Use of data for improving education: international experts shared experiences in Uruguay

EdTech Exchange Meeting: Korean & Latin American Experiences: Data-driven educational policies aimed to promote the exchange of experiences, knowledge and best practices on the integration and use of data for creating evidence-based educational technology policies and understand the current challenges and recommendations for the years to come, specifically in the field of educational technology; educational data mining, learning analytics and the use of Artificial Intelligence and Machine Learning for education, as well as analyzing and discussing metrics, approaches and innovative research methodologies.

During the past few years, international organizations and education systems worldwide have increased their efforts for promoting evaluation and assessment, focusing in the use and integration of data for educational decision-making and the adoption of evidence-based policies. Effective interventions require quality data and good information, constant evaluation, robust metrics and indicators to assess teachers, students, education policies and systems alike (World Bank, 2018). 

There has been a gradual cultural shift towards improving and increasing the collection and use of educational data, and its integration and analysis in order to promote measuring and evaluation. Not only have evaluation and assessment become pillars for addressing the needs of learning and teaching processes, but also the methods, resources and practices have gradually evolved. Despite standardized evaluations such as PISA, remain among the most relevant instruments worldwide, technology-driven transformations in areas such as Big Data, Analytics and Artificial Intelligence, have widely increased the potential for introducing new approaches in education evaluation and assessment. 

More specifically, their use has shown a strong potential for understanding the underlying factors that influence learning and teaching outcomes and practices; improving educational management and decision-making, and to better understand and address students and teachers performance (Cobo, C., Zucchetti A., Rivas, A., 2018).

Within this framework, the technical cooperation between Uruguay and Korea, through the Inter-American Development Bank, intended to implement a monitoring system for Learning Analytics that could enable the integration and analysis of massive data from different sources of Plan Ceibal. The technical cooperation started in 2015 and required the development of several processes among which: creating capacities within the organization in the field of learning analytics and Big Data; working in the quality of data, metadata and datasets, designing and implementing the platform for data analysis, creating two Committees -an internal one for Privacy and Data Protection- and an external and institutional one for analyzing and addressing the ethical risks in the use of massive data for education, strengthening research in learning analytics and Big Data, among several other areas. Those actions aimed to provide targeted answers and address some of the education system difficulties; to generate evidence-based decision and policy making at the educational level. 

EdTech Exchange Meeting: Korean & Latin American Experiences: Data-driven educational policies, which was part of the activities included in the technical cooperation, was held during the first week of October in Montevideo, with the participation of a wide range of Uruguayan, regional and international experts from prestigious institutions: Sungkyunkwan University (Korea), Chungbuk National University (Korea), Inter-American Development Bank, Tel Aviv University (Israel), The Open University (Portudal), Monash University (Australia), INEEd (Uruguay), World Bank, USP – Universidade de São Paulo (Brazil), Universidad Católica de Uruguay, EDUY21 (Uruguay), CAF – Development Bank of Latin America, Engineering Faculty of Universidad de la República (Uruguay), ANII (Uruguay), Plan Ceibal (Uruguay), Universidad ORT (Uruguay), Ceibal Foundation (Uruguay), Universidad de Montevideo (Uruguay), DIEE-ANEP (Uruguay), IESTA – UDELAR (Uruguay), UTEC – Data Science Programme (Uruguay), Psychology Faculty (Uruguay), ICT4V (Uruguay). 

Documents:

• Check the full agenda of the event here.
• Presentations:
  • EdTech for the future: practices and experiences in Korean Education
    • DJHwang-Smart Transformation of EdTech Toward Student Success
  • Ethics, privacy and data protection
    • Alessia Zucchetti-Introducing a new approach in a data-driven ecosystem_ Digital Ethics for Education
  • Learning Analytics: The state of the art, latest improvements, current and future challenges
  • • Arnon Hershkovitz-How Can Big Data Inform Educational Decisions (Big and Small)
    • Francisco Iniesto-The use of data in Distance and Open Education pathways to student inclusion
  • New frontiers for educational policy: the potential of AI and ML
    • Luis Chiruzzo-Natural Language Processing for Education in Uruguay
  • Plan Ceibal: the use of data for research and evidence-based decision-making
  • • • Cecilia Marconi-Analytics in Plan Ceibal_Better information to make better decisions
      • Germán Capdehourat-Unveiling User Profiles_A First Look at a K-12 Education Service Provider
    • Research projects and data-driven best practices in educational policy making
    • • Julian Cristia-Using Platform Data to Search for Bottlenecks
      • Natalia da Silva-Statistical technologies for evaluating and monitoring VLEs
      • Roberto Martinez Maldonado-Moving from multimodal data to higher-order educational constructs 
      • Seiji Isotani-A new paradigm to evaluate educational technologies
      • Virginia Robano-Innovative Education spurring an entrepreneurial ecosystem