Abstract
The rapid growth of online education provides massive behavioral data for classroom behavior research. To analyse the empirical research of classroom behavior, this article retrieved 124 empirical researches of classroom behavior from Web of Science, EBSCO, and CNKI. After statistical analysis, the results were as follows: (1) The empirical research on classroom behavior has increased rapidly. (2) The topics focused on the research of classroom behavior influencing factors and classroom behavior characteristics. (3) The research mostly used manual acquisition for data collection and were mainly quantitative researches. (4) Most of the researches centered on primary and secondary school subjects with incomplete overviews of school divisions and disciplines. (5) Empirical research of classroom behavior provided reference for mining the law of classroom behavior and improving classroom teaching. Therefore, the article called for a more sophisticated approach to empirical research which combines online education and complex classroom behaviors.
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References
Ding B (2013) Summary of classroom teaching behavior research. The Guide of Science & Education 176(22):65–85. https://doi.org/10.16400/j.cnki.kjdkz.2013.11.113
Flanders N (1970) Analyzing teacher behavior. Addison-Wesley, Oxford, England
Amidon EJ, Hunter E (1968) Abstracted from Verbal Interaction Category System (VICS). Classr Interact Newsl 3(2):1–5. http://www.jstor.org/stable/23887540
Gu X, Wang W (2004) New exploration of classroom analysis techniques to support teacher professional development. China Educational Technology 07:18–21
Fang H, Gao C, Chen J (2012) Improved Flanders interactive analysis system and its application. China Educational Technology 10:109–113
Mu S, Zuo P (2015) Research on the analysis method of classroom teaching behavior under the information teaching environment. E-Education Res 36(09):62–69. https://doi.org/10.13811/j.cnki.eer.2015.09.011
Liu X, Tian D, Wang Y (2018) What kind of empirical research we need: types and application Models——Taking 195 empirical Research Papers of Modern Distance Education Research(2010–2017) as an Example. Mod Distance Educ Res 4:49–58
Xie Y, Li K (2017) Basic Research Methods in Educational Technology. Higher Education Press
Dinsmore DL, Alexander PA (2012) A critical discussion of Deep and Surface Processing: what it means, how it is measured, the role of Context, and Model Specification. Educational Psychol Rev 24(4):499–567. https://doi.org/10.1007/s10648-012-9198-7
Gao G, Chen S (2020) A case study of teacher-student Interaction in Remote Online Russian Audiovisual Class based on iFIAS. Russian in China 39(04):76–85
Li H, Wang L, Bian P, Ji H, Li Q (2022) J Distance Educ 40(03):67–75. https://doi.org/10.15881/j.cnki.cn33-1304/g4.2022.03.004. A General Analysis Framework of Classroom Interaction Double Coding for Big data of Teaching Behavior and Its Variant Application
Yin C, Uosaki N, Chu H-C, Hwang G-J, Hwang J-J, Hatono I, Kumamoto E, Tabata Y (2017) Learning Behavioral Pattern Analysis based on Students’ Logs in Reading Digital Books.
