Exploring Intersections and Integrations: Advancing Equity in Educational HR Analytics

Main Article Content

Gifty Parker

Abstract

In the realm of education, fostering equitable systems that promote student success necessitates preparing HR MBA students, administrators, and faculty to engage effectively with data and analytics. This research examines the intersection of HR analytics and educational equity, focusing on identifying and addressing gaps in the practical application of People Analytical Platforms (PAPs) within educational settings. Central to this inquiry is the concept of 'multimodal inclusiveness,' which emphasizes the adoption of practices that recognize and accommodate diverse modes of communication and interaction inherent in educational contexts. By fostering equitable engagement with analytical tools, this approach seeks to empower stakeholders to collaborate effectively and inclusively. This study employed a primarily survey‑based approach to explore how HR professionals engage with data and analytics in educational settings. An online questionnaire was completed by 192 participants—148 university administrators (mostly from Canadian and U.S. HR MBA programs), 18 alumni/current students, and 26 faculty and lecturers. Using survey analysis and thematic exploration, the study investigates how HR education programs prepare students to leverage analytics for fostering inclusivity, promoting ethical practices, and challenging inequities in education. By bridging the gap between theoretical knowledge and practical application, this research aims to equip future HR professionals with the tools and competencies needed to drive systemic change, enhance organizational accountability, and prioritize inclusivity. Ultimately, the findings underscore the transformative potential of HR analytics in shaping equitable, ethical, and inclusive practices within educational institutions, advancing both student well-being and institutional success.

Article Details

How to Cite
Exploring Intersections and Integrations: Advancing Equity in Educational HR Analytics. (2025). International Journal of Management and Data Analytics, 5(1), 132-148. https://ijmada.com/index.php/ijmada/article/view/79
Section
Regular Paper

How to Cite

Exploring Intersections and Integrations: Advancing Equity in Educational HR Analytics. (2025). International Journal of Management and Data Analytics, 5(1), 132-148. https://ijmada.com/index.php/ijmada/article/view/79

References

Abellán-Sevilla, A.-J., & Ortiz-de-Urbina-Criado, M. (2023). Smart human resource analytics for happiness management. The Journal of Management Development, 42(6), 514–525. https://doi.org/10.1108/JMD-03-2023-0064

Al-Hamad, N., Oladapo, O. J., Afolabi, J. O. A., & Olatundun, F. (2023). Enhancing educational outcomes through strategic human resources (HR) initiatives: emphasizing faculty development, diversity, and leadership excellence. Education, 1-11.

Belcourt, M., Singh, P., Snell, S., & Morris, S. (2022). Managing Human Resources, 10CE, Cengage Canada.

Boatright, D., London, M., Soriano, A. J., Westervelt, M., Sanchez, S., Gonzalo, J. D., McDade, W., & Fancher, T. L. (2023). Strategies and Best Practices to Improve Diversity, Equity, and Inclusion Among US Graduate Medical Education Programs. JAMA Network Open, 6(2), e2255110–e2255110. https://doi.org/10.1001/jamanetworkopen.2022.55110

Brancaccio-Taras, L., Awong-Taylor, J., Linden, M., Marley, K., Reiness, C. G., & Uzman, J. A. (2022). The PULSE diversity, equity, and inclusion (DEI) rubric is a tool to help assess departmental DEI efforts. Journal of microbiology and biology education, 23(3), e00057-22.

Brynjolfsson, E., & McElheran, K. (2019). Data in action: data-driven decision making and predictive analytics in US manufacturing. Rotman School of Management Working Paper, (3422397).

Bourdieu, P. (1986). The forms of capital. Handbook of theory and research for the sociology of education, 241(58), 241-258.

Cayla, J. (2021). Reforming Educational HR: A Poststructuralist Perspective. Educational Theory, 71(2), 245-263.

Claus, L. (2019). HR disruption—Time already to reinvent talent management. BRQ Business Research Quarterly, 22(3), 207-215.

Corsino, L., & Fuller, A. T. (2021). Educating for diversity, equity, and inclusion: A review of commonly used educational approaches. Journal of Clinical and Translational Science, 5(1), e169.

