The Bloom Taxonomy from 1956 suggests the following steps for teaching and learning:
When building an math bot Sofia
in 2004, we were not aware of the Bloom scheme and made up our own:
Question Concept Objects Bloom analogue
1. What Knowledge Terminology Knowledge
2. How Skills Algorithms Application
3. Why Insight Concepts Comprehension
4. Why Not Creativity Innovation Synthesis
This was ordered according to the difficulty when teaching mathematics to a machine:
Teaching definitions is no problem. More challenging is to implement getting
solutions to standard tasks. Wolfram alpha can do that very well already.
Teaching insight is already hard and the holy grail in education.
The last step, to challenge notions and finding new ways
is the hardest part and very challenging. Its difficulty is underestimated by
anybody who has never done it. It is hard to be creative for a simple reason:
it is just hard.
In the lecture
"What is mathematics"
from a teaching math in a historical context course,
I illustrated how arbitrary taxonomies can be. Take the classical 7 liberal arts and sciences,
consisting of the trivium and quadrivium: one can see
Grammar as a metaphor for "What", Rhetorics as a "How", and Logic as a "Why".
The creative part is not in the Trivium. But the quadrivium includes it.
Arithmetic can be seen as a metaphor for "Doing things", Geometry to
"See things", Music to "Feel things" and Astronomy as "Seek new things".
Trivium: Grammar Rhetorics Logic
What? How? Why?
Quadrivium Arithmetic Geometry Music Astronomy
Do It! See it! Feel it! Seek it!
This bending of the 7 liberal arts and sciences illustrates
how arbitrary taxonomies can be. As the Bloom taxonomy, it can fit the
learning process. Here is a
of the numbered nonsense. Especially with the number 7 (seven ways to ...)
There are two major difference between the Bloom Taxonomy and what we had done
in that AI project:
A) We put "Application" before "Comprehension".
B) We placed "Evaluation" as a separate process.
I want to argue here that for learning processes, application should come before comprehension
and that it makes sense to take out evaluation as the later is a different entity which
should apply to all four steps.
The "Hitchhikers guide to the galaxy" satirically puts in Chapter 20
the "How,Why and Where phase" in that order.
The joke is that "Where" should definitely come before "How" and the "Why" later.
Here is the quote:
"The history of every major galactic civilization tends to pass through
three distinct and recognizable phases, those of Survival,
Inquiry and Sophistication, otherwise known as the How, Why, and
Where phases. For instance, the first phase is characterized by the
question `How can we eat?', the second by the question
`Why do we eat?' and the third by the question, `Where shall we have lunch?'.
I really like that quote because it gets the order of "How" and "Why" right.
I did not think about the "Where" yet ...
Example 1: Learning how to drive.
Most learn to drive a car before gaining insight of the inner workings of a car.
Even when learning to drive tanks, I first learned to drive it before being explained
the concept of how steering and power is related. One can argue that it is
of advantage to know the details of how a clutch rsp power stearing works in order to understand how
to drive a car or tank. But only very academic or rule driven military minds do that.
Yes, it is useful to know how things work and one only becomes a master if one knows
it, but the understanding comes only after one has done it. On M109 tanks for example,
one hits the gas pedal strongly when making a turn. This is counter intuitive but can
be explained: the steering mechanism needs pressure to work. Would previous theoretical
knowledge help to learn it? No, you simply experience that if you get away from the
gas pedal and try to make a turn, nothing happens.
Example 2: Learning a language.
The fastest way to learn a language is to pick up some key phrases and play with
them without being too worried at first to be grammatically correct. Then take well
chosen texts and learning them. After a while,
with more vocabulary and knowledge one starts to understand the connections and patterns.
I learned English and French like that. For Latin, it went differently. In Latin, we
first learned all the grammar and rules and then started to work with concrete texts.
That was actually refreshing for a change and it helped me to understand also the grammar
of other languages better. On the other hand, I never learned how to speak Latin, even
after being instructed 7 years (entire middle and high school time) in it.
Example 3: Learning to cook
While it is helpful to know the chemical workings of spices and ingredients
of a dish, most start cooking with the cookbook. With some experience, one starts
to experiment and push the boundaries. A professional cook needs to know about the
physical processes going on, when cooking and what the ingredients exactly contain.
But most folks just do it, use trial and error and experience from other cooks
without trying to understand first, why things are done in a particular order or
in a particular way. A steak tastes differently when it was cooked with an initially
sizzling hot pan rather than having pan being heated up while the meat is inside.
It is physics: the initially raw meet closes faster on the surface in a hot pan. Does
a chef need to know this? Probably not, but the chef needs to consider a few dozen
other parameters. Getting one thing wrong can ruin the task.
Example 4. Learning to play an instrument
While music theory is important and helps to learn to play an instrument, it is
often more effective, just to play first, then later connect the dots.
