A Framework for Evaluating AI Powered Learning Platforms in K-12 and University CS Education

Integrating artificial intelligence (AI) in education holds great potential for enhancing learning experiences. However, the proliferation of AI learning platforms complicates the assessment of their effectiveness, especially across diverse learner groups. This paper presents a comprehensive evaluation framework for assessing AI-powered learning platforms in K12 and university computer science education. The framework considers factors such as pedagogical alignment, learner engagement, cognitive load, and accessibility. Tailored surveys combine standardized scales to provide a holistic understanding of AI platforms' impact on learning outcomes. A case study in an introductory AI course utilized the framework to evaluate an adaptive learning assistant. Results indicated that the framework effectively identified usage patterns and impacts on the learning processes. Findings emphasize the need for carefully designed AI learning platforms that support educational goals. The framework is a valuable tool for educators integrating AI technologies into their teaching. Future developments will include advanced analytical methods and automated surveys, enabling informed decisions about AI in education.