The TPCK Model of Technological Education: Explaining Everything, Achieving Little


Digital media are becoming more common in classrooms around the world. The underlying pedagogy and design of curricula determine the benefits to students. Picture credit: Northeastern University


The TPCK (also known as TPACK) Model of Technological Pedagogical Content Knowledge, originally proposed by Misrah and Koehler (Koehler & Mishra, 2005, 2008, Misrah & Koehler, 2006), has taken the academic world by storm by proposing a pragmatic and systematic theoretical grounding to assist teachers integrating content knowledge, pedagogy and technology.

The model was developed by the authors during a five-year cooperation with American K-12 teachers and the faculty of Michigan State University. Its theoretical foundation is based on Shulman’s concept of pedagogical content knowledge, in short PCK (Shulman, 1986, 1987). At the heart of PCK stands the intuitive argument that in order for teachers being able to render content knowledge (CK) accessible to their students, it is a prerequisite for them to transform content knowledge in a pedagogically sensible manner (P), integrating both expert content and pedagogical knowledge. To their credit, Misrah and Koehler pointed out that professional organizations such as the National Science Teachers Association (NSTA, 1999) and National Council for the Accreditation of Teacher Education (NCATE, 2001) acknowledged the value of PCK for teacher preparation and teacher professional development.

Description of the TPCK Model

The authors gradually extended Shulman’s model by the component of technology (T), translating it into what is known today as the TPCK (or TPACK) model. How does this model work?


Graphic: A visualisation of TPACK

Using Shulman’s metaphor of three overlapping circular domains, the model concludes a total of seven key areas of knowledge. Beyond the technological, pedagogical- and content knowledge (the body of expert knowledge about a subject matter), four new areas come into play:

Technology Knowledge (TK) is defined by the authors as the teacher’s ability to use and apply digital technology in the classroom.

Technological Content Knowledge (TCK) relates to how technology shapes and influences the representation of content. Recent examples would be, e.g., the examination of phenomena by statistics, predictive analytics or computer simulations, opening new ways of exploring the world that was not available prior to the advent of digital technology.

Technological Pedagogical Knowledge (TPK) is defined by Misrah and Koehler as the pedagogical knowledge about the educational benefit of digital tools. The authors cite as examples digital class record systems, online grading, discussion boards and chat rooms.

Technological Pedagogical Content Knowledge (TPCK), finally, as the cross-section of all areas ”… is the basis of good teaching with technology and requires an understanding of the representation of concepts using technologies; pedagogical techniques that use technologies in constructive ways to teach content; knowledge of what makes concepts difficult or easy to learn and how technology can help redress some of the problems that students face; knowledge of students’ prior knowledge and theories of epistemology; and knowledge of how technologies can be used to build on existing knowledge and to develop new epistemologies or strengthen old ones.” (2006, p. 1029.)

A Critical Reading of the Original Script

The original script contains two segments. The first describes the TPACK model, as outlined above, while the second segment was named ‘APPLYING THE TPCK FRAMEWORK TO PEDAGOGY’. This section advocates what is typically described in the literature as design thinking (Brown & Katz, 2009; Lietka et al., 2017; Plattner et al., 2016; Rowe, 1998). Mishra and Koehler define their approach explicitly as ‘learning technology by design’ (p. 1034).

In this application part, the authors forward some valid points that are typically conceptualized in constructivist pedagogy. These arguments consist of notions such as

  1. Technology changes fast, which is why teachers need to be able to update their skills, classroom content and mode of delivery continuously. This argument also entails (contradicting TPACK) that learners cannot primarily rely on content that is easily outdated, advocating the development of process skills to make appropriate content available and to relate facts with changing ideas and complex concepts.
  2. Learning happens in situated contexts, which is why digital technology needs to support the age of learners and their developmental needs, the type of school or a variety of individual learning styles. In design thinking, this notion is complemented by taking a user- or human-centred approach. This entails that pedagogy is not arbitrary as well.
  3. Competencies need to be developed: A mere wish-list of competencies does not tell teachers on how to achieve them. TPACK promises a structured approach to guide implementation.

On face value, the TPACK model appears intuitive in stating technology, content and pedagogy as the main drivers of education. Similarities to theories such as Maslow’s Hierarchy of Needs or Bloom’s Taxonomy arise in so far, as an additive modular framework is proposed to explain and guide the complex dynamics of learning processes. TPACK seems to intuitively answer to all potential combinations of its components by starting with simplified assumptions.

A closer view, however, reveals that TPACK rests on a number of problematic assumptions:

  • Isolated domains: The first assumption is that technology, pedagogical- and content knowledge exists in isolation and can be understood by relating them via distinct overlapping circles as a representation of empirical reality. The second reading of this first assumption is that technological, content- and pedagogical knowledge exists as an a priori construct, each type of knowledge separated from the learning processes of involved actors. Shulman’s original categorical distinction between pedagogical and content knowledge was not further questioned by Misrah and Koehler. Citing McEvan & Bull (1991) and Segall (2004), Archambault and Barnett (2010) pointed out that ‘content, in the form of scholarship, cannot exist without pedagogy, and (…) explanations of concepts are inherently pedagogical in nature.’ (p. 1657). To this extent, Shulman’s framework appears to unnecessarily complicate the reciprocal relationship between content knowledge construction and the corresponding metacognitive reflection (pedagogical knowledge) that accommodates and frames it. Adding technology to the equation does not solve the initial lack of construct validity.
  • The dominance of content knowledge: The second assumption is that content knowledge (CK) represents one of the main components of digital- or media-education and should be regarded as one of the main educational concerns. It is not elaborated and justified why and how that is. Modern pedagogy is concerned about the acquisition of competencies, personal resources and process skills, but not content per se. Content is framed by overarching concepts and therefore cannot be separated from discoursive epistemological access.
  • A Model without actors and goals in mind: The third assumption is that the placing of abstracted thematic blocks (T, P and CK) is the most appropriate manner to plan learning and teaching activities with and about digital media. By excluding the actors of learning processes from the model (teachers, facilitators, students or the school administration), TPACK is not developed as a student-centred framework, which should be a grave concern for any educator.

The Design Thinking Conundrum

The TPACK application section focusses on design thinking which is, by definition and its human (learner)-centered approach, constructivist in nature. Typical issues of design thinking do not deal with content dissemination, but problem-solving, the development of innovative and novel solutions to challenges, the creation of new knowledge and ideas. Design thinking is about facilitating testable hypotheses as well as developing and improving ways of communication and group collaboration. There appears to be an internal contradiction and gap in the approach suggested by Misrah and Koehler; this is to build on a teacher-centered model based on content dissemination on one hand and to promote design thinking, which is based on active self-directed learning, on the other. There is neither a clear explanation given nor a discussion facilitated by this significantly different and incompatible choice of philosophies. The elephant standing in the room is the role of constructivist pedagogy. Since the TPACK model had been originally developed in collaboration with K-12 teachers, it is likely that teacher-centred pedagogy was assumed as the default model whereby design thinking was added on as a technological-compatible, convenient afterthought.

In a blog post, Punya Misrah answered when asked about Problem-based Learning (PBL) as follows: “There is a value to small group activities as there is to a lecture. Clearly if we are emphasizing higher order thinking skills – we need to move away from simple rote-learning tasks. It is just that TPACK per se does not lean one way or the other. It does not speak to the broader goals of education. Some of my more recent work has focussed on these broader goals – and in that there are many areas (if not all) that we will be in agreement. Finally, TPACK does not privilege content, technology or pedagogy. In fact we have argued (quite clearly) that there are situations where one or the other is the driver.”

Misrah states unequivocally that TPACK is not a goal-oriented model. Educators may find an issue with the argument of taking a neutral stand on pedagogy. If we seek to educate strong self-directed, lifelong learners that build in intrinsic motivation in order to thrive in a digitized and globalized society 4.0, then a merely instructional or a behavioristic approach is not an option. Given that the goal of education is the empowerment of learners of all ages, TPACK cannot have it both ways.

Mishra is also wrong assuming an arbitrary relationship between pedagogy and technology. Empirical research has demonstrated that teacher-centred instructors use technology in significantly different ways as compared to instructors willing to change form and content of curricula via digital media or colleagues who have embraced constructivist forms of pedagogy (Schaumburg, 2003). His mention of online discussions as an example of technology driving pedagogy is not correct insofar e.g., teachers advocating rote-learning would simply not bother using online chats to disrupt their practice. It is the pedagogical attitudes of teachers that determine the use of technology in the classroom, not vice versa. Technology is not neutral in this regard since technology either supports or distracts from facilitating learning processes and achieving learning outcomes. In an arbitrary framework that facilitates any system, there can be no definite criteria for the usefulness or quality of digital media.

Conclusion: TPACK’s Lack of Empirical Support and Scientific Usefulness

While some academics find in TPACK a universal model for curricula design, teachers in the field may find it cumbersome, misleading and confusing to sort out the finer details of TK, PK, CK, TPK, PCK, TCK and TPACK in order to progress with the design of learning units. In their empirical study comprising 596 online teachers across the United States, Archambault and Barnett (2010) could not verify pedagogy, content and technology as three separate domains. The only domain that distinguished itself from the others was technology.

