Proactive experiences of vibrotactile stimuli enhance learners’ task-specific confidence in cooking skills

In skill acquisition, learners’ motivation plays an important role. Based on embodied cognition and haptic learning, we hypothesized that vibro-acoustic stimuli could serve as valuable feedback to enhance motivation. In this study, three experiments explored whether such stimuli strengthen learners’ task-specific confidence in their cooking abilities. Experiment 1 examined the discriminability of vibro-acoustic stimuli as feedback. Sounds and vibrations were recorded when a professional chef and an amateur cut two types of food, and were presented via a haptic device to participants, who evaluated the sensations. Participants successfully distinguished between the two performers solely through the vibro-acoustic stimuli. Experiments 2 and 3 investigated how vibro-acoustic stimuli corresponding to food cutting affect task-specific confidence. Participants who actively experienced the stimuli while watching a professional chef’s video showed greater confidence than those who only felt the stimuli passively. These findings point to the potential applicability of vibro-acoustic stimuli in facilitating certain aspects of cooking skill acquisition, although the current work is an exploratory step toward integrating haptic cues into cooking education rather than a demonstration of performance improvement.

1 Introduction

Recent studies have investigated how digital technologies can support skill learning by enabling learners to physically experience relevant motor movements. (Juliano and Liew, 2020). In the medical field, virtual reality has been employed to teach skills for which physical training materials are unavailable, such as surgical procedures (Sveistrup, 2004) and rehabilitation training (Gallagher et al., 2005). Moreover, research in sports and rehabilitation has intensively investigated multimodal feedback within the framework of motor learning as reviewed in Sigrist et al. (2013).

Previous studies on cooking-skill acquisition have mainly utilized visual information to promote understanding of complex cooking processes. For instance, a digital cooking navigation system was developed to help beginners follow recipes more efficiently by visualizing step-by-step structures (Hamada et al., 2005). Other systems have displayed process-related information directly on physical cooking devices (Sato et al., 2014), and virtual-reality cooking applications have been proposed for patients with Alzheimer’s disease (Yamaguchi et al., 2012). Video-based assistance has also been shown to improve learners’ cooking skills by fostering self-confidence (Surgenor et al., 2017). While these systems have advanced procedural understanding, less attention has been paid to learners’ motivational factors in acquiring cooking skills.

Motivation and awareness of what a skill entails are crucial in skill acquisition. In this regard, self-efficacy theory (Bandura, 1977), including self-control, is considered a key factor influencing motivation (Wulf, 2007; Wulf et al., 2010). Wulf (2007) reported that when learners have a sense of autonomy and control over their own movements, their motivation increases and their attention to the task strengthens, thereby enhancing learning outcomes. Given that preparedness self-efficacy improves through exposure to educational virtual reality (Shu et al., 2019), and that students’ self-perception of their abilities affects self-efficacy for learning (Daradoumis et al., 2022), this study explores whether learners’ motivation to acquire cooking skills can be enhanced without face-to-face instruction by using multimedia content.

From the perspective of embodied cognition, cognitive processes are grounded in bodily interactions with the environment (Barsalou, 2008; Wilson, 2002). Learning, therefore, is not purely mental but shaped by sensorimotor engagement. Haptic feedback, though still underutilized, bridges abstract conceptual understanding and bodily experience (Minogue and Jones, 2006). Prior research has shown that multimodal feedback combining visual, auditory, and haptic cues can enhance motor learning and engagement (Sigrist et al., 2013), and that adaptive haptic systems promote users’ sense of control and mastery (Nishida et al., 2022). Building on these foundations, recent studies demonstrate the motivational potential of haptic stimulation across learning domains. Manrique et al. (2024) reported that haptic interaction in 3D anatomy workshops increased students’ motivation compared with 2D instruction. Lee et al. (2025) found that incorporating haptic feedback into piano-learning interfaces enhanced engagement, while Ratschat et al. (2024) showed that combining tactile and kinesthetic feedback reduced task errors of shape reproduction and encouraged sustained exploration. Reviews further highlight the clinical and training potential of haptic technology, emphasizing its role in promoting engagement, confidence, and self-efficacy through embodied interaction (Pacheco-Barrios et al., 2024). Collectively, these findings suggest that coupling active movements with haptic feedback enhances both performance and motivational outcomes.

