Home About the Journal Latest Work Current Issue Archive Special Issues Editorial Board
<< Previous Next >>

2020, 2(6): 556-568

Published Date:2020-12-20 DOI: 10.1016/j.vrih.2020.08.001

Virtual 3D environment for exploring the spatial ability of students


Spatial ability is an unique type of intelligence; it can be distinguished from other forms of intelligence and plays an essential role in an individual's success in many academic fields, particular in this era of technology. Instruction-assisted 3D technology can display stereo graphics and promote students' understanding of the geometrical structure and characteristics of graphics. Spatial ability includes several aspects. Few software programs are available for training different aspects of spatial ability for senior high school students. This study aims to explore an effective method for training the spatial ability for senior high school students, and to promote the development of students' independent inquiry ability.
First, an inquiry design strategy to improve the spatial ability of students is proposed. Based on this strategy, unity3D was used to develop a 3D inquiry environment that can use leap motion to complete a gesture interaction. Finally, researchers carried out experience-based activities and issued user experience questionnaires to participants to verify the application effect of the spatial ability inquiry environment and used interviews to understand the user experience of participants exploring the leap motion device in a 3D inquiry environment.
32 learners participated in the experiment. learners have a high score for perceived usefulness and willingness to use. Compared with the perceived ease of use and perceived usefulness, the average score of the application effect is relatively low. In terms of willingness to use, most of the learners expressed their willingness to use a similar inquiry environment for spatial ability training in the future.
The spatial ability inquiry environment can help learners better understand different concepts. The users showed a strong willingness to continue using the device. The device also updates the teaching concept to a certain extent and emphasizes the dominant position of a student.


3D ; Inquiry learning ; Spatial ability ; 3D inquiry environment ; Leap motion

Cite this article

Yingqian LI, Yang YANG, Zhengwei YAO, Guangtao XU. Virtual 3D environment for exploring the spatial ability of students. Virtual Reality & Intelligent Hardware, 2020, 2(6): 556-568 DOI:10.1016/j.vrih.2020.08.001


1. Stieff M, Uttal D. How much can spatial training improve STEM achievement? Educational Psychology Review, 2015, 27(4): 607–615 DOI:10.1007/s10648-015-9304-8

2. Uttal D H, Miller D I, Newcombe N S. Exploring and enhancing spatial thinking links to achievement in science, technology, engineering, and mathematics? Current Directions in Psychological Science, 2013, 22(5): 367–373 DOI:10.1177/0963721413484756

3. Bodner G M, Guay R B. The purdue visualization of rotations test. The Chemical Educator, 1997, 2(4): 1–17 DOI:10.1007/s00897970138a

4. Eliot J. About spatial intelligence: I. Perceptual and Motor Skills, 2002, 94(2): 479–486 DOI:10.2466/pms.2002.94.2.479

5. Lohman D F. Spatial ability: a review and reanalysis of the correlational literature. Stanford Univ Calif School Of Education, 1979

6. Gaughran W. Cognitive modelling for engineers. In: 2002 American Society for Engineering Education annual conference and exposition. Montréal, Canada, American Society for Engineering Education, 2002

7. Sutton K, Allen R. Assessing and improving spatial ability for design-based disciplines utilising online systems: Australian Learning and Teaching Council, 2011

8. McGee M G. Human spatial abilities: psychometric studies and environmental, genetic, hormonal, and neurological influences. Psychological Bulletin, 1979, 86(5): 889–918

9. Sorby S A. Developing 3D spatial visualization skills. Engineering Design Graphics Journal, 1999, 63(2): 21–32

10. Juan W, Yonghe W, Ye D, Jun J. The innovative perspective of education application of 3D technology. 2015

11. [USA]National Research Council. National standards for Science Education in the United States. Beijing, Science and Technology Literature Press, 1999, 30

12. Xu G T. Research on the function space and effect of technology to enable scientific inquiry learning. 2016

13. Xu F, Li J. Research on application of web 3D technology in teaching environment. J Science and Technology Information (Academic Research), 2008(12):348–349

14. Feng J, Spence I, Pratt J. Playing an action video game reduces gender differences in spatial cognition. Psychological Science, 2007, 18(10): 850–855 DOI:10.1111/j.1467-9280.2007.01990.x

15. Panorkou N, Pratt D. Using google SketchUp to develop students' experiencesof dimension in geometry. Digital Experiences in Mathematics Education, 2016, 2(3): 199–227 DOI:10.1007/s40751-016-0021-9

16. Sun J S, Lin L, Ren Y. An empirical study of 3D cad effects on developing spatial visualization and creativity for secondary school students. China Educational Technology, 2016(10): 45–50 DOI:10.1177/0963721413484756