As expected, teachers struggled with making clear inferences to the overlapping fields. The authors specified the following example: “Three online teachers were challenged with separating out specific issues of content and pedagogy. For example, Item d – “My ability to decide on the scope of concepts taught within my class” was interpreted by two teachers as belonging to the domain of pedagogical content rather than content alone. The same misinterpretation happened with Item b – “My ability to create materials that map to specific district/ state standards.” The participants saw this item as a part of pedagogy content (Archambault & Crippen, 2009). These examples, coupled with the results from the factor analysis, support the notion that TPACK creates additional boundaries along and already ambiguous lines drawn between pedagogy and content knowledge.(p. 1659)

TPACK, to state the obvious, is not a theory that can be empirically verified. There are no dependent or independent variables defined (since all components are regarded as equal with no clear causal or conditional relationships implied), there are no null-hypotheses to test and there are no evidence-based outcomes to predict. TPACK failed in initial empirical research distinguishing its seven mutually separated domains. Most worryingly, however, the model offers neither a goal-directed framework that is concerned with the empowerment of learners in the use of digital technology, nor is it concerned about the effects of digital socialization trajectories on society.

It still needs to be demonstrated that the positive effects attributed to TPACK are inherent effects of the model and not based on the critical reflections that are bound to come up when educators discuss the integration of digital media for the classroom.



Archambault, L.H. & Barnett J.H. (2010). Revisiting pedagogical content knowledge: Exploring the TPACK framework. Computers & Education, 55 (2010) 1656–1662

Brown, T., & Katz, B. (2009). Change by design: How design thinking can transform organizations and inspire innovation. New York, NY: HarperCollins Publishers.

Koehler, M., & Mishra, P. (2005). What happens when teachers design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2), 131–152.

Koehler, M., & Mishra, P. (2008). Introducing TPCK. In AACTE Committee on Innovation and Technology. (Ed.), Handbook of technological pedagogical content knowledge (TPCK). New York: Routledge.

Liedtka, J., Salzman, R., & Azer, D. (2017). Design thinking for the greater good. New York: Columbia University Press.

McEwan, H., & Bull, B. (1991). The pedagogic nature of subject matter knowledge. American Educational Research Journal, 28(2), 316–334.

Mishra, P., & Koehler, M. (2006). Technological pedagogical content knowledge: a framework for integrating technology in teacher knowledge. Teachers College Record, 108(6), 1017–1054.

National Council for Accreditation of Teacher Education. (2001). Professional standards for the accreditation of schools, colleges, and departments of education ([Electronic version]. Washington, DC: Author. Retrieved June 27, 2004, from

National Science Teachers Association. (1999). NSTA standards for science teacher preparation [Electronic version]. Arlington, VA: Author. Retrieved June 28, 2004, from

Plattner, H., Meinel, C., & Leifer, L. J. (2016). Design thinking research: Making design thinking foundational. Cham, Switzerland: Springer

Rowe, P. G. (1998). Design thinking. Cambridge, Mass: MIT Press.

Schaumburg, H. (2003). Konstruktivistischer Unterricht mit Laptops? Dissertation. Berlin: Freie Universität Berlin. Internet-Dokument: [5.6.2015]

Segall, A. (2004). Revisiting pedagogical content knowledge: the pedagogy of content/the content of pedagogy. Teaching and Teacher Education, 20(5), 489–504.

Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.

Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–22.



Why Solidarity? Notes on Social Justice


Our Natural Sense of Solidarity is Both Necessary and Compromised

Our natural sense of solidarity with others is situationally compromised, no matter how self-glorifying we perceive ourselves. While we generally feel great empathy for the suffering of others such as e.g., on TV as we see children ripped apart by bombs in war zones or scrapping for food on third-world garbage landfills, we also close our eyes with ease once we are asked to pay a price for solidarity.  Refugees should receive help by the UNHCR, we all agree, but better not knock at our doorsteps. We know very well about the difficulties of countries such as Italy or Greece to deal with the influx of refugees and the unbalanced demands of the Dublin treaty, but conveniently close our eyes at the remote prospect of having to share the burden. We opt for solidarity when it suits us and as long as it does not cause personal inconvenience. Our natural sense of solidarity, mirror neurons activated or not, appears only of limited use to solve issues of social justice. Natural perceptions of human solidarity are easily corruptible, especially by politics.

Three Principles of Social Justice

Generally, we are dealing with three principles of social justice: the principle of need, the principle of performance and the principle of participation.

The principle of need says that people should get what they need. Like in Maslow’s hierarchy of needs, people need to be provided food and shelter, comfort and respect. This is fair. From a Machiavellian perspective we could state that unless the poor are not comfortably poor, social unrest will knock on the door. Typically, we all agree that people should be provided with the basics of life, such as medical care and education. Social justice is served when people are provided what they need.

The principle of performance says that it is justice when an effort is rewarded. We commonly hear two variations of this principle. (1) On a negative attributional note, it says: Someone ambitious cannot be treated the same as someone lazy. Be it grades at school or salaries – those who put in an extra effort need to be rewarded while others even may get punished. (2) On a positive normative note, it says: People are not equal. Some are content to live simple, happy lives while others are ambitious to live more demanding lives that also involve higher responsibilities. A surgeon should be paid more than a taxi driver because, obviously, a surgeon carries greater responsibility and requires years and decades of qualification while a taxi driver does not. When I visited China in 1985, corrupt taxi drivers actually made more money than doctors at a hospital, so assumptions on the principle of performance should not be taken for granted.

The principle of participation says that justice is when all people can participate in society and nobody should be excluded. People from socially disadvantaged backgrounds should enjoy going to the movies, theatres, order a pizza, not be discriminated against etc. just like anyone else. Disadvantaged socioeconomic groups should not be worn down to the point where they stop voting, lose hope in a better future, limit their world to immediate physical needs to merely live in the here and now. Participation entails the empowerment to contribute to the whole of society and to play an active part in it.

Conflicting Principles – Now What?

It is easy to figure out that although we generally agree on the justification of these noble and sensible principles, they can conflict with one another. Let’s take capital gain for instance. If I work hard enough, I accumulate capital. This capital is earned by my blood, sweat and tears and I shall, therefore, enjoy the benefits. So goes the traditional libertarian narrative. Soberingly, stock markets do not know blood, sweat and tears. They know numbers, patterns and trends, investor sentiments and market dynamics, but not private perspectives. Once people have accumulated enough capital, such as by inheritance, they do not need to work anymore for anyone, at least not directly. The non-working rich contrasted against the working poor violate the principle of performance: It is against the principle of performance that people enjoy the benefit of a luxurious and comfortable life without effort and qualification. In dictatorial states, such as North Korea, a small corrupt elite manages a different system in which people are rather poor together (low needs satisfaction, high social inclusion cemented by ideology) while performance is measured by the loyalty to the regime.

Currently, the USA under Trump promotes a Rusian model favouring oligarchs, reminiscent of feudal societies of the Middle Ages. In this system, a caste of ultra-rich and powerful individuals and multinational corporations govern the rest of society. Democratic institutions, such as the judiciary or media, are hollowed out and remodelled to serve the reigning caste. Trump and Putin essentially share the same idea of society. Eventually, large parts of the population become socially and politically excluded (and alienated), they will not be able to satisfy basic needs and, in addition, experience how honest effort and hard work do not translate into a better life. People work hard but stay poor. The American Dream has come to its end. How does this compare to North Korea where a large part of the population prefers staying poor together, united under a God-like leader?

The cited examples share a common trait – they are based on inequality. This is not inequality in people being different, which by nature they are, but by attributed inequality (in this case the ‘entitled’ versus the ‘non-entitled’ members of society). Inequality corrupts all three principles of social justice. In a society where rich and powerful elites reign there can neither be a fair gain by effort (since wealth and power are inherited and stays within the caste) nor can there be a fair social participation (little or no social mobility, Wallmart for the poor and luxury brands for the rich) nor can there be a fair distribution of social goods such as medical services, housing, a decent infrastructure, democratic political influence and education. Perversely, it is even beneficial to reigning elites if the rest of society stays poor, uneducated and easily controllable. Recent technological advances in Big Data and AI provide dominating classes with powerful tools to predict social motivation and to influence groups’ decision-making.

Why Solidarity?

Kant would have argued that since we are agents of reason, we cannot use others as a means to an end. Applying the Categorical Imperative, it would be immoral to instrumentalise others, or groups of others, for one’s personal benefit and gain since we would violate their autonomy as well as betray our own. But why should powerful elites care about Kantian reason?

The Habermasian argument goes deeper. Reasoning, unlike a Kantian metaphysical concept, renders for Habermas as a function of intersubjectivity and underlies social action. No matter how unequal and suppressive a regime might be, it can never fully silence questions of legitimisation and justification. Which good argument (that is not ideological and arbitrary) could legitimize inequality? Stakeholders in society can raise the questions of a fair mediation of applied principles at any time. Emancipating inquiry, suppressed or endorsed, is in principle always open and possible. Only in a society that is based on solidarity, claims to social justice can be mediated amicably, peacefully and productively. The process of globalisation supports Habermas’ view since questions about the legitimisation of systems and the distribution of wealth are amplified in an interconnected world – or ‘spaces of flow’, as Manuel Castells put it.

