Potential Abstract: This research article examines the intersection of stereotypes, educational technology, and assessment practices in the context of cloud-based operations. Drawing on Marxist theory, the study explores how power dynamics, social constructions, and ideologies manifest in the design and implementation of assessment tools within educational technology platforms. Through a critical analysis of existing literature and case studies, this article seeks to uncover the ways in which stereotypes are perpetuated and reinforced through standard assessment practices in cloud-based operations, and proposes strategies for promoting more authentic assessment methods that challenge and disrupt these stereotypes. By centering the experiences and perspectives of marginalized groups, this research aims to contribute to a more equitable and inclusive educational technology landscape.
Potential References:
- Using the implicit relational assessment procedure (IRAP) to examine implicit gender stereotypes in science, technology, engineering and maths (STEM)
- Gender stereotypes in educational software for young children
- Static and dynamic assessment of STEM gender stereotypes in secondary education using a novel cluster-based analysis
- A supervised learning approach to detect gender stereotype in online educational technologies
- Breaking the STEM stereotype: Investigating the use of robotics to change young children’s gender stereotypes about technology and engineering
