Berkeley cyberlearning 030811_final

Editor's Notes

• #2: - An intentional echo of Vannevar Bush’s founding document for the NSF –his 1950 volume: Science: The Endless Frontier. - Why? Because cyberlearning IS an endless frontier- we will never be done – the content will always be advancing; the representational and computational technologies and associated user experiences with content with which we learn will always be developing – as will the social and organizational arrangements in which we find ourselves doing this learning. With our endless ability to continue to innovate new designs for how we learn the complexities of the evolving disciplines – we will never be done. - Cyberlearning WILL be an endless frontier.
• #4: NOTE – Why STEM focus? On the community point - The US “scene” in learning sciences and technologies programs isnt ready to be responsive to the Moore’s Law, Metcalfe’s Law and other accelerative drivers of technology developments in society today. It does not know yet how to deal with Google’s Map-Reduce software framework for large scale distributed data processing, Amazon Elastic Cloud Computing, or many other cyberinfrastructures. It is rarely developing in iOS, Android, Windows mobile OS’s – or on web development in AJAX or Flex paradigms that are shaping user experiences in today’s expansive web. - Not all of these problems admit of technological solutions – but ICT designs could catalyze advances and accelerate needed transformations.
• #6: Imagine a high school student in 2015. She’s grown up in a world where learning is as accessible through technologies at home as it is in the classroom, and digital content is as real to her as paper, lab equipment, or textbooks. **At school, she and her classmates engage in creative problem-solving activities by manipulating simulations in a virtual laboratory or by downloading and analyzing visualizations of real-time data from remote sensors . **Away from class, she has seamless access to school materials & homework assignments using inexpensive mobile technologies . She continues to collaborate with her classmates in virtual environments that allow not only social interaction with each other but also rich connections with a wealth of supplementary content. ** Her teacher can track her progress over the course of a lesson plan and compare her performance and aptitudes across a lifelong “digital portfolio,” making note of areas that need additional attention through personalized assignments and alerting parents to specific concerns. While in the NSF taskforce scenario the learning environment design is driven from school standards and topics, a comparable scenario could be driven from a peer group interested in advancing their learning, as in creating game mods to achieve higher levels of massively multiple player game play, or a community might be learning how to assess water quality and consider environmental justice issues associated with pollution being situated in the low-income neighborhoods.
• #7: Enter Cyberlearning – as a new innovative force to address some of these problems for STEM education. Evokes cyberinfrastructure: “if infrastructure is required for an industrial economy, then we could say that cyberinfrastructure is required for a knowledge economy.” “ Cyber” also evokes Wiener’s (1948) “cybernetics” — built on the Greek term for “steering” as a way to signal the intertwined tapestry of concepts relating the goal-directed actions, predictions, feedback, and responses in the physical, social, engineering systems for which cybernetics was to provide an explanatory framework .
• #8: Cyberlearning has tremendous potential right now because we have powerful new technologies, increased understanding of learning and instruction, and widespread demand for solutions to educational problems. Over the last 10-20 years, the design of technologies and our understanding of how people learn have evolved together, while new approaches to research & design make the development and testing of technologies more responsive to real-world requirements and learning environments. Visual programming languages for children Microworlds for learning computational thinking in science, technology, engineering and mathematics Intelligent tutoring systems in algebra, geometry, programming, chemistry, stat’s, foreign languages Microcomputer-based laboratories and handheld computing versions of probeware and sensors for capturing and graphing data during scientific inquiry Online learning communities for teachers and learners in many subject domains Data visualization environments for examining and understanding complexity in the STEM disciplines Educational robotics STEM learning games and virtual worlds
• #9: - These developments promise widespread access to increasingly sophisticated technologies and advances in understanding of how individuals learn - which should combine to provide a stunning opportunity to transform education worldwide. These advances are extremely important since we cannot even physically construct the needed universities, schools, and classrooms to serve education needs, especially in the developing world. Right in front of our eyes, the learning and educational platform of the century ahead is emerging, and it is not the classroom or the school, although I deeply hope that schools and classrooms and educators can figure out how to harness these resources. - Surprising result to many is that…
• #10: ** UPDATE OR DUMP THIS SLIDE** Note her concurrent open channels of the cell call, myspace social network, iPod music player, several books and television. - Yet many of today’s digital natives, who exploit these tools to understand and learn on their own, often find schools unchanged from those of their parents and certainly unconnected from their real time ties to the web for information and their friends that they experience outside school.
