Student Performance Analytics: Key Factors for Academic Success

Data-Driven Insights from 1,000 Students

Nhat Minh Tran

June 11, 2025

Profiling the Struggling Student

This profile represents the median student in the bottom 10% of the class, based on our dataset of 1,000 students.

  • Exam Score: 41.7%
  • Attendance: 84%
  • Study Time: 1.5 hours/day
  • Screen Time: 5.1 hours/day
  • Sleep: 6.3 hours/night

These data points represent common, real-world patterns that correlate with low academic performance.

The #1 Game-Changer: Quality Over Quantity in Study Time

  • Strong Positive Correlation: Study hours show a positive correlation with exam scores (r = 0.825), but with diminishing returns.

  • The Sweet Spot: Study performance starts to reach its peak and maintain its position after approximately 4 hours of daily study. According to Zubair et al. (2024), 4-6 hours of focused daily study is the optimal range.

  • Conclusion: Maximizing performance is not about studying more, but studying smarter. Quality and consistency within the optimal range are more effective than simply logging more hours (Zubair et al, 2024).

The Mind-Performance Connection: Why Mental Health is Your Academic Superpower

  • Remarkable Positive Correlation: Mental health rating witnesses a significant positive correlation with exam scores (r = 0.322).

  • Performance Gap: Students with excellent mental health (rating 8-10) score an average of 13 points higher than those with poor mental health (rating 1-3).

  • Academic Risk Factor: Poor mental health (rating 1-3) affects 30.1% of students in our dataset, representing a significant at-risk population.

  • Conclusion: Mental wellness is not separate from academic success—it’s a fundamental component. Students with better mental health consistently demonstrate higher academic performance (Garces et al., 2024).

The Silent Performance Killer: How Your Phone is Sabotaging Your Success

  • Negative Correlation: Excessive daily screen time (social media + entertainment) records a negative correlation with exam scores (r = -0.238).

  • The Performance Penalty: Students with low screen time (<3 hours/day) score an average of 12.7 points higher than those with high screen time (4+ hours/day).

  • Conclusion: Unmanaged screen time is a significant liability. Setting clear boundaries for digital entertainment is essential for academic focus and success (Rahaman & Saidi, 2024).

The Foundation Factor: Why Simply Showing Up Changes Everything

  • Weak but Consistent Correlation: While the correlation between class attendance and final exam scores is relatively weak (r = 0.09), the practical impact is still meaningful.

  • Practical Impact: Students with high attendance (90%+) score, on average, 3.3 points higher than those with low attendance (<80%), despite the modest statistical correlation.

  • Foundation Building: This finding suggests that attendance acts as a foundational habit rather than a direct performance driver—it enables other success factors to work effectively (Lu & Cutumisu, 2022).

  • Conclusion: While attendance alone won’t guarantee high performance, it creates the necessary foundation for academic success by ensuring students don’t miss crucial information and maintain engagement with course material (Gump, 2010).

The Recovery Factor: How Sleeps Powers Academic Performance

  • Noticeable Correlation: Sleep hours illustrate a positive correlation with exam scores (r = 0.122), highlighting the importance of adequate rest for cognitive function.

  • Performance Gap: Students who get adequate sleep (7+ hours) score an average of 4.6 points higher than those who are sleep-deprived (<6 hours nightly).

  • Conclusion: Sleep isn’t just recovery time—it’s when the brain processes and consolidates learning. Consistent, adequate sleep is a non-negotiable foundation for peak academic performance (Fonseca & Genzel, 2020).

A Blueprint for Transformation: From Low to High Performer

The Transformation Blueprint

Here we compare the median profiles of students from the bottom 10% and the top 10% of the class.

Profile: The Low Performer (Bottom 10%):

  • Exam Score: 41.7%
  • Attendance: 84%
  • Study Hours: 1.5/day
  • Screen Time: 5.1 hours/day
  • Sleep: 6.3 hours/night

Profile: The High Performer (Top 10%):

  • Exam Score: 99.3%
  • Attendance: 86%
  • Study Hours: 5.8/day
  • Screen Time: 3.5 hours/day
  • Sleep: 6.8 hours/night

A Data-Driven Blueprint for Academic Improvement

Academic Improvement Plan | Total Potential Final Score Gain: Up to 69.7 points
Focus Area Target Expected Gain Key Action
Study Time Optimization Find your 4-6 hour daily rhythm of focused study Up to 36.1 points Track daily study hours and rate focus quality
Mental Health & Wellness Maintain good mental health through stress management Up to 13 points Develop healthy coping strategies and social connections
Screen Time Control Cut non-academic screen time to below 3 hours daily Up to 12.7 points Use app timers and create distraction-free study environment
Attendance Habit Achieve 95%+ attendance rate Up to 3.3 points Prepare for every class the night before
Sleep Recovery Maintain 7-8 hours of quality sleep nightly Up to 4.6 points Establish consistent sleep schedule, screen-free bedtime


Concluding Analysis

The data clearly indicates that academic success is not random. It is strongly correlated with controllable habits: balanced study, managed screen time, mental wellness and maintain with circadian rhythm, with attendance serving as an enabling foundation. By focusing on these key areas, students have a clear, data-backed path to significantly improve their performance.

References

  • Fonseca, A. G. & Genzel, L. (2020). Sleep and academic performance: considering amount, quality and timing. Current Opinion in Behavioral Sciences, 33, 65-71. https://doi.org/10.1016/j.cobeha.2019.12.008
  • Garces, N. N., Fajardo, Z. I. E., Villao, M. L. S., Caguana, D. R. M. & Esteves, A. C. Q. (2024). Relationships between Mental Well-being and Academic Performance in University Students: A Systematic Review. Salud, Ciencia Y Tecnología - Serie De Conferencias, 3, 972. https://doi.org/10.56294/sctconf2024972
  • Gump, S. E. (2005). The Cost of Cutting Class: Attendance As A Predictor of Success. College Teaching, 53(1), 21–26. https://doi.org/10.3200/CTCH.53.1.21-26
  • Lu, C. & Cutumisu, M. (2022). Online engagement and performance on formative assessments mediate the relationship between attendance and course performance. International Journal of Educational Technology in Higher Education, 19(2). https://doi.org/10.1186/s41239-021-00307-5
  • Nath, J. (2025). Student Habits and Academic Performance. https://www.kaggle.com/datasets/jayaantanaath/student-habits-vs-academic-performance.
  • Rahaman, N, H. & Saidi, L. A. (2024). EXPLORING THE RELATIONSHIP BETWEEN SCREEN DEPENDENCY DISORDER AND PSYCHOLOGICAL WELL-BEING AMONG ADOLESCENTS: A LITERATURE REVIEW. INTERNATIONAL JOURNAL OF EDUCATION, PSYCHOLOGY AND COUNSELLING (IJEPC), 9(54). https://doi.org/10.35631/ijepc.954017
  • Zubair, T., Qazi, U., Faisal, S. M. & Khan, A. K. (2024). The impact of study hours on academic performance: A statistical analysis of students’ grades. International Journal of Multidisciplinary Research and Growth Evaluation, 5(3), 720-728. https://doi.org/10.54660/.IJMRGE.2024.5.3.720-728