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LACLOD: LEARNING ANALYTICS FOR CHILDREN'S LOGIC DEVELOPMENT

Authors: Suzani Mohamad Samuri;

LACLOD: LEARNING ANALYTICS FOR CHILDREN'S LOGIC DEVELOPMENT

Abstract

Learning Analytics for Children's Logic Development (LACLOD) is a web-based and mobile friendly learning analytic platform for assessing the logic development of children age 3 to 4 years old in TASKA PERMATA UPSI Malaysia. The platform is developed using Unity and connected through Google Analytics (GA) plugin where it tracked the user interaction for the application. LACLOD is designed only for mobile or tablet which is using Android. In this paper, the development of this learning analytic platform is presented. For evaluation of this system, observation and survey have been used, to get the feedback from 2 teachers (female) and 3 children (2 female and 1 male). Based on the evaluation, it can be seen that there are still rooms for improvement. Female children found it quit hard to understand the game but the male children looked satisfy because he knew on how to navigate the app and he actively played the app by himself. As for teachers, the acceptance to this kind of assessment is moderate, however they agree that this application can better improve the children’s learning especially in logic development.

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Keywords

Learning analytics, Game-based learning, Unity software, Google analytics, and Assessment technology, Learning analytics

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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