Computer Science Teachers
as Amateurs, Students and
Researchers
Raymond Lister
University of Technology, Sydney, Australia
1
Teacher-centred knowledge
12
3
6
2
The Rise and Fall
of an Academic Discipline

Pre-Discipline



Boom-Discipline




Part of larger discipline(s)
E.g. Computer Science pre-1970s
Critical mass of undergraduates
Teacher-centred knowledge
Computing in the late 20th Century
Post-Discipline


Loss of undergraduates
E.g. English literature, physics 1980s,
… Computing in the 21st Century ?????
3
Doomed?
4
The formal study of
how novices come to
know a discipline is
central to the
sustained health
of a discipline.
5
Folk Medicine
See
file:///c:/talks/2005KoliCallingBBCNEWSMothersWereRightOverColdsKoliAttempt.htm
And …
Benjamin, H. (1936)
“Everybody’s Guide to Nature Cure”
6
Pedagogy
Folk Medicine
×
Bruner, 1996
“… intuitive theories about how other minds work …
… badly want some deconstructing if their
implications are to be appreciated".
7
Differing folk pedagogies cannot be resolved …
… and there is no progress.
8
Research vs. Teaching

Read literature, attend
seminars/conferences

Guided by direct
experience and
introspection
We lead a double life


Work within well
defined theoretical or
empirical framework

Guided by “folk
pedagogies”
Publish

Outcomes remain
private
9
&&
Research vs. Teaching
×



Read literature, attend
seminars/conferences
Work within well
defined theoretical or
empirical framework


Publish

Koli, ACE;
ACM’s ICER, SIGCSE,
& ITiCSE
E.g. constructivism,
Bloom’s taxonomy,
Kolb learning cycle
Publish! (see above)
10
Boyer (1990)
But what exactly
did he mean
by “scholar”
11
The Three Types of Academic Teacher
Practise
Theory
12
The Three Types of Academic Teacher
Practise
Theory
Amateur
• Guided by folk pedagogies
• Possibly an amateur in the finest sense of the
word.
• … but has little influence on colleagues.
13
The Three Types of Academic Teacher
Practise
Theory
Amateur
Education
Specialist
• May be a gifted teacher, or clumsy.
Implements education theory uncritically
• Possibly an amateur in the finest sense of
theVictim of theory wars?
word.
• Guided by folk pedagogies
Student
• Has little influence on colleagues.
14
The Three Types of Academic Teacher
Practise
Theory
Amateur
Student
Education
Specialist
Note:
NOT
uncritically
researcher Implements education
Teachertheory
as
as teacher
Researcher
Sees theory as either discipline-specific or
requiring discipline-specific validation.
15
Two dimensions
(and short term vs. long term)
Quality of engagement with students
low
low
Quality of
engagement
with
colleagues
high
high
amateur
researcher
16
Overview of this talk

Amateur, Student, Researcher


One example from my own work



Just finished that
Leeds Working Group …
 A logical break point
… followed by BRACElet
See my Koli paper for other examples
from my work
17
One Example from my Work:
Teaching the Novice (“CS1”)
18
McCracken, et al. (2001)

10 authors, 8 universities, 5 countries
19
McCracken, et al. (2001)
Number of Students
40
35
30
25
20
15
10
5
0
1
8
16
24
32
40
48
56
64
72
80
88
96
Scores



Remember, 8 universities, 5 countries …
... it says something about our discipline.
Amateurs! … don’t blame yourself!
20
But Why?
21
The Problem-Solving Gene
Conjecture
“You cannot teach problemsolving. It’s innate.”
The amateur feels no need to test
that conjecture (fact?).
The teacher-as-researcher asks
“What experiment will test that
conjecture?”
Answer: Eliminate problem-solving.
22
The Leeds Group (2004) 12 universities, 7 countries, >500 students
23
Twelve Multiple
Choice
Questions
24
Evidence against the problem-solving gene
Quartile
Scores
Top 25%
Second
Third
Bottom 25%
The Leeds Group, 2004.
10-12
12 universities,
8-9
7 countries,
over 500 students
5-7
0-4
Number of Students
40
Bottom 25%
of students
McCracken
et al., 2001
performing at a level
consistent with chance!
35
30
25
20
15
10
5
0
1
8
16
24
32
40
48
56
64
72
80
88
96
Scores
25
A logical break point in the talk
12
3
6
26
Overview of this talk, again
(break point)

