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The Informed Brain in a Digital World
Interdisciplinary Research Team Challenges

The Informed Brain in a Digital World Interdisciplinary Research Team Challenge 1:
Develop innovative curricula that will help students develop expertise in dealing with the inofrmation overload they will encounter during and after their schooling.

Challenge Summary
While the age in which we live has been termed the Age of Information, it also seems self-evident that the system by which we educate our youth is failing to produce the self-motivated, skilled citizen who can acquire, analyze and create information that will contribute to the health and welfare of society. Even before the advent of the internet and the access to enormous petabytes of machine-readable text, U.S. corporations bemoaned their requirement to spend millions of dollars to teach high school graduates to read, write and perform basic mathematics. American students place well down the list of proficient students among lesser industrialized nations.  Thanks to decades of intermittent federal investments in biomedical research, the pool of factual data amenable to analysis, and which should become part of all new physicians’ operational skills is becoming so large as to be unmanageable.

This IDR Team will engage with the crisis in education and the lack of a strategy to devise tools for efficient learning and will involve the intersection of neuroscience, engineering, and medical research. Under this umbrella neuroscientists who study memory and learning, attention, and decision making, could work with engineers and educators to develop innovative curricula that would help our young students cultivate expertise in dealing with the information overload they will encounter in and after their schooling. This broad topic represents a massive opportunity to create what Branscomb, Holton and Sonnert (2001) have termed “cutting edge research in the service of public objectives,” and what is sometimes abbreviated as “Science for Society” or “Jeffersonian Science”.

One major test ground for the implementation of methods for efficient lifelong learning could focus on the medical student who must learn not only the relevant facts and their application to disease mechanisms, treatment, diagnosis and prevention, but also to assimilate into that body of working knowledge all the new facts that will emerge during their careers as practicing physicians.  This is also the case confronting tomorrow's clinical trainees – and the paraprofessionals who will be needed to support them; the ever more rapid medical discoveries that need to be translated into care and prevention, the lack of time to train in federally funded residency programs and additional constraints imposed on this training by maximum hour work weeks, and a national healthcare plan that will reduce the Medicare funding for post-graduate clinical training.

While the IBM-Watson device and proprietary differential diagnostic systems – costing hundreds of thousands of dollars – are beginning to enter some forms of managed healthcare, such computer-assisted judgments can scarcely be an acceptable form of medical practice.  Therefore, the underlying problem remains of devising an educational system that will not only motivate students to become skilled in basic academics, in the technology of any occupational discipline, but also evolve into a citizen who contributes back to society. Can a formal education system include only academic basics for collecting knowledge, or should it also include understanding the value of that knowledge, the processing of knowledge, the emotional value of inspiration, creativity, risk, and resilience from failures?

Two developments based on the use of information technology to support instruction and discovery that show some promise are learning management systems (LMSs) and the developing Semantic Web.  The use of learning management systems, both proprietary and open source, to support traditional face-to-face instruction has been in place and widely practiced for well over a decade, but there is decidedly little scientific assessment of effectiveness. For those caught on the analog side of the digital divide, persons located in places ill served by telecommunications, the cadre of essential computer and network support personnel, and the instructors adept and willing to exploit the possibilities of LMSs, the possibilities are limited. 

For those in the middle-of-the-bell-curve of usage of information communications and technologies, there seems to be benefits to the use of LMSs, such as: more efficient administration of courses with more supplemental materials, collaborative document creation, online study sessions, and practice and exams with final grades transmitted directly to student information systems. On-campus users of LMSs seem to interact more with the Web-based course support than do commuter students, but both improve performance in a course supported by an LMS.  Among the environmental elements not tested is that of the engagement of social networking behaviors (via the likes of Facebook, Twitter, blogging, and similar) on intellectual development. Seemingly important information appearing as a result of a Web search on Google or Bing or similar have not been studied with the possible exception of the Stanford experiment by Thrun et al, who broadcast a course on Artificial Intelligence to over 100,000 “students” anywhere on this Earth.  These experiments, and others such as asynchronous audio or visual course LMSs, deserve critical analysis.

