Xaverian College: Seeing the long term benefit of personalised learning with bespoke VLE

Xaverian College has created a bespoke web-based solution for the academic, pastoral, managerial and administrative requirements of the College that is accessible to all staff and students. Their VLE/ILP intranet system is cutting edge as it offers a remarkable degree of integration because of its holistic approach and is very ‘student-friendly’.

Chelmsford College: Full circle – using systems integration to enhance observation, appraisal and CPD

Chelmsford College has created an observation, appraisal and continuing professional development (CPD) cycle by successfully integrating a collection of bespoke web-based systems together within its intranet. Students have benefitted from improved teaching and learning because of the rapid, transparent and thorough cycle of staff being observed, appraised and given appropriate CPD. The College has also saved time and money by being able to use single-source data to schedule observations, appraisals and CPD to individuals' needs.

Lancaster and Morecambe College: Uses serious computer games as a teaching tool

John Latham, International Projects Co-ordinator at Lancaster and Morecambe College (LMC), got involved with the project Serious Computer Games as a Teaching Tool (SCOGATT) after using the game EnerCities with his students. The web based platform at www.scogatt.eu serves as a One Stop Toolkit for vocational teachers and trainers who want to use serious computer games (SCG) in their teaching environments but might need a helping hand. There they will be able to find a compendium of serious games, SCOGATT pilot results, teacher reports and the exemplar games, EnerCities.

MIRACLE Project Plan

Social scientists have used agent-based models (ABMs) to explore the interaction and feedbacks among social agents and their environments. The bottom-up structure of ABMs enables simulation and investigation of complex systems and their emergent behaviour with a high level of detail; however the stochastic nature and potential combinations of parameters of such models create large non-linear multidimensional “big data,” which are difficult to analyze using traditional statistical methods. Our proposed project seeks to address this challenge by developing algorithms and web-based analysis and visualization tools that provide automated means of discovering complex relationships among variables. The tools will enable modellers to easily manage, analyze, visualize, and compare their output data, and will provide stakeholders, policy makers and the general public with intuitive web interfaces to explore, interact with and provide feedback on otherwise difficult-to-understand models.