Research Article | Vol. 6, Issue 2 | Journal of Dental Health and Oral Research | Open Access DOI : https://doi.org/10.46889/JDHOR.2025.6216

Influence of Learning Modality on Dental Students’ Human View: Face-to-Face Experiential vs Online Learning

Ken-ichi Tonami^1,2*, Sachi Umemori^1,2

¹Department of Oral Health Sciences, School of Health Sciences, Meikai University, Chiba, Japan
²Department of General Dentistry, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan

*Correspondence author: Ken-ichi Tonami DDS, PhD, Professor, Department of Oral Health Sciences, School of Health Sciences, Meikai University, Chiba, Japan and Department of General Dentistry, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan; E-mail: [email protected]

Citation: Tonami K, et al. Influence of Learning Modality on Dental Students’ Human View: Face-to-Face Experiential vs Online Learning. J Dental Health Oral Res. 2025;6(2):1-9.

Copyright^© 2025 by Tonami K, et al. All rights reserved. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Item No.	Belief
1	I always try to respect others.
2	I communicate with others trying to understand them.
3	I understand myself very well.
4	I can have different points of view.
5	I cannot understand others when their logic is different from mine.
6	I can understand others when I have enough knowledge about them.
7	I can change my behavior when I can understand a logical reason for that change.
8	I feel emotion is really meaningful for humans.
9	I consider each human being irreplaceable.
10	I think humans can understand each other.
11	I think humans can change.
12	I think that to understand others means to know their secrets.
13	One needs to know oneself to develop a good relationship with others.
14	I consider myself a human being rather than a medical provider.
15	I can say what I feel to others freely.
16	I can express myself frankly.
17	I am willing to associate with others whose way of thinking is different from mine.
18	I do not associate with people whom I do not like.
19	I can accept my imperfections and my weaknesses.
20	I value my originality.

Table 1: Interpersonal relationship beliefs on the questionnaire.

Ethical Approval           

The present study was approved by the ethical committee of the Faculty of Dentistry, Tokyo Medical and Dental University (D2018-063-01).

Results

Students who did not submit a survey form, as well as those who submitted forms with missing values, were excluded from the analysis. As a result, the number of subjects of each EXL and DLC were 467 and 100, respectively. Cronbach’s alpha values for EXL1, EXL2, DLC1 and DLC2 were 0.717, 0.763, 0.745 and 0.730, respectively.

The results of factor analysis for EXL1 are shown in Table 2. In EXL1, six factors were extracted, accounting for 39.06% of the cumulative variance. Based on the items composing each factor, the following names were assigned in order of factor contribution: Factor 1, Self-Disclosure; Factor 2, Acceptance of Diversity; Factor 3, Beliefs about Self; Factor 4, Understanding People through Knowledge; Factor 5, Beliefs about Humanity in General; and Factor 6, Understanding Others.

The results of the factor analysis for EXL2 are shown in Table 3. In EXL2, five factors were extracted, accounting for 38.49% of the cumulative variance. Of the five factors, Self-Disclosure, Acceptance of Diversity and Understanding People through Knowledge were extracted with the same Item composition as in EXL1. However, Items that composed Beliefs about Self, Beliefs about Humanity in General and Understanding Others in EXL1 were, except for Items 4 and 9, integrated into a single factor, which was designated “Human Esteem” based on its content. Item 3, which was not a part of any factor in EXL1, formed a factor with Items 4 and 9 in EXL2 and this was designated “Self-Reflection”.  The results of the factor analysis for DLC1 are shown in Table 4. In DLC1, six factors were extracted, accounting for 46.77% of the cumulative variance. Comparing the Item composition of each factor with EXL1, factors related to Understanding Others, Acceptance of Diversity and Understanding People through Knowledge were extracted with almost the same Item composition and thus were similarly designated. However, three of the five Items that comprised Beliefs about Self in EXL1 were integrated with two Items from Human Esteem, forming a factor designated “Self-Esteem,” while two Items were integrated with the Self-Disclosure factor in EXL1, forming a factor designated “Self-Affirmation”.

