ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025
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Comparative Study of Conventional and App- and Video-Based
Learning in Medical Education
*Devalraju Ravisankar1, Sridevi Vishnumolakala2
1Medinirai Medical College and Hospital, Department of Biochemistry, Medininagar, Palamu,
Jhakhand, India Pin-822102
2Vananchal Dental College and Hospital, Garhwa, Jharkhand
Corresponding Author*
ABSTRACT
This study compares the effectiveness of conventional lecture-based teaching with app- and video-based learning
methods in Biochemistry education for first-year MBBS students. Sixty students were randomly assigned into
two groups: Conventional Learning Group (CLG) and App- and Video-Based Learning Group (AVLG).
Knowledge acquisition was assessed through pre-tests, post-tests, and delayed retention tests. Results revealed
significant improvements within both groups, with no major statistical differences overall, though conventional
methods showed slight superiority in one topic. Student feedback highlighted the flexibility and visual clarity of
digital tools, alongside the structured guidance of classroom teaching. The findings support a blended approach
that integrates digital resources with traditional pedagogy to optimize engagement, retention, and performance.
Key words: Medical education, Biochemistry, Conventional teaching, App-based learning, Video-based
learning, MBBS curriculum, Knowledge retention, Student engagement
INTRODUCTION
Medical education is currently undergoing a significant transformation, primarily driven by the increasing
integration of digital technologies into the teaching-learning process. Historically, Conventional Didactic
Lectures (CDL), delivered via traditional chalk-and-talk methods or PowerPoint presentations, have served as
the foundational mode of instruction in medical colleges. While CDL methods are highly effective for delivering
structured content, they often struggle to provide the necessary interactivity and adaptability required to cater to
the diverse learning styles and varied attention spans of contemporary students.
To address these recognized limitations, App- and Video-Based Learning (AVL) platforms have emerged as
increasingly prominent alternatives. These digital resources provide students with mobile access to a rich array
of educational materials, including concept-based videos, interactive quizzes, animations, and other multimedia
elements. This learner-centred approach is widely acknowledged for fostering self-directed learning, improving
conceptual clarity, and enhancing visual and kinaesthetic engagement, particularly in complex subjects such as
Biochemistry. Studies have shown that e-learning can lead to statistically significant improvements in learning
outcomes compared to traditional methods , and research indicates that video-based teaching can be at least as
effective as traditional lectures, often resulting in positive impacts on student motivation and concentration.
This study adopted a prospective cohort design to comprehensively compare the effectiveness of these two
teaching modalities: conventional learning versus app- and video-based learning, specifically within the subject
of Biochemistry. The evaluation encompassed assessments of academic performance, knowledge retention,
student engagement, and overall learning satisfaction. The core goal of this research is to provide valuable,
evidence-based insights for curriculum planners, guiding them on the most effective strategies for integrating
digital tools alongside traditional pedagogical methods in undergraduate medical education.
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025
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Materials and Methods
Study Design and Setting This was a prospective cohort study conducted over a 14-week intervention period
in 2025. The study focused on first-year MBBS students from the 2024-2025 academic batch.
Participants and Randomization A total of 60 first-year MBBS students who consented to participate were
selected from the 100 enrolled students. Participants were allocated into two equal groups (n=30 each) using a
chit-based random allocation method to ensure unbiased group formation and enhance internal validity.
Study Groups and Intervention Participants were assigned to one of two groups:
1. Conventional Learning Group (CLG): Students were taught using traditional classroom methods,
including the standard curriculum lectures delivered via blackboard and PowerPoint presentations.
Their supplementary learning resource was the textbook Textbook of Biochemistry by DM Vasudavan
and MD. Rafi.
2. App- and Video-Based Learning Group (AVLG): Students received the identical standard curriculum
lectures (blackboard/PPT) as the CLG. However, their supplementary resources included access to a
mobile learning application (Marrow app) and concept-oriented Dr Rajesh Kawaduji Jambulkar
YouTube videos, which provided interactive and multimedia content.
Teaching Content and Duration The intervention lasted for 14 weeks. Both groups received structured
teaching on identical core topics in Biochemistry. The topics included: Carbohydrates, Proteins, Lipids,
Enzymes, and Vitamins & Minerals.
Assessment Strategy A validated set of 25 Multiple-Choice Questions (MCQs) was used for all knowledge
assessments, which were conducted via Google Forms.
1. Pre-Test (Formative): An unannounced spot test conducted to measure the immediate recall and
comprehension of topics recently covered.
