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Computing Education Research Computer Science Education Research Conference (CSERC ‘11) 7 th April 2011, Heelen, The Netherlands Sally Fincher

Computing Education Research

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Computer Science Education Research Conference (CSERC ‘11) 7 th April 2011, Heelen, The Netherlands Sally Fincher. Computing Education Research. About me. I run the Computing Education Research Group in the Computing Laboratory at the University of Kent (have done since 1997) - PowerPoint PPT Presentation

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Page 1: Computing Education Research

Computing Education Research

Computer Science Education Research Conference (CSERC ‘11) 7th April 2011, Heelen, The Netherlands

Sally Fincher

Page 2: Computing Education Research

About me

• I run the Computing Education Research Group in the Computing Laboratory at the University of Kent (have done since 1997) So know about trying to do disciplinary-specific education

research

• I edit the Journal Computer Science Education So have seen what others think are appropriate outputs of

disciplinary-specific education reearch

• I was Secretary of ACM Special Interest Group on Computer Science Education (SIGCSE) for 6 years So have some sense of the scale of the interest in this

area

Page 3: Computing Education Research

Bootstrapping & friends

• From 2002/3 I devised (together with Marian Petre from the Open University and Josh Tenenberg from the University of Washington, Tacoma) a series of workshops, aimed at helping people find a “way in” to CS Education research.

Page 4: Computing Education Research

Bootstrapping & friends

• We collected some of that material into a book

• I’ll revisit some of that today

Page 5: Computing Education Research

Topics and Areas

• One of the ways we sliced things in 2004 was by topic, by what people were interested in researching. We listed 10 areas then: Student Understanding Animation, visualization & simulation Teaching methods Assessment Educational technology Transferring professional practice to the classroom Incorporating new developments & technologies Transferring from f2f to distance education Recruitment and retention (incl. diversity & gender) Construction of the discipline

Page 6: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Developing a Computer Science Curriculum in the South African Context

Page 7: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

A Lab-based Approach for Introductory Computing that

Emphasizes Collaboration

Page 8: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Plagiarism detection for Java: a tool comparison

Page 9: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Peer Production & Peer Support at the Free

Technology Academy

Page 10: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Student discussion forums: What is in it for

them?

Page 11: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Sciences, Computing, Informatics: who is the

keeper of the Real Faith?

Page 12: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Game Based Learning for Computer Science

Education

Page 13: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

A Distributed Virtual Computer Security Lab with Central Authority

Page 14: Computing Education Research

Topics and Areas

• Student Understanding

• Animation, visualization & simulation

• Teaching methods

• Assessment

• Educational technology

• Transferring professional practice to the classroom

• Incorporating new developments & technologies

• Transferring from f2f to distance education

• Recruitment and retention (incl. diversity & gender)

• Construction of the discipline

Some challenges for Computer Science

Education in a Knowledge Society

Page 15: Computing Education Research

Topics and Areas

• Today, these don’t seem to be wrong.

• They’re still areas that motivate people to work in the area. The still give a response to the question “Why are you interested in Computing Education Research?”

• But they are not a complete answer.

• They don’t speak to what people want as a result of a piece of Computing Education Research

• And they don’t begin to address the “How do you do Computing Education Research?” question

Page 16: Computing Education Research

CSEd Research: Three lenses

• Discipline

• Classroom

• Community

Page 17: Computing Education Research

CSEd Research: Three lenses

• Discipline

• Classroom

• Community

Page 18: Computing Education Research

Discipline

• The methods of CS education research are not the methods of CS.

• You cannot study classrooms, people and their interactions with algorithms and proofs.

• As CSEd researchers, we have to use other methods – other epistemologies, “ways of knowing” I from other disciplines Education ... Sociology ... Psychology ... Anthropology ...

Can be methodologically isolating

Page 19: Computing Education Research

Cognitive Psychological tradition

• Many early CS Ed investigations (1980’s) were from the psychological tradition – conducted by psychologists for the most part.

• Programming was a new and interesting way to investigate how people think, and was conducive to laboratory-based investigation.

• There was a very influential series of meetings/publications Empirical Studies of Programmers

Page 20: Computing Education Research

Cognitive Psychological: what people want

• The sort of positivist, quantitative knowledge that cognitive psychology creates is very attractive – and persistently so.

