Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

88
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
88
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

125
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
125
Biot-Savart Law: Problem-Solving00:59

Biot-Savart Law: Problem-Solving

2.8K
The magnitude and direction of a magnetic field created by a steady current can be calculated using the Biot-Savart law.
Consider a mobile phone battery bank as a source of steady current, which flows through the wire connected between the two. What is the magnitude of the magnetic field created by this current at a field point P?
To estimate the magnitude of the total magnetic field, we first consider a small current element of length dl, at a distance r from the field point. Now the following...
2.8K
Cognitive Learning01:21

Cognitive Learning

459
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
459
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

684
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
684
Principle of Virtual Work: Problem Solving01:13

Principle of Virtual Work: Problem Solving

1.2K
The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
To apply the principle of virtual work,...
1.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Shortening the MacArthur-Bates Communicative Developmental Inventory Using Machine Learning Based Computerized Adaptive Testing (ML-CAT).

IEEE journal of biomedical and health informatics·2026
Same author

Remote fall prevention training for community-dwelling older adults: comparison with face-to-face and effect of delivery sequence-A randomized controlled trial.

Geriatric nursing (New York, N.Y.)·2026
Same author

Wine economy in Byzantine Shivta (Negev, Israel): Exploring the role of runoff agriculture and droughts through Agent-Based Modeling.

PloS one·2025
Same author

Feasibility and effectiveness of physical exercise for older adults delivered remotely via videoconferencing-systematic review and meta analysis.

Age and ageing·2025
Same author

Remote versus face-to-face fall risk assessment in home dwelling older adults: a reliability study.

Physiotherapy theory and practice·2024
Same author

Disorder-specific versus transdiagnostic cognitive mechanisms in anxiety and depression: Machine-learning-based prediction of symptom severity.

Journal of affective disorders·2024
Same journal

Seductive details hamper learning even when they do not disrupt.

Instructional science·2023
Same journal

Living the DReaM: The interrelations between statistical, scientific and nature of science uncertainty articulations through citizen science.

Instructional science·2023
Same journal

Fostering engineering and science students' and teachers' systems thinking and conceptual modeling skills.

Instructional science·2023
Same journal

Comparing instructional strategies to support student teachers' learning to prepare an open-minded citizenship education lesson.

Instructional science·2023
Same journal

Fostering students' motivation towards learning research skills: the role of autonomy, competence and relatedness support.

Instructional science·2023
Same journal

Strategies for facilitating processing of transient information in instructional videos by using learner control mechanisms.

Instructional science·2022
See all related articles

Related Experiment Video

Updated: Jul 30, 2025

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
09:49

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Published on: November 18, 2015

12.3K

Promoting learning transfer in science through a complexity approach and computational modeling.

Janan Saba1, Hagit Hel-Or2, Sharona T Levy1

  • 1Faculty of Education, University of Haifa, 199 Aba Khoushy AveMount Carmel, 3498838 Haifa, Israel.

Instructional Science
|May 16, 2023
PubMed
Summary
This summary is machine-generated.

Middle schoolers using computational thinking (CT) and complex systems modeling improved science knowledge and learning transfer. Visual scaffolds in modeling platforms enhance understanding and promote far transfer of skills across domains.

Keywords:
Complex systemsComputational thinkingModellingScience learningTechnologyTransfer of learning

More Related Videos

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module
10:39

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module

Published on: June 18, 2015

13.2K
Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

10.0K

Related Experiment Videos

Last Updated: Jul 30, 2025

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
09:49

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Published on: November 18, 2015

12.3K
Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module
10:39

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module

Published on: June 18, 2015

13.2K
Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

10.0K

Area of Science:

  • Science Education
  • Computational Thinking
  • Systems Understanding

Background:

  • The relationship between computer-based model construction and knowledge transfer remains underexplored.
  • Middle school students' learning of complex systems and computational thinking (CT) is crucial for science education.
  • Existing research has not fully investigated the impact of visual epistemic structures on learning transfer.

Purpose of the Study:

  • To investigate the impact of computational modeling using a complexity-based visual epistemic structure on middle school students' science conceptual knowledge, systems understanding, and CT.
  • To explore the transferability of this complexity-based structure across different scientific domains.
  • To determine the independent contributions of CT, complex thinking, and science conceptual understanding to learning transfer.

Main Methods:

  • A quasi-experimental, pretest-intervention-posttest-control comparison-group design was employed.
  • Seventh-grade students (n=50) were divided into an experimental group (modeling with Much.Matter.in.Motion platform) and a comparison group.
  • The Much.Matter.in.Motion platform utilized a complexity-based visual epistemic structure to guide students' modeling of systemic phenomena.

Main Results:

  • Students who constructed computational models showed significant improvements in science conceptual knowledge, systems understanding, and CT.
  • A medium effect size was observed for far transfer of learning, with students explaining phenomena using micro-level entity properties and interactions.
  • Learning CT and complex thinking independently contributed to learning transfer, while science conceptual understanding influenced transfer via micro-level behaviors.

Conclusions:

  • Computational model construction, guided by visual epistemic scaffolds, significantly enhances science learning and transfer in middle school students.
  • The complexity-based structure of the Much.Matter.in.Motion platform effectively promotes both near and far learning transfer.
  • A method for promoting far transfer involves using visual epistemic scaffolds that represent general thinking processes within problem-solving activities.