Tue 7th March 2017 - 14:41

Case study on the ODEdu project: education based on learning analytics

Maria Zotou, researcher at the University of Macedonia is involved in the project Open Data Education and Training Based on Problem Based Learning and Learning Analytics (ODEdu). The project started in 2016 and is expected to be completed in 2018. We asked Maria to tell us more about the ODEdu project and her experiences. 

ODEdu is a 3-year project (2016-2018) funded by the Erasmus+ Programme. It aims to establish a knowledge alliance between academia, business and the public sector that will boost open data education and training.

The general challenge observed in academia, business and the public sector is the need for the existing and future workforce to become skilled and adaptable lifelong learners, and contribute to the economy and society. With the ODEdu project we wanted to address this challenge by bridging these two sectors. We decided to do this by using the well-established and structured learning strategy of problem-based learning, and the innovative technology of learning analytics to better understand the learning process.

Learning analytics is the collection, processing, analysis and reporting of data about learners and their contexts. The purpose is to understand and optimise learning and the environment in which it occurs. It can help both educators and learners make sense of the learning process and improve learners’ performance. Educators are able to monitor their learners’ progress and make decisions to scaffold or intervene when necessary based on analytics visualisations. Learners become more aware of their achievements as well as their miscomprehensions.

Our project consists of 3 main stages:

  1. Create an open data curriculum skeleton and data-driven pedagogical model:
    To implement this stage we used desk research, focus groups, face-to-face and online interviews, brainstorming sessions and questionnaires.
  2. Set up an e-learning platform and develop learning materials:
    We will utilise open source technologies to develop the e-learning platform, open source learning analytics tools as well as content on open data that will cover the produced curriculum skeleton.
  3. Implement pilots that will use the obtained results and validate their efficiency:
    For the implementation of the final stage, we will perform educational and training activities in each sector and gather evaluation results to draw conclusions.

An important challenge that we faced was the creation of the open data curriculum skeleton, because we had to consolidate results from many sources (questionnaires, focus groups, interviews) and many sectors (university students, teachers, private employees, public employees). To overcome this challenge, we created templates for questions that should be asked to each sector as well as templates that helped us structure the answers in order to achieve homogenous results.

The measureable results of the project are:

  • Open data curriculum structure that contain multiple categories and units of learning
  • Data-driven problem-based model comprised of multiple steps that can successfully structure a course on Open Data
  • Educational materials for Open Data publication and re-use
  • e-Learning platform containing all developed materials and problem-based activities
  • Learning analytics tools integrated in the project’s trial activities.

Whilst working on this project I have gained additional knowledge on the open data sources that are available. I am grateful to have met very skilled people on the subject open and linked data as well as on pedagogical strategies.

I will never forget the close cooperation and collaboration amongst all partners during the elicitation of the open data curriculum skeleton. It verified the efficient results that a strong well organised team can produce. I am lucky enough to be able to work on the latest developments in research and with so many people from various countries.

Coordinating Organisation:
Language Help