PhD research proposal presentation Sonia Saddiqui 28 Nov 2013

1. PhD Research Proposal
28 Nov, 2013
‘On My Honour!’
An Investigation into the Feasibility of
Academic Honour Codes in the Australian
University Context
Sonia Saddiqui
School of Education
Department of Human Sciences
Macquarie University

2. Today‟s presentation:
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Research rationale,
Definitions
Associated factors
Current responses to managing
Academic Integrity
Theoretical framework
Research questions, aims and
methodology

3. Research Rationale
Why research student academic integrity
management?
Breaches are pervasive
 Rates among students in the US have been as
high as 64% (McCabe & Trevino, 1996)
 70% of US college students self-reported breach
behaviours (Whitley,1998)

4. Research Rationale
Why investigate student academic integrity
management?
HE Sector Changes

Focus on consistent standards, benchmarking,
increasing accountability and monitoring (Bradley
Review, 2008)
 Government commitment to addressing
academic integrity issues
 4 x Office of Learning & Teaching Priority Projects
(2012-2014)

5. Research Rationale
Why research student academic integrity management?
Breaches are harmful
Effects program efficacy
 Disrupt transmission of knowledge and the assessment of
student competencies
Undermines good scholarship
 Fails to recognise the contributions of past scholars
Creates culture of distrust
 Lack of faith in rules and policies leads to lack of student
satisfaction (AUSSE, 2008)
 Perception of systemic unfairness

6. Research Rationale
Why research student academic integrity
management?
Breaches are harmful
Damage to reputation
 University reputation – institutions and/or programs
become less desirable options for students
 Less likely to attract talented staff and research
funding
 Personal and professional reputation costs
Future professional unethical conduct
 Breach behaviour in university linked to breach
behaviour in the workplace (Sims, 1993; Thompson
2000)

7. Associated Factors
What are the intrinsic and extrinsic factors commonly
associated with increased likelihood of breach activity?
Impact of ICT
Lack of skills and knowledge
Differing pedagogical philosophies
Changing values and expectations relating to
academia
Increasing competition and pressure
Peer influence

8. Associated Factors
Peer Influence/ Peer culture
 Significantly correlated with the likelihood
of breach activity (McCabe & Trevino, 1993; McCabe
& Trevino, 1997; McCabe, Trevino & Butterfield, 2002).
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Students who perceive that breaches are
commonplace are more likely to commit
breaches themselves.
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Peer disapproval of cheating is
associated with decreased cheating
(McCabe and Trevino, 1993).

9. Examples of AI breaches
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Plagiarism
Collusion
Falsification
Cheating in exams
Ghost-writing
Purchasing assignments
Submitting the same assignment more
than once
 Sabotage
 Enlisting a proxy to take an examination
 Bribery

10. Definitions used in AI literature
Why are definitions important?
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Because language, tone and register is
important.
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Terminology in AI policies often places
students in the role of potential offenders, and
academic staff in a policing and judgment role
(Sutherland-Smith 2010)
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Definitions and processes should encourage
inclusivity
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Legalistic definitions with moral overtones are
limiting and limited

11. Key Terms
Academic Integrity
 ICAI definition consists of 5
fundamental values: honesty, trust,
fairness, respect, and responsibility
(„courage‟ has been added to the
latest draft) (ICAI, 2012, 2013)
Academic Integrity Breaches
 Behaviour that is incongruent with
these values (Gallant, 2008)

12. Common Terms
Some synonymous concepts
 Academic misconduct
 Plagiarism
 Academic dishonesty
 Cheating
51% of Aust. university AI policies used „academic
misconduct‟ and „plagiarism‟ as key terms
(Bretag et. al. 2011)
41% of Aust. university AI policies used „academic
integrity‟ as the key term (Bretag et. al., 2011)

13. Defining „Academic Integrity
Breach‟
Any intentional or unintentional
activity by a student that
breaches the rules of an
assessment task and/or
the accepted standards of
academic behaviour at
an institution.

14. Current Approaches
What are the characteristics of current AI
management systems at universities?
1) Punitive
2) Pedagogical
3) Process
& Policy

15. Current Approaches
What are the characteristics of current AI management
systems at universities?
Punitive Approaches
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Basic
Involves warnings, disciplinary outcomes
Penalties as deterrence
Emphasis on „catch and punish‟
PDS (e.g. Turnitin)
Can be devised and implemented quickly
E.g. „academic misconduct penalties‟

16. Current Approaches
What are the characteristics of current AI management
systems at universities?
Pedagogical Approaches
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Logical long-term strategy
Acculturation to academia
Supportive
Deterrence through equipping students with skills
and knowledge
Can be tailored to suit particular disciplines
„Good customer service‟
E.g. learning support programs, online modules,
embedding AI elements into curriculum

17. Current Approaches
What are the characteristics of current AI management
systems at universities?
Process & Policy Approaches
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Refers to the larger systems within which AI is
managed
 Policies – definitions, rhetoric & language,
formulation, dissemination
 Processes – Policies in action, informal
processes
 E.g. Training and induction for staff

