Recommendation System for Knowledge Acquisition in MOOCs Ecosystems
Resumo
In recent years, students face difficulties in choosing the best content from the online distance learning of MOOCs (Massive Open Online Courses). The emerged recommendations systems to solve this problem do not identify the student's prior knowledge broadly. From this problem, the main contribution of this work is the identification and reduction of the students' knowledge gap in MOOCs. As such, in this Master's thesis, we model and analyze the MOOCs ecosystems and propose a solution for recommending parts of courses. Based on a set of three experiments, we verify that our recommendations are accurate, useful and reliable. We also present new content to fill the knowledge gap of users as the main contribution of this work to the state of the art.
Palavras-chave:
MOOCs, Knowledge Acquisition, Ecosystems
Referências
Aggarwal CC. 2016. Recommender systems. Cham: Springer International Publishing.
Apaza RG, Cervantes EV, Quispe LC. 2014. Online Courses Recommendation based on LDA. In: SIMBig., p 42–48.
Araujo R. 2016. Information Systems and the Open World Challenges. Boscarioli, C, R.M Araujo e R.S.P Maciel. I Gd. - Gd. Res. Challenges Inf. Syst. Brazil 2016-2026. Spec. Comm. Inf. Syst.: 42--51.
Barbosa OALP, Santos RP, Alves CF, Werner CML, Jansen S. 2013. A Systematic Mapping Study on Software Ecosystems from a Three-Dimensional Perspective. In: Software Ecosystems: Analyzing and Managing Business Networks in the Software Industry., 1ed. Northampton/USA: Edward Elgar Publishing, p 59–81.
Basili VR. 1992. Software modeling and measurement: the Goal/Question/Metric paradigm.
Bhatt C, Cooper M, Zhao J. 2018. SeqSense: Video Recommendation Using Topic Sequence Mining. In: Springer, editor. Proceedings of the International Conference on Multimedia Modeling. Cham, Switzerland, p 252–263.
Campos R. 2019. Recommendation System for Knowledge Acquisition in MOOCs Ecosystems. Master’s Thesis in Informatics. PPGI/UFRJ. Rio de Janeiro, Brazil.
Campos R, Santos RP, Oliveira J. 2020. A Recommendation System based on Knowledge Gap Identification in MOOCs Ecosystems. In: XVI Simpósio Brasileiro de Sistemas de Informação., p 8.
Campos R, Santos RP, Oliveira J. 2019. A Recommendation System Enhanced by Topic Modeling for Knowledge Reuse in MOOCs Ecosystems. In: Reuse in Intelligent Systems. Boca Raton, Florida, EUA: CRC Press (in press).
Campos R, Santos RP, Oliveira J. 2018a. Recommendation Systems for Knowledge Reuse Management in MOOCs Ecosystems. In: Anais do XIV Simpósio Brasileiro de Sistemas de Informação (SBSI), editor. XI WTDSI - XI Workshop de Teses e Dissertações em Sistemas de Informação. Caxias do Sul/RS, Brasil: Porto Alegre: SBC, p 46–48.
Campos R, Santos RP, Oliveira J. 2018b. Using Multilayer Social Networks in an Analysis of Higher Education for Professional Demand. In: I Workshop on Big Social Data and Urban Computing (BIDU), 2018, Rio de Janeiro. Proceedings of the Poster Track of the BiDU 2018. 44th International Conference on Very Large Data Bases (VLDB). Aachen: CEUR-WS, 2018, p 1–15.
Campos R, Santos RP, Oliveira J. 2018c. Web-Based Recommendation System Architecture for Knowledge Reuse in MOOCs Ecosystems. In: 2018 IEEE International Conference on Information Reuse and Integration (IRI). IEEE, p 193–200.
Corbellini A, Mateos C, Zunino A, Godoy D, Schiaffino S. 2017. Persisting big-data: The NoSQL landscape. Inf. Syst. 63: 1–23.
Greene D, O’Callaghan D, Cunningham P. 2014. How Many Topics? Stability Analysis for Topic Models. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Berlin: Springer, p 498--513.
Jing X, Tang J. 2017. Guess You Like: Course Recommendation in MOOCs. In: Proceedings of the International Conference on Web Intelligence. ACM, p 783–789.
Li C, Song Z, Tang J. 2018. User Tagging in MOOCs Through Network Embedding. In: 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). IEEE, p 235–241.
Marinho LH, Campos R, Santos RP, Ferreira da Silva M, Oliveira J. 2019. Conceitos, Implementação e Dados Privados de Algoritmos de Recomendação. In: França TC de, Thomaselli Nogueira JL, Antunes JF, editors. Minicursos da ERSI-RJ 2019 - VI Escola Regional de Sistemas de Informação do Rio de Janeiro (ERSI). SBC, p 32.
Nolasco D. 2016. Identificação Automática de Áreas de Pesquisa em C&T. Master’s Thesis in Informatics. PPGI/UFRJ. Rio de Janeiro, Brazil. 195 p.
O’Callaghan D, Greene D, Carthy J, Cunningham P. 2015. An analysis of the coherence of descriptors in topic modeling. Expert Syst. Appl. 42: 5645–5657.
Ricci F, Rokach L, Shapira B, Kantor PB. 2015. Recommender systems handbook. Springer.
Shah D. 2019. Year of MOOC-based Degrees: A Review of MOOC Stats and Trends in 2018.
Shanyun K, Qin S, Guolin Z. 2015. Research on the Construction of MOOC Learning Community Ecosystem Circle. In: 2015 International Conference of Educational Innovation through Technology (EITT). IEEE, p 199–203.
Song J, Zhang Y, Duan K, Hossain MS. 2017. TOLA: Topic-oriented learning assistance based on cyber-physical system and big data. Futur. Gener. Comput. Syst. 75: 200–205.