In cooking, bodily interaction with utensils and materials is fundamental. Vibro-acoustic stimuli (hereafter “V-A stim”), which combine tactile vibration and auditory cues, may therefore serve as an effective form of embodied, multimodal feedback for learning cooking skills. Given that vibrations generated during knife-cutting encode tactile information about texture, such as the firmness of vegetables or the resistance of fish bones (Zhang et al., 2019), such stimuli may enhance learners’ confidence in performing cooking tasks. Accordingly, we hypothesize that active engagement with V-A stim during food-cutting actions can enhance learners’ task-specific confidence.

As a preliminary investigation, three experiments were conducted using a device developed to deliver V-A stim (Komazaki et al., 2023). Experiment 1 examined whether V-A stim could convey information about the performer’s skill and the quality of cooking tools. Experiment 2 compared active and passive engagement to assess effects on learners’ confidence. Experiment 3 further explored how V-A stim influences the task-specific confidence. It should be note that this study serves as an initial exploratory step toward integrating V-A stim feedback into cooking education, aiming to provide preliminary insights rather than to demonstrate direct improvements in performance.

2 Experiment 1: cooking skill discrimination without visual information

This experiment examined the discriminability and evaluation of cooking V–A stim generated when a professional chef and an amateur cut two food materials.

2.1 Method

This experiment used a within-subjects design to investigate whether participants could discriminate differences in cooking skill and tool quality based on V–A stim. All participants experienced all stimulus conditions.

2.1.1 Participants

Sixteen undergraduate and graduate students participated (ages 18 or older; one participant in their late teens and the remaining 15 in their twenties; 4 males, 12 females; all right-handed; none with professional cooking experience). The procedures were explained beforehand, and permission to use the data for research purposes was obtained both orally and in writing. Only those who agreed participated. The experiment was conducted in accordance with the Declaration of Helsinki and approved by the authors’ institutional ethics committee.

2.1.2 Apparatus

A professional (a senior chef at a Japanese restaurant, right-handed) and an amateur (a person who does not cook daily, right-handed) were filmed cutting various food materials with a knife on a cutting board, and the sounds and vibrations generated were recorded (Figure 1-1). An external microphone (Rode, NTG) was attached to a camera (Leica, AG) for recording the video and audio, and simultaneously, a 3-axis acceleration sensor (Kionix, KXTC9-2050) was attached with double-sided tape to the back of a sawara wood cutting board (W × D × H of 420 mm × 300 mm × 55 mm) to record vibration signals. The cutting board had steps underneath to lift the board from the table, and the space created resonant sound. Signals from the sensor were recorded using a recording device (Tascam, DR40). The video, audio, and vibration signals were mixed to create video clips. The video clip was played using a tablet PC (Chuwi, UBOOK) (Figure 1-2a). The audio and vibration signals were mixed and sent to an actuator (Foster, 576865) attached to the back of a cutting board (W × D of 350 mm × 250 mm, with 10-mm-thick rubber between the wooden top surface and a 20-mm high aluminium frame) through an amplifier (Classic Pro, DCP30 mini).

Figure 1

Figure 1. System configurations and experimental procedures. (1) System configuration for filming. (2) Presenting stimuli. (2a,2b) illustrate the passive (board only) and active (board + knife) conditions, respectively. (3) Experimental procedure of Experiment 1. (4) Experimental procedure of Experiment 2. (3,4) depict the trial sequences of Experiments 1 and 2.

2.1.3 Materials

Six vibration-and-sound stimuli were used. Two types of vegetables considered easy for untrained individuals to cut (cabbage (Brassica oleracea L. var. capitata) and welsh onion (Allium fistulosum)) were cut by the amateur with a household knife, by the professional with a household knife, and by the professional with a professional knife, each for about 20 s.

2.1.4 Procedure

Each stimulus was presented once via the board device. Participants placed both hands on the device to experience the vibration (Figure 1-3). After each stimulus, participants rated three items on a 10-point scale: attractiveness of the vibration (attractiveness), perceived materiality (materiality), and cooking skill of the performer (cooking skill). The stimulus order was randomized within vegetable type. Participants were told only that the stimuli involved cutting food materials and were given no criteria for judging skill; evaluations were left entirely to subjective impressions.

2.1.5 Analysis

Ratings were analyzed with one-way ANOVAs for each vegetable and each index to examine whether participants could discriminate performers and tools. Analyses were conducted using statistical software HAD ver. 17_202 (Shimizu, 2016).