18. A holistic response is
recommended
(Devlin 2002; Freeman, et al., 2007; JISC, 2011; MacDonald & Carroll, 2006 and Park, 2003)
Punitive
Process
&
Policy
AI
Management
?
Pedagogical

19. The missing „P‟?
Participation!
Punitive
Process
&
Policy
AI
Management
Participation
Pedagogical

20. Participatory Approach to AI
Management
What does it entail?
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Establishing an academic integrity community
Articulating common values
Engaging students - more meaningful
involvement of students in AI processes and info.
dissemination
Promoting shared ownership and shared
responsibility of academic integrity
Students gain knowledge and experience
through participation
More likely to create longer-lasting, positive
cultural change in AI

21. Participatory Approach to AI
Management
Are there existing models we can refer to ?
Academic Honour Codes
Provides an existing framework to refer to,
adapt and build-upon.
Their effects and implementation processes
have been studied.

22. Participatory Approach to AI
Management
What are Honour Codes?
Honour Codes
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Formalised codes that require students
(and in some cases, staff) to abide by
certain rules of ethical academic and
personal conduct.
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Most commonly associated with US
institutions
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Strong emphasis on community, trust and
mutual responsibility.

23. Participatory Approach to AI
Management
Honour Codes Types
Traditional
 Contracts, pledges, oaths
 Responsibility lies mainly with students
 Disciplinary committees may consist entirely of
students
 Students may be required to report breaches and
may be permitted unsupervised examinations
Modified
 Adapted from the traditional format to suit the
campus culture
 AI responsibilities are more likely to be shared
with staff

24. Honour Codes
University of Virginia
Image source: http://i.huffpost.com/gen/1369399/thumbs/o-UNIVERSITY-OF-VIRGINIAfacebook.jpg

25. Honour Codes
University of Virginia – Quotes from students & staff
http://www.virginia.edu/honor/benefits-of-honor/#sthash.bShLksXL.dpuf)
“Honor empowers students to take ownership and responsibility for
their community. Students do not pass through this University, they
shape it.” - UVA student
The tangible meaning is obvious-no cheating, lying, stealing, etc.
But I think on a more abstract level it has a general meaning of
attempting to hold both yourself and the community to a desirable
standard.”
- UVA student
“I would not want to teach anywhere a community of trust did not
exist. It is an honor in itself to be accepted as a student or faculty
member into this community.”
- UVA Professor

26. Dan Ariely: „Why we think it's
OK to cheat and steal
(sometimes)‟
<video removed due to size restrictions>
To see the video, please visit youtube:
http://www.youtube.com/watch?v=nUdsTizSxSI
Reference:
Dan Ariely. (2009, March 18). Why we think it's OK to cheat and steal
(sometimes) [Video file] Retrieved from:
http://www.youtube.com/watch?v=nUdsTizSxSI

27. Participatory Approach to AI
Management
Honour Codes
But can they work HERE?
Yes…provided there is:
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„Buy in‟ from students
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Endorsement by the university community
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Embedment and institutional support
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Effective dissemination
(McCabe, Trevino & Butterfield, 2002; Dufresne, 2004)

28. Theoretical Framework
Psychological Sense of Community (Sarason,
1974)
Further developed by Chavis et. al., (1986)
into
4 Sense of Community Elements:
 Membership
 Influence
 Integration and fulfilment of needs
 Shared emotional connection
Aim? To assess presence, impact and
evidence of Sense of Community elements in
HC

29. Research Questions
1.
2.
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4.
What are the main elements of
Honour Codes?
How are Honour Codes created and
maintained?
What do student and staff think of
honour codes (or similar student-led
model) in terms of: purpose,
application, effects and viability (in
the Aust. HE context)
(Maybe) How would an Honour Code
(or similar) Society be implemented
at an Australian university?

30. Research Aims
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Create categories & classify „types‟ of
honour codes
Identify honour code stakeholders and
their respective roles
Identify honour code processes,
dissemination & application
Ascertain staff & student attitudes
about honour codes
Assess feasibility
(Maybe) Develop guidelines for
implementation

31. Research Method
This PhD research is attached to a
current OLT Academic Integrity
Study led by MQ:
Academic Integrity in Australia –
Understanding and Changing Culture
and Practice (Oct 2012 – April 2014)
Ethical clearance (for OLT project +
PhD) was granted by MQ HREC for
the following:
 Focus groups (Ethics no.
5201300429)
 Interviews (Ethics no.5201300430)

32. Research Method
Research Questions 1& 2:
 Content analysis of honour codes using
Grounded Theory approach, informed by
the 4 Sense of Community elements
 Honour Codes will be sourced from the list
of institutions cited by the ICAI (n=360)
Research Questions 3 & 4
 Focus groups (n=26 students)
 Interviews (n=40 students + staff) who play
advisory, advocacy and administrative roles
in AI, at approx. 20 unis.
Maybe….
 Evaluation of pilot Honour Code Society
(part of current OLT study)