| 1,835 | 32 | 439 |
| 下载次数 | 被引频次 | 阅读次数 |
基于数据智能分析的学习资源推送是精准支持个性化学习的教学服务方式之一。随着人工智能技术和学习分析技术的发展，通过对行为数据、测评数据和日志数据等的分析进行资源推送虽已有较成功应用，但未能实现学习者个人情感状态为引导的资源推送。为此，该研究针对个性化学习资源推荐中情感价值、情感控制理论和实践的缺失，以实现个性化学习多维度情感识别为目标，采用BERT模型和TextCNN构建个性化学习资源推荐文本情感识别模型，并提出了基于学习者作业、论坛内容等的文本情感识别模型实现过程。学习资源推荐文本情感识别模型和实现过程可为真实应用提供方法支持和技术路线指引。
Abstract：Learning resource pushing based on data intelligence analysis is one of the teaching services that precisely support personalized learning. With the development of artificial intelligence technology and learning analytics, resource pushing through the analysis of behavioral data, assessment data and log data has been more successfully applied, but it fails to realize resource pushing guided by learners' personal emotional state. Therefore, this study addresses the lack of theory and practice of emotion value and emotion control in personalized learning resource recommendation, and aims to achieve multidimensional emotion recognition for personalized learning, uses BERT model and TextCNN to build a text emotion recognition model for personalized learning resource recommendation, and proposes the process of implementing the text emotion recognition model based on learners' homework and forum content. The learning resource recommendation text sentiment recognition model and the implementation process can provide methodological support and technical route guidance for real applications.
[1]祝智庭.教育数字化转型新认知[J].教育家,2023,360(4):13-15.
[2]宗阳,郑勤华等.中国MOOCs学习者价值研究--基于RFM模型的在线学习行为分析[J].现代远距离教育,2016,164(2):21-28.
[3]吴正洋,汤庸等.个性化学习推荐研究综述[J].计算机科学与探索,2022,16(1):21-40.
[4]翟雪松,许家奇等.在线教育中的学习情感计算研究--基于多源数据融合视角[J].华东师范大学学报(教育科学版),2022,40(9):32-44.
[5]SCHERER K R.Psychological models of emotion[J].The Neuropsychology of Emotion,2000,137(3):137-162.
[6]ORTONY A,TURNER T J.What’s basic about basic emotions?[J].Psychological Review,1990,97(3):315.
[7]MEHRABIAN A.Pleasure-arousal-dominance:A general framework for describing and measuring individual differences in temperament[J].Current Psychology,1996,14(4):261-292.
[8]Bahreini,K.,Nadolski,R.,et al.Towards multimodal emotion recognition in E-learning environments[J].Interactive Learn Ing Environments,2016,24(3):590-605.
[9]Cordero,J.,Aguilar,J.,et al.Intelligent approaches to identify student learning styles through emotions in a classroom[J].Revista Ibérica de Sistemas e Tecnologias de Informa??o,2019,E17:703-716.
[10]Hudlicka E.To feel or not to feel:The role of affect in humancomputer interaction[J].International Journal of Human-Computer Studies,2003,59(1):1-32.
[11]Picard R.Affective computing:challenges[J].International Journal of Human-Computer Studies,2003,59(1):55-64.
[12]Sheng Z,Lin Z Y,et al.The model of E-learning based on affective computing[C].Chengdu:IEEE,2010.
[13]S D’Mello,Lehman B,et al.Confusion can be beneficial for learning[J].Learning&Instruction,2014,29:153-170.
[14]Yadegaridehkordi E,Noor N,et al.Affective computing in education:Asystematic review and future research[DB/OL].https://www.sciencedirect.com/science/article/pii/S0360131519302027,2019-09-09.
[15]权学良,曾志刚等.基于生理信号的情感计算研究综述[J].自动化学报,2021,47(8):1769-1784.
[16]Woolf,B.P.,Arroyo,I,et al.Affective Tutors:Automatic Detection of and Response to Student Emotion[C].Berlin:Springer,2010.207-227.