The results of the factor analysis for DLC2 are shown in Table 5. In DLC2, seven factors were extracted, accounting for 50.3% of the cumulative variance, which is an increase in the number of factors compared to DLC1. When examining the Items that comprised each factor, Self-Esteem, Understanding Others, Understanding People through Knowledge and Self-Disclosure were extracted with nearly the same Item composition as in EXL1 or DLC1. A factor similar to Beliefs about Self in EXL1 was also extracted and designated accordingly. In addition, there were factors composed solely of Item 10 or Item 17, respectively. Additionally, three Items that did not participate in any factor were identified, indicating a tendency for the factor structure to be more difficult to extract compared to those in EXL1, EXL2 and DLC1.

Name of the Factor	Item	Loading	Variance Explained (%)
Factor 1 　Self-Disclosure	Item15	0.772	7.16
	Item16	0.748
Factor 2　Acceptance of Diversity	Item 5	0.605	6.96
	Item17	0.644
	Item18	0.499
Factor 3   Beliefs about Self	Item 4	0.422	6.81
	Item13	0.388
	Item14	0.425
	Item19	0.445
	Item20	0.518
Factor 4   Understanding People through Knowledge	Item 6	0.597	6.76
	Item 7	0.8
	Item12	0.401
Factor 5   Beliefs about Humanity in General	Item 8	0.455	6.31
	Item 9	0.525
	Item10	0.588
	Item11	0.353
Factor 6   Understanding Others	Item 1	0.742	5.06
	Item 2	0.492
Item not included in factors	Item 3
Cumulative			39.06

Table 2: The results of the factor analysis for EXL1.

Factor	Item	Loading	Variance Explained (%)
Factor 1   Human Esteem	Item 1	0.464	12.55
	Item 2	0.546
	Item 8	0.653
	Item 9	0.697
	Item10	0.41
	Item13	0.464
	Item14	0.376
	Item20	0.428
Factor 2   Understanding People through Knowledge	Item 6	0.737	6.88
	Item 7	0.628
	Item12	0.442
Factor 3   Self-Disclosure	Item15	0.708	6.87
	Item16	0.747
Factor 4   Acceptance of Diversity	Item 5	0.679	6.19
	Item17	0.49
	Item18	0.495
Factor 5   Self-Reflection	Item 3	0.473	6.00
	Item 4	0.426
	Item19	0.551
Item not included in factors	Item11
Cumulative			38.49

Table 3: The results of the factor analysis for EXL2.

Name of the Factor	Item	Loading	Variance Explained (%)
Factor 1   Self-Esteem	Item14	0.650	9.578
	Item13	0.593
	Item9	0.546
	Item8	0.501
	Item19	0.427
Factor 2　Self-Affirmation	Item15	0.851	9.181
	Item16	0.727
	Item20	0.374
	Item4	0.354
Factor 3   Understanding Others	Item2	0.978	8.801
	Item1	0.582
Factor 4   Acceptance of Diversity	Item18	-0.587	7.304
	Item17	0.577
	Item11	0.381
	Item5	-0.462
Factor 5  Understanding People through Knowledge	Item6	0.889	7.175
	Item7	0.385
	Item3	0.356
Factor 6   Human understanding	Item10	0.844	4.735
Item not included in factors	Item 12
Cumulative			46.770

Table 4: The results of the factor analysis for DLC1.

Name of the Factor	Item	Loading	Variance Explained (%)
Factor 1 　Beliefs about Self	Item04	0.732	8.900
	Item19	0.666
	Item03	0.412
	Item20	0.392
Factor 2　 Self-Esteem	Item13	0.657	8.296
	Item08	0.600
	Item14	0.513
	Item09	0.465
Factor 3  Self-Disclosure	Item15	0.968	7.962
	Item16	0.651
Factor 4   Understanding Others	Item02	0.973	7.060
	Item01	0.483
Factor 5   Understanding People through Knowledge	Item05	0.577	6.931
	Item06	0.628
	Item07	0.647
Factor 6  Acceptance of Diversity	Item17	0.919	6.269
Factor 7  Human understanding	Item10	0.742	4.898
Item not included in factors	Item11
	Item12
	Item18
Cumulative			50.320

Table 5: The results of the factor analysis for DLC2.

