Meta-cognitive projection of analytics and personalized learning

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By Juan Domingo Farnós, independent researcher in education technologies, elearning and knowledge management

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We are at a moment when, first of all, we need to be clear on how our mind works – and therefore the synergies that are produced at a neuronal level – and, second of all, its correspondence with our relationships and, consequently, our network learning.

We are seeing that this is vital, not only to take into account how to reach our personalized excellence, but also to find the help we need to achieve it, at the level of external memories and personal feedback.

We need software that is scalable but also adaptable to every situation, and prepared – open – so that it can be of use to us at any time, not simply because of its standard quality (which it must fulfil) but because of the possibility of modifying itself and continuing to be of quality.

To establish personalized excellence, we need, on the one hand, to use the most «cerebral» part of every person: ie the neuronal synergies that permit both the acquisition of knowledge and its subsequent learning due to the contribution of added value to the social community (experiences). And of course, on the other hand, we will use the other part of our brain that makes us learn «intuitively», which makes everyone unique and different.

The strategy to be used with personal knowledge mastery (PKM) is to create a mind map of the information that we manage so that it becomes our personalized and personal knowledge. Could our computer hard drives act as a substitute? A place to create or a representation? Obviously, they can act as a support.

« For personalized excellence we need both the most “cerebral” and the most “intuitive” part of every person »

This first step in the strategy with PKM calls for determining and using the application of a personal classification system, indexing and presentation principles. Consequently, with the use of our PKM, we will achieve our “best sources”, which will improve our results in knowledge acquisition – more relevant results with less static – increasing the value of the information.

The filtering of information, data and metadata, will be submitted to processes of analysis and critique, entering another stage that will lead them directly to the filtering per se, at all times supported by feedback that will give results based on needs, possibilities, etc., that will mark out the future of the learning we will undertake.

We will do all of this through algorithms, which will give us not only a personalized route but will produce a “personalized” effect of learning and, consequently, will take us to the “sought-after” “personalized excellence”.

This work of diversity and personalization will enable the achievement not only of a greater quantity but also a better quality of the knowledge acquired and of the learning to be applied.

With all this, we establish the following points of reference for this development of the whole knowledge acquisition-learning process:

1. From tacit to tacit through socialization: Socialization is the process of sharing tacit knowledge, not through language but through observation, imitation and practice. The socialization mode begins with the construction of a “place” or “context” of social interaction (social learning).

2. From tacit to explicit through externalization: Externalization is a process of articulating tacit knowledge in explicit concepts. It is generally produced on the basis of metaphors, analogies, concepts, hypotheses and models.

3. From explicit to explicit through combination: Combination is the process of systematizing concepts in a knowledge system, and it integrates different bodies of explicit knowledge. Once the knowledge has been captured, it becomes explicit information and can be stored and visited. During the combination process, the reconfiguration of existing knowledge can – through classification, addition, reorganization and combination – lead to new knowledge.

4. From explicit to tacit through internalization: Internalization is the process of incorporating explicit knowledge in tacit knowledge.

The acquisition of PKM skills is a complex and continuous process that can be fostered by the right conditions and the internalization of adequate and effective behavioural practices and values.

With this work methodology, we establish the planning of the PKM training for each of the learners, who will attain continuous training from experts, eg pre-degree students. We believe that the development of training aimed at activation processes is possible, such that digital and social literacy skills and competency can be gradually enriched, internalized and transformed into personalized ones by non-expert subjects.

« Diversity and personalization will enable the achievement not only of a greater quantity but also a better quality of the knowledge acquired »

Therefore, with this we are training in the effective practices of expert learners in relation to Web 2.0 tools and environments. On the basis of a qualitative study, our aim will always be directed at demarcating a 2.0 lifelong student skills profile with a view to identifying a planning tools support – quality training that we will conduct developing PKM skills – in non-experts. This PKM model is focused on basic competencies and skills of a higher order (meta-skills) and identifies the conditions that allow this and the competencies that foster effective PKM management so that knowledge and learning can always be connected in a network.

However, in social learning we constantly find a duality: knowledge has to compete with a sea of data that must be analysed to be subsequently made known as open and implemented in learning and work. Due to all this, the learning process is like a journey that takes us from the neuronal synapse, which helps us manage information and acquire knowledge, to the purging of this knowledge in our social relationships and its subsequent use in data analysis, which we can now do with greater productivity and quality through big data.

Nuevos paradigmas, nuevos algoritmos de aprendizaje personalizados! (Educación disruptiva).

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Tecnología educativa y roles de profesores y alumnos en un mundo 2.0

Tags: learning, personalized excellence, software, personal knowledge mastery, knowledge, information, social learning, big data.

About/Bio:

Juan Domingo Farnós

Independent researcher in education technologies, e learning and knowledge management (Spain).

Juan Domingo Farnós has a PhD in e-Learning and is a researcher, communicator and disseminator of online learning, education technologies and mobile learning, as well as ICT, Web 2.0 and artificial intelligence. In the field of education, he is a staunch defender of open, inclusive and ubiquitous learning. For over a decade, Farnós has been a tutor and online teacher on a number of postgraduate and master’s programmes at various Latin American universities, especially in the sphere of the introduction of inclusive education and the Web 2.0 in learning processes in higher education. He is also an affiliate member of the Network of Excellence in Internet Science.

juandomingofarnos@gmail.com

whatsApp: +34 678739410

Farnós’s blog: http://juandomingdisruptive.blogspot.com.es/

Farnós’s LinkedIn page: https://www.linkedin.com/pub/juan-farnos/34/294/a88

Farnós’s Twitter account: https://twitter.com/juandoming