Self-efficacy and Cognitive Load & Prior Knowledge by Keith Brennan


Both terms are connected to the meaning of self-efficacy in Albert Bandura’s work. Self-efficacy is our belief that a task is achievable by us. High self-efficacy students work harder and are less likely discouraged. Low self-efficacy work less and for shorter periods of time.

  • Cognitive load: the amount of information we can take in, process and retain. It’s a critical mechanism to explain why novice learners may have difficulty in unstructured environments.
  • Prior Knowledge: the idea that what we already know has a powerful determining effect on what we can learn, and how quickly.

Educators encourage or undermine SE in four ways:

  • physical and psychological responses: educators need reassuring students, especially novices
  • encouragement and verbal persuasion: educators need to scaffold the learning experience for students
  • vicarious experience: our capability increases when we see people we consider similar to ourselves achieve a task.
  • mastery experiences: these experiences are characterised by corrective feedback, achievability, and cognitive load that represents both a challenge, but also leaves enough space for complex learning.

The author advocates for guided instruction because modes of learning such as discovery learning/ problem-based learning/ inquiry learning/ experiential learning/ constructivism &/ connectivism despite their popularity, do not support novices enough. The focus is on novices as they are the ones who might be discouraged and withdraw in case their learning experiences requires more than they can give.

Long-term memory is the central dominant structure of human cognition. Everything we see, hear and think about is critically dependent on and influenced by our long-term memory (…) we are skillful in an area because our long-term memory contains huge amounts of information concerning the area (…) the aim of the instruction is alter long-term memory (…) any instruction recommendation that does not or cannot specify what has been changed in long-term memory, or that does not increase the efficiency with which relevant information is stored in or retrieved from long-term memory, is likely to be ineffective. (Kirschner, Sweller, Clark)



Brennan, K., 2013. In Connectivism, no one can hear you scream: a guide to understanding the mood novice, in Digital Pedagogy Lab (24th July 2013), full article available here

Kirschner, P.A., Sweller, J., Clark R.E., 2006. Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential and inquiry-based teaching, in Educational Psychologist, 4l(2), pp.75-86, Lawrence Erlbaum Associates, Inc, full paper available here

Image available here

Zone of Proximal Development


The zone of proximal development, often abbreviated as ZPD, is the difference between what a learner can do without help and what he or she can do with help. It is a concept introduced, yet not fully developed, by Soviet psychologist Lev Vygotsky (1896–1934) during the last ten years of his life (…) Vygotsky stated that we can’t just look at what students are capable of doing on their own; we have to look at what they are capable of doing in a social setting. In many cases students are able to complete a task within a group before they are able to complete it on their own.

Image available here/ Source Wikipedia



Competence in design praxis appears not to be measured by the quantity of knowledge gained, but by knowing where to find it, which specific kind of knowledge to apply in a particular situation, and how to use it when needed. It is the development of thinking skills that is critical in design education (…) there is more in knowing how to design than just knowing about designs. Meta-knowledge is the knowledge of how to organize what one knows (…) knowledge acquisition is based upon the organization and development of conceptual structures (…) in order to model design thinking processes, the conceptual mapping of design ideas can be constructed into larger structures, the think-maps.


Think maps

  • they are founded on constructivism (active learner/learning by doing) and mapping (organizing and representing knowledge)
  • they propose that by constructing a map that reflects one’s thinking in a domain, we make knowledge learned explicit. they attempt to convey knowledge directly.
  • they are a cognitive teaching framework based upon the student’s ability to organize and formulate knowledge structures in design thinking.

A concept map is a representation of knowledge structures through a graphlike
structure of nodes and links (…) a map is achieved when a meaningful structure has been created (…) an important distinction is frequently made between in-domain linkages in the map and cross-domain linkages (…) Think-Maps is a form of conceptual mapping for design


Rivka Oxman, 2004. Think-maps: teaching design thinking in design education. In Design Studies 25, pp. 63–91, doi:10.1016/S0142-694X(03)00033-4

Images available here

Knowledge claims


  • Claims of fact: those that can be verified or falsified, proven true or false
  • Claims of value: value judgments
  • Claims of policy: what should be done instead of what is being done
  • Claims of concept: those that are about the meaning of things
  • Claims of interpretation: how are some data understood

The authors claim that natural and social science publications tend to make singular knowledge claims of similar kinds whereas design publications often contain multiple knowledge claims of different kinds.

Multiple knowledge claims of different kinds within individual journal publications might be the consequence of a young, multidisciplinary field. Another explanation might be that scholars publishing in Design Studies tend to embrace the values of design and science, which may account for those publications making claims of fact and claims of policy. Finally, a third explanation might be that scholars publishing in Design Studies are writing for multiple audiences with diverse needs. (bold is mine)



Jordan Beck, Erik Stolterman, 2016. Examining the Types of Knowledge Claims Made in Design Research. In she ji, Tongji University and Tongji University Press.

