What Can Be Learned from Computer Modeling? Comparing Expository and Modeling Approaches to Teaching Dynamic Systems Behavior

被引:25
|
作者
van Borkulo, Sylvia P. [1 ,2 ]
van Joolingen, Wouter R. [1 ]
Savelsbergh, Elwin R. [2 ]
de Jong, Ton [1 ]
机构
[1] Univ Twente, Dept Instruct Technol, Fac Behav Sci, NL-7500 AE Enschede, Netherlands
[2] Univ Utrecht, Freudenthal Inst Sci & Math Educ, Utrecht, Netherlands
关键词
Assessment; Computer modeling; Dynamic systems; Instructional technology; Simulation-based learning environments; DISCOVERY; INSTRUCTION; SIMULATION; STUDENTS; THINKING; CONTEXT;
D O I
10.1007/s10956-011-9314-3
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Computer modeling has been widely promoted as a means to attain higher order learning outcomes. Substantiating these benefits, however, has been problematic due to a lack of proper assessment tools. In this study, we compared computer modeling with expository instruction, using a tailored assessment designed to reveal the benefits of either mode of instruction. The assessment addresses proficiency in declarative knowledge, application, construction, and evaluation. The subscales differentiate between simple and complex structure. The learning task concerns the dynamics of global warming. We found that, for complex tasks, the modeling group outperformed the expository group on declarative knowledge and on evaluating complex models and data. No differences were found with regard to the application of knowledge or the creation of models. These results confirmed that modeling and direct instruction lead to qualitatively different learning outcomes, and that these two modes of instruction cannot be compared on a single "ffectiveness measure".
引用
收藏
页码:267 / 275
页数:9
相关论文
共 50 条
  • [1] What Can Be Learned from Computer Modeling? Comparing Expository and Modeling Approaches to Teaching Dynamic Systems Behavior
    Sylvia P. van Borkulo
    Wouter R. van Joolingen
    Elwin R. Savelsbergh
    Ton de Jong
    [J]. Journal of Science Education and Technology, 2012, 21 : 267 - 275
  • [2] COMPUTER MODELING OF PHYSIOLOGICAL SYSTEMS IN TEACHING
    KATZEFF, IE
    BECK, F
    WILLENBERG, K
    CILLIERS, GD
    [J]. SOUTH AFRICAN JOURNAL OF SCIENCE, 1982, 78 (02) : 83 - 83
  • [3] Zeolites at the Molecular Level: What Can Be Learned from Molecular Modeling
    Broclawik, Ewa
    Kozyra, Pawel
    Mitoraj, Mariusz
    Radon, Mariusz
    Rejmak, Pawel
    [J]. MOLECULES, 2021, 26 (06):
  • [4] Effect of basic parameters of computer modeling on the behavior of dynamic systems with strange attractors
    Afanasev, VV
    Mikhailov, SV
    Polskii, YE
    Toropov, AY
    [J]. PISMA V ZHURNAL TEKHNICHESKOI FIZIKI, 1995, 21 (23): : 10 - 14
  • [5] Modeling of Dynamic Behavior of AGV systems
    Veiga, Joao
    Sousa, Joao
    Machado, Jose
    Mendonca, Joao
    Machado, Toni
    Silva, Pedro
    [J]. 2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019), 2019, : 1307 - 1312
  • [6] Approaches to Cognitive Modeling in Dynamic Systems Control
    Holt, Daniel V.
    Osman, Magda
    [J]. FRONTIERS IN PSYCHOLOGY, 2017, 8
  • [7] Spectral Albedo in Bifacial Photovoltaic Modeling: What can be Learned from Onsite Measurements?
    Riedel-Lyngskaer, Nicholas
    Ribaconka, Martynas
    Po, Mario
    Thorsteinsson, Sune
    Thorseth, Anders
    Dam-Hansen, Carsten
    Jakobsen, Michael L.
    [J]. 2021 IEEE 48TH PHOTOVOLTAIC SPECIALISTS CONFERENCE (PVSC), 2021, : 942 - 949
  • [8] MODELING CENTRAL BANK BEHAVIOR - WHAT HAVE WE LEARNED
    LOMBRA, RE
    KAUFMAN, HM
    [J]. JOURNAL OF POLICY MODELING, 1992, 14 (02) : 227 - 248
  • [9] Impact of computer modeling on learning and teaching systems thinking
    Nguyen, Ha
    Santagata, Rossella
    [J]. JOURNAL OF RESEARCH IN SCIENCE TEACHING, 2021, 58 (05) : 661 - 688
  • [10] Comparing driver information systems in a dynamic modeling framework
    Luk, JYK
    Yang, C
    [J]. JOURNAL OF TRANSPORTATION ENGINEERING-ASCE, 2003, 129 (01): : 42 - 50