• PPIG posting, 20th March 2011

• To clarify my test … I'm going to compare miniC (a minimal C implementation built on BYOB) vs regular C environments. I want to test if students that learned C by using miniC:

- do less syntactic mistakes- remember to declare their variables more often- use sequence/loop/conditionals in a more consistent way

Page 21: Computing Education Research

PPIG mailing list: 20th March 2011

• What I'm not sure is if they are using the correct instruments to get correct, unbiased data from their tests. …

• After all, from these tests they should claim that their work is successful. Are they doing it in the right way? Shouldn't we have a common, clearly-understood test-bed on which this kind of experimentation should be performed? This doesn't mean that the test-bed should be unupdateable, but at least important part of it should. Otherwise our tests wouldn't be comparable as they should.

Page 22: Computing Education Research

PPIG mailing list: 20th March 2011

• What I'm not sure is if they are using the correct instruments to get correct, unbiased data from their tests. …

• After all, from these tests they should claim that their work is successful. Are they doing it in the right way? Shouldn't we have a common, clearly-understood test-bed on which this kind of experimentation should be performed? This doesn't mean that the test-bed should be unupdateable, but at least important part of it should. Otherwise our tests wouldn't be comparable as they should.

Page 23: Computing Education Research

PPIG mailing list: 20th March 2011

• What I'm not sure is if they are using the correct instruments to get correct, unbiased data from their tests. …

• After all, from these tests they should claim that their work is successful. Are they doing it in the right way? Shouldn't we have a common, clearly-understood test-bed on which this kind of experimentation should be performed? This doesn't mean that the test-bed should be unupdateable, but at least important part of it should. Otherwise our tests wouldn't be comparable as they should.

Page 24: Computing Education Research

PPIG mailing list: 20th March 2011

• What I'm not sure is if they are using the correct instruments to get correct, unbiased data from their tests. …

• After all, from these tests they should claim that their work is successful. Are they doing it in the right way? Shouldn't we have a common, clearly-understood test-bed on which this kind of experimentation should be performed? This doesn't mean that the test-bed should be unupdateable, but at least important part of it should. Otherwise our tests wouldn't be comparable as they should.

Page 25: Computing Education Research

Epistemology

• We can see in this plea the assumptions – and expectations – of the experimental sciences. A fixed natural world, with knowable data The notion of predictive theory The expectation that my classroom, my students and their

abilities are in some sense the same as yours, are directly comparable with yours.

Page 26: Computing Education Research

Cognitive Psychological, today

• Developing a validated assessment of fundamental CS1 concepts. Proceedings of the 41st SIGCSE Technical Symposium on Computer Science Education, (Milwaukee, WI), 97-101, 2010

• The FCS1: A Language Independent Assessment of CS1 Knowledge. Proceedings of the 42nd SIGCSE Technical Symposium on Computer Science Education, (Dallas, TX), 2011

• Allison Elliot Tew & Mark Guzdial

Page 27: Computing Education Research

Other questions, other needs

• I was trying to understand real learning in real classrooms, but I was using the conventional pencil-and-paper things and massaging the data with multivariate statistics. Collecting the data directly from students ... and then trying to make sense of it just led me into a huge shift in my thinking

• I went away and started to think about it – opening up the whole business of how experience is interpreted. I don’t think before that I’d thought much about how people construct their own meaning for experiences and events

(quotes reported in Fencham, p. 42 & 45)

Page 28: Computing Education Research

Sociological tradition

• Sociology asks different questions, and uses different methods to answer them. It is (usually) more group-based than psychological investigations, and more interested in the nature of processes. Its theories (characteristic of the social sciences) are explanatory rather than predictive. Key sociological questions are: What role does education play in the life chances of

different groups? How can we best explain why some groups systematically

win and others lose? Is education a means of liberating individuals or is a

means of social control?

Page 29: Computing Education Research

Sociological tradition

• Lecia Jane Barker, Kathy Garvin-Doxas & Michele Jackson

• Defensive Climate in the Computer Science Classroom Proceedings of the 33rd SIGCSE technical symposium on Computer science education (Covington, KY), 43-47, 2002

• A learning environment comprises “all of the physical surroundings, psychosocial or emotional conditions and social or cultural influences” present in a learning situation.

• Over the course of an academic year they “ethnographically” observed 10 courses for a total of 254 hours.