2.2 Results

An ANOVA test was conducted on the three indices (attractiveness, materiality, and cooking skill of performer) for cabbage (Attractiveness; F (2,30) = 19.035, p < 0.001, partial η² = 0.559, Materiality; F (2,30) = 2.753, p = 0.081, partial η² =0 .155, Cooking skill; F (2,30) = 98.778, p < 0.001, partial η² =0 .868) and welsh onion (Attractiveness; F (2,30) = 34.634, p < 0.001, partial η² = 0.698, Materiality; F (2,30) = 12.347, p < 0.001, partial η² =0 .451, Cooking skill; F (2,30) = 223.557, p < 0.001, partial η² =0 .937), and significant differences were found for all indices except for cabbage materiality (Figure 2-1).

Figure 2

Figure 2. Results of Experiment 1. (1) Mean evaluation scores (10-point scale) for three indices - Attractiveness, Materiality, and Cooking skill - in the cabbage and Welsh onion cutting conditions. White bars indicate an amateur using a household knife; light gray bars, a professional using a household knife; and dark gray bars, a professional using a professional knife. Asterisks indicate significant differences (p < 0.01). Mauchly’s test indicated that the assumption of sphericity was met for all measures in the cabbage condition (all ps > 0.05). In the Welsh onion condition, sphericity was violated for Attractiveness (p = 0.011) and Materiality (p = 0.025), which were corrected using the Greenhouse–Geisser method (both corrected ps < 0.001), while Cooking skill met the assumption of sphericity (p > 0.05). (2) Typical waveform patterns of V-A stim recorded from an amateur and a professional chef while cutting cabbage with a household knife. The professional waveform shows greater amplitude and rhythmicity. Amplitude values were normalized to a range between −1 and 1. (3) Typical waveform patterns recorded from a professional chef cutting Welsh onion using a professional knife versus a household knife. The waveform generated with the professional knife shows less noise and greater consistency. Amplitude values were normalized to a range between −1 and 1.

Typical waveform patterns for the amateur and professional are shown in Figure 2-2. Although both waveforms were generated while cutting similar parts of the cabbage, the professional’s waveform exhibited greater amplitude and rhythmicity. Typical waveform patterns for the professional using household and professional knives are shown in Figure 2-3. Although generated while cutting similar parts of the Welsh onion, the waveform using the professional knife appeared less noisy.

These results indicated that, for the two food materials used, differences between the performers can be discriminated in terms of attractiveness and cooking skill simply by perceiving the V-A stim of cutting. In addition, the participants evaluated the stimuli of the professional chef’s cutting with the professional knife as being more attractive and skilled even when no instruction about the performers and devices were given.

3 Experiment 2: rating task-specific confidence in cooking skills

This experiment compared active and passive experiences of V-A stim while participants watched a cooking video to explore how such stimuli affect task-specific confidence in cooking skills.

3.1 Method

This experiment used a within-subjects design to investigate how active versus passive experiences of V-A stim affects learners’ task-specific confidence.

3.1.1 Participants

The same sixteen undergraduate and graduate students who participated in Experiment 1 took part in this experiment.

3.1.2 Apparatus

The video clip was played on a tablet PC (Chuwi, UBOOK) (Figure 1-2b). The video signal was sent to a 21.5-inch monitor (HP Pavilion 22bw). Audio and vibration signals were mixed and delivered to an actuator (Foster, 576865) attached to the back of a cutting board (W × D of 350 mm × 250 mm, with 10-mm-thick rubber between the wooden top surface and a 20-mm-high aluminium frame) through an amplifier (Classic Pro, DCP30 mini). The audio and vibration signals were also played with an actuator (Foster, 639897) attached to the center of the blade of a knife-type device. The knife-type device was fabricated with a 3D printer based on the shape of a Santoku kitchen knife, which is commonly used in households in Japan.

3.1.3 Materials

A cabbage and a Hamo (daggertooth pike conger, and Muraenesox cinereus) were used. Video, vibration, and sound were recorded from the professional chef cutting the cabbage into thin strips and cutting the bones of the Hamo (approximately 40 s each). The videos were horizontally mirrored to facilitate imitation of right-handed participants. The cabbage had to be cut as finely (thinly sliced) and quickly as possible, while only the bones and flesh of the Hamo, which is a species with many small bones, had to be cut as closely as possible without cutting the skin. Two stimuli of the professional with a professional knife performing “thin-slicing cabbage” (Figure 3-1) and “bone-cutting a Hamo” (Figure 3-2) were prepared.

