Building information visualization of e-learning data with Vis2Learning guidelines




Information Visualization, User Interaction, InfoVis, Educational Data, Learning Analytics


Information Visualization provides techniques to make better charts that enhance human perception about patterns in data and consequently support the user interpretation. In the educational area, visualizations help professionals to analyze a great amount of data to inform decisions to improve the learning­teaching process. The literature has shown that there is a gap in the development of educational data visualizations that fulfill end­user needs. This paper presents Vis2Learning: a scenario­based set of guidelines for the development of visualizations in the e­learning context. Vis2Learning provides a set of scenarios from which educational data visualizations can be developed, for each scenario, we provide the recommended chart, its aim, characteristics and examples of its application in the e­learning context. Besides, we provide a set of guidelines to improve users’ interaction with each chart. We applied an online questionnaire with 34 end­users (Brazilian teachers), evaluating visualizations that were created by using the Vis2Learning. The results reveal: (1) the visualizations, based on Vis2Learning, were more suitable to be applied in the e­learning context; (2) some non­traditional visualization formats are difficult to interpret by users who did not have previous experience with visualizations in the e­learning context; and (3) experience in teaching is not strictly related to knowledge of charts about educational data.


Download data is not yet available.


Alves, N., Rodrigues, R., Dourado, R., and Cavalcanti, A. (2018a). Investigating the suitability of multi­-dimensional data visualization as an instrument for assisting distance learning instructors. In Anais dos Workshops do VII Congresso Brasileiro de Informática na Educação, WCBIE ’18, page 399, Porto Alegre, BRA. RBIE.

Alves, N., Rodrigues, R., Dourado, R., and Cavalcanti, A. (2018b). On the usability of parallel coordinates plots for representing behavioral attributes in lms platforms. In Anais do XXIX Simpósio Brasileiro de Informática na Educação, SBIE ’18, page 1946, Porto Alegre, BRA. RBIE.

Barbosa, A., Araujo, N., Pordeus, J. P., and Santos, E. (2017). Using learning analytics and visualization techniques to evaluate the structure of higher education curricula. In Anais do XXVIII Simpósio Brasileiro de Informática na Educação, SBIE ’17, page 1297–1306, Porto Alegre, BRA. RBIE.

Barros, T., Silva, I., and Guedes, L. (2017). Modelagem e visualização científica de dados educacionais: estudo de caso sobre o desempenho em componentes curriculares. In Anais dos Workshops do VI Congresso Brasileiro de Informática na Educação, WCBIE ’17, page 654–663, Porto Alegre, BRA. RBIE.

Card, S. and Jacko, J. A. (2012). Human­-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications, Third Edition. CRC Press, Boca Raton, FL, USA.

Card, S., Mackinlay, J., and Shneiderman, B. (1999). Readings in Information Visualization: Using Vision To Think. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.

Carneiro, G. d. F. and Mendonça, M. G. d. (2013). Sourceminer - a multi­-perspective software visualization environment. In Proceedings of the 15th International Conference on Enterprise Information Systems ­ Volume 2: ICEIS, pages 25–36. INSTICC, SciTePress.

Chen, Y., Chen, Q., Zhao, M., Boyer, S., Veeramachaneni, K., and Qu, H. (2016). Dropoutseer: Visualizing learning patterns in massive open online courses for dropout reasoning and prediction. In 2016 IEEE Conference on Visual Analytics Science and Technology, VAST, page 111–120, NY, USA. IEEE.

Conde, M. A., García-­Penalvo, F. J., Gómez-­Aguilar, D.­-A., and Therón, R. (2015). Exploring software engineering subjects by using visual learning analytics techniques. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 10(4):242–252.

Dourado, R. A., Rodrigues, R. L., Ferreira, N., and Gomes, A. S. (2018). Mapeamento sistemático sobre o uso de visualização de dados para análise processual da aprendizagem em ambientes virtuais. In Anais do XXIX Simpósio Brasileiro de Informática na Educação, SBIE ’18, page 1563–1572, Porto Alegre, BRA. RBIE.

Fisher, R. A. (1922). On the interpretation of x2 from contingency tables, and the calculation of p. Journal of the Royal Statistical Society, 85(1):87–94.

