«Learning Analytics for Large Scale Data»
Alexandra CristeaProfessor, Head of the Innovative Computing research group and Deputy Head at the Computer Science Department, Advisory Board Member at the Ustinov College, Durham University. (English)
Abstract
Learning Analytics has many definitions, but one of great simplicity and elegance yet clarity is ‘collecting traces that learners leave behind and using those traces to improve learning’ [Eric Duval]. More recently, however, the interest has moved towards ‘big data’, or large scale data, in all aspects of our lives, including for education and learning. This talk will discuss various recent approaches to learning analytics implemented and published by our AIHS research group (Artificial Intelligence and Human Systems) at Durham Computer Science. It will include processing of and analytics based on MOOC data, large-scale questionnaires, private versus public channels of communication in online or blended courses, with applications such as in predicting learner dropout, gamification approaches as well as temporal sentiment analysis, or instructor intervention need.
Bio
Alexandra I. Cristea is Professor, Head of the Innovative Computing research group and Deputy Head at the Computer Science Department, Advisory Board Member at the Ustinov College, Durham University. She is N8 CIR Digital Humanities team lead for Durham. She is Honorary Professor at the Computer Science Department, Warwick University. Her research includes web science, learning analytics, user modelling and personalisation, semantic web, social web, authoring, with over 300 papers on these subjects (over 4000 citations on Google Scholar, h-index 33). Especially, her work on frameworks for adaptive systems has influenced many researchers and is highly cited (with the top paper with over 200 citations). She was classified within the top 50 researchers in the world in the area of educational computer-based research according to Microsoft Research. Prof. Cristea has been highly active and has an influential role in international research projects. She has led various projects – Weizman Institute funded JANET (Joint Lab in Learning Analytics for Personalised Science Teaching) project (2020-2022); Newton funded workshop on Higher Education for All (’14-’18), Santander funded Education for disadvantaged pupils (’14-18′), Warwick-funded project APLIC (’11-;12), EU Minerva projects ALS (06-09) and EU Minerva ADAPT (’02-’05); as well as participated as university PI in several EU FP7 projects – BLOGFOREVER (’11-’13), GRAPPLE (’08- ’11), PROLEARN (’07) and as co-PI in the Warwick-funded Engaging Young People with Assistance Technologies (’13-’15) also featured by the BBC. Recently she has taken giving back to the community to a different level, with the project TechUP (2019-2020) training 100 women in computer science from various (BAME) backgrounds.
