You will be provided with a reference and some statements. Please determine whether each statement is 'supported', 'unsupported', or 'unknown' with respect to the reference. Please note:
First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
If the reference is valid, for a given statement: if the facts or data it contains can be found entirely or partially within the reference, it is considered 'supported' (data accepts rounding); if all facts and data in the statement cannot be found in the reference, it is considered 'unsupported'.

You should return the result in a JSON list format, where each item in the list contains the statement's index and the judgment result, for example:
[
    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

Below are the reference and statements:
<reference>
Mentor-Guided Learning in Immersive Virtual Environments: The Impact of Visual and Haptic Feedback on Skill Acquisition

In the early stages of learning a technical skill, trainees require guidance from a mentor through augmented feedback to develop higher expertise. However, the impact of such feedback and the different modalities used to communicate it remain underexplored in immersive virtual environments (IVE). This paper presents a study in which 27 participants were divided into three groups to learn a tool manipulation trajectory in an IVE. Two experimental groups received guidance from an expert using visual and/or haptic augmented feedback, while the control group received no feedback. The results indicate that both experimental groups showed significantly greater improvement in tool trajectory performance than the control group from pre- to post-test, with no significant differences between them. Analysis of their learning curves revealed similar performance improvements in tool trajectory across trials, outperforming the control group. Additionally, the visual-haptic feedback condition was linked to lower task load in three out of six dimensions of the NASA-TLX and a higher perceived interdependence with the expert's actions. These findings suggest that augmented feedback from an expert enhances the learning of tool manipulation skills. Although adding haptic feedback did not lead to better learning outcomes compared to visual feedback alone, it did enhance the overall user experience. These results offer valuable insights for designing IVEs that support mentor-trainee interactions through augmented feedback.

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IEEE Transactions on Visualization and Computer Graphics
2025.05
IEEE Transactions on Visualization and Computer Graphics
Mentor-Guided Learning in Immersive Virtual Environments: The Impact of Visual and Haptic Feedback on Skill Acquisition
May
2025,
pp. 3547-3557,
vol. 31
DOI Bookmark:
10.1109/TVCG.2025.3549547
Authors
Flavien Lebrun
,
IBISC Lab, Université Evry Paris-Saclay, France

Cassandre Simon
,
IBISC Lab, Université Evry Paris-Saclay, France

Assia Boukezzi
,
IBISC, Algerian Higher National School of Computer Science, France

Samir Otmane
,
IBISC Lab, Université Evry Paris-Saclay, France

Amine Chellali
,
IBISC Lab, Université Evry Paris-Saclay, France
Download PDF
SHARE ARTICLE
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Keywords
Visualization, Haptic Interfaces, Motors, Collaboration, Training, Hands, Virtual Environments, Trajectory, Timing, Visual Communication, Multimodal Interactions, Augmented Feedback, Mentorship, Remote Collaboration, Immersive Learning, Skill Acquisition, Video Feedback, Impact Of Feedback, Learning Curve, User Experience, Technical Skills, Augmented Feedback, Training Phase, Completion Time, Feedback Effects, Effective Mode, Motor Learning, Greenhouse Geisser Correction, Visual Modality, Obstacle Avoidance, Reference Trajectory, Force Feedback, Role Of Feedback, Feedback Modalities, Dynamic Time Warping, Participants Hand, Feedback Group, Main Effect Of Modality, Reference Path, Level Of Feedback, Feedback Learning, Pre Test Phase, Combination Of Modalities, Auditory Modality, Visual Cues
Abstract
In the early stages of learning a technical skill, trainees require guidance from a mentor through augmented feedback to develop higher expertise. However, the impact of such feedback and the different modalities used to communicate it remain underexplored in immersive virtual environments (IVE). This paper presents a study in which 27 participants were divided into three groups to learn a tool manipulation trajectory in an IVE. Two experimental groups received guidance from an expert using visual and/or haptic augmented feedback, while the control group received no feedback. The results indicate that both experimental groups showed significantly greater improvement in tool trajectory performance than the control group from pre- to post-test, with no significant differences between them. Analysis of their learning curves revealed similar performance improvements in tool trajectory across trials, outperforming the control group. Additionally, the visual-haptic feedback condition was linked to lower task load in three out of six dimensions of the NASA-TLX and a higher perceived interdependence with the expert's actions. These findings suggest that augmented feedback from an expert enhances the learning of tool manipulation skills. Although adding haptic feedback did not lead to better learning outcomes compared to visual feedback alone, it did enhance the overall user experience. These results offer valuable insights for designing IVEs that support mentor-trainee interactions through augmented feedback.
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References

