Correspondence Bias in Performance Evaluation: Why Grade Inflation Works

Gino, Francesca; Swift, Samuel A.; Sharek, Zachariah S.

doi:10.2139/ssrn.728627

Cited by 3 publications

(1 citation statement)

References 47 publications

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“…Because students take a different mix of courses each term, our specifications include the expected GPA for fall, winter, and spring terms, allowing for differences in course taking behavior across time. Following the specification for observed GPA, the three expected GPA controls are 8 Recent work have shown incentives for grade inflation that can differ across departments and institutions (e.g., Gino et al 2007;Bar et al 2008). Higher education institutions are also aware that grades do not directly correlate with performance in the classroom and are moving towards reporting such measures as the median grade (e.g., Dartmouth, Cornell) and the percent A-range grades (e.g., Columbia) on the transcript.…”

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

Modeling Retention at a Large Public University: Can At-Risk Students Be Identified Early Enough to Treat?

Singell

Waddell

2010

Res High Educ

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We examine the extent to which readily available data at a large public university can be used to a priori identify at-risk students who may benefit from targeted retention efforts. Although it is possible to identify such students, there remains an inevitable tradeoff in any resource allocation between not treating the students who are likely to exit without treatment and treating students who are likely not to exit in the absence of the treatment. At-risk students are found to remain at risk throughout their college career. Moreover, conditional on exiting the institution, the degree to which the student was at risk is predictive of whether the student subsequently re-enrolls elsewhere and the type of institution at which this re-enrollment occurs. In this context, we discuss how retention policies relate to insuring the initial match is appropriate, recognizing that some attrition can be in keeping with the broad social interest.

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Section: Data and Descriptive Statisticsmentioning

confidence: 99%

Modeling Retention at a Large Public University: Can At-Risk Students Be Identified Early Enough to Treat?

Singell

Waddell

2010

Res High Educ

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9 The Case for Behavioral Decision Research in Organizational Behavior

Moore,

Flynn

2008

The Academy of Management Annals

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The Main Factors beyond Decision Making

Al-Tarawneh¹

2011

jmr

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This paper argues that the time has come to focus attention on the search for factors that affect decision making because decision making errors are costly and are growing more costly, decision makers are receptive, and academic insights are sure to follow from research on improvement. In addition to calling for research on improvement strategies, this paper aims to conclude the main factors that affect decision making, and how these factors have a great impact and influence on decision makers. The researcher focuses on literature review to come up with these main factors.

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Correspondence Bias in Performance Evaluation: Why Grade Inflation Works

Cited by 3 publications

References 47 publications

Modeling Retention at a Large Public University: Can At-Risk Students Be Identified Early Enough to Treat?

Modeling Retention at a Large Public University: Can At-Risk Students Be Identified Early Enough to Treat?

9 The Case for Behavioral Decision Research in Organizational Behavior

The Main Factors beyond Decision Making

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