Findings from a survey of key researchers in the computer assisted assessment field to identify the seminal research in this field to date.

1. Looking backwards to move
forwards
Seminal research that has influenced key researchers in
the field of Computer Assisted Assessment
Denise Whitelock
Institute of Educational Technology
The Open University
d.m.whitelock@open.ac.uk

2. Outline
Overview Seminal literature Quick survey
Discussion Analysis Response
DMW July 12 CAA conference

3. Objectives
. To understand what is meant
by seminal work in the field
. To investigate key researchers’
understanding of seminal work
. To analyse the findings
. To identify the gaps that need
to be filled in the current
DMW July 12 CAA conference

4. Seminal literature for CAA
• What are the classics? • What should all your
• What’s in the CAA students read?
archive?
DMW July 12 CAA conference

5. Ask the experts
• 12 subjects
• Epistolary interviews
• Facilitated dialogue
• Seminal literature
redefined
• What is seminal in our
time?
• Context changes focus
DMW July 12 CAA conference

6. Subjects
• 5 women
• 7 men
• Age approx 48 years
• Majority professorial
status
• Publications that have
had impact
DMW July 12 CAA conference

7. The experts’ response
• Difficult question
• Why do you want to know?
• What influenced me in my
research
• What I think is a big
influence for now
• Paper often before its time
• Ignore citation index
• Looking more to a 4*
paper?
DMW July 12 CAA conference

8. Top articles
Journal Article Number of
Responses
Bennet R.E. (2002) Inexorable and Inevitable: the Continuing Story of Technology and 6
Assessment JLearning Technology and Assessment Vol 1 no1
Collins, Hawkins and Friederiksen (1994) Three Different views of Students : the Role of 5
Technology in Assessing Student performance JLearning Sciences 3 (2) 205-217
Sleeman and Brown (1982) Intelligent Tutoring Systems Science vol 228 Issue 4698 7
Academic Press 456-462
Nicol and Macfarlane Dick (2006) Formative assessment and self regulated learning: A 9
model and 7 principles of good practice feedback studies in Higher Ed,32 (2) 199 -216
H.S Ashton, C.E Beevers et al ( 2006) Automatic measurement of Mathematical Ability in 4
Secondary Education (2006) BJET 37 1, 93-119
Landauer, Latham and Foltz Automatic Essay Assessment 7
http;www.tandfonline.com/dol/abs/10.1080/0969594032000148154
Whitelock, D., Watt, S., Raw, Y. and Moreale, E. (2003) ‘Analysing Tutor Feedback to 3
Students: First steps towards constructing an Electronic Monitoring System’. Association
for Learning Technology Journal (ALT-J). Vol. 11, No. 3
DMW July 12 CAA conference

9. Main categories
• Automatic essay
marking
• Modelling
• History recaps
• Automatic Assessment
in Anger
• Feedback both non
and automatic
DMW July 12 CAA conference

10. Automatic marking of free
text entry
• Open comment
• Mitchell
• Science at the OU
• Jordan
• SafeSea new EPSRC
project Whitelock
and Pulman
DMW July 12 CAA conference

11. Open Mentor: Feedback to
tutors
What is Open Mentor?
• A learning support tool for tutors that provides
reflective comments on their assessment of feedback
added to students’ assignments
How does it work?
• Flander’s categories inappropriate
• Bales’ categories
• Open Mentor provides tutors with guidance by analysing
the comments and grouping them in four major
categories
DMW July 12 CAA conference

12. Identifying trends: H801
D Pass 4
D Pass 3
Bales' Interactional Categories at each PassLlevel
D Pass 2
D Pass 1
C Pass 4
C Pass 3
C Pass 2
C Pass 1
B Pass 4
B Pass 3
B Pass 2
B Pass 1
A Pass 4
A Pass 3
A Pass 2
A Pass 1
0 5 10 15 20 25
Number ofIincidences
Graph shows conflated Bales’ categories against mean number
of incidences in H801 scripts
DMW July 12 CAA conference