[1]
M. J. Barrington, D. M. Wong, B. Slater, J. J. Ivanusic, and M. Ovens. Ultrasound-guided regional anesthesia: how much practice do novices require before
achieving competency in ultrasound needle visualization using a cadaver model.
Regional Anesthesia & Pain Medicine
, 37(3):334–339, 2012. doi: 10.1097/AAP.0b013e3182475fba 1.

[2]
C. Basdogan, C. Ho, M. A. Srinivasan, and M. Slater. An experimental study on the role of touch in shared virtual environments.
ACM Transactions on Computer-Human Interaction (TOCHI)
, 7:443–460, 2000. 5.

[3]
J. Boyd and A. Godbout. Corrective sonic feedback for speed skating: A case study.
Georgia Institute of Technology
, 2010. 2.

[4]
J. L. Burke, M. S. Prewett, A. A. Gray, L. Yang, F. R. Stilson, M. D. Coovert, L. R. Elliot, and E. Redden. Comparing the effects of visual-auditory and visual-tactile feedback on user performance:
a meta-analysis. In
Proceedings of the 8th international conference on Multimodal interfaces
, pp. 108–117, 2006. 2.

[5]
D. Cecilio-Fernandes, F. Cnossen, J. Coster, A. D. C. Jaarsma, and R. A. Tio. The effects of expert and augmented feedback on learning a complex medical skill.
Perceptual and motor skills
, 127(4):766–784, 2020. 2.

[6]
A. Chellali, W. Ahn, G. Sankaranarayanan, J. Flinn, S. D. Schwaitzberg, D. B. Jones, S. De, and C. G. Cao. Preliminary evaluation of the pattern cutting and the ligating loop virtual laparoscopic
trainers.
Surgical endoscopy
, 29:815–821, 2015. 2.

[7]
A. Chellali, C. Dumas, and I. Milleville-Pennel. Haptic communication to support biopsy procedures learning in virtual environments.
Presence: Teleoperators and Virtual Environments
, 21(4):470–489, 2012. 3.

[8]
A. Chellali, I. Milleville-Pennel, and C. Dumas. Influence of contextual objects on spatial interactions and viewpoints sharing in
virtual environments.
Virtual Reality
, 17(1):1–15, 2013. 3.

[9]
E. F. Churchill, D. N. Snowdon, and A. J. Munro. Collaborative virtual environments: digital places and spaces for interaction.
Springer Science & Business Media
, 2012. 2.

[10]
C. Conati and H. Maclaren. Exploring the role of individual differences in information visualization. In
Proceedings of the working conference on Advanced visual interfaces
, pp. 199–206, 2008. 2.

[11]
G. Convertino, H. M. Mentis, A. Slavkovic, M. B. Rosson, and J. M. Carroll. Supporting common ground and awareness in emergency management planning: A design
research project.
ACM Transactions on Computer-Human Interaction (TOCHI)
, 18(4):1–34, 2011. 3.

[12]
R. Crandall and E. Karadogan. Designing pedagogically effective haptic systems for learning: a review.
Applied Sciences
, 11(14):6245, 2021. 9.

