Developing Problem Solving Behaviours,

Attitudes and DispositionsBy Mark Dorling

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“A high-quality computing education equips pupils to use computational thinking and creativity to

understand and change the world. Computing has deep links with mathematics, science and design and technology, and provides insight into both natural and

artificial systems.”Document Source

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Concepts

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Abstraction

Algorithmic Thinking

DecompositionGeneralisation

Evaluation

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Concepts (Practices)

Learning behaviours (Practices)“Hiding

functional complexity”

“Identifying commonality”

“Making trade-offs between competing

requirements”

“Making judgments about effectiveness (When is

good enough good enough?)”

“Organising data into structures for

processing”

“Moving solutions or parts of solutions to different problems”

“Identifying information necessary for a solution”

“Expressing logic in a standard notation”

“Sequencing, iteration and

selection”

“Breaking down problems into sub-

problems”

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Interpreted Curriculum(Concepts and key constructs)

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Linking: (Concepts) + (Practices)

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AL for AlgorithmDE for DecompositionGE for Generalisation and patternsAB for Abstraction and representation

EV for Evaluation

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Mark Dorling & Matthew Walker (2014)

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Mixture of skills and behaviors

(Practices)

Primary Secondary

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Good teaching and learning

“children’s enjoyment of learning, includingtheir participation and willingness to makechoices and decisions, and the extent towhich children are active and inquisitivelearners who are creative and thinkcritically”.

Ofsted Inspection handbook page 60 (paragraph 191)

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Focus of lesson observation

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CAS QuickStart Computing (2015)

Reflective practice

• What was your pedagogical choice?• My decision was…

• What was the impact on the behaviour of learners?• How do I know and what am I looking for…

• What is the evidence of this behavior by learners?• I know this because…

• What would I try differently next time and is my next step?• My next step will be…

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Choice of pedagogy

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Social Constructivism: Groups construct knowledge for one another, collaboratively creating a smaller culture of shared artifacts with shared meaning.

Constructivism: The learner is not a passive recipient of knowledge but that knowledge is ‘constructed’ by the learner.

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Constructionism: The idea that learners’ learn best through building things that are tangible and sharable with the public

Supporting constructivist & constructionist pedagogy

• Using examples that are relevant to students’ own experiences e.g. relating to real-world experiences

• Active learning experiences e.g. unplugged, kinesthetic activities

• Learning by exploration e.g. exploring programming environments and open-ended tasks

• Learning by solving problems e.g. self-directed projects and problem-solving

• Open-ended discussion and working in groups e.g. paired and group problem-solving.

(Sentence and Csizmadia 2015)

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Social constructivist: Paired programming

• Software developers generally spend:•30% of their time working alone•50% of their time working with one other person•20% of their time working with two or more people

(DeMarco and Lister, 1987)

Three forms of peer-based interaction in the classroom: 1. Tutoring, where the less capable are guided by the more capable; 2. Co-operation, where learners work on different parts of the task; 3. Collaboration, where learners work jointly on almost all parts of the

task. Jehng (1997)

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Observing and assessing CT

How we teach CT

How CT is developed in learners’ minds

How CT is demonstrated by learners’

Behaviorism: Learning is accomplished when a proper response isdemonstrated following the presentation of a specific environmental stimulus.

Cognitivism: Learning is concerned not so much with what learners do but withwhat they know and how they come to acquire it. Knowledge acquisition isdescribed as a mental activity that entails internal coding and structuring by thelearner. The learner is viewed as a very active participant in the learningprocess.

Constructivism: Constructionism:

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One approach…

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Check out…CAS Quantum

Assessing Artifacts

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Mark Dorling (2015)

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Why

The definitionThe challenge at the start of the unit i.e. the problem to solve. The philosophical discussion i.e. asking questions

Problem solving skills Computational thinking behaviours

(practices) to solve the problem

Functional skills Essential skills e.g. coding

EvidenceCreation of artifact by learners

ConceptsInterpretation of the curriculum

(concepts and key constructs)What

How

Mark Dorling (2016)

How do I assess learners’ attainment in Programming?

• Does the program run?

