人工智能支持下的智适应学习模式

Intelligent Adaptive Learning Model Supported by Artificial Intelligence

因材施教抑或因材促学一直是个性化学习追求的价值取向,然而如何获悉已学知识点的掌握程度以及学习者学习捷径的引领则是其亟需面临的挑战,基于人工智能技术的智适应学习系统为解决这一困境提供了有效参照。智适应学习以知识空间理论、信息流理论以及贝叶斯定理等为基础实现了人工智能技术支持下的高效个性化学习。智适应学习以纳米级的知识点作为学习内容形态,以最佳学习路径的引荐作为学习过程向导,以个性化学习和高效学习效率作为智适应学习的出发点和最终归宿。智适应学习系统呈现了一个完整的智适应学习运行流程,形成了"测、学、练、测、辅"五位一体的学习模式。智适应学习的应用案例表明,其在1:1教与学、精准学习评价以及O2O学习中具有突出的潜在优势。

Teaching or promoting learning according to learners’ aptitude have been the value orientation of the pursuit for individualized learning. However, how to learn the mastery of knowledge and how to guide learners to learn shortcuts are urgent challenges. The intelligent adaptive learning system based on artificial intelligence provides an effective reference to solve this dilemma, w realizes high efficient individualized learning under the support of artificial intelligence technology based on the theory of knowledge space, the theory of information flow and the Bayes theorem. The intelligence adaptation learning takes nanoscale knowledge points as learning content form, takes the recommendation of best learning path as the guide of learning process, and takes personalized and efficient learning as the starting point and final destination of intelligent adaptive learning. The system presents a complete intelligent adaptive learning process, builds the learning mode including five Essential factors that are "test, study, training, testing, and auxiliary". The application example of adaptive learning show that it have some outstanding advantages among 1:1 teaching and learning, precision learning evaluation and O2O learning.