Related Experiment Video
Updated: Oct 8, 2025
08:35
Interactive and Visualized Online Experimentation System for Engineering Education and Research
Published on: November 24, 2021
2.7K
Immersive Learning Design for Technology Education: A Soft Systems Methodology.
C H Wu1, Y M Tang2,3, Y P Tsang2
1Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong SAR, China.
Frontiers in Psychology
|January 3, 2022
Summary
Soft Systems Methodology (SSM) effectively designs technology education courses. Immersive technologies, like mixed reality for radio frequency identification (RFID), enhance student learning performance and skill acquisition in higher education.
Area of Science:
- Technology Education
- Higher Education Pedagogy
- Immersive Learning Environments
Background:
- Technology Education (TE) is crucial for developing applied skills in STEM.
- Immersive technologies are increasingly researched for enhancing TE effectiveness in higher education.
- Radio Frequency Identification (RFID) is a key technology within TE curricula.
Purpose of the Study:
- To evaluate the learning effectiveness of RFID education assisted by mixed reality technologies.
- To apply Soft Systems Methodology (SSM) for structuring stakeholder perceptions and improving TE course design.
- To assess the impact of immersive technologies on student learning performance in higher education TE.
Main Methods:
- Utilized Soft Systems Methodology (SSM) to structure stakeholder perceptions of immersive learning and RFID education.
- Developed a mixed reality-assisted learning environment for a higher education RFID course.
- Employed SSM framework to create a 'rich picture' for teaching activity control, monitoring, and evaluation.
Main Results:
- SSM proved effective in designing technology education courses focused on hands-on technologies.
- Immersive technologies significantly improved learning performance in acquiring fundamental knowledge and application know-how.
- The developed TE course design met the needs of students, teachers, and industry trends.
Conclusions:
- Soft Systems Methodology is a valuable approach for designing technology education courses, especially those involving complex, hands-on technologies.
- Mixed reality-enhanced learning environments demonstrably improve student outcomes in technology education.
- Integrating immersive technologies and robust pedagogical frameworks like SSM leads to more effective and relevant higher education technology programs.
Related Concept Videos
01:22Purposive Learning
218
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
218
01:13Principle of Virtual Work: Problem Solving
1.3K
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,...
To apply the principle of virtual work,...
1.3K
01:21Cognitive Learning
695
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...
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...
695
01:16Response Surface Methodology
315
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
315
01:18Design Example: Designing Water Slide
338
When designing a water slide, controlling the speed of water flow is crucial for rider safety while maintaining an exciting experience. As water flows down the slide, gravity causes it to accelerate, with its speed at the bottom depending on the height from which it starts. The higher the slide, the more potential energy the water has at the top, which is converted into kinetic energy as it descends, increasing its speed.
Bernoulli's principle determines the water's velocity along the...
Bernoulli's principle determines the water's velocity along the...
338
01:30Information Processing Approach
208
The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
208