2. Post-Test (Summative): A pre-planned, formal assessment conducted after structured study hours to
measure consolidated understanding and overall mastery.
3. Retention Test: A delayed post-test (25 MCQs) was conducted six weeks after the intervention to
evaluate long-term knowledge retention.
Engagement and Satisfaction Survey A structured assessment was conducted using a Likert-scale
questionnaire and an open-ended feedback survey to collect data on motivation, interest, usability of digital
tools, and satisfaction.
Data Collection and Statistical Analysis Quantitative data was processed using SPSS software (version 17).
Statistical tests included:
• Paired t-test: To compare pre- and post-intervention scores within each group.
• Independent t-test: To compare mean scores between the CLG and AVLG at each assessment point.
• ANOVA: To evaluate changes across retention test scores. The level of significance was set at p < 0.05.
Qualitative open-ended responses underwent thematic analysis.
Ethical Considerations Prior to commencing the research, approval was obtained from the Institutional Ethics
Committee (IEC). Written informed consent was secured from all participants, and the confidentiality of all
student data was strictly maintained.
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OBSERVATION AND RESULTS
Baseline Findings A baseline survey revealed that students were technologically well-equipped, with 95%
having access to smartphones/laptops and 60% using educational apps. Regarding preference, 50% favored
lecture-based methods.
Knowledge Acquisition Statistical analysis demonstrated that both the CLG and AVLG achieved statistically
significant improvements in their mean scores from the pre-test to the post-test, indicating effective learning
within both groups.
The independent t-test comparing the two groups' performance showed that the overall differences in mean
scores were generally not statistically significant (p-values ranged from 0.111 to 0.756). This suggests that
both conventional and app-based learning were equally effective in immediate learning outcomes.
However, one paired sample analysis showed a significant decrease in the CLG mean score from 22.73 (pre) to
20.83 (post) in the first test (p = 0.005), while the AVLG mean score non-significantly increased from 22.23
(pre) to 21.47 (post) (p = 0.243).
Group
N
Mean
Std.
Deviation
Std. Error
Mean
P value
1
PreS1
CGL
30
22.73
2.449
.447
0.461
AVL
30
22.23
2.763
.504
2
PostS1
CGL
30
20.83
2.601
.475
0.303
AVL
30
21.47
2.097
.383
3
PreS2
CGL
30
19.47
3.471
.634
0.121
AVL
30
20.83
3.249
.593
4
PostS2
CGL
30
17.57
2.967
.542
0.316
AVL
30
18.33
2.905
.530
5
PreS3
CGL
30
19.20
2.058
.376
0.665
AVL
30
18.97
2.092
.382
6
PostS3
CGL
30
19.60
2.908
.531
0.756
AVL
30
19.37
2.883
.526
7
PreS4
CGL
30
19.27
1.530
.279
0.146
AVL
30
18.53
2.255
.412
8
PostS4
CGL
30
20.93
2.449
.447
0.443
AVL
30
20.40
2.884
.527
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025
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9
PreS5
CGL
30
20.07
3.205
.585
0.137
AVL
30
21.23
2.775
.507
10
PostS5
CGL
30
23.17
1.967
.359
0.111
AVL
30
22.03
3.296
.602
11
DRT
CGL
30
18.83
3.514
.642
0.295
AVL
30
19.73
3.073
.561
Test
Comparison
F-statistic
p-value
Significance
Pretest-1
Conventional vs. App & Video (One-
Way ANOVA)
0.28
0.598
No
22.73 22.23 20.83 21.47 19.47 20.83
17.57 18.33 19.2 18.97 19.6 19.37 19.27 18.53
20.93 20.4 20.07 21.23 23.17 22.03
18.83
19.73
0
5
10
15
20
25
CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL CGL AVL
PreS1 PostS1 PreS2 PostS2 PreS3 PostS3 PreS4 PostS4 PreS5 PostS5 DRT
1 2 3 4 5 6 7 8 9 10 11
Group Independent Statistics (CGL vs AVL) Mean
22.73
20.83 22.23 21.47
19.47
17.57
20.83
18.33 19.2 19.6 18.97 19.37 19.27 20.93
18.53
20.4 20.07
23.17
21.23
22.03
0
5
10
15
20
25
PreCGLS1
PostCGLS1
PreAVLS1
PostAVLS1
PreCGLS2
PostCGLS2
PreAVLS2
PostAVLS2
PreCGLS3
PostCGLS3
PreAVLS3
PostAVLS3
PreCGLS4
PostCGLS4
PreAVLS4
PostAVLS4
PreCGLS5
PostCGLS5
PreAVLS5
PostAVLS5
1 2 3 4 5 6 7 8 9 10
Paired Samples Statistics (Comparison between Pre & Post) Mean
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025
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Post test -1
Conventional vs. App & Video (One-
Way ANOVA)
0.71
0.404
No
Pretest-2
Conventional vs. App & Video (One-
Way ANOVA)
2.34
0.130
No
Post test -2
Conventional vs. App & Video (One-
