If the Damerau-Levenshtein distance between strings and is then the similarity is defined as
![string similarity string similarity](https://i.ytimg.com/vi/e9pfuRz54cY/hqdefault.jpg)
Simplicity, the evaluation of a student's answer does not take place by means of a semantic distance, but using the string distance to the respective cluster as a whole (single linkage, minimum distance, nearest neighbour, see for example ). Note that the presented method is, strictly speaking, not only based on the strings, but also on semantics, because by introducing the denylist and allowlist respectively, a (trivial) semantic graph consisting of two clusters is set up. Here we need an empirically determined threshold parameter. Applying the similarity on allowlist and denylist we define an acceptance domain for the students' answers. To have a relative measure of the difference between two strings, we convert the distance to similarity. To increase the quality of the assessment, we extended the basic metric function by the adding the components: allowlist and denylist. This enables a suitable string evaluation. Note that this distance is a metric in mathematical sense, in particular it satisfies the triangle inequality. Informally, this distance is the minimum number of single-character edits (insertion, deletion, substitution, transition) required to change one string sequence into the other. To automatically mark fill-in-the-blank questions we used one of the string metrics for measuring the distance between two strings: the Damerau-Levenshtein distance, which plays an important role in natural language processing. But they can be hardly implemented, since typing and spelling errors, synonyms and geuine alternatives have to be taken into account when evaluating the students' answers.
![string similarity string similarity](https://corpustools.readthedocs.io/en/version1.1/_images/stringsimilarityresults.png)
The fill-in-the-blank questions are important from a didactic point of view. We also show a STACK question equipped with a string metric, by evaluating its use in mathematics courses.
![string similarity string similarity](https://i.stack.imgur.com/rUHxg.jpg)
To increase the quality of the evaluation, we use two lists: allowlist and denylist instead of a single teacher's answer. We present a method to evaluate fill-in-the-blank student answers in STACK using a string metric. Eichhorn and Andreas Helfrich-Schkarbanenko Abstract Question Answering in STACK Applying String SimilarityĪchim.