ITS2012 Key-Note Speakers
* Update: the presentations of all key-note speakers are now available online. Please scroll down to download the files.
Dr. Colin Allison
Colin Allison is a Reader in the School of Computer Science at the University of St Andrews, the oldest in Scotland. He has worked for over twenty years in two complementary research strands: the use of networked and distributed systems to support teaching and learning, and the analyses of systems and networks when loaded by distributed learning environments: Quality of Service for Quality of Experience. His approach to research has always been to work with colleagues to build, deploy and evaluate learning environments rather than simply imagine them. Examples include Finesse (Finance Education in a Scalable Software Environment), TAGS (Tutor and Groups Support), MMS (Module Management System), FIGS (Finesse Grid Services), WiFi Virtual Laboratory and TCP Live. Most recently his attention has focussed on the great potential of open source immersive 3D multi-user virtual worlds for education, and the challenges they present to current client, server and network technologies when doing so. He is a member of the Engineering and Physical Science Research Council (EPSRC) Peer Review College; the Institute of Electronic and Electrical Engineers (IEEE), including the Computer, Communications and Education Societies; the Association of Computing Machinery (ACM), including SIGOPS (Operating Systems), SIGCOMM (Networks), and SIGCSE (Computer Science Education); and the Higher Education Academy for Computer and Information Sciences (HEA ICS).
"Open Virtual Worlds for Exploratory Learning"
Continuing advances and reduced costs in computational power, graphics and network bandwidth have led to 3D immersive multi-user virtual worlds becoming increasingly accessible while offering an improved and engaging quality of experience. Many educators have seen the potential of virtual worlds for learning activities since their appearance as a new type of Internet service ten years ago. Much initial use involved recreating familiar educational situations such as online tutorial groups, presentations and lectures in these novel virtual worlds, albeit enhanced by the exotic nature of the surroundings and the usersʼ avatars. Although this type of use is relatively lightweight educationally it is clear that students enjoy the nature of the unusual social settings and "in-world" experiences, and engage positively with the technology. Virtual worlds are now moving into a new phase which make them much more suitable for educational use. In particular there are now open source platforms which enable educators to take full control of the behaviour and content of a virtual world. This talk reports on the educational benefits from the new generation of open virtual worlds. The breadth and depth of the potential of open virtual worlds is illustrated by example learning environments from both the STEM and the Cultural Heritage domains. WiFi Island shows how interactive multimedia can be augmented by virtual laboratories; Routing Island illustrates how complex algorithms can be interacted with and visualised in totally new ways; detailed reconstructions of important historical buildings which are now in ruins are illustrated by an 8th century Byzantine Basilica at Sparta and St Andrews Cathedral as it was in the 14th century. Of course there are challenges: programmability, scalability, support for developers, creating appropriate management facilities, how to distribute and deploy 3D learning environments; how to adapt to the network Quality of Service to support a suitable Quality of Experience for end users. Our experience of developing and deploying these exploratory learning facilities allows us to explain how to address both the needs of educators and the technical challenges encountered when adopting open virtual worlds for teaching and learning.
Emeritus Prof. Maria Grigoriadou
Maria Grigoriadou received the BA degree in physics from the University of Athens in 1968 and the DEA and doctorate degrees from the University of Paris VII in 1972 and 1975, respectively. She is now Emeritus Professor in education and language technology and head of the Education and Language Technology Group, Department of Informatics and Telecommunications, University of Athens. Her current research interests include the areas of adaptive learning environments, Web-based education, ITS, educational software, natural language processing tools, and computer science education. She was the recipient of eight awards, has participated in 15 projects, and has four invited talks to her credit. She has 47 publications in international journals, 12 in international book chapters, 200 in proceedings of international conferences and more than 1200 citations to her research work. Emeritus Professor Grgoriadou is a member of IEEE, AACE, IADIS, EDEN, Kaleidoscope and LeMoRe.
