EDUSPRINGS / THE LEARNING GENOME:
BUILDING SMART SCHOOLS THROUGH COMMUNITIES
Our 21st Century Future for Public Education
by
INTRODUCTION
This paper presents a closely twined double helix conceived to move public education into the information age. The first strand is based on building The Learning Genome, a Web2.0 research environment. Its purpose is to differentiate students and provide a foundation forIT to support individualized learning. The second strand is EduSprings, which focuses on building instructional support and resource development communities around our understanding of differentiated needs of students and teachers.
TOWARD AN INDIVIDUALIZED SCIENCE OF LEARNING
Because we do not perceive the rich diversity of our students, our schools fail to educate almost all students to their potential. Without accurate insight into each student, we fail to fully reach and teach most learners. Though we say we educate individuals, our limited knowledge of the gifts and limitations of each student shows us as blind archers.
Public education will not transform until we use IT to evolve our science of individual learning to the point wherewe can build measurement-based, differentiating, Learner Profiles for each student. When we identify the learner in ways that inform instructional resource development, delivery, interactions, assessment and feedback, then we will see the improvements in learning that our values honor.
Companies that use IT to create new student assessments have demonstrated the remarkable efficiency of information age tools for rapidly assessing individual capacities, skills, and preferences on a range of variables—perceptual, personality, social, cognitive, learning style, and background knowledge. These digital assessments, combined with data-collection from online interactions and student and educator evaluations, provide the basis for a new science of individual learning. We cannot overstate the potential of the Learning Genome for energizing research, resource development and instruction, and for deploying rich digital and human resources in the service of learning. We are on the verge of creating smart learning systems from within smart learning communities. The Learning Genome has the potential to serve as the hub of this work.
CHALLENGES ADDRESSED BY EDUSPRINGS & THE LEARNING GENOME
The challenge for education stakeholders—students, teachers, administrators, parents, IT companies, foundations, publishers, universities and research groups is to link Research, Resource Development, and Management systems that support and are supported by six components:
1) Use information age tools to develop and support a research infrastructure that provides information on learner variables—The Learning Genome;
2) Support the development and distribution of educational programs and productivity tools that generate user data to evolve student profiles—The Learning Genome;
3) Support distributed curriculum development, adaptation, and continuous improvement of curriculum, driven by data about diverse learners and their interactions with resources—EduSprings/The Learning Genome;
4) Provide an online store for the distribution of digital curriculum, assessment, and staff development resources--EduSprings;
5) Provide a comprehensive learner-management system that customizes learner-choices and feedback based on student profiles—EduSprings/The Learning Genome;
6) Enable communities to match learner needs to local resources that will engage students around ecological and economic issues, mentoring and apprenticeship opportunities, cultural resources like artists, museum workers, business people, and science and math workers such as biology field personnel—EduSprings/The Learning Genome.
POISED TO ENTER THE INFORMATION AGE
Enterprises that rely on measurement and data refinement to advance theory and practice, were quick to organize their research, communication, development, and to-market procedures around IT.
Public education, on the other hand, has yet to organize in ways that take advantage of the information age. Though the educational enterprise is an information industry and should be organized around the continuous improvement and use of data, it has not built the infrastructure to rely on measurement, data analysis, networking and data driven product development, management and distribution.
Advances in IT instruments that measure student capacities, interests, background knowledge, and social inclinations provide a wealth of information about the potential of IT to build unique learner profiles. When we combine these advances with user, instructor, and parent evaluations, pedagogical science, distributed resource development, and new instructional management systems, we will truly transform public education.
Examining how IT is affecting medicine, from research to practice, helps build a transformative model for public education. In medicine, research from The Genome Project is built on the unique power of IT systems to measure, group, analyze, and share data. The result is a redefinition of patient, disease and treatments. We see a profound movement away from treating a generic disease with a generic protocol. Instead, medical practice is redefined so we treat genetically unique individuals with protocols specified for the individual’s genetic make up. Treatments are smart in the sense that the treatment is customized to target a specific patient with unique disease patterns. Drugs and delivery are individualized. Research groups shift from the phenotype of symptoms to the genotype that builds from the unique biology of the patient.
A similar process and result is now practical if we develop The Learning Genome. This project will target and continuously refine the delivery of customized, smart learning and feedback processes through adaptive systems. Currently our application of theories and instruments for measuring learners is limited by a paucity of research variables and data. When we can mine the full range of data about learners and link these variables together, the resulting insights will decrease the number of students who fail to achieve their potential--first as students and then as workers. Thus, we can develop smart learning experiences--systems that deliver products and processes based on the specific needs of each student, and intelligently grouped students, just as medicine delivers smart treatments to diverse clinical populations.
BUILDING WEB2 SYSTEMS FOR EDUCATIONAL RESEARCH
Educational research is a daunting task. Researchers often develop their own reliable and valid instruments. They struggle to locate sufficient and appropriate populations of students and teachers. Administration, scoring, and data analysis can be labor intensive. Populations of subjects are usually small and undifferentiated; control groups are too random to be matched, and ways to drill down into the data are limited because too often there is little other data on the subjects. Currently, educational assessment is more of a cottage industry than a scalable enterprise.
We need to correct this by 1) providing our educational research community with research tool kits that support the rapid programming of sophisticated online assessment instruments to capture learner data in a variety of contexts—through formal adaptive instruments and from data gathered during online learning activities; and 2) the online publication of research data to provide the basis for complex analysis and data mining.
Researchers have another need the web can meet. Research involves a number of procedures, protocols, and communications. It is challenging for each researcher to find his research population, communicate with teachers and perhaps parents and/or students. All of this can be more automated. When these supports for research are in place, the amount and utility of research will skyrocket as will the value of the information and its application to learning.
NEW MODELS OF INDIVIDUAL LEARNERS
As new measurements are applied to existing data pools, we place ourselves squarely on the threshold of new insights about individual and group learning behavior. This information will drive planning processes that create personalized learning.