Image available here



ADAPT-r is an ITN network that aims to develop new knowledge and understanding of Creative Practice Research (CPR) thus design thinking, public behavior, as well as the emergence of new methods oriented towards the explication of tacit knowledge. It comprises of 33 early stage researchers all creative practitioners and PhD candidates, 7 experienced researchers and 7 institutional partners. Research was conducted in the form of 9 paired interviews.

WORK PACKAGE 01_Primary Research: it follows the logic of the referential focuses of creative practice research training;

  • case studies: these are the venturous practices of the creative practitioners
  • community of practice: the communities that contextualize these case studies
  • transformative triggers: what shifts and transforms their creative practice and how it is related to social contexts; triggers uncover the challenges and the challengers of creativity the practitioners are not aware of; the revisiting, sorting and mapping past work triggers changing understandings; they are the markers of knowledge creation and recognition of development and change in the creative research practice; when things fall into place; Embracing Uncertainty: The space of not knowing; Other ways of knowing: intuition, hunch, feeling and bodily knowledge; they are not immediate insights but rather a means of opening up
  • public behaviors: it means that the practitioner positions himself/herself in his/her communities of practice/relevance; they point to navigating contexts; it is an interaction ritual
  • explicating tacit knowledge,
  • explication of methods

Methodology Analysis: Wording/Metaphoring/Anecdoting/ Diagramming*/ Choosing/ Playing/ Manifesting/ Structuring

Interesting findings on knowledge creation and creativity. 

(…) by thinking about knowledge as socially constructed, something that operates in networks, in relationships between actors, it becomes clear that there is no singular thing that amounts to knowing, instead, there are multiple knowledges. Knowledge represents multiple considerations about creativity. creativity can be a new idea, imagination and/or innovation; it too is multiple. As such it can be thought of as a responsive and relational, not classic and timeless.

There are three types of knowledge. There is input knowledge: the knowing before action. There is output knowledge: the knowing after action. There is relational knowledge: the knowing in action (communities of practice) developed relationally through interaction and collaboration

In order for innovation to be innovative it must be recognized as such by the creative practice researcher’s community of practice (…) the outputs of creative practice go beyond any objects of practice(…) doing creative practice is not the same as doing creative practice research; the practice needs to be framed differently



J. Verbeke, K. Heron, T. Zupancic, Relational Knowledge and Creative Practice, 2017, A publication by ADAPT-r (eds Tadeja Zupancic, Claus Peder Pedersen), ISBN 9789082510850, available here

ADAPT-r official webpage

*Diagrams as a research tool, Annotated, Different Aesthetics, Handmade, Collage, Landscape-like, as tools to discover or represent, as texts, to measure and visualize the projects, spider diagrams, time diagrams, architectonic diagrams, research space diagrams

From design to cybernetics


Scientific Research is a restricted form of design. Design is thus not necessarily scientific.

Design: is central to the act of design is circularity (…) it is a conversation often involving a paper and a pencil with an other; ourselves or someone else (…) a distinguished element of design is novelty (…) scientific research is a design activity (..) we design our experiences and objects by finding commonalities (simplification) we design how we assemble them into patterns (…) looking at these patterns we make further patterns, thus in doing science, we learn (…) design is the object of study and as a means we carry out this study (…) scientific  research should be judged by design criteria, not the other way around (…) rigorous, honesty, clarification, testing and the relative strength of argument over assertion are essential qualities of design

The role of the observer as participant: making knowledge, abstracting it to theory, theorising about theory, constructing the way we obtain this knowledge, all is done by the actor (…) at every step it is the actor designing (…) the designer is central to science

The nature of these circular systems are examined in cybernetics. According to Norbert Wiener,  cybernetics is the scientific study of control and communication in the animal and the machine, whereas currently it is used as in ‘control of any system using technology’. In Glanville’s terms:

cybernetics has elucidated conversation, creativity and the invention of the new; multiple points and their implications for their objects of attention; self-generation and ‘the emergence’ of stability; post-rationalization; representation and experience; constructivism; and distinction drawing and the theory of boundaries



Ranulph Glanville, Researching Design and Designing Research. In Design Issues Vol. 15, No. 2, Design Research (Summer, 1999), pp. 80-91, available here

Image available here

The circular relationship of experiment and theory


  • Theory from experiment: it involves pattern finding (…) it is the making of a concept from many distinct perceptions (…) it formalises the significance and necessity of pattern (…) theories are patterns with widespread credence and accepted as accounting for a part of our experience (…)  we simplify to make our continuum of our experience de-finite (…) if we did not simplify we wouldn’t be able to recognise nor generalise (..) this allows us to make predictions as a means of extending the range of our observations
  • Theory from theory: it is the examination of concepts to clarify these concepts further (…) science depends not only on theory based on collecting and organising of empirical evidence but also on theory based on the consequences of that evidence (…) theory on theory is us acting self-referentially by using the devices of simplification and pattern finding (…) our understandings help us develop our understandings but also restrict them (…) when we find contradictions we modify or reject this understanding; this cyclical process is a design  process (…) the continuous modification and the inclusion of more and more in a coherent whole (…) one form of theory in theory is criticism



Ranulph Glanville, Researching Design and Designing Research. In Design Issues Vol. 15, No. 2, Design Research (Summer, 1999), pp. 80-91

Image available here

Bandura’s Social Learning Theory (Part I)


In the social learning system new patterns of behavior can be acquired through direct experience or by observing the behavior of others.