Way ANOVA)
0.81
0.372
No
Pretest -3
Conventional vs. App & Video (One-
Way ANOVA)
0.00
0.952
No
Post test-3
Conventional vs. App & Video (One-
Way ANOVA)
0.14
0.710
No
Pretest-4
Conventional vs. App & Video (One-
Way ANOVA)
0.66
0.420
No
Post test-4
Conventional vs. App & Video (One-
Way ANOVA)
1.30
0.259
No
Pretest-5
Conventional vs. App & Video (One-
Way ANOVA)
1.99
0.163
No
Post test-5
Conventional vs. App & Video (One-
Way ANOVA)
3.10
0.084
No
Retention
Test
Conventional vs. App & Video (One-
Way ANOVA)
0.98
0.326
No
Knowledge Retention In the delayed retention test conducted six weeks post-intervention, the mean scores were
18.83 for the CLG and 19.73 for the AVLG. While the Conventional group experienced a greater drop than the
App & Video group, their final retention scores remained statistically comparable, with a p-value of 0.295.
This finding further supports the conclusion that both methods achieved equivalent long-term knowledge
retention.
Engagement and Satisfaction The satisfaction surveys indicated:
• Students highly appreciated the use of digital tools, specifically citing the flexibility and visual clarity
that app- and video-based content provided.
• Students still placed high value on the elements of structured classroom interaction and instructor
guidance provided by the conventional teaching model.
• A majority (27 out of 30) of students Strongly Agreed or Agreed that a blended learning model is
ideal for medical education.
DISCUSSION
The core finding that the academic performance and knowledge retention outcomes were statistically
comparable between the conventional and digital methods is consistent with existing medical education
literature. This confirms that digital learning is not inferior to, and can be considered an equivalent alternative
to, traditional teaching. For instance, previous research found video-based teaching to be as effective as standard
lectures.
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025
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The qualitative data highlighted that students valued both the visual superiority and flexibility of audio-visual
content (which can lead to up to 95% recall compared to 10% for text) and the structure provided by traditional
teaching. The comparable outcomes coupled with the high student preference for a combined approach strongly
advocates for a blended learning model to optimize the educational experience.
CONCLUSIONS
Both conventional and app- and video-based teaching methods are effective in improving short-term knowledge
acquisition and achieving comparable long-term retention in first-year MBBS students. The study strongly
recommends a blended learning approach that strategically integrates the strengths of both modalities—
leveraging the visual clarity and flexibility of digital tools while preserving the critical role of instructor-led,
structured classroom interaction—thereby optimizing student engagement, learning outcomes, and knowledge
retention in medical education.
Conflicts of Interest The authors declare no conflicts of interest.
Ethical Approval Ethical approval for this study was obtained from the Institutional Ethics Committee (IEC)
prior to the commencement of the research.
ACKNOWLEDGMENTS
I would like to express my sincere gratitude to everyone who supported and guided me throughout this project.
My deepest thanks go to Dr. Vimala Venkatesh, Acme Coordinator at KGMU, for her invaluable assistance and
coordination. I am profoundly grateful to my guide, Dr. Anita Rani, and co-guide, Dr. Pooja Ramakant, for
their continuous encouragement, expert guidance, and unwavering support; their insights were instrumental in
shaping this research. I also extend my appreciation to Dr. P.N. Mahto, the Principal of my college, and Dr.
Arvind Kumar, Head of my department, for providing the necessary resources, and a special thank you to Dr.
D.K. Jha, my Medical Education Unit Coordinator, for his support. Finally, I am thankful for the cooperation
and enthusiasm of all the staff members of my department and my beloved students of the 1st MBBS Professional
batch (2024-25), who made this project a truly enriching experience.
REFERENCES
1. Kazi RNA, El-Kashif MML, Kolhar M. A comparative study of learning outcomes between video-
based and traditional lecture-based teaching in physiology. Bangladesh J Med Sci. 2021;20(4):833–9.
