@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 = {

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.

}, keywords = {automatic analysis of grades, biases in assessment, grading discrepancies, massive laboratories, project-based learning, software quality analysis}, issn = {0949-149X}, attachments = {https://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} }