I myself got some basic music theory at the beginning but just enough to be
able to read the music notes. Then it was playing and playing and practicing
and practicing. Later in high school, when I took lessons from Sava Savof, it came a bit with
a revenge that I did not learn enough music theory. Yes, our music classes in
high school covered a bit of theory, also physics (like the physics of the
Laplacian for drums), and other approaches to music like Stockhausen, but I
never learned music theory, as it would be useful for playing piano well. Still,
having put the music theory at the very beginning would have been pointless.
Switching "How" and "Why"
How quickly "concepts" should be introduced into the learning process is a hotly debated
point and there will never be agreement: what should come first, the
"How" or the "Why", when learning. I hope the examples before have made a point that
for most learning processes the "How" comes before "Why". I know however that especially
in academic circles, many would put first the "Why" and then the "How". But this often has
a crippling effect on learning, especially in practical matters like using software.
The reason is simple: for software of many other human made things, the "How" often does
not have a good answer or is too complex even for an engineer. But it has a funny effect
that intelligent people can often be rather helpless in practical matters when using a new tool.
Kids are usually very good at exploring new things
because the "How" is more like a game type approach in contrast to the
more analytic approach which adults chose. Playing around
first is faster and more efficient in learning things.
And once, the "How" is mastered, the "Why" starts to become accessible.
Since there is so much disagreement in this matter, lets argue again why having things the other way
can have a paralyzing effect: trying to decipher a manual of an older watch or camera or
learn a programming language by first learning the syntax rules or theoretical properties
of a language or first learning music theory is harder
than just playing around with that thing, just programming some examples or playing around
with the music instrument. Most folks do what kids do naturally: they play
first with it before analyzing it. When learning a language, asking first to learn the structure and
workings of grammar makes sense but it can lead to frustration and therefore loss of interest.
It is better first to learn to talk, repeating sentences even blindly before
understanding them and then fill the gaps. The examples themselves then explain the grammar.
Similarly when playing a musical instrument, it is better first to learn how to play and
only later learn the music theory behind it.
In math, the meaning and interpretation of things usually come only much after mastering
"how to do things".
In my opinion, the Bloom mixup of "How" and "Why" has serious consequences:
students do no more know the basics if the basics are questioned very early on.
It is expected now that the student comes up with a clever or new way to compute things even in
basic arithmetic. Having to be creative all the time produces stress and
uncertainty. But creativity only flourishes, once there is enough firm knowledge built in.
Creativity to a large degree also just comes from ``going the wrong way".
But going the wrong way all the time is not helpful and the lack of success hinders learning.
It is like stuffing too much paper and wood onto a freshly lit fire. The fire first needs to
be developed a bit before it can handle the challenge.
"Evaluation" as a different entity
"Testing and evaluation" is an important step as it allows to pinpoint
misconceptions. But it should not be part of the taxonomy as
the evaluation part appears everywhere.
The assessment of "understanding" is a complicated process and it is so important that
it merits its own taxonomy: A way to assess the understanding is to check whether one is
- We have to learn the meaning and definitions and test whether we know the definitions.
- We have to learn the algorithms and know how to do it and check that we do it right:
- Then we need to apply it to new situations and look at limiting situations where it fails.
- Finally, we should be able to develop it further and go beyond what has been done. That evaluation can take centuries.
being able read it
being able to write it
being able to teach it
being able to program it
Each is a multiple times harder than the previous one. Reading or hearing it is passive but
it can be challenging already. Take a book about a subject you are unfamiliar with and you know
that this stage can be challenging.
Writing requires to reformulate it or solve problems.
Teaching requires to be able to answer unexpected questions about it and programming it requires
to understand every detail, every special case, every limiting case.
Teaching it also could mean to give a talk about it or explain it to somebody else.
Programming it can be overwhelming and is the ultimate test whether one understands the material.
A machine is unforgiving. The smallest misconception prevents things from working.
And if things don't work, there is nobody else to blame. We simply don't understand it well enough
Taxonomy for solving problems
An other taxonomy for creativity can be seen on the front of the Boston science museum
which are all related to inquiry
It does not claim to be a taxonomy as the later aims to be a classification.
Assume however it would:
how does one make discoveries, where does one search and explore to innovate?
The words themselves are quite useless since they do not provide any constructive
path to research: if it were then the order and equip it with context:
imagine What is the goal or vision?
search What has been done? Look around.
discover Recognize that something is new.
innovate Improve and realize the project
would be better. The most famous problem solving advise is the "How to solve it"
guidelines by George Polya
what is the question Understand the problem
outline a path Make a plan
carry out the plan Realize the plan
review and check Revise and improve
It was an extremely important book for me as it helped me to improve my problem
The most difficult part is certainly the creative step to find the solution:
also here there are models. An example is the "snowflake model" of creativity
of David Perkins:
Allow complexity and disorganization. Enjoy challenge and chaos.
