2026-04-22T17:32:09Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/99422025-01-17T01:05:31Zcom_10259_4219com_10259_5086com_10259_2604col_10259_4220
Repositorio Institucional de la Universidad de Burgos
author
Izquierdo Amo, Roberto
author
Barbero Aparicio, José Antonio
author
Garrido Labrador, José Luis
author
Olivares Gil, Alicia
author
García Osorio, César
2025-01-16T10:16:02Z
2025-01-16T10:16:02Z
2025-01
http://hdl.handle.net/10259/9942
10.3390/educsci15010075
2227-7102
Moodle quizzes are a convenient way of online assessment, benefiting both teachers and students. Unfortunately, their preparation is slow, cumbersome, and error-prone. In addition to the effort of designing the questions, it is necessary to enter them in Moodle. Furthermore, for questions that require images, these must first be created and then uploaded to Moodle. If this process has to be repeated with many questions, the required work becomes prohibitive. This paper presents a tool that solves all these problems, allowing the automatic and massive generation of questions for the evaluation of the knowledge about lexical analysis algorithms. The evaluation of these algorithms is relevant in the subjects of both automata and formal languages and in those of compiler design. The tool allows the creation of exercises of configurable complexity, after which the text, tables, and associated images are generated for quick upload to Moodle. The main impact of this tool is the substantial reduction of question preparation time, reducing hundreds or thousands of interactions with Moodle forms to just a few simple steps. In addition, the ease of question generation makes it possible to prepare self-assessment questionnaires for the students, something that they greatly appreciate as a study aid.
eng
Atribución 4.0 Internacional
Moodle quizzes
Continuous assessment
Cloze questions
Quiz generation
Finite state automata
Regular expressions
Genetic programming
Automatic Generation of Moodle Cloze Questions for the Assessment of Knowledge About Lexical Analysis Algorithms
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/9942/1/izquierdo-es_2025.pdf
File
MD5
ec89a778ca42117a7b1766dde61adf5a
2787100
application/pdf
izquierdo-es_2025.pdf