The Future of Intelligent Teaching Systems: Bridging the Gap Between Human and AI Instructions

Abstract

Intelligent Teaching Systems (ITS) perspectives are the subject matter of this paper, specifically focusing on how these systems could be used to improve educational outcomes. The study conducted a survey using educators from different education levels, and the findings showed that it greatly benefits the students in terms of enhancing engagement and exposing learning disparities and individual differences among the learners. Nonetheless, some of the main concerns are data privacy, low usability, and inadequate technical support, which becomes a significant concern to ITS adoption. Privacy was the most bracing issue for 60% of the participants, who were anxious over data privacy and had inherent biases within the algorithms. Several concerns on usability were also raised by educators who reported inadequate training materials and difficulties in incorporating ITS with conventional teaching-learning methods. This work also emphasizes moderation, where ITS supplements human tutor guidance, enabling educators to incorporate flexible system learning while maintaining human affinity, sensitivity, and adaptability. This research provides valuable information on areas needing ITS focus in the future, such as ethical guidelines, proper training, and better access as the groundwork for proper ITS development.