Computer science is the spine that has created a continually improving R&D and distribution system in nearly every major endeavor. Examples include science, engineering, social science, medicine, retail, aviation, and entertainment. It has given us systems, tools, and techniques to enable us to design, organize, adapt, and share knowledge and techniques. That said, the largest knowledge industry and the one that touches the most people and is most important for the quality of people's lives and our future education is not supported by a systematic, scientific R&D agenda.
To successfully reimagine learning, we need to optimize computer science to re-engineer and deepen our thinking about human nature, learning, design, and social interactions. By applying best practices from SEL (Social Emotional Learning) and STEAM (Science, Technology, Engineering, Arts, Mathematics), we can evolve toward personalizing learning for all students by designing robust and engaging curriculum that aligns with the stages, diversities, motivations, and idiosyncrasies unique people’s development.
These efforts will immerse students in a SEL and STEAM culture where they co-design their learning experiences. This will give students a practical initiation into our 21st century knowledge economy.
Let's consider the realms of computer science and engineering that will be foundational for building fully reimagined learning processes. These include R&D in social interactions, research into all dimensions of diversity among students and teachers, knowledge engineering, and new design paradigms.
The many roles of computer science and engineering in 21st century learning systems
1. Social Engineering helps us to use technology wedded to our social, cultural, psychological, and community-organizing sciences to create smart, compatible learning groups. These groups allow the intelligent connection of students and teachers with the appropriate peers, tutors, cross-age role models, and mentors.
As we move towards personalized learning, we are challenged to learn about the unique dimensions of each person in our community. We should ask: how can we use computer science to learn about the range and depth of sensory, social, emotional, intuitive, and cognitive traits and values that will enable us to support and enrich the lives of students, teachers, administrators, parents, and others.
Think of the possibilities if we were to adapt and extend some of the computer science used by online matchmaking services and product marketing. Our social networks for student support would go far beyond dating and volunteer matching services -- we would explore personality traits, goals, interests, cultural considerations, communication, learning styles, and other dimensions we've yet to consider. Such social networks would be dynamic and self-refining, as they would continually gain machine and human intelligence through use, users, and changing purposes.
We can profoundly improve learning if we put the entire local, face-to-face, and virtual community at our students' and teachers' fingertips. This means that every student, whether their passion is rocks or rockets, music or mountaineering, math or mashed potatoes, can find congenial peers and experts, friends and collaborators, facilitators and a supportive audience to support their interests.
Given our deep drives to work and learn together to solve authentic personal, social, cultural, and environmental problems, having access to focused social networks can propel learning into the realms of service that will help establish purpose, identity, and compassion.
The implications of building and improving social networks for students, teachers, administrators, and curriculum designers can't be overestimated.
2. Research Engineering will help us to better understand and respond to the diversity among students, teachers, parents, and community members. This research will build from a rich variety of non-invasive measures correlated with observations and reflections. The science of building systems to improve data will help us design and align personalized learning experiences.
Essential factors to understanding the wide range of variables that influence each student's learning include sensory capacities, concentration, working memory, motivations, background knowledge, openness, perseverance, interests and so much more.
Recognizing that a learner's sense of purpose affects cognition and imagination and is built on a social-emotional footing means we need to focus research on identifying the social-emotional experiences that build solid foundations within each student and teacher.
One under explored area is a smart learner portfolio that will also include social networking with family, friends, and mentors., Social and machine feedback features and appreciations will be balanced. Simply having information about learners' writing in terms of the richness of vocabulary, syntax, and other machine measurable variables will indicate a great deal about student engagement and cognitive development.
The implications of students, teachers, mentors and curriculum designers understanding key dimensions of diversity are profound beyond our current imagining.
3. Knowledge Engineering grows directly from Research Engineering, and extends into the design, organization, and sharing of learning experiences.
There are many ways to apply technology to support the design, organization and continuous improvement of learning experiences. The content of a learning experience, be it a lecture, video, field trip, poem, story, simulation, or service project can and should have many designs that will improve access across different ranges of ability, interest, and talent.
For example, the same story can be written at multiple reading levels and in many languages. This represents an important step toward Universal Design for Learning, a framework to improve and optimize teaching and learning for everyone based on insights into diversity.
We should note that not all curriculum created by technology supported design should be online, far from it! Small group discussions, texts, board games, simulations, worksheets, community service and environmental projects should be designed and supported by technology, yet many of the activities would be done away from the computer screen, and many will involve using mobile devices in the field.
Knowledge Engineering provides a framework for refining and applying our understanding of the scope, sequence, and scaffolds to optimize learning. It helps manage customization, version control, and dissemination. It also uses the data about the student like reading level, interests, and favorite friends to provide students with a good set of customized choices about what, how, when, where, and with whom each student would like to learn.
4. Design Engineering is a subset of Knowledge Engineering. It provides educator-designers a unique set of design, presentation, interaction, assessment, and feedback tools to help design teams shape their designs to fit the wide-ranging sensory, affective, cognitive, intuitive, and aesthetic needs of students, teachers and communities.
The first principles of design are: 1) design with and in the presence of the people and community you serve; and 2) create something your clients' love; and 3) be able to adapt and modify based on experience..
To achieve these, it's essential that teachers and students be co-designers. Designers need to watch and listen. They need to ask for help and feedback. Great design is inspired by love for the users and love for the subject or skill to be mastered.
When we connect social and knowledge engineering to research and design, we can make our classrooms into smart design studios in which in-residence, cross-discipline teams participate and become co-creators with students and teachers.
A digital latticework that is created and maintained by in-residence computer scientists and engineers who continually evolve the system to serve the learning community's needs is fundamental to support this design work.
CONCLUSION
This SEL, STEAM approach enables local educators and community members to apply intentional design within their school so it is localized and continually improves based on knowledge about learner diversity. In this way we can create an ever more engaging curriculum that is adaptable to individual students and teachers, local conditions, needs, and talents.
This approach promises to deepen each community’s insight, talent and care for the amazing sensitivity, talent, and needs of the next generation. In this way we can discover and optimize a common 21st century spirit devoted to gaining and applying knowledge to enlarge and serve humanity. As we grow into our role as knowledge workers, we will become lifelong learners and creators. Education will become the work of creating a culture that aligns with serving human development within nurturing, smart, and inspired communities.