Beyond demonstrating the logic of solidarity via a communication-bound rationality, I could think of another good argument. This is that in a diverse, open pluralistic society any public solution-development tends to be superior and more sustainable as compared to single-minded propositions by dominating groups. Social coherence, shared wealth, democratic innovation and a future-oriented design of institutions are best mitigated within conditions of solidarity where stronger members openly support and foster the disadvantaged of society. We may in the short term suppress the perspectives of others, but only at the cost of negative long-term ramifications.

The more perspectives are invited to a discourse, the more differentiated and fair policies can be designed. Let’s call it the cultural problem-solving argument. It asks what kind of society we want to live in and which benefits, or suffering, we are we willing to impose on our members. In economics, solidarity is realized by a social market economy. It aims at empowering, not alimenting, the less well-off members of society.

Conclusion: Social Trust versus Living in Fear and Paranoia

Although principles of social justice compete with one another, we cannot escape the social and cultural conditions that we create. Solidarity, as an underlying expression of unity and framework to mediate claims to social justice, is a prerequisite for unbiased public discourse.  Solidarity goes beyond the weighing of interests or the balancing of influence since it aims at a cooperative system design. Cooperative design creates, beyond more sustainable solutions, the precious outcome of social trust. Correspondent Jan-Philipp Sendker illustrated the argument by telling the story of a Chinese billionaire (Talkshow with Markus Lenz on German TV, ZDF, on 30. November 2017).

Despite his incredible wealth, this man lived in constant fear of authorities and even of his family who, according to him, could not be trusted with taking care of his autistic son after he and his wife would die. This is how he asked Jan-Philipp Sendker if he could assist him applying for German citizenship. He had heard in the media that Switzerland, New Zealand and Germany were among the few countries where handicapped children could be institutionalized and trusted but not Chinese institutions. Not all the money and power in the world was able to provide him with the comfort of public trust.

Solidarity among all groups of society is a prerequisite for social justice. This is how divisive and polarizing populists run down countries by turning them into plutocratic oligarchies. It is not a trajectory that open Western societies want to follow.

Learning Outcomes for the 21st Century: How and What to Learn in an Increasingly Dynamic World

cat robot Toshifumi Kitamura AFP

Picture credit: Toshifumi Katamura 

This script as PDF: Learning Outcomes for the 21st Century, Kompa 2017

Which are the Necessary Conditions for Learning in a Dynamic World?

As a saying goes, ‘One man’s jungle is another’s rainforest’. The choice of educational outcomes relates to rather diverse socio-cultural, economic-political, psychological and philosophical assumptions so that we may never find a final, all-encompassing consensus on contemporary educational goals. Still, in order to derive at a sensible pragmatic result, we can ask critically for the necessary conditions that are required for people of the 21st century to constitute their lifeworld and systems, to use the terms of Jürgen Habermas. At the end of the day, our influence on the real world is the final measure of success. If only the less capable and competent run our world it demonstrates that our educational and political systems are at peril.

We know that epistemological competencies of knowledge construction are equally as important as the ability to communicate knowledge within society or to create new knowledge in context. To add to the list of expectations, we are aware that the challenges of globalized and digitized societies raise the bar for individual self-regulation. This means that people need to be able to cope psychologically with ongoing changes (such as how workplace changes affect one’s personal life), unlike traditional societies that are still based on rigidly-structured and predictable cycles of knowledge acquisition. A good example of this change is the new ideal of lifelong learning as well as the awareness of the increasing diversity and discontinuity of contemporary careers and jobs markets. On a societal level, things do not become less complex.

This is how, looking for relevant goals, it is not only important to secure better individual and social learning opportunities for young people but to empower them to develop, manage and improve the social systems they live in. This notion entails the fostering of systemic competencies. If people do not want to become passive onlookers on their lives, they need to be able to mediate the disruptions and conflicts arising from technological and economic developments. This is how the superordinate educational meta-goals need to assist sustaining the continuous improvement of individual, social as well as systemic conditions. Since self-governance and cooperative problem-solving play a major role in our historical situation of globalized and technologically transformed societies, we find ourselves redirected to the values of autonomy and solidarity of the Age of Enlightenment.

The Overarching Structure of Modern Educational Goals

Traditional education systems rely heavily on the acquisition of individual-cognitive competencies (such as, e.g., traditional reading, writing, arithmetic etc.) which serve as a resource to draw upon for the rest of life. Society 4.0, in stark contrast, requires continuous professional development, the situational updating of social and intercultural skills as well as restructuring our psychological organisation to accommodate the complexity of multi-dimensional change. Once we become aware of the new societal conditions governing the 21st century, we can paint a fairly coherent picture of the critical conditions that are needed for sustaining successful biographical life projects within an open democratic society.

In this light, Self-Determination Theory (SDT) (Deci & Ryan, 2012; Ryan et al., 2012) differentiates between the human needs for social relations, competence and autonomy. The latter relies not only on individual factors such as motivation and basic knowledge but on accommodating social conditions to empower autonomy. Since the cognitive acquisition of competencies remains the central topic in empirical educational science, the need for competency development is hardly an issue of controversy. Likewise, it is generally agreed upon that the acquisition of competencies depends on both individual and social conditions such as access to education for all, adequate support, well-equipped schools and small class sizes.

The concept of embracing both theory and practice corresponds to the German ‘duales System’ (dual system) which promotes a dialectic relationship between hypothesis-generation and application, similar to the idea of a scholar-practitioner. We know things by creating them. Instead of talking about the acquisition of competencies, psychologist Carol Ryff uses the term ‚Environmental Mastery‘, which points beyond an abstracted, context-unrelated acquisition of skills and knowledge. Her 6-factor model (Ryff, 1989, 1995) also forwards the question how people make sense of their lives, how they can find happiness and psychological well-being. Unfortunately, well-being and happiness do not play a role in the educational models proposed by the OECD.

The Social Construction of Individual Meaning

  • Positive self-concept and the Art of Living (Ars Vivendi)

Life goals and resulting life tasks develop through authentic experiences. A prerequisite to translate personal experiences into future-oriented concepts is a positive and self-regulating Global Self that remains active during all stages of life. The goal of education is thus to empower people to assume positive self-regulation and not only functional problem-solving. We need to develop an art of living which is able to safeguard our psychological well-being. We need to learn how to make and keep ourselves happy (in a eudaimonic manner) which entails embracing wisdom, courage, humanity, justice, temperance, and transcendence (Peterson & Seligman, 2004). Human flourishing is what makes life worth living.

  • Future-oriented developmental perspectives versus alienation and social exclusion

Since life goals are mediated socially, political and socio-economic systems lose their legitimacy the moment personal and systemic interests and activities cannot be mediated reciprocally. Cutting the ties between lifeworld and system renders the system meaningless and epiphenomenal for all democratic participants. Hence, it must be a goal of education to foster mediation skills (systemic competencies) between individuals and democratic institutions in order to align individual life projects with institutionally guaranteed rights and benefits. Constructive political participation depends on properly-acquired socio-political competencies (e.g., how to mediate conflicts collaboratively and taking others’ perspectives into consideration), which renders in the light of emerging populism a strong argument.

  • Environmental adaptation

People find meaning in new and novel concepts of structuring their lives. In economy 4.0, more people work in teams and enjoy the benefits of a high division of labour but they are also confronted with problems that previous generations could never have anticipated (e.g., try explaining a Distributed Denial of Service Attack threatening the survival of a rural community to someone who had lived some decades ago). In highly dynamic economies such as of the OECD countries, young people are required to ‘learn how to learn’, as first conceptualised by Alexander von Humboldt. Self-motivation in solving problems, conceptual thinking skills and able to work in cooperation with others become essential skills to survive in job markets that currently polarize into higher and lower qualified jobs and thin out medium-qualified positions. Inevitably pressure mounts on education systems to formulate new educational goals that are based on understanding, designing and regulating processes rather than teaching static academic knowledge which is of only limited value in practice. Traditional school knowledge may not vanish completely, but it is currently reinterpreted conceptually (such as favouring mental operators, such as analysing, synthesising and evaluating, see Bloom’s Taxonomy, over factual knowledge) and has to prove itself in the context of transferability within interdisciplinary study paths.

Connecting points between researchers

In the following some remarks on the chosen authors to exemplify modern educational goals. Deanna Kuhn (Kuhn, 1991, 20056) defined competencies to formulate and discuss rational arguments, already present in the work of Barrows, from an epistemological perspective. Howard Barrows extended the rational construction of knowledge towards metacognitive reasoning (Barrows, 1992) which, in the meantime, has been further differentiated into individual and social metacognition (Briñol & DeMarree, 2012). As described by Barrows, problem-solving skills depend on a number of discursive-epistemological (hypothesis guided, relating facts to ideas) as well as social-communicative competencies (rational practice, open inquiry and collaborative deliberation). Albert Bandura, one of the most influential psychologists of our time, emphasises in his latest publications (Bandura, 2006, 2008) the necessity of rational, future-oriented self-directedness and self-efficacy to guard individual and collective perspectives of social action. All leading researchers agree on the rational foundation of knowledge construction.

