In Latin America (LATAM), socioeconomic inequality and lack of resources shape the context of educational institutions in particular ways. Programme quality and dropout rates preoccupy educationalists and governments. The learning analytics (LA) model has become an appealing approach to make educational institutions more effective in understanding students’ behaviours and needs. The use of LA is expanding worldwide, as a way of improving teaching and learning, based on evidence collected from virtual spaces in online, blended and face-to-face courses. However, implementing LA approaches effectively is not straightforward, and demands the engagement of different stakeholders.
‘The learning analytics (LA) model has become an appealing approach to make educational institutions more effective in understanding students’ behaviours and needs.’
Our article, ‘Applications of learning analytics in Latin America’ (Pontual Falcão, Mello, & Rodrigues, 2020), introduces a special section of the British Journal of Educational Technology (BJET) to contribute to the dissemination and visibility of LA research and adoption in the region, which, although in expansion, is still at its early stages (Cechinel et al., 2020).
The special section points to key challenges regarding LA adoption by educational institutions in LATAM. The lack of policies to support data-based actions and of well-established data protection laws makes access to educational datasets limited (Hilliger et al., 2020, Salas-Pilco & Yang, 2020). In addition, the available learning management systems have limited resources for data collection (Hilliger et al., 2020).
Nevertheless, the special section also highlights how LA research in LATAM is being applied in educational institutions to close these gaps, with promising results. For instance, combining policymaking and LA implementation through a coordination model to support the process of adopting LA at scale (Broos et al., 2020); and the development of software tools to support data collection, analysis and implementation of solutions. The latter include: systems to support the development of quality open educational resources by educators (Avila, Baldiris, Fabregat, & Graf, 2020); detection of effective and ineffective behaviours in learning from students’ interactions (Pereira et al., 2020); and academic advising dashboards for allowing instructors to systematically help students to make effective study plans (Guerra et al., 2020; Laet et al., 2020).
As the Covid-19 pandemic struck LATAM in 2020, a sudden expansion of the adoption of online tools by educational institutions took place. There seems to be a general consensus that blended learning is here to stay, with no coming back to fully face-to-face courses; as a result, digital data related to learning processes is bound to increase dramatically. In this context, educational institutions are pressured to adapt their methods and structure to integrate virtual interactions, making LA even more relevant, and broadening the opportunities for applications that may improve education.
This blog is based on ‘Applications of learning analytics in Latin America’ by Taciana Pontual Falcão, Rafael Ferreira Mello and Rodrigo Lins Rodrigues, their editorial to a newly published special section of the British Journal of Educational Technology on that topic.
That editorial has been made free-to-view to those without a subscription to the journal for a limited period, courtesy of our publisher, Wiley.
Avila, C., Baldiris, S., Fabregat, R., & Graf, S. (2020). Evaluation of a learning analytics tool for supporting teachers in the creation and evaluation of accessible and quality open educational resources. British Journal of Educational Technology, 51(4), 1019–1038. https://doi.org/10.1111/bjet.12940
Broos, T., Hilliger, I., Pérez-Sanagustín, M., Htun, N.-N., Millecamp, M., Pesántez-Cabrera, P., Solano‐Quinde, L., Siguenza‐Guzman, L., Zuñiga‐Prieto, M., Verbert, K., & De Laet, T. (2020). Coordinating learning analytics policymaking and implementation at scale. British Journal of Educational Technology, 51(4), 938–954. https://doi.org/10.1111/bjet.12934
Cechinel, C., Ochoa, X., dos Santos, H. L., Nunes, J. B. C., Rodés, V., & Queiroga, E. M. (2020). Mapping learning analytics initiatives in Latin America [Editorial]. British Journal of Educational Technology, 51(4), 892–914. https://doi.org/10.1111/bjet.12941
De Laet, T., Millecamp, M., Ortiz‐Rojas, M., Jimenez, A., Maya, R., & Verbert, K. (2020). Adoption and impact of a learning analytics dashboard supporting the advisor–student dialogue in a higher education institute in Latin America. British Journal of Educational Technology, 51(4), 1002–1018. https://doi.org/10.1111/bjet.12962
Guerra, J., Ortiz-Rojas, M., Zúñiga‐Prieto, M.A., Scheihing, E., Jiménez, A., Broos, T., De Laet, T., & Verbert, K. (2020). Adaptation and evaluation of a learning analytics dashboard to improve academic support at three Latin American universities. British Journal of Educational Technology, 51(4), 973–1001. https://doi.org/10.1111/bjet.12950
Hilliger, I., Ortiz‐Rojas, M., Pesántez‐Cabrera, P., Scheihing, E., Tsai, Y.-S., Muñoz‐Merino, P. J., Broos, T., Whitelock‐Wainwright, A., Gašević, D., & Pérez‐Sanagustín, M. (2020). Towards learning analytics adoption: A mixed methods study of data‐related practices and policies in Latin American universities. British Journal of Education Technology, 51(4), 915–937. https://doi.org/10.1111/bjet.12933
Pereira, F. D., Oliveira, E. H. T., Oliveira, D. B. F., Cristea, A. I., Carvalho, L. S. G. Fonseca, S. C., Toda, A., & Isotani, S. (2020). Using learning analytics in the Amazonas: Understanding students’ behaviour in introductory programming. British Journal of Educational Technology, 51(4), 955–972. https://doi.org/10.1111/bjet.12953
Pontual Falcão, T., Mello, R. F., & Rodrigues, R. L. (2020). Applications of learning analytics in Latin America. British Journal of Educational Technology, 51(4), 871–874. https://doi.org/10.1111/bjet.12978
Salas-Pilco, S. Z., & Yang, Y. (2020). Learning analytics initiatives in Latin America: Implications for educational researchers, practitioners and decision makers. British Journal of Educational Technology, 51(4), 875–891. https://doi.org/10.1111/bjet.12952