Wang J, Xiang J, Uchino K. 2015. Topic-Specific Recommendation for Open Education Resources. In: International Conference on Web-Based Learning., p 71–81.
Apaza RG, Cervantes EV, Quispe LC. 2014. Online Courses Recommendation based on LDA. In: SIMBig., p 42–48.
Araujo R. 2016. Information Systems and the Open World Challenges. Boscarioli, C, R.M Araujo e R.S.P Maciel. I Gd. - Gd. Res. Challenges Inf. Syst. Brazil 2016-2026. Spec. Comm. Inf. Syst.: 42--51.
Barbosa OALP, Santos RP, Alves CF, Werner CML, Jansen S. 2013. A Systematic Mapping Study on Software Ecosystems from a Three-Dimensional Perspective. In: Software Ecosystems: Analyzing and Managing Business Networks in the Software Industry., 1ed. Northampton/USA: Edward Elgar Publishing, p 59–81.
Basili VR. 1992. Software modeling and measurement: the Goal/Question/Metric paradigm.
Bhatt C, Cooper M, Zhao J. 2018. SeqSense: Video Recommendation Using Topic Sequence Mining. In: Springer, editor. Proceedings of the International Conference on Multimedia Modeling. Cham, Switzerland, p 252–263.
Campos R. 2019. Recommendation System for Knowledge Acquisition in MOOCs Ecosystems. Master’s Thesis in Informatics. PPGI/UFRJ. Rio de Janeiro, Brazil.
Campos R, Santos RP, Oliveira J. 2020. A Recommendation System based on Knowledge Gap Identification in MOOCs Ecosystems. In: XVI Simpósio Brasileiro de Sistemas de Informação., p 8.
Campos R, Santos RP, Oliveira J. 2019. A Recommendation System Enhanced by Topic Modeling for Knowledge Reuse in MOOCs Ecosystems. In: Reuse in Intelligent Systems. Boca Raton, Florida, EUA: CRC Press (in press).
Campos R, Santos RP, Oliveira J. 2018a. Recommendation Systems for Knowledge Reuse Management in MOOCs Ecosystems. In: Anais do XIV Simpósio Brasileiro de Sistemas de Informação (SBSI), editor. XI WTDSI - XI Workshop de Teses e Dissertações em Sistemas de Informação. Caxias do Sul/RS, Brasil: Porto Alegre: SBC, p 46–48.
Campos R, Santos RP, Oliveira J. 2018b. Using Multilayer Social Networks in an Analysis of Higher Education for Professional Demand. In: I Workshop on Big Social Data and Urban Computing (BIDU), 2018, Rio de Janeiro. Proceedings of the Poster Track of the BiDU 2018. 44th International Conference on Very Large Data Bases (VLDB). Aachen: CEUR-WS, 2018, p 1–15.
Campos R, Santos RP, Oliveira J. 2018c. Web-Based Recommendation System Architecture for Knowledge Reuse in MOOCs Ecosystems. In: 2018 IEEE International Conference on Information Reuse and Integration (IRI). IEEE, p 193–200.
Corbellini A, Mateos C, Zunino A, Godoy D, Schiaffino S. 2017. Persisting big-data: The NoSQL landscape. Inf. Syst. 63: 1–23.
Greene D, O’Callaghan D, Cunningham P. 2014. How Many Topics? Stability Analysis for Topic Models. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Berlin: Springer, p 498--513.
Jing X, Tang J. 2017. Guess You Like: Course Recommendation in MOOCs. In: Proceedings of the International Conference on Web Intelligence. ACM, p 783–789.
Li C, Song Z, Tang J. 2018. User Tagging in MOOCs Through Network Embedding. In: 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). IEEE, p 235–241.
Marinho LH, Campos R, Santos RP, Ferreira da Silva M, Oliveira J. 2019. Conceitos, Implementação e Dados Privados de Algoritmos de Recomendação. In: França TC de, Thomaselli Nogueira JL, Antunes JF, editors. Minicursos da ERSI-RJ 2019 - VI Escola Regional de Sistemas de Informação do Rio de Janeiro (ERSI). SBC, p 32.
Nolasco D. 2016. Identificação Automática de Áreas de Pesquisa em C&T. Master’s Thesis in Informatics. PPGI/UFRJ. Rio de Janeiro, Brazil. 195 p.
O’Callaghan D, Greene D, Carthy J, Cunningham P. 2015. An analysis of the coherence of descriptors in topic modeling. Expert Syst. Appl. 42: 5645–5657.
Ricci F, Rokach L, Shapira B, Kantor PB. 2015. Recommender systems handbook. Springer.
Shah D. 2019. Year of MOOC-based Degrees: A Review of MOOC Stats and Trends in 2018.
Shanyun K, Qin S, Guolin Z. 2015. Research on the Construction of MOOC Learning Community Ecosystem Circle. In: 2015 International Conference of Educational Innovation through Technology (EITT). IEEE, p 199–203.
Song J, Zhang Y, Duan K, Hossain MS. 2017. TOLA: Topic-oriented learning assistance based on cyber-physical system and big data. Futur. Gener. Comput. Syst. 75: 200–205.
Wang J, Xiang J, Uchino K. 2015. Topic-Specific Recommendation for Open Education Resources. In: International Conference on Web-Based Learning., p 71–81.
Publicado
03/11/2020
Como Citar
CAMPOS, Rodrigo; SANTOS, Rodrigo; OLIVEIRA, Jonice.
Recommendation System for Knowledge Acquisition in MOOCs Ecosystems. In: CONCURSO DE TESES E DISSERTAÇÕES EM SISTEMAS DE INFORMAÇÃO - SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 16. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 93-108.
DOI: https://doi.org/10.5753/sbsi.2020.13132.