[17]Feng T,Gao P,et al.Recognizing and regulating e-learners’emotions based on interactive Chinese texts in e-learning systems[J].Knowledge-Based Systems,2014,55:148-164.
[18]Fatahi,S.An experimental study on an adaptive e-learning environment based on learner’s personality and emotion[J].Educ Inf Technol,2019,(24):2225-2241.
[19]田元,周晓蕾等.学习情感分析方法研究综述[J].中国教育信息化,2021,505(22):1-6.
[20]黄兆培,张峰源等.情感识别中的迁移学习问题综述[EB/OL].http://kns.cnki.net/kcms/detail/11.2406.TN.20230227.0856.002.html,2023-04-02.
[21][39]PEKRUN R,GOETZ T,et al.Academic Emotions in Students’Self-Regulated Learning and Achievement:A Program of Qualitative and Quantitative Research[J].Educational Psychologist,2002,37(2):91-105.
[22][26]赵宏,傅兆阳等.基于特征融合的中文文本情感分析方法[J].兰州理工大学学报,2022,48(3):94-102.
[23][25]李艳,张慕华.高校学生慕课和翻转课堂体验实证研究--基于231条在线学习日志分析[J].现代远程教育研究,2015,137(5):73-84+93.
[24]邹菊梅,胡梦荻等.线上、线下及混合学习情感体验的特征分析与比较[J].现代教育技术,2022,32(4):50-60.
[27]赵京胜,宋梦雪等.自然语言处理中的文本表示研究[J].软件学报,2022,33(1):102-128.
[28]戴敏,朱珠等.面向中文文本的情感信息抽取语料库构建[J].中文信息学报,2015,29(4):67-73.
[29]刘娟,谭均翘等.基于MOOC平台数学类课程情感词典的文本分析研究[J].科教导刊,2021,451(19):78-80.
[30]Salazar,C.,Montoya-Múnera,E.,et al.Sentiment analysis in learning resources[EB/OL].https://doi.org/10.1007/s40692-022-00237-9,2022-09-05.
[31]穆肃,崔萌等.全景透视多模态学习分析的数据整合方法[J].现代远程教育研究,2021,33(1):26-37+48.
[32]马志强,苏珊.学习分析视域下的学习者模型研究脉络与进展[J].现代远距离教育,2016,166(4):44-50.
[33]李同同,谭多宁等.在线学习情感体验的维度、特征及其作用机制[J].成人教育,2022,42(10):63-70.
[34]刘智,杨重阳等.SPOC论坛互动中学习者情绪特征及其与学习效果的关系研究[J].中国电化教育,2018,(4):102-110.
[35]单迎杰,傅钢善等.基于反思文本的慕课学习情感体验特征分析[J].电化教育研究,2021,42(4):53-60+75.
[36]朱孝平,邹菊梅等.实训活动体验的情态分析方法[J].职业技术教育,2014,35(13):31-35.
[37]马宁,张燕玲等.面向在线异步交互文本的情感-认知自动化分析模型研究--以大规模教师在线培训为例[J].现代教育技术,2022,32(5):83-92.
[38]张娜,乔德聪.基于深度学习的在线学习评论情感分析研究[J].河南城建学院学报,2020,29(4):63-71+92.
[40]Hurley J M,Carter C K,et al.Examining the predictive relationship between personality and emotion traits and students’agent-directed emotions:towards emotionally-adaptive agent-based learning environments[J].User Modeling and User-Adapted Interaction,2016,26(2-3):177-219.
基本信息:
中图分类号:G434;TP391.1
引用信息:
[1]许桂芳,穆肃.个性化学习资源推荐中文本情感识别的作用及关键技术[J].中国电化教育,2023,No.436(05):105-112.
基金信息:
国家自然科学基金2022年度重点项目“课堂流媒体跨模态知识元协同解析与评估方法”(项目编号:62237001)研究成果
2023-05-09
2023-05-09