Evidence map›Paper›PMID 34975635›Full record

ArticleFrontiers in psychology2021

Immersive Learning Design for Technology Education: A Soft Systems Methodology.

C H Wu, Y M Tang, Y P Tsang, K Y Chau

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

C H WuDepartment of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong SAR, China.
Y M TangDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
Y P TsangDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
K Y ChauFaculty of Business, City University of Macau, Macao, Macau SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Science, technology, engineering and mathematics (STEM) education is a globalized trend of equipping students to facilitate technological and scientific developments. Among STEM education, technology education (TE) plays a significant role in teaching applied knowledge and skills to create and add value to systems and products. In higher education, the learning effectiveness of the TE assisted by the immersive technologies is an active research area to enhance the teaching quality and learning performance. In this study, a taught subject of radio frequency identification (RFID) assisted by using mixed reality technologies in a higher education institution was examined, while the soft systems methodology (SSM) was incorporated to evaluate the changes in learning performance. Under the framework of SSM, stakeholders' perceptions toward immersive learning and RFID education are structured. Thus, a rich picture for teaching activities is established for subject control, monitoring, and evaluation. Subsequently, the design of TE does not only satisfy the students' needs but also requirements from teachers, industries, and market trends. Finally, it is found that SSM is an effective approach in designing courses regarding hands-on technologies, and the use of immersive technologies improves the learning performance for acquiring fundamental knowledge and application know-how.

Indexed as

immersive learninglearning performanceradio frequency identificationsoft systems methodologytechnology education

Identifiers

PMID34975635
PMCPMC8719480

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.