The Emergence of Learning-Teaching Trajectories in Education: a Complex Dynamic Systems Approach

被引:0
|
作者
Steenbeek, Henderien [1 ]
van Geert, Paul [1 ]
机构
[1] Univ Groningen, NL-9712 TS Groningen, Netherlands
关键词
education; learning; complex adaptive system; computational modeling; SELF-REGULATION; INTRAINDIVIDUAL VARIABILITY; ACHIEVEMENT GOALS; HELP-SEEKING; MODEL; MOTIVATION; TEACHERS; METACOGNITION; PERCEPTIONS; CLASSROOM;
D O I
暂无
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
In this article we shall focus on learning-teaching trajectories - "successful" as well as "unsuccessful" ones - as emergent and dynamic phenomena resulting from the interactions in the entire educational context, in particular the interaction between students and teachers viewed as processes of intertwining self-, other- and co-regulation. The article provides a review of the educational research literature on action regulation in learning and teaching, and interprets this literature in light of the theory of complex dynamic systems. Based on this reinterpretation of the literature, two dynamic models are proposed, one focusing on the short-term dynamics of learning-teaching interactions as they take place in classrooms, the other focusing on the long-term dynamics of interactions in a network of variables encompassing concerns, evaluations, actions and action effects (such as learning) students and teachers. The aim of presenting these models is to demonstrate, first, the possibility of transforming existing educational theory into dynamic models and, second, to provide some suggestions as to how such models can be used to further educational theory and practice.
引用
收藏
页码:233 / 267
页数:35
相关论文
共 50 条
  • [41] Innovative Approach to Teaching Distributed Systems in Education 4.0
    Purkovic, Safet
    Fetahovic, Irfan
    Mekic, Edis
    Katipoglu, Gokmen
    Utku, Semih
    International Journal of Engineering Education, 2024, 40 (05) : 1229 - 1244
  • [42] A deep learning approach to predicting vehicle trajectories in complex road networks
    Sundari, K.
    Thilak, A. Senthil
    INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS, 2024,
  • [43] Dynamic analysis of complex systems by Volterra approach
    Carassale, L.
    Kareem, A.
    COMPUTATIONAL STOCHASTIC MECHANICS, 2003, : 107 - 117
  • [44] A dynamic systems approach to the feeling toned complex
    Krieger, Nancy M.
    JOURNAL OF ANALYTICAL PSYCHOLOGY, 2019, 64 (05) : 738 - 760
  • [45] SYNERGETICS - AN APPROACH TO COMPLEX DYNAMIC-SYSTEMS
    HAKEN, H
    ADVANCES IN APPLIED PROBABILITY, 1982, 14 (02) : 197 - 197
  • [46] A Machine Learning Based Biased-Sampling Approach for Planning Safe Trajectories in Complex, Dynamic Traffic-Scenarios
    Chaulwar, Amit
    Botsc, Michael
    Utschick, Wolfgang
    2017 28TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2017), 2017, : 297 - 303
  • [47] Teaching Students How to Calculate the Area of Complex Figures With Circles by Using Learning Trajectories
    Chen, Chia-Huang
    Wu, Bi-Tsz
    JOURNAL OF RESEARCH IN EDUCATION SCIENCES, 2016, 61 (01): : 1 - 41
  • [48] Teaching Embedded Systems with Active Learning: The SMEAGOL Approach
    Meshkova, Elena
    Riihijaervi, Janne
    Maehoenen, Petri
    FIE: 2008 IEEE FRONTIERS IN EDUCATION CONFERENCE, VOLS 1-3, 2008, : 620 - 625
  • [49] Taoism, teaching and learning: A nature-based approach to education
    Cheng, Lin
    EDUCATIONAL PHILOSOPHY AND THEORY, 2024, 56 (01) : 91 - 94
  • [50] Teaching and learning conceptions in Engineering Education: an innovative approach on Mathematics
    Borges, Mario Neto
    Goncalves, Maria Do Carmo Narciso Silva
    Cunha, Flavio Macedo
    European Journal of Engineering Education, 2003, 28 (04) : 523 - 534