• #11: A Nielsen survey indicates that at the end of 2010, nearly a third of US mobile users had smartphones, with the installed base evenly tied between Apple, RIM, and Android licensees. Projections are this percentage will double in two years and that prices will drop below $50.
• #12: A major observation today is that ICT - information and computing technologies - has become ubiquitous for everyday use in developed nations, with huge and relatively unexplored implications for education. - Over 2 BILLION people have access to the internet (over a 600 million new people since we published our cyberlearning report in Summer 2008). Nearly 5 Bil people have a mobile phone. Proportion of these mobiles that are on broadband networks is rapidly growing – in Europe, 50% penetration by 2013. Professional technologies such as desktop and laptop computers have begun to merge with personal technologies such as mobile phones, PDAs, music players, digital video recorders, digital cameras, TVs – changing the HOME MEDIA ECOLOGY - Cultural change: A new era of Web-enabled applications built around user-generated or user-manipulated content - wikis, blogs, podcasts, sites for sharing video and photos & social networking, virtual worlds – new value arising from harnessing collective intelligence for a ‘digital commons’ – not only being an AUDIENCE to content but a CREATOR
• #13: A major reason why we are spending so much more time online is that we collectively have been making that information much more useful to us.
• #15: And this is not counting the past 5 yrs of innovation such as the iPod, iPhone and iPad, and Android phones.
• #16: Grown since these graphics were developed last year – 35 hrs of video are now uploaded every minute into Youtube (11/10); 700 billion playbacks in 2010.
• #17: Date as of 3/11 on FB; Smartphones will comprise themajority of all phones sold in 2012.
• #18: I know want to shift to provide a historical framing to the future of cyberlearning… The centrality of mediation is vital for learning futures, as we see the historical framing of our current moment.
• #19: I know want to shift to provide a historical framing to the future of cyberlearning… The centrality of mediation is vital for learning futures, as we see the historical framing of our current moment.
• #22: This figure depicts historical advances in the communication and information resources available for human interaction. Basic face-to-face interaction at the most basic level required no resources to mediate communication. The second wave of resources offered symbol systems such as written language, graphics, and mathematics but introduced a mediating layer between people. The communication revolution of radio, telephony, television, and satellites was the third wave. The outcomes of the fourth wave—networked personal computers, web publishing, and global search—set the stage for the fifth wave of cyberinfrastructure and participatory technologies that we reviewed. In sum, the set of actions and interactions people consider possible has changed with each new wave of mediating technologies, from writing to telephony to the Internet and now cyberinfrastructure. We can now interact at a distance, accessing complex and useful resources in ways unimaginable in early eras – changing possible goals, intentions for action and means for achieving them.
• #24: • The opportunities for cyberlearning need to be situated in the context of growing realizations of the importance of learning outside of school • Our unique LIFE focus - to deeply examine the special roles of the social in learning. Learning in K-12 settings under 20% awake time – relatively unexplored sea of blue for learning the other 80% time. Greater potential than realized for harvesting “funds of knowledge” from people’s learning experiences outside of classrooms. Many more forms of productive learning are found and experienced outside school than those exploited by schooling today. • We can imagine a future of seamless networked STEM learning across formal and informal learning environments • Cyberlearning affords the opportunity with mobiles and related always-on service to do the BRIDGING, to make the learning PATHWAYS which are resonant with learner interests and which can incorporate learning from out-of-classroom experiences that is relevant to developing STEM competencies.