Dahlbom, P., Siikanen, N., Sajasalo, P., & Jarvenpää, M. (2020). Big data and HR analytics in the digital era. Baltic Journal of Management, 15(1), 120–138.

Derrida, J. (1973). Speech and Phenomena (D. B. Allison, Trans.). Evanston, IL: Northwestern University Press. (Original work published 1967)

Dodman, S. L., Swalwell, K., DeMulder, E. K., & Stribling, S. M. (2021). Critical data-driven decision making: A conceptual model of data used for equity, Teaching and Teacher Education, 99, 103272.

Eubanks, V. (2018). Automating inequality: how high-tech tools profile, police and punish the poor / Virginia Eubanks. (First edition.). St. Martin’s Press.

Etukudo, R. (2019). Strategies for using analytics to improve Human Resource Management (Doctoral dissertation, Walden University).

Fitzpatrick, K. (2019). Generous thinking: a radical approach to saving the university / Kathleen Fitzpatrick. Johns Hopkins University Press.

Freire, P. (1970). Pedagogy of the oppressed / Paulo Friere; translated by Myra Bergman Ramos. Herder and Herder.

Gal, U., Jensen, T. B., & Stein, M. K. (2020). Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics. Information and Organization, 30(2), 100301.

Gerber, R. (1994). Educational HR and Neoliberal Reforms: An Analysis. Journal of Educational Policy, 11(3), 345-361.

Guan, C., Mou, J., & Jiang, Z. (2020). Artificial intelligence innovation in education: A twenty-year data-driven historical analysis. International Journal of Innovation Studies, 4(4), 134–147.

Huang, X., Yang, F., Zheng, J., Feng, C., & Zhang, L. (2023). Personalized human resource management via HR analytics and artificial intelligence: theory and implications. Asia Pacific Management Review, 28(4), 598–610.

Huselid, M. A. (2018). The science and practice of workforce analytics: Introduction to the HRM special issue. Human Resource Management, 57(3), 679-684.

Johnson, M. P., & Chichirau, G. R. (2020). Diversity, equity, and inclusion in operations research and analytics: A research agenda for scholarship, practice, and service. Pushing the boundaries: Frontiers in impactful OR/OM research, 1-38.

Karwehl, L. (2021). Traditional and new ways in competence management: application of HR analytics in competence management.

Kolb, D. A. (1984). Experiential learning: experience as the source of learning and development / David A. Kolb. Prentice-Hall.

Kress, G., & van Leeuwen, T. (2001). Multimodal Discourse: The Modes and Media of Contemporary Communication. Bloomsbury Academic.

Kurilovas, E. (2020a). data-driven decision-making for quality education. Computers in Human Behavior, 107, 105774.

Kurilovas, E. (2020b). On data-driven decision-making for quality education. Computers in Human Behavior, 107, 105774. https://doi.org/10.1016/j.chb.2018.11.003

Larsson, A. S., & Edwards, M. R. (2022). Insider econometrics meets people analytics and strategic human resource management. The International Journal of Human Resource Management, 33(12), 2373-2419.

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.

Lengnick-Hall, M. L., Neely, A. R., & Stone, C. B. (2018). Human resource management in the digital age: Big data, HR analytics and artificial intelligence. In Management and technological challenges in the digital age (pp. 1-30). CRC Press.

Locke, T. (2004). Critical discourse analysis / Terry Locke. (1st ed.). Continuum.

Mandinach, E. B., & Schildkamp, K. (2021). Misconceptions about data-based decision making in education: An exploration of the literature. Studies in Educational Evaluation, 69, 100842. https://doi.org/10.1016/j.stueduc.2020.100842

Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32 (2), 100795.

McIver, D., Lengnick-Hall, M. L., & Lengnick-Hall, C. A. (2018). A strategic approach to workforce analytics: Integrating science and agility. Business Horizons, 61(3), 397-407.

Miller, S. R., Moore, F., & Eden, L. (2024). Ethics and international business research: considerations and best practices. International Business Review, 33(1), 102207.

Noble, S. U., & Project Muse, distributor. (2018). Algorithms of oppression: how search engines reinforce racism / Safiya Umoja Noble. New York University Press.

