Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Analyzing CS Competenciesusing The SOLO Taxonomy

Claus Brabrand((( brabrand@itu.dk )))((( http://www.itu.dk/people/brabrand/ )))

Associate Professor,IT University of Copenhagen Denmark

ITiCSE'09 – Keynote

[ 2 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Outline

1) Introduction Constructive Alignment The SOLO Taxonomy

2) From Content to Competence Advocate a shift in perspective Elaborate The SOLO Taxonomy

3) Analyzing CS Competencies …using The SOLO Taxonomy Compare: CS vs NAT vs MAT

[ 3 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

“Teaching for Quality Learning at University

- What the student does”

“Teaching for Quality Learning at University

- What the student does”

Constructive Alignment & SOLO Taxonomy:

Introduction to…:

“Teaching Teaching & Understanding Understanding”

“Teaching Teaching & Understanding Understanding”19 min award-winning short-film on Constructive Alignment(available on DVD in 7 languages, epilogue by John Biggs)

John Biggs’ popular and heavily cited book:

Note: 3rd Edition now available [J.Biggs & C.Tang, 2009]

[ 4 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

What are the ‘main messages’of the film (which did YOU findparticularly relevant, …if any)?

Activation Exercise

Discuss with your neighbour:

T

[ 5 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Outline

1) Introduction Constructive Alignment The SOLO Taxonomy

2) From Content to Competence Advocate a shift in perspective Elaborate The SOLO Taxonomy

3) Analyzing CS Competencies …using The SOLO Taxonomy Compare: CS vs NAT vs MAT

[ 6 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

From Content to Competence

My old course descriptions (Concurrency 2004): Given in terms of a 'content description':

Essentially:

This is a bad ideafor two reasons...!

Goal is…:

To understand: deadlock interference synchronization ...

[ 7 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Goal is…:

To understand: deadlock interference synchronization ...

Problem 1 !

Problem with 'content' as goals ! analyze ...theorize ...

define deadlockdescribe solutions

name solutionsrecite conditons

Stud. C

Stud. A

Stud. B

analyze systemsexplain causes

Censor

Teacher

P.S.: even if it werepossible to agree, we know that the

exam will dictate thelearning anyway.

agreem

ent

analyze systemsexplain causes

tacit kno

wled

ge fro

m a

research-b

ased trad

ition

no

t kno

wn

by stu

den

t

[ 8 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Problem 2 !

Problem with 'understanding' as goals !

The answer is simple:

'concept of deadlock' ?!

Goal is…:

To understand: deadlock interference synchronization ...

It cannot be measured !

[ 9 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Competence !

'Competence' as goals !

Have the student do something;and then "measure" the product and/or process

'SOLO' = Structure of the Observed Learning Outcome

Note': inherently operational (~ verbs)

Objective !

To learn how to: analyze systems for... explain cause/effects... prove properties of... compare methods of... ...

Note: 'understanding' is of course

pre-requisitional !

Competence := knowledge + capacity to act upon it

[ 10 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO Advantages

Advantages of The SOLO Taxonomy: Linear hierarchical structure Aimed at evaluating student learning Converges on research (at SOLO 5)

Research:Production ofnew knowledge

[ 11 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO (elaborated)Note: the list is non-exhaustive

SOLO 2”uni-structural”

SOLO 3“multi-structural”

SOLO 4“relational”

SOLO 5“extended abstract”

theorize generalize hypothesize predict judge reflect transfer theory

(to new domain) …

analyze compare contrast integrate relate explain causes apply theory

(to its domain) …

combine structure describe classify enumerate list do algorithm apply method …

define identify count name recite paraphrase follow (simple)

instructions …

Graphic Legend

problem / question / cue known related issue - given! hypothetical related issue - not given! student response

Q

R

QUANTITATIVE QUALITATIVE

R

R'Q

RQRQRQ

[ 12 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Using SOLO in Practice

Intended Learning Outcomes [Algorithms 101]

After the course, the students are expected to be able to:

identify and formulate algorithmic problems ;

classify and compare algorithms ;

construct and analyze algorithms using standard paradigms;

implement algorithms for simple problems.

2) List sub-goals as 'bullets': Clearer than text

3) Use 'Verb + Noun' formulation:

What the student is expected to

do with a given matterV N

N

N

V

V V N

V V

V V

N

4) Avoid 'understanding-goals':

"To understand X", "Be familiar with Y", "Have a notion of Z", ...!

Recommendations on course descriptions:

1) Use 'standard formulation':

a) puts learning focus on the student

b) competence formulation: "to be able to"

[ 13 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Activation Exercise

Which do you predict are key CS competences ?

