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Exploring students’ study time allocation Iris Yocarini Joran Jongerling Samantha Bouwmeester
Studying students’ strategic study behavior
Study time allocation and academic performance
Mixed results: Study time allocation and
academic performance
Mixed results: Study time allocation and
academic performance
Explaining the mixed results
Measuring study time allocation Two approaches 1. Self-reports 2. Diary studies
Explaining the mixed results
Measuring study time allocation Two approaches 1. Self-reports 2. Diary studies 2 Challenges 1. Degree of retrospection 2. Demands put on participants
Balancing two challenges: using an EMA approach
Other explanations
• Operationalization of study time • Formal study time • Self study time
Other explanations
• Operationalization of study time • Formal study time • Self study time
• Quality of students’ study time • Effort • Self-efficacy (related to control of time and task persistence)
Other explanations
• Operationalization of study time • Formal study time • Self study time
• Quality of students’ study time • Effort • Self-efficacy (related to control of time and task persistence)
• Additional control variables • Stress
Design - sample
• 57 students • Introduction to Psychometrics course
Design
Design
Design
‘Since the last measurement, how much time did you spent on self study/ formal study?’
‘How do you rate the quality of this study time?’
Design
‘Since the last measurement, how much time did you spent on self study/ formal study?’
‘How do you rate the quality of this study time?’
‘How interesting did you think the studied material was?’
‘How useful did you think the studied material was?’
‘How much stress did you experience today?’
‘How much confidence do you have that you will grasp the studied material from the self/ formal study of today?’
Results
Results
Results
Variable Mean Min Max Grade 5.53 1.2 9.1 Time SS 1.85 hours 1.03 3.70 Time FS 2.03 hours 1.13 2.83 Qual SS 4.26 2.73 5.75 Qual FS 3.56 2.00 4.79 Self-efficacy 5.04 3.1 7.0 Motivation 4.10 1.73 5.82 Stress 3.46 1.0 6.27
Network
Network – edge-weight accuracy
Network
Network - Bayesian Glasso
Network - Bayesian Glasso
Node Strength Closeness Betweenness Total SS time 0.32 [-0.11; 0.80] 0 [-0.01; 0.01 ] 0 [-1.76; 12.24] Total FS time 0.32 [-0.08; 0.83] 0 [-0.01; 0.01] 0 [-0.50; 11.50] Grade 0.28 [-0.07; 0.76] 0 [-0.01; 0.01] 0 [0; 8] Quality SS 0.53 [0.12; 0.96] 0 [-0.01; 0.01] 0 [-1.59; 12.41] Qualtiy FS 0.47 [0.10; 0.92] 0 [-0.01; 0.01] 0 [-0.42; 11.58] Motivation 0.75 [0.31; 1.27] 0 [-0.01; 0.01] 12 [7.88; 23.88] Self-efficacy 0.81 [0.40; 1.28] 0 [-0.01; 0.01] 14 [7.18; 27.18] Stress 0.31 [-0.08; 0.87] 0 [-0.01; 0.01] 0 [0; 10]
Conclusion
• As a tool EMA using a mobile phone app is an adequate method to measure students’ study time investment
• SE seems most important
• Bayesian Glasso: imputation & accuracy small sample
Future directions
• Additional data collection
• Application of longitudinal network analysis using future Joran’s package BayesGGM
Question? Mail me: [email protected]