Figure 3

Figure 3. Stimulus images and experimental conditions in Experiments 2 and 3. (1) Stimulus frames captured from the videos of a professional chef cutting thin-sliced cabbage. (2) Stimulus frames captured from the videos of a professional chef cutting a Hamo. (3) Photograph of passive condition in Experiment 2 (corresponding to the watching condition in Experiment 3), in which participants placed both hands on the board device while watching a cutting video displayed on the monitor. (4) Photograph of active condition in Experiment 2 (corresponding to the moving and active conditions in Experiment 3), in which participants placed the left hand on the board device and held the knife device with the right hand while watching a cutting video. The scenes shown in (3,4) are examples representing the participant setup during the experiments.

3.1.4 Procedure

Each of the two stimuli was presented under two conditions: 1) a passive condition using the board device and 2) an active condition using the board and knife devices. In the passive condition, participants placed both their hands on the board device (Figure 1-4 left; Figure 3-3). In the active condition, participants placed the left hand on the board device, held the knife device with the right hand, and moved it in synchrony with the knife movements shown in the video (Figure 1-4 right; Figure 3-4). We have already confirmed the difference in experience between holding a knife-shaped device and moving it actively (Komazaki et al., 2023). For each stimulus, the participants rated the following three items on a 10-point scale: attractiveness, materiality, and cooking skill, and evaluated two questions on a 10-point scale: “If you were to actually cut the food that you experienced vibrating, do you think you could do it with confidence?” (task-specific confidence, labelled as “confidence” in Figure 4), and “Can you imagine yourself cutting the food that you experienced?” (motor imagery, labelled as “image” in Figure 4). The passive condition always preceded the active condition for all participants.

Figure 4

Figure 4. Results of Experiments 2 and 3. (1) Mean evaluation scores (10-point scale) for five indices - Attractiveness, Materiality, Cooking skill, Confidence, and Image - in the “thin-sliced cabbage” and “bone-cutting a Hamo” conditions of Experiment 2. In the passive condition, participants placed both hands on the board device. In the active condition, they placed the left hand on the board device, held the knife device with the right hand, and moved it in synchrony with the knife movements shown in the video. White bars indicate the passive condition (board only), and gray bars indicate the active condition (board and knife). (2) Mean evaluation scores (10-point scale) for the “bone-cutting a Hamo” condition in Experiment 3, evaluated on the same five indices. The watching condition involved no vibration while participants kept both hands on the board device. The moving condition involved synchronized knife movement without vibration, and the active condition included both vibration and movement. White bars indicate the watching condition, light gray bars the moving condition, and dark gray bars the active condition. Mauchly’s test indicated that the assumption of sphericity was violated for Materiality (p = 0.023) and one other measure, which were corrected using the Greenhouse–Geisser method (both corrected ps < 0.001). All remaining measures met the assumption of sphericity (all ps > 0.05).

3.1.5 Analysis

Paired t-tests were conducted for each index (Attractiveness, Materiality, Cooking skill, Confidence, Image) to compare the active and passive conditions. Effect sizes (Cohen’s d) were also calculated.

3.2 Results

As shown in Figure 4-1, corresponding t-tests for “thin-slicing cabbage” and “bone-cutting a Hamo” were conducted on the five indices. For “thin-slicing cabbage,” the scores under the active condition (cutting board and knife) were significantly higher than those under the passive condition (cutting board alone) in the three indices of cooking skill, confidence, and image (Attractiveness; t (15) = 0.000, p = 1.000, d =0 .000, Materiality; t (15) = 1.826, p = 0.088, d =0 .383, Cooking skill; t (15) = 2.236, p < 0.05, d =0 .716, Confidence; t (15) = 3.308, p < 0.01, d =0 .495, Image; t (15) = 2.952, p < 0.01, d =0 .578). For “bone-cutting a Hamo,” the scores under the active condition were significantly higher than those under the passive condition for confidence and image (Attractiveness; t (15) = 0.436, p = 0.669, d =0.155, Materiality; t (15) = 0.212, p = 0.835, d =0 .074, Cooking skill; t (15) = 1.732, p = 0.104, d =0 .603, Confidence; t (15) = 4.876, p < 0.001, d =0 .901, Image; t (15) = 4.452, p < 0.001, d =0 .947).

These results indicate that task-specific confidence and motor imagery can be enhanced by proactively experiencing V-A stim while watching a professional chef’s cutting actions, demonstrating the advantage of the active condition over the passive condition.

4 Experiment 3: effectiveness of vibro-acoustic stimuli on confidence in cooking skills

Experiment 2 indicated that the V-A stim in the active condition affects the task-specific confidence regardless of food type. In this experiment, to explore effectiveness of V-A stim, we made a comparison between moving hand operations with and without V-A stim while participants watched a cooking video.