Finally, my choice of including Claude Robert Cloninger is somehow ambiguous since I call the all-encompassing influence of genetically determined personality traits critically into question. Still, Cloninger identified in his Temperament and Character Inventory (TCI) (Cloninger, 1994) important personality traits that are critical to future-oriented learning. These are in particular the development of personal resources, the ability to take responsibility, the social acceptance of others, the ability to empathise, openness towards new experiences and unselfish behaviour. These are noble qualities, we could argue with Bandura (Bandura, 1977), that can also be learned socially and are not exclusively determined genetically.

In conclusion, most leading researchers connect individual and social competencies with abilities of truth finding, concept generation and meaningful social action (Frith, 2012) that integrate systemic perspectives. The arising key argument is that individual, social and systemic competencies relate to each other in a reciprocally-interactive manner. Traditional education, in stark contrast, has primarily only focussed on the acquisition of individual and cognitive competencies. Active learning philosophy has added social skills, systemic competencies and a more advanced psychological regulation to the list of essential educational goals.

From coarse-grained to fine-grained educational outcomes

In the following, I have mapped the discussed educational outcomes within a matrix as a working hypothesis. Besides the findings of leading researchers, we can verify necessary goals by a simple thought experiment. All we need to do is to imagine the consequences of missing objectives, e.g., what would happen if students cannot relate ideas to facts, or if they are unable to work together with others, what if they fail to communicate their concepts to the public and so on and so forth.

An educational goal can be regarded as critical and necessary if its absence leads to logical contradictions, self-negation or compromises higher mental and psychological functioning. Necessary educational goals do not exist a priori, but they evolve from intersubjective relations, which means that the absence or deterioration of objectives (higher educational standards) leads inevitably to social pathologies such as the emergence of aggression-reinforcing group polarisation, the development of rigid social hierarchies, elitist privileges or establishing the permanent exclusion of minority groups.

The concluded critical educational objectives are listed in the following PDF as ‘Extended Educational Outcomes’ (Click here: Extended Learning Outcomes, Kompa 2017). The associated 24 criteria are by themselves latent variables that require operationalisation within didactic contexts. To this extent, the EEO should not be regarded as a standardised ‘one-size-fits-all’ model, but an array of logical building blocks that allow for an almost infinite number of pedagogically useful models. It would be insightful to investigate how qualitative and quantitative data of these latent variables could be integrated so that user-generated data-sets for the optimisation and enrichment of learning processes can be utilized more appropriately.

We have just begun to envision the design of more creative, innovative and more holistic schools that encourage the human spirit to flourish, rather than to stifle it. For now, I like to put forward these extended outcomes as a proposal in order to empower young people being able to master our increasingly complex world. Compromising these standards and settling for any lesser would render a huge disservice to upcoming generations that have deserved better.


While traditional education favours the development of (a) individual cognitive competencies, modern education encompasses in addition (b) social skills, (c) systemic competencies and (d) a more complex internal psychological organisation to empower learners of all ages. Learning outcomes are not arbitrary but are based on real-world environmental demands. The proposed model matches an earlier concept advocated by UNESCO titled ‘Learning the Treasure Within‘ (1996) differentiating between Learning to Know, Learning to Do, Learning to Live Together and Learning to Be. As leading researchers agree on the importance of a rational foundation of knowledge creation, the question arises how knowledge construction and extended environmental demands can be woven into a next-generation pedagogy.



Bandura, A. (1977). Social learning theory. Englewood Cliffs, N.J: Prentice Hall.

Bandura, A. (2006). Toward a psychology of human agency. Perspectives on Psychological Science, 1, 164-180.

Bandura, A. (2008). Toward an agentic theory of the self. In H. Marsh, R. G. Craven, & D. M. McInerney (Eds.), Advances in Self Research, Vol. 3: Self-processes, learning, and enabling human potential (pp. 15-49). Charlotte, NC: Information Age Publishing.

Barrows, H. S. (1992). The tutorial process. Springfield, Ill: Southern Illinois University School of Medicine.

Briñol, P., & DeMarree, K. G. (2012). Social metacognition. New York, NY: Psychology Press.

Cloninger, C.R. (1994). The temperament and character inventory (TCI): A guide to its development and use. St. Louis, MO: Center for Psychobiology of Personality, Washington University.

Deci, E. L., & Ryan, R. M. (2012). Motivation, personality, and development within embedded social contexts: An overview of self-determination theory. In R. M. Ryan (Ed.), Oxford handbook of human motivation (pp. 85-107).

Frith, C.D. (2012). The role of metacognition in human social interactions. Philosophical Transactions Of The Royal Society B-Biological Sciences, 367(1599), 2213-2223. Oxford, UK: Oxford University Press. doi: 10.1093/oxfordhb/9780195399820.001.0001

Kuhn, D. (1991). The skills of argument. Cambridge: Cambridge University Press.

Kuhn, D. (2005). Education for thinking. Cambridge, Mass: Harvard University Press.

Peterson, C., & Seligman, M. E. P. (2004). Character strengths and virtues: A handbook and classification. New York: Oxford University Press/Washington, DC: American Psychological Association.

Ryan, R. M., Legate, N., Niemiec, C. P., & Deci, E. L. (2012). Beyond illusions and defense: Exploring the possibilities and limits of human autonomy and responsibility through self-determination theory. In P. R. Shaver & M. Mikulincer (Eds.), Meaning, mortality, and choice: The social psychology of existential concerns (pp. 215-233). Washington, WA: American Psychological Association. doi: 10.1037/13748-012

Ryff, C. D. (1989). “Happiness is everything, or is it? Explorations on the meaning of psychological well-being”. Journal of Personality and Social Psychology. 57: 1069–1081. doi:10.1037/0022-3514.57.6.1069

Ryff, C. D. & Keyes, C.M. (1995), The Structure of Psychological Well-Being Revisited, Journal of Personality and Social Psychology, 69 (4): 719–727

What the OECD Findings on Students’ Collaborative Problem-Solving Skills Tell Us … And What Not

PISA-CPS-Girls-vs-BoysCongratulations, Singapore!

As one of the pioneers that have championed Problem-Based learning (PBL) in Singapore, I was delighted to see Singapore on the No.1 spot in collaborative problem-solving when the OECD (OECD, 2017) presented its results on November 21, 2017. Many years of hard work by consultants like myself and government investment into a more student-centered pedagogy have, obviously, paid off.  Still, we need to be prudent on how to interpret the results since there is much more implied in the study than meets the eye.

Lesson No.1: Collaborate problem-solving is the exception to the rule, even among top performers

Graphs, like the one above, seldom tell us the overall picture. One remarkable key-finding of the study was  that (highlights by me) ‘(…) on average across OECD countries, not even one in ten students can handle problem-solving tasks that require them to maintain awareness of group dynamics, take initiative to overcome obstacles, and resolve disagreements and conflicts.’ (OECD, page 5). The study points out that even for top-performer Singapore only one in five students attain a high level among the cited criteria, while three-quarters of students are able to address problems of medium difficulty and can integrate diverse social perspectives. Collaboration as a key competence of the knowledge society (Moshman & Geil, 1998) appears rudimentary in practically all developed nations. The results reveal that there is much room for improvement across the board.

The unexplained gender gap

One of the central graphics and headline presented to the media by the OECD organisation (above) suggests that girls categorically outperform boys in collaborative problem-solving skills, which is not the case. Similarly, in a previous study, boys were found to outperform girls in individual problem-solving. Gender differences are statistically significant, but as in all statistics, this means that in reality there is still a large overlap between the better performing boys and the not so well performing girls (or vice versa, when looking at individual problem-solving skills). The authors of the study do no try to explain the international gender gap. They speculate that girls might simply be more receptive to interpreting nonverbal cues (Hall & Matsumoto, 2004; Rosip & Hall, 2004) since the gender gap cannot be explained sufficiently even after accounting for better reading literacy among girls.

Another reason might be found in different age-related competencies between boys and girls. Girls tend to mature faster than boys. This is how longitudinal analyses would be in a better position to explain underlying developmental factors. Judging from my experience with adolescent students, the gender gap diminishes as student populations grow older. In support of this hypothesis, the earlier maturation in girls has been associated with different neurological development (Lim et al., 2015). If varying neurological development could be identified to impact collaborative skills, the gender gap might not qualify as a solid predictor of collaborative skills in adulthood as data may suggest at first sight (see Figure V.4.4 below).

Looking at top-performers Singapore, Japan and Korea, the cultural influence on collaborative skills in interdependent Asian societies (Fiske et al., 1998) who also assign a high social value to education would be another worthwhile topic of investigation. As can be concluded from data, girls do slightly better than boys while some cultures do notably better than others. However, cultural differences clearly outweigh gender differences.

by gender

The big question: Is learning still enjoyable?

