WP2 - Development

Methodology:

The WP aims at mapping the free Open Source Machine Learning Frameworks produced by the main players in the market. Then, an initial phase of research and mapping of such software will be followed by an evaluation of use on materials produced in university courses, and a comparison between the outputs provided by the tools in relation to similar data. Following a tool selection phase, in which the most suitable tools will be chosen, an aggregator will be set up to ensure the execution of the three characteristic phases of the feedback process: analysis, clustering, delivery of feedback. At the same time, a user-friendly interface will be set up to allow a human agent with no IT experience to interact with the software and its connections.

Tasks

2.1 Interface design and development. Activities: user design and development

2.2 To cluster relations in feedback between students and teachers (by considering both supervised

and unsupervised approaches) Activities: data analysis; clustering; consultation with target groups; design drafting

2.3 To define the final protocol for the software use. Activities: writing of essential steps regulating the relation agent/machine; design and development of procedures.

Deliverables

D2.1 Interface for teachers and students

D2.2 Clusters hypotheses

Key performance indicators (KPIs):

Min 6 researchers involved in the clustering exercises at M14

Min 2 fields of study covered by the clustering exercises at M12

Dissemination of results

Dissemination of results will be mostly at scientific level, through presentation of research results at conferences and papers submissions.