Semantic annotations for the recommendation of educational contents

• Grant number: 18/00313-2
• Support Opportunities: Scholarships in Brazil - Master
• Start date: March 01, 2018
• End date: February 29, 2020
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Julio Cesar dos Reis
• Grantee: Marcos Vinicius Macêdo Borges
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 17/02325-5 - EvOLoD: linked data evolution on the Semantic Web, AP.JP

Abstract

Learning support systems explore several audio-visual resources to consider individual needs and learning styles aiming to stimulate learning experiences. However, the large amount of educational content in different formats and the possibility of making them available in a fragmented way makes difficult the tasks of accessing to these resources and understanding of the concepts under study. Although, the literature has proposed approaches to explore explicit semantic representation through artifacts such as ontologies in learning support systems, this research line still requires research efforts. This master research project aims to achieve a method for recommending educational content by exploring the use of semantic annotations over textual transcriptions of video lessons. The annotations serve as metadata that express the meaning of excerpts from classes. The recommendation technique, as the main expected contribution, is based on the available annotations to define ranking content strategies from the semantic proximity of concepts. We will explore the development of software prototypes for the validation of the proposal. The solution to be obtained will be evaluated experimentally based on real-world video lesson content and should highlight the main advantages and limitations of this research. Getting more appropriate recommendations can leverage the learning process by presenting the possibility of more satisfying students experience (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DOS REIS, JULIO CESAR; BORGES, MARCOS VINICIUS MACEDO; GRIBELER, GUILHERME PEREIRA; IEEE. Empirical Analysis of Semantic Metadata Extraction from Video Lecture Subtitles. 2019 IEEE 28TH INTERNATIONAL CONFERENCE ON ENABLING TECHNOLOGIES: INFRASTRUCTURE FOR COLLABORATIVE ENTERPRISES (WETICE), v. N/A, p. 6-pg., 2019-01-01. (17/02325-5, 18/00313-2)

MACEDO BORGES, MARCOS VINICIUS; DOS REIS, JULIO CESAR; CHANG, M; SAMPSON, DG; HUANG, R; GOMES, AS; CHEN, NS; BITTENCOURT, II; KINSHUK; DERMEVAL, D; et al. Semantic-enhanced Recommendation of Video Lectures. 2019 IEEE 19TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2019), v. N/A, p. 5-pg., 2019-01-01. (17/02325-5, 18/00313-2)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

BORGES, Marcos Vinicius Macêdo. Anotação semântica para recomendação de conteúdos educacionais. 2021. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Instituto de Computação Campinas, SP.