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Turner, Paul – Australian Senior Mathematics Journal, 2015
This article aims to illustrate a process of making connections, not between mathematics and other activities, but within mathematics itself--between diverse parts of the subject. Novel connections are still possible in previously explored mathematics when the material happens to be unfamiliar, as may be the case for a learner at any career stage.…
Descriptors: Mathematics, Geometric Concepts, Graphs, Matrices
Gambhir, Victor; Wadhwa, N. C.; Grover, Sandeep – Quality Assurance in Education: An International Perspective, 2016
Purpose: The paper aims to discuss current Technical Education scenarios in India. It proposes modelling the factors affecting quality in a technical institute and then applying a suitable technique for assessment, comparison and ranking. Design/methodology/approach: The paper chose graph theoretic approach for quantification of quality-enabled…
Descriptors: Foreign Countries, Technical Education, Educational Quality, Program Evaluation
Peer reviewedLeutner, Detlev; Weinsier, Philip D. – Computers in Human Behavior, 1994
This article's goals are to validate the Computer and Information Technology Attitude Inventory (Weinsier and Leutner, 1988), a nontraditional approach to attitude measurement; and to report on a study designed to search for intercultural differences or cross-cultural consistency of attitudes toward computers and information technology. (46…
Descriptors: Attitude Measures, College Students, Comparative Analysis, Computer Anxiety
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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