Employing Artificial Intelligence in Developing Blended Learning Strategies in Educational Institutions

Abstract

Artificial Intelligence (AI) is utilized in blended learning to personalize educational pathways according to students' patterns and needs, thereby enhancing effectiveness and flexibility within educational institutions. AI-driven Learning Management Systems (LMS) also help automate repetitive tasks like assessment and content development, and provide accurate analytics to monitor student progress. Moreover, AI transforms the role of the teacher from a knowledge dispenser to a facilitator and mentor, encouraging students to think critically and build digital literacy skills. But there are also basic issues in implementing such an approach, with the most important being the poor technical infrastructure, a lack of faculty training, and the ethical questions of algorithmic bias and data integrity. Research shows that integrated institutional structures with well-defined connections between learning outcomes and integrated AI systems, as well as designing educational activities involving a mix of self-paced learning and in-person interaction, are essential to successful integration. Models have been successfully implemented in a wide variety of settings, including some in Iraqi universities, which have helped to boost success rates and increase engagement when institutional support is provided, and sufficient institutional training is given. Furthermore, the application of generative tools, such as the use of chatbots, in a flipped classroom has proven effective in improving interaction and giving immediate feedback, provided they have adequate skills in prompt engineering to not be relying on the output. Building policies, forming partnerships with technology providers and creating sustainable professional development programs are essential in the future to ensure AI technologies are adopted in a way that is ethical and effective in blended learning environments.