Leading Research Projects in USA & European Union A Brief Survey

NSF Science of Learning Centers US$25 millions NSF grant Five years Initialed from Fall of 2004 Sponsored 4 Centers

Science of Learning Centers (SLGs) 1. The Learning in Informal and Formal Environments (LIFE) Center 2. The Pittsburgh Science of Learning Center (PSLC) 3. Center of Excellence in Education, Science and Technology (CELEST) 4. Center for Cognitive and Educational Neuroscience (CCEN)

The Learning in Informal and Formal Environments (LIFE) Center To understand and advance human learning through a simultaneous focus on implicit learning informal learning & formal learning

People & Partners University of Washington Cognitive Studies in Education John Bransford, Philip Bell, Reed Stevens, Nancy Vye University of Washington Institute for Learning & Brain Sciences (I-LABS) Pat Kuhl, Andrew Meltzoff, Maritza Rivera-Gaxiola Stanford University Stanford Center for Innovations in Learning (SCIL) Brigid Barron, Roy Pea, Dan Schwartz Stanford University Center for the Study of Language and Information Byron Reeves SRI International Center for Technology and Learning Nora Sabelli

LIFE Center Organization

LIFE Long and Life Wide

Research Program ECO: Education, Collaboration, and Outreach Strands of Research on Human Learning Strand 1: Implicit Learning and the Brain Represents cognitive neuroscience Strand 2: Informal Learning Represents the socio-cultural tradition Strand 3: Formal Learning Represents the cognition and technology tradition Across-Strand Research on Learning

Mechanisms for Promoting Crosstalk among Research Strands Intellectual exchanges Conceptual collisions Spontaneous debates Arise regarding topics of interest across Research Strands Hot topic discussions and workshops Scheduled discussions that occur weekly on specific interdisciplinary topics Signature projects Inter-strand, collaborative research projects

Students Exchange LIFE Research Internships for Graduate Students Support up to four graduate students to spend several months at the LIFE Center Students will be asked to Participate in ongoing LIFE research activities and other relevant center activities Develop a detailed plan for a new learning study that could be conducted when they return to their home institution in ongoing compatible interdisciplinary goals

Recommended Websites SCIL, Stanford Stanford Center for Innovations in Learning SRI International Center for technology in learning TELS Center for Technology Enhanced Learning in Science Informal learning Exploratorium museum Center for Informal Learning and Schools (CILS) Daniel Schwartz’s lab Marcia C. Linn’s Website

Pittsburgh Science of Learning Center (PSLC) Support research on robust learning learnlab.org

People Ken Koedinger, Human-Computer Interaction Institute, CMU Kurt VanLehn, Dept. of Computer Science, University of Pittsburgh Micki Chi, Dept. of Psychology, University of Pittsburgh Lauren Resnick, Learning Research and Development Center, University of Pittsburgh etc.

Partners Carnegie Mellon University HCI: Human Computer Interaction Institute LTI: Language Technologies Institute SCS: School of Computer Science Carnegie Mellon University Psychology University of Pittsburgh LRDC: Learning Research and Development Center IFL: Institute for Learning PACT: Pittsburgh Advanced Cognitive Tutor Center Carnegie Learning

Multi-direction payoffs of the Pittsburgh tradition

What is LearnLab? A national resource for learning research that includes Authoring tools for online courses, experiments, and integrated computational learner models Support for running in vivo learning experiments Longitudinal microgenetic data from entire courses Data analysis tools, including software for learning curve analysis and semi-automated coding of verbal data

Purpose & Mission Studying Robust Learning with Learning Experiments in Real Classrooms The goal is to produce results that survive rigorous experimentation with laboratory-quality methods in real classroom settings This paradigm is called in vivo learning experimentation The rigorous classroom methodologies include design research, case studies, and ethnography

Research questions 1.Co-training. When, how, and why do students' use of multiple inputs, representations or strategies facilitate learning by providing an avenue for "self-supervised" learning that goes beyond learning supported by teacher and peer feedback? 2.Dialogue. When, how, and why does classroom talk and tutorial dialog, whether by human or computer, promote robust learning? 3.Refinement. How do learners determine the causal connections between cues in the environment, their actions, and desired knowledge and how can instructional support and feedback facilitate learners in making such connections? 4.Fluency. How does more isolated learning of knowledge components interact with learning within larger authentic performances and how can instruction can support such interactions to yield more fluent and robust learning?

The PSLC Theoretical Framework Focuses on explaining and predicting robust learning Learning is robust if the acquired knowledge or skill meets at least one of the following three criteria Retention: It is retained for long periods of time, at least for days and even for years. Transfer: It can be used in situations that differ significantly from the situations present during instruction. Future Learning: It accelerates future learning. That is, when related instruction is presented in the future, this knowledge allows them to learn more quickly and effectively learn from it.