These new models of learning will be based on connecting biology, pedagogy, perceptual, affective, and cognitive psychology, brain-based learning, and insights from personality theory, anthropology and sociology. Thus, we view the student as a bio-psychological being acting within social and cultural contexts. Using digital instruments, online feedback, and increasingly intelligent menus of student choices, we will rapidly, unobtrusively, and continuously gain information that enables adaptive learning.
By linking this data to an instructional management system, students, teachers, administrators, and parents will make more informed and productive decisions at all stages of teaching and learning. More students will feel recognized and will realize their potential and fewer people will slip between today’s ever widening cracks.
EXPANDING OUR DEFINITION OF LEARNER DIVERSITY
As we move public education into the information age, we will discover that there is a great deal more to individuality than we expected, and certainly more than we provide for in our schools. We will discover that individuals who first appear to be similar may function in very different ways, and may have vastly different capacities. They may perform at similar levels but for very different reasons.
This takes us into the realm of phenotypes, or how the surface appears, and genotypes, or the underlying structures of characteristics. Until now, public education, has functioned at the phenotype or surface level, and even at this level has made only a few adjustments.
For example, a group of students may all exhibit the same delays in learning to read. In one case, poor eyesight results in prescribing corrective lenses and the font is enlarged and darkened. Or the problem may have to do with eye muscle control and difficulties in focusing and tracking in a left to right pattern, calling for vision exercises. In a third, fourth or fifth case the difficulties may relate to problems in focusing that may have neurological or psychological causes that call for anything from pharmaceuticals to psychological support or computer mediated brain development activities.
Other sources of problems may relate to weaknesses in figure-ground perception (in ability to discriminate letters), deficient memory for linking visual and auditory cues (phonics), or to long-term memory as this relates to comprehension based on syntactic patterns or story maps. Remediation may require a wide range of strategies, and resetting expectations while underlying neural structures and habits of perception, memory and thought are developed.
Finally, where words can be read and sentences understood but comprehension falters, we may need to understand the student’s cognitive style and psychosocial or cultural make up, background knowledge, and motivation. Remediation is likely to be in areas related to selecting interesting and patterned texts, more oral and dramatic experience with texts, providing background knowledge and vocabulary, and selecting interactions that are culturally supported.
A decade ago it wasn’t possible to gather, analyze and track all these kinds of data on each student. Today it can become common place because it is relatively simple to use IT to create tests and questionnaires to assess everything from visual and auditory perception to small muscle control, short and long term memory, cognitive capacities related to subject areas, learning style, and emotional, social and cultural variables. We can assess in all of these areas and use digital systems to assist in building models to help us understand different kinds of students and how they are likely to interact with teachers, peers, mentors, computers, and a variety of learning experiences in all disciplines.
Management systems will have increased intelligence based on previous data about the student and data about other students with similar learning profiles. This information can help administrators understand how best to group students, can help teachers understand how best to select or design learning experiences that teach to student strengths and needs, and can help a student become smarter about how to manage his or her learning.
BUILDING INDIVIDUAL LEARNER TAXONOMIES
For nearly a century public education has used one, general developmental taxonomy of learning. It applied to all students and subjects. Today we can imagine developing multiple taxonomies of learning, and also taxonomies for each learner in a discipline.
Educational practice has properly identified formative assessment as key to adapting instruction to individual needs. Current theory and metrics in assessment demonstrate that test item analysis can indicate what a student knows or doesn’t and can provide insight into the structure of knowledge in a given discipline. As the science of assessing learner knowledge is linked to the structure of subject area knowledge, we will make important progress toward building individual learning taxonomies.
Thus, we will develop different taxonomies for how different subjects are learned by different students. For example, we will create a developmental taxonomy for how different people learn to write (do math or science). Our new wealth of data about students’ writings, when matched with learner, instructor and computer observations of the online writing process and computer analyzed writing samples, will help us build IT systems that see that there are different types of students learning to write at different rates and in very different ways.
This means that our one-size-fits-all approach to writing instruction will be replaced by opportunities to develop writing in personalized ways. In this process, the individual becomes a good writer by developing his or her unique voice and style while also practicing discrete skills. This writing instruction/practice is mediated by feedback from new breeds of educational word processors and by working with peers and mentors in socially supportive writing groups. In writing, as in other areas of learning, combining digital tools with participation in a community-of-practice, will produce engagement, insight, and empowerment. We can now see IT supporting social learning networks.
CREATING DIVERSE LEARNER RESOURCES
The process of developing and delivering instructional resources will be mediated by a greatly enlarged educational community that uses IT as its research, development, publishing, and coordination tool. This doesn’t mean that all instruction will occur on the computer. It does mean that some individualized seatwork may be generated and practiced online, either done individually or in small groups. Two benefits of online work are IT-based feedback and data collection and analysis.
Other materials may be custom configured or adapted on computer and then printed—published on demand. These recommended activities may involve using manipulatives, doing science, art or other project-based learning, playing games, doing community service, or other off-line, in-the-world projects. However, even these off-line activities may have online evaluations that support ratings by participants and observers. Evaluations may become part of the student’s portfolio and add to the learner’s profile.
As our knowledge of the student and his community improves, we will differentiate the learning and social support that the community can provide. A peer or cross-age tutor or an adult mentor with whom the student is matched by social networking software will provide non-teacher support. This may involve a virtual and/or face-to-face relationship depending on the student’s need for social support. This mobilization of face-to-face as well as virtual social resources that are smart with regard to the learner and the community will profoundly improve the quality of participation and learning.
MOVING PUBLISHING FROM THE INDUSTRIAL TO THE DIGITAL AGE
To grasp the magnitude of the approaching transformation, we need to see that the industry that currently develops educational materials is the result of technologies from the industrial age and is driven by market and sales cycles. Most current learning resources are bound, printed pages shipped from warehouses. They do not improve based on use, nor do they track learning or give feedback based on student responses.
