Invited Speech 1 - Oct. 7, 2013 (Mon.)
Community Learning Analytics - Challenges and Opportunities
Dr. rer. nat. Ralf Klamma
RWTH Aachen University
E-Mail: klamma@informatik.rwth-aachen.de
7 October 2013, 10:40-11:30 Hill1, H Resort
Abstract of Speech
Learning Analytics has become a major research area recently. In particular learning institutions seek ways to collect, manage, analyze and exploit data from learners and instructors for the facilitation of formal learning processes. However, in the world of informal learning at the workplace, knowledge gained from formal learning analytics is only applicable on a commodity level. Since professional communities need learning support beyond this level, we need a deep understanding of interactions between learners and other entities in community-regulated learning processes - a conceptual extension of self-regulated learning processes. In this presentation, we discuss scaling challenges for community learning analytics and give both conceptual and technical solutions. We report experiences from ongoing research in this area, in particular from the two EU integrating project ROLE (Responsive Open Learning Environments) and Learning Layers (Scaling up Technologies for Informal Learning in SME Clusters).
Invited Speech 2 - Oct. 7, 2013 (Mon.)
Affective Learning: Evidences from Neuroscience
Prof. Chia-Ju Liu
Dean of College of Science, National Kaohsiung Normal University
Kaohsiung,Taiwan
E-Mail: chiaju1105@gmail.com
7 October 2013, 11:30-12:20 Hill1, H Resort
Abstract of Speech
Many researches indicated that the cognitive dimensions could promote students’ learning achievements, but to improve the whole efficacy of science education must integrate the consideration of students’ learning and teachers’ teaching with affective dimensions. The difficulties of affective dimensions measurements are been solved by using neuroscience technologies. In this presentation, the concept of affection and categorizes the affective dimensions in science education will be discussed. The evidences from neuroscience which included topographic EEG mapping, the α and δ power value, and the P300 amplitude and latencies of frontal lobe will be illustrated in the issues of affective learning.