Page 30: Computing Education Research

Sociological tradition (ii)

• Categories emerging from data analysis included 1) impersonal environment and guarded behaviour; and 2) the creation and maintenance of informal heirarchy resulting in competetive behaviours. These communication patterns lead to a defensive climate characterised by competitiiveness rather than cooperation, judgments about others, superiority and neutrality rather than empathy.

Page 31: Computing Education Research

Educational tradition

• Although “education” as a field is itself is a hybrid disciplinary influence and method.

• The Case for Case Studies Communications of the ACM (CACM) Volume 35 Issue 3, March 1992

• Marcia Linn & Michael Clancy

Page 32: Computing Education Research

Educational tradition

• Another way of working – teaming up.

• “Marcia Linn showed up at my door ... she said, we want to research people learning to program and we've heard you teach a lot of those.”

Page 33: Computing Education Research

Teaming up

• “There was a vast set of things I got from this. I was a clueless teacher, trying things as a whim and flying by the seat of my pants. What I got from Marcia is that she could see the big picture and say “Oh yeah—what you're doing is—and here's how it is in math, physics and chemistry” ... then I could see how what they were doing in other disciplines related to what I was trying.”

Page 34: Computing Education Research

Tested

• Mixed methods – “balanced groups” (some with case studies, some without), small-scale observations, statistical conclusions.

• “I still think that—I have not found a better way to address complex concepts but to use a case study to make concepts concrete”

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Computer Science

• Compared to other areas of disciplinary-specific education research, we—uniquely—have additional disciplinary influences ...

• ... but they’re not academic influences

• They come from the practice of the discipline.

• And they come in two ways ...

• Industrial practice (e.g. pair programming)

• Practice of our craft (e.g. tool building – Alice, Greenfoot, Scratch)

Page 36: Computing Education Research

Discipline

• Partly a matter of temperament—what methods and approaches are you comfortable with?

• Partly a matter of epistemology—what questions do you want to ask and what evidence will satisfy you that they’ve been answered?

Computing Education

PsychologyAnthropologyStatistics

Page 37: Computing Education Research

CSEd Research: Three lenses

• Discipline

• Classroom

• Community

Page 38: Computing Education Research

CSEd Research: Three lenses

• Discipline

• Classroom

• Community

Page 39: Computing Education Research

Classroom

• Most CS Education researchers are not motivated by generalised results – at least not at first.

• Most are motivated to understand what happens in their classroom, how to describe the learning that takes place there and what to do to change/improve it.

There are some obvious problems with this

Page 40: Computing Education Research

Fincher (2001): A Fictitious Paper

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1 8 16 24 32 40 48 56 64 72 80 88 96

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• A single author, presenting results for a single institution.

A Study of Assessment of Programming Skills of First-Year CS Students

Sally FincherUniversity of Kent

UK

Page 41: Computing Education Research

Fincher (2001): A Fictitious Paper

• Explanations?

1. Sally can’t teach.

2. The students are British.

3. Sally teaches at an atypically poor institution

4. If Sally changed:a) From Pascal to C to C++ to Java to Pythonb) Objects early ← → Procedural c) Used closed labs ← → Used open labsd) More assignments ← → Less assignments

• < insert your favourite deck chair permutation for the “C.S. Titanic” >

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0

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McCracken, et al. (2001)

10 authors; data collected at 4 universities in 2 countries:

• They all can’t teach?

• They can’t all be British!

• They are all atypically poor institutions?

Fincher (2001): A Fictitious Paper

Page 43: Computing Education Research

• ITiCSE (Innovation and Technology in Computer Science Education).

• ACM SIGCSE European conference.

• 16th year (27-29 June, Darmstadt)

• Has associated “working groups”

The “ITiCSE Working Group Model”: i

Page 44: Computing Education Research

a) topics are proposed, and peer-reviewed

b) one or more topics are selected for presentation

c) the topic is posted with an invitation for others to join in the work specified

d) the resulting group(s) work electronically before the conference, then work at the conference (and often for a day or more in advance)

e) the group(s) write a paper detailing their results. This is peer-reviewed and, if accepted, published in the SIGCSE Bulletin

f) the group disbands

The “ITiCSE Working Group Model”: ii

Page 45: Computing Education Research

Usually these groups produce a report that:

• Distils collected resources and experiences on an issue of direct relevance to practicing teachers. For example Resources, Tools, and Techniques for

