华东师范大学学报（自然科学版） >

2018 , Vol. 2018 >Issue 5: 17 - 29

DOI: https://doi.org/10.3969/j.issn.1000-5641.2018.05.002

综述论文

基于非干预式感知的个性化学业求助资源推荐研究进展

  • 汤路民 ,
  • 余若男 ,
  • 董启文 ,
  • 洪道诚 ,
  • 傅云斌
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  • 华东师范大学 数据科学与工程学院, 上海 200062
汤路民,男,硕士研究生,研究方向为机器学习.E-mail:51174500126@stu.ecnu.edu.cn.

收稿日期: 2018-07-09

  网络出版日期: 2018-09-26

基金资助

教育部人文社科青年基金（15YJC630032）；国家自然科学基金（61332013，61672161）；华东师范大学信息化软课题

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A review of non-intrusive sensing based personalized resource recommendations for help-seekers in education

  • TANG Lu-min ,
  • YU Ruo-nan ,
  • DONG Qi-wen ,
  • HONG Dao-cheng ,
  • FU Yun-bin
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  • School of Data Science and Engineering, East China Normal University, Shanghai 200062, China

Received date: 2018-07-09

  Online published: 2018-09-26

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摘要

现代信息技术提供的强大移动终端、数据存储和计算平台，极大地促进了信息技术和教育学科的深度融合，有利地推动了"教育信息化2.0行动计划"的实施，也为研究学业求助提供了坚实的技术保障.借助多种新型的感知机理和实现技术，建立日常教学实践活动中非干预式的学业求助行为感知和分类，使实现自适应个性化的学业求助资源推荐成为可能.本文针对非干预式感知的个性化学业求助资源推荐研究状况，展开具体分析，并针对未来可能研究进行了展望：学业求助非干预式感知、学业求助多源异构数据分析、以及学业求助资源个性化推荐方法.以上研究内容充分利用和发挥了现代信息技术的优势，探索其在学业求助应用场景下切实可行的途径和方法.有利于实现对学习者学业求助需求的精准定位并提供自适应个性化的资源推荐，贯彻了我国教育信息化2.0建设中的精准教育理念，具有理论和实际的双重意义.

关键词： 学业求助; 非干预式感知; 教育信息化2.0; 个性化教育; 精准教育

本文引用格式

汤路民 , 余若男 , 董启文 , 洪道诚 , 傅云斌 . 基于非干预式感知的个性化学业求助资源推荐研究进展[J]. 华东师范大学学报（自然科学版）, 2018 , 2018(5) : 17 -29 . DOI: 10.3969/j.issn.1000-5641.2018.05.002

Abstract

Mobile devices, data storage, and computing platforms of modern information technology have accelerated the integration of the information technology and education disciplines, promoted the "Education Informatization 2.0" Plan, and provided a solid technical foundation for academic help-seeking. With the help of new sensing mechanisms and techniques, non-intrusive sensing of help-seeking and personalized recommendation methods can now be used for teaching practices in academia. This study reviews the research progress of non-intrusive sensing based personalized resource recommendations, offers detailed analysis, and lists possible directions for research; potential future research topics include non-intrusive sensing for help-seeking, continuous association analysis and integration for multidimensional data, and personalized resource recommendations for help-seekers. This study also makes contributions to precision education and personalized education for the China Education Informatization 2.0 Plan by providing solutions for non-intrusive sensing based personalized resource recommendations for help-seekers.

Key words： help-seeking; non-interventional perception; education informatization 2.0; personalized education; precision education

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