Analytic Dashboard on Talent Search Examination Data Using Structure of Intellect Model

EasyChair Preprint 4651

Abstract

The potential of Analytics and Data mining methodologies, that extract useful and actionable information from large data-sets, has transformed one field of scientific inquiry after another. Analytics has been widely applied in Business Organizations as Business Analytics  and when applied to education, these methodologies are referred to as Learning Analytics and Educational Data mining. Learning Analytics proposes to collect, measure and analyze  data  in learning environments to improve teaching and learning process. Educational Data mining (EDM) thrives on existing data collected by learning management systems.  The applicability of Learning Analytic  and Educational Data mining can be extended to traditional learning processes by  suitably combining data collected  from technology enabled processes such as Admission and Assessment with data generated from analysis of learning interactions.  The intellectual performance of the students can be analyzed using some well known Learning Frameworks. This paper demonstrates the Complete Analytics   process from data collection, measurement to Analysis using  Guilford's structure of intellect model.  An analytic dashboard provides the necessary information in concise and visual form and in an interactive mode. The  analytic process presented on talent examination data  can be generalized to similar examinations in traditional educational setup.

Keyphrases: Dashboard, Educational Data Mining, Learning Analytic, Structure of Intellect model

@booklet{EasyChair:4651,
  author    = {Vyankat Munde and Binod Kumar and Anagha Vaidya and Shailaja Shirwaikar},
  title     = {Analytic  Dashboard on Talent Search Examination Data  Using Structure of Intellect Model},
  howpublished = {EasyChair Preprint 4651},
  year      = {EasyChair, 2020}}