Discussion

Experiential learning and subsequent reflection are effective educational strategies for fostering medical professionalism. Experience and reflection are essential components in the processes of abstract conceptualization and subsequent active experimentation [12-16]. Furthermore, it has been reported that experiential learning facilitates the acquisition of tacit knowledge, which is difficult to articulate or teach explicitly [17,18]. At our institution, this experiential learning course is utilized as part of our professionalism education, specifically aimed at cultivating students’ human view. The questionnaire used in this study was originally developed to facilitate students’ self-reflection on human view and has been in use since the course was first introduced in 1994. Thus, the questionnaire was not originally developed for the purpose of the present analysis. Nevertheless, it is considered to have face validity, as the clinical psychologist who conducted the course at the time carefully examined whether the content was consistent with the educational objectives. Furthermore, in the present study, the Cronbach’s alpha was approximately 0.7, indicating acceptable internal consistency. Factor analysis is a statistical method that identifies underlying factors by grouping observed variables based on their intercorrelations. In the present study, factor analysis was employed to examine changes in students’ cognitive frameworks by analyzing shifts in the correlations among questionnaire Item s.　The results revealed the presence of both consistently extracted factors across all survey periods and factors that varied over time. Among the former, the factors of “Self-Disclosure,” “Acceptance of Diversity,” and “Understanding People through Knowledge” were consistently identified before and after the course, as well as before and during the COVID-19 pandemic. This suggests that the course did not lead to changes in the underlying structure of these conceptual domains. In contrast, Items related to beliefs about respect for humanity and understanding of others showed variations in factor structure depending on the timing of the survey, indicating that the meanings conveyed by these factors changed over time. These results suggest that students’ cognitive structures regarding these particular concepts evolved. The following section discusses these changes as reflections of the educational effects of the course. In the factor analysis conducted prior to the course, based on data collected before the COVID-19 pandemic, three distinct factors emerged from Items related to humanity and the understanding of others. These factors reflect differentiated orientations toward the self, others and humanity in general. Following the completion of the course, these three factors were integrated into a single factor, suggesting that the course facilitated a cognitive transformation, leading to a more unified perception of the self, others and human nature. Selman [19,20] defined the capacity to understand and infer the psychological states of oneself and others in social and interpersonal contexts as “social perspective-taking.” According to this framework, social perspective-taking develops in sequential stages, progressing from a subjective viewpoint to second-person, third-person and ultimately to a socially symbolic perspective. Similarly, the observed integration of perspectives in the present study may be interpreted as a reflection of the consolidation of social viewpoints, symbolized by shifts in referential perspective. This finding implies that the experiential learning implemented in the course may have supported the reconstruction of students’ social perspectives, thereby contributing to their professional development. Pagatpatan, et al., emphasized the importance of community-based education, particularly the role of reflection within the affective domain [21]. Reflection is not merely an individual mental process but also a socially situated process [22]. Moreover, reflection can be categorized into two types: “reflection-in-action,” which occurs unconsciously during the experience and “reflection-on-action,” which takes place consciously after the experience has occurred [22-24]. In the pre-COVID-19 curriculum of this course, considerable time was allocated to “reflection-on-action” through SGDs and plenary sessions following experiential activities. This learning strategy, centered on reflection as a social activity, likely contributed to the integration of perspectives. Furthermore, the intentional engagement in “reflection-on-action” may have heightened students’ metacognitive awareness of the reflective process itself, thereby facilitating the development of a cognitive framework for self-reflection. As a result, it is presumed that “Self-Reflection” emerged as a newly identified factor in the post-course analysis.