Committees in schools and publishing houses drive textbook development. Committees in billion-dollar publishing houses ramp up, in five or seven year adoption cycles, to design textbooks for adoption committees in California, Florida and Texas. These committees are concerned with meeting the needs of the middle group of learners that exists only on a normal curve. With the development of individual learning profiles and smart learning resources, generic textbooks will become obsolete.
What will replace the publishing houses with their presses, warehouses, and sales-cycle development groups in cubicles forty floors above classrooms? The replacement will come from the street—from members of the educational community. The new publishers will be individuals in classrooms, or retired teachers, along with children’s book authors, storytellers, scientists, mentors, zookeepers, naturalists, museum workers, university-based researchers, business people and other cultural workers creating on their own or in virtual or face-to-face development groups.
Inspired by insights from research about students, enthusiasm for subject areas, and a deep intuitive sense of how to match the individual (and the groups these students represent), with the knowledge of their disciplines, educators and culture workers will use digital tools to develop, field test, publish, and continuously refine educational resources designed to meet differentiated needs.
On one hand these resources will simply match students by their profiles with particular learning resources and strategies. For example, they will provide personalized, online flashcards that are oriented toward visual, auditory and kinesthetic learning of spelling with an emphasis on the student’s dominant function for pattern recognition and memory. The online practice sessions will be structured based on knowledge about attention span for this kind of activity. The spelling list will be chosen by the student from a list of words generated by the spell checker from words that the student has demonstrated that he frequently uses and often misspells. We can even imagine the spelling test as a spelling bee in which each student competes from his own list of words.
We will also see a computer generated, individualized literature for the classroom. Subject area reading materials, like history, will be customized and interactive. Each student in a smartly configured study group will be included by name in the text, and each student will read the particular text that is tailored for the student’s reading level. The previous reader will read a more complex text that includes all of the next reader’s vocabulary in order to scaffold reading for the less skillful student.
In the case where students read a personalized math word problem, the students will delete all distracting details, bold key information, and then create diagrams and explain in writing how they solved the problem. Their approach will then be projected and compared with the approaches of other groups.
DEVELOPMENTAL CURRICULUMS
Comprehension that leads to mastery always involves scaffolding or grafting of the new skill onto an older one. This is true in developing cognitive or motor skills and is well documented by brain-based learning research. The science of understanding the optimum developmental chains and the art of creating practice to develop these is challenging. For example, the math genius needs many fewer scaffolding steps and related practice than the student who is math challenged—but which steps does each require. Textbooks often lack thoughtful developmental sequences, and, where they are provided, they use a one-size-fits-all model. This is guaranteed to frustrate the challenged and bore the gifted.
COLLABORATIVE LEARNING
With the development of social network sites, IM, Open Source, and Wikis, the power of our drive to communicate, share, work and learn together has become the phenomena of Web 2.0. This is the song of our current digital age. If there is one lyric, it is let us sing our profound and silly songs together.
Given our natural drive to work, chatter and explore in groups, educators, going back to Dewey, have worked to get students out from behind their desks. We possess a wide range of strategies that support small and large group learning.
It is fair to say that cooperative learning is as well established in its patterns and proofs as any approach. Cooperative learning strategies can now be adapted, enriched and profoundly expanded through digital technologies.
Imagining the future, one can see students building a website that they use to post and discuss poetry they like (usually discovered at a poetry website tagged with del.icio.us, perhaps with a few sites recommended by the instructor). As students post their preferred poems, they place them in various categories, with some poems qualifying for many categories. Students explain their thinking and reflect on their experience of the poem. Discussions proliferate and groups develop around themes as diverse as pregnancy, mothering and soldiering. Written interactions in online discussions are analyzed by text parsing tools that provide feedback that characterize the interactions.
In writing we see collaborative learning and Instant Messaging as informal allies. The question in play is how to find ways to integrate the social dimensions of IM into more formal discourse—for example as planning or prewriting dialogues.
Web-searches that support educational ratings of websites should become widely used by collaborative project groups. For students this means they are evaluating the writing of others on multiple levels—for their search purpose and quality of argument, graphics, etc.
THEMATIC INTEGRATION
Another change in moving from an industrial process of producing textbooks to a community process of producing interactive, collaborative, and adaptable resources is that curriculum will finally begin to achieve the holy grail of thematic integration. The combination of teachers, specialists, artists and authors working with a wide-range of experts and having the benefit of student and teacher feedback within a digital environment will lead to integration of key ideas across subject areas.
Instructional design in and among subjects will improve while the connections among subjects will enrich inquiry and analysis. Finding the math patterns within various disciplines will become more prevalent. The process of using multiple means for representation of ideas will improve curriculums and processes of inquiry and synthesis of ideas. Students will engage more deeply as lessons become more collaborative and meaningful. So math, science, reading and writing, and history will no longer be taught in segregated silos and in fragmented ways on fragmented days.
This does not mean that in the information age there will be no place for large publishing companies. It does suggest, however, that for publishers to survive they will need to develop strategies to differentiate learners and customize resources. They also will need to find ways to engage communities in order to continuously improve resources.
COMMUNITIES THAT CONTINUOUSLY REFINE KNOWLEDGE
By using the digital environment as the product development and distribution system, public education will take a page (or screen) from the Wiki-movement exemplified by Wikipedia. Wikipedia holds the promise of containing all of a community’s knowledge on a given subject at a given time. It encourages the continuous evolution of that knowledge and how it is presented. Wikipedia is evolving a continuously improving information resource as it builds a vital online community.
The ability of educators to customize resources to fit the particular needs of their students is Wiki-like. Likewise the Wiki-curriculum and assessment communities will evolve their intellectual property within an equally vibrant, quality-motivated process.
