I'm in the process of writing a number of papers about the TRAILER project. TRAILER is an attempt to relate thinking about self-certified competencies and informal learning with the organisational needs and reflexive processes of businesses. It's an ambitious project because there is so much conceptual and technological territory to cover. Unsurprisingly for a relatively small-scale Lifelong Learning project, some of the interventions have been a bit hit-and-miss. However, something important is, I think, being uncovered - not so much in the project's successes, but in its challenges.
A big problem within the tooling of the TRAILER system is the necessity for users to make selections from enormous lists of competencies. This isn't TRAILER's fault! It's really the fault of an EU commission obsession with taxonomies of what are pretty meaningless terms as a means of coordinating professional development. Unfortunately, I think a powerful group of academically ambitious semantic-web software engineers rather oversold the potential of their technologies as they insisted on the creation of job 'ontologies': would that there had been some decent philosophers inspecting things, and they would have pointed out that these so-called 'ontologies' were really 'epistemologies' - and bad ones at that!
Worse has been the fact that ineffective taxonomies attracted bureaucrats because they appeared to make highly complex educational domains manipulable by managers. Consequently, the 'competency' idea caught on - most recently Poland was proudly presenting its own competency frameworks, drawing heavily on models in other EU nations.
The problem with competency as it is conceived by the commission is very deep. Fundamentally the problem is about "aboutness". A competency statement is a statement 'about' a flow of experience: either the experience of performing a particular skill, or the experience of watching someone performing a skill. We see this every day, and we say informally, "what I'm seeing is really about...". However, how I decide what something is about is a mystery. How it relates to the flow of experiences is poorly understood. Yet this lack of understanding doesn't stop the competency taxonomists labelling experiences everywhere, saying what they are about, and then treating their statements of 'aboutness' as a kind of code for employability.
I believe the way to tackle this is to look more deeply at the nature of 'aboutness'. To say something is 'about' something is, in the final analysis, a decision to make a particular utterance. Something in the flow of experience has contributed to the conditions within which that decision can be made. This utterance is an expression of an expectation which is in some way maintained by the flow of experience, in the same way that a melody is maintained by its accompanying harmony and figuration. There are mechanisms (particularly in biology) that we might draw on to explain this. One of the principle mechanisms may be the way that the flow of experience acts as a 'catalyst' for the formation of particular expectations over time (in the way that certain enzymes catalyse cellular growth). I think the equivelent of enzymes in human communication are 'redundancies' - all the parts of a communication which are not directly relevant to the aboutness of a thing.
If we understand how we arrive at an understanding of aboutness, we don't need to create taxonomies. We can instead infer the aboutness of something analytically. Through processes of data mining and simple data requests from users ("say briefly what you think this is about in your own words") we can not only get a grasp of a somebody's competency, but also an indication of the way individuals see themselves, and the extent to which professional skills and personal values are integrated. All these are things that we intuitively 'read' when we meet someone, and with data mining it might be possible to access a rich enough dataset of information in order to at least have a much deeper dialogue with somebody.
What this requires to work is a corpus of information. I talked the other day about the 'personal corpus'. But what of the 'business corpus'? The Business Corpus is a collection of all the documents, minutes of meetings, strategies, tenders, legal documents, etc. that a business produces. All business continually ask themselves what they are about, how they relate to the world (their customers), what skills they require, what products to develop, etc. The answers to these questions lie in between an examination of what they have already done, and an examination of what's happening in the world and what's changed. On looking at the Business Corpus, and on being asked "what matters right now?", an analysis can be performed which examines the relation between what is already known and what might be possible. Throw into this particular profiles generated through individual 'personal corpuses' and sophisticated matching can show where things might become possible.
This is what TRAILER is really about. But so far TRAILER has attempted it with taxonomic competencies, not data mining. Exploring the alternatives is now a priority, because there are clearly problems with taxonomies. But more important, there are now technical opportunities to do the data mining, and open source tools to do it with, which were not there before. Furthermore, our understanding of how the 'aboutness' of something arises over time can be connected with this analytical effort can result in both individuals and businesses seeing what is meaningful to them without the burden of making choices that fit into a bureaucratic machine.
