ALGORITHMIC THINKING AND DIGITAL FABRICATION

Guide: Prof. Pradeep G. Yammiyavar

Prabhat Kumar

Rishika Jain

Harshit Agrawal

To make it easy for people to understand spatial reasoning and simultaneously enhance algorithmic

thinking through an easy to use programing platform.

Aim

Remove misconceptions that people have related to

programing.

Objective

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

Remove misconceptions that people have related to

programing.

Objective

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

Remove misconceptions that people have related to

programing.

Objective

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

Remove misconceptions that people have related to

programing.

Objective

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

Methodology

Prototype Future workConceptualizing

new platformUser study

Existing

platforms

Logo Scratch

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

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.

Logo

Microworld of Turtle Geometry

Microworlds serve as incubators of powerful ideas, productively constrained, self-contained 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

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]

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 sub-procedures is discovered and they are taught to the turtle.

Logo

Interface

Turtle indicates the state

Anthropomorphic metaphor in language

Research on Learning Taxonomies

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.

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.

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.

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.

User study

User Type 1: People venturing into the world of programing

Programing Misconceptions

Program execution

The program flow

Parameter passing

Trace

Unnecessarily strict rules

Viability

Users Type 2: Spatial Thinking Skills

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.

Problems Identified

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.

How to teach Spatial Thinking

representation

reasoning

space

Conceptualizing a new environment

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

Follow the flow

See the state

Create by reacting

Create by abstracting

Language

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

How fab can help

experiential education

constructionismcritical

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.

Why Fab: Iterative cycle of creative learning

think creatively

analyze

critically

work

collaboratively

communicate

clearlydesign

iteratively

learn

continuously

plan

systematically

Existing Attempts

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

But essential prior learningTraining to understand 3-Dimension world inside computer screen

(Space, Representation and Reasoning)

Space

Representation

Reasoning

Method A: Spin Around the axis

Method B : Move the Turtle

Method C: Construction Kits

Source: http://www.thingiverse.com/thing:15754

Method D: Deconstruction

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

Prototyping

http://prabhat1992.wordpress.com/

Current Prototype

Future Work

User interface design

Development

Testing

References

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