What are the didactical principles for teaching computer science

Professor Viera K. ProulxCollege of Computer ScienceNortheastern UniversityBoston, Massachusetts, USA

vkp@ccs.neu.eduhttp://www.ccs.neu.edu/home/vkp

Didactics for Computer Science >><< Viera K. Proulx >><< May 1999

Outline

Why teach computer science/informatics What are the key ideas What are the key didactical principles Using technology to teach computer science Teaching computer science without technology Concluding remarks Acknowledgements

Why teach computer science/informatics

Recent report by the National Research Council, USA defined:

Fluency in Information Technology contemporary skills

use of computer and applications foundational concepts

mostly informatics intellectual capabilities

abstract thinking and reasoning skills

http://www2.nas.edu/cstbweb/

Contemporary skills (NRC report) setting up a personal computer using basic operating system features using a word processor, spreadsheet, database using graphics package connecting to a network and using Internet to find

information using computer to communicate with others using instructional materials to learn how to use new

applications or features

Intellectual Capabilities (NRC report) engage in sustained reasoning manage complexity test a solution manage problems in faulty solutions organize and navigate information structures and

evaluate information collaborate; communicate to other audiences expect the unexpected anticipate changing technologies think about information technology abstractly

Foundational Concepts (NRC report) computers: program, interpretation, CPU, memory, I/O information systems: hardware, software, interfaces, people… networks: physical structure, protocols, bandwidth, standards digital representation of information: text, images, sound,

video modeling and abstraction: validity, limitations, how it works algorithmic thinking and programming universality: every computer works the same way!!! limitations: growth rate, tractability, decidability, accuracy societal impact of information and information technology

What are the key didactical principles

Understand what are the key concepts you are trying to teach

Make examples interesting and relevant Provide projects that focus on the concept Use graphics and illustrations to model the

concept Present patterns in design and programs Support collaboration and interaction Set the stage for further exploration

Using Technology to teach computer science

Programs that generate graphics as main output motivation and visual debugging illustration of concepts

Animations that illustrate the key concepts to support lectures to provide environment for experimentation

Modeling real uses of computers Web sites with supporting material Excel as a modeling and exploration tool

(ask Erich Neuwirth…)

Programs that generate graphics:scaled drawings

Programs that generate graphics:animated loops

Programs that generate graphics:nested loop patterns

Graphics for feedback and motivation:maze search

Graphics for feedback and motivation:function plotting and sorting

Mini applications:piano keyboard, MiniPaint

Modeling real world computer science:cryptography (Ceasar’s shift)

Modeling real world computer science:Mars planetary images

real datalot of datamixed text, numeric, and pixel dataimage enhancementadditional topics

Modeling real world computer science:Mars planetary images

Modeling real world computer science:morphing line drawings

Modeling real world computer science:morphing images

Modeling real world computer science:recursive fractal grammars

recursive fractal grammars (L-systems)impressive use of recursionexample of the need for extensive computational power

seeing order of growth in ‘real life’design issues for display (scaling)

need for recomputation, good designpower of algorithm

generate complex drawings from only a few lines of grammar definition

recursive fractal grammars (L-systems)Example:

The Sierpinski Gasket:angle = 60°S -> RL -> R+L+RR -> L-R-L

FASS Curves (space-filling, self-avoiding, simple, and self-similar)Example:

Hexagonal Gosper Curve:angle = 60°S -> LL -> L+R++R-L--LL-R+R -> -L+RR++R+L--L-R

Modeling real world computer science:

recursive fractal grammars

Modeling real world computer science:recursive fractal grammars: Sierpinski gasket, dragon

recursive fractal grammars: tree

Bracketed OL-systems

angle = 20°S -> FF -> F[+F]F[-F][F]N = 6

traffic simulation

Using technology to teach algorithms

Animated demonstration to present concept in a lecture for student to explore on her own to compare several algorithms and their properties

Timing analysis programs to conduct experiments to learn about algorithm complexity to learn to design and evaluate experiments

Using technology to teach algorithms:sorting

Insertion sort

Using technology to teach algorithms:sorting

Quicksort

Using technology to teach algorithms:binary trees

Expression tree:

Using technology to teach algorithms:binary trees

Heap (priority queue):

Using technology to teach algorithms:graph algorithms: breadth first search

Understand what are the key concepts you are trying to teach

#Make examples interesting and relevant Provide projects that focus on the concept #Use graphics and illustrations to model the

concept Present patterns in design and programs Support collaboration and interaction #Set the stage for further exploration

#Understand what are the key concepts you are trying to teach

many input prompts and input statements make code messy• solution: filtered input:

– X = RequestInt(“Next number:”, 0);

when animating algorithms, make sure focus is on algorithm

Provide projects that focus on the concept design the solution first:

• make students work on key parts• supply the framework

make your code a model of good practice

Present patterns in design and programs programming patterns:

loop design patterns decision patterns

algorithmic patterns do for all and collect cumulative result greedy method - do the easiest case first divide and conquer

Present patterns in design and programs design and object patterns:

scaling change in the frame of reference objects that represent a state function objects that generate values migrating objects that belong to several collections over

time collection objects

• of other objects• of references to objects

traversal objects (iterators)

Present patterns in design and programs

Hospital Emergency Room Simulation patient arrival: random number, severity code,

treatment time discrete probability distribution function object generates next value for a given probability

waiting room: priority queue beds: available versus in-use

design choices how to handle the free list patient object: migrating object = referenced statistics:

where is data collected, design of the experiments meaning and validity of results

Support collaboration and interaction group work exploration of animations hands-on illustrations “food for thought” questions

Support interaction

Towers of Hanoi: hand simulate to deduce the pattern estimate and verify the expected number of moves when will the world end - exponential growth (rice)

Support interaction

Binary cards:

1 0 1 1 0 = 21

Support interaction

Binary story: I was born in year 110 1100 1010 in Bonn I became a professional musician at the age of 1011 I lived in Vienna since 111 0000 0010 I wrote my first symphony in 111 0000 1000 The third symphonyEroica was written in 111 0000 1100 I died in 111 0010 0011 My name is: ???????

Support interaction

Binary clock:

The network game

Compare your address 1 0 0 1with address on the message 1 1 0 1

Mark with X all places wherethe addresses are the same, X X

and copy the address of the message into the other places X 1 0 X

The network game

Select a color for one of the positions that do not have X

Mark the selected position with X and send the message along the wire of that color

For example, for the message address X 1 0 X

select the second position mark the new address as X X 0 X and send along the wire of the

second color.

The network game

If you receive a message, select next color

and send it.

Messages with addresses X X X X are for you.

Read them and reply to the sender.

Which concepts did we cover:

Foundational Concepts (NRC report) computers: program, interpretation, CPU, memory, I/O information systems: hardware, software, interfaces, people… networks: physical structure, protocols, bandwidth, standards digital representation of information: text, images, sound,

video modeling and abstraction: validity, limitations, how it works algorithmic thinking and programming universality: every computer works the same way!!! limitations: growth rate, tractability, decidability, accuracy societal impact of information and information technology

Which capabilities did we cover:

Intellectual Capabilities (NRC report) engage in sustained reasoning manage complexity test a solution manage problems in faulty solutions organize and navigate information structures and

evaluate information collaborate; communicate to other audiences expect the unexpected anticipate changing technologies think about information technology abstractly

Conclusion

Computer science provides foundation for abstract thinking and reasoning

The key ideas help understand the technology and adapt to the change

The key didactical principles: experiential learning

Use technology, engage students without technology

Explore the breadth of computer science applications

Acknowledgements

Collaborators: Richard Rasala and Harriet Fell Support form the NSF Foundation

DUE ILI-LLD 9650552

Support from MicroSoft Corporation Inspiration and suggestions: Erich Neuwirth and my family…

http://www2.nas.edu/cstbweb/ http://www.acm.org/education/hscur/ http://www.ccs.neu.edu/home/vkp/

What are the didactical principles for teaching computer science

computer science programs

computer scienceprograms

informationusing computer

conceptuse graphics

information structures

key ideaswhat

word processor

sustained reasoningmanage

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