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* Challenging assumptions: Once it has established what they are, learning organization must constantly challenge its processes, instructions, assumptions and even its basic structure. The true learning organization is redesigning itself constantly.
* Challenging assumptions: Once it has established what they are, learning organization must constantly challenge its processes, instructions, assumptions and even its basic structure. The true learning organization is redesigning itself constantly.


==Scientific Learning Organizations==

The tools of ‘[[knowing]]’ & ‘l[[earning]]’ that are employed by professional [[scientific]] organizations are not the same approaches as those used by other disciplines for ‘knowing’ and ‘learning’.

Once simply an idle curiosity, this difference in how scientific organizations ‘know’ and ‘learn’ vis-à-vis how other professional disciplines ‘know’ and ‘learn’ has become a vital research interest in the [[Science]] & [[Technology]] [[Information Age]] of the 21st Century. As a result, new insights about those [[knowledge]] creation approaches that ‘work’ in scientific learning organizations, as compared to those that don’t, are rapidly emerging.

Many factors are likely driving the new field of scientific learning organization research, including a re-examination of science-based social infrastructure elements that were originally built upon older [[Industrial Revolution]] tools & approaches. Many of these [[science]]-based [[social]]-support programs (like the U.S. [[Medicare]] System) are becoming over-burdened with new demands for services and resources.

The single most-important factor that is driving the active investigation of the performance of scientific learning organizations is the recognition that many Western societies are increasingly depending upon '''''this specific pattern of professional learning & knowledge-creation''''' to drive their newly-emerging economies: As many Western societies lose their industrial & manufacturing business-bases, most are also rapidly transforming into [[Science]]-'''Based''' [[Societies]].

It is important to recognize that because of the advent of the [[Internet]] and global scientific information sharing, all western scientific organizations (especially government-supported healthcare organizations) are scientific learning organizations. The central question for any specific scientific organization is whether it qualifies as a 'high-performing scientific learning organization'.

Scientists now recognize that the majority of [[organizational learning]] tools, when applied to the various disciplines of science (particularly in the United States), are subject to three very powerful constraints, giving rise to a specific set of scientific learning tools for scientific learning organizations.

The three central constraints to learning (creating new [[scientific knowledge]]) in scientific learning organizations are:

1. All [[grant]]-funded science, and particularly [[government]]-supported medicine, in most Western nations is conducted in a [[community of practice]] setting, which provides rigid restraints on the creation and use of [[scientific knowledge]];

2. All scientific [[knowledge]] derives from (and also influences) scientific [[information]], and all scientific information derives from scientific [[data]]; and

3. All scientific knowledge that is created and improved by the organization must reflect the use of the [[scientific method]].

Since the publication of the landmark “'''''Communities of Practice'''''” research paper by William Snyder and Xavier de Souza Briggs in 2003, it has been recognized that '''all grant-funded and/or government-supported scientific endeavors''' in most Western nations, such as the U.S., '''are conducted within the context of a scientific community of practice''' (CoP) ( [http://www.businessofgovernment.org/pdfs/Snyder_report.pdf] ): Scientific CoPs steward the knowledge-assets of scientific organizations: They also steward the learning assets of such organizations. '''The quality of any organization’s scientific knowledge- and learning-assets can be measured scientifically'''. Thus, effective scientific learning organizations must be aware of the CoP constraint upon their operation, and they must learn to create new knowledge accordingly. The U.S. [[National Institutes of Health]] (NIH) has recently acknowledged the validity and the power of the scientific communities of practice approach to measuring the value of its processes for accumulating new scientific knowledge with the launching of the new '''NIH Office of Behavioral & Social Science Research''' intiative (see page 5 of the '''NIH "Healthier Lives Through Behavioral & Social Sciences Research" Report''' { [http://obssr.od.nih.gov/OBSSR10th/pdf/OBSSR%20Brochure.pdf] }

All scientific learning organizations depend upon [[scientific knowledge]] for their proper operation: After all, the Latin root word for ‘science’ means ‘having knowledge’. In addition, the pace of change in the flow of new scientific information and knowledge requires that all scientific learning organizations, particularly in the field of medicine, be capable of synthesizing new scientific knowledge ( = scientific learning). '''Scientific learning organizations are constrained by in the creation of new knowledge by the DIK scientific learning pathway''' ( [http://www.systems-thinking.org/dikw/dikw.htm] ). In their 2004 '''''“Data, Information, Knowledge, and Wisdom”''''' paper, Gene Bellinger, Durval Castro, and Anthony Mills outline the basic steps of the DIK learning pathway:

• In scientific CoPs, scientific [[knowledge]] constitutes ‘the ability to predict the pattern of responses’ and is derived from (and also influences) a specific cluster of scientific information.

