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Record W4414497345 · doi:10.2196/74383

The Effectiveness of Live and Prerecorded Video Demonstrations in Teaching Restorative Dentistry to Undergraduate Students: Cohort Study

2025· article· en· W4414497345 on OpenAlexvenueno aff
Rana Alkattan, Lulwah Alreshaid

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsRestorative dentistryCohort studyBlended learningCohortTeaching method

Abstract

fetched live from OpenAlex

Background: Mastering complex psychomotor skills is essential in undergraduate dental education; however, traditional live demonstrations (LDs) face limitations such as high instructor-to-student ratios and restricted viewing angles. Prerecorded video demonstrations (VDs) offer scalable, repeatable instructions and the ability to integrate multimedia cues but may lack real-time interaction and immediate feedback. There is limited evidence comparing these teaching modalities, particularly regarding gender differences, in the acquisition of restorative dentistry skills. Objective: This study aimed to (1) compare first-year dental students' knowledge acquisition and procedural performance following a LD versus a prerecorded VD of a class II amalgam restoration and (2) evaluate whether gender influences outcomes within each demonstration method. Methods: A total of 51 students enrolled in an Introduction to Operative Dentistry course (2024-2025) participated in this cohort study. The students were randomized into 2 groups: LD (26/51, 51%) or VD (25/51, 49%). Both groups received identical lectures and demonstrations of a standardized class II cavity preparation and amalgam restoration. Knowledge was assessed via preprocedural and postprocedural multiple-choice questionnaires, and the procedural performance was graded by 2 blinded raters using a 10-point rubric. Student perceptions were measured with an 8-item Likert survey. Mixed ANOVA and independent and paired 2-tailed t tests evaluated between-group and within-group differences, while gender analyses used factorial ANOVA. Interrater reliability (interclass correlation coefficient=0.991) was confirmed. Results: The baseline knowledge scores did not differ between the 2 groups. After the demonstration, knowledge was significantly higher with LD (mean 71.22, SD 17.3) than VD (mean 58.4, SD 21.7; P=.02; Cohen d=0.65). The LD method demonstrated significant within-group improvement (P<.001; Cohen d=0.83). Procedural grading favored LD (mean 8.3, SD 0.9 vs mean 7.9, SD 1.0); however, results were not statistically significant (P=.08; Cohen d=0.50). No significant differences were found in the student perception survey. Gender analysis revealed that male students in the LD group achieved higher postknowledge scores (mean 74.0, SD 12.3 vs mean 55.0, SD 24.3; P=.03), greater score improvements (P=.03), and higher grading scores (mean 8.5, SD 0.6 vs mean 7.6, SD 1.3; P=.03) compared to those in the VD group. No significant differences were observed among female students. Conclusions: LDs yielded superior knowledge acquisition and better performance compared to VDs, particularly for male students. VDs remain a viable alternative when supplemented with interactive elements and instructor feedback. Blended teaching models integrating live and video methods may optimize the demonstration experience for the students, thus enhancing the learning outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.474
Teacher spread0.439 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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