Define ‘blended’ PART I

BLENDED LEARNING_EDUCAUSEBLENDKIT_Blended courses (also known as hybrid or mixed-mode courses) are classes where a portion of the traditional face-to-face instruction is replaced by web-based online learning.

OLC_a course where 30%-70% of the instruction is delivered online

EDUCAUSE_Blended learning mixes F2F and non-F2F activities, some performed synchronously, some asynchronously. As such, blended learning provides the flexibility to address a broad range of curricular and institutional needs, opportunities, and goals. For more click here

Abrams & Haefner, 2002; Bender 2006_Combines personal interaction from live class sessions with online education for greater learning flexibility (Bender, Vredevoogd, 2006)

MIT (J. Pankin, J. Roberts, M. Savio, 2012)_We define blended learning as structured
opportunities to learn, which use more than one learning or training method, inside or outside the classroom.

KINEO_The Oxford Group_2013&2014_Blended learning is the seamless integration of online and offline learning methods. These methods can be formal and informal in the way they are created or accessed.

RYERSON UNIVERSITY_2012_No definition, just methodology description




Abrams, G. & Haefner, J., 2002, ‘Blending online and traditional instruction in the mathematics classroom’, in The Technology Source, available here

Bender, D. M., & Vredevoogd, J. D. (2006). ‘Using Online Education Technologies to Support Studio Instruction’, Educational Technology & Society, 9 (4), 114-122.

Pankin, J., Roberts, J., Savio, M., 2012, ‘Blended Learning at MIT’, available here

Thompson, K., ‘Undwerstanding Blended Learning’, available here


Heuristics & Cognitive Biases


Heuristic (adj): searching to discover

Heuristics: thinking relying on the use of intuition, human feel, experience, rules of thumb, examples by analogy for judgemnet and decision making in real life conditions, without normative analysis based on mathematical representation. (Tversky and Kahneman 1982; Schon 1983)

Heuristics are used to reach quick, reasonably effective, and creative solutions, but they may also lead to errors and fail because of cognitive biases (e.g. Tversky and Kahneman 1982a; Baron 1994; Evans 1995; Osherson 1995), which are unwarranted confidence in believing the likelihood of an outcome.

Frequent Biases or illusions of Validity:

  • Representativeness: rely on similarity
  • Availability: based on the ease of recall and imaginability, top down bias where the way information is stored in memory has misleading effect on the way we access it.
  • Anchoring and Adjustment: dependence on adjustment from an initial value
  • Insensitivity to predictability

Debiasing Strategies:

  • making the task easier
  • teach probability estimation skills
  • consider alternatives
  • decrease reliance on memory
  • warning of the possible biases at work
  • the rebuttal or disqualification  mecchanism, thinking about exception


References & Image

Bay, Joo-Hwa, 2001, ‘Cognitive Biases on Design: The case of tropical architecture’, PhD Dissertation, Technische Universiteit Delft

A short history of Architecture schools (in progress)


St. Luke Displaying a Painting of the Virgin by Guercino

  • Academia di San Luca, 1577, Rome: taught ‘l’arte del disegno’ a Vasari term, with theoretical lectures on geometry
  • Academie royale d’ architecture, 1671, France: ex-cathedra teaching
  • Ecole Politechnique, 1794, Paris, the firstserious attempt to overcome the gap between theory & practice. Alexander Tzonis states: “morning hourse were assigned to theory classes through lectures and the afternoon was dedicated to design exercises applying the theory taught in the morning (…) the formula proved to be naive and inadequate.”
  • MIT, 1865, Cambridge Massachusetts: first professor was William Robert Ware who later founded Columbia University



Tzonis, A., 2014, A framework for architectural education, Higher Education Press Limited Company, available here

Image available here

Ina Klaasen’s Modelling Reality


Models: Definition

a simplified rendering of reality – present or future- is called a ‘model’ of that reality, provided that a structural relatedness exists with that reality and that the model is based on conscious interpretation of that reality

Kinds of models:

  • verbal: a discourse in words
  • mathematical: made up by numbers or symbols, all computer models are mathematical models
  • spatial: a spatial rendering of three dimensional reality on scale, all architectural designs and maps
  • mechanical: is a model functioning in analogy with its original, a  spatial model with the fourth dimension of time.

