Giving Online Quizzes in Corporate Finance and Investments for a Better Use of Seat Time

Peng, Zhuoming Joe

doi:10.9743/jeo.2007.2.3

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…A contrasting study found no statistically significant differences in MCT scores between undergraduate finance students taking an unsupervised online test vs. those taking the supervised test in-class (Peng 2007). The e-test was available over 30 h, took 80 min to complete and questions were allocated randomly from a pool of questions.…”

Section: Online Testingmentioning

confidence: 99%

Post-graduate student performance in ‘supervised in-class’ vs. ‘unsupervised online’ multiple choice tests: implications for cheating and test security

Ladyshewsky

2014

Assessment & Evaluation in Higher Education

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This research explores differences in multiple choice test (MCT) scores in a cohort of post-graduate students enrolled in a management and leadership course. A total of 250 students completed the MCT in either a supervised inclass paper and pencil test or an unsupervised online test. The only statistically significant difference between the nine test scores was for one test where the students scored significantly lower in the unsupervised online test. There was no increase in mean test scores over time and the mean test scores for the unsupervised online test were not significantly higher than the mean test scores for the supervised in-class test. The study suggests that unsupervised online MCTs can be a viable tool for assessing knowledge in post-graduate students provided they meet best practice standards for online assessment. Concerns about increased cheating in unsupervised online testing are not supported.

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Section: Online Testingmentioning

confidence: 99%

Post-graduate student performance in ‘supervised in-class’ vs. ‘unsupervised online’ multiple choice tests: implications for cheating and test security

Ladyshewsky

2014

Assessment & Evaluation in Higher Education

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“…It is estimated that this technological approach saves almost five classes or more than ten percent of the class meetings in a regular semester. This savings in “seat time” (Peng , p. 10) allows the instructor to cover extra course material. The OL exams provide flexibility for traveling students, especially athletes who can take the online exams at any time or place.…”

Section: Cheating Detection Framework Conceptualizationmentioning

confidence: 99%

“…However, results from earlier studies are mixed. Some studies have reported cheating (Fask et al., ; Harmon & Lambrinos, ; King et al., ) while others registered no cheating (Greenberg et al., ; Hollister & Berenson, ; Peng, ; Werhner, ). Shen, Chung, Challis, and Cheung () found no significant performance difference between the traditional classes and online classes, although the traditional class performed slightly better than the online class.…”

Section: Introductionmentioning

confidence: 99%

“…Academic dishonesty has been studied under different exam‐course settings, including: (1) unproctored online (OL) exams in online (OL) courses (Hollister & Berenson, ; King et al., ); (2) proctored in‐class (IC) exams in OL courses (Hollister & Berenson, ; Werhner, ); (3) proctored IC exams in traditional IC courses (Shon, ); (4) unproctored take‐home (TH) exams in IC courses (Andrada & Linden, ; Marsh, ); and (5) OL exams or quizzes in IC courses (Fask et al., ; Peng, ). This study consisted of OL exams in IC courses and TH exams in IC courses.…”

Section: Introductionmentioning

confidence: 99%

“…Researchers have extensively applied hypothesis testing to determine if cheating took place in online exams by comparing if there is a significant difference in the scores of an OL unproctored and IC proctored exam score (Fask et al., ; Harmon & Lambrinos, ; Hollister & Berenson, ; Peng, ; Werhner, ). If the exam scores between OL and IC or TH and IC are significantly different, then the differences denote that chance causes can be ruled out and we can conclude that cheating may have taken place.…”

Section: Introductionmentioning

confidence: 99%

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A Conceptual Framework for Detecting Cheating in Online and Take‐Home Exams

D'Souza

Siegfeldt

2017

Decision Sci J Innov Edu

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Selecting the right methodology to use for detecting cheating in online exams requires considerable time and effort due to a wide variety of scholarly publications on academic dishonesty in online education. This article offers a cheating detection framework that can serve as a guideline for conducting cheating studies. The necessary theories and related statistical models are arranged into three phases/sections within the framework to allow cheating studies to be completed in a sufficiently quick and precise manner. This cheating detection framework includes commonly used models in each phase and addresses the collection and analysis of the needed data. The model's level of complexity ascends progressively from a graphical representation of data and descriptive statistical models to more advanced inferential statistics, correlation analysis, regression analysis, and the optional comparison method and the Goldfeld-Quandt Test for heteroskedasticity. An instructor receiving positive results on the possibility of cheating in Phases 1 or 2 can avoid using more advanced models in Phase 3. Tests conducted on sample courses showed that models in Phases 1 and 2 of the proposed framework provided results effectively for over 70% of the test groups, saving users further time and effort. High-tech systems and low-cost recommendations that can mitigate cheating are discussed. This framework will be beneficial in guiding instructors who are converting from the traditionally proctored in-class exam to a take-home or online exam without authentication or proctoring. In addition, it can serve as a powerful deterrent that will alleviate the concerns that an institution's stakeholders might have about the reliability of their programs.

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Do Online Exams Facilitate Cheating? An Experiment Designed to Separate Possible Cheating from the Effect of the Online Test Taking Environment

2014

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Giving Online Quizzes in Corporate Finance and Investments for a Better Use of Seat Time

Cited by 9 publications

References 9 publications

Post-graduate student performance in ‘supervised in-class’ vs. ‘unsupervised online’ multiple choice tests: implications for cheating and test security

Post-graduate student performance in ‘supervised in-class’ vs. ‘unsupervised online’ multiple choice tests: implications for cheating and test security

A Conceptual Framework for Detecting Cheating in Online and Take‐Home Exams

Do Online Exams Facilitate Cheating? An Experiment Designed to Separate Possible Cheating from the Effect of the Online Test Taking Environment

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