Contributors: Judi Fusco and Nora Sabelli
This brief summarizes the main points of the Cyber Workforce Development (CLWD) Task Force Report; more detailed technical considerations can be found in the report itself.
Continuous Collaborative Computational Cloud (C4) environment
As our economy becomes increasingly knowledge-based and dependent on technology, our workforce requires a larger number of individuals more competent in science, technology, engineering and mathematics (STEM). New industries and jobs are based on science and engineering and are more computational and data-intensive (CDS&E). A recent report by the NSF Cyberlearning Workforce Development (CLWD) Task Force  notes a growing mismatch between education and curricula, and the workforce needs of employers, including universities. The report makes recommendations for NSF’s role in new cyberinfrastructure and cyberlearning research and education strategies to achieve a workforce technologically competent and competitive. The recommendations will not be mentioned here in detail. Instead, we will summarize the sections that deal principally with research and education.
The report looks at how cyberlearning fundamentally changes how people seek knowledge and skills, and comments on how it should be used to become a lifelong learning resource and how it can provide access to disadvantaged or disconnected individuals, thus addressing society’s need for full workforce inclusion. The report includes sections on Higher Education, Cyberlearning, K-14 and Lifelong Learning, Campus Infrastructure, and Broadening Participation. In this brief, we will concentrate on the first two and mention briefly the last one.
Higher Education and Society Issues
The CWLD Task Force report is based is a conception of the cyberinfrastructure as a Continuous Collaborative Computational Cloud (C4) environment that supports the preparation of professional careers that require CDS&E thinking. The authors discuss their vision for how the concept of an integrated C4 environment could potentially transform our educational systems from pre-K through college and beyond (pre-K through Gray), and more seamlessly blend the formal and informal learning worlds. Tools and technology built around integration implied by C4 would seamlessly connect networks, servers, personal-devices (e.g., laptops, smart phones, and others) and supercomputers. They would help provide just-in-time access to the personalized knowledge individuals need and could replace textbooks with dynamic learning environments better suited to the continuous advances that will confront the Net Generation workforce. Cyberlearning fundamentally changes how people seek new knowledge and skills and can reduce barriers for those who are disadvantaged or disconnected.
The following paragraph from the Higher Education section is worth highlighting (italicized paragraphs are taken verbatim from the report): In order to meet the challenge, the NSF should introspectively … articulate a vision for the future, and equally important, articulate processes and metrics to define how to execute on that vision and how to measure the outcomes. While predictions regarding this digital transformation have been around as long as computers have existed, we believe that a primary measure of success will be the extent to which students and the workforce in 2020 look to C4 for their principal means for lifelong learning.
Cyberlearning Research, Community, and Education
The Cyberlearning section points out that basic research issues underlie some of the problems with present actions and policy. As a consequence, the report calls for the cyberlearning community to incorporate the additional expertise of disciplines such as social and organizational sciences, political science, economics, and others that have not traditionally engaged with learning. The needed community does not exist now—its creation is a first task to undertake.
The Task force used the following statement to clarify the meaning of cyberlearning:
Cyberlearning is learning (personal, social, and distributed) that is mediated by a variety of rapidly evolving computational devices, (e.g., computers, smart phones), and CI (e.g., Web, Cloud). In this complex environment, cyberlearning should strive to be coherent across platforms and settings.
Cyberlearning is not only about learning to use computers or to think computationally. Social networking has made it clear that the need is much more encompassing, including new modes of collaborating and of learning for the full variety of human experiences mediated by networked computing and communications technologies.
Cyberlearning is especially relevant to STEM learning, where it is critical for mediating the learning of computational thinking skills and the effective use of the cyberinfrastructure; its challenges and promise will affect learning in all areas (humanities, arts, science, engineering, etc.) and settings (school, workplace, home, public spaces).
The educational system needs to undergo a paradigm shift to address the new need, created by a pervasive C4 environment, to upgrade skills, learn new topics and individualize learning. This need is not restricted to technology professionals, and the affordances of a C4 environment can help lead to learning modalities support the larger need since it engages innate natural learning processes: it is more interactive, pedagogically Socratic, adaptive, and supporting “just-in-time” learning. Our educational system was designed in the past when it was necessary to give all students a standard and common set of educational skills and knowledge. Standardization was useful when our economy was based on jobs of mass production where workers could be trained initially and then work in a similar manner over their entire careers. Now, new sets of skills are continually needed in knowledge work. Standardized curriculum and testing doesn’t help students learn what they need. Our educational system needs to undergo a paradigm shift and help support people learn throughout their lives as they need new skills and knowledge.
