Difference between revisions of "ABC-Academic integrity"
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| − | '''Academic Integrity''' is a promise that scholars and scientists world wide give each other, that we will uphold, protect, and promote ethical and practical standards for our work. Its most basic values are honesty, trust, fairness, respect, responsibility, and courage. These are simple ideas, but in order to give them meaning we need to discuss how these values get translated to the details of our everyday work. | + | '''Academic Integrity''' is a promise that scholars and scientists world-wide give each other, that we will uphold, protect, and promote ethical and practical standards for our work. Its most basic values are proclaimed as honesty, trust, fairness, respect, responsibility, and courage. These are simple ideas, but in order to give them meaning we need to discuss how these values get translated to the details of our everyday work. Unfortunately, this important topic is often compressed to discussing ''cheating'' and ''plagiarism'', to managing procedures to detect dishonesty, and to threatening sanctions. It is overlooked that those are just the manifestations of much deeper problems, and focussing on those symptoms alone perpetuates a stereotyped us-versus-them mentality of educators and students alike that is much more likely to make the problem worse than to solve it. The key to counter this lies in a proper understanding of academic integrity as a relational value, and ''respect'' as its foundation. |
| − | + | Discussing academic integrity in the abstract is of limited use, the challenge is to put the concepts in practice, in every aspect of this course and this is not a question of behaviour, but of attitude. The attitude needs to be reflected in the choice of teaching materials, in the care in their preparation, in the attitude of impartiality and reproducibility we bring to our experiments, in mutual trust in class, in fairness in assessments, and honesty in assignments. One everyday issue is ''attribution'' and we operate a '''Full Disclosure Policy''' for attribution in this course. This means '''everything''' that is not one's own, original idea must be identified and properly attributed. Neither I nor you are already perfect in this, but I trust we can come together as a learning community to educate each other and improve. | |
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* ... understand the basic values of academic integrity; | * ... understand the basic values of academic integrity; | ||
* ... can see how adopting these values for yourself makes you a part of the global community of scholars and scientists; | * ... can see how adopting these values for yourself makes you a part of the global community of scholars and scientists; | ||
| − | * ... understand the "full-disclosure policy" of our course, as the basis for avoiding | + | * ... understand the "full-disclosure policy" of our course, as the basis for avoiding academic misconduct; |
* ... know how to translate the values of academic integrity into your everyday work in practice. | * ... know how to translate the values of academic integrity into your everyday work in practice. | ||
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<!-- The rules are simple, but non-negotiable: | <!-- The rules are simple, but non-negotiable: | ||
| − | *Do not fabricate results. | + | * All results are reported exactly as they were obtained.<ref>Or: Do not fabricate results.</ref> |
| − | *Do not resubmit previous assignments. | + | * All submissions are prepared specifically for the requirement.<ref>Do not resubmit previous assignments.</ref> |
| − | *Do not copy anything<ref>The word "anything" explicitly includes the R code and other writing supplied with your course materials!</ref> | + | * All contributions by others are fairly attributed.<ref>Do not copy anything without attributing its source.</ref><ref>The word "anything" explicitly includes the R code and other writing supplied with your course materials!</ref><ref>This includes journal articles and books, obviously, but also blogs, discussions on StackOverflow, Github gists, and especially course material of '''this''' and other courses, your peer's notes and journal entries. and material you have produced previously.</ref> |
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:2017-08-05 | :2017-08-05 | ||
<b>Modified:</b><br /> | <b>Modified:</b><br /> | ||
| − | :2021- | + | :2021-08-27 |
<b>Version:</b><br /> | <b>Version:</b><br /> | ||
:2.0 | :2.0 | ||
Latest revision as of 14:00, 26 August 2021
Academic Integrity and Plagiarism
(The components of academic integrity, pitfalls of lagiarism, proper citing, steering clear of academic misconduct, rules for collaboration in this course)
Abstract:
Academic Integrity is a promise that scholars and scientists world-wide give each other, that we will uphold, protect, and promote ethical and practical standards for our work. Its most basic values are proclaimed as honesty, trust, fairness, respect, responsibility, and courage. These are simple ideas, but in order to give them meaning we need to discuss how these values get translated to the details of our everyday work. Unfortunately, this important topic is often compressed to discussing cheating and plagiarism, to managing procedures to detect dishonesty, and to threatening sanctions. It is overlooked that those are just the manifestations of much deeper problems, and focussing on those symptoms alone perpetuates a stereotyped us-versus-them mentality of educators and students alike that is much more likely to make the problem worse than to solve it. The key to counter this lies in a proper understanding of academic integrity as a relational value, and respect as its foundation.