In contrast to the pre-COVID-19 period, the factor analysis conducted prior to the course during the COVID-19 pandemic did not identify any factors related to an integrated belief in humanity that encompasses multiple perspectives. Instead, factors named Self-Esteem and Self-Affirmation were extracted. Self-esteem and self-affirmation are considered psychological mindsets that contribute to enhanced resilience [25-27]. During the period of social isolation caused by COVID-19, especially among students living alone, reports indicated significant limitations in social connectedness and highly stressful living conditions [28-30]. Under such circumstances, students may have been compelled to adopt cognitive strategies that promoted psychological resilience. Consequently, the emergence of self-esteem and self-affirmation as factors in the COVID-19 period may reflect adaptive coping mechanisms developed in response to the pandemic environment.

In the post-course survey conducted during the COVID-19 pandemic, a greater number of factors were extracted compared to the pre-course survey. Additionally, there was also an increase in the number of Items that did not load onto any factor. This suggests a tendency toward greater divergence in students’ perceptions, rather than the formation of a shared understanding. Previous studies have reported that online learning environments reduce social processes such as interaction with peers and instructors, which can negatively affect learning outcomes [3]. Furthermore, in online settings, social presence plays a critical role in performance; not only cognitive recognition but also emotional engagement is necessary to facilitate meaningful information exchange [31]. In the present study, reflections conducted during the pandemic were based on text-based case analyses rather than real-world social interactions with service users or supervisors in welfare facilities. As a result, the amount of time devoted to “reflection-on-action” was limited and the social presence of both students and instructors was also diminished. It is plausible that these conditions of online learning hindered the development of shared understanding during SGDs, leading to greater variability in students’ cognitive representations. As this course spans several months, students are exposed to various experiences not only through the course content but also in their daily lives. Particularly during the COVID-19 pandemic, informal communication between students and instructors outside of class was severely restricted. The absence of basic interpersonal interactions in everyday life may also have influenced students’ perceptions and learning outcomes. Therefore, the findings of this study should not be interpreted solely as a comparison of instructional strategies, but rather should be understood within the broader socio-contextual framework in which the course was delivered.

The results suggest that the COVID-19 pandemic did more than simply accelerate digital transformation in the educational field-it also highlighted the fundamental importance of social interaction in learning. As we consider educational strategies in the post-COVID-19 era, a key challenge will be how to incorporate social processes into digital learning environments.

Conclusion

Experiential learning in face-to-face settings appears to facilitate the reconstruction of students’ human view by integrating their perceptions of self, others and humanity in general. On the other hand, this cognitive integration was not observed in students attending online classes during the COVID-19 pandemic. Establishing social interaction would be one of the key issues to achieve such perspective integration.

Conflict of Interest

The authors declare that they have no conflicts of interest with the contents of the article.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

Author Contributions

All authors contributed equally for this paper.