This bottom-up curriculum and assessment development will also benefit from the Open Source model that produced Linux. Like the Wiki-community, the Open Source community has development tools and procedures for distributed, collaborative work and continuous improvement of resources. One of their contributions is the Digital Commons, an eEnvironment where programmers meet online to discuss problems, form workgroups, and leave code to be vetted, refined, and used in others’ projects.
The new IT-based schools will benefit from an Amazon.com, eBay (without auction) distribution model that demonstrates how bottom-up retailing communities can develop around a virtual store. This virtual store supports a shopping community with useful search capacities, ratings and reviews of products/providers. The crowd intelligence reflected in client ratings and reviews enables a community to inform and police itself.
**In addition to building resource development and distribution communities, IT will support the development of face-to-face communities. The walls between school, home, museum, zoo, business, university, artist’s studios and other community resources will become transparent. Administrators and teachers will have information that helps link students who will benefit from various kinds of support. Peer and cross-grade tutors, mentors, work-study and various in-community and online service and research projects will all be enriched by using information about students to connect them with people in a growing network of purpose driven entities.
Historically, there was great concern that computers would dehumanize classrooms and would decrease social interactions. Using the model presented here, we see IT linking individuals to improve engagement. For example a university researcher may team with teachers to develop a measurement instrument or a remediation procedure. The measurement instrument may be used online. The remediation procedure may include online lesson plans that involve rolling and catching balls on the floor with high school students interested in physics or physical education.
SOCIAL & ECONOMIC BENEFITS OF SMARTER COMMUNITIES
Building online and face-to-face educational communities linked through IT will save our schools, corporations and governments billions of dollars annually. These savings will come from costs associated with students who drop out and become members of a non-tax-paying under-class. The savings will also come from decreases in the population of underachievers who place themselves at-risk in so many ways that endanger themselves and others. Thus, the cost of the social safety net and of the judicial and prison system will decrease while the benefits flowing from people who contribute to society increase.
By helping more students realize their potential as students, workers and citizens, we will also improve the quality of the workforce and the polis. This will enable all countries to grow their economies and politics. The need and opportunities for local and global citizenship and workforce creativity and vigor has never been greater. Our health and wealth have never been more closely tied to our understanding of each other and our relationship to science, technology, one another, and our local and global ecologies.
**EDUCATION AS A BOTTOM UP ENTREPRENEURIAL ENTERPRISE
Viewed from an entrepreneur’s perspective, building IT-based educational communities will spawn huge opportunities for educators and educational consortiums—particularly among teams of individuals, schools, universities and research groups.
Traditionally underpaid, educators leave the profession to better their economic and expressive prospects. As classrooms become the essential laboratories, teaching will become more creative, collaborative, and rewarding and teachers will find themselves playing varied roles as valued partner.
Schools and districts that traditionally have seen themselves as consumers of curriculum will now see themselves as resource creators that can develop and publish educational materials. Those individuals and groups that produce successful products will be richly rewarded; yet the development, manufacturing, marketing and sales costs for producing these smart and smarter products will be a fraction of the costs associated with traditional publishing. Many of these savings will go to customers, many of which will also be creators and adaptors. Thus, the one-way direction of cash out of schools will become a cycle in which the school-based educational community becomes more profitable while the costs of goods decreases as quality increases.
THE LEARNING GENOME AND EDUCATION POLICY
As we develop pedagogies that fit individual learners, we will influence policy debates. One example is merit pay.Merit pay will become rational when we are able to view learning gains in relation to a learner potential. A gain of 2 months over the course of a school year may be a fine achievement for one student and teacher, while a gain of 2 years may not be satisfactory for another. Only when we understand the learning potential of each student can we gage a teacher’s achievements. Perhaps even more important, this kind of data will help the teacher and administrator to know the students each teacher is most and least capable of educating.
The reading wars represent another seemingly endless policy debate because we simply lack the science to differentiate those learners who learn best by emphasizing phonics versus those who do well within a more balanced or whole language regimen. The Learning Genome will help us see that different students benefit from different levels of each pedagogy and that most students do best when teachers integrate both approaches.
ORGANIZING TO BUILD A SMART SCHOOLING ENTERPRISE
To conceptualize and design pedagogy and instructional processes that are informed by R&D, we need to create a platform from which to build The Learning Genome and tailor smart learning resource and processes. The construction of this R&D, publishing and community-learning platform goes far beyond the scope and focus of current enterprises.
To form and manage this enterprise we need to establish a means to provide capital and shared ownership among educators, IT industries, foundations and public agencies. This will assure that local and global educational communities continuously benefit from the R&D and knowledge transmitting capacities that will drive this enterprise. This will be fundamental for moving industrial and pre-industrial societies into the information age. What The Genome Project promises for pharmaceuticals and 21st century medicine The Learning Genome and Smart Schooling promises for the development of education.
The U.S., EU, and many nations in Asia and Latin America are positioned to be leaders. As these groups refine this model and produce resources, they can help others to leapfrog over the industrial age built by the printing press. This community approach to public education is the foundation to move humanity toward a sustainable, quality future built on taking responsibility for creating cultures and networks that serve humanity’s future.
The U.S., working with global partners, will be well served to develop a clearly defined education initiative so we can help lead the world into an age of democracy and humanitarian purpose that provides the basis for increasing wealth in sustainable economies. To date there is no national strategy to guide new investment and to develop our educational communities around information age practices, but the need is stunning, the time is ripe, and our human and technical resources are ready.
Are you absolutely sure you want to delete this article? This process cannot be undone and is permanent.
Yes, Delete This Article
Are you absolutely sure you want to remove this article? This process cannot be undone and is permanent.