• #25: As a quick view on the complexities involved in developing understanding of informal and formal learning and their interrelationships, consider formal/informal settings and formal/informal learning processes. Upper left and bottom right as extremes. But other two cells quite interesting as well. We need technology-enhanced supports for all of these varieties of informal and formal cyberlearning.
• #26: LIFE Professor Brigid Barron@ Stanford has developed a learning ecology framework in which technobiography timelines are mapped out from interviews with adolescent learners and their learning partners, family, and teachers - These technobiography timelines depict the CONTENT of key developments in technological fluencies (e.g., digital art creation; commercial web development) and their CONTEXTS (e.g., home, school, neighborhood), key PARTICIPANTS, and “turning points” perceived by the learner and other stakeholders to have considerable significance for the choices they make in their learning pathways later. A major result from this work is the multi-directionality of technological fluency development - school is actually often under-resourced in courses and teachers for the kinds of things that the learners WANT to learn, and so distributed web resources, social networks in their peer community or online, brokering of learning opportunities by parents (among other roles they play) end up being major contributors to the learning pathways that the learners enact.
• #27: Explain context of selecting 8 case studies – several hundred Silicon Valley youth completing technology experience surveys in which breadth and depth of engagement across different creative uses of technology were asked about. These are high-end cases from this sample, and the hope was to begin to understand some of the conditions associated with such broad and deep technology fluency engagements and learning.
• #28: This technobiography timeline depicts the diverse social influences and interests which drove AJ to become extremely technically proficient by his 13 th year, running two different tech services companies while still going to school fulltime. - Then read the HEADER.
• #29: * With the framing of the opportunities for cyberlearning and their theoretical foundations in mind, and the concept of learning ecologies across settings as a useful tool, now let us turn to the NSF task force report that inspired the theme of your conference : Fostering Learning in the Networked World. * I enjoyed working on this with my colleagues and would like to share its main findings and recommendations – and bring new developments and examples to fore for your consideration.
• #30: Transition - Cyberlearning requires a coherent, supportive infrastructure and to effectively grow one we recommended a set of strategies and their associated research questions for building a cyberlearning infrastructure – and we described opportunities for action that we considered to have the greatest short-term payoff and long term promise.
• #31: Among the special opportunities for action we felt to have the greatest short-term payoff and long-term promise are those that tap into the potential of technologies to coordinate learning across multiple contexts as with mobiles ; those that connect students with remote and virtual laboratories (with high school and college labs often in bad shape); and those that develop and exploit virtual or “mixed reality” environments for interactive exchanges for cyberlearning . Many other promising areas but we felt these especially central. *MANY INSPIRING INSTANCES OF THESE DEVELOPMENTS REPRESENTED AS OUR CONFERENCE HERE AND THANKS TO KEMI JONA AND OTHERS FOR ORGANIZING THESE EVENTS! Background image above is from World of Warcraft Inset images are from Second Life, Virtual Anatomy project (NSF SciVis competition), and 1st Google phone from T-Mobile running the Android open development platform for web apps
• #32: Building Human capacity is a real issue. The field is moving rapidly and needs new cross-disciplinary contributors to experiment, develop best practices, and develop new career paths. Help build a vibrant cyberlearning field by promoting cross-disciplinary communities of cyberlearning researchers and practitioners including software developers and IT staff, educators at all levels, domain scientists, and social scientists - and equip them for carrying forward cyberlearning effectively in new cyberlearning programs in colleges and universities and for benefiting K-12. NSF can advance their insights through the publication of best practices and the ongoing recruitment of diverse talents to carry the field forward. URL: http://www.flickr.com/photos/7446536@N03/430561725/
• #33: We emphasized ways that cyberlearning can transform — and not only make more efficient STEM disciplines and K–12 education — technologies allow new ways of looking at and understanding content; and can prepare students for computational thinking throughout curricular topics. The growing deluge of data is another key concern. Students and teachers alike need to be taught how to manage large amounts of data, whether produced through scientific research - or collected as part of a student’s educational history. About the image: GalaxyZoo.org In July 2007 a group of astronomers created a ‘mashup’ of galaxy images from the Sloan Digital Sky Survey (‘the Cosmic Genome Project’), the world’s largest digital map of the Universe. The public was asked to perform a simple visual classification of about a million galaxies. The response was overwhelming, over 100,000 people participated, and created 40 million classifications. The results were on par with a similar, but much smaller scale effort made by professional astronomers. The level of enthusiasm resulted in thousands of blogs by video gaming communities - the participants were thrilled by able to help in doing real, meaningful science. In December 2007, a Dutch physics teacher noticed an irregularity near one of the galaxies, and published a blog about the object (Yanni’s Voorwerp). Her observation produced a truly unique, original discovery, and the object was since confirmed by the world’s largest telescopes and space observatories (Lintott, 2008).