Types of models in relation to reality:

  • concrete:spatial and mechanical, composed of empirical identities, they correspond to matter
  • model: conceptual as in verbal, mathematical, spatial and mechanical, a mental construction (theory, sketch) referring to (past, present, future) reality, composed of conceptual identities, they correspond to comprehension. all two-dimensional spatial models are thought models.
  • formal: mathematical models, it is an uninterpreted syntactic system of symbols, it corresponds to abstract names, like the concept of a ‘point’

Functions of models:

  • descriptive: maps the existing situation
  • explicative: it addresses the ‘why’ and or ‘because of what’
  • predictive or probable-projective: what will probably happen based on insight
  • intentional-projective: it is a model for a situation deemed desirable, it does not yet exist
  • explorative-potential-projective: what is the case, what might be the case, future possibilities

Klaasen claims that the choice which type of model to use depends on “the intention with which reality is approached, the function the model must perform and personal preference of the person making the model.” She also goes on to say that  “mis-conceptions may occur about the possibilities as well as on the limitations of designs and analyses: model overextension”. (see figure above)


References & Image

Klaasen, I., 2002, ‘Modelling Reality’, in T.T. de Jong and D.J.M. Van der Voort (eds), “Ways to Study and Research Architectural”, Urban and Technical Design, Delft University Press, Netherlands


Design Conversations


  • Collaborative Conversations (CC): they are either discussions about concepts indirectly raleted to the design or the presentation of a resolved design solution, they have a predictable pattern where negotiation and moving actions do not combine. Discussions involve explaining and questioning while Presentations involve proposing.

  • Collaborative Ideation Loop (CI Loop): it is the most recognizable element of Design Conversation, it is called a loop because it repeats itself; frequently the one who sealed a loop with a decision making will initiate the next loop; at least two or more participants should be involved. Two types of loops: Immature and Mature. Immature Loops focus on securing design concepts, while Mature Loops focus on giving form to previously agreed general concepts

  • Collaborative Moving (CM): rapid ideation where a number of small decisions are being made on the sketch as it progresses. This kind of conversation accompanies the last stage of ideation before switching to another kind of design tool, which is different from illustrating a concept to better communicate it to a third party. As its name states, CM is collaborative.



Dorta, Th., Lesage, A., Di Bartolo, C., 2012, “Collaboration and Design Education through the Interconnected HIS: Immature vs. Mature CI Loops observed through Ethnography by Telepresence”, eCAADe 30, Vol. 2, pp 97-10

What is design solution? (in progress)

Various definitions through literature (text in progress)

  • a social process that involves a variety of participants with different skills, responsabilities and interests, who see the object of design differently. participants who do not share the same mental representations of the design, negotiate by managing a design conversation (Buciarelli, 1988)
  • a collective sense building where interaction is not the sum of effective work, but reciprocal incentives that contribute to the design task (Achten, 2002)
  • a negotiation between different stakeholders who define and redefine the design problem (Rittel, 1973)
  • the co-evolution of the problem-solution (Dorst and Cross, 2001)
  • two processes: one is to generate a plan for a programme, and the other is to justify the plan in relation to a programme (Tzonis and Oorschot, 1987)



Dorta, Th., Lesage, A., Di Bartolo, C., 2012, “Collaboration and Design Education through the Interconnected HIS: Immature vs. Mature CI Loops observed through Ethnography by Telepresence”, eCAADe 30, Vol. 2, pp 97-10

Bay, Joo-Hwa, 2001, ‘Cognitive Biases on Design: The case of tropical architecture’, PhD Dissertation, Technische Universiteit Delft



This was an experiment conducted by Dr Giovanni Birindelli in ETH Zurich during the years 2007-2009. Its results can be seen here.

What is interesting about mt_EAST is that it relies on remote collaboration intended here as a cooperative work over distance between relatively small groups of two to three students from each participating institute. This was achieved through remote collaboration and remote seminars. In the first case students met online for 45 to 60 minutes each week and discussed their project. According to Birindelli:

The personal distance between partners enables students to present professional and constructive criticism, as well as to develop a subject-specific language

The online seminars on the other hand aimed at denoting a new type of educational forum in which “multiple students are able ot receive the support of a docent through the help of an electronic table.”

Despite the noble act to introduce remote collaboration, the high end e-table used and the related software (though Marratech is no longer available) make it difficult for other institutions to follow. Nevertheless, this was an important step in recognizing the need to incorporate technology features in a design studio and making students from different institutions work together online. If you think about it, this was never about the e-table afterall.