[13]
D. L. Eaves, G. Breslin, P. Van Schaik, E. Robinson, and I. R. Spears. The short-term effects of real-time virtual reality feedback on motor learning in
dance.
Presence: Teleoperators and Virtual Environments
, 20(1):62–77, 2011. 2.

[14]
D. L. Eaves, M. Riach, P. S. Holmes, and D. J. Wright. Motor imagery during action observation: a brief review of evidence, theory and future
research opportunities.
Frontiers in neuroscience
, 10:514, 2016. 8.

[15]
O. Ehmer and G. Brône. Instructing embodied knowledge: multimodal approaches to interactive practices for
knowledge constitution.
Linguistics Vanguard
, 7(s4):20210012, 2021. 2.

[16]
M. Eriksson, K. A. Halvorsen, and L. Gullstrand. Immediate effect of visual and auditory feedback to control the running mechanics
of well-trained athletes.
Journal of sports sciences
, 29(3):253–262, 2011. 2.

[17]
B. E. Erlandson, B. C. Nelson, and W. C. Savenye. Collaboration modality, cognitive load, and science inquiry learning in virtual inquiry
environments.
Educational Technology Research and Development
, 58:693–710, 2010. 9.

[18]
Y. Feng, H. McGowan, A. Semsar, H. R. Zahiri, I. M. George, A. Park, A. Kleinsmith, and H. Mentis. Virtual pointer for gaze guidance in laparoscopic surgery.
Surgical endoscopy
, 34:3533–3539, 2020. 3.

[19]
D. Feygin, M. Keehner, and R. Tendick. Haptic guidance: Experimental evaluation of a haptic training method for a perceptual
motor skill. In
Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator
Systems. HAPTICS 2002
, pp. 40–47. IEEE, 2002. 2.

[20]
N. S. Fong, W. F. A.W. Mansor, M. H. Zakaria, N. H. M. Sharif, and N. A. Nordin. The roles of mentors in a collaborative virtual learning environment (cvle) project.
Procedia-Social and behavioral sciences
, 66:302–311, 2012. 8.

[21]
R. K. Ghamandi, R. K. Kattoju, Y. Hmaiti, M. Maslych, E. M. Taranta, R. P. McMahan, and J. LaViola. Unlocking understanding: An investigation of multimodal communication in virtual reality
collaboration. In
Proceedings of the CHI Conference on Human Factors in Computing Systems
, pp. 1–16, 2024. 2, 3.

[22]
G. Gignac. How2statsbook (online 2023 edition), chapter 11.
Perth, Australia
, 2023. 7, 8.

[23]
R. B. Gillespie, M. S. O'Modhrain, P. Tang, D. Zaretzky, and C. Pham. The virtual teacher. In
ASME International Mechanical Engineering Congress and Exposition
, vol. 15861, pp. 171–178. American Society of Mechanical Engineers, 1998. 1.

[24]
C. Gutwin, O. Schneider, R. Xiao, and S. Brewster. Chalk sounds: the effects of dynamic synthesized audio on workspace awareness in distributed
groupware. In
Proceedings of the ACM 2011 conference on Computer supported cooperative work
, pp. 85–94, 2011. 3.

[25]
C. Harms and F. Biocca. Internal consistency and reliability of the networked minds measure of social presence. In
Seventh Annual International Workshop: Presence 2004
, 2004. 5.

[26]
S. G. Hart. Nasa-task load index (nasa-tlx); 20 years later. In
Proceedings of the human factors and ergonomics society annual meeting
, vol. 50, pp. 904–908. Sage publications Sage CA: Los Angeles, CA, 2006. 6.

[27]
S. G. Hart and L. E. Staveland. Development of NASA-TLX (task load index): Results of empirical and theoretical research. In
Advances in psychology
, vol. 52, pp. 139–183. Elsevier, 1988. doi: 10.1016/s0166-4115(08)62386-9 5.

[28]
J. Hattie and H. Timperley. The power of feedback.
Review of educational research
, 77(1):81–112, 2007. 1.

