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Tsong, Chau Kien; Chong, Toh Seong; Samsudin, Zarina – Turkish Online Journal of Educational Technology - TOJET, 2012
Multimedia augmented with tangible objects is an area that has not been explored. Current multimedia systems lack the natural elements that allow young children to learn tangibly and intuitively. In view of this, we propose a research to merge tangible objects with multimedia for preschoolers, and propose to term it as "tangible…
Descriptors: Foreign Countries, Multimedia Instruction, Case Studies, Observation
Hsieh, Pei-Hsuan; Chen, Nian-Shing – Turkish Online Journal of Educational Technology - TOJET, 2012
The purpose of this study is to examine the effects of reflective thinking effects in the process of designing software on students' learning performances. The study contends that reflective thinking is a useful teaching strategy to improve learning performance among lower achieving students. Participants were students from two groups: Higher…
Descriptors: Foreign Countries, Computer Software, Computer Software Evaluation, Programming
Genc, Humeyra – Turkish Online Journal of Educational Technology - TOJET, 2012
The present study tried to evaluate the 6th grade students' attitudes towards the use of a CALL program which is called BELT Success used in English language learning course in a private school, the relationship to students' attitudes to their English language proficiency level, and finally teachers` experiences and opinions towards the use of…
Descriptors: Foreign Countries, Computer Assisted Instruction, Blended Learning, Interviews
Macfadyen, Leah P.; Dawson, Shane – Computers & Education, 2010
Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…
Descriptors: Network Analysis, Academic Achievement, At Risk Students, Prediction