17. Merchant Z, Goetz E T, Keeney-Kennicutt W, Cifuentes L, Kwok O, Davis T J. Exploring 3D virtual reality technology for spatial ability and chemistry achievement. Journal of Computer Assisted Learning, 2013, 29(6): 579–590 DOI:10.1111/jcal.12018

18. Yurt E, Sunbul A M. Effect of modeling-based activities developed using virtual environments and concrete objects on spatial thinking and mental rotation skills. Kuram Ve Uygulamada Egitim Bilimleri, 2012, 12(3): 1987–1992

19. Dünser A, Steinbügl K, Kaufmann H, Glück J. Virtual and augmented reality as spatial ability training tools. In: Proceedings of the 7th ACM SIGCHI New Zealand chapter's international conference on computer-human interaction: design centered HCI. 2006, 125–132

20. Yeh S C, Wang J L, Wang C Y, Lin P H, Chen G D, Rizzo A. Motion controllers for learners to manipulate and interact with 3D objects for mental rotation training. British Journal of Educational Technology, 2014, 45(4): 666–675 DOI:10.1111/bjet.12059

21. Davis F D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 1989, 13(3): 319 DOI:10.2307/249008

22. Lucas J. Immersive VR in the construction classroom to increase student understanding of sequence, assembly, and space of wood frame construction. Journal of Information Technology in Construction, 2018, 23(9): 179–194

23. Hew K F, Cheung W S. Use of three-dimensional (3D) immersive virtual worlds in K-12 and higher education settings: a review of the research. British Journal of Educational Technology, 2010, 41(1): 33–55 DOI:10.1111/j.1467-8535.2008.00900.x


1. Meng SONG, Shiyi LIU, Ge YU, Lili GUO, Dangxiao WANG, An immersive space liquid bridge experiment system with gesture interaction and vibrotactile feedback Virtual Reality & Intelligent Hardware 2019, 1(2): 219-232

2. Zili ZHANG, Yunchi CEN, Fan ZHANG, Xiaohui LIANG, Cumulus cloud modeling from images based on VAE-GAN Virtual Reality & Intelligent Hardware 2021, 3(2): 171-181

3. Mohan XU, Hong HUA, Co-axial depth sensor with an extended depth range for AR/VR applications Virtual Reality & Intelligent Hardware 2020, 2(1): 1-11

4. Cheng WANG, Chenglu WEN, Yudi DAI, Shangshu YU, Minghao LIU, Urban 3D modeling using mobile laser scanning: a review Virtual Reality & Intelligent Hardware 2020, 2(3): 175-212

5. Xin WANG, Su GAO, Monan WANG, Zhenghua DUAN, A marching cube algorithm based on edge growth Virtual Reality & Intelligent Hardware 2021, 3(4): 336-349

6. Hantong XU, Jiamin XU, Weiwei XU, Survey of 3D modeling using depth cameras Virtual Reality & Intelligent Hardware 2019, 1(5): 483-499

7. Pengfei HAN, Gang ZHAO, A review of edge-based 3D tracking of rigid objects Virtual Reality & Intelligent Hardware 2019, 1(6): 580-596

8. Pingbo HU, Bisheng YANG, Visual perception driven 3D building structure representa-tion from airborne laser scanning point cloud Virtual Reality & Intelligent Hardware 2020, 2(3): 261-275

9. Gustavo ALOMÍA, Diego LOAIZA, Claudia ZÙÑIGA, Xun LUO, Rafael ASOREY-CACHEDA, Procedural modeling applied to the 3D city model of Bogota: A case study Virtual Reality & Intelligent Hardware 2021, 3(5): 423-433

10. Fanfan WU, Feihu YAN, Weimin SHI, Zhong ZHOU, 3D scene graph prediction from point clouds Virtual Reality & Intelligent Hardware 2022, 4(1): 76-88

11. Xiang GAO, Hainan CUI, Lingjie ZHU, Tianxin SHI, Shuhan SHEN, Multi-source data-based 3D digital preservation of large-scale ancient chinese architecture: A case report Virtual Reality & Intelligent Hardware 2019, 1(5): 525-541

12. Abhishek MUKHOPADHYAY, G S Rajshekar REDDY, KamalPreet Singh SALUJA, Subhankar GHOSH, Anasol PEÑA-RIOS, Gokul GOPAL, Pradipta BISWAS, Virtual-reality-based digital twin of office spaces with social distance measurement feature Virtual Reality & Intelligent Hardware 2022, 4(1): 55-75

13. Wei LYU, Zhong ZHOU, Lang CHEN, Yi ZHOU, A survey on image and video stitching Virtual Reality & Intelligent Hardware 2019, 1(1): 55-83

14. Lin HUANG, Boshen ZHANG, Zhilin GUO, Yang XIAO, Zhiguo CAO, Junsong YUAN, Survey on depth and RGB image-based 3D hand shape and pose estimation Virtual Reality & Intelligent Hardware 2021, 3(3): 207-234