Improving Moral Behaviour in the Business Use of ICT
Bibliographic record
Abstract
The 21st century has seen a much-increased focus on the importance of ethical behaviour in business, driven by major scandals, calls for stricter regulation and increased demands for improved governance and reporting. In parallel, there are calls for the incorporation of moral and ethical elements in business education and university accreditation bodies and schools are responding. In particular, the explosion of technology change, particularly Internet, social media and beyond have raised many challenges for individuals, organizations and legislators. However, educational responses are varied and little has been done to determine the effectiveness of what has been done. Most responses to this need to provide ethical education follow a cognitive, rule-based approach, often using case-based techniques. This can improve knowledge and understanding of ethical issues, but it may have limited influence on actual behaviour. A relatively new field – Positive Psychology -- provides an alternate perspective, focusing on what is good rather than what is poor behaviour. One Positive Psychology approach, that of Appreciative Inquiry, which has not previously been used in ICT ethics education, offers a promising technique to develop improved moral attitudes and behaviour. This paper reports on a large-scale pedagogical research project that: (1) examines ethical perspectives from philosophy, psychology and pedagogy in the context of ICT professional education; (2) describes the development and multistage implementation of an ethics course in an undergraduate business ICT program delivered to more than 1,200 students; (3) discusses the formal evaluation of changes in moral attitude following a Positive Psychology intervention in the education of some 300 Business ICT students using the Defining Issues Test, Version 2 (DIT2) and the IMIS Survey developed at the Centre for Computing and Social Responsibility. The project results demonstrate that a well-designed applied ICT ethics course produces measureable positive changes in the ethical stances of participants and that the use of Appreciative Inquiry increases the impact of these changes. In addition to the relevance of the findings for educators they can provide guidance to those in organisations responsible for the ethical behaviour of their ICT employees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".