2. Nikopoulou-Smyrni P, Nikopoulos CK. Evaluating the impact of video-based versus traditional lectures
on student learning. Educ Res. 2010;1(8):304–11.
3. Sharma AK, Sharma HR, Choudhary U. E-Learning Versus Traditional Teaching in Medical Education:
A Comparative Study. JK Sci. 2020;22(3):137–40.
4. Ellaway R, Masters K. AMEE Guide 32: e-Learning in medical education Part 1: Learning, teaching
and assessment. Med Teach. 2008;30(5):455–73.
5. Clarke AA, Somerset L, Parker OG. Assessing the effect of video-based versus traditional lectures on
student education. Int J Educ Res Rev. 2015;3(6):366–72.
6. Choi HJ, Johnson SD. The effect of problem-based video instruction on learner satisfaction,
comprehension and retention in college courses. Br J Educ Technol. 2007;38(5):885–95.
7. UKEssays. Traditional versus modern methods of effective teaching. 2018 [cited 2025 Jun 28].
Available from: https://www.ukessays.com/essays/education/traditional-versus-modern-methods-of-
effective-teaching-education-essay.php?vref=1.
8. El-Seoud SA, Taj-Eddin IM, Seddiek NA, Halfa IA, Riad AM. E-Learning and Students’ Motivation:
A Research Study on the Effect of E-Learning on Higher Education. Int J Learn Technol.
2014;9(2):166–93.
9. Almarzooq ZI, Mohammed FI, Alamin AA. Does blended learning improve students’ performance in
medical education? A systematic review. J Med Educ Curric Dev. 2018;5:2382120518774775.
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025
Page 1346
www.rsisinternational.org
10. Shrivastava N, Chaurasia N. Comparative study of video-assisted teaching versus traditional teaching
methods in undergraduate medical students. Int J Med Sci Public Health. 2017;6(2):401–5.
11. Setia S. Methodology in medical research: basic principles. Indian J Dermatol Venereol Leprol.
2016;82(5):590–5.
12. Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: updated guidelines for reporting parallel
group randomised trials. BMJ. 2010;340:c332.
13. Taherian F, Zallmi T, Moattari M. The effect of electronic learning on medical students’ achievement
and satisfaction in medical education. J Adv Med Educ Prof. 2019;7(3):154–9.
14. Al-Harbi AM. The effect of E-Learning on students’ achievement and attitudes in medical education. J
Educ Pract. 2018;9(25):113–8.
15. Rao M. Educational Evaluation and Measurement. New Delhi: APH Publishing Corporation; 2000.
16. Sriram R. Likert scale in medical education research. Indian J Community Med. 2020;45(1):153–5.
17. Creswell JW. Research design: qualitative, quantitative, and mixed methods approaches. 4th ed.
Thousand Oaks: Sage Publications; 2014.
18. Field A. Discovering statistics using IBM SPSS statistics. 5th ed. Thousand Oaks: Sage Publications;
2018.
19. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.
20. World Medical Association. World Medical Association Declaration of Helsinki: Ethical Principles for
Medical Research Involving Human Subjects. JAMA. 2013;310(20):2191–4.
21. Roy S, Kumar N, Singh V, Samaiya D, Sachan AK. Short- and Long-Term Retentivity of Knowledge
by Various Teaching Methods in Medical Education and Perception of Students Towards Them: A
Comparative Study in a Medical University Hospital of Northern India. Cureus. 2023;15(10):e48043.
doi:10.7759/cureus.48043.
22. Zhang W, Wei J, Guo W, Wang Z, Chen S. Comparing the effects of team-based and problem-based
learning strategies in medical education: a systematic review. BMC Med Educ. 2024;24(1):172.
doi:10.1186/s12909-024-05107-9.
23. Chandran VP, Balakrishnan A, Rashid M, Kulyadi GP, Khan S, Devi ES, Thunga G. Mobile
applications in medical education: A systematic review and meta-analysis. PLoS One.
2024;19(1):e0294726. doi:10.1371/journal.pone.0294726.
24. Munjal A, Gupta N. Comparative study of video-assisted teaching versus traditional lecture-based
teaching in undergraduate medical students. Int J Med Res Rev. 2019;7(4):259–64.
25. Munjal A, Gupta N. Comparative study of video-assisted teaching versus traditional lecture-based
teaching in undergraduate medical students. Int J Med Res Rev. 2019;7(4):259–64.