4.1 Method

This experiment used a within-subjects design with three conditions (watching, moving, and, active) to examine the effect of V-A stim and hand movement on participants’ confidence, imagery, and perceptual evaluations.

4.1.1 Participants

Ten undergraduate students participated (aged in their 20s; all males; all right-handed; none with professional cooking experience). They did not participate in Experiment 1 or 2.

4.1.2 Apparatus

The apparatus was identical to that used in Experiment 2, except for the PC and monitor. The video clip was played on a notebook PC (MacBook Pro, 14-inch), and the video signal was displayed on a 15.6-inch external monitor (Cocopar, ZB-156).

4.1.3 Materials

The same video, vibration, and sound data of “bone-cutting Hamo” used in Experiment 2 were used.

4.1.4 Procedure

The Hamo stimulus was presented under three conditions: 1) a watching condition that was the same as the passive condition in Experiment 2 except that no vibration was presented, 2) a moving condition that was the same as the active condition in Experiment 2 except that no vibration was presented, and 3) an active condition that was the same in Experiment 2. In the watching condition the participants placed both their hands on the board device (Figure 3-3). In the moving and active conditions, participants placed the left hand on the board device, held the knife device with the right hand, and moved it in synchrony with the knife movements shown in the video (Figure 3-4). In watching and moving conditions, no vibration was presented with the devices. For each stimulus, the participants rated the same five questions as in Experiment 2. The watching condition was performed first for all participants, and the order of the moving and active conditions was counterbalanced across participants.

4.1.5 Analysis

Data were analyzed using repeated-measures ANOVA on the five dependent variables (Attractiveness, Materiality, Cooking skill, Confidence, and Image) across the three conditions. Non-significant results were interpreted in relation to the characteristics of the stimuli and participants’ prior experience.

4.2 Results

As shown in Figures 4–2, ANOVA tests were conducted on the five indices. Significant differences across conditions were observed for Attractiveness, Confidence, and Image, with the highest scores in the active condition, followed by the moving and watching conditions (Attractiveness: F (2, 18) = 36.763, p < 0.001, partial η² = 0.803; Confidence: F (2, 18) = 18.321, p < 0.001, partial η² = 0.671; Image: F (2, 18) = 26.567, p < 0.001, partial η² = 0.747). For Materiality and Cooking skill, the active condition showed significantly higher scores than the other two conditions, which did not differ from each other (Materiality: F (2, 18) = 16.930, p < 0.01, partial η² = 0.653; Cooking skill: F (2, 18) = 13.795, p < 0.01, partial η² = 0.605).

5 Discussion

5.1 General discussion

The results of Experiment 1 indicated that V-A stim can convey information about the cooking skills of performers and the quality of the cooking tools used. The participants were able to recognize the differences between the two performers and between the two tools, which suggests the possibility of distinguishing the performers’ unique features (e.g., characteristics of movements and skill level) from the same cooking action. They evaluated the recorded stimuli of the professional chef as being more skilled. Considering the association with waveforms (Figure 2-2; Figures 2-3), the constant rhythm and smoothness of cutting may be perceived as skillfulness and reflecting the quality of the tool. It should also be noted that no significant difference in materiality was observed for cabbage, while a clear effect appeared for welsh onion. This likely reflects differences in food properties: the soft texture of the cabbage generates relatively weak vibrations, whereas the fibrous variation of welsh onion produces richer cues for materiality. Thus, the non-significant result seems to arise from the characteristics of the stimulus rather than from insensitivity of the method. Although visual information has so far been emphasized in the learning of cooking process (e.g., Hamada et al., 2005), the use of vibro-acoustic information may be a potentially effective approach in enhancing motivation of learning cooking skills. These findings are consistent with previous studies showing that haptic cues can provide meaningful information about skill level and material properties in motor tasks (Minogue and Jones, 2006; Sigrist et al., 2013), supporting the role of embodied perception in skill evaluation (Wilson, 2002).

In Experiment 2, higher ratings of confidence and image were observed for both food materials under the active condition. While the participants placed their right palm on the board-type device in the passive condition, they held the knife-type device and moved their right arm in the air under the active condition. Moving hands is related to manipulating an object, and when the movements of hands and the vibration were synchronized, they might have felt as if they were cutting food materials. At the same time, attractiveness and materiality did not show significant differences between conditions, and cooking skill showed only a trend. One possible explanation is that they had already encountered V-A stim in Experiment 1, so the initial sense of novelty and excitement that may have boosted attractiveness ratings was diminished in Experiment 2. These results align with prior research in haptic and motor learning, highlighting that active engagement with tactile stimuli can improve motivational components of self-efficacy even when perceptual novelty is reduced (Sigrist et al., 2013). Taking the results of Experiment 3 into account, it was indicated that both movements of manipulation and vibrotactile sensations in response to the movements are essential for enhancing confidence in cooking skills.