T

Concurrency:

analyze systemscompare models

Concurrency:

analyze systemscompare models

[ 14 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Outline

1) Introduction Constructive Alignment The SOLO Taxonomy

2) From Content to Competence Advocate a shift in perspective Elaborate The SOLO Taxonomy

3) Analyzing CS Competencies …using The SOLO Taxonomy Compare: CS vs NAT vs MAT

Joint work with Bettina Dahl at Aarhus University

[ 15 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Grade Scales

ECTSSCALE

A, B, C, D, E, Fx, F

...

4 steps

8 steps

10 steps

21 steps

...

4 steps

8 steps

10 steps

21 steps

7 steps:

...

... ...

Conversion (between EU countries):

All Universities:Explicit ILO's

The SOLO Taxonomy!

Grade := Degree of realization

of course objectives!

[ 16 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Massive DATA set

Unique Opportunity…:

Systematically formulated ILO's for all courses Quantifiable (analyzable) via The SOLO Taxonomy

5,608

734

institutesTWO universities

competenciescourses

21

[ 17 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO Mapping

Mapped by: B. Dahl & C. Brabrand

With help from: 3 Educational research

colleagues (medicine) J. Biggs & C. Tang

[ 18 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Top 10 Competencies

Top 10 Competencies:

" " := { Physics, Chemistry, Biology, Molecular Biology }

Natural Sciences

[ 19 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Histogram of Top Competencies

If we look closer (comparative visualization)...:

Legend:

Computer Science Natural Science Mathematics

%

CS

CS

CS

MAT

MAT

MAT MAT MAT

MAT

More than 3x More than 3x

CS

…also: program construct structure

NAT

NAT

CS: 15 %NAT: 1.0 %MAT: 0.3 %

CS: 4.5 %NAT: 4.4 %MAT: 40 %

CS: 14 %NAT: 14 %MAT: 60 %

More than 2x

with apply

[ 20 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO Distribution

SOLO distribution:

The 15% "programming competences" (all at SOLO 4): { implement, program, design, construct, structure }

SOLO 2 SOLO 3 SOLO 4 SOLO 5Legend:

15% E[X] = 3.7

E[X] = 3.4

E[X] = 3.1

[ 21 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Assumptions

SOLO is an appropriate competence measure (we refer to [J.Biggs & K.F.Collis, 1982] )

Context independence of SOLO mapping (for each competence we inspected several goals)

Subject independence of SOLO mapping (we limit ourselves to a 'science context')

Equal weight assumptions (Competences in a goal & goals in a course have equal weight)

Outcomes: intended formulated achieved (we “analyze” formulated, but “reason about” achieved)

Assumptions:

[Biggs’ studies]

[approximation]

[approximation]

[approximation]

[implicational]

[ 22 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Conclusions Most frequent CS Competences are:

describe (13%), explain (10%), apply method (9%), implement (7%), analyze (6%), …

"Programming-related" skills: 15% of CS-curriculum

The "Essence of Math" is: reproducing, formulating,

proving, solving, argueing,(and applying)

SOLO-levels of subjects: CS >SOLO NAT >SOLO MAT

15%

[ 23 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

1) Introduction Constructive Alignment The SOLO Taxonomy

2) From Content to Competence Advocate a shift in perspective Elaborate The SOLO Taxonomy

3) Analyzing CS Competencies …using The SOLO Taxonomy Compare: CS vs NAT vs MAT

Outline

[ 24 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Keynote Points

Constructive Alignment …addresses many teaching / learning problems; e.g.:

Esp. student motivational issues (learning incentives) ...and student performance issues (learning support)

The SOLO Taxonomy …is good for reasoning about competencies:

Esp. for designing courses and curricula

DATA Study, analyze, and reflect on teaching / learning

…using (objective) DATA!

[ 25 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Questions...

"What is good teaching?"

The Short-Film

Cognitive processes

Association

new ~ old

The Book

John Biggs

"understanding"

content competence

Student activation

Susan & RobertTeacher models

levels 1 - 2 - 3

Course descriptions

Constructive AlignmentTop 10 Competences

15% programming

CS v. NAT v. MAT

Students at University

My researchand teaching

'TLA'Teaching / Learning

Activities

Tips'n'Tricks

?

recitegeneralize

R

R'

Q

The SOLO Taxonomy

Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Thank You!

((( http://www.daimi.au.dk/~brabrand/short-film/ )))

Film's homepage:

[ 27 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Related References ”Teaching for Quality Learning at University (what the student does)”

John Biggs & Catherine TangSociety for Research into Higher Education, 2007. McGraw-Hill.

