  Numerous AI ethics checklists and frameworks have been proposed focusing on
different dimensions of ethical AI such as fairness, explainability, and
safety. Yet, no such work has been done on developing transparent AI systems
for real-world educational scenarios. This paper presents a Transparency Index
framework that has been iteratively co-designed with different stakeholders of
AI in education, including educators, ed-tech experts, and AI practitioners. We
map the requirements of transparency for different categories of stakeholders
of AI in education and demonstrate that transparency considerations are
embedded in the entire AI development process from the data collection stage
until the AI system is deployed in the real world and iteratively improved. We
also demonstrate how transparency enables the implementation of other ethical
AI dimensions in Education like interpretability, accountability, and safety.
In conclusion, we discuss the directions for future research in this newly
emerging field. The main contribution of this study is that it highlights the
importance of transparency in developing AI-powered educational technologies
and proposes an index framework for its conceptualization for AI in education.