Amateur, Student, Researcher

One example from my own work

Leeds Working Group …



Just finished that
… followed by BRACElet
See my Koli paper for other
examples from my work
27
Leeds Group as Research



Read literature, attend
seminars/conferences
Work within well
defined theoretical or
empirical framework
Publish




McCracken et al.,
2001 … and a host
of other papers
Empirical, yes.
Theoretical, no.
SIGCSE Bulletin,
December 2004.
28
Bracelet
×
Leeds Group as Research


Read literature, attend
seminars/conferences
Work within well
defined theoretical or
empirical framework



McCracken
et al.,
Leeds Group
2001
… and a host
SIGCSE
of other
papers
Bulletin,
2004.
Empirical, yes.
Theoretical, no.
×
SOLO taxonomy

Publish

SIGCSE
Whalley,Bulletin,
Lister,
December
2004.
et al., to appear,
ACE2006
29
BRACElet

A collaboration between four New Zealand
institutions and one Australian (me).




Jacqueline Whalley, Tony Clear, Phil Robbins
Errol Thompson
Ajith Kumar
Christine Prasad
30
BRACElet


Several multiple choice questions,
superficially like the Leeds Group
questions, plus …
One “explain in plain English”
question …
31
BRACElet
In plain English, explain what the following code does:
int iNumbers[iMAX]; // iMAX is a constant
… array initialization omitted in question to students…
bool bValid = true;
for (int i = 0; i < iMAX-1; i++) {
if (iNumbers[i] > iNumbers[i+1])
{
bValid = false;
}
}
32
SOLO Taxonomy (Biggs & Collis ’82 –
general theory, not programming)
•
•
•
“Prestructural” or “Unistructural”
• An incorrect understanding of the semantics
of the programming language.
“Multistructural”
• Line-by-line understanding, but no grasp of
what the code does as whole
• “failing to see the forest for the trees”
“Relational”
• A summary of the purpose of the code, for
example “it checks if the elements in the
array are sorted”
• The student “sees the forest”
33
BRACElet
% of students
The multiple choice questions determine quartile
70
60
50
40
30
20
10
0
Quartile
Q1 1 Quartile
Q2 2
Quartile
Q3 3
Quartile
Q4 4
Relational
Multistructural
Unistructural
Prestructural
34
BRACElet
% of students
Relational “see the forest”
70
60
50
40
30
20
10
0
Quartile
Q1 1 Quartile
Q2 2
Quartile
Q3 3
Quartile
Q4 4
Relational
Multistructural
Unistructural
Prestructural
35
% of students
BRACElet
70
60
50
40
30
20
10
0
Quartile
Q1 1 Quartile
Q2 2
Quartile
Q3 3
Quartile
Q4 4
Relational
Multistructural
Unistructural
Prestructural
36
BRACElet
% of students
Multistructural “failing to see the forest for the trees”
70
60
50
40
30
20
10
0
Q1
Q2
Q3
Q4
Relational
Multistructural
Unistructural
Prestructural
37
How?
e.g. Roles of Variables
file:///2005KoliRolesOfVariablesHomePage.htm
file:///c:/talks/2005KoliLiteratureOnRolesOfVariables.htm
38
We are near the end of our time:
Teacher-centred knowledge
12
3
6
39
Overview of this talk (again)

Amateur, Student, Researcher

One example from my own work



Leeds Working Group …
… followed by BRACElet
See my Koli paper for other
examples from my work
40
Summary and Conclusion:
Research vs. Teaching
&&
×



Read literature, attend
seminars/conferences
Work within well
defined theoretical or
empirical framework
Publish

The formal
study of how
novices come to
know a discipline
is central to the
sustained
health of a
discipline.
The End
41