Using Data Analytics to Monitor Gender Equality in Higher Education Institutions

Using Data Analytics to Monitor Gender Equality in Higher Education Institutions

  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-12
Year of Publication : 2022
Author : Silvia Gaftandzhieva, Rositsa Doneva, Marieta Atanasova, Milen Bliznakov
DOI : 10.14445/22315381/IJETT-V70I12P202

How to Cite?

Silvia Gaftandzhieva, Rositsa Doneva, Marieta Atanasova, Milen Bliznakov, "Using Data Analytics to Monitor Gender Equality in Higher Education Institutions," International Journal of Engineering Trends and Technology, vol. 70, no. 12, pp. 13-19, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I12P202

Abstract
Nowadays, many policies have encouraged organizations to develop Gender Equality Plans (GEPs) and monitor their implementation. The paper presents a prototype of a data analytics tool for gender equality monitoring GEAnalyst designed for the needs of higher education institutions (HEIs) from the perspective of different stakeholder groups. The tool allows them to understand key gaps between women and men within the HEI and its activities, take data-informed decisions to ensure equal access to education and career development, increase the sense of equality among the university community, set priorities, and adjust these priorities as the situation evolves.

Keywords
Data analytics, Software tools, Data collection, Monitoring, Higher education institutions.

References
[1] European Commission, “Horizon Europe Guidance on Gender Equality Plans,” Publications Office of the European Union, Luxembourg, 2021. Crossref, http://doi.org/10.2777/876509
[2] C. Lopes, and S. Bailur, “Gender Equality and Big Data: Making Gender Data Visible,” 2019.
[3] Beatriz Sanz Sáiz, “Five Ways Data Analytics Can Help Close the Gender Gap,” 2019. [Online]. Available: https://www.ey.com/en_bg/digital/five-ways-data-analytics-can-help-close-the-gender-gap
[4] Kayla Matthews, “How HR is Using Data Science and Analytics to Close the Gender Gap,” 2020. [Online]. Available: https://www.kdnuggets.com/2020/01/hr-data-science-analytics-gender-gap.html
[5] Vandana Joshi, “Gender Discrimination at Work Place: A Significant Barrier for Women Empowerment,” SSRG International Journal of Humanities and Social Science, vol. 6, no. 1, pp. 12-15, 2019. Crossref, https://doi.org/10.14445/23942703/IJHSS-V6I1P103
[6] G. Muneeswari et al., "Urban Computing: Recent Developments and Analytics Techniques in Big Data," International Journal of Engineering Trends and Technology, vol. 70, no. 7, pp. 158-168, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I7P217
[7] Surabhi Singh, Lata Bajpai Singh, and Anjali Rai, “Investigating the Analytics for Workforce Automation,” SSRG International Journal of Economics and Management Studies, vol. 9, no. 5, pp. 23-31, 2022. Crossref, https://doi.org/10.14445/23939125/IJEMS-V9I5P103
[8] Bart Rienties et al., “A Review of Ten Years of Implementation and Research in Aligning Learning Design with Learning Analytics at the Open University UK,” Interaction Design and Architecture(s), vol. 33, pp. 134–154, 2017.
[9] Sadiq Hussain et al., “Prediction Model on Student Performance based on Internal Assessment using Deep Learning,” International Journal of Emerging Technologies in Learning, vol. 14, no. 8, pp. 4-22, 2019. Crossref, https://doi.org/10.3991/ijet.v14i08.10001
[10] Nurbiha A Shukor, and Zaleha Abdullah, “Using Learning Analytics to Improve MOOC Instructional Design,” International Journal of Emerging Technologies in Learning, vol. 14, no. 24, pp. 6-17, 2019. Crossref, https://doi.org/10.3991/ijet.v14i24.12185
[11] Silvia Gaftandzhieva et al., “Mobile Learning Analytics Application: Using Students' Big Data to Improve Student Success,” International Journal on Information Technologies & Security, vol.10, no. 3, pp. 53-64, 2018.
[12] Billy Tak-ming Wong, and Kam Cheong Li, “A Review of Learning Analytics Intervention in Higher Education (2011–2018),” Journal of Computers in Education, vol. 7, pp. 7–28, 2020. Crossref, https://doi.org/10.1007/s40692-019-00143-7
[13] Miloslava Cerna, “Modified Recommender System Model for the Utilized e-learning Platform,” Journal of Computers in Education, vol. 7, no. 1, pp. 105–129, 2020. Crossref, https://doi.org/10.1007/s40692-019-00133-9
[14] S. Gaftandzhieva, and R. Doneva, “Data Analytics to Improve and Optimize University Processes,” ICERI21 Proceedings, pp. 6236-6245, 2021. Crossref, http://doi: 10.21125/iceri.2021.1404.
[15] Sadiq Hussain et al., “Regression Analysis of Student Academic Performance Using Deep Learning,” Education and Information Technologies, vol. 26, no. 1, pp. 783–798, 2021. Crossref, https://doi.org/10.1007/s10639-020-10241-0
[16] Silvia Gaftandzhieva, Rositsa Doneva, and Milen Bliznakov, “Internal and External QA in HE: LA Tools and Self-Evaluation Report Preparation,” International Journal of Emerging Technologies in Learning, vol. 15, no. 16, pp. 191-199, 2020. Crossref, https://doi.org/10.3991/ijet.v15i16.14401
[17] Rositsa Doneva et al., “Learning Analytics Software Tool Supporting Decision Making in Higher Education,” International Journal on Information Technologies and Security, vol. 12, no. 2, pp. 37-46, 2020.
[18] TARGET, “Taking a Reflexive Approach to Gender Equality for Institutional Transformation,” 2018.
[19] EIGE, “Gear Tool,” 2016. [Online]. Available: https://eige.europa.eu
[20] Venkateswarlu Pynam, R Roje Spanadna, and Kolli Srikanth, "An Extensive Study of Data Analysis Tools (Rapid Miner, Weka, R Tool, Knime, Orange)," SSRG International Journal of Computer Science and Engineering, vol. 5, no. 9, pp. 4-11, 2018. Crossref, https://doi.org/10.14445/23488387/IJCSE-V5I9P102
[21] R. Doneva, S. Gaftandzhieva, and K. Boykova, “An Approach to Monitoring Gender Equality Plans Implementation,” EDULEARN22 Proceedings, pp. 3383-3391, 2022. Crossref, https://doi.org/10.21125/edulearn.2022.0829
[22] Radi Petrov Romansky, “A Survey of Digital World Opportunities and Challenges for User’s Privacy,” International Journal on Information Technologies and Security, vol. 9, no. 4, pp. 97-112, 2017.
[23] L. Madamshetty, K. Suresh, and B. Naidu, “Integrating Big Data in Higher Education: Perspectives and Challenges,” 2020. [Online]. Available: https://www.¬ee.co.za/-article/integrating-big-data-in-higher-education-perspectives-and-challenges.html
[24] Plovdiv University, Paisius of Hilendar, “Gender Equality Plan (2021-2024),” 2021. [Online] Available: https://genderspear.eu/assets/content/¬PU_GEP_EN¬finalS.PDF
[25] Ben Daniel, “Big Data and Analytics in Higher Education: Opportunities and Challenges,” British Journal of Educational Technology, vol. 46, no. 5, pp. 904-920, 2019. Crossref, https://doi.org/10.1111/bjet.12230