[29]
D. Hecht and M. Reiner. Sensory dominance in combinations of audio, visual and haptic stimuli.
Experimental brain research
, 193:307–314, 2009. 8.

[30]
N. Houghton, A. Prionas, R. Kneebone, and V. Papalois. Ethics of training surgeons.
British Journal of Surgery
, 111(12):znae252, 2024. 1.

[31]
M. S. Islam and S. Lim. Vibrotactile feedback in virtual motor learning: A systematic review.
Applied Ergonomics
, 101:103694, 2022. 2.

[32]
A. J. Kovacs and C. H. Shea. The learning of 90 continuous relative phase with and without lissajous feedback:
external and internally generated bimanual coordination.
Acta psychologica
, 136(3):311–320, 2011. 2.

[33]
J. W. Krakauer and P. Mazzoni. Human sensorimotor learning: adaptation, skill, and beyond.
Current opinion in neurobiology
, 21(4):636–644, 2011. 8.

[34]
T. Langerak, J. J. Zárate, V. Vechev, D. Lindlbauer, D. Panozzo, and O. Hilliges. Optimal control for electromagnetic haptic guidance systems. In
Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology
, pp. 951–965, 2020. 4.

[35]
B. Lauber and M. Keller. Improving motor performance: Selected aspects of augmented feedback in exercise and
health.
European journal of sport science
, 14(1):36–43, 2014. 7, 8.

[36]
C. Lin, D. Andersen, V. Popescu, E. Rojas-Munoz, M. E. Cabrera, B. Mullis, B. Zarzaur, K. Anderson, S. Marley, and J. Wachs. A first-person mentee second-person mentor ar interface for surgical telementoring. In
2018 IEEE international symposium on mixed and augmented reality adjunct (ISMAR-Adjunct)
, pp. 3–8. IEEE, 2018. 3.

[37]
M. Liu, S. Wilder, S. Sanford, M. Glassen, S. Dewil, S. Saleh, and R. Nataraj. Augmented feedback modes during functional grasp training with an intelligent glove
and virtual reality for persons with traumatic brain injury.
Frontiers in Robotics and AI
, 10:1230086, 2023. 3.

[38]
C. MacKenzie, T. M. Chan, and S. Mondoux. Clinical improvement interventions for residents and practicing physicians: a scoping
review of coaching and mentoring for practice improvement.
AEM Education and Training
, 3(4):353–364, 2019. 1.

[39]
L. Marchal-Crespo and D. J. Reinkensmeyer. Review of control strategies for robotic movement training after neurologic injury.
Journal of neuroengineering and rehabilitation
, 6:1–15, 2009. 2.

[40]
D. Martin, S. Malpica, D. Gutierrez, B. Masia, and A. Serrano. Multimodality in vr: A survey.
ACM Computing Surveys (CSUR)
, 54(10s):1–36, 2022. 2, 3.

[41]
A. Moinuddin, A. Goel, and Y. Sethi. The role of augmented feedback on motor learning: a systematic review.
Cureus
, 13(11), 2021. 1, 2, 7.

[42]
J. Moll, E.-L. S. Pysander, K. S. Eklundh, and S.-O. Hellström. The effects of audio and haptic feedback on collaborative scanning and placing.
Interacting with computers
, 26(3):177–195, 2014. 3.

[43]
K. L. Nowak and F. Biocca. The effect of the agency and anthropomorphism of users' sense of telepresence, copresence,
and social presence in virtual environments.
Presence: Teleoper. Virtual Environ.
, 12:481–494, 2003. doi: 10.1162/105474603322761289 5.

[44]
I. Oakley, S. Brewster, and P. Gray. Can you feel the force? an investigation of haptic collaboration in shared editors. In
proceedings of EuroHaptics
, vol. 2001, pp. 54–59, 2001. 2.

[45]
S. Ojala, J. Sirola, T. Nykopp, H. Kröger, and H. Nuutinen. The impact of teacher's presence on learning basic surgical tasks with virtual reality
head-set among medical students.
Medical education online
, 27(1):2050345, 2022. 8.