To facilitate lifelong learning, learning itself should be an enjoyable, motivating and insightful process. Learning should take place within a positive social environment and it needs to develop students’ personal resources. Although the significant effect of positive social relations for collaborative skills has been emphasised in the OECD study, there is no explicit connection drawn to problem-solving made in the classroom.

The generally stricter and more rigid learning environments in Singapore classrooms do not compare, by a wide stretch, to the more explorative and intrinsic motivation-based classrooms in Finland. This is how, to me, the psychological winner of the OECD study is Finland. Finland demonstrates that a nation can be a leader in collaborative problem-solving while advocating a student-centred, active learning pedagogy at the same time. This fact leads to another scientific blind spot, which is the issue of developing a sustainable intrinsic motivation to solve professional and personal problems throughout the lifetime. In the meantime, the successful alternative approach in Finland has been recognized in Singapore on a ministerial level (Sinnakruppan, 2017).

Lesson No.2: Problem-solvers are not necessarily innovators and entrepreneurs

With the promotion of collaborative problem-solving skills, Singapore had hoped to create an innovation hub reminiscent of an SE-Asian version of Silicon Valley. Although Singapore students fare well in problem-solving, innovation and entrepreneurship did not materialize to the extent it was anticipated by the government. Some factors inhibiting innovation appear to be the cultural habit of relying on a centralized administration, the unwillingness to take risks and to exchange ideas (Wan et al., 2005).

Although I am an ardent supporter of PBL myself, I had to learn over the years that problem-solving and entrepreneurship require different skillsets. Entrepreneurs display a high degree of frustration tolerance and are willing to take above-average risks. Entrepreneurs learn from failures, evolve advanced mental abilities to simulate future scenarios and develop high motivational levels in support of personal perseverance – all qualities that collaborative group processes do not necessarily imply. Innovators need to be brave: The truth is that more innovative ideas have also a higher probability of failure.


One of the key takeaways from the latest OECD study was that collaborative problem-solving is still in its infant stages, even among the top performers. Averages do not represent the stunning underdevelopment among practically all nations. We can agree with the authors of the OECD study that collaborating students only mature within collaborative schools. Beyond the mere measure of cognitive competencies, the development of personal resources and social skills seem to pave the way to succeed in the emerging knowledge societies.



Fiske, A. P., Kitayama, S., Markus, H. R., & Nisbett, R. E. (1998). The cultural matrix of social psychology. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (pp. 915-981). New York: McGraw-Hill.

Hall J.A. & Matsumoto D. (2004), Gender differences in judgments of multiple emotions from facial expressions, Emotion, Vol. 4/2, pp. 201-206,

Lim S., Han C.E., Uhlhaas P.J. & Kaiser M. (2015). Preferential Detachment During Human Brain Development: Age- and Sex-Specific Structural Connectivity in Diffusion Tensor Imaging (DTI) Data, Cerebral Cortex, Volume 25, Issue 6, 1 June 2015, Pages 1477–1489,

Moshman D. & Geil M. (1998), Collaborative reasoning: Evidence for collective rationality, Thinking and Reasoning, Vol. 4/3, 10. pp. 231-248,

OECD (2017), PISA 2015 Results (Volume V): Collaborative Problem Solving, OECD Publishing, Paris.

Rosip J.C. & Hall J.A. (2004). Knowledge of nonverbal cues, gender, and nonverbal decoding accuracy, Journal of Nonverbal Behaviour, Vol. 28/4, pp. 267-286,

Sinnakaruppan S. (Nov 26, 2017). Why Singapore’s education system needs an overhaul. In: Todayonline. Retrieved from:

Wan D., Ong C.H. & Lee F. (2005). Determinants of firm innovation in Singapore, In: Technovation, Volume 25, Issue 3, 2005, Pages 261-268, ISSN 0166-4972. Retrieved from:

About the Methodology of Social Change


The emergence of cooperative research

The Problem of Traditional Research Cycles

The biggest challenge to social sciences is the alienation between research and application. In social sciences and education, few empirical findings find their way back into improving everyday life and not everything that is being researched is of relevance in real-world settings. The gap between theory and application, between expert cultures and social actors, is grounded in traditional belief models.

Typically, it is assumed that a social problem, which is identified by researchers and decision makers, requires quantitative analysis to be objectively addressed. The tool of choice is empirical studies that reveal the causal, correlational and conditional relations of a social problem, e.g., by employing statistical methods such as regression models or structural equation models. At the bottom of the scientific hierarchy, we find smaller single-case studies, followed by correlational research, quasi-experimental studies and on the top meta-analyses and Randomized Controlled Field Trials (RCT/ RCFT). The latter is highly structured for the quality of reporting ‘enabling readers to understand a trial’s design, conduct, analysis and interpretation, and to assess the validity of its results.’ (CONSORT, 2010).

A problem that science despite all rigour, however, cannot reflect is the roles of involved decision-makers who interpret and apply scientific studies on behalf of their employees, staff as well as their users. A good example was the PISA studies that had a major political influence on educational governance across Europe. Local school principals, teachers, parents and students could only watch in disbelief how politicians surrendered to a merely economized view of education based on the measurement of few scant competencies. The top-down approach of monopolized research implies a number of problems when looking at developing sustainable social solutions. The most prominent critique is that social actors are degraded to mere data sources, for example via survey-based research, but they are not included as actively contributing rational agents.

This imposes four fundamental limitations to improving social systems:

(1) CONSTRUCT COMPLEXITY AND ENVIRONMENTAL VALIDITY: The complex nature of people’s lifeworld (their needs, interests, perspectives, motivations, ideas and wishes) is excluded in traditional research. The traditional objectifying approach, e.g., by limiting questions and potential answers of social actors to Likert Scales, imposes a reductionist perspective right at the beginning of the research process.

Traditional research implies a number of conceptual assumptions that may not coincide with the context in situ. Quantitative studies work well in settings where a problem can be clearly defined beforehand, such as medical problems with experimental- and control groups, but they necessarily fail in the case of social solutions development that depends on the active and adaptive contributions of social actors. In this case, the relation between research and research subjects is of an entirely different nature – one is descriptive while the other is participatory.

(2) DISEMPOWERMENT: This argument states that social actors are denied ownership of the problem at hand. By circumventing the perspectives of affected parties, participants of social transformation are excluded from the discourse to improve their environment. As a result, frustration and resentment may set in as participants are degraded to passive onlookers on the implementation of top-down policies. In addition, research and policy-making lose individual and collective meaning which otherwise would have emerged via active participation.

(3) SOCIAL INPUT AND DEVELOPMENT: Traditional empirical research rests on a number of unreflected assumptions. For example, which should be the desired effects of an intervention from the perspective of social actors, which noticeable criteria can measure these effects and which local resources are available to accommodate improvements? It is one perspective to abide by professional standards, such as promoting the acquisition of competencies or to develop individual autonomy, and another to empower social actors to work on solutions taking their unique cultural tools, personal motivation and local resources into account.

(4) SUSTAINABLE OUTCOMES: Social models that are created in cooperation naturally develop areas of corresponding responsibilities. Systems, where policies are imposed onto populations externally, suffer from the drawback that nobody feels in charge of managing them due to the lack of ownership. People assume responsibility for the systems they create.

The development of participatory models

We may take schools as an example. How a school deals with diversity, heterogeneity, its psychological climate, social support networks or mechanisms for continuous improvement is entirely based on the coordinated effort of the administration, teachers, students, their parents and the social context at large.

Due to the need for consensus, social problems and their consequences need to be set in relation qualitatively (Which is the meaning of problems to the individual and which are their social impacts ?) as well as quantitatively (How do problems scale in the social sphere?). Typically, such questions are more adequately addressed in mixed study designs. Mixed-study designs, unlike large quantitative studies, recognize the complexity of social transformations but still fall short of the criteria of democratic empowerment and cooperative local development. New innovative scientific approaches that are based on the input from social actors will be discussed in Part 2 of this essay.

From a data perspective

From a data perspective, we could state that in traditional research a fixed statistical method, based on collected data sets, is employed to determine the significance of effects or the causal interdependencies of factors within a construct. By contrast, in cooperative research, we need to design logical operators (methods) in such a way that we derive at a measurable, computable result. The traditional statistical method is fixed by its choice of initial study design, while cooperative efforts are based on the premise of performing adaptive process changes (competitive prototyping) in regards to achieving desired outcomes.



The Creative Mind: Kant, Hegel and the Complexity of Life in the 21st Century

Artwork: Through spirit’s gaze by Andrew James Campbell. Acrylic on torn paper. A4 1982. With kind permission of the artist. The source of the title is “The Spirit shall look out through matters gaze, and matter shall reveal the Spirits face” Sri Aurobindo

Kant and Hegel, 2.0

When Kant postulated in a Cartesian manner that we are the children of two distinct worlds, the cognitive and the empirical, and that we can derive clear-cut conclusions from there, he was rightfully criticized by Hegel that things may not be as easy as they seem. Assuming that we do not live in a dualist, but in a coherent material reality where the biological-cognitive domain emerges from physical groundings (despite enjoying distinct supervenient-symbolic sets of freedom), such a view entails an organic, rather than a Kantian-categorical model of how our mind, the world and others relate. As history progresses, Hegel’s subject-object evolves and expands through cultural evolution. For Hegel, subject and object constitute each other reciprocally. The concept of such a ‘subject-object information field‘ was also introduced as a scientific paradigm by Eleanor Rosch for the domain of cognitive psychology.

