Teachers' Perspectives on the Use of AI Detection Tools: Insights from Ridge Regression Analysis

TL;DR

This study investigates Filipino teachers' perceptions of AI detection tools, highlighting trust as the key factor influencing perceived fairness and decision-making, with concerns and social norms playing lesser roles.

Contribution

It provides empirical evidence on the importance of trust in AI tools for teachers' perceptions, using ridge regression analysis to identify key predictors.

Findings

Trust significantly predicts perceived fairness and decision-making.

Concerns and social norms have limited effects on perceptions.

Training and guidelines can enhance trust and effective use.

Abstract

This study explores the perceptions of 213 Filipino teachers toward AI detection tools in academic settings. It focuses on the factors that influence teachers' trust, concerns, and decision-making regarding these tools. The research investigates how teachers' trust in AI detection tools affects their perceptions of fairness and decision-making in evaluating student outputs. It also explores how concerns about AI tools and social norms influence the relationship between trust and decision-making. Ridge Regression analysis was used to examine the relationships between the predictors and the dependent variable. The results revealed that trust in AI detection tools is the most significant predictor of perceived fairness and decision-making among teachers. Concerns about AI tools and social norms have weaker effects on teachers' perceptions. The study emphasized critical role of trust in shaping teachers' perceptions of AI detection tools. Teachers who trust these tools are more likely to view them as fair and effective. In contrast, concerns and social norms have a limited influence on perceptions and decision-making. For recommendations, training and institutional guidelines should emphasize how these tools work, their limitations, and best practices for their use. Striking a balance between policy enforcement and educator support is essential for fostering trust in AI detection technologies. Encouraging experienced users to share insights through communities of practice could enhance the adoption and effective use of AI detection tools in educational settings..