This review evaluates the undergraduate research "Comprehensive Review of the Utilization of QR Codes as Perceived by the College Engineering Students of PUP Main Campus." While the study provides useful descriptive insights into QR code usage, its major statistical conclusions are not supported by sound methodology.
- Surveyed 101 engineering students using a 30-item Likert questionnaire.
- Measured six constructs:
- Information Quality
- System Quality
- Usefulness
- Ease of Use
- Student Behavior
- Student Attitude
- Used descriptive statistics, t-tests, correlation analysis, Cronbach's alpha, and thematic analysis.
The study reports:
- Overall positive perception of QR codes (Mean = 3.956)
- Significant results for all six constructs
- Strong reported correlation between usage frequency and perception
- High reliability (Cronbach's α ≈ 0.88)
- Positive themes highlighting convenience, accessibility, and future applications.
The study contains several methodological flaws that undermine its quantitative conclusions:
- Invalid correlation analysis — computed using only six aggregated data points instead of individual responses.
- Contradictory conclusions — reports a negative correlation while claiming a positive relationship.
- Assumed standard deviations — significance tests are based on estimated rather than actual data.
- Incorrect Cronbach's alpha — reliability was not calculated from item-level responses.
- Inconsistent sample sizes across multiple tables.
- Sampling method mismatch — described as stratified random sampling but executed as convenience sampling.
- Missing calculations and incomplete tables affecting reproducibility.
- Weak referencing and statistical reporting throughout the paper.
- Descriptive statistics
- Student opinions and qualitative themes
- Observations on current and potential QR code applications
- Correlation analysis
- One-sample t-tests
- Reliability (Cronbach's alpha)
- Statistical claims supporting hypothesis testing
The paper is a solid undergraduate survey with useful descriptive findings, but its inferential statistics are methodologically flawed. Its quantitative conclusions should not be treated as statistically validated, while its descriptive and qualitative results remain useful for exploratory research.
- Analyze individual respondent data instead of aggregated values.
- Use actual standard deviations and item-level responses.
- Compute Cronbach's alpha correctly.
- Maintain consistent sample sizes.
- Clearly describe the actual sampling method.
- Improve qualitative coding and references.