"From learning theories to learning environments"
Innovations in education may emerge from using familiar technologies in innovative ways or from the development of new e-learning environments. Learning Environments designed on modern learning theories, aim at enhancing the interaction with learners in order to support them fullfil their learning goals in multiple ways: (i) introducing students to a wide range of materials, activities and learning tasks, (ii) supporting students in experimentation/observation, (iii) encouraging participation in collaborative activities and facilitate students’ communication, (iv) providing students the appropriate means to externalise their thoughts, to elicit any misconceptions and restructure their knowledge.
A variety of learning environments/tools, some of them with adaptive capabilities, have been lately developed based on various learning theories in order to promote pedagogically meaningful and effective interactions with learners and enable them to take control over their own learning. Alternative designs for learning have been adopted focusing on the design of content including multiple representations targeted at various levels of perfomance and learning styles, on collaborative learning, on assessment as an opportunity for learning, on text comprehension, etc. In the keynote speech the following learning environments will be presented and discussed as representatives of learning environments inspired by alternative learning theories.
INSPIRE delivers personalised courses and supports learners through the interaction taking into account their individual characteristics such as knowledge level and learning style. INSPIRE allows learners to freely explore the available content that consists of a variety of modules ranging from expository examples to problems that promote learners to explore the underlying concepts, in order to attain various levels of performance. Further more INSPIRE provides learners with visual representations of their interaction behaviour aiming to enhance awareness about their learning strategies.
SCALE environment supports learners to work on individual and collaborative activities taking into account their knowledge level, to collaborate in synchronous or asynchronous mode, to access informative and tutoring feedback components according to their preferences. The design principles of SCALE lie on the Activity Theory interweaving individualized with collaborative learning.
ALMA supports and assesses learners’ text comprehension through a series of activities such as: text recall, summaries, text-based, bridging inference, elaborative inference, problem solving, case studies, active experimentation and sorting tasks. ALMA actively engages students in the learning process taking into account their learning preferences and proposing activities aligned with the Kolb cycle. ALMA also takes into account students’ background-knowledge in order to propose the appropriate text version from four versions of a text with the same content but different cohesion at the local and global level. The design rational of ALMA is based on Kintsch’s Construction-Integration model for text comprehension.
The cognitive tool Semandix constitutes a semantic database of Computer Science concepts based on the text comprehension model of Denhière and Baudet, that extends existing cognitive tools, such as databases and concept mapping tools, as well as semantic computational dictionaries and natural language processing tools. Semandix makes diagnosis of learners’ Computer Science concepts comprehension and provides appropriate feedback with information regarding the cognitive categories appearing in Computer Science texts, in order to support learners on scientific knowledge construction.
Professor Dr. Sheizaf Rafaeli
Professor Rafaeli (B.A., Haifa University, M.A. Ohio State University, M.A., Ph.D., Stanford University) is Director of the the Sagy Center for Internet Research (InfoSoc, the Center for the Study of the Information Society) (1998 - present), and former Head of the Graduate School of Management (2005-2011), University of Haifa Israel. He also leads the "Games for Exectives Project" and serves as Director in a series of public interest organizations.
Prof. Rafaeli has published in journals such as Behaviour and Information Technology, Communication Research, Computers and the Social Sciences, Computers and Human Behaviour (CHB). He is co-editor, along with Fay Sudweeks and Margaret McLaughlin, of Network and NetPlay: Virtual Groups on the Internet published by MIT Press, 1998.
He has served as co-coordinator of the international ProjectH and is proud of initiating and setting up the SHIL (Citizen's Advice Board) online service. He is currently member of several editorial boards. Prof. Rafaeli is a long time member of the Stockholm International Challenge Jury for Information Systems' Projects.
