ICTACT Journal on Management Studies

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Emerging Trends In Research And Pedagogy Regarding Business Analytics - Opportunities And Challenges In Higher Education In India - 21 St Century-A Systematic Literature Review


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1 Department of Management Studies, Velidi Venkateswarlu and Mangamma Degree College, India
     

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The Advancement of technology has provided the opportunity to track and store students’ learning activities as big data sets within online environments. Big data refers to the capability of storing large quantities of data over an extended period and down to particular transactions. Educational data mining focuses on developing and implementing methods to promote discoveries from data in educational settings. It examines patterns in a large data set related to students’ actions. Learning analytics uses predictive models that provide actionable information. It is a multidisciplinary approach based on data processing, technology-learning enhancement, educational data mining, and visualization. LA increases awareness of learners and educators in their current situations that can help them make constructive decisions and more effectively perform their tasks. The literature review revealed that LA uses various methods including visual data analysis techniques, social network analysis, semantic, and educational data mining including prediction, clustering, relationship mining, discovery with models, and separation of data for human judgment to analyze data. Challenges include issues related to data tracking, collection, evaluation, analysis, lack of connection to learning sciences, optimizing learning environments, and ethical and privacy issues. Such a comprehensive overview provides an integrative report for faculty, course developers, and administrators about the methods, benefits, and challenges of LA so that they may apply LA more effectively to improve teaching and learning in higher education. This study has revealed the different methods used by learning analytics not only to show how the use of big data can benefit education but also to reveal the challenges faced by stakeholders in the educational process.

Keywords

Learning Analytics, Data Processing, Technology-Learning Enhancement
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  • Obadya Ray Shaguri, “Higher Education in India Access, Equity, Quality”, Available at https://docplayer.net/6311022-Higher-education-in-indiaaccess-equity-quality-obadya-ray-shaguri.html, Accessed at 2013.

  • Zareer Masani, “India Still Asia's Reluctant Tiger, BBC Radio 4”, Special Report: The Education Race, pp. 1-56, 2011.

  • Sramana Mitra, “How To Save The World's Back Office of Forbes”, Available at https://www.forbes.com/2008/03 /13/mitra-india-outsourcing-tech-enter-x_sm_0314outsourc e.html?sh=336b84513977. Accessed at 2008.

  • Fabrics Henard, “Learning our Lesson: Review of Quality teaching in Higher Education”, OECD Publisher, 2012.

  • P. Arunachalam, “Higher Education Sector in India: Issues and Imperatives”, Journal of Global Economy, Vol. 6, No 4, pp. 1-14, 2010.

  • S. Mallick, “Privatization of Education: A Boon or A Bane?”, Available at http://www.geocities.com/husociology/privatization.htm, Accessed at 2001.

  • Dukkipati Uttara, “Higher Education in India: Sustaining Long Term Growth”, South Asia Monitor, Available at https://csis-website-prod.s3.amazonaws.com/s3fspublic/legacy_files/files/publication/sam_141.pdf, Accessed at 2010.

  • Debkumar Mukherjee, “Higher Education in IndiaConcerns and Strategies”, Journal of Education and Practices, Vol. 3, No. 2, pp. 17-24, 2010.

  • Sumeet Gupta, “Higher Education in India: Twelfth Five Year Plan (2012–2017) and Beyond”, Available at https://www.ficci-hes.com/eny-report.html, Accessed at 2012.

  • Higher Education in India: Issues, Concerns and New Directions, Available at http://www.ugc.ac.in/pub/heindia.pdf, Accessed at 2019.

  • American Federation of Teachers, “Higher Education Program and Policy Council”, Available at http://www.aft.org/higher_ed/downloadable/distance.pdf, Accessed at 2000.

  • J.F. Chizmar and M.S. Walber, “Web-Based Learning Environments Guided by Principles of Good Teaching Practice”, Journal of Economic Education, Vol. 3, No. 2, pp.248-264, 1999.

  • Institute for Higher Education Policy, “Quality on the line: benchmarks for success in Internet-base distance education. Washington, DC: Institute for Higher Education Accreditation”, Available at

  • http://www.ihep.org/Pubs/PDF/Quality.pdf, Accessed at 1999.

  • L.A. Petrides, “Web-Based Technologies for Distributed (or Distance) Learning: Creating Learner-Centered Educational Experiences in the Higher Education Classroom”, International Journal of Instructional Media, Vol. 29, No.1, pp. 69-77, 2002.


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  • Emerging Trends In Research And Pedagogy Regarding Business Analytics - Opportunities And Challenges In Higher Education In India - 21 St Century-A Systematic Literature Review

Abstract Views: 285  |  PDF Views: 0

Authors

V Venkateswara Rao
Department of Management Studies, Velidi Venkateswarlu and Mangamma Degree College, India

Abstract


The Advancement of technology has provided the opportunity to track and store students’ learning activities as big data sets within online environments. Big data refers to the capability of storing large quantities of data over an extended period and down to particular transactions. Educational data mining focuses on developing and implementing methods to promote discoveries from data in educational settings. It examines patterns in a large data set related to students’ actions. Learning analytics uses predictive models that provide actionable information. It is a multidisciplinary approach based on data processing, technology-learning enhancement, educational data mining, and visualization. LA increases awareness of learners and educators in their current situations that can help them make constructive decisions and more effectively perform their tasks. The literature review revealed that LA uses various methods including visual data analysis techniques, social network analysis, semantic, and educational data mining including prediction, clustering, relationship mining, discovery with models, and separation of data for human judgment to analyze data. Challenges include issues related to data tracking, collection, evaluation, analysis, lack of connection to learning sciences, optimizing learning environments, and ethical and privacy issues. Such a comprehensive overview provides an integrative report for faculty, course developers, and administrators about the methods, benefits, and challenges of LA so that they may apply LA more effectively to improve teaching and learning in higher education. This study has revealed the different methods used by learning analytics not only to show how the use of big data can benefit education but also to reveal the challenges faced by stakeholders in the educational process.

Keywords


Learning Analytics, Data Processing, Technology-Learning Enhancement

References