A big problem within the tooling of the TRAILER system is the necessity for users to make selections from enormous lists of competencies. This isn't TRAILER's fault! It's really the fault of an EU commission obsession with taxonomies of what are pretty meaningless terms as a means of coordinating professional development. Unfortunately, I think a powerful group of academically ambitious semantic-web software engineers rather oversold the potential of their technologies as they insisted on the creation of job 'ontologies': would that there had been some decent philosophers inspecting things, and they would have pointed out that these so-called 'ontologies' were really 'epistemologies' - and bad ones at that!
Worse has been the fact that ineffective taxonomies attracted bureaucrats because they appeared to make highly complex educational domains manipulable by managers. Consequently, the 'competency' idea caught on - most recently Poland was proudly presenting its own competency frameworks, drawing heavily on models in other EU nations.
The problem with competency as it is conceived by the commission is very deep. Fundamentally the problem is about "aboutness". A competency statement is a statement 'about' a flow of experience: either the experience of performing a particular skill, or the experience of watching someone performing a skill. We see this every day, and we say informally, "what I'm seeing is really about...". However, how I decide what something is about is a mystery. How it relates to the flow of experiences is poorly understood. Yet this lack of understanding doesn't stop the competency taxonomists labelling experiences everywhere, saying what they are about, and then treating their statements of 'aboutness' as a kind of code for employability.
I believe the way to tackle this is to look more deeply at the nature of 'aboutness'. To say something is 'about' something is, in the final analysis, a decision to make a particular utterance. Something in the flow of experience has contributed to the conditions within which that decision can be made. This utterance is an expression of an expectation which is in some way maintained by the flow of experience, in the same way that a melody is maintained by its accompanying harmony and figuration. There are mechanisms (particularly in biology) that we might draw on to explain this. One of the principle mechanisms may be the way that the flow of experience acts as a 'catalyst' for the formation of particular expectations over time (in the way that certain enzymes catalyse cellular growth). I think the equivelent of enzymes in human communication are 'redundancies' - all the parts of a communication which are not directly relevant to the aboutness of a thing.
If we understand how we arrive at an understanding of aboutness, we don't need to create taxonomies. We can instead infer the aboutness of something analytically. Through processes of data mining and simple data requests from users ("say briefly what you think this is about in your own words") we can not only get a grasp of a somebody's competency, but also an indication of the way individuals see themselves, and the extent to which professional skills and personal values are integrated. All these are things that we intuitively 'read' when we meet someone, and with data mining it might be possible to access a rich enough dataset of information in order to at least have a much deeper dialogue with somebody.
What this requires to work is a corpus of information. I talked the other day about the 'personal corpus'. But what of the 'business corpus'? The Business Corpus is a collection of all the documents, minutes of meetings, strategies, tenders, legal documents, etc. that a business produces. All business continually ask themselves what they are about, how they relate to the world (their customers), what skills they require, what products to develop, etc. The answers to these questions lie in between an examination of what they have already done, and an examination of what's happening in the world and what's changed. On looking at the Business Corpus, and on being asked "what matters right now?", an analysis can be performed which examines the relation between what is already known and what might be possible. Throw into this particular profiles generated through individual 'personal corpuses' and sophisticated matching can show where things might become possible.
This is what TRAILER is really about. But so far TRAILER has attempted it with taxonomic competencies, not data mining. Exploring the alternatives is now a priority, because there are clearly problems with taxonomies. But more important, there are now technical opportunities to do the data mining, and open source tools to do it with, which were not there before. Furthermore, our understanding of how the 'aboutness' of something arises over time can be connected with this analytical effort can result in both individuals and businesses seeing what is meaningful to them without the burden of making choices that fit into a bureaucratic machine.
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