  • Birindelli, G., “Learning in Distances” lecture, available here
  • Birindelli, G., “mt_EAST: e_ teamwork GUIDE”, available here


available at

Co-Op or Co-Lab?

Interesting distinction between coperation and collaboration by Thomas Kvan of the University of Hong Kong while discussing collaborative design. The author attempts to make the distinction between the two terms by comparing their etymologies. Therefore:

  • Co-operari means to work together while
  • Col Labore means to labour together

At this point Kvan notices a subtle distinction; collaboration is a joint problem solving act, it means working with others to find solutions satisfying all concerned to a problem they mutually agree on, to be open and exploratory, trusting and accepting.  Coperation on the other hand is to work together in conjuction for a mutual benefit and it does not necessarily mean that there should be a deep level of trust between parties to carry out the work, Kvan claims.

Design is an act that involves many others and this according to  Kvan can be done in two ways:

  • with close-coupled designers: people working closely with each other or
  • with loosely coupled designers: people contributing each to a different domain of the project

Gero and McNeill, says Kvan, have shown that “design is in fact a process that consists of a series of distinct events that occupy discrete and measurable periods of time. Most significantly, they have shown that the temporal span of these design events is remarkably short”. Therefore, the design activity  consists of discrete decisions not intimately linked.

In the light of this Kvan distinguisghed between three types of collaboration:

  • Mutual: the participants work with the other
  • Exclusive: participants work on separate parts, negotiating occasionaly
  • Dictator: the participants decide who is in charge and that person leads the process

Key word to understanding this is the term compromise a term already suggesting that there can be only a partial agreement between those involved. Kvan goes further to suggest that collaboration is so time consuming that it is usually cooperation and compromise that prevail as they should in order to realize a successful project.


Kvan, Th., 1997, “But is it collaboration?, in Challenges of the Future [15th eCAADe Conference Proceedings / ISBN 0-9523687-3-0] Vienna (Austria) 17-20 September 1997

full article available here

Collaborative design


Henro Achten and Jakob Beetz from the University of Eindhoven collected 324 papers on collaborative design and they carefully examined them in regard to their content. Here is what they have discovered and published in a paper entitled “What happened in collaborative design?” in 2009.

Papers written between:

  • 1983_1993: describe it as a potentially possible direction
  • 1994_1997: look for technological solutions to support it
  • 1997_2008: express a steady reflection of what collaborative design really is.

Papers were also classified in regard to their contribution to:

  • support_largest category, 3d virtual environments, synchronous and asynchronous applications, comprehensive systems, community participation, tools
  • methodology_all aspects how to research collaborative design through case studies & research methodology
  • theory_focus on the nature of collaborative design: design management as in how CD is managed and controlled and kind of design as in publications that describe CD as a specific type of design.
  • model_design modelling, information modelling, knowldge modelling & representations
  • technology_ multi-agent systems, technology
  • education_pedagogical models (how CD should be taught), virtual design studios

Through the examination of the above mentioned papers CD is considered a good thing but often too difficult to achieve. Institutions, the authors claim, are still teaching the students as individuals.

References and Image

Achten, H.H., Beetz, J., 2009, “What happened to collaborative design?” in Computation: The new realm of architectural design – Proceedings of the 27th Conference on Education and Research in Computer Aided Architectural Design in Europe / Ed. G. Cagdas, C. Gulen. – Istanbul : Istanbul Technical University & Yildiz Technical University, 2009. – ISBN 978-0-9541183-8-9. – p. 357-365

Design Concept Formation

Ullman_1992: examines design concept formation in designing or redesigning devices with specific functionality, within the context of mecchanical engineering. Generation of multiple concepts for the same task as:

  • functional decomposition: breaking down the needed function of a device as finely as possiblewith as few assumptions about form as possible
  • concept generation from functions: listing conceptual ideas for each function that come from the designer’s own expertise enhanced through brainstorming etc.

Schon_1963: proposes the displacement of concepts as a principle that explains innovation. Old concepts can be used as a projective model for new situations, transformed or transposed. Design process is considered a situated activity during which designers seek to solve a problem where the conceptual task is to frame the problem. For this puprpose the designer initiates a reflective conversation involving action and reflection on the consequences.

Gero_1998: draws examples from the genetic engineering of evolutionary systems to show that design concept formation is based on the emergence of patterns in the available design representations.

