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How to Best Measure Academic Dishonesty in Students A Systematic Review of Self-Report Assessment Methods and Psychometric Quality
被引:0
|作者:
Fritz, Tanja
[1
]
Cruz, Hernan Gonzalez
[2
]
Janke, Stefan
[2
]
Daumiller, Martin
[3
]
机构:
[1] Univ Augsburg, Dept Behav Hlth Technol, Alter Postweg 101, D-86159 Augsburg, Germany
[2] Univ Mannheim, Sch Social Sci, Mannheim, Germany
[3] Univ Augsburg, Dept Psychol, Augsburg, Germany
关键词:
systematic review;
academic dishonesty;
students;
self-report;
assessment methods;
CHEATING BEHAVIOR;
COLLEGE-STUDENTS;
PLANNED BEHAVIOR;
MISCONDUCT;
PERCEPTIONS;
PERSONALITY;
MOTIVATION;
MODEL;
SCALE;
JUSTIFICATIONS;
D O I:
10.1027/1015-5759/a000861
中图分类号:
B849 [应用心理学];
学科分类号:
040203 ;
摘要:
Addressing a pervasive problem in educational institutions, investigations into academic dishonesty by students have produced a vast body of empirical research, mostly based on self-report measures. However, the literature repeatedly points to inconsistencies in assessment methods and unclear measurement quality. We conducted a preregistered systematic review to compare and evaluate self-report assessments (including past cheating behavior and cheating intentions). Of 256 instruments in 231 studies, 70% were unique self-report measures and 38.7% of studies did not investigate or report psychometric quality criteria. As such, the academic dishonesty literature is no exception in questionable measurement practices, where reports often lack key measurement information, such as the full item list (missing in 32%) or the time frames for behavioral assessment (missing in 50.4%). Our findings illustrate the threat to interpretability and comparability due to a lack of psychometric understanding and inconsistent measurement approaches. Contrary to aiming at a unified measure, we propose a focus on best practices in measurement construction and reporting to address diverse contexts, populations, and research questions. To guide future research, we provide a selection of psychometrically validated scales, recommendations for analysis, operationalization, and reporting, and discuss methodological considerations to enhance the psychometric foundation of academic dishonesty research.
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