• #34: ICT has dramatically transformed how scientific disciplines pursue their work - it can and should be similarly transformative for learners at all levels, from K to grey. Forging the links between these transformations and better integrating research and education is our challenge. Technologies that allow interaction with scientific data, visualizations, remote and virtual laboratories, and human expertise offer opportunities for new research & broad implementation, particularly for STEM disciplines. Apple iPhone app store & Open Google Android apps platform a hint of what’s to come. Promoting bridging of desktop and mobile technologies and informal and formal learning has special promise. In addition, teachers’ professional development should be supported through training programs, professional societies, and ongoing collaboration on the creation of new educational materials.
• #35: One of the biggest impacts of CL will be insights deriving from the vast data these systems will produce. Opportunity to collect & use & analyze massive amounts of data in measuring the effectiveness of new educational tools and methods - and in putting in place feedback mechanisms for improvement. Educational technology research funding has typically been funded based on small-scale, pre-network assumptions about development, deployment and scale. Cyberinfrastructure has the potential to change the education sector as much as it has changed finance, advertising, commerce, and medicine -- through the possibility of building on shared platforms, taking advantage of network effects, and instituting feedback mechanisms that lead to improvement. The figures below are learning curves generated from an open repository of learner data [1] collected during student use of an intelligent tutor for Geometry. These learning curves show a change in student error rates (the y-axis) over successive opportunities to practice and learn (the x-axis) in attempting to apply a geometry concept (e.g., circle-area) during problem solving. The red line shows average student data and the blue line shows predictions from a best-fitting cognitive-psychometric model. Notice how for the circle-area and trapezoid-area concepts, the student average error rate is initially quite high, but with practice and tutoring it improves. In contrast, the learning curves for square-area and rectangle-area indicate that students have little trouble right from that start (less than 10% error rate), but nevertheless get lots of practice (10 opportunities). Given such visualizations, it is not hard for one to conclude that a redesign is needed to reduce the unnecessary over-practice on some concepts and instead spend the valuable instructional time where it is needed. Just such a redesign was done and compared to the original version in a randomized controlled classroom study (Cen, Koedinger & Junker, 2007) that ran inside the technology and was essentially invisible to students and teachers. The results indicated a significant 20% savings of student time without any loss in learning, transfer, or retention outcomes. [1] The Pittsburgh Science of Learning Center’s DataShop can be found at learnlab.web.cmu.edu/datashop.
• #36: Instill a “platform perspective”—shared, interoperable designs of hardware, software, and services—into NSF’s cyberlearning activities. This is a new worldview against a prior history of developing applications distributed through CDs or installed on client computers. An effective platform should incorporate promising innovations arising out of industry as well as from newly funded technology projects and offer fully tested and supported modules for use in classrooms. It should ensure that learning materials targeted for the platforms are widely useable and remain useable over time. The ongoing evolution of platform designs should be guided by an expert panel of public and private sector participation. Big issue - reduplication avoidance. 10-20 or more learning management systems in use on many campuses!
• #38: Open source Elgg social media platform Class X – explain intent and new features and open courseware aims. Short videos – easy capture, zoom in, cleanup graphics, navigate by slides; learning communities around challenging moments in videos; embedded assessments; classtime for focused interaction.
