Progression from Digital Novice to Digital Mastery

As I have previously pointed out; proficiency is the capability, skill, and knowledge that you might have for doing something. There are general levels of proficiency: literacy, fluency, mastery. 

Proficiency is a progression.

Pedagogy is the art, science, and practice of teaching. Teachers can help one navigate from novice to literacy to fluency and ultimately to mastery. The graphic below (from this web site) shows the progression this way:


Digital proficiency is the capability to understand the change between "realspace" and "cyberspace".  One key benefit of digital proficiency is that it helps you understand the true limitations of technology.

What one needs to understand can change as the tools that become available to the learner changes. Digital proficiency at this point in time is not about things like learning to code or being able to read the XBRL technical specification.

In my view, the first step to digital proficiency is digital literacy and the ability to communicate effectively with software engineers that are building software tools that will be used by business professionals.  This is a bit of a "chicken or the egg" type of problem.  Digital literacy is helpful in imagining what you might want to ask for but working software eliminates the need to imagine by making things more tangible.  This "dance" helps to get the appropriate software constructed.

How all this will unfold is hard to predict.  But what is certain is that change is inevitable.  "Digital" makes a whole not of sense.

Additional Information:

Comments

Post a Comment

Popular posts from this blog

Relational Knowledge Graph System (RKGS)

Image
Relational Knowledge Graph System (RKGS) is an interesting idea that combines the relational paradigm and the knowledge graph paradigm.  This documentation, Why RKGS , explains the idea. This gets even more interesting with the notion of "relational AI".  RelationalAI is described as follows by the company of the same name, Relational.ai : “RelationalAI is a cloud-based relational knowledge graph management system, with state of the art probabilistic processing and declarative reasoning at scale to make developing Data Applications a superpower for your business.” This notion of knowledge graphs represented in relational databases fits into my belief that knowledge graphs have two aspects: the expression SYNTAX and the logic of what is expressed or SEMANTICS. While the LOGIC of a knowledge graph is always the same regardless of technical syntax used to express that logic; there are many, many different technical syntaxes that can be used to represent a knowledge graph. There
Read more

Graph Hairball

Image
Knowledge graph system logic, the "things" and "relations between things" that  graph theory calls "vertices" (a.k.a. nodes, points, entities, things) and "edges" (a.k.a.  links, lines, relations, associations), looks like a big graph hairball as some people call it an example of which you can see here: Why?  This common view of a graph is because there has to be some "general view" of the information provided by the graph.  This is just like a general view of the information within a relational database is a table ; a set of ROWS and COLUMNS for exactly one table at a time. So what is interesting is that with a graph database the default view is everything in the graph of knowledge.  Whereas the default view of everything in a relational database is one table at a time. Further, it does not really matter whether the information that populates your knowledge graph comes from, say, CSV files, Excel, JSON, XBRL, RDF, PROLOG or whateve
Read more

PLATINUM Business Use Cases, Test Cases, Conformance Suite

Image
A brick wall is made of exactly two things: bricks, mortar. But a brick wall created by a master craftsman, or mason, and a brick wall created by a “weekend warrior” with no knowledge of masonry will be very different. Master craftsmen are created and that process takes time and effort. This blog post is a first prototype that brings several things together into one useful resource for business professionals.  It pulls together the human readable information of the Showcase of Reports   and the machine readable information of the Conformance Suite of XBRL-based Financial Reports Prepared using the Seattle Method .  Then, I want to incorporate the information found in these PLATINUM XBRL-based Financial Report Examples . The three resources can be useful and used independently; but they are even more useful when used together.  Business professionals really could not care a less about the technical details of getting some result that they want.  But technical professionals need to under
Read more