• Is the program formatted and readable?

• Is the program commented for understandability?

• Is the program extensible and portable?

• Is the product good?

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Which is right… which is better…

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Assessing computational thinking

Approaches:

• Project portfolio analysis

• Artifact-Based Interviews

• Design scenarios

Suggestions:

• Supporting further learning

• Incorporating artifacts

• Illuminating processes

• Checking in at multiple waypoints

• Valuing multiple ways of knowing

• Including multiple viewpoints

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Brennan & Resnick 2012

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Dispositions (Perspectives)

Attitudes and dispositions• Confidence in dealing with

complexity• Persistence in working with

difficult problems• Tolerance for ambiguity• The ability to deal with open

ended problems• The ability to communicate

and work with others to achieve a common goal or solution

Identity and Motivation

• Personal interest in coding

• Willingness to engage further

• Positive perception of coding

• Confidence in coding

• Digital empowerment

• Computational identity

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Document Source

Brennan & Resnick 2012 CSTA (2011)

Dispositions + Perspectives

• Used as a self, peer and teacher tool. • Inspiration taken (and further developed) from CTSA Operational definition of

Computational Thinking for K12 Education (2011) and Brennan and Resnick(2012)

Mark Dorling and Tom Stephens (2016)

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What we learnt…

Passive verbs = internal & unobservable behaviours

Understand Be aware of…

Appreciate Be concious of…

Comprehend Learn

Grasp Perceieve

Know Value

See Get

Accept Apprehend

Have knowledge of… Be familiar with…

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Using the problem solving rubric

Phil Bagge

Computing Inspector/Advisor Hampshire

CAS Master Teacher

Code-it.co.uk Author

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Worked with Mark Dorling & others to develop & refine problem solving rubric

@baggiepr

Computing Problem Solver

Copes with Complexity

Open EndedProblem Solver

Handles Ambiguity

AdaptsInvestigates

Perseveres

Communicates

Evaluates

@baggiepr

Copes with Complexity

Open Ended Problem Solver

Handles Ambiguity

Adapts

Investigates

Perseveres

Communicates

Evaluates

I can break complex problems into parts

I recognise there is more than one way to solve/describe a problem

I look for a range of solution to the same problem

I can identify patterns in problems & solutions

I can develop, test and debug until a product is refined

I can design criteria to evaluate my creations

I can encourage others to share their ideas

I look for how a project can be extended

I lead using all the people talent in my group

I repeatedly experiment through predicting, making, testing & debugging

I can persevere even if the solution is not obvious

I don’t just accept the first solution

I can evaluate my solutions against a set criteria

I can contribute useful ideas to a partner or group

I learn from setbacks and don’t let them put me off

I can adapt existing ideas to solve new problems

I can discover / concentrate on the most important part of a problem

I make predictions about what will happen

Computing Problem Solver

@baggiepr

Where are we using this?

• Shared with primary computing support groups in Hampshire• Very positive response

• One school adopting for use across school

• Many using in computing

• Shared with KS3 Assessment group in Hampshire• Adapting a version of this to be used in KS3 assessment

• Own classroom practice

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Prompts & Stickers

http://code-it.co.uk/attitudes/

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We don’t make pupils persevere just by telling them to be resilient we need a catalyst, a game changer. Computing

science provides this with emphasis on debugging

I can persevere even if the solution is not obvious

I learn from setbacks and don’t let them put me off

Perseveres

@baggiepr

Perseveres • Combatting historic resilience problems in ICT

• Promoting debugging

• Combatting learnt helplessness

• Ok to make bugs

• Stopping solving things for pupils

Learned Helplessness http://code-it.co.uk/articles

I can persevere even if the solution is not

obvious

I learn from setbacks and don’t let them put

me off

@baggiepr

CommunicatesI can encourage others to share

their ideas

I lead using all the people talent in my

group

I can contribute useful ideas to a partner or group

Communication & collaboration are really important for solving problems

We have to nurture these in our classrooms

@baggiepr

CommunicatesPupils

• Nominate your class mate for a sticker

Teacher

• Looking out for weak pairings where one pupil is the passenger

I can encourage others to share their ideas

I lead using all the people talent in my group

I can contribute useful ideas to a partner or group

Stickers http://code-it.co.uk/attitudes/@baggiepr

Open Ended Problem Solver

I look for a range of solution to the same problem

I look for how a project can be extended

I don’t just accept the first solution

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Open Ended Problem Solver

• More able who find a quick solution challenged to find more ways to solve the problem