Yes, Remove This Article
EDUSPRINGS / THE LEARNING GENOME:
BUILDING SMART SCHOOLS THROUGH COMMUNITIES
Our 21st Century Future for Public Education
by
INTRODUCTION
This paper presents a closely twined double helix conceived to move public education into the information age. The first strand is based on building The Learning Genome, a Web2.0 research environment. Its purpose is to differentiate students and provide a foundation forIT to support individualized learning. The second strand is EduSprings, which focuses on building instructional support and resource development communities around our understanding of differentiated needs of students and teachers.
TOWARD AN INDIVIDUALIZED SCIENCE OF LEARNING
Because we do not perceive the rich diversity of our students, our schools fail to educate almost all students to their potential. Without accurate insight into each student, we fail to fully reach and teach most learners. Though we say we educate individuals, our limited knowledge of the gifts and limitations of each student shows us as blind archers.
Public education will not transform until we use IT to evolve our science of individual learning to the point wherewe can build measurement-based, differentiating, Learner Profiles for each student. When we identify the learner in ways that inform instructional resource development, delivery, interactions, assessment and feedback, then we will see the improvements in learning that our values honor.
Companies that use IT to create new student assessments have demonstrated the remarkable efficiency of information age tools for rapidly assessing individual capacities, skills, and preferences on a range of variables—perceptual, personality, social, cognitive, learning style, and background knowledge. These digital assessments, combined with data-collection from online interactions and student and educator evaluations, provide the basis for a new science of individual learning. We cannot overstate the potential of the Learning Genome for energizing research, resource development and instruction, and for deploying rich digital and human resources in the service of learning. We are on the verge of creating smart learning systems from within smart learning communities. The Learning Genome has the potential to serve as the hub of this work.
CHALLENGES ADDRESSED BY EDUSPRINGS & THE LEARNING GENOME
The challenge for education stakeholders—students, teachers, administrators, parents, IT companies, foundations, publishers, universities and research groups is to link Research, Resource Development, and Management systems that support and are supported by six components:
1) Use information age tools to develop and support a research infrastructure that provides information on learner variables—The Learning Genome;
2) Support the development and distribution of educational programs and productivity tools that generate user data to evolve student profiles—The Learning Genome;
3) Support distributed curriculum development, adaptation, and continuous improvement of curriculum, driven by data about diverse learners and their interactions with resources—EduSprings/The Learning Genome;
4) Provide an online store for the distribution of digital curriculum, assessment, and staff development resources--EduSprings;
5) Provide a comprehensive learner-management system that customizes learner-choices and feedback based on student profiles—EduSprings/The Learning Genome;
6) Enable communities to match learner needs to local resources that will engage students around ecological and economic issues, mentoring and apprenticeship opportunities, cultural resources like artists, museum workers, business people, and science and math workers such as biology field personnel—EduSprings/The Learning Genome.
POISED TO ENTER THE INFORMATION AGE
Enterprises that rely on measurement and data refinement to advance theory and practice, were quick to organize their research, communication, development, and to-market procedures around IT.
Public education, on the other hand, has yet to organize in ways that take advantage of the information age. Though the educational enterprise is an information industry and should be organized around the continuous improvement and use of data, it has not built the infrastructure to rely on measurement, data analysis, networking and data driven product development, management and distribution.
Advances in IT instruments that measure student capacities, interests, background knowledge, and social inclinations provide a wealth of information about the potential of IT to build unique learner profiles. When we combine these advances with user, instructor, and parent evaluations, pedagogical science, distributed resource development, and new instructional management systems, we will truly transform public education.
Examining how IT is affecting medicine, from research to practice, helps build a transformative model for public education. In medicine, research from The Genome Project is built on the unique power of IT systems to measure, group, analyze, and share data. The result is a redefinition of patient, disease and treatments. We see a profound movement away from treating a generic disease with a generic protocol. Instead, medical practice is redefined so we treat genetically unique individuals with protocols specified for the individual’s genetic make up. Treatments are smart in the sense that the treatment is customized to target a specific patient with unique disease patterns. Drugs and delivery are individualized. Research groups shift from the phenotype of symptoms to the genotype that builds from the unique biology of the patient.
A similar process and result is now practical if we develop The Learning Genome. This project will target and continuously refine the delivery of customized, smart learning and feedback processes through adaptive systems. Currently our application of theories and instruments for measuring learners is limited by a paucity of research variables and data. When we can mine the full range of data about learners and link these variables together, the resulting insights will decrease the number of students who fail to achieve their potential--first as students and then as workers. Thus, we can develop smart learning experiences--systems that deliver products and processes based on the specific needs of each student, and intelligently grouped students, just as medicine delivers smart treatments to diverse clinical populations.
BUILDING WEB2 SYSTEMS FOR EDUCATIONAL RESEARCH
Educational research is a daunting task. Researchers often develop their own reliable and valid instruments. They struggle to locate sufficient and appropriate populations of students and teachers. Administration, scoring, and data analysis can be labor intensive. Populations of subjects are usually small and undifferentiated; control groups are too random to be matched, and ways to drill down into the data are limited because too often there is little other data on the subjects. Currently, educational assessment is more of a cottage industry than a scalable enterprise.
We need to correct this by 1) providing our educational research community with research tool kits that support the rapid programming of sophisticated online assessment instruments to capture learner data in a variety of contexts—through formal adaptive instruments and from data gathered during online learning activities; and 2) the online publication of research data to provide the basis for complex analysis and data mining.
Researchers have another need the web can meet. Research involves a number of procedures, protocols, and communications. It is challenging for each researcher to find his research population, communicate with teachers and perhaps parents and/or students. All of this can be more automated. When these supports for research are in place, the amount and utility of research will skyrocket as will the value of the information and its application to learning.
NEW MODELS OF INDIVIDUAL LEARNERS
As new measurements are applied to existing data pools, we place ourselves squarely on the threshold of new insights about individual and group learning behavior. This information will drive planning processes that create personalized learning.
