在线学习个性化推荐中多维度学习者模型研究  

Research on multi-dimensional learner model in online learning personalized recommendation

作　　者：刘芳[1] 田枫[1] 李欣 刘宗堡[3] 黄美晨 赵玲[1] LIU Fang;TIAN Feng;LI Xin;LIU Zong-bao;HUANG Mei-chen;ZHAO Ling(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,Heilongjiang Province,China;Nehe No.1 Middle School,Qiqihar 161300,Heilongjiang Province,China;School of Earth Sciences,Northeast Petroleum University,Daqing 163318,Heilongjiang Province,China)

机构地区：[1]东北石油大学计算机与信息技术学院,黑龙江大庆163318 [2]讷河市第一中学,黑龙江齐齐哈尔161300 [3]东北石油大学地球科学学院,黑龙江大庆163318

出　　处：《信息技术》2024年第1期44-51,共8页Information Technology

基　　金：黑龙江省哲学社会科学基金(22EDE389);东北石油大学引导性创新基金项目(2020YDL-11);东北石油大学优秀中青年科研创新团队(KYCXTD201903);东北石油大学研究生教育创新工程项目(JYCX_11_2020);黑龙江省教育科学规划重点课题(GJB1421113);黑龙江省高等学校教改工程项目(SJGZ20200037);黑龙江省优秀青年科学基金项目(YQ2020D001)。

摘　　要：随着在线学习平台的广泛使用,在线学习资源快速增长,“信息迷航”问题亟待解决。针对在线学习个性化推荐中以单一特征为主,多维度学习者模型研究较少的问题,文中以CELTS-11学习者模型规范为基础,以教育学相关理论为指导,对学习者的学习风格、知识状态、认知能力、兴趣偏好等多维度的个性化特征进行细化分类研究。利用教育数据挖掘等技术获得学习者特征项,进而构建出个性化的多维度学习者模型。该模型为后续在线学习个性化的推送服务提供有力的依据。With the wide use of online learning platforms and the rapid growth of online learning resources,the problem of “information trek” needs to be solved urgently.To solve the problem that online learning personalized recommendation is dominated by single features and there are few studies on multi-dimensional learner model,based on the CELTS-11 learner model and guided by relevant theories of pedagogy,this paper conducts a detailed classification study from the perspective of learners' learning style,knowledge state,cognitive ability,interest preference and other multidimensional personalized characteristics.By using educational data mining and other techniques to obtain learner feature items,a personalized multidimensional learner model is constructed.This model provides a strong basis for personalized push service of online learning.

关 键 词：个性化推荐 多维度学习者模型 学习风格 认知能力 知识状态 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术] G434[自动化与计算机技术—计算机科学与技术]