• One opportunity in a lesson to find more than one way to solve something for everyone

• Project cut off so all pupils can look at how they might extend it

I look for a range of solution to the same problem

I look for how a project can be extended

I don’t just accept the first solution

Different ways to leave a colour trail in the slug trail game

@baggiepr

Copes with Complexity

I can break complex problems into parts

I can discover / concentrate on the most important part of a problem

@baggiepr

Copes with Complexity

I can break complex problems into parts

Year 3 pupils breaking a stone age scene down into parts before creating a stop motion animation

@baggiepr

Copes with Complexity

I can break complex problems into parts

Classic programming decomposition, breaking a project into parts to solve it separately

http://code-it.co.uk/scratch/tablesgame/tablesgameoverview@baggiepr

Copes with Complexity

Put a 1, 2 & 3 by the jobs you think need to be done first

I can discover / concentrate on the most important part

of a problem

http://code-it.co.uk/carpet@baggiepr

Evaluates

I can design criteria to evaluate my creations

I can evaluate my solutions against a set criteria

@baggiepr

Evaluates• Involving pupils in designing evaluations

‘What does a good one of those look like?’ (Wagoll)

• Peer evaluation, valuing constructive criticism

• Right to reply

‘I agree with your point I will try to change it by…’

‘I don’t agree with your point because….’

• Evaluating during project so that pupils can act on it not at the end I can design criteria to

evaluate my creations

I can evaluate my solutions against a set criteria

@baggiepr

Adapts

AdaptsI can identify

patterns in problems & solutions

I can adapt existing ideas to solve new

problems

My pupils know that if they can suggest a good project that demonstrates using an existing idea to solve a new

problem I will often find time for them to make it

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Adapts

I can identify patterns in problems &

solutions

http://code-it.co.uk/scratch/clock/clockoverview@baggiepr

AdaptsI can adapt existing ideas

to solve new problems

http://code-it.co.uk/scratch/actionassess/actionoverview

These are some of the blocks we have used in Y3 this year

What could you use them to make?

Later here is a more complex idea can you retro fit this into an earlier project

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Investigates

I can develop, test and debug until a product is refined

I repeatedly experiment through predicting, making,

testing & debugging

I make predictions about what will

happen

@baggiepr

Investigates I make predictions about what will happen

http://code-it.co.uk/bracelet/

Write or draw what shape you think this code will create

@baggiepr

Assessing problem solving

B

B

A

A

B A

http://code-it.co.uk/attitudes/@baggiepr

Copes with Complexity

Open EndedProblem Solver

Handles Ambiguity

AdaptsInvestigates

Perseveres

Communicates

Evaluates

Resourceshttp://code-it.co.uk/attitudes/Adapt Practice in Computing?OrHelping pupils to become independent problem solving learners in all subjects

Thanks for listeningAny questions?

‘How to teach primary programming using Scratch’

http://goo.gl/W4bQ1a

References for Part 1By Mark Dorling

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References

• BBC Bitesized (2016), Computational Thinking: http://www.bbc.co.uk/education/topics/z7tp34j

• Barr, V. & Stephenson, C. (2011), Bringing Computational Thinking to K12: http://www.amanyadav.org/CEP991A/wp-content/uploads/2014/08/Barr_Stephenson_2011.pdf

• Bhattacharya, N., (2016), Tinkering (an introduction): https://vimeo.com/182482442

• Brennan, K., & Resnick, M. (2012), New frameworks for studying and assessing the development of computational thinking: http://web.media.mit.edu/~kbrennan/files/Brennan_Resnick_AERA2012_CT.pdf

• Computing At School (2014), CAS Barefoot Computational Thinking: http://barefootcas.org.uk/barefoot-primary-computing-resources/concepts/computational-thinking/

