How can the learning of maths online be optimized?

Learning and teaching mathematics in higher education courses run fully online is a major challenge. Mathematics involves a great deal of highly abstract concepts, and having to convey them by means of emails and text editors is an added hurdle. Josep Figueroa Cañas, a secondary school teacher and researcher at the Universitat Oberta de Catalunya (UOC), believes that "there's a great deal of room for improvement in learning mathematics". With this approach in mind, and as part of his thesis for the doctoral programme in Education and ICT (E-Learning) at the UOC, Figueroa has developed a series of measures to optimize how the subject is taught online and to improve student outcomes. 

The starting point for his research is the previous research studies carried out by the Learning Analytics for Innovation and Knowledge Application in Higher Education group (LAIKA), headed by Professor Teresa Sancho, member of the Faculty of Computer Science, Multimedia and Telecommunications and supervisor of Figueroa's thesis on online learning.

His research focuses on the learning of mathematics in engineering courses at the UOC. By administering questionnaires to students, Figueroa investigated the learning process and used the data he obtained to propose teaching interventions that can improve it. To do this he used the learning analytics methodology pioneered by Doug Clow, which shows how constant improvement in learning takes place in cycles with four phases: selection of the students, data collection, data analysis and planning, and the implementation of a teaching intervention to improve learning.

Practice and personalized feedback – key to learning

Engineering students at the UOC do mathematical activities involving tests called Wiris-Quizzes and a continuous assessment system. These quizzes, which have been used at the UOC since the 2010/2011 academic year, enable students to receive immediate and personalized feedback about their answers. 

Figueroa carried out four studies with groups of students in order to obtain different types of data: the relationship between students' practices and their academic results; predictors to identify students at risk of dropping out of the course; and the impact of a teaching intervention on those students to prevent them from dropping out. 

According to Figueroa, "learning analytics are an essential tool for the constant improvement of mathematics learning at the UOC: they provide a new way to improve learning based on the analysis of objective data, and not on opinions or assumptions which have been confirmed to varying degrees. It's also a continuous process which never ends", added the researcher.

The conclusions of Figueroa's thesis show that practice with quizzes providing automatic and immediate feedback and correction leads to better grades for students in continuous assessment activities and has an impact on learning and the result of examinations for the course. He also concluded that it is already possible to identify students who are at risk of dropping out of a mathematics course (Statistics in this case) or of not passing the final exam with just the grades obtained in the first continuous assessment activity quizzes. These assessments mean that teaching interventions can be carried out at an early stage. In short, the continuous use of quizzes with automatic correction and feedback helps students to achieve their learning objectives. And learning analytics are essential for making decisions about improving teaching practice.

The measures proposed by Figueroa can be applied in both the UOC's online learning system and at traditional educational institutions, such as universities and secondary schools. 

This UOC research supports Sustainable Development Goal (SDG) 4, Quality Education.

Reference document:

Figueroa Cañas, Josep. Pràctica continuada i feedback automàtic en l'aprenentatge de matemàtiques en línia: un estudi des de la perspectiva de les analítiques d'aprenentatge. https://openaccess.uoc.edu/handle/10609/143326?locale=en.

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