Exploration of College Students' Learning Adaptability Under the Background of Wisdom Education

Introduction

With the rapid development of internet+, big data, and artificial intelligence technology, the traditional education industry is showing the characteristics of “wisdom.” By means of information technology, intelligent technology is applied to education to improve the quality and efficiency of education (Nevzorova et al., 2023). The core of wisdom education is to provide personalized learning resources and teaching methods according to students' individual characteristics and needs, so as to promote students' learning interest and initiative (Yuniata et al., 2023). With the rapid development of smart education, it is very important for college students to learn adaptively (Clunis, 2023). In traditional education, teachers are the main focus, and students passively accept knowledge (Cheung et al., 2021). However, under smart education, students get rich educational resources and information, and they can realize personalized learning according to their own interests, hobbies, and learning styles (Keskitalo & Ruokamo, 2021). This adaptive learning method stimulates students' learning motivation and potential and improves learning effect. Therefore, under wisdom education, the study of college students' learning adaptability is of great significance (Ivemark & Ambrose, 2021). This paper takes college students' learning adaptability as the research object; adopts B/S structure to develop an adaptive learning platform; designs a learner data model, a learning style model, a learning resource presentation module, and an ability level testing module; tests the platform through simulated data; analyzes college students’ learning style, knowledge level, and learner collaboration level; and provides theoretical data support for exploring college students' learning adaptability under the background of smart education.