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References

• CoolThink@JB (2016), Our approach to Computational Thinking: http://coolthink.hk/en/ct/

• Csizmadia, A., Cuzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C. and Woollard, J. (2015), Computational thinking: A guide for teachers: https://community.computingatschool.org.uk/resources/2324

• Computing At School (2015), Lesson observation form with prompts: http://www.quickstartcomputing.org/secondary/section4.html

• CSTA (2011), Operational definition of Computational Thinking for K12 Education: https://csta.acm.org/Curriculum/sub/CurrFiles/CompThinkingFlyer.pdf

• CSTA Voice (2016), Irene Lee: Reclaiming the Roots of CT, Page 4: https://csta.acm.org/Communications/sub/CSTAVoice_Files/csta_voice_03_2016.pdf

• Department for Education (2014), Computing Programmes of Study: https://www.gov.uk/government/publications/national-curriculum-in-england-computing-programmes-of-study

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References

• DeMarco, T., and Lister, T. (1987). Peopleware, New York: Dorset House Publishers.

• Dorling, M. & Stephens, S. (2016), Problem solving and Computational Thhining rubric: http://community.computingatschool.org.uk/resources/4793

• Dorling, M. & Walker, M. (2014), Computing At School Progression Pathways: https://community.computingatschool.org.uk/resources/1692

• Fuller et. Al. (2007), Developing a computer science-specific learning taxonomy: http://dl.acm.org/citation.cfm?id=1345438

• Google (2016), Computational Thinking for Educators: https://computationalthinkingcourse.withgoogle.com/unit

• Google (2016), Computational Thinking from a Dispositions Perspective: http://googleforeducation.blogspot.co.uk/2016/09/Computational-Thinking.html?m=1

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References

• Google (2016), Exploring Computational Thinking: https://www.google.com/edu/resources/programs/exploring-computational-thinking/index.html#!ct-overview

• Jehng, J. c. J. (1997). The psycho-social processes and cognitive effects of peer-based collaborative interactions with computers. Journal of Educational Computing Research, 17, 19-46.

• Lister, R. (2011). Concrete and other neo-piagetian forms of reasoning in the novice programmer

• Lister, R., Adams, E. S., Fitzgerald, S., Fone, W., Hamer, J., Lindholm, M., . . . Thomas, L. (2004). A multi-national study of reading and tracing skills in novice programmers.

• McCracken, M., Almstrum, V., Diaz, D., Guzdial, M., Hagen, D., Kolikant, Y., Laxer, C., Thomas, L., Utting, I., and Wilusz, T. (2001) A Multi-National, Multi-Institutional Study of Assessment of Programming Skills of First-year CS Students. SIGCSE Bull., 33(4). pp 125-140.

• Lopez, M., Whalley, J., Robbins, P., & Lister, R. (2008). Relationships between reading, tracing and writing skills in introductory programming.

• Potter. M, and Kustra (2012), A primer on learning outcomes and the SOLO Taxonmy: http://www1.uwindsor.ca/ctl/system/files/PRIMER-on-Learning-Outcomes.pdf

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References

• Michaelson, G., 2015. Teaching Programming with Computational and Informational Thinking.

• Roth, W.-M. (1993). Construction sites: Science labs and classrooms. In K. Tobin (Ed.), The practice of constructivism in science education, (pp. 145-170). Hillsdale, NJ: Erlbaum.

• Sentence, S. and Csizmadia, A., (2015). Teachers’ perspectives on successful strategies for teaching Computing in school

• STEM Learning, Computational Thinking: https://www.stem.org.uk/elibrary/resource/35192

• Van Gorp, M. J., and Grissom, S. (2001). An empirical evaluation of using constructive classroom activities to teach introductory programming.

• A focus on writing learning outcomes: https://afocusonlearningoutcomes.wordpress.com/resources/extras/

• L. Williams, E. Wiebe, K. Yang, M. Ferzli, and C. Miller, “In Support of Pair Programming in the Introductory Computer Science Course,” Computer Science Education, vol. 12, pp. 197-212, 2002.

• Wing, J. M. (2006). Computational thinking.

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