Confidence in one’s own abilities (a part of self-efficacy) is crucial to achieving goals. In the field of education, it has been reported that high self-efficacy increases the motivation to learn (Schunk, 1985). Previous research on writing ability indicated that students’ confidence can influence their writing motivation and performance; for example, students’ English essay scores correlated with their writing self-efficacy (Pajares, 2003). Interestingly, the participants reported confidence in cooking the Hamo used in Experiment 2 and 3, despite the fact that it is a luxury fish, difficult to obtain, not easily prepared, and takes even professional chefs several years or more to master the skill. When considering the difference in food materials, the experience of vibration of a professional chef cooking may encourage some learners to improve their skills, regardless of the type of food material. Overall, these findings suggest that V-A stim may support learners’ motivation and confidence in certain contexts, consistent with theories of embodied cognition and previous work on multimodal feedback in motor learning (Wilson, 2002; Minogue and Jones, 2006; Sigrist et al., 2013).

Several mechanisms may underlie the effects of V-A stim. From the perspective of predictive coding (Friston, 2010), the brain continuously generates predictions about the sensory consequences of one’s actions and updates these predictions based on discrepancies between expected and actual feedback. V-A stim provide learners with vibrotactile cues that help minimize this prediction error, enhancing learners’ task-specific confidence. In addition, when learners observe the rhythmic cutting actions of a chef in the video, their sensorimotor system may mirror these movements as if performing them themselves. From the framework of motor resonance (Gallese and Goldman, 1998; Keysers and Gazzola, 2009), combined with synchronized V-A stim, this embodied resonance allows learners to internalize the characteristics of skilled performance. Consequently, V-A stim feedback paired with active movement may foster learners’ confidence in their cooking skills even in the absence of actual task performance.

5.2 Limitations and future direction

There exist several limitations in the experiments performed in this study, although our results indicated possibilities of V-A stim for enhancing task-specific confidence in cooking skill learning. In this study, the passive condition in Experiment 2 (watching condition in Experiment 3) was always presented first, as it was intended to serve as a baseline for comparison. While this fixed order allowed us to clearly contrast proactive experiences with initial perceptual impressions, it is possible that familiarity or anticipation effects may have influenced their subsequent ratings in the latter condition. Future studies should use counterbalanced or randomized the order of conditions to control for potential biases arising from presentation sequence. Moreover, expanding the sample size and participant diversity would all strengthen the research.

This study primarily examined short-term effects, leaving the long-term impact of V-A stim on skill acquisition unaddressed. It should also be noted that no assessment was conducted to measure changes in learners’ actual performance before and after the learning process. Although the results suggest that proactive experiences of V-A stim can enhance motivation for acquiring cooking skills as an initial step, future research should incorporate objective performance measures to directly evaluate learning outcomes. Nevertheless, despite these limitations, exploring how V-A stim might help lower psychological barriers to learning could provide a promising avenue for future research.

Beyond laboratory settings, the findings of this study may inform the design of interactive learning systems that use V-A stim feedback to enhance engagement and motivation. For instance, VR-based culinary training systems could integrate vibrotactile cues synchronized with cooking actions to help learners develop sensory awareness and task-specific confidence without face-to-face instruction. Similarly, remote rehabilitation contexts where vibro-acoustic feedback can supplement visual cues. Integrating such multisensory feedback could provide learners or patients with a more immersive and motivating experience.

6 Conclusion

This study conducted three experiments as an initial exploratory step, focusing on preliminary investigation rather than on demonstrating performance improvement. Experiment 1 examined the discriminability of V-A stim, demonstrating that the participants were able to recognize the performers’ cooking skill simply by perceiving them. Experiment 2 and 3 investigated the difference in terms of the confidence in cooking skills between passive and proactive experiences of the V-A stim. The results showed that the learner’s confidence in cooking skills can be enhanced by proactively experiencing V-A stim of the professional chef’s cutting, implying that it could enhance motivation related to a particular aspect of cooking skill acquisition.

Data availability statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by Ritsumeikan University (Experiments 1 and 2) and Communication Science Laboratories, NTT, Inc. (Experiment 3). All studies were conducted in accordance with local legislation and institutional requirements. All participants provided written informed consent to participate.