Discussing academic integrity in the abstract is of limited use, the challenge is to put the concepts in practice, in every aspect of this course and this is not a question of behaviour, but of attitude. The attitude needs to be reflected in the choice of teaching materials, in the care in their preparation, in the attitude of impartiality and reproducibility we bring to our experiments, in mutual trust in class, in fairness in assessments, and honesty in assignments. One everyday issue is attribution and we operate a Full Disclosure Policy for attribution in this course. This means everything that is not one's own, original idea must be identified and properly attributed. Neither I nor you are already perfect in this, but I trust we can come together as a learning community to educate each other and improve.
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Objectives:
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Outcomes:
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Deliverables:
- Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
- Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don't overlook these.
- Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.
Contents
Evaluation
Evaluation: NA
Contents
Make your work on this unit the first entry of your Journal!
You need to understand where we come from on that, and what this means in detail. So read on. Make sure you understand, and make these ideas your own.
This is the age of open source, boundless mashup, awesome reposts and instant repurposing of information. It might seem that our rules of referencing and citation are just another academic anachronism. After all, we all copy from stack overflow, right?
No - actually: wrong for two reasons. One: information is not any longer a commodity that increases in value if its supply is artificially constrained. Rather the value of information in academia - our common currency - is now "mindshare", and mindshare cannot grow without attribution. And two: part of any course at UofT is its "summative assessment": we mark submissions to evaluate the aptitude and achievements of students. That can only be done if original thinking by the student is clearly identified, and distinguished from merely repeating other's thoughts.
But let's face it: UofT has a plagiarism problem. This has gotten worse over the past years - and it seems worse in the CS realms than in the domains of the life sciences. Yet, even if all your peers think no one cares about missing attributions, that doesn't make it somehow right: ethics is not a result of opinion polls. No matter how socially acceptable plagiarism has become, no matter how many others do "it", no matter how many likes or upvotes or retweets a "No Big Deal!" post attracts, unethical behaviour is wrong. It goes against everything we stand for as scientists. And it is corrosive, not just for your community, but first and foremost for yourself.
In this course we operate a Full Disclosure Policy. That doesn't mean you can't get good data and examples from wherever you find them - on the contrary I absolutely expect you to hunt everywhere for information and examples: biostars, stack, RBloggers, even reddit (sometimes). There is great value in finding how others have addressed a problem, or divide up and organize a particular topic, and compiling the knowledge of the entire community is a great starting point for excellent work. But (a) this process has to be transparent, and, indeed you need to develop and document a sense of pride in mastering this art and attributing the contributions of your sources, and (b) compiling information does not substitute for your understanding of the material that you are presenting.
Regardless whether you are reusing, quoting, paraphrasing, summarizing or following someone else's structure or advice: reference it. You can never reference too much, but if you don't reference enough you are probably committing an academic offence and I am obliged by University Policy to take the issue to the Office of Student Academic Integrity (OSAI). Regardless whether you are writing an assignment, updating your journal, uploading code, replying to posts on the mailing list - for anything that is submitted for credit, directly or indirectly: make sure all your references are complete.
The principle is quite simple:
Full disclosure policy for this course:
If it's not your own, new idea, it has a source.
All sources must be referenced.
How to reference
You probably have seen resources that refer to other's observations or opinions, and teach you to reference in manuscripts and essays in the life sciences and the humanities. These are generally less relevant for the kind of work that we do, and perhaps this is one of the reasons for poor uptake. Indeed, most of the writing in our courses is informal, and it may not be obvious how to properly embed citations in the flow of the narrative.
The solution is to thouroughly contextualize your attributions with statements such as:
- "inspired by...",
- ""based on...",
- "according to ...",
- "following ...",
- "see also ...",
etc. as appropriate.
Some specific points to consider:
- On Wiki pages, use the <ref>text</ref> tag to organize your citations.
- In R code, put your citations directly into the code in a comment.
- The URL of an image on the Internet is not by itself an adequate reference. Author and context must be shown.
