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b) Learning analytics, educational data mining
The Open University of Catalonia (UOC) is an e-learning university, which the main headquarter is located in Barcelona, Spain. With more than 50.000 students, it aims at innovating and improving the different tools and methodologies used to support the learning and teaching processes. In this sense, the UOC is preparing a proposal that endeavours to define and test a set of user-friendly, personalised and innovative tools which will improve the practise of teaching and learning. The interrelation between learning analytics methods, user needs and requirements and cognitive models will be used into the definition and conceptualization of these tools.
* Preferably not Spanish institutions (updated 20/12/12)
State-of-the-art data mining technologies to mine the extensive amount of information that is acquired during a distant learning process. The goal of this mining process will be to make available a wide range of detailed information regarding the learning activity and suggestions for the agents involved in the learning process.
Interviews to students and teachers to gather their needs regarding their learning processes in order to know what kind of variables do students and teachers consider key components in the personalization and improvement of the learning processes. This qualitative data will complement the data obtained by the mining processes.
Cognitive models: A set of cognitive models of learning styles will be unfolded in order to configure the theoretical framework of the experience.
As a result, a set of tools will be provided, in which relevant data will be displayed to teachers and students for the personalization and enhancing of learning and teaching. In the case of teachers, the set of tools will provide them with personalised information on the learning features of each of his/her students. These learning features will provide an approximate matching of the students to cognitive models in order to help teachers to identify the student’s learning style, the student’s precise situation in the learning process and a set of actions that can be taken in order to improve the student's learning experience and the professor's teaching experience at that precise point of the learning process. On the other hand, the set of tools will also provide students with personalised information on their learning process and suggestions that will help students to be more conscious of their knowledge and their progress within the learning process and improve their learning experience.
We will use open source information to implement services over a data architecture that will make these data available to third parties through open standards.
Experts in learning analytics
Construction of a map of available data in the educational institutions to be mined. These data will ideally consists of an extremely rich set of inputs regarding the students and teachers' learning and teaching activity both in a distant and blended learning scenario.
Identification of correlations among the mined data, in order to extract learning patterns and variables, making possible to understand the learners knowledge, progress and learning environment by matching it with cognitive models of learning.
Experts in data mining and NLP
To extract relevant information from students and teachers' recorded activity, including Natural Language Processing for the analysis of textual data.
Experts in cognitive models and learning styles
A set of cognitive models of learning styles will be unfolded in order to configure the theoretical framework of the experience.
Experts in open source development and learning analytics standards
Distance learning universities
As a data source for the data mining processes.
To hold pilot test
Universities, SMEs, distance learning universities, technology centres, research centers.
The ideal-ist2018 project is funded by the European Commission under the Leading Industrial Enabling Technologies ICT theme, of the seventh H2020 – Research & Innovation Framework Programme. Any options expressed in these pages are those of the author/organisation and do not necessarily reflect the views of the European Commission.