Wei Y, Qin D, Hu J (2019) The Recognition of Students’ Classroom Behaviors based on deep learning. Mod Educational Technol 29(07):87–91
Xie W, Tao Y, Gao J (2022) YOWO Based Real-time Recognition of Classroom Learning Behaviors. Mod Educational Technol 32(06):107–114
Wang Z, Shen C, Zhao C, Liu X, Chen J (2022) Recognition of classroom learning behaviors based on the fusion of human pose estimation and object detection. J East China Normal University(Natural Science) 02:55–66
Zheng Z, Liang G, Luo H, Yin H (2022) Attention assessment based on multi-view classroom behavior recognition. https://doi.org/10.1049/cvi2.12146. IET Computer Vision, n/a-n/a
Zhou J, Ran F, Li G, Peng J, Li K, Wang Z (2022) Classroom Learning Status Assessment Based on Deep Learning. Mathematical Problems in Engineering, 2022, 7049458. https://doi.org/10.1155/2022/7049458
Chen H, Guan J (2022) Teacher–Student Behavior Recognition in Classroom Teaching based on Improved YOLO-v4 and internet of things Technology[J]. Electronics 11(23):3998
Cheng Y, Wang Y, Wang F (2017) Research on the quantitative analysis methods for interactive depth of Classroom Teaching and Learning Behaviors. Mod Educational Technol 27(09):26–32
Cheng Y, Liu Q, Wang Y (2017) The research on construction and application of cloud model for analysis of classroom teaching and learning behavior. J Distance Educ 35(02):36–42. https://doi.org/10.15881/j.cnki.cn33-1304/g4.2017.02.005
Zhang H, Cui Y, Yu L, Ji M, Wang Y (2020) Study of Classroom Event Logic Graph of Intelligent Teaching based on Method of Data Mining. J Distance Educ 38(02):80–88. https://doi.org/10.15881/j.cnki.cn33-1304/g4.2020.02.008
Wang D, Liu H, Qiu M (2020) Analysis Method and Application Verification on Teacher Behavior Data in Smart Classroom. China Educational Technology 05:120–127
Volpe R, Briesch A (2016) Dependability of two scaling approaches to Direct Behavior Rating Multi-Item Scales assessing Disruptive Classroom Behavior. School Psychol Rev 45:39–52. https://doi.org/10.17105/SPR45-1.39-52
Caldarella P, Larsen RAA, Williams L et al (2017) Monitoring academic and social skills in elementary school: a psychometric evaluation of the Classroom Performance Survey[J]. J Posit Behav Interventions 19(2):78–89
Caldarella P, Larsen RAA, Williams L et al (2022) Behavior monitoring in the Middle Grades: evaluation of the Classroom Performance Survey[J]. RMLE Online 45(6):1–15
Wei X, Wang J, Zhao X, Tian J, Ding R (2019) A Case Study of Teaching Interaction Behavior in Synchronous Interactive dedicated Classroom——Take the art Course Painting the Road of First Grade as an Example. Mod Educational Technol 29(12):41–47
Liu J, Chen N (2021) Research on the interactive Behaviors in Classroom teaching under Smart Classroom Environment——Taking 10 high-quality Junior High School Mathematics Teaching Courses as Observation Objects. Mod Educational Technol 31(09):28–36
Ajiboye S, Adebayo D, Abubakar S (2020) Teachers’ Assessment of Inattentive Classroom Behavior among Primary School students in Ilorin City, Kwara State, Nigeria. Mimbar Sekolah Dasar 7:172–183. https://doi.org/10.17509/mimbar-sd.v7i2.24101
Böheim R, Knogler M, Kosel C, Seidel T (2020) Exploring student hand-raising across two school subjects using mixed methods: an investigation of an everyday classroom behavior from a motivational perspective. Learn Instruction 65:101250. https://doi.org/10.1016/j.learninstruc.2019.101250
Zhang Q, Liu Q, Zhang W, Wu L, Zhang N (2019) Analysis of teacher’s behavior characteristics and research on strategies from the perspective of Classroom Teacher-Student Interaction——Based on the Leary Model. Mod Distance Educ 03:30–37. https://doi.org/10.13927/j.cnki.yuan.2019.0025
Shi Y, Peng C, Zhang J, Yang H (2019) Research on the teacher-student Interaction Behavior in Colleges and Universities under Smart Classroom Environment. Mod Educational Technol 29(01):45–51
