PhD research proposal presentation Sonia Saddiqui 28 Nov 2013


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PhD research proposal presentation Sonia Saddiqui 28 Nov 2013

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PhD research proposal presentation Sonia Saddiqui 28 Nov 2013

  1. 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. 2. Today‟s presentation:       Research rationale, Definitions Associated factors Current responses to managing Academic Integrity Theoretical framework Research questions, aims and methodology
  3. 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. 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. 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. 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. 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. 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).  Students who perceive that breaches are commonplace are more likely to commit breaches themselves.  Peer disapproval of cheating is associated with decreased cheating (McCabe and Trevino, 1993).
  9. 9. Examples of AI breaches        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. 10. Definitions used in AI literature Why are definitions important?  Because language, tone and register is important.  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)  Definitions and processes should encourage inclusivity  Legalistic definitions with moral overtones are limiting and limited
  11. 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. 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. 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. 14. Current Approaches What are the characteristics of current AI management systems at universities? 1) Punitive 2) Pedagogical 3) Process & Policy
  15. 15. Current Approaches What are the characteristics of current AI management systems at universities? Punitive Approaches        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. 16. Current Approaches What are the characteristics of current AI management systems at universities? Pedagogical Approaches        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. 17. Current Approaches What are the characteristics of current AI management systems at universities? Process & Policy Approaches  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. 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. 19. The missing „P‟? Participation! Punitive Process & Policy AI Management Participation Pedagogical
  20. 20. Participatory Approach to AI Management What does it entail?       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. 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. 22. Participatory Approach to AI Management What are Honour Codes? Honour Codes  Formalised codes that require students (and in some cases, staff) to abide by certain rules of ethical academic and personal conduct.  Most commonly associated with US institutions  Strong emphasis on community, trust and mutual responsibility.
  23. 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. 24. Honour Codes University of Virginia Image source:
  25. 25. Honour Codes University of Virginia – Quotes from students & staff “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. 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: Reference: Dan Ariely. (2009, March 18). Why we think it's OK to cheat and steal (sometimes) [Video file] Retrieved from:
  27. 27. Participatory Approach to AI Management Honour Codes But can they work HERE? Yes…provided there is:  „Buy in‟ from students  Endorsement by the university community  Embedment and institutional support  Effective dissemination (McCabe, Trevino & Butterfield, 2002; Dufresne, 2004)
  28. 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. 29. Research Questions 1. 2. 3. 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. 30. Research Aims       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. 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. 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)