[46]
A. Peña Pérez Negrón, N. E. Rangel Bernal, and G. Lara López. Nonverbal interaction contextualized in collaborative virtual environments.
Journal on Multimodal User Interfaces
, 9:253–260, 2015. 2.

[47]
L. Proteau and D. Elliott.
Vision and motor control
. Elsevier, 1992. 2.

[48]
R. Ranganathan and K. M. Newell. Influence of augmented feedback on coordination strategies.
Journal of motor behavior
, 41(4):317–330, 2009. 2.

[49]
G. Rauter, R. Sigrist, R. Riener, and P. Wolf. Learning of temporal and spatial movement aspects: A comparison of four types of haptic
control and concurrent visual feedback.
IEEE transactions on haptics
, 8(4):421–433, 2015. 2.

[50]
R. Riener, M. Harders, R. Riener, and M. Harders. Vr for medical training.
Virtual reality in medicine
, pp. 181–210, 2012. 8.

[51]
E. M. Ritter and D. J. Scott. Design of a proficiency-based skills training curriculum for the fundamentals of laparoscopic
surgery.
Surgical innovation
, 14(2):107–112, 2007. 4.

[52]
E.-L. Sallnäs, K. Rassmus-Gröhn, and C. Sjöström. Supporting presence in collaborative environments by haptic force feedback.
ACM Transactions on Computer-Human Interaction (TOCHI)
, 7(4):461–476, 2000. 3.

[53]
R. A. Schmidt. Frequent augmented feedback can degrade learning: Evidence and interpretations. In
Tutorials in motor neuroscience
, pp. 59–75. Springer, 1991. 2.

[54]
U. A. Shaikh, A. J. Magana, L. Neri, D. Escobar-Castillejos, J. Noguez, and B. Benes. Undergraduate students' conceptual interpretation and perceptions of haptic-enabled
learning experiences.
International Journal of Educational Technology in Higher Education
, 14:1–21, 2017. 9.

[55]
L. Shams and A. R. Seitz. Benefits of multisensory learning.
Trends in cognitive sciences
, 12(11):411–417, 2008. 2.

[56]
Y. Shi, M. Liu, S. Dewil, N. Y. Harel, S. Sanford, and R. Nataraj. Augmented sensory feedback during training of upper extremity function in virtual
reality. In
2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS)
, pp. 231–236. IEEE, 2024. 3.

[57]
R. Sigrist, G. Rauter, R. Riener, and P. Wolf. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review.
Psychonomic bulletin & review
, 20:21–53, 2013. 2, 9.

[58]
C. Simon, M. Boukli-Hacene, F. Lebrun, S. Otmane, and A. Chellali. Impact of multimodal instructions for tool manipulation skills on performance and
user experience in an immersive environment. In
2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)
, pp. 670–680. IEEE, 2024. 2, 3, 5.

[59]
C. Simon, M. Boukli-Hacene, S. Otmane, and A. Chellali. Study of communication modalities to support teaching tool manipulation skills in
a shared immersive environment.
Computers & Graphics
, 117:31–41, 2023. 2, 3, 9.

[60]
C. Simon, L. Herfort, F. Lebrun, E. Brocas, S. Otmane, and A. Chellali. Design and evaluation of ultrasim: An immersive simulator for learning ultrasound-guided
regional anesthesia basic skills.
Computers & Graphics
, 119:103878, 2024. 3.

[61]
H. G. Stassen, H. J. Bonjer, C. A. Grimbergen, and J. Dankelman. The future of minimally invasive surgery and training.
Engineering for patient safety: issues in minimally invasive procedures
, pp. 272–282, 2005. 1.

[62]
A. Steed and R. Schroeder. Collaboration in immersive and non-immersive virtual environments.
Immersed in media: Telepresence theory, measurement & technology
, pp. 263–282, 2015. 2.

