Trends and Foundations of Creativity Research in Education: A Method Based on Text Mining

被引:4
作者
Mi, Shuaishuai [1 ]
Bi, Hualin [2 ]
Lu, Shanshan [1 ]
机构
[1] Shandong Normal Univ, Jinan 250014, Shandong, Peoples R China
[2] Qufu Normal Univ, Qufu, Shandong, Peoples R China
关键词
Trends; Foundations; Text mining; Education; Creativity; PSYCHOLOGY;
D O I
10.1080/10400419.2020.1821554
中图分类号
G44 [教育心理学];
学科分类号
0402 ; 040202 ;
摘要
This study aimed to identify trends and foundations of creativity research in education using the Structural Topic Model (STM). First, English-language journal articles about creativity research in education included in the Social Science Citation Index and Science Citation Index Expanded databases were selected. Then, considering semantic cohesiveness and exclusivity of words to topics, the articles were divided into twelve topics using STM. Topic 2, which attracted increasing research interest, was selected using a method similar to standard regression analysis. The changing focus of Topic 2 was identified through an analysis of its research contents. Finally, the foundations of creativity research in education across three periods (1990-1999, 2000-2009, and 2010-2019) were obtained through a review of their 10 most highly cited papers. The conclusions are that a) there are twelve topics of creativity research in education; b) research about the creative process of engineering design in STEM education is likely to attract further interest in the future; and c) highly cited papers are mainly concerned about the mechanisms underlying idea generation and personality and social factors. Studies of the mechanisms underlying idea generation have been the foundation of creativity research throughout all time periods studied.
引用
收藏
页码:215 / 227
页数:13
相关论文
共 50 条
[41]   Sentiment Analysis of China's Education Policy Online Opinion Based on Text Mining [J].
Zhang, Danchen ;
Zhang, Jie ;
Zhang, Yuqi ;
Wu, Yuxin .
2021 9TH INTERNATIONAL CONFERENCE ON INFORMATION AND EDUCATION TECHNOLOGY (ICIET 2021), 2021, :73-77
[42]   A text mining-based approach for the evaluation of patenting trends on nanomaterials [J].
Douglas Henrique Milanez ;
Leandro Innocentini Lopes de Faria ;
Daniel Rodrigo Leiva .
Journal of Nanoparticle Research, 2021, 23
[43]   Sustainability trends in the process industries: A text mining-based analysis [J].
Liew, Wan Te ;
Adhitya, Arief ;
Srinivasan, Rajagopalan .
COMPUTERS IN INDUSTRY, 2014, 65 (03) :393-400
[44]   A text mining-based approach for the evaluation of patenting trends on nanomaterials [J].
Milanez, Douglas Henrique ;
Lopes de Faria, Leandro Innocentini ;
Leiva, Daniel Rodrigo .
JOURNAL OF NANOPARTICLE RESEARCH, 2021, 23 (09)
[45]   Text Mining of Twitter Data for Mapping the Digital Humanities Research Trends: A Case Study [J].
Sawale, Arti ;
Walia, Paramjeet Kaur .
DESIDOC JOURNAL OF LIBRARY & INFORMATION TECHNOLOGY, 2023, 43 (04) :258-265
[46]   TRENDS IN OVERTOURISM RESEARCH FROM 2018 TO 2021: TEXT MINING AND SEMANTIC NETWORK ANALYSIS [J].
Tang, Ruohan ;
Lee, Won Seok ;
Moon, Joonho ;
Shim, Ji Min .
TOURISM REVIEW INTERNATIONAL, 2023, 27 (3-4) :187-200
[47]   Research trends in text mining: Semantic network and main path analysis of selected journals [J].
Jung, Hoon ;
Lee, Bong Gyou .
EXPERT SYSTEMS WITH APPLICATIONS, 2020, 162
[48]   Editorial: Text mining-based mental health research [J].
Amjad, Tehmina ;
Timakum, Tatsawan ;
Xie, Qing ;
Song, Min .
FRONTIERS IN RESEARCH METRICS AND ANALYTICS, 2024, 9
[49]   Research on the Frame of Text Mining based on Grid in the Network Environment [J].
Li Cheng-mao ;
Huang Xiao-yu ;
Chenping .
2009 IEEE 10TH INTERNATIONAL CONFERENCE ON COMPUTER-AIDED INDUSTRIAL DESIGN & CONCEPTUAL DESIGN, VOLS 1-3: E-BUSINESS, CREATIVE DESIGN, MANUFACTURING - CAID&CD'2009, 2009, :2374-2377
[50]   Research on fault diagnosis of patient monitor based on text mining [J].
He X. ;
Zhang H. ;
Huang J. ;
Zhao D. ;
Li Y. ;
Nie R. ;
Liu X. .
Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering, 2024, 41 (01) :168-176