Nocker, M., & Sena, V. (2019). Big data and human resources management: The rise of talent analytics. Social Sciences, 8(10), 273.

Ogedengbe, D. E., James, O. O., Afolabi, J. O. A., Olatoye, F. O., & Eboigbe, E. O. (2023). Human resources in the fourth industrial revolution (4IR) era: strategies and innovations in the global south. Engineering Science & Technology Journal, 4(5), 308–322.

Oswald, F. L., Behrend, T. S., Putka, D. J., & Sinar, E. (2020). Big data in industrial-organizational psychology and human resource management: Forward progress for organizational research and practice. Annual Review of Organizational Psychology and Organizational Behavior, 7(1), 505-533.

Parker, G. (2023). Deconstructing people, analytics, and platforms: Multimodality, inclusion, and practice (Doctoral dissertation). Simon Fraser University, Faculty of Education.

Pinkett, R. (2023). Data-driven DEI: The tools and metrics you need to measure, analyze, and improve diversity, equity, and inclusion. John Wiley & Sons.

Pirini, J., et al. (2018). Multimodal Discourse Analysis: A Practical Guide for Social Researchers. Oxford University Press.

Qamar, Y., & Samad, T. A. (2022). Human resource analytics: a review and bibliometric analysis. Personnel Review, 51(1), 251-283

Rodgers, W., Murray, J. M., Stefanidis, A., Degbey, W. Y., & Tarba, S. Y. (2023). An artificial intelligence algorithmic approach to ethical decision-making in human resource management processes. Human resource management review, 33(1), 100925.

Roij, A., & Ahmed, S. (2015). On being included: racism and diversity in institutional life [Review of On being included: racism and diversity in institutional life]. International Sociology, 30(2), 172–175. https://doi.org/10.1177/0268580915571811

Saling, K. C., & Do, M. D. (2020). Leveraging people analytics for an adaptive complex talent management system. Procedia Computer Science, 168, 105-111.

Sedkaoui, S. (2018). How is data analytics changing entrepreneurial opportunities? International Journal of Innovation Science, 10(2), 274-294.

Selwyn, N. (2017). Education and technology: key issues and debates / Neil Selwyn. (2nd ed.). Bloomsbury Academic.

Talerico, C. K. M. (2022). Assessing the analytic competency gap for HR professionals: Providing HR a roadmap to data-driven decision-making.

Tran, H. (2022). Revolutionizing school HR strategies and practices to reflect talent centered education leadership. Leadership and Policy in Schools, 21(2), 238-252.

Tursunbayeva, A., Pagliari, C., Di Lauro, S., & Antonelli, G. (2022). The ethics of people analytics: risks, opportunities and recommendations. Personnel Review, 51(3), 900-921.

Tzimas, D., & Demetriadis, S. (2021). Ethical issues in learning analytics: A review of the field. Educational Technology Research and Development, 69, 1101-1133.

Varma, D., & Dutta, P. (2023). Empowering human resource functions with data-driven decision-making in start-ups: a narrative inquiry approach. International Journal of Organizational Analysis, 31(4), 945-958.

Varma, A., Dawkins, C., & Chaudhuri, K. (2023). Artificial intelligence and people management: A critical assessment through the ethical lens. Human Resource Management Review, 33(1), 100923.

Visscher, A. J. (2021). On the value of data-based decision-making in education: evidence from six intervention studies. Studies in educational evaluation, 69, 100899.

Wodak, R. (2011). Commentary Discourse, Context, and Interdisciplinarity. Annals of the International Communication Association, 35(1), 287–296. https://doi.org/10.1080/23808985.2011.11679119

Wu, L., Hitt, L., & Lou, B. (2020). Data analytics, innovation, and firm productivity. Management Science, 66(5), 2017-2039.

Zhang, Y., Xu, S., Zhang, L., & Yang, M. (2021). Big data and human resource management research: An integrative review and new directions for future research. Journal of Business Research, 133, 34-50.

Zuboff, S., & EBSCOhost. (2019). The age of surveillance capitalism: the fight for a human future at the new frontier of power / Shoshana Zuboff. (First edition.). PublicAffairs.

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