• Scientific [[information]] functionally operates as ‘a new insight about relationships between data that places a demand on the attention of the scientific-observer’, and is derived from a specific grouping of scientific data.

• In turn, scientific [[data]] are simply the infinite facts of the universe itself, which serve as the basis for all scientific inquiry and discovery.

Thus, effective scientific learning organizations must be aware of the DIK learning pathway constraint upon their operation, and they must learn to manage their scientific knowledge creation processes accordingly.

Finally, '''all scientific learning organizations, by definition, must adhere to the [[scientific method]] in the process of creating and improving their scientific knowledge'''. As reviewed elsewhere in Wikipedia, the [[scientific method]] has many different interpretations, particularly with regard to those instances where a ‘scientific [[paradigm shift]]' occurs. At the same time, in its most basic and conservative form, the scientific method has a well-established core framework for decision-making & learning, as summarized by W. L. Jerome in a 1994 scientific research article entitled “'''''The Scientific Method'''''”, ( [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=7865018&dopt=Abstract] ). In its most basic form, the scientific method is a structured thought & action process that leads to the creation of new scientific knowledge, and it contains the following basic steps:

• [[Questions]];

• [[Hypothesis]] generation;

• [[Predictions]];

• Design of appropriately-controlled [[experiments]];

• Proper collection of experimental '''results''';

• Appropriate interpretation of [[evidence]];

• Honest sharing of new knowledge and pertinent [[methodologies]] with others; and

• Checking for [[reproducibility]] of results and scientific conclusions by others.

Effective scientific learning organizations must be aware of the limitations and constraints on knowledge creation and knowledge development that are imposed by the [[scientific method]], and they must learn to manage their organizational operations accordingly.



Modern scientific learning organizations and scientific learning societies must also address (by avoiding) four additional [[performance]]-impeding elements in the design of their scientific learning systems.

• [[Scientific]]-[[Information]] [[Overload]]: Too much scientific-information demanding the attention of the members of the scientific [[community of practice]]. Scientific information overload leaves members feeling ‘dazed & [[confused]]’.

• [[Scientific]]-[[Knowledge]] [[Overload]]: Too much scientific-knowledge to be actionable by the members of the scientific community-of-practice. Scientific knowledge overload tends to create an experience of '[[guilt]]' in scientific learning organization members.

• [[Scientific]] [[Discipline]]-[[Fragmentation]]: The inability of members of one scientific sub-discipline to learn with members of another scientific sub-discipline. Scientific discipline-fragmentation is also known as ‘the professional silo’ or ‘Tower of Babel’ syndrome.

• '''Low''' [[Scientific]] [[Moral]]-[[Meaning]]: This syndrome refers to a state of [[uncertainty]] within a scientific community of practice, upon any given exchange of scientific knowledge, about whether this new knowledge will promote a new state where all CoP members will be valued and supported. This scientific [[moral]]-[[meaning]] [[uncertainty]] tends to be experienced as ‘[[fear]]’: As Dr. [[Robert Bellah]] (University of California, Berkeley) describes: “The awareness of interconnectedness, in the absence of moral-meaning, is terrifying.”

Fortunately, the proper use of scientific learning organization tools( that operate cleanly within the first three above-cited scientific learning organization constraints) is capable of also avoiding these four performance-impeding syndromes. By deliberately and consciously avoiding these challenges, high-performing scientific CoPs are able to position their members for the #1 priority of the organization: [[Scientific]]-[[learning]] (scientifically defined as ‘changing the meaning of life-experience, by the creation of new scientific knowledge, using the scientific method’).



Expressed in [[Venn Diagram]] visual terms, scientific learning organization tools are designed to operate in the space where

1. the scientific CoP constraint,

2. the DIK scientific learning pathway constraint, and

3. the scientific method constraint

intersect.

The beauty and the performance advantage of the scientific learning organization approach is that their proper use does not place the user(s) in conflict with any of the core tenets of the discipline of science itself.


It is worth noting that scientific learning organizations are not capable of creating any form of ' [[truth]] ', at least not in any traditional sense. In this fashion, the scientific [[learning]] landscape is free of [[dogma]], and instead is populated by [[reproducible]], [[evidence]]-based [[predictive]] insights about the operation of our [[universe]] -- that can readily be replaced as the scientific learning organization gains more-powerful, more-reproducible, more-predictive evidence-based insights.


The rigorous scientific examination of scientific learning organization tools is still in its infancy. It is reasonable to expect further refinements at this level of scientific understanding, as Western economies transition out of their former Industrial/Manufacturing traditions into the new [[Science]] & [[Technology]] [[Information Age]].





Revision as of 22:00, 14 March 2007

The concept of the learning organization is that the successful organization must — and does — continually adapt and learn in order to respond to changes in environment and to grow. This raises a range of scholarly and theoretical questions relating to what it means for an organization to learn, and practical questions around what organizations need to do in order to learn and adapt.

