TY - GEN
T1 - Analysis of the Level of Inclusion of Digital Competencies in the Educational Curriculum
T2 - A Case Study at UNEMI University
AU - Chifla Villón, Mario Rubén
AU - Saquicela Galarza, Víctor Hugo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025/2/2
Y1 - 2025/2/2
N2 - Education in the 21st century requires students to develop essential digital skills such as privacy protection and digital security, communication and collaboration in digital contexts, digital culture, and digital citizenship, including evaluation and digital content creation. However, the integration of these digital competencies in Education-related degrees syllabi is very limited, which may lead to insufficient training of future teachers to face the challenges of the 21st century. This study analyzes the integration of digital competencies in the curricula of UNEMI's Education degree program, employing a process based on Large Language Models (LLMs). By processing a large volume of textual data from the syllabi, LLM allows to accurately identify the degree to which digital competencies defined by DIGCOMP are addressed. Our results reveal significant variability between subjects, evidencing the necessity to strengthen the inclusion of these skills in the curriculum to ensure that future teachers are prepared for the challenges of digital education.
AB - Education in the 21st century requires students to develop essential digital skills such as privacy protection and digital security, communication and collaboration in digital contexts, digital culture, and digital citizenship, including evaluation and digital content creation. However, the integration of these digital competencies in Education-related degrees syllabi is very limited, which may lead to insufficient training of future teachers to face the challenges of the 21st century. This study analyzes the integration of digital competencies in the curricula of UNEMI's Education degree program, employing a process based on Large Language Models (LLMs). By processing a large volume of textual data from the syllabi, LLM allows to accurately identify the degree to which digital competencies defined by DIGCOMP are addressed. Our results reveal significant variability between subjects, evidencing the necessity to strengthen the inclusion of these skills in the curriculum to ensure that future teachers are prepared for the challenges of digital education.
KW - DigComp
KW - Digital Competences
KW - LLM
KW - Syllabus
KW - DigComp
KW - Digital Competences
KW - LLM
KW - Syllabus
UR - https://www.scopus.com/pages/publications/105026630495
UR - https://link.springer.com/chapter/10.1007/978-981-95-5234-4_22
U2 - 10.1007/978-981-95-5234-4_22
DO - 10.1007/978-981-95-5234-4_22
M3 - Contribución a la conferencia
AN - SCOPUS:105026630495
T3 - Lecture Notes in Educational Technology
SP - 231
EP - 238
BT - Proceedings of The 6th International Conference on Education Development and Studies 2025
PB - Springer Science and Business Media Deutschland GmbH
ER -