13. Identifying trends: H801
1.61
5.96
5.73 Key:
A
A = Positive reactions
B
C B = Responses
D C = Questions
D = Negative reactions
17.13
Pie Chart shows the mean number of incidences per pass per conflated
Bales' Interactional Category for all four levels of pass in H801 scripts
DMW July 12 CAA conference

14. DMW, CALRG, May 2009

15. HEA-funded Synthesis Report
on Assessment and Feedback
• Consult the academic community on useful references
– Seminar series
– Survey
– Advisors
– Invited contributors
• Prioritise evidence-based references
• Synthesise main points
• For readers:
– Academics using technology enhancement for assessment and
feedback
– Learning technologists
– Managers of academic departments
DMW July 12 CAA conference

16. Evidence-based literature
• 142 references
• Technology-enhanced
methods
• Use for assessment and
feedback
• Type of evidence
• Ease of access (18 could
not be retrieved)
DMW July 12 CAA conference

17. Categories of evidence used
Category Description
1a Peer reviewed generalizable study providing effect
size estimates and which includes (i) some form of
control group or treatment (may involve
participants acting as their own control, such as
before and after), and / or (ii) blind or preferably
double-blind protocol.
1b Peer reviewed generalizable study providing effect
size estimates, or sufficient information to allow
estimates of effect size.
2 Peer reviewed ‘generalizable’ study providing
quantified evidence (counts, percentages, etc)
short of allowing estimates of effect sizes.
3 Peer-reviewed study.
4 Other reputable study providing guidance.
DMW July 12 CAA conference

18. Number of references recommended in
each evidence category
Evidence Number of Cumulative
category references %
recommended
1a 15 12.1%
1b 8 18.5%
2 12 28.2%
3 49 67.7%
4 40 100.00%
Total 124
DMW July 12 CAA conference

19. How do the findings compare with Gilbert,
Whitelock and Gale HEA study?
• All Journal articles
• No practice guides
• More technical papers
• History of deep questions
showing the early
struggles in the field
• David Nicholls’ work
common to both
• Whitelock’s work common
to both
DMW July 12 CAA conference

20. Characteristics Descriptor
Authentic Involving real-world knowledge and skills
Personalised Tailored to the knowledge, skills and interests of each student
Negotiated Agreed between the learner and the teacher
Engaging Involving the personal interests of the students
Recognises existing skills Willing to accredit the student’s existing work
Deep Assessing deep knowledge – not memorization
Problem oriented Original tasks requiring genuine problem solving skills
Collaboratively produced Produced in partnership with fellow students
Peer and self assessed Involving self reflection and peer review
Tool supported Encouraging the use of ICT
Advice for Action
Elliott’s characteristics of Assessment 2.0 activities
DMW July 12 CAA conference

21. What’s under the bonnet?:
Algorithms or heuristics?
• Well! It’s all code
• Pros and cons
• Formalising models
• Pedagogical theory
operationalised
OPEN TO TEST
DMW July 12 CAA conference

22. e-Assessment futures
• Free text entry
• Adaptive testing
• Automatic marking
• Advice for Action
• Learning Analytics
Data mining
• Motivation Badges
and Dweck
DMW July 12 CAA conference

23. Four assessment special issues
• Brna, P. & Whitelock, D. (Eds.) (2010) Special Issue of International
Journal of Continuing Engineering Education and Life-long Learning,
Focusing on electronic Feedback: Feasible progress or just
unfulfilled promises? Volume 2, No. 2
• Whitelock, D. (Ed.) (2009) Special on e-Assessment: Developing
new dialogues for the digital age. Volume 40, No. 2
• Whitelock, D. and Watt, S. (Eds.) (2008). Reframing e-assessment:
adopting new media and adapting old frameworks. Learning, Media
and Technology, Vol. 33, No. 3
• Whitelick, D. and Warburton, W. (2010). Special Issue of
International Journal of e-Assessment (IJEA) entitled ‘Computer
Assisted Assessment: Supporting Student Learning’
DMW July 12 CAA conference