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
  • [41] Comparing containerization-based approaches for reproducible computational modeling of environmental systems
    Choi, Young-Don
    Roy, Binata
    Nguyen, Jared
    Ahmad, Raza
    Maghami, Iman
    Nassar, Ayman
    Li, Zhiyu
    Castronova, Anthony M.
    Malik, Tanu
    Wang, Shaowen
    Goodall, Jonathan L.
    [J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2023, 167
  • [42] Discrete Dynamic Modeling of Learner Behavior Analysis in Physical Education Teaching
    Shi, Jia
    Sun, Jun
    Zheng, Zhonghua
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [43] Research on Discrete Dynamic Modeling of Learner Behavior Analysis in English Teaching
    Fu, Junru
    Cao, Lingmei
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [44] Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
    Raue, Andreas
    Schilling, Marcel
    Bachmann, Julie
    Matteson, Andrew
    Schelke, Max
    Kaschek, Daniel
    Hug, Sabine
    Kreutz, Clemens
    Harms, Brian D.
    Theis, Fabian J.
    Klingmueller, Ursula
    Timmer, Jens
    [J]. PLOS ONE, 2013, 8 (09):
  • [45] Computer modeling of natural silicate melts: What can we learn from ab initio simulations
    Vuilleumier, Rodolphe
    Sator, Nicolas
    Guillot, Bertrand
    [J]. GEOCHIMICA ET COSMOCHIMICA ACTA, 2009, 73 (20) : 6313 - 6339
  • [46] User participation: what can be learned from the information systems domain?
    Engvall, Tove
    [J]. RECORDS MANAGEMENT JOURNAL, 2019, 29 (03) : 320 - 332
  • [47] Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid
    Ahmadi, Mohammad Hossein
    Mohseni-Gharyehsafa, Behnam
    Ghazvini, Mahyar
    Goodarzi, Marjan
    Jilte, Ravindra D.
    Kumar, Ravinder
    [J]. JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY, 2020, 139 (04) : 2585 - 2599
  • [48] Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid
    Mohammad Hossein Ahmadi
    Behnam Mohseni-Gharyehsafa
    Mahyar Ghazvini
    Marjan Goodarzi
    Ravindra D. Jilte
    Ravinder Kumar
    [J]. Journal of Thermal Analysis and Calorimetry, 2020, 139 : 2585 - 2599
  • [49] Comparing the Use of Two Different Approaches to Assess Teachers' Knowledge of Models and Modeling in Science Teaching
    Carroll, Grace
    Park, Soonhye
    [J]. EDUCATION SCIENCES, 2023, 13 (04):
  • [50] Modeling and stability analysis of the dynamic behavior in load sharing systems
    Levi, P
    Schanz, M
    Avrutin, V
    Lammert, R
    [J]. SENSOR BASED INTELLIGENT ROBOTS, 1999, 1724 : 255 - 271