When it comes to creativity, it is not only the artists who create, but scientists, engineers, business-groups, culture, society and the world at large. Generally speaking, all life that is self-sustaining and self-regulating requires creativity, the development of future-oriented, open developmental paths in order to persevere and to evolve. Without it, we would perish or our minds would devolve into repetitive, self-congruent fractal patterns. Once environmental conditions stall, so does evolution. Once environmental conditions become more dynamic, creative evolution starts to get busy.

For Hegel, intuition and concept were just different aspects of the same subject-object unity within a common reality. Kant excelled in his insight that the freedom to reason about our world is a distinct mental property which might be explained by, but not reduced to neurological processes. On the other hand, we can spin Hegel’s argument regarding Kant further: Not only is humanity a mean within itself which cannot (and should not) be instrumentalized, but the same argument extends to the material conditions that safeguard our integrity as rational agents. Examples are the access to education, the availability of creative tools and stimulating environments to develop one’s faculties, the integrity of body, the malleability and adequate development of the brain, the practical autonomy as a person and so on and so forth.

The freedom of our mind matters as much as the material conditions that enable it. The extended Hegelian argument goes as follows: If there is in principle only one physical reality (nature, also following Spinoza’s path here), then the laws of self-governed freedom must apply to all; not only content and form but also the physical grounds that allow conceptual form and mental content to emerge.

The creative mind works from both ends, from the conceptual-cognitive as much as from the intuitive-emotive. Modern psychology and neuroscience have dismissed the mechanical idea of people as thinking machines; or ‘thinking animals’ as Descartes described himself in his Meditations. Without emotion, we could not think, an argument elaborated upon by neurologist António Damásio in his book ‘Descartes’ Error’. Without the empirical reality of our embodied minds, our needs, desires and vulnerabilities, we would have no motivation and no grounding to come up with a single thought. From a Hegelian perspective, environment and mind, intuition and concept, object and subject constitute each other reciprocally as a function of environmental interaction. We may mention Kurt Lewin’s equation B = ƒ(PE), namely that behaviour is a function of the person and the environment. This approach makes more sense than postulating ad hoc metaphysical ideas about life and reality since reciprocality (bi-directional, mutually constituting causality) can be measured and verified scientifically as a phenomenon of our common and shared reality.

Creativity as a Vulnerable State of Mind

Being able to talk about things constitutes us as human beings that can marvel, play, discuss, react and ponder about the world and others. Verbal, non-verbal language and action act as the glue between empirical and mental domains, whereby empirical conditions become the material placeholders for mental content and processes. As such, the mental is folded inside the empirical conditions that surround it. From a phenomenological perspective, we could call this the empirical bracketing of mental content. Creativity, as a bracketed process, evolves in the gentle, protected space where empirical conditions are not too tight to suffocate or destroy creative freedom and not too loose that the mind has only a paucity of environmental stimuli to fall back upon.

Creativity finds itself among adjacent human faculties. According to Sternberg’s Triarchic Theory of Intelligence, the creative intelligence is complemented by analytical and practical intelligence. His choice of categories is peculiar as it echoes the underlying matrix of the information field; this is that the polarized object-subject field collapses between its two poles (the creative and the analytic) and concludes in social action and individual behaviour (Sternberg’s practical intelligence).

The creative action reveals itself always a collapse, a judgment call, a point where subject and object, mind and physical conditions unite. Subjective and objective information is woven into a coherent fabric by the loom of life in which we appear as finite beings within a practically infinite process. It is in our actions (inclusive of speech-acts and electronic interaction) that we constitute ourselves as rational beings. Spinoza might have added that those who dedicate their intellect to the search of such truth are blessed. Truth-searchers are enlightened as they recognize humbly their necessary incompleteness and fallibility. They remain mindful as they position themselves as responsible, autonomous beings. Like a glass of water, the fluidity of the water serves as a metaphor for creativity while the composedness of a rational mind, the function of the glass, holds potentials together. Creative processes need ratio as its guiding vector while ratio depends on creative processes as its source of inspiration, its ground for innovation and renewal.

Dimensions of Creativity

Regarding the dimensionality of creativity, much depends on our point of view. On the level of object-materiality, the creative mind recombines objects and shapes them within information hierarchies. We extract features, recognize patterns, chain and cluster, copy and paste, recombine and sort, analyse and synthesise, create interactive building blocks, define a system’s syntax (such as computer languages) to serve an instrumental purpose and so on. Object-materiality also engages our senses and emotions to which it guides our decision-making. The latter not only serves to create more pleasing outcomes but, in combination with our mental faculties, to create sustainable outcomes that are beneficial to all. This is the level of material design and hypothetical imperatives.

On the level of subject-object and inter-subjectivity, semantics appear on the horizon and we are dealing with what the Philosophy of Mind has defined as qualia. The creative mind takes semantics and qualia into consideration to create new forms, to morph, to evaluate, to restructure typology, to diversify in order for creations to serve and reflect the plethora of the human lifeworld and experience. As life’s paths are developmental open, so must creations serve the openness towards our shared future. As we need information and data to process semantics and qualia, we could call this type of creative processes ‘In-formations’ (to put into a form) since they address the development of ideas based on facts (idea), the meaningful creation of typologies (typos) in order to relate ideas to concepts and the need to change the overall form of structures (morphe) to suit human needs. On this second level, we design not only artefacts but systems. In system design, empathy is critical. The rational grounding of empathy lies firstly in the Kantian recognition that all individuals regardless of particulars are categorical representatives of mankind and secondly in the notion that no single man-made system stands in isolation of another. Hence, our emotional interest in the plight of other stakeholders is a ‘rational emotion’ (from a Kantian perspective). In endorsing empathy, we recognize the state of the rational grounding of others. We not only accept other’s dignity, but we also respect the systems they engage to make sense of the world. Ideally, we co-create systems.

Finally, on the level of environmental interaction, creativity transcends the subject-object. We interpret, re-define, constitute our social Selves, embed our lives in cultural memory, make gutsy lifetime decisions and undertake deep emotional investments, develop concepts, get inspired by intuitions and think critically about the relationships between ourselves and our future possibilities in the context of the environment. Since we are dealing with a global and holistic view of the subject-object phenomenon and its continuing transformations, we could name this type of creative processes ‘Transcendations’. It defines all processes that transcend their self-congruent borders and reformulate a system’s local particulars in view of global development and emergence. From a psychological perspective, cognitive dissonance and cognitive restructuring are the keywords.

From a scientific perspective, looking through our mental lens, we just defined different levels of detail and interaction, whereby each point of view enjoys its particular merit. All three levels of engagement challenge our individual and collective competencies, in particular with regard to increasing system complexity.

To conclude, creativity is not an arbitrary subjective faculty that escapes objective measure. This would be both the wrong perception as well as the wrong underlying question. The whole point of intact (flowing and exchanging) information fields is not to infer a preferred view within the object-subject (e.g., a spiritualized mind over matter belief or big data manipulating personal integrity) but to realize that the creative process requires a formal scaffolding and modes of creative processing in order to inform qualitative and quantitative aspects of research and investigation. To this extent, creativity is perhaps also the deepest political force of all, more profound than any ideology ever could, as we find our new historical role as designers of globally compatible and beneficial systems. Measuring our aspirations against real-world outcomes, the openness towards critique and ongoing improvement becomes our most precious virtue. The higher our standards, the stricter our self-critique.

The Creative Reasoning of Actors

But who are the drivers of change? The material grounding of good design is stakeholders, not shareholders or onlookers. It is only when participants can bring their genuine interests, intuitions, perspectives, sufferings and passions to the table that we can complement those original requests by mindful conceptualizing, not by automated technocratic processes. Kant delivers the deciding argument here and I shall extend his proposition a bit. Only by critical reasoning as well as making our creative reasoning a matter of public discourse for the sake of a better lifeworld design, we can evade the pitfalls of dehumanizing our environment to the point where autonomy and freedom slip off our hands. The argument is that once the conditions for open systems creation become means to a purpose and surrender to hypothetical imperatives (such as e.g., by commercialisation or the maintenance of privilege at the expense of others), spaces for sensible negotiations and co-creations between stakeholders deteriorate or vanish. Creativity in the 21st century has never had so many options and has never been in so much peril of being instrumentalised. We need to work hard, stay open-minded, be patient, listen to our hearts and take uncomfortable risks for mind to matter.

Special thanks to Andrew James Campbell for all our conversations inspiring this script.

Metacognition (Part 2): What Makes Us Truly Human? A Literature Review

original robot picTo learn is to create: Educational robotics are a very recent trend that requires children and adolescents to plan, reason, experiment, create, play and learn from failure. In the process, they acquire and apply new knowledge. As in most such technology-based scenarios, students learn in teams. Photograph by Alain Herzog, 2015

The path of least resistance and least trouble is a mental rut already made. It requires troublesome work to undertake the alteration of old beliefs.

