Zayet Tasnim M A, Ismail Maizatul Akmar, Almadi Sara H S, Zawia Jamallah Mohammed Hussein, Mohamad Nor Azmawaty
Faculty of Computer Science and Information Technology, Universiti Malaya, 50603 Kuala Lumpur, Malaysia.
Faculty of Education, Universiti Malaya, 50603 Kuala Lumpur, Malaysia.
Educ Inf Technol (Dordr). 2023;28(6):7487-7508. doi: 10.1007/s10639-022-11489-4. Epub 2022 Dec 5.
Online learning has significantly expanded along with the spread of the coronavirus disease (COVID-19). Personalization becomes an essential component of learning systems due to students' different learning styles and abilities. Recommending materials that meet the needs and are tailored to learners' styles and abilities is necessary to ensure a personalized learning system. The study conducted a systematic literature review (SLR) of papers on recommendation systems for e-learning in the K12 setting published between 2017 and 2021 and aims to identify the most important component of a personalized recommender system for school students' e-learning. Recommendations for later studies were proposed based on the identified components, namely a personalized conceptual framework for providing materials to school students. The proposed framework comprised four stages: student profiling, material collection, material filtering, and validation.
随着冠状病毒病（COVID-19）的传播，在线学习有了显著扩展。由于学生的学习风格和能力各不相同，个性化成为学习系统的一个重要组成部分。推荐符合需求并根据学习者的风格和能力量身定制的材料对于确保个性化学习系统是必要的。该研究对2017年至2021年间发表的关于K12环境下电子学习推荐系统的论文进行了系统的文献综述（SLR），旨在确定针对中小学生电子学习的个性化推荐系统的最重要组成部分。基于所确定的组成部分，即一个为中小学生提供材料的个性化概念框架，提出了对后续研究的建议。所提出的框架包括四个阶段：学生画像、材料收集、材料筛选和验证。
