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Deming Cycle is a good method for developing practical projects and research in order to get iteration and rigorous results. It is one relevant addition, a lower level tool for GoodReason.

Definition: Deming Cycle (Wiki)

Deming’s cycle has been a popular process development method for practical life and science for decades. Its cycles include: Plan, Do, Check, Act.  and  Adjust. 

Fig 1: Extending Deming Cycle into an embedded universality learning – principle

Fig 1 has adopted some ideas about cybernetics to extend learning. The flow there is not limited into information, but the flows also can move energy, material, money, service and management.

An assumed higher system (manager or controlled) is shown. Input goes into the Learning box and there are three types of output: output at the samel level than input, design output after the Planning box and system output after a possible implementation, which outputs to the higher system.

The system (yellow) is a so called cognitive agent, whose properties are needed in relations to the environment.

This web implementation shows the four main topics as menu items:

1:  Learning. This submenu presents ideas of the new paradigm, an atomistic and holistic way to understand ”anything”.

2:  Analyzing. This submenu shows some examples, demonstrations about how knowledge is created even about world wide large topics in order for everybody to catch the focus.

3:  Planning. This submenu helps in building installations, organizations and structures using rules of cybernetics.

4:  Meta vision. This submenu is a brave step forward: to understand ideal society and sustainable principles for the world.

To learn more, the principle of the method is next presented as GoodReason praxis.

Principles of On demand – learning as a demonstration

GoodReason recommends to use analogies for connecting different kinds of topics and systems. Below the principle of On demand learning is drawn using two nesting graphs with 8 sectors. The meaning of each sector is often important. The user can seek the best possible meanings for his/her own topics.

In Fig 2. information comes from left to the line 3 and after transformation (learning phase) it creates understanding and a synthesis (number 7). How it really happens, it is the focus of the systems thinker to study and explain in each context. It is one of the main ideas of GoodReason and Metayliopisto.

Fig 2: On demand learning.

From this figure there is only a small step to the contents of Wikipedia and other hypertext media to start to learn them.

Example about Learning Theories: Connectivism

Connectivism is a theory of learning in a digital age that emphasizes the role of social and cultural context in how and where learning occurs.

Connectivism has been selected to one of GoodReason’s values, because it is effecting everywhere, and it has much social influence in all sectors of human life everywhere due to social media.

The principles of connectivism are (Fig 3):

Fig 3: Connectivism.

A. Learning and knowledge rests in diversity of opinions.

B. Learning is a process of connecting specialized nodes or information sources.

C. Learning may reside in non-human appliances.

D. Learning is more critical than knowing.

E. Maintaining and nurturing connections is needed to facilitate continual learning.

F. Perceiving connections between fields, ideas and concepts is a core skill.

G. Currency (accurate, up-to-date knowledge) is the intent of learning activities.

H. Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality.

Wikipedia is one relevant source for understanding any topic from any discipline, although it is not scientific quality. We use it as a demonstration to easily create well understandable models.

Understanding robots and AI with personal skills

All the figures here can be thought to be skills or features of AI and robots, because the sectors have been selected so.

The graphs are suggesting for focusing, how to delegate tasks, to where to recruit personnel and in some cases, how to schedule jobs between start (1) and end (8).