1. ALGORITHMIC THINKING AND
DIGITAL FABRICATION
Guide: Prof. Pradeep G. Yammiyavar
Prabhat Kumar
Rishika Jain
Harshit Agrawal

2. Aim
To make it easy for people to understand spatial reasoning and simultaneously enhance algorithmic
thinking through an easy to use programing platform.

3. Objective
Remove misconceptions that people have related to
programing.
Make learning programing and understanding of algorithmic
thinking as simple as manipulating blocks on screen
Motivate algorithmic thinking by relating code to a visual output
on the screen and to a tangible output of personal creation
Platform that helps teaching programing in a way that is
accessible to people with minimal computer knowledge

4. Objective
Remove misconceptions that people have related to
programing.
Make learning programing and understanding of algorithmic
thinking as simple as manipulating blocks on screen
Motivate algorithmic thinking by relating code to a visual output
on the screen and to a tangible output of personal creation
Platform that helps teaching programing in a way that is
accessible to people with minimal computer knowledge

5. Objective
Remove misconceptions that people have related to
programing.
Make learning programing and understanding of algorithmic
thinking as simple as manipulating blocks on screen
Motivate algorithmic thinking by relating code to a visual output
on the screen and to a tangible output of personal creation
Platform that helps teaching programing in a way that is
accessible to people with minimal computer knowledge

6. Objective
Remove misconceptions that people have related to
programing.
Make learning programing and understanding of algorithmic
thinking as simple as manipulating blocks on screen
Motivate algorithmic thinking by relating code to a visual output
on the screen and to a tangible output of personal creation
Platform that helps teaching programing in a way that is
accessible to people with minimal computer knowledge

7. Methodology
Existing
platforms
User study
Conceptualizing
new platform
Prototype
Future work

8. Logo
Scratch

9. Logo
Mathetic (knowledge about learning) aspects of Turtle Geometry
Turtle geometry is an aid to learning other things because it encourages the conscious,
deliberate use of problem-solving and mathematic strategies (in order to learn
something, first make sense of it)
Play Turtle. Do it yourself.
Turtle circle is an incident of syntonic learning

10. Logo
Transitional Object : bridge between concrete and formal reasoning
Logo turtle - a ‟mathematical creature‟ that can move forwards or backwards and turn right or
left in response to programmed commands.
Kids can identify with the turtle
The link to formal reasoning through the turtle is effected in large part by a procedural
language(Logo) (hence, logo+turtle - real screen-based transitional object)
Might be experienced by children as simultaneously cognitive and emotional artifacts.
Is entirely screen-based and affects different kids to different extents
There is a need to rethink design of effective transitional objects objects and in the light of
new material technologies.

11. Logo
Microworld of Turtle Geometry
Microworlds serve as incubators of powerful ideas, productively constrained, selfcontained cognitive worlds
Again completely screen based in LOGO
Computationally enhanced construction kits can serve as micro worlds
(Eisenberg, 2003)
We aim to empower kids to build their own construction kits, a microworld that is
partially computational and partially tangible

12. Logo
‘Mathland’ as a cultural setting in which ideas of mathematics become
natural, personalized, and humanized
The idea of “talking mathematics” to a computer can be generalized to a view of
learning mathematics in “Mathland”; that is to say, in a context which is to learning
mathematics what living in France is to learning French. [Mindstorms, p. 6]

13. Logo
Decomposition
Papert refers to it as breaking down a program into "mind-size bites”.
Logo uses the metaphor of "teaching the turtle a new word”. The need for subprocedures is discovered and they are taught to the turtle.

14. Logo
Interface
Turtle indicates the state
Anthropomorphic metaphor in language

15. Research on
Learning Taxonomies

16. Bloom‟s taxonomy
sorts learning
objectives by
cognitive complexity
Knowledge: the student can recall specific facts or methods.
This level is characterized by verbs such as
enumerate, name, and define.
Comprehension: the student understands the meaning of
facts or concepts. This level is characterized by verbs such as
explain, discuss, and paraphrase.
Application: the student can solve problems by applying
knowledge to new concrete situations. This level is
characterized by verbs such as produce, implement, and
solve.
Analysis: the student can break down information into its
parts to determine motives or causes, or to make inferences.
This level is characterized by verbs such as
analyze, discriminate, and infer.
Synthesis: the student can combine elements in new ways to
produce novel wholes. This level is characterized by verbs
such as create, compose, and invent.
Evaluation: the student can make judgments about material
in light of selected criteria. This level is characterized by verbs
such as appraise, critique, and compare.