[63]
S. Sülzenbück and H. Heuer. Type of visual feedback during practice influences the precision of the acquired internal
model of a complex visuo-motor transformation.
Ergonomics
, 54(1):34–46, 2011. 2.

[64]
Y. Sunaryadi. The role of augmented feedback on motor skill learning. In
6th International Conference on Educational, Management, Administration and Leadership
, pp. 271–275. Atlantis Press, 2016. 1.

[65]
M. Tagliabue and J. McIntyre. A modular theory of multisensory integration for motor control.
Frontiers in computational neuroscience
, 8:1, 2014. 8.

[66]
S. M. Underwood. Effects of augmented real-time auditory feedback on top-level precision shooting performance.
Master's thesis, University of Kentucky
, 2009. 2.

[67]
J. B. Van Erp and A. Toet. Social touch in human-computer interaction.
Frontiers in digital humanities
, 2:2, 2015. 9.

[68]
H. S. Vitense, J. A. Jacko, and V. K. Emery. Multimodal feedback: an assessment of performance and mental workload.
Ergonomics
, 46(1–3):68-87, 2003. 9.

[69]
J. Wang, A. Chellali, and C. G. Cao. Haptic communication in collaborative virtual environments.
Human factors
, 58(3):496–508, 2016. 3.

[70]
K. Wei and K. Kording. Relevance of error: what drives motor adaptation?
Journal of neurophysiology
, 101(2):655–664, 2009. 2.

[71]
D. M. Wolpert and J. R. Flanagan. Motor learning.
Current biology
, 20(11):R467-R472, 2010. 8.

[72]
F. Wu, J. Thomas, S. Chinnola, and E. S. Rosenberg. Exploring communication modalities to support collaborative guidance in virtual reality. In
2020 IEEE conference on virtual reality and 3d user interfaces abstracts and workshops
(VRW)
, pp. 79–86. IEEE, 2020. 3.

[73]
G. Wulf and C. H. Shea. Principles derived from the study of simple skills do not generalize to complex skill
learning.
Psychonomic bulletin & review
, 9(2):185–211, 2002. 1.

[74]
G. Wyvill, C. McPheeters, and B. Wyvill. Data structure for soft objects.
The Visual Computer
, 2(4):227–234, Aug.1986. doi: 10.1007/BF01900346 5.

[75]
X.-D. Yang, W. F. Bischof, and P. Boulanger. Validating the performance of haptic motor skill training. In
2008 Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
, pp. 129–135. IEEE, 2008. 2.

[76]
E. Yiannakopoulou, N. Nikiteas, D. Perrea, and C. Tsigris. Virtual reality simulators and training in laparoscopic surgery.
International Journal of Surgery
, 13:60–64, 2015. 2.

[77]
A. Ziv, P. R. Wolpe, S. D. Small, and S. Glick. Simulation-based medical education: an ethical imperative.
Simulation in Healthcare
, 1(4):252–256, 2006. 1.

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</reference>

<statements>
1. Wearable vibrotactile actuators apply targeted tactile pulses to relevant limbs, prompting rapid reflexive adjustments when joint angles exceed acceptable margins [16].
2. The delivery and frequency of this feedback are guided by the Guidance Hypothesis formulated by Salmoni, Schmidt, and Walter [16].
3. Continuous concurrent feedback can accelerate short-term performance gains during guided practice, but it frequently undermines long-term motor skill retention because learners become dependent on external cues instead of developing internal proprioceptive error-detection mechanisms [16].
4. Faded feedback provides frequent guidance during early cognitive stages and systematically reduces feedback frequency as movement patterns stabilize [16].
5. Terminal summary feedback delays detailed kinematic breakdowns and visual retrospectives until the end of a drill set, encouraging reflective self-assessment between practice attempts [16].
6. Processing delays exceeding 100 milliseconds disrupt an athlete's motor control timing and diminish the effectiveness of augmented sensory feedback [16].
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.