Author contributions

SI: Project administration, Data curation, Formal Analysis, Writing – original draft, Conceptualization, Writing – review and editing, Resources, Investigation. KK: Conceptualization, Methodology; Data curation, Writing – review and editing, Project administration, Resources. YW: Writing – review and editing, Project administration. JW: Conceptualization; Data curation, Writing– review and editing, Project administration, Resources.

Funding

The authors declare that financial support was received for the research and/or publication of this article. Authors SI and YW received research support from NTT, Inc. as a part of a joint research on “Creating New Value through Food Experience x Digital Transformation (DX) (translation from Japanese title)” between NTT, Inc. and Ritsumeikan university (2019-2021). The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

Acknowledgements

The authors would like to thank Chef. Ryuichi Takano, Tomofumi Yoshida, and the All Japan Food Association for their support in preparing the stimuli.

Conflict of interest

Authors KK and JW were employed by Communication Science Laboratories, NTT, Inc.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that Generative AI was used in the creation of this manuscript. This manuscript was edited for English language clarity and fluency using AI-assisted tools, including ChatGPT-5 (OpenAI). This tool was employed solely to assist the authors in language editing. The AI was not used to generate any original research ideas, results, or interpretations.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychol. Rev. 84 (2), 191–215. doi:10.1037/0033-295X.84.2.191

PubMed Abstract | CrossRef Full Text | Google Scholar

Barsalou, L. W. (2008). Grounded cognition. Annu. Rev. Psychol. 59, 617–645. doi:10.1146/annurev.psych.59.103006.093639

PubMed Abstract | CrossRef Full Text | Google Scholar

Daradoumis, T., Puig, J. M. M., Arguedas, M., and Liñan, L. C. (2022). Enhancing students’ beliefs regarding programming self-efficacy and intrinsic value of an online distributed programming environment. J. Comput. High. Educ. 34 (3), 577–607. doi:10.1007/s12528-022-09310-9

CrossRef Full Text | Google Scholar

Friston, K. (2010). The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138. doi:10.1038/nrn2787

PubMed Abstract | CrossRef Full Text | Google Scholar

Gallagher, A. G., Ritter, E. M., Champion, H., Higgins, G., Fried, M. P., Moses, G., et al. (2005). Virtual reality simulation for the operating room: proficiency-based training as a paradigm shift in surgical skills training. Ann. Surg. 241 (2), 364–372. doi:10.1097/01.sla.0000151982.85062.80

PubMed Abstract | CrossRef Full Text | Google Scholar

Gallese, V., and Goldman, A. (1998). Mirror neurons and the simulation theory of mind-reading. Trends Cogn. Sci. 2 (12), 493–501. doi:10.1016/S1364-6613(98)01262-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Hamada, R., Okabe, J., Ide, I., Satoh, S., Sakai, S., and Tanaka, H. (2005). Cooking navi: assistant for daily cooking in kitchen. Proc. 13th ACM Int. Conf. Multimed., 371–374. doi:10.1145/1101149.1101228

CrossRef Full Text | Google Scholar

Juliano, J. M., and Liew, S.-L. (2020). Transfer of motor skill between virtual reality viewed using a head-mounted display and conventional screen environments. J. Neuroeng. Rehabil. 17 (1), 48. doi:10.1186/s12984-020-00678-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Keysers, C., and Gazzola, V. (2009). Expanding the mirror: vicarious activity for actions, emotions, and sensations. Curr. Opin. Neurobiol. 19 (6), 666–671. doi:10.1016/j.conb.2009.10.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Komazaki, K., Inoue, S., Wada, Y., and Watanabe, J. (2023). Contents of cooking vibration -Examination of active and passive experiences. J. Ritsumeikan Gastron. Arts Sci 8, 57–62. doi:10.34382/00018720

CrossRef Full Text | Google Scholar

Lee, K., Kim, J., Park, S., and Choi, H. (2025). “Hapticus: exploring the effects of haptic feedback in piano learning,” in Proceeding 2025 ACM SIGCHI conference on human factors in computing systems, 1–20. doi:10.1145/3706598.3713821

CrossRef Full Text | Google Scholar

Manrique, M., Mondragón, I. F., Flórez-Valencia, L., Montoya, L., García, A., Mera, C. A., et al. (2024). Haptic experience to significantly motivate anatomy learning in medical students. BMC Med. Educ. 24, 946. doi:10.1186/s12909-024-05829-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Minogue, J., and Jones, M. G. (2006). Haptics in education: exploring an untapped sensory modality. Rev. Educ. Res. 76 (3), 317–348. doi:10.3102/00346543076003317