"Online Games and Sharing in Learning"
In this talk Prof. Rafaeli will elaborate on the development, implementation and evaluation of the use of online tools for learning, with special attention to games and gamification, sharing and collaboration. His experience is mostly at the University and upper level high school levels, and is focused on the teaching and learning of particular disciplines, But the opportunities and issues are widespread, almost universal. The introduction of networked tools to enable Play and Collaboration is a major challenge for intelligent tutoring systems research. He will discuss some generic and theoretical issues, including Interactivity and Subjective Value of Information, report on recent findings, and describe the practical implications of designing and adopting these tools and practices for learning.
"Online Games and Sharing in Learning"
In this talk Prof. Rafaeli will elaborate on the development, implementation and evaluation of the use of online tools for learning, with special attention to games and gamification, sharing and collaboration. His experience is mostly at the University and upper level high school levels, and is focused on the teaching and learning of particular disciplines, But the opportunities and issues are widespread, almost universal. The introduction of networked tools to enable Play and Collaboration is a major challenge for intelligent tutoring systems research. He will discuss some generic and theoretical issues, including Interactivity and Subjective Value of Information, report on recent findings, and describe the practical implications of designing and adopting these tools and practices for learning.
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Prof. Dr. Norbert M. Seel
Prof. Seel is chair and professor for research on learning and instructional design as well as the head of the Department of Educational Science at the Albert-Ludwigs-University at Freiburg, Germany. His research interests include model-based learning and thinking, inductive reasoning and complex problem solving, the investigation of exploratory learning within technology-enhanced environments, and processes of decision making in instructional design.
Dr. Seel has published 18 books, among them the textbook "Psychology of Learning (2nd ed.), as well as more than 180 refereed journal articles and book chapters in the area of cognitive psychology, learning research and instruction. He is the editor-in-chief of the Encyclopedia of the Sciences of Learning.
"The Three Learning Sciences (Biological, Artificial, Human)"
Learning is existential, and so its study must be complex and interdisciplinary. Over the past centuries, researchers from different fields have developed many theories to explain how humans and animals learn and behave, i.e., how they acquire, organize, and deploy knowledge and skills. Basically, learning is defined as a relatively permanent change in behavior and/or in mental associations due to specific experiences. Learning is a response to environmental requirements and different from biological maturation, which, however, is a fundamental basis for learning.
"The Three Learning Sciences (Biological, Artificial, Human)"
Learning is existential, and so its study must be complex and interdisciplinary. Over the past centuries, researchers from different fields have developed many theories to explain how humans and animals learn and behave, i.e., how they acquire, organize, and deploy knowledge and skills. Basically, learning is defined as a relatively permanent change in behavior and/or in mental associations due to specific experiences. Learning is a response to environmental requirements and different from biological maturation, which, however, is a fundamental basis for learning.
Beyond psychology and biology, disciplines such as anthropology, sociology, and education focused on the topic of human learning in the course of the past centuries. However, one of the most important innovations for research on learning resulted from the emerging computer sciences and their focus on machine learning. Machine learning usually refers to changes in systems that perform tasks associated with artificial intelligence (AI). Many techniques in machine learning are derived from the efforts of psychologists to make their theories of animal and humanlearning more precise through computational models. Conversely, it seems that the concepts and techniques being explored in the field of machine learning also illuminate certain aspects of the biology of learning. Accordingly, closely related to machine learning is also the study of human and animal learning in psychology, neuroscience, and related fields.
In my speech I will focus on the biological foundations of learning, mainly discussed in terms of the interplay between assimilation and accommodation that correspond the basic functions of schemas and mental models. Second, I will focus on cumulative or incremental learning as an example to demonstrate basic correspondences between theories of human and artificial learning. Finally, I will discuss practical implications for interdisciplinary research on human and artificial learning.
| Attachment | Size |
|---|---|
| Presentation Allison ITS2012.pdf | 13.81 MB |
| Presentation Grigoriadou ITS2012.pdf | 2.54 MB |
| Presentation Rafaeli ITS2012.pdf | 5.68 MB |
| Presentation Seel ITS2012.pdf | 1.05 MB |
