@article {175,
	title = {Methodology for the Analysis of Instructors{\textquoteright} Grading Discrepancies in a Laboratory Course},
	journal = {International Journal of Engineering Education},
	volume = {22},
	year = {2006},
	month = {09/2006},
	pages = {1053-1062 },
	publisher = {TEMPUS Publications, Dublin Institute of Technology},
	address = {Irlanda},
	abstract = {<p>
<div>This paper introduces a new methodology to analyze grading discrepancies in PBL software-engineering courses with a high student-to-faculty ratio. The methodology is based on a quantitative analysis of the more relevant software features according to the grades assigned by each instructor. In order to reduce the discrepancies detected, a new grading consensus has to be built, and automatic analysis tools must assist the instructors when grading. The evaluation of the methodology in two academic years revealed a 62\% reduction of the grading discrepancies, achieving an average inter-instructor discrepancy of 0.10 in a scale from 0 to 1.</div>
</p>},
	keywords = {automatic analysis of grades, biases in assessment, grading discrepancies, massive laboratories, project-based learning, software quality analysis},
	issn = {0949-149X},
	attachments = {https://smtp.geintra-uah.org/en/system/files/IJEE1748.pdf},
	author = {Juan Manuel Montero and San Segundo, Ruben and Javier Macias-Guarasa and Ricardo Cordoba and Javier Ferreiros}
}