”Evaluating the Quality of Learning: The SOLO Taxonomy”John Biggs & Kevin F. CollisLondon: Academic Press, 1982

”Teaching Teaching & Understanding Understanding”Claus Brabrand & Jacob Andersen19 minute award-winning short-film (DVD)Aarhus University Press, Aarhus University, 2006

”Using the SOLO Taxonomy to Analyze Competence Progression of University Science Curricula”Claus Brabrand & Bettina DahlHigher Education, 2009

"Constructive Alignment & The SOLO Taxonomy: a Comparative Study of University Competencies in Computer Science vs. Mathematics"Claus Brabrand & Bettina DahlCRPIT, Vol. 88, ACS 3-17, R. Lister & Simon, Eds., 2007

[ 28 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Implementing Alignment

Alignment Implementation Process:

1) Think carefully about: overall goal of course (what are the stud. to learn?)

2) Operationalize these goals and formulate them as SOLO intended learning outcomes

3) Choose carefully the form(s) of assessment (~ intended learning outcomes)

4) Choose carefully the form(s) of teaching (~ intended learning outcomes)

alignmentlearning incentive learning support

Think of teachingactivities as

”training for exam”

[ 29 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO Progression

SOLO Progression: Computer Science vs. Mathematics vs. …

[ 30 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Conclusion (Progression)

What have we really shown?!?

A) SOLO has "proved" that progression exists in curricula (since we "believe" in SOLO as a measure)

B) SOLO has "been proven" to be a good tool for analyzing competence progression (since we "believe" in the existence of progression)

xor

[ 31 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Progression Assumptions

Numeric quantification of SOLO [assumption] (i.e., numeric step from 2-3 is comparable to 3-4 and 4-5)

Progression manifests itself as competences [assumption] (i.e., in 'verb'-, not 'noun'-dimension)

Extra assumptions wrt. Progression:

[ 32 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO Calculation Method

Calculation Example (for a course):

"SOLO average": [ (2+3)/2 + (3+4)/2 + (4+4)/2 + 4 ] / 4 = 3.50

"SOLO distribution":

identify (2) and formulate (3) algorithmic problems;

classify (3) and compare (4) algorithms;

construct (4) and analyze (4) algorithms using standard paradigms;

implement (4) algorithms for simple problems.

"double weight averaging"

[ 33 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Neighbour Discussion

Discuss with neighbour:"does this make sense ?!?"

(content competence)

T

E.g.: ("Learning about programming" vs. "Learning to program" )

[ 34 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Discuss what you predict wewould find in the DATA set ?

Activation Exercise III

Discuss with your neighbour:

T

Questions: a) most frequent CS competences? b) percentage of "programming-related" competences? c) CS v. NAT v. MAT (wrt. SOLO levels)?

[ 35 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Post-It exercise

Write down 1-2 key competences (i.e., verbs)

(for your course)

T

Concurrency:

analyze systems for deadlock

compare models wrt. behavior

Concurrency:

analyze systems for deadlock

compare models wrt. behavior

[ 36 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Tips'n'Tricks (activation)

Neighbour discussions:

Frequent breaks:

Post-It exercise: focus: zoom in anonymous (!) swap'able everyone will engage empathetic control shared knowledge pool

pu

lse

re

ad

er

me

asu

rem

en

ts:

more questions (students dare ask them)

better questions (students had a chance to discuss)

1-2 min timeout [Phil Race]

Form variation:

lecturing blended with in-class activation exercises

[ 37 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Tips'n'Tricks (cont'd)

"Less-is-more":

Use many examples:(build on student pre-knowledge)

Explicit structure:

analyze compare relate

common deadlock, uncommon deadlock, A-synchronization, B-synchronization, hand-shake, multi-party synchronization, multi-party hand-shake, binary semaphores, generalized semaphores, blocking semaphores, recursive locks, ...

vs.

Emphasize depth over breadth (coverage)

NEWOLD

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4. wwwwwww

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2. yyyyyyyyyy

3. zzzzzzzzzz

4. wwwwwww

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2. yyyyyyyyyy

3. zzzzzzzzzz

4. wwwwwww

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4. wwwwwww

self evident to you [ teacher ] not to a learner [ student ] (esp. during learning process)

Student 'recap' at end:

after 1 dayafter 1 week

after 3 weeks

after 2 weeks

now

[ 38 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Now, please: "3-minute recap"

Please spend 3' on thinking about and writing down the most important points from the talk – now!:

After 1 dayAfter 1 week

After 3 weeksAfter 2 weeks

Immediately

[ 39 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

E.g. course: ”Databases” (at RUC/Roskilde):

Note: almost entirely non-operational(!)

i.e. measure how?!

obtain knowledge about the structure of database systems; be familiar with design of databases by use of special notations like E/R and analysis through normalization; get an overview of the most important database models and a detailed knowledge about the most important model - the relational model as well as the language SQL; get an overview of database indexing and query processing; obtain knowledge about application programming for DB systems.