Fawley KD, Stokes TF, Rainear CA et al (2020) Universal TCIT improves teacher–child interactions and management of child behavior[J]. J Behav Educ 29:635–656
Ilhan F, Ozfidan B, Yilmaz S (2019) Home visit effectiveness on students’ classroom behavior and academic achievement[J]. J Social Stud Educ Res 10(1):61–80
Waxman H, Padron Y, Keese J (2021) Learning environment and students’ classroom behavior differences between effective, average, and ineffective urban elementary schools for hispanic students. Educ Res Policy Pract 20:1–18. https://doi.org/10.1007/s10671-020-09281-7
Schulz T, Cividini-Motta C, Blair K-S, MacNaul H (2022) A comparison of high-tech and low-tech response modalities to Improve Student Classroom Behavior. J Behav Educ 31. https://doi.org/10.1007/s10864-020-09393-3
Zhao L, Zhang H (n.d.). Flipped classroom teaching behavior and effect analysis based on ITIAS. China University Teaching, 387(11), 87–95
Zhang S, Song N, Cai J (2022) Research on Problem Posing Classroom Teaching Behavior of Elementary Mathematics Teachers. J Math Educ 31(02):46–52
Lu G, Xie K, Liu Q, Zhang C, Yu S (2021) Automated annotation of Classroom Behaviours with AI Engine. Open Educ Res 27(06):97–107. https://doi.org/10.13966/j.cnki.kfjyyj.2021.06.011
Tian H (2006) Mixed methods research: a new paradigm in american education research. J Higher Educ 11:74–78
Qin J, Li Y, Jing Y, Peng Y (2022) Teacher Dev Res 6(04):87–94. https://doi.org/10.19618/j.cnki.issn2096-319x.2022.04.010. A Study of the Effective Classroom Teaching Behavior Indicators of Primary and Secondary School Teachers
Aran O, Ari I, Guvensan A, Haberdar H, Kurt Z, Turkmen I, Uyar A, Akarun L (2007) A database of non-manual signs in turkish sign Language. 2007 IEEE 15th Signal Processing and Communications Applications. 1–4. https://doi.org/10.1109/SIU.2007.4298708
Oertel C, Mora KA, Sheikhi S, Odobez J, Gustafson J (2014) Who Will Get the Grant? A Multimodal Corpus for the Analysis of Conversational Behaviours in Group Interviews. UM3I ‘14
Shahroudy A, Liu J, Ng T-T, Wang G (2016) NTU RGB+D: a large Scale dataset for 3D human activity analysis. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 1010–1019. https://doi.org/10.1109/CVPR.2016.115
Liu J, Shahroudy A, Perez M, Wang G, Duan L, Kot AC (2020) NTU RGB + D 120: a large-scale benchmark for 3D human activity understanding. IEEE Trans Pattern Anal Mach Intell 42(10):2684–2701. https://doi.org/10.1109/TPAMI.2019.2916873
Guo Q (2022) System Analysis of the Learning Behavior Recognition System for students in a Law Classroom: based on the improved SSD behavior Recognition Algorithm. Scientific Programming
Xie D, Meng F, He H, Yan Q (2022) Lie Group feature representation Method Applied to Head Behavior Recognition in Classroom Environment. Comput Eng Appl 58(06):164–169
Cheng Y, Wang Y, Wang F, Huang K, Zhang R (2017) Research on the quantitative analysis methods for interactive depth of Classroom Teaching and Learning Behaviors. Mod Educational Technol 27(09):26–32
Cheng Y, Liu Q, Wang Y, Wang F, Mao G (2017) The Research on Construction and Application of Cloud Model for Analysis of Classroom Teaching and Learning Behavior. J Distance Educ 02:05. https://doi.org/10.15881/j.cnki.cn33-1304/g4.2017.02.005
Gao Y, Lin K, Ma H (2015) Quantitative Tool to Study Modern Chemistry Classroom Teaching Behavior:3 C-FIAS. Chin J Chem Educ 37(05):18–24. https://doi.org/10.13884/j.1003-3807hxjy.2015070113
Wolcott CS, Williford AP (2015) Teacher and TA ratings of Preschoolers’ externalizing behavior: Agreement and Associations with observed Classroom Behavior. Top Early Child Special Educ 34(4):211–222. https://doi.org/10.1177/0271121414546008
Chen W, Gu X, Wong L-H (2017) To click or not to click: effectiveness of rating classroom behaviors on academic achievement with tablets. Br J Edu Technol 50. https://doi.org/10.1111/bjet.12593