Robust Learning Process Denotes both an instructional process that is intended to cause robust learning outcomes and the learning/cognitive process that it is intended to promote Coordinative learning Interactive communication Fluency and refinement

Coordinative learning cluster Visual-Verbal Learning in Geometry (Aleven & Butcher) Tutoring a meta-cognitive skill: help-seeking (Aleven & McLaren) Handwriting in algebra learning (Anthony, Yang & Koedinger) Note-taking technologies (Bauer & Koedinger) Knowledge component construction vs. recall (Booth, Siegler, Koedinger & Rittle-Johnson) Adding diagrams of acid-base solutions (Davenport, Klahr & Koedinger) Co-training of Chinese characters (Liu, Perfetti, Mitchell & Wang) Co-training in the self-correction of speech errors (McCormick, O’Neill & Siskin) Personalization and example studying in chemistry (McLaren, Koedinger & Yaron) Understanding culture from film (Ogan, Aleven & Jones) Does learning from examples improve tutored problem solving? (Renkl, Aleven & Salden)

Interactive communication cluster Deep, rhetorical questions during example studying (Craig & Chi) Does it matter who generates the explanation? (Hausmann & VanLehn) Self-explanation vs. interactive dialogue (Katz) Conceptual vs. quantitative applications of knowledge (Katz) Peer tutoring scripted collaboration (McLaren, Rummel & Spada)

Fluency and refinement cluster Successful recall vs. unsuccessful recall plus feedback (de Jong, Perfetti, DeKeyser) Implicit vs. explicit instruction on word meanings (Juffs & Eskenazi) Video vs. audio-only training of pronunciation (Liu, Perfetti & Wang) Basics skills training (MacWhinney) First language effects on second language grammar acquisition (Mitamura) Optimizing the practice schedule (Pavlik) Semantic grouping during vocabulary training (Tokowicz) Mental rotations during vocabulary acquisition (Tokowicz) Visual enhancement of Chinese tone learning (Wang, Lui & Perfetti)

Three pathways to robust learning Rederivation Adaptation Self-supervised learning

LearnLab Courses Two high school math courses Algebra and Geometry Two college-level science courses Physics and Chemistry Three college-level language courses Chinese, French, and English as a Second Language Courses incorporate intelligent tutoring systems and face-to-face and computer-mediated peer, tutor, and instructor interactions

Center of Excellence in Education, Science and Technology (CELEST) Brain & Learning Stephen Grossberg, Boston University

Mission of CELEST combine training and research on quantitative behavioral and brain modeling of normal and abnormal learning during perception, cognition, emotion, and action with interdisciplinary cognitive and neuroscience experiments

Center for Cognitive and Educational Neuroscience (CCEN) Michael Gazzaniga, Dartmouth College

Mission of CCEN work to understand the brain mechanisms of learning as well as build collaborations to implement learning techniques among K-12 students and teachers

Kaleidoscope Shaping the scientific evolution of Technology Enhanced Learning

Directors Scientific Director Nicolas Balacheff CNRS, France Deputy Scientific Director Mike Sharples LSRI University of Nottingham, UK

Summary of Kaleidoscope Project type: Network of Excellence Start date: 1 January 2004 Duration: 48 months EU Funding: EUR 9,350,000 (USD 11 million) Partners: 76 organizations 91 research units from 24 countries More than 1095 researchers

What is Kaleidoscope? A network of leading researchers and research laboratories from across Europe Working in the field of Technology Enhanced Learning (TEL)

What is Kaleidoscope Doing? Integration Integrating the leading research teams in the field, who work collaboratively across educational, computer and social sciences Transformation Transforming the quality and reach of the learning experience.

Fostering Innovation and Creativity Kaleidoscope fosters innovation and creativity through the development of New technologies Methodologies and concepts Defining the challenges and solutions for interdisciplinary research

Goal Inform knowledge transfer between education, industry, and the wider society. Build a dynamic knowledge-based economy for Europe, engaging with social, economic and political stakeholders at all levels.

Research Issues Collaborative, mobile and inquiry learning Developing software for professional learning and training Design and compatibility of interactive learning objects Valid social, epistemic and technological factors in learning Blended learning: concepts and models Contexts of learner interactions Informal learning Authoring and learning systems Theory and investigation

Three Types of Research at a European Level Special Interest Groups (SIGs) Communities of individual researchers European Research Teams (ERTs) Clusters of research institutions Integrate varying research approaches in order to build common research standards Jointly-Executed Integrated Research Projects (JEIRPs) Focused, short-term, multidisciplinary research projects Common research programs that facilitate the cross-fertilization of the partners’ research.

Partners Distribution in EU

Partners Distribution Worldwide

Kaleidoscope Community in 2006 European Research Teams (ERTs) Special Interest Groups (SIGs) Jointly-Executed Integrated Research Projects (JEIRPs)

PROLEARN Network of Excellence

Mission To bring together the most important research groups in the area of professional learning and training, as well as other key organizations and industrial partners, thus bridging the currently existing gap between research and education at universities and similar organizations and training and continuous education that is provided for and within companies.

SOCRATES - MINERVA ODL and ICT in Education mes/socrates/minerva/index_en.html

Mission Enabling citizens of the European Union to take advantage of an open European area for cooperation in education. Seeking to promote European co-operation in the field of Open and Distance Learning (ODL) and Information and Communication Technology (ICT) in education.

Elearning in Europa elearningeuropa.info An initiative of the European Commission A portal established by the European Commission Managed by the Directorate-General for Education and Culture Multimedia Unit.

Mission To promote the use of multimedia technologies and Internet at the service of education and training.

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