The Semantic Web, a theoretical proposition envisioned by Tim Berners-Lee, the “inventor” of the World Wide Web, is intended to supersede the present chaos of the Web by the creation of a massive collection of information objects on the web that “understand” one another in a machine sense, to create a structured web of documents enabling much more efficient retrieval of relevant information objects in response to human queries.  As the number of machine readable statements of relationships with associated, unchanging web addresses for the related information objects expands dramatically, the likelihood of the improvement of discovery of numerous ideas, objects, and references in numerous formats and genres that are highly relevant increases, while the time and effort necessary to search and retrieve those will decline dramatically, and hot links to the initial investigative entry will be created.  The potential for computer-assisted lifelong learning as well as computer-assisted research at the highest level is also increased, without regard for the flood of new data joining the swamp of older data on the Web.  The ability of these new agents to increase our intellectual reach without the necessity of remembering any more than the essence of the most relevant documents and the taxonomy of terms in the combined essences of one’s interests will expand our ability to deal with the flood and the swamp.  Humans’ responsibilities to remember will become more nuanced, but our abilities or duties to understand, analyze, evaluate, and then apply knowledge will increase.  The creation of new knowledge and the discovery of new relationships among ideas and facts and systems will advance the state of our comprehension of our world from the most atomic or even subatomic frame to the cosmological.  The contributions made possible by this quiet revolution will address matters of human health, our environment, transportation systems, education, and all the other aspects of our lives susceptible to rational thought and discourse.

Key Questions
Can human knowledge acquisition and creation be made more efficient or more efficacious with computer-assisted learning systems, and if so at what price in what time and in which arenas of society?

In which domains of learning, could such devices improve learning efficiency and in which are such improvements less certain?

Is medicine/health the most societally-important test ground in which to apply such a learning system, or would the end result be improved with a longer time frame by starting with another test ground such as infants/toddlers?

What is the evidence that scientific understanding has become more comprehensive and facile since scholarly journals went digital?  Do scientists read more or less? Do they have deeper knowledge of their areas of specialization? Has time spent on literature researching improved the speed or breadth of discovery?

Is there evidence that the brain is changing as the attributes of the World Wide Web, including social networking, are accessed often by various age cohorts?

Suggested Reading
Berners-Lee T, Hendler J, and Lassila O. The Semantic Web. Scientific American 17 May 2001;284;34-43.  (Preview available online: http://www.scientificamerican.com/article.cfm?id=the-semantic-web-overview.)

Bird S, Bradshaw D, Chan WK, Clark C, Mears A, Milton U, Nuttall C, Palin A, Petroff A, Scholten B, Smith E. Online learning.  Financial Times (Special Report) 12 March 2012.  (Accessed online March 28, 2012: http://www.ft.com/intl/reports/online-learning-2011.)

Bloom B. Taxonomy of learning domains.  5 June 1999. (Accessed online January 31, 2012: http://www.nwlink.com/~donclark/hrd/bloom.html).

Branscomb L, Holton G, Sonnert G, Packard and Sloan Foundations. Science for society: Cutting edge basic research in the service of public objectiveness. A blueprint for intellectually bold and socially beneficial science policy, 2001. (Accessed online January 31, 2012: http://www.cspo.org/products/reports/scienceforsociety.pdf.)

Brown E.  IBM Watson: Final Jeopardy! And the future of Watson.  TED Presentation.  (Accessed online January 31, 2012: http://www.ted.com/pages/593.) 

Council on Library and Information Resources.  Linked data for libraries, museums, and archives: survey and workshop report October 2011.  (Accessed online January 31, 2012: http://www.clir.org/pubs/abstract/pub152abst.html.)

Keller MA. Linked data: a way out of the information chaos and toward the semantic web. Educause Review  July/August 2011;46(4).  (Accessed online January 31, 2012: http://www.educause.edu/EDUCAUSE+Review/EDUCAUSEReviewMagazineVolume46/LinkedDataAWay
OutoftheInformat/231827
.)

Thrun S, et. al. MIT/Stanford artificial intelligence experiment.  Wikipedia. (Accessed online March 28, 2012: http://en.wikipedia.org/wiki/Sebastian_Thrun.)

Watson, D. Pedagogy before technology: Re-thinking the relationship between ICT and teaching. Education and Information Technologies 2001;6(4):251-266.  (Abstract accessed online January 31, 2012: http://www.mendeley.com/research/pedagogy-before-technology-rethinking-the-relationship-between-ict-and-teaching/.)