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Page 2 of 7 - AI Writing Overview Submission ID trn:oid:::1:3102914834
0% detected as AI Caution: Review required.
The percentage indicates the combined amount of likely AI-generated text as It is essential to understand the limitations of AI detection before making decisions
well as likely AI-generated text that was also likely AI-paraphrased. about a student’s work. We encourage you to learn more about Turnitin’s AI detection
capabilities before using the tool.
Detection Groups
1 AI-generated only 0%
Likely AI-generated text from a large-language model.
2 AI-generated text that was AI-paraphrased 0%
Likely AI-generated text that was likely revised using an AI-paraphrase tool
or word spinner.
Disclaimer
Our AI writing assessment is designed to help educators identify text that might be prepared by a generative AI tool. Our AI writing assessment may not always be accurate (it may misidentify
writing that is likely AI generated as AI generated and AI paraphrased or likely AI generated and AI paraphrased writing as only AI generated) so it should not be used as the sole basis for
adverse actions against a student. It takes further scrutiny and human judgment in conjunction with an organization's application of its specific academic policies to determine whether any
academic misconduct has occurred.
Frequently Asked Questions
How should I interpret Turnitin's AI writing percentage and false positives?
The percentage shown in the AI writing report is the amount of qualifying text within the submission that Turnitin’s AI writing
detection model determines was either likely AI-generated text from a large-language model or likely AI-generated text that was
likely revised using an AI-paraphrase tool or word spinner.
False positives (incorrectly flagging human-written text as AI-generated) are a possibility in AI models.
AI detection scores under 20%, which we do not surface in new reports, have a higher likelihood of false positives. To reduce the
likelihood of misinterpretation, no score or highlights are attributed and are indicated with an asterisk in the report (*%).
The AI writing percentage should not be the sole basis to determine whether misconduct has occurred. The reviewer/instructor
should use the percentage as a means to start a formative conversation with their student and/or use it to examine the submitted
assignment in accordance with their school's policies.
What does 'qualifying text' mean?
Our model only processes qualifying text in the form of long-form writing. Long-form writing means individual sentences contained in paragraphs that make up a
longer piece of written work, such as an essay, a dissertation, or an article, etc. Qualifying text that has been determined to be likely AI-generated will be
highlighted in cyan in the submission, and likely AI-generated and then likely AI-paraphrased will be highlighted purple.
Non-qualifying text, such as bullet points, annotated bibliographies, etc., will not be processed and can create disparity between the submission highlights and the
percentage shown.
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Application Paper
Student’s Name
Institutional Affiliation
Course Code and Name
Professor
Date
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Application Paper
Scenario 1: Sub-par Peer Performance
Then if one realize that they have made the decision to give a coworker that is assigned to
something that they could have done but did not, then it is important for to take care of the situation
clearly and with empathy. Wrench’s ideas of feedback and expectation management teach that
feedback is a good thing. Feedback should be specific, not personal: The way you comment on
this work is not good enough, you would find it more effective to respond to the missing part, “the
report was missing data analysis section” for instance. "Next time can you, please focus on adding
that?"
For expectation management concept, one should clearly communicate what you expect
your peer to do. If you do not clearly state your expectations with the initial request, then learn
from it and change your approach next time to make your goals clear and much more specific than
you did before. It means no more excuses about it is not good enough, because you have a clearer
benchmark of what success is so it removes ambiguity around what constitutes success and allows
your co-workers to understand how to meet your standards. It also helps to lower frustration from
either side.
Now you need to learn to balance the feedback so as not to do the work for your coworking.
That is why we need empowerment. Instead of simply correcting the task you can suggest them
what they have to do differently, giving them tools or resources that will enhance their
productivity.
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You can also ask: 'Do you have any support or resource issues to support you to meet the
expectations?' This model lets your coworker work with their name, or their brand, behind their
work and if you trust them enough to know that they can only get better and really care about their
work, it means they own it.
Moreover, collaboration requires attention. One might instead want to suggest a follow up
meeting to go over the task together as it asks to be a team effort. It also means you are not
nitpicking, you really are wanting to work together to achieve the best outcome. This feedback is
delivered as a reprimand and if left unchecked a culture of hurt feelings remains. But delivered as
one of collaboration we all grow together.
Scenario 2: Training Challenge
You will be working to host a training course that communicates with members of a team
that speak English, Spanish, and everything in between. Wrench explores what it takes to tackle
language barriers and achieve cultural competence when it comes to training: It is equitable that
both groups receive the same quality of training.
To achieve all this one need to have bilingual training material that can be supported by
bilingual team members or use professional translators to help explaining or otherwise interpreting
the important points during the training session. But it also ensures that no one misses critical
information and that it’s just as accessible to everyone.
Furthermore, workers must be bilingual, speaking English and Spanish, so that they can
speak to other employees in the language that they are familiar with. Trainers communicate
differently, have different expectations and different learning preferences based on their culture.
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For example, if team members are Spanish speakers then one must take into consideration a
formality that's needed and what level of authority they need while being in training. This is why
culture trained and culturally competent professional would have an idea of this and would
approach each group on their communication preferences. For example, they could include within
their learning examples or references that are culturally pertinent to each group to help people
relate to the learning and become more engaged in it.
Visual aids, like diagrams, can further aid in reducing language gap while delivering the
training in the verbal content through the use of non-verbal communication techniques. This will
remove the languages barrier and guarantee that no one participant fails to understand the main
points of the session. In addition, it is beneficial to allow both groups to attend and to ask questions
by the language that they commonly use as it will help retain equal engagement of all team
members and, consequently, avoiding misunderstanding.
Lastly, one can create an inclusive space where both groups can comfortably share their
language or can comfortably share their ideas while working with each other. Encouraging team
members to use small group discussions wherein each member would pair up with someone who
speaks the other language is equally important. This helps ensure the training meets the linguistic
challenge but also is fertile ground for working simultaneously and learning about each other.
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References
Wrench, J. S. (2013). Workplace communication for the 21st century: Tools and strategies that
impact the bottom line [2 volumes]. Bloomsbury Publishing USA.
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