With the advent of the “Internet+” era, with the rapid development of emerging technologies such as the Internet of Things, cloud computing, big data, and artificial intelligence, the era of the technological change in education has arrived, with diversification of resources and large-scale data. And the intelligence of computing provides an opportunity for the research and practice of personalized support services. Personalized learning is the future learning method under the demands of smart education, and the learner’s interest feature model is the core of personalized learning services. Although the research on smarter classrooms has achieved certain results, there are still shortcomings that cannot be ignored, that is, how to use smarter classrooms to meet the “personalized needs” of learners and give students “personalized feedback” is still an urgent problem to be solved. Therefore, building a student interest model in a smart learning environment will help teachers better capture students’ learning interests and personalized needs, so as to provide them with personalized learning services.