|Author||Jayal, Ambikesh ♦ Shepperd, Martin|
|Source||ACM Digital Library|
|Publisher||Association for Computing Machinery (ACM)|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||E-assessment ♦ Diagrams|
|Abstract||In this article we explore a problematic aspect of automated assessment of diagrams. Diagrams have partial and sometimes inconsistent semantics. Typically much of the meaning of a diagram resides in the labels; however, the choice of labeling is largely unrestricted. This means a correct solution may utilize differing yet semantically equivalent labels to the specimen solution. With human marking this problem can be easily overcome. Unfortunately with e-assessment this is challenging. We empirically explore the scale of the problem of synonyms by analyzing 160 student solutions to a UML task. From this we find that cumulative growth of synonyms only shows a limited tendency to reduce at the margin despite using a range of text processing algorithms such as stemming and auto-correction of spelling errors. This finding has significant implications for the ease in which we may develop future e-assessment systems of diagrams, in that the need for better algorithms for assessing label semantic similarity becomes inescapable.|
|Age Range||18 to 22 years ♦ above 22 year|
|Education Level||UG and PG|
|Learning Resource Type||Article|
|Publisher Place||New York|
|Journal||Journal on Educational Resources in Computing (JERIC)|
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