Complexity of digital resources: an analysis based on their conceptual networks


Knowing the level of complexity of digital resources is crucial to delimit their use in the educational context. This paper summarizes the contributions of my thesis and focuses on strategies to build conceptual networks based on the content of digital resources; identifying metrics and features to measure complexity in conceptual networks accurately; and, proposes new approaches to level digital resources complexity. The contributions of this thesis are extensively evaluated with two large datasets containing resources in varied levels of complexity. The results show that the proposed metrics and features are suitable to estimate digital resources complexity and applicability in educational scenarios. The outcomes of this thesis have been published in high-impact venues.

Palavras-chave: Digital resources, Conceptual networks, Complexity


Bansal, M. and Sharma, D. (2015). Improving webpage visibility in search engines by enhancing keyword density using improved on-page optimization technique. International Journal of Computer Science and Information Technologies, 6(6):5347–5352.

Benjamin, R. G. (2012). Reconstructing readability: Recent developments and recommendations in the analysis of text difficulty. Educational Psychology Review, 24(1):63–88.

Berlyne, D. E. (1960). Conflict, arousal, and curiosity. page 303p.

Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment, 2008(10):P10008.

Collins-Thompson, K., Bennett, P. N., White, R. W., De La Chica, S., and Sontag, D. (2011). Personalizing web search results by reading level. In Proceedings of the 20th ACM international conference on Information and knowledge management, pages 403–412.

Feltovich, P. J., Spiro, R. J., and Coulson, R. L. (1993). Learning, teaching, and testing for complex conceptual understanding. Test theory for a new generation of tests.

Gell-Mann, M. (1995). What is complexity? Remarks on simplicity and complexity by the Nobel Prize-winning author of The Quark and the Jaguar. Complexity, 1(1):16–19.

Gimenez, P., Machado, M., Pinelli, C., and Siqueira, S. (2020). Investigating the learning perspective of searching as learning, a review of the state of the art. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 302–311, Porto Alegre, RS, Brasil. SBC.

Kursa, M. B., Rudnicki, W. R., et al. (2010). Feature selection with the boruta package. J Stat Softw, 36(11):1–13.

Mainzer, K. and Landauer, R. (1995). Thinking in Complexity: The Complex Dynamics of Matter, Mind, and Mankind. American Journal of Physics.

Malaga, R. A. (2009). Web 2.0 techniques for search engine optimization: Two case studies. Review of Business Research, 9(1):132–139.

Mandl, H., Gruber, H., and Renkl, A. (1993). Misconceptions and knowledge compartmentalization. In Advances in psychology, volume 101, pages 161–176. Elsevier.

Manrique, R., Sosa, J., Marino, O., Nunes, B. P., and Cardozo, N. (2018). Investigating learning resources precedence relations via concept prerequisite learning. In 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pages 198–205. IEEE.

Pereira, C. K., Medeiros, J. F., Siqueira, S. W., and Nunes, B. P. (2019). How complex is the complexity of a concept in exploratory search. In 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), volume 2161, pages 17–21. IEEE.

Pereira, C. K., Nunes, B. P., Siqueira, S. W., Manrique, R., and Medeiros, J. F. (2020). 'a little knowledge is a dangerous thing': A method to automatically detect knowledge compartmentalization and oversimplification. In 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT), pages 140–144. IEEE.

Pereira, C. K., Siqueira, S., and Nunes, B. P. (2017a). Dados conectados na educação. In 6º DesafIE! - Workshop de Desafios da Computação aplicada à Educação, 2017, São Paulo. Anais do XXXVII Congresso da Sociedade Brasileira de Computação - CSBC.

Pereira, C. K., Siqueira, S. W. M., Nunes, B. P., and Dietze, S. (2017b). Linked data in education: a survey and a synthesis of actual research and future challenges. IEEE Transactions on Learning Technologies, 11(3):400–412.

Piech, C., Spencer, J., Huang, J., Ganguli, S., Sahami, M., Guibas, L., and Sohl-Dickstein, J. (2015). Deep knowledge tracing. arXiv preprint arXiv:1506.05908.

Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3):379–423.

Silvia, P. J. (2005). What is interesting? exploring the appraisal structure of interest. Emotion, 5(1):89.

Sweller, J. and Chandler, P. (1994). Why some material is difficult to learn. Cognition and instruction, 12(3):185–233.

van der Sluis, F. and van den Broek, E. L. (2010). Using complexity measures in information retrieval. In Proceedings of the third symposium on information interaction in context, pages 383–388. ACM.

Van der Sluis, F., Van den Broek, E. L., Glassey, R. J., van Dijk, E. M., and de Jong, F. M. (2014). When complexity becomes interesting. Journal of the Association for Information Science and Technology, 65(7):1478–1500.

Wiesner, K. and Ladyman, J. (2020). Measuring complexity.

Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics bulletin, 1(6):80–83.

Wu, Q. and Miao, C. (2013). Curiosity: From psychology to computation. ACM Computing Surveys (CSUR), 46(2):18.

Zyngier, S., Van Peer, W., and Hakemulder, J. (2007). Complexity and foregrounding: In the eye of the beholder? Poetics Today, 28(4):653–682.
Como Citar

Selecione um Formato
SILVA, Crystiam K. P.; SIQUEIRA, Sean W. M.; NUNES, Bernardo P.. Complexity of digital resources: an analysis based on their conceptual networks. In: S WORKSHOPS DO CONGRESSO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (WCBIE) , 2021 Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 51-60. DOI: