, twitter etc. This paper focusses on the extraction of knowledge from the data floated by the University students on social websites in different…
Descriptors: Social Media, College Students, Data Processing, Web Sites
Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal – International Association for Development of the Information Society, 2017
Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…
Descriptors: Student Characteristics, Profiles, Courseware, Electronic Learning
Slez, Adam; O'Connell, Heather A.; Curtis, Katherine J. – Sociological Methods & Research, 2017
Areal data have been used to good effect in a wide range of sociological research. One of the most persistent problems associated with this type of data, however, is the need to combine data sets with incongruous boundaries. To help address this problem, we introduce a new method for identifying common geographies. We show that identifying common…
Descriptors: Data, Data Processing, Geographic Information Systems, Research Methodology
Hildebrandt, Mireille – Journal of Learning Analytics, 2017
This article is a revised version of the keynote presented at LAK '16 in Edinburgh. The article investigates some of the assumptions of learning analytics, notably those related to behaviourism. Building on the work of Ivan Pavlov, Herbert Simon, and James Gibson as ways of "learning as a machine," the article then develops two levels of…
Descriptors: Behaviorism, Data Processing, Profiles, Learning Processes
Jones, Kyle M. L.; Salo, Dorothea – College & Research Libraries, 2018
In this paper, the authors address learning analytics and the ways academic libraries are beginning to participate in wider institutional learning analytics initiatives. Since there are moral issues associated with learning analytics, the authors consider how data mining practices run counter to ethical principles in the American Library…
Descriptors: Academic Libraries, Ethics, Intellectual Freedom, Privacy
Villanueva Manjarres, Andrés; Moreno Sandoval, Luis Gabriel; Salinas Suárez, Martha Janneth – Digital Education Review, 2018
Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…
Descriptors: Information Retrieval, Data Analysis, Educational Environment, Research Methodology
Yannakoudakis, Helen; Andersen, Øistein E.; Geranpayeh, Ardeshir; Briscoe, Ted; Nicholls, Diane – Applied Measurement in Education, 2018
There are quite a few challenges in the development of an automated writing placement model for non-native English learners, among them the fact that exams that encompass the full range of language proficiency exhibited at different stages of learning are hard to design. However, acquisition of appropriate training data that are relevant to the…
Descriptors: Automation, Data Processing, Student Placement, English Language Learners
Jackson, Michael; Diliberti, Melissa; Kemp, Jana; Hummel, Steven; Cox, Christina; Gbondo-Tugbawa, Komba; Simon, Dillon – National Center for Education Statistics, 2018
The School Survey on Crime and Safety (SSOCS) is managed by the National Center for Education Statistics (NCES) within the Institute of Education Sciences of the U.S. Department of Education. SSOCS collects extensive crime and safety data from principals and administrators of public schools in the United States. Data from this collection can be…
Descriptors: School Surveys, Crime, School Safety, Public Schools
Figlio, David; Karbownik, Krzysztof; Salvanes, Kjell – Education Finance and Policy, 2017
Thanks to extraordinary and exponential improvements in data storage and computing capacities, it is now possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago. As the world has developed this remarkable capacity to store and analyze data, so have the world's governments…
Descriptors: Educational Research, Data, Information Utilization, Management Information Systems