The idea of a learning organization suggests that there is some learning in organizations that takes place over and above the learning undertaken by different individuals as part of their work and experience in organizations. This has been contested by different authors, but has proven an interesting idea. Is it possible, for example, for certain aspects of learning to remain in an organization, even if the participants responsible for it leave? It has been proposed that certain organizational artifacts, such as stories, records, system of doing work, tools, recipes, et cetera, function in a way that detaches the learning from individuals and makes it a property of organizations themselves.

Peter Senge and the Learning Organization

In his book The Fifth Discipline: The Art and Practice of the Learning Organization, Peter Senge defined a learning organization as human beings cooperating in dynamical systems that are in a state of continuous adaptation and improvement. According to Senge:

Real learning gets to the heart of what it means to be human. Through learning we re-create ourselves. Through learning we become able to do something we never were able to do. Through learning we reperceive the world and our relationship to it. Through learning we extend our capacity to create, to be part of the generative process of life. There is within each of us a deep hunger for this type of learning.

The reality each of us sees and understands depend on what we believe is there. By learning the principles of the five disciplines, teams begin to understand how they can think and inquire that reality, so that they can collaborate in discussions and in working together create the results that matter (to them).

Often the practitioner has seen the work as a vital yet viable means of developing a cadre of high performance leaders able to mobilize peoples' commitment towards results and change in organizations with ease.

  • Taxonomy: A learning organization may create a specific enterprise taxonomy - a common and agreed upon understanding of terms, concepts, categories and keywords that apply within that organization.
  • Challenging assumptions: Once it has established what they are, learning organization must constantly challenge its processes, instructions, assumptions and even its basic structure. The true learning organization is redesigning itself constantly.


Scientific Learning Organizations

The tools of ‘knowing’ & ‘learning’ that are employed by professional scientific organizations are not the same approaches as those used by other disciplines for ‘knowing’ and ‘learning’.

Once simply an idle curiosity, this difference in how scientific organizations ‘know’ and ‘learn’ vis-à-vis how other professional disciplines ‘know’ and ‘learn’ has become a vital research interest in the Science & Technology Information Age of the 21st Century. As a result, new insights about those knowledge creation approaches that ‘work’ in scientific learning organizations, as compared to those that don’t, are rapidly emerging.

Many factors are likely driving the new field of scientific learning organization research, including a re-examination of science-based social infrastructure elements that were originally built upon older Industrial Revolution tools & approaches. Many of these science-based social-support programs (like the U.S. Medicare System) are becoming over-burdened with new demands for services and resources.

The single most-important factor that is driving the active investigation of the performance of scientific learning organizations is the recognition that many Western societies are increasingly depending upon this specific pattern of professional learning & knowledge-creation to drive their newly-emerging economies: As many Western societies lose their industrial & manufacturing business-bases, most are also rapidly transforming into Science-Based Societies.

It is important to recognize that because of the advent of the Internet and global scientific information sharing, all western scientific organizations (especially government-supported healthcare organizations) are scientific learning organizations. The central question for any specific scientific organization is whether it qualifies as a 'high-performing scientific learning organization'.

Scientists now recognize that the majority of organizational learning tools, when applied to the various disciplines of science (particularly in the United States), are subject to three very powerful constraints, giving rise to a specific set of scientific learning tools for scientific learning organizations.

The three central constraints to learning (creating new scientific knowledge) in scientific learning organizations are:

1. All grant-funded science, and particularly government-supported medicine, in most Western nations is conducted in a community of practice setting, which provides rigid restraints on the creation and use of scientific knowledge;

2. All scientific knowledge derives from (and also influences) scientific information, and all scientific information derives from scientific data; and

3. All scientific knowledge that is created and improved by the organization must reflect the use of the scientific method.

Since the publication of the landmark “Communities of Practice” research paper by William Snyder and Xavier de Souza Briggs in 2003, it has been recognized that all grant-funded and/or government-supported scientific endeavors in most Western nations, such as the U.S., are conducted within the context of a scientific community of practice (CoP) ( [1] ): Scientific CoPs steward the knowledge-assets of scientific organizations: They also steward the learning assets of such organizations. The quality of any organization’s scientific knowledge- and learning-assets can be measured scientifically. Thus, effective scientific learning organizations must be aware of the CoP constraint upon their operation, and they must learn to create new knowledge accordingly. The U.S. National Institutes of Health (NIH) has recently acknowledged the validity and the power of the scientific communities of practice approach to measuring the value of its processes for accumulating new scientific knowledge with the launching of the new NIH Office of Behavioral & Social Science Research intiative (see page 5 of the NIH "Healthier Lives Through Behavioral & Social Sciences Research" Report { [2] }

All scientific learning organizations depend upon scientific knowledge for their proper operation: After all, the Latin root word for ‘science’ means ‘having knowledge’. In addition, the pace of change in the flow of new scientific information and knowledge requires that all scientific learning organizations, particularly in the field of medicine, be capable of synthesizing new scientific knowledge ( = scientific learning). Scientific learning organizations are constrained by in the creation of new knowledge by the DIK scientific learning pathway ( [3] ). In their 2004 “Data, Information, Knowledge, and Wisdom” paper, Gene Bellinger, Durval Castro, and Anthony Mills outline the basic steps of the DIK learning pathway:

• In scientific CoPs, scientific knowledge constitutes ‘the ability to predict the pattern of responses’ and is derived from (and also influences) a specific cluster of scientific information.

