Combining analytic rubrics and automated non-compensatory rules for more reliable, fair and transparent assessment

Analytic rubrics are widely used in Computer Science (CS) assessment to support marking consistency and transparency. However, they pose reliability problems (affecting fairness), and additively obtained marks may not reflect achievement of learning outcomes. Using non-additive non-compensatory (NANC) rules based on student performance in certain aspects of the assessment to automatically calculate marks can address these issues, but it impacts transparency to students. We propose integrating analytic rubrics and automated NANC rules as an extension to a marking tool named MarkEd, to reap the benefits of both. Evaluation with academics and markers showed high usability and positive perceptions of improved marking reliability and fairness in CS education.