Psychology Study Guide on Caffeine’s Effects on
Student Academic Performance
Study Overview
Research Focus: Effects of caffeine consumption on university students' academic performance
Date: December 2017, University of Ottawa Sample: 50 students (25 male, 25 female, ages 18-
23)
I. Research Framework
Research Questions
1. Sleep Patterns: Does caffeine consumption affect students' sleeping patterns (hours of
sleep, sleep quality)?
2. Performance: Does the number of caffeinated beverages consumed daily influence
concentration and productivity in courses?
3. Gender Differences: Are there differences in caffeine dependency levels between males
and females?
Hypotheses
1. H1: Caffeine will have multiple negative effects on students' sleeping patterns
2. H2: Consuming more than one caffeinated beverage will enhance students' productivity
and concentration in class
3. H3: No significant difference between sexes in caffeine dependency and withdrawal
symptoms
II. Methodology
Study Design
• Sampling Method: Random sampling
• Data Collection: 4-part online survey with consent form
• Exclusion Criteria: Personal knowledge of researcher, non-caffeine consumers
Measurement Scales
, • Parts 1-2: Nominal scales (demographic and consumption patterns)
• Parts 3-4: Interval scales (motivation/sleep and dependency measures)
Statistical Analysis Tools
• Correlations
• Chi-square tests
• T-tests
• Hierarchical regressions
• SPSS software
III. Key Variables
Independent Variables
• Caffeine consumption (dichotomous: yes/no)
• Number of caffeinated beverages per day (continuous)
• Gender (nominal/dichotomous)
Dependent Variables
• Sleep patterns (dichotomous: positive/negative effects)
• Hours of sleep per night (continuous)
• Concentration and productivity (continuous)
• Dependency levels (continuous)
IV. Major Findings
Sleep Effects
• Result: No significant associations found
• Statistics:
o Daily consumption vs. sleep schedule: χ²(1) = 8, p = .841
o Daily consumption vs. hours slept: χ²(1) = 11.55, p = .240
• Notable: 30% of participants slept less after consuming 1+ caffeinated beverages
• Average: 55% of participants sleep 5-7 hours nightly
Performance & Motivation
• Significant Positive Correlations Found:
o More coffee consumption → better academic marks: r = .646, p = .02
Student Academic Performance
Study Overview
Research Focus: Effects of caffeine consumption on university students' academic performance
Date: December 2017, University of Ottawa Sample: 50 students (25 male, 25 female, ages 18-
23)
I. Research Framework
Research Questions
1. Sleep Patterns: Does caffeine consumption affect students' sleeping patterns (hours of
sleep, sleep quality)?
2. Performance: Does the number of caffeinated beverages consumed daily influence
concentration and productivity in courses?
3. Gender Differences: Are there differences in caffeine dependency levels between males
and females?
Hypotheses
1. H1: Caffeine will have multiple negative effects on students' sleeping patterns
2. H2: Consuming more than one caffeinated beverage will enhance students' productivity
and concentration in class
3. H3: No significant difference between sexes in caffeine dependency and withdrawal
symptoms
II. Methodology
Study Design
• Sampling Method: Random sampling
• Data Collection: 4-part online survey with consent form
• Exclusion Criteria: Personal knowledge of researcher, non-caffeine consumers
Measurement Scales
, • Parts 1-2: Nominal scales (demographic and consumption patterns)
• Parts 3-4: Interval scales (motivation/sleep and dependency measures)
Statistical Analysis Tools
• Correlations
• Chi-square tests
• T-tests
• Hierarchical regressions
• SPSS software
III. Key Variables
Independent Variables
• Caffeine consumption (dichotomous: yes/no)
• Number of caffeinated beverages per day (continuous)
• Gender (nominal/dichotomous)
Dependent Variables
• Sleep patterns (dichotomous: positive/negative effects)
• Hours of sleep per night (continuous)
• Concentration and productivity (continuous)
• Dependency levels (continuous)
IV. Major Findings
Sleep Effects
• Result: No significant associations found
• Statistics:
o Daily consumption vs. sleep schedule: χ²(1) = 8, p = .841
o Daily consumption vs. hours slept: χ²(1) = 11.55, p = .240
• Notable: 30% of participants slept less after consuming 1+ caffeinated beverages
• Average: 55% of participants sleep 5-7 hours nightly
Performance & Motivation
• Significant Positive Correlations Found:
o More coffee consumption → better academic marks: r = .646, p = .02