Reference

1. Maatuk AM, Elberkawi EK, Aljawarneh S, Rashaideh H, Alharbi H. The COVID-19 pandemic and E-learning: Challenges and opportunities from the perspective of students and instructors. J Comput High Educ. 2022;34(1):21-38.
2. Sandars J, and Patel R. The challenge of online learning for medical education during the COVID-19 pandemic. Int J Med Educ. 2020;11: 169-170.
3. Wut Tm., Xu J. Person-to-person interactions in online classroom settings under the impact of COVID-19: A social presence theory perspective. Asia Pacific Educ. Rev. 2021;22:371-83.
4. Jiang Z, Wu H, Cheng H, et al. Twelve tips for teaching medical students online under COVID-19. Medical Education Online. 2020;26(1) :1854066.
5. Rose S. Medical Student Education in the Time of COVID-19. JAMA. 2020;323 (21):2131-2.
6. Gherheș V, Stoian CE, Fărcașiu MA, Stanici M. E-learning vs Face-to-face learning: Analyzing students’ preferences and behaviors. Sustainability. 2021;13(8):4381.
7. Zheng, M., Bender, D., Lyon, C. Online learning during COVID-19 produced equivalent or better student course performance as compared with pre-pandemic: empirical evidence from a school-wide comparative study. BMC Med Educ. 2021;21:495.
8. Singh J, Steele K, Singh L. Combining the best of online and face-to-face learning: hybrid and blended learning approach for covid-19, post vaccine and post-pandemic world. Journal of Educational Technology Systems. 2021;50(2):140-71.
9. Rapanta C, Botturi L, Goodyear P. Online university teaching during and after the COVID-19 crisis: refocusing teacher presence and learning activity. Postdigit Sci Educ. 2020;2:923-45.
10. Adedoyin OB, Soykan E. COVID-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments. 2020;31(2):863-75.
11. Torda A, Shulruf B. It’s what you do, not the way you do it – online versus face-to-face small group teaching in first year medical school. BMC Med Educ. 2021;21:541.　
12. Kaufman DM. Teaching and learning in medical education. In: Swanwic T, Forrest K, O’Brien BC, editor. Understanding medical education: evidence, theory, and practice. Third Edition. New Jersey: Willy. 2018;37-69.
13. Kolb AY, Kolb DA. Experiential learning theory as a guide for experiential educators in higher education. Experiential Learning and Teaching In Higher Education. 2022;1(1):38.
14. Yardley S. Teunissen PW, Dornan T. Experiential learning: Transforming theory into practice. Medical Teacher. 2012;34(2):161-4.
15. Mann KV. Theoretical perspectives in medical education: past experience and future possibilities. Medical Education. 2011;45:60-8.
16. Principles for designing a program for the teaching and learning of professionalism at the undergraduate level. In: Cruess RL, Cruess SR, Steinert Y. Teaching medical professionalism. New York: Cambridge University Press. 2009;73-92.
17. Armstrong SJ, Mahmud A. Experiential learning and the acquisition of managerial tacit knowledge. Academy of Management Learning and Education. 2008;7(2):189-208.
18. Matthew CT, Sternberg RJ, Developing experience-based (tacit) knowledge through reflection. Learning and Individual Differences. 2009;19(4):530-40.
19. Selman RL. Taking another’s perspective: Role-taking development in early childhood. Child Development. 1971;42(6):1721-34.
20. Selman RL, ByrneDF. A structural-developmental analysis of levels of role-taking in middle childhood. In: The life cycle: Readings In Human Development, New York Chichester. West Sussex: Columbia University Press. 1981;96-104.
21. Pagatpatan CP Jr, Valdezco JAT, Lauron JDC. Teaching the affective domain in community-based medical education: A scoping review. Med Teach. 2020;42(5):507-14.
22. Kemmis D. Action Research and the Politics of Reflection. In: Boud D, Keogh R, Walker D, editor. Reflection: Turning experience into learning. Nichols Publishing Company. 1985;139-63.
23. Schön DA. The Reflective Practitioner: How professionals think in action. London: Routledge. 1992.
24. Hewson MG. Reflection in clinical teaching: An analysis of reflection-on-action and its implications for staffing residents. Med Teach. 1991;13(3):227-31.
25. Traş Z, Arslan C, Hamarta E. An examination of resilience in university students in terms of self-esteem and social self-efficacy. Int J Approximate Reasoning. 2013;5:325-30.
26. Herrman H, Stewart DE, Diaz-Granados N, Berger EL, Jackson B, Yuen T. What is resilience? The Canadian J Psychiatry. 2011;56(5):258-65.
27. Davydov DM, Stewart R, Ritchie K, Chaudieu I, Resilience and mental health. Clinical Psychology Review. 2010;30(5):479-95.
28. Ihm L, Zhang H, Vijfeijken A, Waugh MG. Impacts of the COVID-19 pandemic on the health of university students. Int J Health Plann Mgmt. 2021;36:618-27.
29. Korneeva E, Strielkowski W, Krayneva R, Sherstobitova A. social health and psychological safety of students involved in online education during the COVID-19 pandemic. Int J Environmental Research and Public Health. 2022;19(21):13928.
30. Riboldi I, Capogrosso CA, Piacenti S. Mental health and COVID-19 in university students: Findings from a qualitative, comparative study in Italy and the UK. Int J Environmental Research and Public Health. 2023;20(5):4071.
31. Shen KN, Yu AY, Khalifa K. Knowledge contribution in virtual communities: Accounting for multiple dimensions of social presence through social identity. Behaviour and Information Technology. 2010;29(4):337-48.