John Dewey

What makes us truly human? Part 1 of this series (‘What or how we think is not quite as important as how we can govern ourselves’) outlined the significance of metacognition on the individual and social level. It was concluded that the freedom to develop alternative solutions to a problem and to become self-aware of one’s own as well as others intentions, perspectives, feelings and interests constitute key competencies of the human condition. Without such freedom, our mind would simply follow environmental stimuli or tradition and we would barely be capable of developing a more complex and rewarding lifeworld.

The following review investigates the deeper structure of metacognition. It is divided into two sections. Section 1 provides an overview of leading concepts that investigate individual and social metacognition (ISM). Section 2 reviews the suitability of various theoretical frameworks in order to propose a unifying approach of how to measure metacognition in the context of autonomous (intrinsic) versus heteronomous (extrinsic) regulation.

1. The dimensionality of individual and social metacognition

Individual Metacognition: Self-Knowledge and Behavioral Control

The first formal model of individual metacognition was developed by John Flavell (Flavell, 1979, 1981) who was influenced by the constructivist psychology of Jean Piaget (Flavell, 1963). Flavell (1979) defined metacognition broadly as a person’s self-knowledge and regulation over her own cognition, an overarching concept that is shared in literature (Brown, 1987; Flavell, 1976, 1979; Kuhn & Dean, 2004; Martinez, 2006; Paris & Winograd, 1990; Schraw & Moshman, 1995; Schraw et al., 2006).  Metacognition is accompanied by metacognitive experiences such as the feeling of difficulty (or ease of learning), the experience of self-efficacy, affective states dealing with uncertainty and task motivation (Efklides, 2006, 2009, 2014; Flavell, 1981; Kleitman & Moscrop, 2010; Schneider, 2008; Zimmerman, 2008). Metacognitive experiences have been identified to play a critical role in self-enhancement motivation (Jiang & Kleitman, 2015) to support self-regulated learning (Boekaerts & Corno, 2005; Boekaerts & Niemivirta, 2000; Dweck, 1998).

Metacognitive knowledge generally refers to the reflective knowledge that people have about their information processing skills which entail the knowledge of tasks, task complexity and the knowledge of strategies on how to cope with tasks. Corresponding metacognitive regulation describes the related executive skills of cognitive monitoring and self-regulation associated with metacognitive knowledge (Schraw et al., 2006; Schneider, 2008). Flavell’s original blueprint has since been extended considerably by other researchers.

Adding to the definition of metacognitive knowledge, several authors (Cross & Paris, 1988; Kuhn & Dean, 2004; Schraw et al., 2006) have identified declarative, procedural and conditional knowledge as its central components. Declarative knowledge refers to a learner’s self-knowledge of resources and abilities. Procedural knowledge refers to the knowledge of the purpose and the processes involved to solve problems and to self-regulate tasks (Metcalfe & Shimamura, 1994; Nelson, 1994, 1996) while conditional knowledge refers to knowing the conditions under which knowledge can be generated, transferred and applied (Schraw & Dennison, 1994).

The concept of metacognitive regulation has likewise been expanded upon and includes the planning and critical evaluation of cognitive tasks and goals (Brown, 1987; Dunlosky & Metcalfe, 2009; Cross & Paris, 1988; Martinez, 2006; Paris &Winograd, 1990; Schraw et al., 2006; Schraw & Moshman, 1995; Whitebread et al., 2009). Metacognitive planning entails the abilities of forethought (Pintrich, 2000), for example by goal setting and resource allocation, while Schraw & Moshman (1995) and Schraw & Dennison (1994) added debugging strategies to correct for comprehension and performance errors, information management strategies to process information more efficiently and comprehension monitoring to allow for the self-assessment of one’s learning.

Metacognitive regulation has been further segmented into (a) Cognitive monitoring, which refers to making self-aware judgments about one’s learning. (b) Metacognitive planning which, as outlined above, refers to the evaluation and employment of most efficient resources and strategies (Cross & Paris, 1988; Li et al., 2015; Schraw et al., 2006; Whitebread et al., 2009) and (c) Metacognitive evaluation, which refers to the ability of making metacognitive judgments and formulating monitored interpretations (Dunlosky& Metcalfe, 2009; Pintrich, 2000; Schraw & Moshman, 1995; Wang, 2014).

Formulating a more holistic approach, Pressley, Borkowski, and Schneider (1989) have proposed the ‘Good Information Processing Model’ which also takes into consideration the elements of prior knowledge about the world, motivational orientation and the ease of employing successful strategies automatically. This model was later extended to include metacognitive self-regulation skills (Efklides, 2001; Schunk & Zimmerman, 1998, Schneider, 2008). The level of prior knowledge plays a large role in pedagogy as it defines the scope of a learner’s inner resources such as coherent concepts and internalised ideas.

Much of current research on metacognition deals predominantly with empowering student learners such as in literacy, reading and comprehension (Baker, 2008; Israel et al., 2005; Leopold & Leutner, 2015), developing self-efficacy (Aydin, 2006), improving problem-solving (Cornoldi et al, 2015; Wismath & Orr, 2015), essay writing (Surat et al., 2014) and mathematics (Desoete & Veenman, 2006; Özcan & Erktin, 2015; Kleden, 2015). Other studies have focused on peripheral topics such as linking metacognition to worrying and sleep (Thielsch, Andor, &Ehring, 2015; Thielsch et al., 2015) or consumer knowledge discrimination (Pillai et al., 2015). Not much research has been conducted in areas such as the workplace, organisational decision-making, culture or politics.


Picture (MIT): Prof. Tommi Jaakkola during a class in AI “Introduction to Machine Learning”. The more complex a society, the more relevant becomes cognitive and metacognitive regulation

As part of self-regulated learning, metacognition has also been linked to critical thinking skills (Bowell & Kemp, 2010; Dwyer et al., 2014; Felton & Kuhn, 2007; Halpern, 1998; Ku & Ho, 2010; Kuhn, 1999; Magno, 2010; Mayer & Goodchild, 1990; Olson & Astington, 1993; Schroyens, 2005) since metacognition is self-correcting and refers to the epistemological question ‘What do I know and how do I know it?’ (Kuhn, 1999, p. 18).Critical thinking skills involve executive functions for difficult cognitive tasks, such as recognizing assumptions, making inferences and deductions, formulating interpretations and evaluating arguments (Magno, 2010). Despite general agreement on the overall construct of metacognition, Kuhn & Dean (2004) pointed out that there is e.g., a large divide between psychological researchers, emphasizing on objective standards, and practitioners who expect students to be empowered to contribute to a democratic society. Both standpoints beg reconciliation. An overview of the general taxonomy of individual metacognition is summarized in Figure 1.

Figure 1: Systematic overview on the concept of  individual metacognition by the author (click to enlarge)

Social Metacognition: The Awareness of Others

No human life, not even the life of the hermit in nature’s wilderness, is possible without a world which directly or indirectly testifies to the presence of other human beings.

Hannah Arendt, The Human Condition

The official advent of social metacognition in social psychology was marked by a publication of an edited volume on metacognition by Dardenne, Lories & Yzerbyt (1998) which connected topics that are of particular interest to social psychologists, such as relating feeling-of-knowing judgments and theories about the social influence on memory with topics such as stereotyping, prejudice and social bias correction.  Since then, social metacognition has been established as an essential topic in social psychology (Bless & Forgas, 2000; Mischel, 1998).

One of the key issues has been, ever since, differentiating social metacognition from individual metacognition. Briñol (2012) argued that metacognition is primarily defined as thinking about one’s own (vs. others’) thinking, since primary thought is causally more efficient if it appears in one’s own head. Social metacognition is represented for Briñol in many ways, for example as an individual’s mentalizing about social objects (e.g., the perception of family and relationships), thoughts shared by a community (thoughts about others’ thoughts) or thoughts communicated to others.

Briñol rejected the proposal by Jost and colleagues (1998) who called for an expansionist approach of social metacognition on the grounds that the true agent of mentalization is still the individual subject. In this proposal the authors called for the inclusion of (a) mentalizing about other people’s cognition, (b) momentary convictions, such as ‘the feeling of knowing’ (Nelson & Nahrens, 1994) and (c) descriptive general beliefs of how the mind works, such as beliefs about intelligence (Dweck, 2013) as well as normative beliefs of how the mind should or should not work, such as deferring to make stereotype judgments about others (Yzerbyt et al., 1994).

Jost and colleagues (1998,  p. 140) argued, with experimental evidence from studies on familiarity heuristics, that ‘fleeting feelings’ are often guided by metacognitive states (Banaji & Greenwald, 1995; Begg, Armour & Kerr, 1985; Jacoby et al., 1989; Metcalfe; Strack & Bless, 1994). The authors argued that self-concepts such as beliefs about self-efficacy (Bandura, 1991; Ferrari, 1996) or the nature of intelligence (Dweck, 2013) are modelled via social learning processes and thus need to be included in social metacognition.