• #40: Image: CENSEI is a cyberlearning project that builds the necessary scaffolding to allow students to use the same sensor data that scientists are using to learn about general scientific concepts as well as fundamentals of handling and using data, through in-classroom activities and online activities.
• #41: The use of cyberlearning technologies also introduces specific issues that require prompt action. For example, policies can play a role in guaranteeing open educational resources are truly open & available for future use. We made aggressive recommendations that materials funded by NSF should be made readily available on the web with permission for unrestricted reuse and recombination using Creative Commons licenses. Copyright has limited broad exploitation of developing innovations and restricted their being made into re-usable components that could form new capabilities to advance learning. EXTRA Open educational resources (OER) are teaching, learning, and research resources that reside in the public domain or have been released under an intellectual-property license that permits their free use or customization by others. Open content includes video, multi-media, and cognitive tutoring courses, open text books, journals, books, data, laboratories, music, library collections, lesson plans, simulations, games, virtual worlds, and so on. Other OER include freely usable and reusable tools to support open content including open source content and learning management systems, search engines, communication systems and intellectual property licenses. Major institutions such as the BBC, the US public television stations, and Harvard University are unlocking their resources from behind passwords, intranets, and archives and figuring out ways of making them available to everyone, everywhere. But, it is the freedom to share, improve through rapid feedback loops from users and other experts, reprint, translate, combine, or adapt them that makes OER educationally different from those that can merely be read online at no cost. Three OER examples are 1) the OpenCourseWare activities that have spread across the world and receive multi-million visits monthly, 2) open textbooks to address the very high price of texts, the lack of quality in many of them, and the scarcity of them in many developing nations, and 3) open full courses in mathematics, engineering and science.
• #43: NO time for details!! The University of Queensland Inverted Pendulum Remote Laboratory - UQ was struggling to provide adequate access for students required to take a control theory course in their undergraduate program. Physical space limited class size to 60 students. Additional lab space was unavailable, & course content was challenging and uninspiring. Take the classic inverted pendulum control experiment. The student attempts to balance a pendulum with the weighted arm pointing upright towards the ceiling rather than hanging towards the floor. Students first write a Simulink model for the experiment and then write a MatLab program to control the motor that swings the pendulum, giving feedback from two sensors in the pendulum arm. Students work in teams of four to iteratively attempt to balance the pendulum via their MatLab application. Prior to the introduction of the iLabs pendulum implementation 5% of the teams balanced the pendulum by the end of the five-week experiment, while spending 50 contact hours on the task. The ilabs Inverted Pendulum made the experiment accessible beyond lab hours. The iLabs software interface presented the data graphically and via a mixed media video cam overlaid with a data driven animation of the pendulum arm. This let students see the results of one experimental run directly compared to another - thus showing the impact visually that their code revisions caused. But the learning story is more compelling. Students ran 30-40 experiments per team in the 5-week period prior to iLabs. With the remote lab students ran 3,210 experiments or on average 39.1 experiments per student. Contact hours decreased to four per week in the iLabs implementation from 10 hours per week previously, while the success rate for students balancing the pendulum went from 5% to 69.5%. Class size was increased from 60 students to 84 students while student ratings of the course rose significantly.
• #44: Perhaps most importantly the NSF directorates need to recognize cyberlearning as a pervasive NSF-wide strategy by funding the development of resources that can be used for both research and education. Take responsibility for sustaining NSF-sponsored cyberlearning innovations. Educational materials and learning innovations need to flourish beyond the funding of a grant. They can be maintained and extended across NSF divisions and through partnerships with industry, professional organizations, foundations and other institutions. Other recommended participants and related organizations include: Educause, which is a nonprofit association whose mission is to advance higher education by promoting the intelligent use of information technology. MacArthur Networks, which are interdisciplinary research networks, "research institutions without walls," addressing a variety of topics. The MacArthur Foundation’s  “Digital Media & Learning” effort to fund research and innovative projects focused on understanding the impact of the widespread use of digital media on our youth and how they learn. From the report: Institute processes and mechanisms for sustaining innovations, so that educational materials developed by grantees will continue to have impact long after Foundation support has ended. Implement effective hand-off and partnership programs so that valuable innovations remain in use and can be built upon.  These programs should consider the role of industry, professional organizations, and other potential contributors. Coordinate cyberlearning activities across all of the NSF divisions to ensure that cross-fertilization – rather than duplication – of efforts occurs. Empower a blue-ribbon panel/board to oversee these activities.  Convene a standing panel of experts from across sectors and charge them with the responsibility to define, explore and take responsibility for maintaining the aforementioned cross-sector partnerships for cyberlearning.
