What is MAPSEL?
MAPSEL is a short 1-year research project exploring new techniques and tools for mining and analyzing social data in learning technology, funded by the Spanish Ministry of Science and Innovation (ref. TIN2009-14164-C04-01) and lead by Dr. Miguel-Angel Sicilia, Information Engineering Research Unit. A new proyect called MAVSEL is a follow-up of MAPSEL.
Rationale and objectives
Learning usually takes place in social settings, with the direct or indirect interaction of learners with peers or tutors. A variety of data is automatically stored as learners and tutors interact between them or with different kinds of resources as learning objects in diverse technology components, including Learning Management Systems, learning object repositories, Wikis and other Web 2.0 tools and social networking sites. This enables new forms of empirical research that were difficult to conduct some years ago.
MAPSEL has the following concrete objectives:
- Elaborate a model that provides a framework for data analysis in educational settings,
informed by theories about the contribution of social interaction to learning.
- Study and analyze elements of existing theories of learning and instructional design theories that consider social interaction as an essential element, identifying how they could be analyzed through methodological and computational tools using the data generated by LMSs and other tools.
- Elaborate a conceptual model and its associated formal representation for the theories selected and their relation to the data that can be gathered.
- Analyze and develop a common schema for different data sources related to on-line educational settings, and establish the link of such data with the relevant theoretical elements identified.
- Select, evaluate and compare different methodological and computational techniques that can be applied to the analysis and subsequent decision making informed by the theories identified.
- Study, select and evaluate data mining and machine learning tools for that purpose.
- Study, select and evaluate social network analysis and collaborative filtering tools as mechanisms for building models of the social structure of the participants in the educational setting.
- Devising the architecture of a software framework integrating the different aspects of educational data and theories addressed.