The opposing positions of Briñol et al. (2012) and Jost et al. (1998) can be reconciled by putting into perspective that social metacognition plays out on a gradient scale between implicit, automated processes and explicit, reflected mental processes. In this light, Schraw & Moshman (1995) proposed a taxonomy defining (a) tacit (b) explicit-informal and (c) explicit-formal metacognitive theories. Tacit theories (a) are acquired, constructed and applied without one’s knowledge. For example, a teacher’s epistemological assumption of how adults learn describes his tacit, implicit theory about students’ learning and decision-making (Kagan, 1992; Sternberg & Caruso, 1985). Explicit-informal theories (b) imply a subject’s awareness and knowledge of some of the mental content, while the rudimentary framework still lacks conscious justification of beliefs and their underlying assumptions.   On the level of explicit-informal theories people reflect purposefully and systematically on their actions and modify their future thinking and performance (Kuhn et al., 1992), differentiating between empirical and formal content (Hergenhahn & Olson, 1993). Finally, in explicit-formal theories (c) people become fully aware of their mental states as demonstrated, e.g., in Problem-based Learning where tutors facilitate metacognitive reasoning by asking group-members to provide arguments for their assumptions, beliefs and propositions (Barrows, 1992; Barrows & Wee, 2007).

Another approach to frame the multi-dimensionality of social metacognition, to pick up on Briñol’s argument of personal mental efficacy, is to differentiate how social metacognition is causally evoked by individual, social and environmental input. Kim and colleagues (2013) asked about the eliciting source of metacognition and propose a dual-agent (individual and social) organization of social metacognition. The authors argued that a single individualistic or social perspective by itself cannot sufficiently explain e.g., how learners with weak metacognitive skills can overcome temporary failures (Kim et al., 2013). Based on the concept of socially shared metacognition (Iiskala et al., 2011) and regulation within groups (Vauras et al., 2003) they concluded that the social level acts as an integrated agent in the form of consensual, participatory goal setting and collective planning. The learning environment evokes, as a separate layer, social metacognition by framing problems of different task complexity and conceptual demand. Individual metacognitive reasoning is for the authors causally defined as ‘due to oneself’ while social-level reasoning is defined ‘due to others’ (Kim et al., 2013, p. 388).

A neglected field of research is the relationship between empathy and social metacognition. The underlying question is how can we be motivated to take the plight of others into perspective if there is no prior emotional identification with the other, this is if we cannot recognize the other as an equal human being despite particular differences. The central role of empathy in combination with social metacognition is however fully recognized in Clinical Science (Eichbaum, 2014: Stansfield et al., 2015).

2. The suitability of theoretical frameworks to measure psychological motivations

If the goal of the research is to measure the entire spectrum of autonomous versus (competing) heteronomous types of regulation, few psychological frameworks offer a useful conceptual base. For example, the Theory of Planned Behavior (Ajzen, 1991, 2002) works under the assumption of individual, goal-directed behavior based on a person’s attitude, subjective norm, perceived behavioral control and individual intentionality. Like most rational-choice theories, the approach does not take into consideration heteronomous factors such as the influence of social habits, social milieu and interaction effects involving cultural context, social norms or group influence (Manstead, 2011).

On the other end of the spectrum, Social Identity Theory (SIT) (Taifel & Turner, 1979) works under the assumption that it is one’s group association that creates a sense of belonging and creates self-esteem, honour, pride and identity. SIT defines the subsequent processes that create social identity as (a) social categorization, where people categorize and define themselves and others in relation to each other, (b) social identification, where people adopt the identity of their new ingroup and (c) social comparison, where one’s ingroup is compared against outgroups, evoking judgments about the other groups’ worthiness as well as one’s own. SIT does conceptually not account for individual reasoning to transcend identities beyond group affiliation.

Self-determination Theory (SDT) (Deci & Ryan, 2012; Ryan et al., 2012), by comparison, takes as a motivational theory the entire spectrum of intrinsic and extrinsic types of motivation into account. It is argued that high-quality forms of motivation support the human needs for autonomy, competence and relatedness (Deci & Ryan, 2000; Ryan, 1995) while social context and cultural factors may even undermine motivation and volition. SDT is empirically well supported across disciplines (Deci et al., 1999; Chircov et al., 2003; Guntert, 2015; Hagger et al., 2015; Masden et al., 2014; Ng et al., 2012; Ryan et al., 2006; Van Berghe et al., 2014; Webb et al., 2013) and has demonstrated cross-cultural validity and reliability (Gagné et al., 2014; Grouzet et al., 2005; Sheldon et al., 2009; Soenens, 2012; Vlachopoulos et al., 2013; Zhou & Deci, 2009). SDT differentiates between five basic types of self-regulation (Ryan et al., 2012, p. 221-223) which shall be briefly described in relation to sociocultural context.

(1) Externally motivated and control-dependent behavior is characterized by the regulation by external rewards and punishments (Skinner, 1953) which exclude the Self. Beyond physical conditioning, rewards and punishments are also represented by peoples’ weighing between payoffs versus costs for complying with social norms (Sherif, 1935; Asch, 1951; Milgram, 1963). Hedonic adaptation (Diener et al., 2009; Kahneman et al., 1999), for example, can be regarded as a result of external motivation.

(2) Introjected regulation includes mental models that have been partially internalized by the self. In this case, the motivation for behavior is governed by the avoidance of shame and guilt or providing for socialized self-esteem rewards (Beer, 2014; James & Amato, 2013; Walker & Bright, 2009) such as in the honor cultures of the Mediterranean and the Middle-East.  Introjected regulation is also facilitated by inferences provided by common sense – (Heider, 2013) and folk psychology (Hutto & Ratcliffe, 2007; Kelley, 1992; Kruglanski et al. 2010) which largely supports culturally-shared, naïve assumptions “how people think they think about the social world” (Wegner & Vallacher, 1981, p. 226). On the other hand, loss of honor is typically followed by feelings of shame, feeling disrespected, disempowered and can be responded with aggression and violence.

(3) Identified regulation (social norm regulation) entails that people identify with their enactment of behavior and assume responsibility for their actions and they relate internalized social norms and values to reflected personal consequences for enacting them. Underlying social norms function on this level as injunctive norms (Cialdini and Trost, 2011), an intricate system of reciprocal expectations that society formulates towards the individual and, in return, expectations of the individual to how others should behave (Bicchieri, 2006).

(4) External integrated regulation describes a type of motivation where people do not only reflect upon personal and social norms, values and identifications, but they bring into congruence the claims and perspectives of others as the basis for cooperation. The causation of such reflective thought due to others is a hallmark of social metacognition (Kim et al., 2013).

(5) Intrinsic motivation implies that a person acts according to his or her personal aspirations. Behavior is initiated because it is experienced as personally enriching and engaging, independent of external stimuli. Intrinsic motivation entails the ability to resist habitual responding and to base decision-making on motivating values which are not a function of anxiety, defense and conditioned response. People seek to proactively develop positive social relations, environmental mastery, self-acceptance, personal growth, autonomy and purpose in life (Ryff, 1989; Kállay & Rus, 2014; Li, 2014) by free personal choice (Deci, 1971, 1975).

To this extent, intrinsic motivation is linked to individual metacognition for developing goal-directed behavior via mental strategies (Coutinho & Neuman, 2008; Ee et al., 2009; Gollwitzer & Schaal, 1998), while monitoring and controlling for adverse environmental influences that may frustrate, inhibit or prevent individual development (Vansteenkiste & Ryan, 2013).

From the perspective of SDT, ISM can be conclusively understood as forms of external integrated and intrinsic regulation. Heteronomous forms of regulation, by contrast, are usually encoded as folk- and cultural beliefs (introjected regulation), social norms and conventions (identified regulation) as well as hedonic well-being (both on an individual and social level with others). This conceptual approach entails a less polarized concept since in everyday life peoples’ lives are ruled by more complex types of motivation that combine individual and collective motives. As Chirkov and colleagues noted, “Because autonomy concerns volition, persons who are strongly connected with others often function with those others’ interests in mind. Put differently, if others are integrated within oneself doing for or conforming with those others could be fully volitional.” (Chirkov et al., 2003, p.103).


Picture: Instead of looking for solutions by respecting and integrating the perspective of others, modern societies often behave like tribes. Photo from an indigenous protest in Brazil during the UN Rio+20 summit. Source: KeystoneUSA-ZUMA / Rex Features

Conclusion: What makes us truly human?

In terms of research approaches, what appears of interest are not necessarily all possible forms of human motivation but those that are most relevant to generate specific outcomes. Since we are interested to empower human agency on all levels, we need to be aware of motivations compromising individual and social freedom and autonomy. In this light, the institutional embeddedness of metacognitive practices is of particular interest here, both in terms of the internal democratic management of organisations as well as developing socially inclusive services and sustainable design for clients. As pointed out in Part I of this series, the connection between empathy, social metacognition and the development of ethical concepts has not yet been fully investigated and lacks empirical research.

Self-awareness, self-regulation, forethought, logical reasoning, creativity, empathy, perspective-taking and the mindfulness of others are some of the key features that make us truly human. We have just begun to grasp the basic grammar of human agency.


Due to the long list, all references to Part 1 and Part 2 of this series are listed as PDF here Literature Review, References Joana Kompa.