Problem Based Learning in Computing, 1998 & A Road Map for Teaching Introductory Programming Using LEGO Mindstorms Robots, 2003

• Addresses common problems that benefit from the application of collective intellectual and analytical effort. For example: How shall we assess this?, 2004 &

Evaluation: turning technology from toy to tool 1996

The “ITiCSE Working Group Model”: iii

Page 46: Computing Education Research

• McCracken (2001) was the first to adapt this to an empirical study

• Subsequently replicated, notably:

• 2004: The “Leeds Group” A study of novice program comprehension Data from 12 universities in 6 countries

The “ITiCSE Working Group Model”: iv

Page 47: Computing Education Research

• Lightweight

• (Relatively) modest commitment of time/effort

The “ITiCSE Working Group Model”: v

Page 48: Computing Education Research

“Bootstrapping” model

• Series of interventions to give practitioners a “way in” to CS Education research

Page 49: Computing Education Research

Year One Year Two

Four day workshop

“Input” – methods, presentations

Work on their own studies

Introduce the Experiment Kit

Intervening

Execution of the Experiment Kit

Four day workshop

Analyse data in aggregate. Write paper

Work on their own studies

The Bootstrapping Model

Page 50: Computing Education Research

Experiment Kit Structure (Bootstrapping)

1. Question formulation

2. Protocol

a. Data collection specification

b. Human Subjects materials

c. Background questionnaire

d. Discriminator question

e. Specification of set-up

f. Experimenters script (including guidance on notes/diagramming)

g. Participant design brief

h. Design criteria elicitation Stimuli set

i. Design criteria elicitation Recording Sheet

3. Analysis protocol

4. Background

5. Literature

Page 51: Computing Education Research

Compared

The “ITiCSE Working Group Model”

• Lightweight

• (Relatively) modest commitment of time/effort

• Effectively free

The “Bootstrapping” Model

• Heavyweight commitment on organisers (writing & piloting Experiment Kit)

• Two-year commitment for participants

• Requires funding

Payback A (modest) paper publication

The “Bootstrapping” Model

Many publications (31 to date)Spin-off studiesOngoing community

Much more detail about this in Fincher & Tenenberg, JEE 2006

Page 52: Computing Education Research

From: Fincher et al. ICER 2005

Page 53: Computing Education Research

Classroom

• Authentic, situated, embodied.

• Need to overcome – or celebrate – limitations of single class: size, sample, generalisation, validity

Page 54: Computing Education Research

CSEd Research: Three lenses

• Discipline

• Classroom

• Community

Page 55: Computing Education Research

CSEd Research: Three lenses

• Discipline

• Classroom

• Community

Page 56: Computing Education Research

Community

• There is no such thing as private research. Indeed, the concept makes little sense.

• For there to be ongoing research there has to be: people doing work places for people to publish their work people reading that work, and building on it (other) people using that work places for people to meet other researchers

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Peter Fensham

• There are issues with CS Education Research as an activity, as I’ve explored.

• There are also issues with CS Education Research as a research area.

• Peter Fensham undertook an interesting piece of work in 2004. He looked at the construction of “Science Education” (in regard to Secondary Schools) as a distinctive field of research.

• He defined three sets of criteria that would have to be populated to be able to claim that a research area was distinctively separate.

Page 58: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria

Page 59: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria

Page 60: Computing Education Research

Research criteria

• Scientific knowledge

• Asking questions

• Conceptual & theoretical development

• Research methodologies

• Progression

• Model publications

• Seminal publications

Page 61: Computing Education Research

Research criteria

• Scientific knowledge Knowledge required to conduct the research

• Asking questions Asking distinctive questions not addressed by other fields

• Conceptual & theoretical development Theoretical models with predictive or explanatory power

• Research methodologies Invention, development or adaptation

• Progression Researchers informed by, and build upon, previous studies

• Model publications Held up as models of conduct & presentation in this field

• Seminal publications Recognised as important or definitive studies; new directions

or new insights

Page 62: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria

Page 63: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria

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Outcome criteria

• Implications for practice Outcomes from research that are applicable to the practice

of [computer] science education

Page 65: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria

Page 66: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria

Page 67: Computing Education Research

Peter Fensham’s criteria

• Research criteria

• Outcome criteria

• Structural criteria Professional Associations Research Conferences Research Journals Academic Recognition

Page 68: Computing Education Research

Professional Associations

• For Computer Science Education Research, there really are none explicitly. But it does occur as part of other activities:

• SIGCSE

• SEFI

Healthy national and international professional associations

Page 69: Computing Education Research

Research Conferences

• SIGCSE: Symposium

• ITiCSE: Innovation and Technology in Computer Science Education

• FiE: Frontiers in Education

Regular conferences for the direct exchange of research that enable researchers to meet in person

• These are practitioner, not research, conferences.

