Informace o publikaci

Interpretable Clustering of Students’ Solutions in Introductory Programming

Autoři

EFFENBERGER Tomáš PELÁNEK Radek

Rok publikování 2021
Druh Článek ve sborníku
Konference Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science, vol 12748
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www https://doi.org/10.1007/978-3-030-78292-4_9
Doi http://dx.doi.org/10.1007/978-3-030-78292-4_9
Klíčová slova interpretable clustering; pattern mining; introductory programming; problem solving
Popis In introductory programming and other problem-solving activities, students can create many variants of a solution. For teachers, content developers, or applications in student modeling, it is useful to find structure in the set of all submitted solutions. We propose a generic, modular algorithm for the construction of interpretable clustering of students’ solutions in problem-solving activities. We describe a specific realization of the algorithm for introductory Python programming and report results of the evaluation on a diverse set of problems.
Související projekty:

Používáte starou verzi internetového prohlížeče. Doporučujeme aktualizovat Váš prohlížeč na nejnovější verzi.

Další info