Richards et al._2007: presents an analysis on the use of frameworks in electrical engineering, with the goal to identify practices to improve the development of systems. Three key issues:

  • artifacts in system design
  • benefits provided by frameworks
  • the measures of effectiveness for assessing the value of frameworks.



Kotsopoulos, S.D., 2007, “Design concepts in architecture: the porosity paradigm”,  Proceeding SW+W2.0’07 Proceedings of the First International Conference on Semantic Web and Web 2.0 in Architectural, Product and Engineering Design – Volume 294, pp. 69-80, available here

Bloom’s taxonomy scheme twice revised

blooms taxonomy inverted

On the left it is the original Bloom scheme, in the middle one can see its revised version in 2001 and on the right is an interpretative image of the revised version according to the articles mentioned here. As I always prefer verbs to nouns myslef,  the revised version is much juicier than the original one. 

Bloom’s taxonomy was introduced in 1956 and later revised in 2001 by a group of cognitive psychologists, curriculum theorists and instructional researchers.  Two history teachers Wineburg  and Schneider in their article entitled ‘Was Bloom’s Taxonomy pointed in the Wrong Direction?’ challenged Bloom’s taxonomy. They conducted an experiment that compared the reactions of a 17 year old AP (Advanced Placement) student and those of a group of history graduate students to an historical document. Despite the fact that the document was foreign to their interests the history graduate students did better analyzing what it was about than the AP student thus proving that knowledge was the result of a questioning process rather than the basis of their investigation. As the authors argue:

Those who go back and read Bloom will find much to praise. That knowledge is the foundation for all further acts of mind, for instance, is a fundamentally sound concept. But our concern is about Bloom in practice – the way that the Taxonomy takes on a life of its own (…) knowledge possessed does not automatically mean knowledge deployed.

Peter Burkholder, while debating the role of content in the design of his history course recalls Wineburg ‘s model ‘wherein students focus on analysis and interpretation and develop these thinking skills at the outset as a way to learn content instead of the other way around’. He performs yet another experiment by inserting quizing protocols in his class (to be later elaborated in group discussions) to engance peer communication and induce opportunities for students to learn the material. He goes on to state that:

The inherent challenge of content, especially the sheer potential volume of it to be covered in history survey courses, is daunting, but primarily because teachers often base their course design off of that content. This study suggests there is another way to envision the survey, one where learning goals of critical thinking, analysis, and evaluation start the course design process, and content is built in to serve those goals—“backward design,” as famously termed by two experts.

I’ll be back for this for the architectural implications of the revised taxonomies.


‘Bloom’s Taxonomy’, by Patricia Armstrong, Assistant Director, Center for Teaching, available here

‘Was Bloom’s Taxonomy pointed in the Wrong Direction?’ by Sam Wineburg and Jack Schneider, The Phi Delta Kappan, Vol. 91, N 4 (Dec., 2009 – Jan., 2010), pp. 56-61 available here

‘A Content Means to a Critical Thinking End: Group Quizzing in History Surveys’ by Peter Burkholder, pp. 551-578, The History Teacher, Volume 47, No 4, August 2014

Image on the left available here

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Reconsidering Boyer’s sense of scholarship through the use of new technologies


Boyer’s definition of Scholarship as

  • discovery: creation of new knowledge
  • integration: knowledge across disciplines
  • application: engagement with the wider world outside academia
  • teaching: tuition fees have changed students to consumers

Scholarship reconsidered by new technologies:

  • discovery as in open data: analyzing and generating unprecedented amounts of data through computing and sharing them publicly_datasets as part of academic communication
  • integration as in open publishing: when the discoveries of others are put into context and applied to wider problems in the form of journal articles, conference proceedings, monographs. Peer reviewing is also transformed as readers copy, append and comment on the content of an article through the medium of distribution.

[i.e. JOVE (journal of visualized experiments) uses videoed contributions that communicate complex experimental techniques and reduce the time taken to learn and adopt new ideas]

  • application as in opening up the boundaries: academics use new communication technologies to address a wider audience [i.e. blogs] complementary to the academic one. Key to realizing a personal brand online is an attitude of openness by sharing aspects of personal life on social network sites, blogging ideas than articles.
  • teaching as in open education: online digital technologies and open approaches to teaching and learning as sharable resources allowing access to high quality materials no longer limited by physical constraints.

‘Digital Scholarship Considered: How New Technologies Could Transform Academic Work’, Nick Pearce, Martin Weller, Eileen Scanlon and Melanie Ashleigh, The Open University available here

Image available here

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.