Further, C4 could help break down rigid barriers between departments at the collegiate level, allow science and engineering students to engage in more collaborative learning and thus support the ““long tail” of “modest-sized” science and engineering which will soon emerge to become the dominant “consumer of Cyberinfrastructure” (p. 28). The report urges NSF and other agencies to work together to help develop a new platform for research and education that will take C4 and collaborative learning in different departments to a new level (p. 30).
Ubiquitous high bandwidth connectivity, even in rural and remote areas will likely characterize most of the U.S. if not the world in the relatively near future. Today the computational Cloud is a set of uncoordinated systems that must be explicitly connected to obtain service; that will surely change. The CWLD Task Force envisions that by 2020 an integrated C4 will be an important part of our lives, as a much larger, more encompassing, constant experience; a reasonable criterion of its successful should be its degree of non-intrusiveness and transparency. Cyberlearing in 2020 will not be constrained to the classroom or laboratory experiences, because students will use robots, sensors, and smart devices to enter active volcanoes, explore the depths of the oceans, or a crowded and polluted metropolis to gather data and conduct science and social experiments never before possible (or even necessary).
The Task Force identified several characteristics of an C4 Education Vision for Content—the Schools in 2020. We list these characteristics without discussion—the reader should consult the report itself for justifications and details. We refer readers to pages 32-37 in the Cyberlearning Task Force Report for more on these points to help explain the vision for C4.
- Didactic vs. Inquiry-driven Self learning as a Core Concept
- Push vs. Pull as a Core Concept
- Learning Environments not restricted to the school setting
- Continuous evaluation and reporting of learners’ progress
- Flexible Dynamic Definition of Grades and Learning Levels
- Educational Gaming and realistic model and simulation-based exploration of concepts in STEM.
- Targeted certification and training opportunities in vocational education
- Broadening participation by making generally available remote resources, tools, and expertise
The science resulting from the envisioned C4 environment presents a challenge to computer science, mathematics, and engineering on the machine and machine-intelligence side, to education and the learning sciences on the human resources side and to society, as well. The societal challenges relate to data storage and human computer interaction differing needs of non-technology stakeholders, such as teachers, students, parents, principals, district-level staff and leadership, researchers and policy-makers—society in general. The role of C4 in the learning process will be, in the words of the task force, “disruptive and revolutionary”, and require re-thinking learning at a national and systemic level, and a focus on appropriate tools.
Significant research opportunities exist in the area of better data reporting and analysis. Much work is needed in human-computer interaction and design research to customize data reporting for the different needs of stakeholders, including teachers, parents, principals, superintendents, policy makers, researchers, and learners themselves. Better visualizations of learning data are needed, as well as tools for online collaborative analysis of data that can benefit from the wisdom of crowds. The state of the art possible in sense-making with interactive data visualizations is illustrated in Hans Rosling’s GapMinder  we need such tools for educational and learning data. (p 42)
The CWFD Report supports instilling into the NSF’s cyberlearning activities a “platform perspective”—shared, interoperable designs of hardware, software, and services.
Critical challenges to creating an effective platform are community (formations of teams that bring multi-disci¬plinary expertise to bear), cumulativity (building on promising innovations from prior technology projects), and sustainability. A cyberlearning platform should not only be a cognitive platform, but also be a metacognitive platform, one that is built to improve through reflection on past performance. The biggest challenge to creating a metacognitive platform is that the platform and its users have access to quality assessment data on learners’ progress and critical inputs to that progress, including from teachers.
Games for education was considered to be is a topic of current interest, seen as relevant to computational thinking and to providing active social learning experiences in computational and data intensive science and engineering.
On the technical side, achieving the seamless C4 vision requires a government, higher education, and industry partnership to develop common standards, such as the successful effort that resulted in the current standard Internet protocol, TCP/IP. Research organizations that depend on the cyberinfrastructure, such as the TeraGrid successor and the Open Science Grid will be essential to the process. These points are retaken in other sections of the Task Force report.
Creating a nation-wide collaborative computing cloud will require more cooperation than we have ever seen among the stakeholders in the world of education.
It’s not clear how C4 is different from the internet, with it’s variety of resources and services. Be more specific about how it would be different, and why the current internet can’t support the specific needs.
Related areas in Cyberlearning
(All Cyberlearning areas are related)
National Science Foundation, Advisory Committee for Cyberinfrastructure Task Force on Cyberlearning and Work Force Development. (March, 2001). A Report of the National Science Foundation Advisory Committee for Cyberinfrastructure.