Skip to main content

Advertisement

Log in

How does Dental Students’ expertise influence their clinical performance and Perceived Task load in a virtual Dental Lab?

  • Published:
Journal of Computing in Higher Education Aims and scope Submit manuscript

Abstract

The purposes of this study were (1) to introduce a virtual dental lab designed to support students’ virtual clinical examinations in a dentistry program in South Korea and (2) to determine how dental students’ levels of expertise (low, medium, or high) influence their clinical performance in terms of dwell time on each tooth location, total examination time, and perceived task load in the virtual dental lab. A total of 93 students participated in the study. Participants were assigned to one of three groups based on their expertise levels and performed virtual reality simulation tasks of detecting and diagnosing dental caries in two clinical cases. The outcome variables were participants’ clinical examination performance (total dwell time on the virtual dental mirror and total examination time) and perceived task load (separated into six subcomponents: mental demands, physical demands, temporal demands, effort, performance, and frustration). The results suggest that the level of expertise significantly affected the performance of dental examinations in all areas except the anterior maxillary teeth. Both total dwell time on the dental mirror and total examination time were significantly shorter for the high expertise group than for the medium and low expertise groups. In addition, the high expertise group rated task load significantly lower for mental demands (p < .05, Cohen’s d = 0.70) and effort (p < .05, Cohen’s d = 0.75) than did the low expertise group.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Alibali, M. W., Boncoddo, R., & Hostetter, A. B. (2014). Gesture in reasoning: An embodied perspective. In L. Shapiro (Ed.), The routledge handbook of embodied cognition (1st ed.) pp.150–159. London, UK:Routledge

  • Al-Saud, L. M. (2020). The utility of haptic simulation in early restorative dental training. A scoping review. Journal of Dental Education, 85(5), 704–721

  • Al-Saud, L. M., Mushtaq, F., Mann, R. P., et al. (2020). Early assessment with a virtual reality haptic simulator predicts performance in clinical practice. BMJ Simulation and Technology Enhanced Learning, 6(5), 274–278

  • Armougum, A., Gaston-Bellegarde, A., Joie-La Marle, C., & Piolino, P. (2020). Expertise reversal effect: Cost of generating new schemas. Computers in Human Behavior, 111, 106406

    Article  Google Scholar 

  • Berger, T. (2019). Using eye-tracking to for analyzing case study materials. The International Journal of Management Education, 17(2), 304–315. doi:https://doi.org/10.1016/j.ijme.2019.05.002

    Article  Google Scholar 

  • Bizhang, M., Wollenweber, N., Singh-Hüsgen, P., Danesh, G., & Zimmer, S. (2016). Pen-type laser fluorescence device versus bitewing radiographs for caries detection on approximal surfaces. Head & face medicine, 12(1), 1–8

    Google Scholar 

  • Blanca, M. J., Alarcón, R., Arnau, J., Bono, R., & Bendayan, R. (2018). Effect of variance ratio on ANOVA robustness: Might 1.5 be the limit? Behavior Research Methods, 50(3), 937–962

    Article  Google Scholar 

  • Bueno, A. P. A., Sato, J. R., & Hornberger, M. (2019). Eye tracking – The overlooked method to measure cognition in neurodegeneration? Neuropsychologia, 133, 107191. doi:https://doi.org/10.1016/j.neuropsychologia.2019.107191

  • Castner, N., Appel, T., Eder, T., Richter, J., Scheiter, K., Keutel, C. … Kasneci, E. (2020). Pupil diameter differentiates expertise in dental radiography visual search. PloS one, 15(5), e0223941

  • Castner, N., Geßler, L., Geisler, D., Hüttig, F., & Kasneci, E. (2020). Towards expert gaze modeling and recognition of a user’s attention in realtime. Procedia Computer Science, 176, 2020–2029. doi:https://doi.org/10.1016/j.procs.2020.09.238

    Article  Google Scholar 

  • Cederberg, R. A., Bentley, D. A., Halpin, R., & Valenza, J. A. (2012). Use of virtual patients in dental education: a survey of U.S. and Canadian dental schools. Journal of Dental Education, 76(10), 1358–1364

    Article  Google Scholar 

  • Chen, N., & Fang, W. (2014). Embodied cognition and gesture-based learning. Proceedings of the 2014 IEEE 14th International Conference on Advanced Learning Technologies (pp. 6–7). Athens, Greece. doi: https://doi.org/10.1109/ICALT.2014.239