Garland, R. (1991). The mid­-point on a rating scale: Is it desirable. Marketing Bulletin, 2:66–70.

Johns, R. (2005). One size doesn’t fit all: Selecting response scales for attitude items. Journal of Elections, Public Opinion and Parties, 15(2):237–264.

Jordão, V., Gonçalves, D., and Gama, S. (2014). Eduvis: Visualizing educational information. In Proceedings of the 8th Nordic Conference on Human-­Computer Interaction: Fun, Fast, Foundational, NordiCHI ’14, page 1011–1014, NY, USA. ACM.

Klerkx, J., Verbert, K., and Duval, E. (2017). Learning analytics dashboards. In Lang, C., Siemens, G., Wise, A. F., and Gaševic, D., editors, The Handbook of Learning Analytics, page 143–150. Society for Learning Analytics Research, Alberta, Canada.

Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Research Methods in Human Computer Interaction. Morgan Kaufmann, Boston, NY, USA

Macedo, M. P., Paiva, R. O. A., Gasparini, I., and Zaina, L. A. M. (2020). Vis2learning: A scenario-­based guide of recommendations for building educational data visualizations. In Proceedings of the 19th Brazilian Symposium on Human Factors in Computing Systems, IHC ’20, New York, NY, USA. Association for Computing Machinery.

Maldonado, R. M., Pardo, A., Mirriahi, N., Yacef, K., Kay, J., and Clayphan, A. (2015). The latux workflow: Designing and deploying awareness tools in technology­-enabled learning settings. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge, LAK ’15, page 1–10, NY, USA. ACM.

Mehta, C. and Patel, N. (1996). SPSS exact tests. IBM.

Munzner, T. (2014). Visualization analysis and design. CRC press, New York, NY, USA.

Paiva, R., Bittencourt, I., Cavalcante, M., and Ospina, P. (2019). Teachers’ perceptions on traditional and non-traditional data visualization for pedagogical decision-making. In Anais do XXX Simpósio Brasileiro de Informática na Educação, SBIE ’19, page 1741, Porto Alegre, BRA. RBIE.

Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. In Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering, EASE ’08, page 68–77, Swindon, UK. BCS Learning & Development Ltd.

Reyes, J. A. (2015). The skinny on big data in education: learning analytics simplified. TechTrends, 59(2):75–80.

Ruipérez-­Valiente, J. A., Merino, P. J. M., Gascon­-Pinedo, J., and Delgado-­Kloos, C. (2017). Scaling to massiveness with analyse: A learning analytics tool for open edx. IEEE Transactions on Human-­Machine Systems, 47(6):909–914.

Schwendimann, B. A., Rodríguez-­Triana, M. J., Vozniuk, A., Prieto, L. P., Boroujeni, M. S., Holzer, A., Gillet, D., and Dillenbourg, P. (2017). Perceiving learning at a glance: A systematic literature review of learning dashboard research. IEEE Transactions on Learning Technologies, 10(1):30–41.

Strey, M. R., Pereira, R., and de Castro Salgado, L. C. (2018). Human data­-interaction: A systematic mapping. In Proceedings of the 17th Brazilian Symposium on Human Factors in Computing Systems, IHC ’18, NY, USA. ACM.

Tervakari, A. M., Silius, K., Koro, J., Paukkeri, J., and Pirttilä, O. (2014). Usefulness of information visualizations based on educational data. In 2014 IEEE Global Engineering Education Conference, EDUCON, page 142–151, NY, USA. IEEE.

Vieira, C., Parsons, P., and Byrd, V. (2018). Visual learning analytics of educational data: a systematic literature review and research agenda. Computers & Education, 122:119–135.

Ware, C. (2012). Information Visualization: perception for design. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.




How to Cite

MACEDO, M. P.; PAIVA, R. O. A.; GASPARINI, I.; ZAINA, L. A. M. Building information visualization of e-learning data with Vis2Learning guidelines. Journal on Interactive Systems, Porto Alegre, RS, v. 13, n. 1, p. 42–53, 2022. DOI: 10.5753/jis.2022.1967. Disponível em: Acesso em: 8 feb. 2023.



Regular Paper