Modelling phenomena are governed by four interrelated sub-processes:

  • attentional processes: a person should recognize the essential features of one’s behavior (…) association preferences play a major role in determining observational experiences (…) within groups some members are to command greater attention that others
  • retension processes: a person is influenced by observation if he/she has a memory of the model he/she is observing (…) long-term retention of activities also play a major role (…) there are two representational systems on OL -an imaginal and a verbal one. During exposure modelling stimuli produce relatively enduring retrievable images of modelled sequences of behavior (…) verbal coding of the visual information accounts for the notable speed of OL and long term retention (…) observers who code modeled activities into words, images etc learn and retain the behavior better than those who simply observe (…) rehearsal serves also as an aid (…) people who mentally rehearse or actually perform modeled patterns are less likely to forget them.
  • motoric reproduction processes: where symbolic representations guide overt actions (…) to achieve behavioral reproduction a learner must put together a given set of responses according t the modeled patterns (…) the amount of OL depends on whether he/she has acquired the component skills (sub skills also exist) (…) performers cannot see the responses they are making (swimming) they depend on onlookers (…) it is exceedingly difficult to guide actions that are not easily observed.
  • reinforcement and motivational processes: actions depend on positive incentives which affect the level of OL by controlling what people attend to.

Provision of models will not automatically create similar patterns of behavior to others.



Albert Bandura, 1971, Social Learning Theory, New York: General Learning Press

Image available here

Dynamic Theory of Organizational Knowledge Creation by Ikujiro Nonaka (Part II)


First and foremost, knowledge creation is primarily dependent on the individual. Its quality depends on the variety of the individual’s experience and the knowledge of experience; thus ‘the embodiment (body and mind brought together) of knowledge through a deep personal commitment into bodily experience.

To bring personal knowledge into a social context within which it can be amplified, it is necessary to have a “field” that provides a place in which individual perspectives are articulated, and conflicts are resolved in the formation of higher-level concepts.

The self-organizing team triggers organizational knowledge creation through two processes:

  • it facilitates the building of trust; this occurs through sharing the individual original experience
  • the shared implicit perspective is conceptualized through continuous dialogues; dialogue in the form of face-to-face communication between persons is a process in which one builds concepts in cooperation with others and test hypotheses; interaction rhythms are both of of simultaneity and sequence

The team’s findings become crystallized through being double checked with other departments; justification comes nest as a process of final convergence; finally, the concept crystallized and justified is integrated into the org knowledge base with the aim to reorganize it.

the three enabling conditions for individual commitment:

  • creative chaos: perceived in its interaction with cosmos in a circular process and then becomes a cosmos; creative chaos is generated in crisis or intentionally by proposing challenging goals; chaos creates tension; tension is followed by reflection;
  • redundancy of information: conscious overlapping of info; it provides a vehicle for problem generation; helps individuals to recognize their location in the org which in turn increases their sense of control and direction;
  • requisite variety: the constructing of information process channels
    that match the information load imposed by the environment; an organization can maximize efficiency by creating within itself the same degree of diversity as the diversity it must process.



Nonaka, I., 1994, A Dynamic Theory of Organizational Knowledge Creation, Organization Science, Vol. 5, No. 1. (Feb., 1994), pp. 14-37.

Images available here 




Oh, I even love the word itself, but what are they, really? Well, it is a type of artificial neuron that takes several binary inputs and produces a single binary output.

What one needs to know are the binary inputs and their relative weight in the decision-making process (…) by varying the weights and the threshold, we can get different models of decision-making (…) a perceptron can weigh up different kinds of evidence in order to make decisions (…) another way perceptrons can be used is to compute the elementary logical functions we usually think of as underlying computation, functions such as AND, OR, and NAND.



Michael Nielsen, Neural Networks and Deep Learning, Chapter 01, full book available here



Connectomics uses advanced brain imaging techniques to identify and map the intricate web of white matter (communication lines) that link gray matter (neural brain volume). Mapping such networks occurs at the level of synaptic connections. This research began in the 70’s but has recently gained interest thanks to technical and computational advances that automate the collection of electron-microscopy data and offer the possibility of mapping even large mammalian brains. “Connectome” was coined in analogy with the “genome”—the entirety of an organism’s hereditary information—studied by biologists. To imagine how the story of the connectome will unfold over the next few decades, it’s helpful to recall the history of the genome. Connectomics is more challenging than genomics; the structure of the brain is extraordinarily complex. With an electron microscope, the branches of neurons can be seen clearly, even when they are tightly packed together in the brain.

People with high creative capacity have more connections between their left and their right hemispheres of their cerebral cortex.



  • Highly Creative People Have Well-Connected Brain Hemispheres, full article and image available here
  • The big data challenges of connectomics, available here
  • Connectomics: Tracing the Wires of the Brains, available here
  • video