V. Munde, Binod Kumar, Anagha Vaidya, S. Shirwaikar
{"title":"基于智力模型结构的人才招聘考试数据分析仪表板","authors":"V. Munde, Binod Kumar, Anagha Vaidya, S. Shirwaikar","doi":"10.47164/IJNGC.V12I2.766","DOIUrl":null,"url":null,"abstract":"The potential of Analytics and Data mining methodologies, that extract useful and actionable information from \nlarge data-sets, has transformed one field of scientific inquiry after another. Analytics has been widely applied \nin Business Organizations as Business Analytics and when applied to education, these methodologies are referred \nto as Learning Analytics and Educational Data mining. Learning Analytics proposes to collect, measure and \nanalyze data in learning environments to improve teaching and learning process. Educational Data mining (EDM) \nthrives on existing data collected by learning management systems. The applicability of Learning Analytics and \nEducational Data mining can be extended to traditional learning processes by suitably combining data collected \nfrom technology enabled processes such as Admission and Assessment with data generated from analysis of learning \ninteractions. The intellectual performance of the students can be analyzed using some well known Learning \nFrameworks. This paper demonstrates the Complete Analytics process from data collection, measurement to \nAnalysis using Guilford’s structure of intellect model. An analytic dashboard provides the necessary information \nin concise and visual form and in an interactive mode. The analytic process presented on talent examination data \ncan be generalized to similar examinations in traditional educational setup.","PeriodicalId":351421,"journal":{"name":"Int. J. Next Gener. Comput.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytics Dashboard on Talent search Examination Data using Structure of Intellect Model\",\"authors\":\"V. Munde, Binod Kumar, Anagha Vaidya, S. Shirwaikar\",\"doi\":\"10.47164/IJNGC.V12I2.766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The potential of Analytics and Data mining methodologies, that extract useful and actionable information from \\nlarge data-sets, has transformed one field of scientific inquiry after another. Analytics has been widely applied \\nin Business Organizations as Business Analytics and when applied to education, these methodologies are referred \\nto as Learning Analytics and Educational Data mining. Learning Analytics proposes to collect, measure and \\nanalyze data in learning environments to improve teaching and learning process. Educational Data mining (EDM) \\nthrives on existing data collected by learning management systems. The applicability of Learning Analytics and \\nEducational Data mining can be extended to traditional learning processes by suitably combining data collected \\nfrom technology enabled processes such as Admission and Assessment with data generated from analysis of learning \\ninteractions. The intellectual performance of the students can be analyzed using some well known Learning \\nFrameworks. This paper demonstrates the Complete Analytics process from data collection, measurement to \\nAnalysis using Guilford’s structure of intellect model. An analytic dashboard provides the necessary information \\nin concise and visual form and in an interactive mode. The analytic process presented on talent examination data \\ncan be generalized to similar examinations in traditional educational setup.\",\"PeriodicalId\":351421,\"journal\":{\"name\":\"Int. J. Next Gener. Comput.\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Next Gener. Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47164/IJNGC.V12I2.766\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Next Gener. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47164/IJNGC.V12I2.766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analytics Dashboard on Talent search Examination Data using Structure of Intellect Model
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 Analytics 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.