- All links in references must be to the original source, not to e.g. a blog post about the source.
- Code that is copied from e.g. stack overflow or similar must be referenced with a link to the post AND the name of the author.
- Use the APA citation format for this course.
When and what to reference
- Some material may be "common knowledge". Obviously, you don't need to cite the resource that taught you how to write a for-loop, for example. Where to draw the line? If in doubt, ask, discuss, seek consensus in the community and in class.
- Example code from an R package vignette that you adapt and reuse must be referenced.
- Code that you take from a different course must be referenced.
- Code that you take from this course must be referenced.
- Code that you have translated from a different language must be referenced.
- Code that you have jointly developed with a classmate must acknowledge the contribution.
- Code that you have copied from a classmate's work on the Student Wiki must be referenced.
- Code that is open source must be referenced.
- Code that is in the public domain must be referenced. This one is particularly troublesome: some authors put their code into the public domain, and state that you are free to use it without any copyright restrictions and without need for acknowledgement. But this can give rise to a misunderstanding: it only refers to the legal status as far as reuse is concerned, it says nothing about authorship. Obviously: just because someone graciously allowed you to use their idea, that does not mean that you are the author.
Reusing previous material
A second mistake that has brought students to the Dean's office more than once is re-use of material from previous courses. This is a simple one: you can't get academic credit for the same material twice. This means: if you have already submitted something for a different course elsewhere, or for a different assessment in the same course, it is no longer an original contribution. Of course you can cite your own work and then reuse it - if it's useful, bravo - good for you. But you have to be upfront about it, and apply the Full Disclosure Policy in spirit. Again: if in doubt, ask for advice.
"Adjusting" results
It sometimes happens that a piece of code you are submitting won't run. It just won't. You can't see the mistake, it's three in the morning and you just can't take it anymore. It's just a small variation from the spec - and you can easily fix the output by hand.
So you edit a few lines in a printout, or a few cells in a spreadsheet, and submit that result. All good, right?
No. Not good at all. You have just falsified your code output. In terms of academic misconduct this is called "concoction". And it's pretty high on the list of things that will make for a very bad day.
Do not ever change code output by hand. If an assignment asks you to submit code and results, the exact code you submit must generate the exact output that is claimed for it. Obvioulsy, there will be assessment scripts that will verify that. And when the assessment script signals a discrepancy, that will set off a process ...
Above, I've highlighted a few issues that I have come accross in past courses. Below, are extensive resources that will help you work better. Go and read them.
Task:
Visit the following sites and read the material carefully:
- Smart Strategies (OSAI)
- How Not to Plagiarize (UofT Writing Advice)
- Quoting (UofT Writing Advice) Mostly relevant for essays, but also for your own journal: when to quote, when to paraphrase, when to summarize.
- Paraphrasing and Summarizing (UofT Writing Advice) Illustrating the distinction between illegitimate and proper paraphrase, and summary by example.
- Standard Documentation formats (UofT Writing Advice) This includes a concise overview on citing electronic sources.
Then - for your own reference - put a model of the following three types of references into your journal:
- a procedure in the methods section of a journal article, as you would cite it in a technical report;
- a piece of code you found in a StackOverflow article, as you would put it as acomment into computer code;
- some contents from a classmate's journal that you incoporate into your own journal.
- A final note
- If you have any questions about these policies, if you would like to start a discussion, or if you can share some anecdotes: post on the discussion list. We need to make these policies alive and meaningful, otherwise we'll see mistake after mistake, tears, anguish and missed graduations. No more!
Further reading, links and resources
- Code of Behaviour on Academic Matters The policy. (Governing Council of the University of Toronto.)
Notes
About ...
Author:
- Boris Steipe <boris.steipe@utoronto.ca>
Created:
- 2017-08-05
Modified:
- 2021-08-27
Version:
- 2.0
Version history:
- 2.0 Rewriting the page: from "plagiarism" to "academic integrity"
- 1.2 Clearly re-stating the basic rules
- 1.1.2 Maintenance
- 1.1.1 Clarification: this course's material falls under the same policy
- 1.1 Update to "Full Disclosure Policy"
- 1.0 Completed to first live version
- 0.2 Links to FAS material
- 0.1 Material collected from previous tutorial
This copyrighted material is licensed under a Creative Commons Attribution 4.0 International License. Follow the link to learn more.