These new models of learning will be based on connecting biology, pedagogy, perceptual, affective, and cognitive psychology, brain-based learning, and insights from personality theory, anthropology and sociology. Thus, we view the student as a bio-psychological being acting within social and cultural contexts. Using digital instruments, online feedback, and increasingly intelligent menus of student choices, we will rapidly, unobtrusively, and continuously gain information that enables adaptive learning.
By linking this data to an instructional management system, students, teachers, administrators, and parents will make more informed and productive decisions at all stages of teaching and learning. More students will feel recognized and will realize their potential and fewer people will slip between today’s ever widening cracks.
EXPANDING OUR DEFINITION OF LEARNER DIVERSITY
As we move public education into the information age, we will discover that there is a great deal more to individuality than we expected, and certainly more than we provide for in our schools. We will discover that individuals who first appear to be similar may function in very different ways, and may have vastly different capacities. They may perform at similar levels but for very different reasons.
This takes us into the realm of phenotypes, or how the surface appears, and genotypes, or the underlying structures of characteristics. Until now, public education, has functioned at the phenotype or surface level, and even at this level has made only a few adjustments.
For example, a group of students may all exhibit the same delays in learning to read. In one case, poor eyesight results in prescribing corrective lenses and the font is enlarged and darkened. Or the problem may have to do with eye muscle control and difficulties in focusing and tracking in a left to right pattern, calling for vision exercises. In a third, fourth or fifth case the difficulties may relate to problems in focusing that may have neurological or psychological causes that call for anything from pharmaceuticals to psychological support or computer mediated brain development activities.
Other sources of problems may relate to weaknesses in figure-ground perception (in ability to discriminate letters), deficient memory for linking visual and auditory cues (phonics), or to long-term memory as this relates to comprehension based on syntactic patterns or story maps. Remediation may require a wide range of strategies, and resetting expectations while underlying neural structures and habits of perception, memory and thought are developed.
Finally, where words can be read and sentences understood but comprehension falters, we may need to understand the student’s cognitive style and psychosocial or cultural make up, background knowledge, and motivation. Remediation is likely to be in areas related to selecting interesting and patterned texts, more oral and dramatic experience with texts, providing background knowledge and vocabulary, and selecting interactions that are culturally supported.
A decade ago it wasn’t possible to gather, analyze and track all these kinds of data on each student. Today it can become common place because it is relatively simple to use IT to create tests and questionnaires to assess everything from visual and auditory perception to small muscle control, short and long term memory, cognitive capacities related to subject areas, learning style, and emotional, social and cultural variables. We can assess in all of these areas and use digital systems to assist in building models to help us understand different kinds of students and how they are likely to interact with teachers, peers, mentors, computers, and a variety of learning experiences in all disciplines.
Management systems will have increased intelligence based on previous data about the student and data about other students with similar learning profiles. This information can help administrators understand how best to group students, can help teachers understand how best to select or design learning experiences that teach to student strengths and needs, and can help a student become smarter about how to manage his or her learning.
BUILDING INDIVIDUAL LEARNER TAXONOMIES
For nearly a century public education has used one, general developmental taxonomy of learning. It applied to all students and subjects. Today we can imagine developing multiple taxonomies of learning, and also taxonomies for each learner in a discipline.
Educational practice has properly identified formative assessment as key to adapting instruction to individual needs. Current theory and metrics in assessment demonstrate that test item analysis can indicate what a student knows or doesn’t and can provide insight into the structure of knowledge in a given discipline. As the science of assessing learner knowledge is linked to the structure of subject area knowledge, we will make important progress toward building individual learning taxonomies.
Thus, we will develop different taxonomies for how different subjects are learned by different students. For example, we will create a developmental taxonomy for how different people learn to write (do math or science). Our new wealth of data about students’ writings, when matched with learner, instructor and computer observations of the online writing process and computer analyzed writing samples, will help us build IT systems that see that there are different types of students learning to write at different rates and in very different ways.
This means that our one-size-fits-all approach to writing instruction will be replaced by opportunities to develop writing in personalized ways. In this process, the individual becomes a good writer by developing his or her unique voice and style while also practicing discrete skills. This writing instruction/practice is mediated by feedback from new breeds of educational word processors and by working with peers and mentors in socially supportive writing groups. In writing, as in other areas of learning, combining digital tools with participation in a community-of-practice, will produce engagement, insight, and empowerment. We can now see IT supporting social learning networks.
CREATING DIVERSE LEARNER RESOURCES
The process of developing and delivering instructional resources will be mediated by a greatly enlarged educational community that uses IT as its research, development, publishing, and coordination tool. This doesn’t mean that all instruction will occur on the computer. It does mean that some individualized seatwork may be generated and practiced online, either done individually or in small groups. Two benefits of online work are IT-based feedback and data collection and analysis.
Other materials may be custom configured or adapted on computer and then printed—published on demand. These recommended activities may involve using manipulatives, doing science, art or other project-based learning, playing games, doing community service, or other off-line, in-the-world projects. However, even these off-line activities may have online evaluations that support ratings by participants and observers. Evaluations may become part of the student’s portfolio and add to the learner’s profile.
As our knowledge of the student and his community improves, we will differentiate the learning and social support that the community can provide. A peer or cross-age tutor or an adult mentor with whom the student is matched by social networking software will provide non-teacher support. This may involve a virtual and/or face-to-face relationship depending on the student’s need for social support. This mobilization of face-to-face as well as virtual social resources that are smart with regard to the learner and the community will profoundly improve the quality of participation and learning.
MOVING PUBLISHING FROM THE INDUSTRIAL TO THE DIGITAL AGE
To grasp the magnitude of the approaching transformation, we need to see that the industry that currently develops educational materials is the result of technologies from the industrial age and is driven by market and sales cycles. Most current learning resources are bound, printed pages shipped from warehouses. They do not improve based on use, nor do they track learning or give feedback based on student responses.