Solve problems. Find creative solutions. Feel for good questions.
Think in opposites, metaphors or analogies. Challenge assumptions.
Take risks. Accept failure. Learn from mistakes. Enjoy incompetence.
Scrutinize own ideas. Seek criticism.Put aside own ego. Test ideas.
Catalysis is enjoyment, satisfaction, and challenge for the work itself.
Also teaching guidelines exist. There are 7 principles for smart teaching
which appears in the book "How learning works".
Get component skills
Practice and feedback
Climate and culture
Self monitor learning
This is not a taxonomy and also not ordered. It is a list which contains probably
anything a group would come up in an hour when being asked "What matters when you teach?"
Maybe it is because the authors are mostly from non STEM areas (there is only one
statistician, the rest are psychologists) that they forgot to mention the most important
point for "How learning works":
learning only works if the one who teaches knows the stuff.
The teacher has to know the subject well.
Not only is it important to understand the material which is taught, but way beyond.
And this is my main critics of teaching models of pure online or flipped classroom teaching:
there are models where the teacher can hide behind ignorance: for Moocs, the videos are simply
"talking heads" like the news anchors in TV or actors in film. They don't have to understand anything.
Similarly, in a flipped classroom, where the teacher does no more have to reorganize
learn and present the material, but simply guide through some pre-canned worksheets (usually where
solutions are given). It is the fast food of teaching and destroys teaching culture.
Doing work in groups or alone or doing presentations is of course extremely important, but
it should come together with good instruction. But the later should not just
consist of pre-canned videos.
Not that flipped classrooms or video instruction should not happen. They are
ancient flavors of teaching (I took a course in electronics 35 years ago in a Telekolleg
which was essentially a MOOCs, there was just no web but TV, but it is pretty much the same model
it came with a book and worksheets and tests. New with MOOC's is the peer review and discussion.
Most of my teachers since first grade used flipped classroom components and it was
nice, for a change). My critics is the propaganda behind "replacing all instruction by flipped classrooms"
and hype about massive online courses is that the proponents often sound as if it is universal.
But there are pitfalls: for example, online discussions and peer review are tricky: most of them on
the web are terrible if not moderated.
Slashdot, wikipedia and stack overflow and stack exchange are well moderated. It needs a critical
mass of actively involved experts so that nonsense is weeded out.
Our group made once a brainstorm experiment on March 9, 2015 to see "what teaching should accomplish
besides the content" and here it what we came up within 10 minutes:
(this is paraphrased only and merge the points and order them differently as they had found:)
Ability to build models
Acquire problem solving skills
Hone communication skills
Ability to think independently
Ability for conceptional thinking
Develop sanity check habits
Practice perseverance and work habits
Appreciation for application
Appreciation for beauty
Appreciate connections with the world
Appreciate connections to history
One problem with trying to accomplish all this at once is
"overload". I myself have seen the problem "overload" in my own
teaching: for many years I had used technology almost in every
class and made every lecture connected with a historical fact.
Applications can be tricky since applications by definition deal
with other subjects which requires expertise and knowledge way
beyond the situation taught.
Teaching appreciation for beauty and connection with the world
can be especially challenging. For all this, one has to keep in mind that
Transferring knowledge and insight
is still by far the most important point. If that does not work, all the others
will fail. The success of dry online lectures like "Khan academy" comes exactly
from the fact that they are "no nonsense" approaches: no coating in stories, cryptic motivation,
mumbo jumbo, pedagogical tricks or politics: knowledge pure.
While working on mathematics myself or when teaching, I also
like to contemplate on the process of how things are found or how a lesson is
planned. This is almost as interesting than the actual mathematics or the teaching itself.
So what is would be my list of advise for research and teaching?
Having scolded taxonomies above, don't take this too seriously and make your own.
- Constantly learn new material. Amass a huge amount of literature. Stimulate yourself with knowledge.
Acquire skills way beyond what is needed.
- Keep a diary. If time does not permit that, write things down immediately in article form.
When teaching, make notes.
- Don't hesitate to start from scratch. With a blank sheet of paper. No books, no internet, no other
person nearby. After having seen "what is important" compare with other sources.
- Explore also fields, where you don't know much. This allows to see things in a new way.
Enjoy to be an idiot. In teaching, it can also mean to push the boundary and teach something new.
- Allow to think sloppily first, be fuzzy and allow errors. This allows to overcome
obstacles. Afterwards, try to get over the obstacles. In lesson planning this means to remain
- Transfer knowledge from one field to an other, even if it makes no sense at first.
For teaching, interests and passions can help to make lectures more interesting.
- Learn from others, learn from students, read the "masters", folks who have broken new ground.
- A draft was written after a workshop organized by the Bok Center
in the fall of 2014.
- April 14 2015, put online.
- April 15 2015, some proofreading.
- May 5, 2015, minor fixes