Yu M, Lu B, Li X, Li W (2021) Research on children’s classroom behavior based on pressure cushion. J Intell Fuzzy Syst 40(4):7939–7949. https://doi.org/10.3233/JIFS-189616
Brokamp SK, Houtveen AA, van De Grift W (2019) The relationship among students’ reading performance, their classroom behavior, and teacher skills. J Educational Res 112:1–11
Leidig T, Casale G, Wilbert J, Hennemann T, Volpe R, Briesch A, Grosche M (2022) Individual, generalized, and moderated effects of the good behavior game on at-risk primary school students: a multilevel multiple baseline study using behavioral progress monitoring. Front Educ 7. https://doi.org/10.3389/feduc.2022.917138
Wu H (2022) Study on classroom teaching behavior in secondary vocation schools from the perspective of classroom revolution——Based on the perspective of the sinning works of the National Vocational College Teaching ability competition. Chin Vocat Tech Educ 14:63–70
Cook CR et al (2017) Evaluating the impact of increasing General Education Teachers’ ratio of positive-to-negative interactions on students’ Classroom Behavior. J Posit Behav Interventions 19(2):67–77
Wei Y, Wang J, Zhao X, Tian J, Ding R (2019) A Case Study of Teaching Interaction Behavior in Synchronous Interactive dedicated Classroom——Take the art Course Painting the Roas of First Grade as an Example. Mod Educational Technol 29(12):41–47
Li X, Zhou C, Zhang S (2022) Interaction Behavior of Teachers and students in Senior High School Chemistry high-end lesson Preparation from the perspective of lag sequence analysis. Chin J Chem Educ 43(05):84–90. https://doi.org/10.13884/j.1003-3807hxjy.2021060143
Dong J, Nie J, Qin Q (2020) (n.d.). Analysis of classroom teaching behavior of mathematics electronic schoolbag from the perspective of core literacy. Teaching & Administration, 21(27–31),
Ilhan F, Ozfidan B, Yilmaz S (2019) Home visit effectiveness on students’ Classroom Behavior and Academic Achievement. J Social Stud Educ Res 10:61–80
Moore T, Alpers A, Rhyne R, Coleman MB, Gordon J, Daniels S, Skinner C, Park Y (2018) Brief prompting to Improve Classroom Behavior: a first-pass intervention option. J Posit Behav Interventions 21:109830071877488. https://doi.org/10.1177/1098300718774881
Closs L, Mahat M, Imms W (2022) Learning environments’ influence on students’ learning experience in an australian Faculty of Business and Economics. Learn Environ Res 25(1):271–285. https://doi.org/10.1007/s10984-021-09361-2
Schulz T, Cividini-Motta C, Blair K-SC, MacNaul H (2022) A comparison of high-tech and low-tech response modalities to Improve Student Classroom Behavior. J Behav Educ 31(2):243–264
Acknowledgements
The authors gratefully acknowledge the financial support from the Natural Science Foundation of China under Grant 62207012, in part by the Key Scientific Research Projects of Department of Education of Hunan Province under Grant 22A0049, 2023 Key Supported Project of the 14th Five Year Plan for Education and Science in Hunan Province with No. ND230795, and in part by the National Social Science Foundation of China under Grant AEA200013.
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Study conception and design: Shuai Liu; data collection and visualization: Changling Peng; analysis and interpretation of results: Yishu Huang; draft manuscript preparation: Yishu Huang; supervision: Shuai Liu. All authors reviewed the results and approved the final version of the manuscript.
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Huang, Y., Peng, C. & Liu, S. Empirical Research of Classroom Behavior Based on Online Education: A Systematic Review. Mobile Netw Appl 28, 1793–1805 (2023). https://doi.org/10.1007/s11036-023-02251-2
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DOI: https://doi.org/10.1007/s11036-023-02251-2