2021
DOI: 10.1177/07342829211034252
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Factor Structure and Measurement Invariance of the Academic Time Management and Procrastination Measure

Abstract: Students’ ability to effectively allocate time toward educational tasks and reduction of maladaptive behaviors such as procrastination are important predictors of successful educational outcomes. The Academic Time Management and Procrastination Measure (ATMPM) purports to measure the extent to which students engage in such behaviors; however, the psychometric properties of the ATMPM have only been explored with exploratory techniques. In addition, the extent to which measurement invariance is supported among f… Show more

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Cited by 6 publications
(2 citation statements)
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“…This has been the primary focus and application of Bayesian methods in education thus far. Indeed, most studies employing Bayesian methods have used them to perform psychometric and factor analyses of novel assessment types (e.g., multi-skill itemized activities and question types) and surveys to study student comprehension, cognition, and attitudes toward learning (Desmarais and Gagnon, 2006;Pardos et al, 2008;Brassil and Couch, 2019;Martinez, 2021;Parkin and Wang, 2021;Vaziri et al, 2021;Wang et al, 2021). The insights obtained from these studies have led to the design, development, and deployment of more adaptive learning and student-focused knowledge assessment content, based on their aptitude levels, allowing educators to learn more about student comprehension and how individualized content can be tailored to students (Drigas et al, 2009).…”
Section: Application To Stem Educational Settings and ML Assessmentmentioning
confidence: 99%
“…This has been the primary focus and application of Bayesian methods in education thus far. Indeed, most studies employing Bayesian methods have used them to perform psychometric and factor analyses of novel assessment types (e.g., multi-skill itemized activities and question types) and surveys to study student comprehension, cognition, and attitudes toward learning (Desmarais and Gagnon, 2006;Pardos et al, 2008;Brassil and Couch, 2019;Martinez, 2021;Parkin and Wang, 2021;Vaziri et al, 2021;Wang et al, 2021). The insights obtained from these studies have led to the design, development, and deployment of more adaptive learning and student-focused knowledge assessment content, based on their aptitude levels, allowing educators to learn more about student comprehension and how individualized content can be tailored to students (Drigas et al, 2009).…”
Section: Application To Stem Educational Settings and ML Assessmentmentioning
confidence: 99%
“…Continuing-continuing generation students have increased access to pre-college advanced academic opportunities and less involvement in remedial academic courses (Covarrubias et al, 2020). Access to these advanced opportunities offers increased ability to handle the transition to college and subsequent degree attainment among continuing-generation peers which first-generation students lack (Antonelli et al, 2020;Atherton, 2014;Martinez, 2021). First-generation college students report coming to college with lower average standardized test scores (Martinez et al, 2016), having taken fewer college preparation classes (Forrest Cataldi et al, 2018), and having higher levels of anxiety about the perceived academic rigor of college (Ricks & Warren, 2021).…”
Section: Characteristics Of First-generation College Studentsmentioning
confidence: 99%