Committees in schools and publishing houses drive textbook development. Committees in billion-dollar publishing houses ramp up, in five or seven year adoption cycles, to design textbooks for adoption committees in California, Florida and Texas. These committees are concerned with meeting the needs of the middle group of learners that exists only on a normal curve. With the development of individual learning profiles and smart learning resources, generic textbooks will become obsolete.
What will replace the publishing houses with their presses, warehouses, and sales-cycle development groups in cubicles forty floors above classrooms? The replacement will come from the street—from members of the educational community. The new publishers will be individuals in classrooms, or retired teachers, along with children’s book authors, storytellers, scientists, mentors, zookeepers, naturalists, museum workers, university-based researchers, business people and other cultural workers creating on their own or in virtual or face-to-face development groups.
Inspired by insights from research about students, enthusiasm for subject areas, and a deep intuitive sense of how to match the individual (and the groups these students represent), with the knowledge of their disciplines, educators and culture workers will use digital tools to develop, field test, publish, and continuously refine educational resources designed to meet differentiated needs.
On one hand these resources will simply match students by their profiles with particular learning resources and strategies. For example, they will provide personalized, online flashcards that are oriented toward visual, auditory and kinesthetic learning of spelling with an emphasis on the student’s dominant function for pattern recognition and memory. The online practice sessions will be structured based on knowledge about attention span for this kind of activity. The spelling list will be chosen by the student from a list of words generated by the spell checker from words that the student has demonstrated that he frequently uses and often misspells. We can even imagine the spelling test as a spelling bee in which each student competes from his own list of words.
We will also see a computer generated, individualized literature for the classroom. Subject area reading materials, like history, will be customized and interactive. Each student in a smartly configured study group will be included by name in the text, and each student will read the particular text that is tailored for the student’s reading level. The previous reader will read a more complex text that includes all of the next reader’s vocabulary in order to scaffold reading for the less skillful student.
In the case where students read a personalized math word problem, the students will delete all distracting details, bold key information, and then create diagrams and explain in writing how they solved the problem. Their approach will then be projected and compared with the approaches of other groups.
DEVELOPMENTAL CURRICULUMS
Comprehension that leads to mastery always involves scaffolding or grafting of the new skill onto an older one. This is true in developing cognitive or motor skills and is well documented by brain-based learning research. The science of understanding the optimum developmental chains and the art of creating practice to develop these is challenging. For example, the math genius needs many fewer scaffolding steps and related practice than the student who is math challenged—but which steps does each require. Textbooks often lack thoughtful developmental sequences, and, where they are provided, they use a one-size-fits-all model. This is guaranteed to frustrate the challenged and bore the gifted.
COLLABORATIVE LEARNING
With the development of social network sites, IM, Open Source, and Wikis, the power of our drive to communicate, share, work and learn together has become the phenomena of Web 2.0. This is the song of our current digital age. If there is one lyric, it is let us sing our profound and silly songs together.
Given our natural drive to work, chatter and explore in groups, educators, going back to Dewey, have worked to get students out from behind their desks. We possess a wide range of strategies that support small and large group learning.
It is fair to say that cooperative learning is as well established in its patterns and proofs as any approach. Cooperative learning strategies can now be adapted, enriched and profoundly expanded through digital technologies.
Imagining the future, one can see students building a website that they use to post and discuss poetry they like (usually discovered at a poetry website tagged with del.icio.us, perhaps with a few sites recommended by the instructor). As students post their preferred poems, they place them in various categories, with some poems qualifying for many categories. Students explain their thinking and reflect on their experience of the poem. Discussions proliferate and groups develop around themes as diverse as pregnancy, mothering and soldiering. Written interactions in online discussions are analyzed by text parsing tools that provide feedback that characterize the interactions.
In writing we see collaborative learning and Instant Messaging as informal allies. The question in play is how to find ways to integrate the social dimensions of IM into more formal discourse—for example as planning or prewriting dialogues.
Web-searches that support educational ratings of websites should become widely used by collaborative project groups. For students this means they are evaluating the writing of others on multiple levels—for their search purpose and quality of argument, graphics, etc.
THEMATIC INTEGRATION
Another change in moving from an industrial process of producing textbooks to a community process of producing interactive, collaborative, and adaptable resources is that curriculum will finally begin to achieve the holy grail of thematic integration. The combination of teachers, specialists, artists and authors working with a wide-range of experts and having the benefit of student and teacher feedback within a digital environment will lead to integration of key ideas across subject areas.
Instructional design in and among subjects will improve while the connections among subjects will enrich inquiry and analysis. Finding the math patterns within various disciplines will become more prevalent. The process of using multiple means for representation of ideas will improve curriculums and processes of inquiry and synthesis of ideas. Students will engage more deeply as lessons become more collaborative and meaningful. So math, science, reading and writing, and history will no longer be taught in segregated silos and in fragmented ways on fragmented days.
This does not mean that in the information age there will be no place for large publishing companies. It does suggest, however, that for publishers to survive they will need to develop strategies to differentiate learners and customize resources. They also will need to find ways to engage communities in order to continuously improve resources.
COMMUNITIES THAT CONTINUOUSLY REFINE KNOWLEDGE
By using the digital environment as the product development and distribution system, public education will take a page (or screen) from the Wiki-movement exemplified by Wikipedia. Wikipedia holds the promise of containing all of a community’s knowledge on a given subject at a given time. It encourages the continuous evolution of that knowledge and how it is presented. Wikipedia is evolving a continuously improving information resource as it builds a vital online community.
The ability of educators to customize resources to fit the particular needs of their students is Wiki-like. Likewise the Wiki-curriculum and assessment communities will evolve their intellectual property within an equally vibrant, quality-motivated process.
This bottom-up curriculum and assessment development will also benefit from the Open Source model that produced Linux. Like the Wiki-community, the Open Source community has development tools and procedures for distributed, collaborative work and continuous improvement of resources. One of their contributions is the Digital Commons, an eEnvironment where programmers meet online to discuss problems, form workgroups, and leave code to be vetted, refined, and used in others’ projects.