  • Clark, G. T., Suri, A., & Enciso, R. (2012). Autonomous virtual patients in dentistry: system accuracy and expert versus novice comparison. Journal of Dental Education, 76(10), 1365–1370

    Article  Google Scholar 

  • Dzeng, R. J., Lin, C. T., & Fang, Y. C. (2016). Using eye-tracker to compare search patterns between experienced and novice workers for site hazard identification. Safety science, 82, 56–67

    Article  Google Scholar 

  • Durham, M., Engel, B., Ferrill, T., Halford, J., Singh, T. P., & Gladwell, M. (2019). Digitally augmented learning in implant dentistry. Oral Maxillofac Surg Clin North Am, 31(3), 387–398. doi:https://doi.org/10.1016/j.coms.2019.03.003

    Article  Google Scholar 

  • Dwisaptarini, A. P., Suebnukarn, S., Rhienmora, P., Haddawy, P., & Koontongkaew, S. (2018). Effectiveness of the multilayered caries model and visuo-tactile virtual reality simulator for minimally invasive caries removal: A randomized controlled trial. Operative Dentistry, 43(3), 110–118

    Article  Google Scholar 

  • Gegenfurtner, A., Lehtinen, E., Jarodzka, H., & Säljö, R. (2017). Effects of eye movement modeling examples on adaptive expertise in medical image diagnosis. Computers & Education, 113, 212–225. doi:https://doi.org/10.1016/j.compedu.2017.06.001

    Article  Google Scholar 

  • Gruppen, L. D. (2017). Clinical reasoning: defining it, teaching it, assessing it, studying it. Western Journal of Emergency Medicine, 18(1), 4–7

    Article  Google Scholar 

  • Harris, D., Wilson, M., & Vine, S. (2020). Development and validation of a simulation workload measure: The simulation task load index (SIM-TLX). Virtual Reality, 24(4), 557–566

    Article  Google Scholar 

  • Hart, S. G. (2006, October). NASA-task load index (NASA-TLX); 20 years later. In Proceedings of the human factors and ergonomics society annual meeting, 50(9), pp. 904–908. Sage CA: Los Angeles, CA: Sage publications

  • Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In Advances in psychology, 52, 139–183

    Article  Google Scholar 

  • Higgins, D., Hayes, M. J., Taylor, J. A., & Wallace, J. P. (2020). How do we teach simulation-based dental education? Time for an evidence‐based, best‐practice framework. European Journal of Dental Education, 24(4), 815–821

    Article  Google Scholar 

  • Hofer, M., Hüsser, A., & Prabhu, S. (2017). The effect of an avatar’s emotional expressions on players’ fear reactions: The mediating role of embodiment. Computers in Human Behavior, 75, 883–890. doi: https://doi.org/10.1016/j.chb.2017.06.024

    Article  Google Scholar 

  • Irlbacher, G., & Girtel, G. (2009). Dental office administration. Burlington, Massachusetts: Jones & Bartlett Learning

    Google Scholar 

  • Jeong, M., Kim, B., & Ryu, J. (2020). The effects of expertise level on performance time, task accuracy, and task load in virtual reality dental simulation. The Korean Journal of Educational Methodology Studies, 32(2), 185–204

    Google Scholar 

  • Joda, T., Bornstein, M. M., Jung, R. E., Ferrari, M., Waltimo, T., & Zitzmann, N. U. (2020). Recent trends and future direction of dental research in the digital era. International journal of environmental research and public health, 17(6), 1987

  • Jung, H., Kim, H., & Moon, S. (2018). Virtual reality training simulator for tooth preparation techniques. Oral Biology Research, 42(4), 235–240

    Article  Google Scholar 

  • Kim, B., Ryu, J., Kim, J., Kim, S., & Choi, N. (2020). Evaluation of virtual reality simulation of dental caries through student questionnaire. Journal of the Korean Academy of Pediatric Dentistry, 47(3), 293–302

    Article  Google Scholar 

  • Kim, B., Yang, E., Choi, N., Kim, S., & Ryu, J. (2020). Effects of auditory feedback and task difficulty on the cognitive load and virtual presence in a virtual reality dental simulation. The Journal of the Korean dental association, 58(11), 670–682

    Google Scholar 

  • Kim, C., Kim, K., & Ryu, J. (2020). The effect of experience level on user perception in the VR based simulation for communication training with virtual patient. The Journal of Educational Information and Media, 26(3), 455–475

