• Hairulliza Mohamad Judi
  • Zanaton H Iksan
  • Noraidah Sahari Ashaari
Keywords: Knowledge structure, data analytics, decision making.


The contribution of data analytics to scientific knowledge and better informed society is widely recognized but there are challenges in the traditional curriculum including the need to incorporate more meaningful computational and graphical tools and to train data analysts with agile problem solving skills. The opportunity of efficient instructional arrangement and student support method may help students with best possible information surroundings that they need. Cognitive visual support using various visual tools may help students with components that improve their communication with the lesson and enhance engagement in the action that would otherwise be outside their capacity. This research demonstrates cognitive visual support implementation in delivering data analytics topic on probability. This investigation utilizes meaningful reception learning method in the instructional arrangement to contribute learning support by perform worked-example data analytics knowledge construction and problem solutions using three useful elements: active, constructive and collaborative. The presentation may provide advisor with specific and entire references to expand an applicable task statement consistently in active data analytics learning.


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How to Cite
Mohamad Judi, H., H Iksan, Z., & Ashaari, N. S. (2018). IMPLEMENTATION OF COGNITIVE VISUAL DATA ANALYTICS LEARNING SUPPORT: APPLYING MEANINGFUL RECEPTION LEARNING THEORY. COMPUSOFT: An International Journal of Advanced Computer Technology, 7(11). Retrieved from