Problematic Courses

Familiar with ?!

Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

BONUS SLIDES

[ 41 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Based on John Biggs' Theories

2nd edition

(3rd edition expected this fall)

"Teaching for Quality Learning at University", John Biggs

[ 42 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Teacher’sintention

Student’sactivity

Exam’sassessment

e.g.- explain- relate- prove- apply

e.g.- memorize- describe

UNALIGNED COURSE

e.g.- memorize- describe

"Dealing with the test"

[ 43 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Teacher’sintention

Student’sactivity

Exam’sassessment

e.g.- explain- relate- prove- apply

ALIGNED COURSE

e.g.- explain- relate- prove- apply

e.g.- explain- relate- prove- apply

e.g.- explain- relate- prove- apply

e.g.- explain- relate- prove- apply

[ 44 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Top 10 Competencies

Top 10 Competencies:

" " := { Physics, Chemistry, Biology, Molecular Biology }

Natural Sciences

[ 45 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO (elaborated)Note: the list is non-exhaustive

SOLO 2”uni-structural”

SOLO 3“multi-structural”

SOLO 4“relational”

SOLO 5“extended abstract”

theorize generalize hypothesize predict judge reflect transfer theory

(to new domain) …

analyze compare contrast integrate relate explain causes apply theory

(to its domain) …

combine structure describe classify enumerate list do algorithm apply method …

define identify count name recite paraphrase follow (simple)

instructions …

Graphic Legend

problem / question / cue known related issue - given! hypothetical related issue - not given! student response

Q

R

QUANTITATIVE QUALITATIVE

R

R'Q

RQR2

R3

R1

Q

RQ

RQ

[ 46 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Exercise

Buzz Session:

1) Discuss w/ neighbour:

2) Write it on a Post-It3) Swap Post-Its…

T

Just KeepSwapping…

"which film messages did you find particularly relevant?"

[ 47 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Student Motivation

Susan: (”intrinsic motivation”) - wants to…: learn ! Robert: (”extrinsic motivation”) - to…: pass exams !

[ 48 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Constructivism

”Transmission is Dead…” : (lectures = ) Knowledge is… Actively Constructed !

active teacher &passive students

!

risk

[ 49 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

SOLO Taxonomy

Hierarchy for Competences:

Deep learning (not surface) !

5: generalize, theorize, predict, …4: explain, analyze, compare, …3: describe, combine, classify, …2: recite, identify, calculate, …

[ 50 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Stud Learning Focus

Focus on Student Learning ! (instead of ”what teacher does” & labelling students: ’good/bad’) Student activitation learning

[ 51 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Alignment

Make explicit ILO’s (Intended Learning Outcomes):

(…and tell this to students)

Exam = ILO’s = Teaching

[ 52 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

The Role of the Exam

Alignment: A theory of planning (over the course of a course) A theory of motivation (and incentive)

The exam as a...:"Necessary evil"

Motivational and learning-guidingpedagogical tool for the teacher(!)

applicationof alignment

"The exam does not come after, but before the course!"

[ 53 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Di-Transitive Verbs

Mono-Transitive verbs:

Di-Transitive verbs:

[ 54 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

Data Set (XML and XQuery)(: Extracts all mathematics courses w/ maximum 1 goal and 2 competencies :)

xquery version "1.0";

<result>{ for $course in fn:doc("data-au.xml") //institute[@name = "MAT"]//course let $goals := $course/goal where (fn:count($goals) le 1) and (fn:count($goals/competence) eq 2) order by $course/@name return $course }</result>

Data set:

[ http://www.itu.dk/people/brabrand/solo.xml ][ http://www.itu.dk/people/brabrand/data-au.xml ][ http://www.itu.dk/people/brabrand/data-sdu.xml ]

XML

XQuery

[ 55 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

The BLOOM Taxonomy (1956)

The BLOOM Taxonomy:

Knowledge

Comprehension

Application

Analysis EvaluationSynthesis

Qualitative

Quantitative

SO

LO 4

+5

SO

LO 2

+3

”[…] really intended to guide the selection of items for a test rather than to evaluate the quality of a student’s response to a particular item”

-- (Biggs & Collis, 1982)”

[ 56 ]Claus Brabrand ITiCSE 2009 – Keynote Paris, France (July 06, 2009)

CS vs Math Distributions

Computer Science:

Mathematics:( = 3.06, = 0.24)

( = 3.68, = 0.39)