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: yocarini@essb.eur.nl