• Scientific information functionally operates as ‘a new insight about relationships between data that places a demand on the attention of the scientific-observer’, and is derived from a specific grouping of scientific data.

• In turn, scientific data are simply the infinite facts of the universe itself, which serve as the basis for all scientific inquiry and discovery.

Thus, effective scientific learning organizations must be aware of the DIK learning pathway constraint upon their operation, and they must learn to manage their scientific knowledge creation processes accordingly.

Finally, all scientific learning organizations, by definition, must adhere to the scientific method in the process of creating and improving their scientific knowledge. As reviewed elsewhere in Wikipedia, the scientific method has many different interpretations, particularly with regard to those instances where a ‘scientific paradigm shift' occurs. At the same time, in its most basic and conservative form, the scientific method has a well-established core framework for decision-making & learning, as summarized by W. L. Jerome in a 1994 scientific research article entitled “The Scientific Method”, ( [4] ). In its most basic form, the scientific method is a structured thought & action process that leads to the creation of new scientific knowledge, and it contains the following basic steps:

Questions;

Hypothesis generation;

Predictions;

• Design of appropriately-controlled experiments;

• Proper collection of experimental results;

• Appropriate interpretation of evidence;

• Honest sharing of new knowledge and pertinent methodologies with others; and

• Checking for reproducibility of results and scientific conclusions by others.

Effective scientific learning organizations must be aware of the limitations and constraints on knowledge creation and knowledge development that are imposed by the scientific method, and they must learn to manage their organizational operations accordingly.


Modern scientific learning organizations and scientific learning societies must also address (by avoiding) four additional performance-impeding elements in the design of their scientific learning systems.

Scientific-Information Overload: Too much scientific-information demanding the attention of the members of the scientific community of practice. Scientific information overload leaves members feeling ‘dazed & confused’.

Scientific-Knowledge Overload: Too much scientific-knowledge to be actionable by the members of the scientific community-of-practice. Scientific knowledge overload tends to create an experience of 'guilt' in scientific learning organization members.

Scientific Discipline-Fragmentation: The inability of members of one scientific sub-discipline to learn with members of another scientific sub-discipline. Scientific discipline-fragmentation is also known as ‘the professional silo’ or ‘Tower of Babel’ syndrome.

Low Scientific Moral-Meaning: This syndrome refers to a state of uncertainty within a scientific community of practice, upon any given exchange of scientific knowledge, about whether this new knowledge will promote a new state where all CoP members will be valued and supported. This scientific moral-meaning uncertainty tends to be experienced as ‘fear’: As Dr. Robert Bellah (University of California, Berkeley) describes: “The awareness of interconnectedness, in the absence of moral-meaning, is terrifying.”

Fortunately, the proper use of scientific learning organization tools( that operate cleanly within the first three above-cited scientific learning organization constraints) is capable of also avoiding these four performance-impeding syndromes. By deliberately and consciously avoiding these challenges, high-performing scientific CoPs are able to position their members for the #1 priority of the organization: Scientific-learning (scientifically defined as ‘changing the meaning of life-experience, by the creation of new scientific knowledge, using the scientific method’).


Expressed in Venn Diagram visual terms, scientific learning organization tools are designed to operate in the space where

1. the scientific CoP constraint,

2. the DIK scientific learning pathway constraint, and

3. the scientific method constraint

intersect.

The beauty and the performance advantage of the scientific learning organization approach is that their proper use does not place the user(s) in conflict with any of the core tenets of the discipline of science itself.


It is worth noting that scientific learning organizations are not capable of creating any form of ' truth ', at least not in any traditional sense. In this fashion, the scientific learning landscape is free of dogma, and instead is populated by reproducible, evidence-based predictive insights about the operation of our universe -- that can readily be replaced as the scientific learning organization gains more-powerful, more-reproducible, more-predictive evidence-based insights.


The rigorous scientific examination of scientific learning organization tools is still in its infancy. It is reasonable to expect further refinements at this level of scientific understanding, as Western economies transition out of their former Industrial/Manufacturing traditions into the new Science & Technology Information Age.


See also

Notes

External links