The new IT-based schools will benefit from an Amazon.com, eBay (without auction) distribution model that demonstrates how bottom-up retailing communities can develop around a virtual store. This virtual store supports a shopping community with useful search capacities, ratings and reviews of products/providers. The crowd intelligence reflected in client ratings and reviews enables a community to inform and police itself.
**In addition to building resource development and distribution communities, IT will support the development of face-to-face communities. The walls between school, home, museum, zoo, business, university, artist’s studios and other community resources will become transparent. Administrators and teachers will have information that helps link students who will benefit from various kinds of support. Peer and cross-grade tutors, mentors, work-study and various in-community and online service and research projects will all be enriched by using information about students to connect them with people in a growing network of purpose driven entities.
Historically, there was great concern that computers would dehumanize classrooms and would decrease social interactions. Using the model presented here, we see IT linking individuals to improve engagement. For example a university researcher may team with teachers to develop a measurement instrument or a remediation procedure. The measurement instrument may be used online. The remediation procedure may include online lesson plans that involve rolling and catching balls on the floor with high school students interested in physics or physical education.
SOCIAL & ECONOMIC BENEFITS OF SMARTER COMMUNITIES
Building online and face-to-face educational communities linked through IT will save our schools, corporations and governments billions of dollars annually. These savings will come from costs associated with students who drop out and become members of a non-tax-paying under-class. The savings will also come from decreases in the population of underachievers who place themselves at-risk in so many ways that endanger themselves and others. Thus, the cost of the social safety net and of the judicial and prison system will decrease while the benefits flowing from people who contribute to society increase.
By helping more students realize their potential as students, workers and citizens, we will also improve the quality of the workforce and the polis. This will enable all countries to grow their economies and politics. The need and opportunities for local and global citizenship and workforce creativity and vigor has never been greater. Our health and wealth have never been more closely tied to our understanding of each other and our relationship to science, technology, one another, and our local and global ecologies.
**EDUCATION AS A BOTTOM UP ENTREPRENEURIAL ENTERPRISE
Viewed from an entrepreneur’s perspective, building IT-based educational communities will spawn huge opportunities for educators and educational consortiums—particularly among teams of individuals, schools, universities and research groups.
Traditionally underpaid, educators leave the profession to better their economic and expressive prospects. As classrooms become the essential laboratories, teaching will become more creative, collaborative, and rewarding and teachers will find themselves playing varied roles as valued partner.
Schools and districts that traditionally have seen themselves as consumers of curriculum will now see themselves as resource creators that can develop and publish educational materials. Those individuals and groups that produce successful products will be richly rewarded; yet the development, manufacturing, marketing and sales costs for producing these smart and smarter products will be a fraction of the costs associated with traditional publishing. Many of these savings will go to customers, many of which will also be creators and adaptors. Thus, the one-way direction of cash out of schools will become a cycle in which the school-based educational community becomes more profitable while the costs of goods decreases as quality increases.
THE LEARNING GENOME AND EDUCATION POLICY
As we develop pedagogies that fit individual learners, we will influence policy debates. One example is merit pay.Merit pay will become rational when we are able to view learning gains in relation to a learner potential. A gain of 2 months over the course of a school year may be a fine achievement for one student and teacher, while a gain of 2 years may not be satisfactory for another. Only when we understand the learning potential of each student can we gage a teacher’s achievements. Perhaps even more important, this kind of data will help the teacher and administrator to know the students each teacher is most and least capable of educating.
The reading wars represent another seemingly endless policy debate because we simply lack the science to differentiate those learners who learn best by emphasizing phonics versus those who do well within a more balanced or whole language regimen. The Learning Genome will help us see that different students benefit from different levels of each pedagogy and that most students do best when teachers integrate both approaches.
ORGANIZING TO BUILD A SMART SCHOOLING ENTERPRISE
To conceptualize and design pedagogy and instructional processes that are informed by R&D, we need to create a platform from which to build The Learning Genome and tailor smart learning resource and processes. The construction of this R&D, publishing and community-learning platform goes far beyond the scope and focus of current enterprises.
To form and manage this enterprise we need to establish a means to provide capital and shared ownership among educators, IT industries, foundations and public agencies. This will assure that local and global educational communities continuously benefit from the R&D and knowledge transmitting capacities that will drive this enterprise. This will be fundamental for moving industrial and pre-industrial societies into the information age. What The Genome Project promises for pharmaceuticals and 21st century medicine The Learning Genome and Smart Schooling promises for the development of education.
The U.S., EU, and many nations in Asia and Latin America are positioned to be leaders. As these groups refine this model and produce resources, they can help others to leapfrog over the industrial age built by the printing press. This community approach to public education is the foundation to move humanity toward a sustainable, quality future built on taking responsibility for creating cultures and networks that serve humanity’s future.
The U.S., working with global partners, will be well served to develop a clearly defined education initiative so we can help lead the world into an age of democracy and humanitarian purpose that provides the basis for increasing wealth in sustainable economies. To date there is no national strategy to guide new investment and to develop our educational communities around information age practices, but the need is stunning, the time is ripe, and our human and technical resources are ready.
Are you absolutely sure you want to delete this article? This process cannot be undone and is permanent.
Yes, Delete This Article
Are you absolutely sure you want to remove this article? This process cannot be undone and is permanent.
Yes, Remove This Article
Contact Us
Send to a Friend
Comments
Posted by Liza Loop on January 29, 2009 1:38 am
I'm with you. What do we do next? Guess I'll read the rest of this site. You, Jon, and your other readers might find some compatible ideas on my wiki cited below.
http://loopcntr.xwiki.com/xwiki/bin/view/Main/OpenEducativeSystems
Also check out www.loopcntr.org
Let's get to work
Liza Loop