17. The SOLO taxonomy
sorts learning
outcomes by structural
complexity
PreStructural: a response at this level misses the
point or consists of empty phrases, which may be
elaborate but show little evidence of actual
learning;
Unistructural: this kind of response meets only a
single part of a given task or answers only one
aspect of question. It misses other important
attributes entirely;
Multistructural: the response is „a bunch of facts‟.
It expresses knowledge of various important
aspects, but does not connect them except
possibly on a surface level. The learner sees „the
trees‟ but not „the forest‟;
Relational: the response relates and integrates
facts into a larger whole that has a meaning of its
own. It is no longer a list of details; rather, facts
are used by the learner to make a point;
Extended abstract: a response at this level goes
beyond what is given and applies it to a broader
domain.

18. Introductory Programming Courses are demanding in today‟s era.
In comparison to its esteemed status in other subfields of education, these
taxonomy have received relatively little attention in programming education until
recent years.

19. Introductory Programming Courses are demanding in today‟s era.
In comparison to its esteemed status in other subfields of education, these
taxonomy have received relatively little attention in programming education until
recent years.

20. User study

21. User Type 1: People venturing into the world of programing

22. Programing Misconceptions
Program execution
The program flow
Parameter passing
Trace
Unnecessarily strict rules
Viability

23. Users Type 2: Spatial Thinking Skills

24. Problems Identified
Measuring of length and area.
Iteration of standard units
Need to apply multiplicative reasoning to the measurement of area.
Learning how to represent angle mathematically.
Children are more aware of angle in the context of movement (turns).
An important aspect of learning about geometry is to recognise the relation between
transformed shapes (rotation, reflection, enlargement). This is also difficult, since children‟s
pre-school experiences lead them to recognise the same shapes as equivalent across such
transformations, rather than to be aware of the nature of the transformation.

25. Observations
Young school children have difficulty with
the idea of decomposing shapes into parts
Difficulty with the inverse process of
composing new shapes by combining
two or more shapes to make a different
shape exists.
The barrier: these are unusual tasks for
children who might learn how to carry them
out easily given the right experience.

26. How to teach Spatial Thinking
space
representation
reasoning

27. Conceptualizing a new environment

28. The programing environment should
allow the learner to
Read the vocabulary: what do these words mean?
Follow the flow: what happens when?
See the state: what is the computer thinking?
Create by reacting: start somewhere, then sculpt
Create by abstracting: start concrete, then generalize

29. Follow the flow

30. See the state

31. Create by reacting

32. Create by abstracting

33. Language

34. Any programming system must have
Individual things
Groups of things
Commands that operate on things
Ways to repeat commands
Ways to make choices
Ways to create chunks
Ways to combine those chunks
Motivation

35. How fab can help
experiential
education
constructionism
critical
pedagogy
The motivation of being able to create and put
together a concept, in the form of a personal
structure makes the activity compelling, as it
results in the forming of an intellectual
attachment to, or engagement with the software
part of the process.
Students can investigate an object from all
angles helping in developing spatial reasoning.

36. Why Fab: Iterative cycle of creative
learning
think creatively
communicate
clearly
plan
systematically
learn
continuously
analyze
critically
work
collaboratively
design
iteratively

37. Existing Attempts

38. Revolve - Solve - Evolve - Resolve
4 different ways of thinking of 3D models that combine spatial
reasoning skills with algorithmic thinking
Method A : Spin around an axis
Method B : Move the Turtle - Body Syntonic (Spatial Thinking)
Method C: Construction Kits
Method D: Deconstruction

39. But essential prior learning
Training to understand 3-Dimension world inside computer screen
(Space, Representation and Reasoning)

40. Space

41. Representation

42. Reasoning

43. Method A: Spin Around the axis

44. Method B : Move the Turtle

45. Method C: Construction Kits
Source: http://www.thingiverse.com/thing:15754

46. Method D: Deconstruction
Source: http://blog.ponoko.com/2012/03/19/a-sophisticated-program-to-create-laser-cuttable-3d-forms/

47. Prototyping

48. http://prabhat1992.wordpress.com/

49. Current Prototype

50. Future Work
User interface design
Development
Testing

51. References

52. ?