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Artificial intelligence (AI) technologies play an essential role in teaching and learning at the high school level. Recently, Generative AI has piqued the interest of educators. A few teaching/learning platforms employ Generative AI technologies to varying degrees. This study evaluates three generative AI platforms, Khanmigo, MATHia®, and Knewton Alta (Education Platform C), using the Task-Technology Fit (TTF) model. Each platform is assessed along five key factors: Real-Time Adaptivity, Predictive Modeling, Knowledge Tracing, Automated Feedback, and Persona Classification. MATHia® showed the best instructional intelligence by offering strong feedback and using cognitive modeling, while Khanmigo was very good at adapting conversations. These results demonstrate how these tools enable teachers to provide varied instructional approaches and support personalized learning in high school STEM classes. The findings offer guidance to teachers and decision-makers on how well these platforms match teaching tasks, helping them make wise choices about using AI in secondary education.

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Comparison of Generative AI Platforms in Secondary Education: An Application Using the Task-Technology Fit Model

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  • 发表日期：

    2026年

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  • Dharmender Salian,
  • Solomon Antony,
  • Rabih Neouchi,
  • Gasan Elkhodari,
  • Steven Brown,
  • Eduard Babulak

摘要

Artificial intelligence (AI) technologies play an essential role in teaching and learning at the high school level. Recently, Generative AI has piqued the interest of educators. A few teaching/learning platforms employ Generative AI technologies to varying degrees. This study evaluates three generative AI platforms, Khanmigo, MATHia®, and Knewton Alta (Education Platform C), using the Task-Technology Fit (TTF) model. Each platform is assessed along five key factors: Real-Time Adaptivity, Predictive Modeling, Knowledge Tracing, Automated Feedback, and Persona Classification. MATHia® showed the best instructional intelligence by offering strong feedback and using cognitive modeling, while Khanmigo was very good at adapting conversations. These results demonstrate how these tools enable teachers to provide varied instructional approaches and support personalized learning in high school STEM classes. The findings offer guidance to teachers and decision-makers on how well these platforms match teaching tasks, helping them make wise choices about using AI in secondary education.