    Google Scholar 

  • Lee, J. Y., Donkers, J., Jarodzka, H., Sellenraad, G., & van Merriënboer, J. J. G. (2020). Different effects of pausing on cognitive load in a medical simulation game. Computers in Human Behavior, 110, 106385. doi:https://doi.org/10.1016/j.chb.2020.106385

    Article  Google Scholar 

  • Lee, S. H. (2018). Research and development of haptic simulator for dental education using virtual reality and user motion. International Journal of Advanced Culture Technology, 6(4), 52–57

    Google Scholar 

  • Liebermann, A., & Erdelt, K. (2020). Virtual education: Dental morphologies in a virtual teaching environment. J Dent Educ, 84(10), 1143–1150. doi:https://doi.org/10.1002/jdd.12235

    Article  Google Scholar 

  • Mai, H. Y., Mai, H. N., Woo, H. W., & Lee, D. H. (2021). Impact of the application of computer-based 3D simulation on acquisition of knowledge of guidance of mandibular movement. Applied Sciences, 11(1), 60

    Article  Google Scholar 

  • Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225–236

    Article  Google Scholar 

  • Marei, H. F., Abdel-Hady, A., Al-Khalifa, K., & Al-Mahalawy, H. (2019). Influence of surgeon experience on the accuracy of implant placement via a partially computer-guided surgical protocol. International Journal of Oral Maxillofacial Implants, 34(5), 1177–1183. doi:https://doi.org/10.11607/jomi.7480

    Article  Google Scholar 

  • McInnis, C., Asif, H., Ajzenberg, H., Wang, P., Mosa, A., Dang, F. … Winthrop, A. (2021). The next SSTEP: The “Surgical Skills and Technology Elective Program” decreases cognitive load during suturing tasks in 2nd year medical students. Journal of Surgical Research, 267, 598–604

    Article  Google Scholar 

  • Mirghani, I., Mushtaq, F., Allsop, M., Al-Saud, L., Tickhill, N., Potter, C. … Manogue, M. (2018). Capturing differences in dental training using a virtual reality simulator. European Journal of Dental Education, 22(1), 67–71

    Article  Google Scholar 

  • Moreau, D. (2013). Motor expertise modulates movement processing in working memory. Acta Psychologica, 142, 356–361. doi: 0.1016/j.actpsy.2013.01.011

  • Murbay, S., Chang, J. W. W., Yeung, S., & Neelakantan, P. (2020). Evaluation of the introduction of a dental virtual simulator on the performance of undergraduate dental students in the pre-clinical operative dentistry course. European Journal of Dental Education, 24(1), 5–16

    Article  Google Scholar 

  • Nassar, H. M., & Tekian, A. (2020). Computer simulation and virtual reality in undergraduate operative and restorative dental education: A critical review. Journal of Dental Education, 84(7), 812–829. doi: https://doi.org/10.1002/jdd.12138

  • Perry, S., Bridges, S. M., & Burrow, M. F. (2015). A review of the use of simulation in dental education. Simulation in Healthcare, 10(1), 31–37

    Article  Google Scholar 

  • Repetto, C., Serino, S., Macedonia, M., & Riva, G. (2016). Virtual reality as an embodied tool to enhance episodic memory in Elderly. Frontiers in Psychology, 7, 1–4. doi:https://doi.org/10.3389/fpsyg.2016.01839

    Article  Google Scholar 

  • Rhienmora, P., Haddawy, P., Khanal, P., Suebnukarn, S., & Dailey, M. N. (2010). A virtual reality simulator for teaching and evaluating dental procedures. Methods of information in medicine, 49(4), 396–405

    Article  Google Scholar 

  • Rogers, B., & Franklin, A. E. (2021). Cognitive load experienced by nurses in simulation-based learning experiences: An integrative review.Nurse Education Today,104815

  • Romero-Hall, E., Watson, G. S., Adcock, A., Bliss, J., & Tufts, A., K (2016). Simulated environments with animated agents: effects on visual attention, emotion, performance, and perception. Journal of Computer Assisted Learning, 32(4), 360–373. doi:https://doi.org/10.1111/jcal.12138

    Article  Google Scholar 

  • Ryu, J., Park, S., Yang, E., & Jeong, M. (2020). The effects of joystick-controlling and walking-around on navigating a virtual space. Educational Technology International, 21(2), 125–153

