Exploring Intersections and Integrations: Advancing Equity in Educational HR Analytics
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.
Institutions
- Simon Fraser University (CA)
- University Canada West (CA)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-03
- DOI
- https://doi.org/10.5281/zenodo.15331148
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00