Collaborative Research and Development
From IAE-Pedia
Contents |
Introduction
A human brain is naturally a curious, creative, and inventive problem solver. Long before the development of reading and writing, knowledge was developed by individuals and shared via show and tell, oral tradition, apprenticeships, and passing on artifacts from one generation to the next.
This accumulative knowledge-building was greatly aided by the development of reading and writing. With reading and writing, knowledge could be preserved and shared both by oral tradition and face-to-face sharing, but also via publication.
Early universities were places where libraries of written material and artifacts were accumulated, and people came together both to use these resources and for scholarly communications. A university might house research instruments and tools such as a telescope or chemistry laboratory.
While research, invention, and development (for simplicity, let's just call it R&D) could be carried out by a single individual, the support provided by the resources and people in a university or research center could well increase productivity.
Nowadays
Nowadays we have R&D centers located throughout the world. Both the people working together and the resources they draw upon may be widely dispersed. Information and Communication Technology help in communication among the people and the shared use of facilities such as the Hadron Collider, the Hubble Telescope, the International Space Station, Supercomputers, and virtual libraries such as the Web. There is considerable international collaboration in medical research and attempting to deal with worldwide health issues. The eradication of smallpox is a great story of success, and progress in dealing with AIDS is being made by a huge number of teams of researchers who are both competitive and collaborative.
Educational Implications
There is still room in our world for the solitary R&D person. However, progress in attacking many of the R&D-related problems confronting people and our world tends to require teams of people, facilitated by support staff and R&D tools.
Thus, our education system faces the task of helping students to develop the types of knowledge and skills useful in collaborative R&D and other types of work. This challenge is often talked about in terms of sports in which a group of players must learn to work together as a team. It is also standard to talk about the employees in a company working together as a team.
Such collaboration is common in academic learning environments. Good examples can be found in situations where students work together on projects, where students form and effectively use study groups, where students learn to provide constructive criticism and useful formative evaluation to each other, and so on.
On the other hand, formal education has a very strong competitive orientation. In some sense, each individual student is competing against other students in terms of a grading system and a process of grading "on a curve." The design of an assessment instrument typically includes a focus on producing a spread of results.
There is another very important educational implication that is not being addressed very well. The R&D and other teams or groups of workers make routine use of Information and Communication Technology and quite powerful tools. However, typically students are not allowed to use such tools when they are taking tests. Our educational system has not yet adjusted to the basic tenets of Computational Thinking and that two brains (human plus computer) are frequently better than one.
Evergreen State College
Quoting from http://en.wikipedia.org/wiki/The_Evergreen_State_College:
- The Evergreen State College is an accredited public liberal arts college and is a member of the Council of Public Liberal Arts Colleges that is located in Olympia, Washington, USA. Founded in 1967, Evergreen was formed to be an experimental and non-traditional college. Faculty issue narrative evaluations of students' work rather than grades, and Evergreen organizes most studies into largely interdisciplinary classes that generally constitute a full-time course load.
…
- Evergreen is unique in that undergraduate students select a program for the entire quarter rather than multiple courses. Full time programs will encompass a quarter's worth of work in everything related to that program concentration. Students have the freedom to choose what courses they feel they need and they are not required to follow a specific set of programs. At the end of the program the professor writes a one page report about the student's activity in the class rather than a letter grade. The professor also determines how many credits should be awarded to the student. [Bold added for emphasis.]
Collaboration Without Pay
In their routine, everyday activities, humans interact with each other and provided services without remuneration to each other. This might be a small think like holding a door open to politely assist a person following you. It might be providing directions to a question such as, "Where is the nearest grocery store?"
The Internet has facilitated some very large scale collaborative efforts in which people work without remuneration. The Wikipedia is typically held up as a prime example. However, there are a great many examples of Crowd Sourcing. In essence, a great many people are willing to share their expertise and to contribute to the common good.
Crowdsourcing
The following is quoted from the iRevolution Website:
- The use of crowdsourcing may be relatively new to the technology, business and humanitarian sectors but when it comes to statistics, crowdsourcing is a well known and established sampling method. Crowdsourcing is just non-probability sampling. The crowdsourcing of crisis information is simply an application of non-probability sampling.
- Lets first review probability sampling in which every unit in the population being sampled has a known probability (greater than zero) of being selected. This approach makes it possible to “produce unbiased estimates of population totals, by weighting sampled units according to their probability selection.”
- Non-probability sampling, on the other hand, describes an approach in which some units of the population have no chance of being selected or where the probability of selection cannot be accurately determined. An example is convenience sampling. The main drawback of non-probability sampling techniques is that “information about the relationship between sample and population is limited, making it difficult to extrapolate from the sample to the population.”
A Math Research Example
An 8/01/2010 article by Lisa Krieger summarizes a crowd sourcing type of collaboration among research mathematicians. Quoting from the article:
- Have you been pondering the probability that two random integers are relatively prime? The answer -- 6/π² -- awaits you in cyberspace.
- In a stunning example of the power of the Internet to attract and connect the smartest minds on earth around the most difficult problems, scholars at UC Berkeley and Stanford have created a free website, called MathOverflow, which is transforming math research.
- The format is simple. By linking questions and answers from hands-on participants, each small solution builds toward a larger understanding, accelerating research. And it proves that mass collaboration can greatly expand human problem-solving abilities.
References
IAE Wiki (n.d.) Crowdsourcing to improve education. Retrieved 8/30 2010 from http://iae-pedia.org/Crowdsourcing_to_Improve_Education.
iRevolution (6/28/2010). Demystifying Crowdsourcing: An Introduction to Non-Probability Sampling. retrieved 8/30/2010 from http://irevolution.wordpress.com/2010/06/28/demystifying-crowdsourcing/.
Krieger, Lisa M (8/8/2010). Stanford and UC Berkeley create massively collaborative math. Mercury News. Retrieved 8/30/2010 from http://www.mercurynews.com/top-stories/ci_15713739?nclick_check=1. The end of the article includes links to Other references: MathOverflow.net, the wiki ncatlab.org, and the blog polymathprojects.org, and mentions the or online journals MathSciNet and arXiv.
Author or Authors
The original version of this document was developed by David Moursund.