    Google Scholar 

  • Sankaranarayanan, G., Odlozil, C. A., Wells, K. O., Leeds, S. G., Chauhan, S., Fleshman, J. W. … De, S. (2020). Training with cognitive load improves performance under similar conditions in a real surgical task. The American Journal of Surgery, 220(3), 620–629. doi:https://doi.org/10.1016/j.amjsurg.2020.02.002

    Article  Google Scholar 

  • Say, R., Visentin, D., Betihavas, V., & Minutillo, S. (2019). A cognitive load theory simulation design to assess and manage deteriorating patients. International journal of nursing education scholarship, 16(1), 1–9

    Article  Google Scholar 

  • Schmidt, H. G., & Mamede, S. (2015). How to improve the teaching of clinical reasoning: A narrative review and a proposal. Medical education, 49(10), 961–973

    Article  Google Scholar 

  • Skulmowski, A., & Xu, K. M. (2021). Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load.Educational psychology review,1–26

  • Suebnukarn, S., Haddawy, P., Rhienmora, P., Jittimanee, P., & Viratket, P. (2010). Augmented kinematic feedback from haptic virtual reality for dental skill acquisition. Journal of Dental Education, 74(12), 1357–1366

    Article  Google Scholar 

  • Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123–138. https://doi.org/10.1007/s10648-010-9128-5

    Article  Google Scholar 

  • Sweller, J., van Merriënboer, J. J., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review Advance online publication, 31, 261–292. https://doi.org/10.1007/ s10648-019-09465-5

    Article  Google Scholar 

  • Szulewski, A., Egan, R., Gegenfurtner, A., Howes, D., Dashi, G., McGraw, N. C. J., & Van Merrienböer, J. J. G. (2019). A new way to look at simulation-based assessment: The relationship between gaze-tracking and exam performance. Canadian Journal of Emergency Medicine, 21(1), 129–137

    Article  Google Scholar 

  • Towers, A., Field, J., Stokes, C., Maddock, S., & Martin, N. (2019). A scoping review of the use and application of virtual reality in pre-clinical dental education. British dental journal, 226(5), 358–366

    Article  Google Scholar 

  • Turgeon, D. P., & Lam, E. W. (2016). Influence of experience and training on dental students’ examination performance regarding panoramic images. Journal of Dental Education, 80(2), 156–164

    Article  Google Scholar 

  • Van der Gijp, A., Ravesloot, C., Jarodzka, H., Van der Schaaf, M., Van der Schaaf, I., van Schaik, J. P., & Cate, T., T. J (2017). How visual search relates to visual diagnostic performance: a narrative systematic review of eye-tracking research in radiology. Advances in Health Sciences Education, 22(3), 765–787

    Article  Google Scholar 

  • Vincent, M., Joseph, D., Amory, C., et al. (2019). Contribution of haptic simulation to analogic training environment in restorative dentistry. Journal of Dent Education, 84(3), 367–376

    Article  Google Scholar 

  • Walker, J., & von Bergmann, H. (2015). Lessons from a pilot project in cognitive task analysis: the potential role of intermediates in preclinical teaching in dental education. Journal of Dental Education, 79(3), 286–294

    Article  Google Scholar 

  • Wang, D., Li, T., Zhang, Y., & Hou, J. (2016). Survey on multisensory feedback virtual reality dental training systems. European Journal of Dental Education, 20(4), 248–260

    Article  Google Scholar 

  • Zimoch, M., Pryss, R., Layher, G., Neumann, H., Probst, T., Schlee, W., & Reichert, M. (2018). Utilizing the capabilities offered by eye-tracking to foster novices’ comprehension of business process models. In Xiao, J., Mao, Z. H., Suzumura, T., & Zhang, L. J. (Eds.) International Conference on Cognitive Computing (pp. 155–163). Berlin/Heidelberg, Germany: Springer, Cham

  • Zorzal, E. R., Paulo, S. F., Rodrigues, P., Mendes, J. J., & Lopes, D. S. (2020). An immersive educational tool for dental implant placement: A study on user acceptance. International Journal of Medical Informatics, 146, 104342

    Article  Google Scholar 

Download references

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5B8070203).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jeeheon Ryu Ph.D..

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, E., Park, S., Ryu, J. et al. How does Dental Students’ expertise influence their clinical performance and Perceived Task load in a virtual Dental Lab?. J Comput High Educ 35, 245–271 (2023). https://doi.org/10.1007/s12528-022-09314-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12528-022-09314-5

Keywords

Navigation