• Nevertheless some research studies are reported in them.

• Characterised by small-scale investigations on a single aspect (of discipline or practice).

• Most often reflect a single classroom.

• Frequently take an individual “action research” approach.

• Reflect their practitioner focus.

Page 70: Computing Education Research

Research Conferences

• PPIG: Psychology of Programming Interest Group • 24 years

• Mostly UK

• ASEE: American Society of Engineering Education• Primarily Engineering Education, some CS element

Regular conferences for the direct exchange of research that enable researchers to meet in person

• Subject-area focussed

• Methodologically focussed

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Research Conferences

• Koli Calling 11th year. Mostly - but not exclusively - Scandinavian

• ICER workshop: International Computing Educational Research 7th year: International in name and International in scope 2011, 8th & 9th August Providence, Rhode Island 2012, Auckland, New Zealand 2013, San Diego, California 2014, Glasgow, Scotland

• Both Koli & ICER have associated Doctoral Consortia

Regular conferences for the direct exchange of research that enable researchers to meet in person

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Research Journals

Successful journals for reporting quality research

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Academic Recognition

• Well, there’s me ...

Full faculty appointments in the area of research

Page 74: Computing Education Research

Computing Education Research

• So what is there?

• A common object of attention – through whatever lens we choose to focus – on the teaching and learning of computing. Who it is for, how it is successful, why it works when it works and why it doesn’t work when it doesn’t.

• A recognition of a community of colleagues.

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Computing Education Research

• We have many (although not all) of the characteristics that Peter Fensham describes

• There is a community of researchers

• There is a body of work

• There is also much work to be done Curriculum gravity Interpretation for practice

• CSERC is happening at an exciting time

• Welcome!

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Acknowledgements

• Part of this material is based upon work supported by the National Science Foundation (NSF) under grants numbered DUE-0243242 and DUE-0122560. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

• The “McCracken” slides of this talk were adapted from those prepared by Raymond Lister for ICER 2005. Thanks, Raymond.

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References

• Peter J. Fensham The Evolution of Science Education as a Field of Research: Defining an Identity, 2004, Springer

• Sally Fincher & Marian Petre (eds) Computer Science Education Research, Routledge Falmer, 2004

• Sally Fincher, Raymond Lister, Tony Clear, Anthony Robins, Josh Tenenberg, Marian Petre Multi-Institutional, Multi-National Studies in CSEd Research: Some design considerations and trade-offs, 2005 ICER

• Sally Fincher & Josh Tenenberg Using theory to inform capacity-building: Bootstrapping communities of practice in computer science education research. Journal of Engineering Education, 95(4):265-278, October 2006

• Sally Fincher & Ian Utting (eds) Special Issue on Initial Learning Environments ACM Transactions on Computing Education (TOCE) Volume 10 Issue 4, November 2010

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References

• Raymond Lister, Elizabeth S. Adams, Sue Fitzgerald, William Fone, John Hamer, Morten Lindholm, Robert McCartney, Jan Erik Moström, Kate Sanders, Otto Seppälä, Beth Simon, Lynda Thomas, A multi-national study of reading and tracing skills in novice programmers. 2004 ITiCSE working group reports, ACM SIGCSE Bulletin pp. 119 - 150

• Michael McCracken, Vicki Almstrum, Danny Diaz, Mark Guzdial, Dianne Hagan, Yifat Ben-David Kolikant, Cary Laxer, Lynda Thomas, Ian Utting, Tadeusz Wilusz, A multi-national, multi-institutional study of assessment of programming skills of first-year CS students 2001 ITiCSE working group reports, ACM SIGCSE Bulletin pp. 125-180

• Project pages for the series of “Bootstrapping …” workshops can be found from: http://www.cs.kent.ac.uk/people/staff/saf/experiment-kits/index.html

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• This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.