Personal Website: http://ww.lkl.ac.uk/manolis

Manolis Mavrikis is Senior Research Fellow in Technology-Enhanced Learning. His primary research interest lie around the representation of domain and pedagogical knowledge, and the modelling of users of Interactive Learning Environments, particularly for mathematics, with the aim to provide adaptive feedback to students and other stakeholders (e.g., teachers). 

In order to analyse students’ interactions, he combines qualitative methods with the rigour and consistency provided by statistical and machine learning techniques. See a more detailed list of his research interest at academia.edu.

Manolis  holds a PhD and an MSc in Artificial Intelligence from the University of Edinburgh (see more details in the publications section). He received his BSc in Applied Mathematics from the University of Athens where he undertook the addiitonal speciallity in Mathematics Education.

Among other LKL projects his main contributions has been in

• The MiGen project - an Exploratory Learning Environment to provide secondary education students experiences with  mathematical generalisation. See more details and publications from the project: http://www.migen.org .

• The Metafora project that designs an on-line system to foster the building of a common understanding and shared reflection among and within groups of students that work with problematic situations in Science and Math. An adaptive diagnostic system utilizing AI techniques supports students during their collaborative meaning generation and learning to learn processes. 

His previous research and development, during his part-time PhD studies, was for the  WaLLiS project, a web-based Intelligent Learning Environment for Mathematics. He was also one of the PI’s in the JISC Serving Maths Project investigating the development of a specification for mathematical questions (MathQTI ) that extends QTI.

He was employed as a researcher for the EU project LeActiveMath to develop content for first year undergraduate students and to conduct empirical studies in order to inform the design of intelligent components of LeActiveMath. He also collaborated with the researchers responsible for the undelying representation of the system to ensure interoperability with MathQTI and the knowledge representation in WaLLiS.

See an updated list in http://www.lkl.ac.uk/manolis/pubs/pubs.html