Abstract
With the rapid development of information technology and data science, as well as the innovative concept of “Internet+” education, personalized e-learning has received widespread attention in school education and family education. The development of education informatization has led to a rapid increase in the number of online learning users and an explosion in the number of learning resources, which makes learners face the dilemma of “information overload” and “learning lost” in the learning process. In the personalized learning resource recommendation system, the most critical thing is the construction of the learner model. Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. The purpose of this paper is to construct a learner model to support the above problems and to strongly support individual learning resources recommendation by learning the resource model which effectively reduces the problem of cold start and sparsity in the recommended process. In this paper, we analyze the behavioral data of learners in the learning process and extract three features of learner’s cognitive ability, knowledge level, and preference for learning of learner model analysis. Among them, the preference model of the learner is constructed using the ontology, and the semantic relation between the knowledge is better understood, and the interest of the student learning is discovered.
Highlights
With the in-depth development of education informatization, online education is highly respected by the majority of learners [1]
“learning lost” in the learning process, and learners have to struggle to find the information they really need from the vast sea of learning resources [3]. erefore, pushing appropriate learning resources for different learners is the focus of personalized learning in the online education environment [4]
Personalized learning emphasizes that the learning process is a process of promoting the full, free, and harmonious development of students in all aspects by adopting appropriate methods, means, contents, and evaluation methods according to their individual characteristics and development potential [5]
Summary
With the in-depth development of education informatization, online education is highly respected by the majority of learners [1]. Complexity uniform model” and “duck-fill model,” which is mainly “teacher-centered.” e teacher transmits knowledge and the learners receive it simultaneously It ignores the differences in learners’ knowledge level, learning ability, and learning preferences in the learning process [7]. Teachers are able to teach precisely through learners’ online learning behaviors, learning styles, learning preferences, and other personal characteristics; learners can access resources shared by experts through the Internet, and they can enter a community that suits their learning and collaborate with community partners to learn [11]. It has the function of inputting educational resource data and the function of data updating
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