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Download full textPanyajamorn, Titie; Suanmali, Suthathip; Kohda, Youji; Chongphaisal, Pornpimol; Supnithi, Thepchai – Malaysian Journal of Learning and Instruction, 2018
Purpose: This study proposed and examined the effectiveness of e-learning content design by considering two different subjects (mathematics and reading) and areas (metropolitan and rural). This study also investigated several variables, i.e., students' satisfaction, motivation, and experience, that influenced learning abilities. Moreover, we…
Descriptors: Electronic Learning, Technology Uses in Education, Reading Instruction, Mathematics Instruction
Direct linkLi, Hongli; Fortner, C. Kevin; Lei, Xiaoxuan – School Effectiveness and School Improvement, 2015
In this study, we examined relationships between the use of test results and US students' math, reading, and science performance in the Programme for International Student Assessment (PISA) 2009. Based on a literature review, we hypothesized that the 16 items in the PISA school questionnaire, which are related to the use of test results, can be…
Descriptors: Academic Achievement, Tests, Evaluation Utilization, Mathematics Achievement
Guo, Jiesi; Parker, Philip D.; Marsh, Herbert W.; Morin, Alexandre J. S. – Developmental Psychology, 2015
Drawing on the expectancy-value model, the present study explored individual and gender differences in university entry and selection of educational pathway (e.g., science, technology, engineering, and mathematics [STEM] course selection). In particular, we examined the multiplicative effects of expectancy and task values on educational outcomes…
Descriptors: Foreign Countries, STEM Education, Expectation, Academic Achievement
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