• #48: • Suggest several areas of strategic priority for the near future, among others we discussed last month in a new NSF Cyberlearning and Work Force Development Advisory group (2010) • Open platform: OER culture has hit critical mass; new devmts could enable easy HD mini-lecture and slide capture (15 mins) and student learning community features that could be integrated with discovery services and integration tools so that faculty could add associated open-source Java, Flash, etc simulations, models and adaptive problem engines and assessments.
• #49: Martin Kemp’s book on Visual Arts in Sciences – a Nature magazine feature for many years NRC book documenting many examples of arts and design contributions to innovations in information technologies and computer science Kenneth Robinson’s UK interdisciplinary commission on educating for creativity (1999) – All our Futures
• #50: March 5, 2010 Release of the Obama Administration National Educational Technology Plan - Establish the purpose and focus of the NETP - Brief you on key elements of the NETP - goals, recommendations, & actions for transforming American education
• #51: Four major differences of previous plans: First focus outside schools – the whole ecology of learning environments, and beyond K-12 to lifelong learning. 2. Focus on transformative system-wide redesign and on processes of continuous improvement 3. Emphasis on applying the advanced technology available in our daily lives to student learning and our entire education system in innovative ways that improve designs, accelerate adoption, and measure outcome 4. Strong scientific research base.
• #55: Connected teaching.
• #56: Games, collaboration, universal access design, interest-driven learning.
• #57: From COMMON TO PERSONALIZED LEARNING experiences – “All students should have common core discipline-specific learning experiences in preparation for college and careers. Networked technologies offer vast opportunites for group and individual learning experiences that are driven by students’ interests. LONG TAIL learning.
• #61: INFRASTRUCTURE
• #63: Grand Challenge Problems: In computing, in environment sciences, in health sciences …. We need our own GCPs at the intersection of developments in cyberinfrastructure, learning sciences, and STEAM education.
• #67: Today, we have examples of systems that can recommend learning resources a person might like, learning materials with embedded tutoring functions, software that can provide UDL supports for any technology-based learning materials, and learning management systems that move individuals through sets of learning materials and keep track of their progress and activity . What we do not have is an integrated system that can perform all these functions dynamically while optimizing engagement and learning for all learners . Such an integrated system is essential for implementing the individualized, differentiated, and personalized learning called for in this plan.
• #68: The multiple-choice tests used in nearly all large-scale assessment programs fail to meet the challenge of capturing some of the most important aspects of 21st century expertise and competencies. Past attempts to measure these areas have been high in cost and limited in their reliability. Promising R&D applying technology to each of these components of the grand challenge are ongoing, but the pieces have yet to be integrated into a single system that is applicable across content domains and cost-effective to implement. To meet the education and productivity goals articulated in the NETP, learners and their parents, educators, school and district leaders, and state and federal policymakers must use timely information about student learning and financial data to inform their decisions. Today, these data are maintained in a variety of digital formats in multiple systems at local and state levels. As the processes of learning, assessment, and financial management and accounting move into the digital realm, educational data systems and educational research has become data-intensive and complex in scale, heterogeneity, and requirements for privacy. Still, we must create systems that capture, curate, maintain, and analyze educational and financial data in all scales and shapes, in near time, from all venues in which learning occurs: school, home, and community. This must be done fully consistent with privacy regulations.