CrossRef Full Text | Google Scholar

Nishida, J., Tanaka, Y., Nith, R., and Lopes, P. (2022). “DigituSync: a dual-user passive exoskeleton glove that adaptively shares hand gestures,” in Proceeding 35th annual ACM symposium on user interface software and technology (UIST), 1–12. doi:10.1145/3526113.3545630

CrossRef Full Text | Google Scholar

Pacheco-Barrios, K., Surname, B., Surname, C., and Surname, D. (2024). Haptic technology: exploring its underexplored clinical applications—A systematic review. Biomedicines 12, 2802. doi:10.3390/biomedicines12122802

PubMed Abstract | CrossRef Full Text | Google Scholar

Pajares, F. (2003). Self-efficacy beliefs, motivation, and achievement in writing: a review of the literature. Read. Writ. Q. 19 (2), 139–158. doi:10.1080/10573560308222

CrossRef Full Text | Google Scholar

Ratschat, A. L., Surname, B., Surname, C., and Surname, D. (2024). Evaluating tactile feedback in addition to kinesthetic feedback during shape reproduction. Front. Virtual Real 5. doi:10.3389/frvir.2024.11039957

CrossRef Full Text | Google Scholar

Sato, A., Watanabe, K., and Rekimoto, J. (2014). “MimiCook: a cooking assistant system with situated guidance,” in Proceeding 8th int. Conf. Tangible embedded embodied interact. (TEI), 121–124. doi:10.1145/2540930.2540952

CrossRef Full Text | Google Scholar

Schunk, D. H. (1985). Self-efficacy and classroom learning. Psychol. Sch. 22 (2), 208–223. doi:10.1002/1520-6807(198504)22:2<208::aid-pits2310220215>3.0.co;2-7

CrossRef Full Text | Google Scholar

Shimizu, H. (2016). An introduction to the statistical free software HAD: suggestions to improve teaching, learning, and practice data analysis. J. Media Inf. Commun. 1, 59–73. Available oneline at: http://hdl.handle.net/11150/10815.

Google Scholar

Shu, Y., Huang, Y.-Z., Chang, S.-H., and Chen, M.-Y. (2019). Do virtual reality head-mounted displays make a difference? A comparison of presence and self-efficacy between head-mounted displays and desktop computer-facilitated virtual environments. Virtual Real 23, 437–446. doi:10.1007/s10055-018-0376-x

CrossRef Full Text | Google Scholar

Sigrist, R., Rauter, G., Riener, R., and Wolf, P. (2013). Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychon. Bull. Rev. 20 (1), 21–53. doi:10.3758/s13423-012-0333-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Surgenor, D., Hollywood, L., Furey, S., Lavelle, F., McGowan, L., Spence, M., et al. (2017). The impact of video technology on learning: a cooking skills experiment. Appetite 114, 306–312. doi:10.1016/j.appet.2017.03.037

PubMed Abstract | CrossRef Full Text | Google Scholar

Sveistrup, H. (2004). Motor rehabilitation using virtual reality. J. Neuroeng. Rehabil. 1, 10. doi:10.1186/1743-0003-1-10

PubMed Abstract | CrossRef Full Text | Google Scholar

Wilson, M. (2002). Six views of embodied cognition. Psychon. Bull. Rev. 9 (4), 625–636. doi:10.3758/BF03196322

PubMed Abstract | CrossRef Full Text | Google Scholar

Wulf, G. (2007). Self-controlled practice enhances motor learning: implications for physiotherapy. Physiotherapy 93 (2), 96–101. doi:10.1016/j.physio.2006.08.005

CrossRef Full Text | Google Scholar

Wulf, G., Shea, C., and Lewthwaite, R. (2010). Motor skill learning and performance: a review of influential factors. Med. Educ. 44 (1), 75–84. doi:10.1111/j.1365-2923.2009.03421.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Yamaguchi, T., Foloppe, D. A., Richard, P., Richard, E., and Allain, P. (2012). A dual-modal virtual reality kitchen for (re) learning of everyday cooking activities in alzheimer's disease. Presence Teleoperators Virtual Environ. 21 (1), 43–57. doi:10.1162/PRES_a_00080

CrossRef Full Text | Google Scholar

Zhang, K., Sharma, M., Veloso, M., and Kroemer, O. (2019). Leveraging multimodal haptic sensory data for robust cutting. Proc. IEEE-RAS 19th Int. Conf. Humanoid Robots (Humanoids), 409–416. doi:10.1109/Humanoids43949.2019.9035073

CrossRef Full Text | Google Scholar