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Zoran Sevarac; Jelena Jovanovic; Vladan Devedzic; Bojan Tomic – Interactive Learning Environments, 2023
The paper proposes EXPLODE, a new model of exploratory learning environment for teaching and learning neural networks. The EXPLODE model is about pedagogically instrumenting a software development environment to transform it into an exploratory learning environment for neural networks. Such an environment is particularly aimed for students who are…
Descriptors: Models, Discovery Learning, Artificial Intelligence, Computer Simulation
Cocea, Mihaela; Magoulas, George D. – IEEE Transactions on Learning Technologies, 2017
Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behavior a…
Descriptors: Generalization, Mathematics Instruction, Computer Simulation, Discovery Learning
Peer reviewedvan Joolingen, Wouter R.; de Jong, Ton – Computers and Education, 1992
Discussion of computer simulations as a form of computer-assisted learning (CAL) focuses on a framework for domain representation for an Intelligent Simulation Learning Environment (ISLE). Topics discussed include knowledge related to computer simulations; formalization of domain knowledge; and the conceptual domain model. (19 references) (LRW)
Descriptors: Computer Assisted Instruction, Computer Simulation, Discovery Learning, Educational Environment
Ting, Choo-Yee; Phon-Amnuaisuk, Somnuk; Chong, Yen-Kuan – Educational Technology & Society, 2008
This article aims at discussing how Dynamic Decision Network (DDN) can be employed to tackle the challenges in modeling temporally variable scientific inquiry skills and provision of adaptive pedagogical interventions in INQPRO, a scientific inquiry exploratory learning environment for learning O'level Physics. We begin with an overview of INQPRO…
Descriptors: Discovery Learning, Educational Environment, Science Instruction, Inquiry
Kurland, D. Midian; Pea, Roy D. – 1983
A study is reported in which 7 children (2 girls and 5 boys, 11 to 12 years of age) with a year of LOGO Programming experience were asked to think aloud about how a LOGO procedure would work, and then to predict by hand-simulation of the programs, what the graphics turtle "pen" would draw when the program was executed. While all children…
Descriptors: Computer Assisted Instruction, Computer Simulation, Discovery Learning, Educational Research
Peer reviewedVan Joolingen, Wouter – Journal of Artificial Intelligence in Education, 1994
Describes QMaPS (Qualitative Matching and Prediction system for Simulations), a qualitative reasoning system designed to function as a module in exploratory simulation learning environments. Highlights include a hierarchical organization of variables; multilevel relation typology; modeling of physical and conceptual domain structures; an…
Descriptors: Computer Assisted Instruction, Computer Simulation, Correlation, Discovery Learning
Allen, Bradford D. – Teaching Mathematics and Its Applications: An International Journal of the IMA, 2004
The analysis and simulation of spiral growth in plants integrates algebra and trigonometry in a botanical setting. When the ideas presented here are used in a mathematics classroom/computer lab, students can better understand how basic assumptions about plant growth lead to the golden ratio and how the use of circular functions leads to accurate…
Descriptors: Plants (Botany), Computer Software, Models, Algebra
Peer reviewedBliss, Joan; Ogborn, Jon – Journal of Computer Assisted Learning, 1989
Discusses the nature and function of mental models, explains tools for exploratory and expressive learning, and describes a research program to be conducted in the United Kingdom for 10- to 16-year-olds that is designed to explore characteristics of students' mental models. Highlights include knowledge domains; software, including simulations; and…
Descriptors: Computer Assisted Instruction, Computer Simulation, Courseware, Discovery Learning
Swaak, Janine; And Others – 1996
In this study, learners worked with a simulation of harmonic oscillation. Two supportive measures were introduced: model progression and assignments. In model progression, the model underlying the simulation is not offered in its full complexity from the start, but variables are gradually introduced. Assignments are small exercises that help the…
Descriptors: Achievement Gains, Assignments, College Students, Computer Simulation
Peer reviewedBeishuizen, J. J. – Journal of Computer Assisted Learning, 1992
Discussion of teaching complex knowledge domains through exploration highlights two experiments that investigated the educational value of a Dutch computer simulation program which models the relationship between erosion and agriculture in a developing country as part of the secondary school geography curriculum. Learning by doing versus learning…
Descriptors: Agriculture, Analysis of Variance, Comparative Analysis, Computer Assisted Instruction
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers

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