LibGuides: ISEP (International Student Entry): AI Chatbots

Scholarly

Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse?
O’Connor, S. (2023) ChatGPT, Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse? Nurse Education in Practice. V 66. https://doi.org/10.1016/j.nepr.2022.103537.
Educational AI Chatbots for Content and Language Integrated Learning
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI chatbots for content and language integrated learning. Applied Sciences, 12(7), 3239. https://doi.org/10.3390/app12073239
Faculty members’ use of artificial intelligence to grade student papers: a case of implications
Kumar, R. Faculty members’ use of artificial intelligence to grade student papers: a case of implications. Int J Educ Integr 19, 9 (2023). https://doi.org/10.1007/s40979-023-00130-7
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
In this paper, the authors critically examine the rapid growth in the field of Natural Language Processing (NLP), specifically focusing on the development of increasingly larger language models such as BERT, GPT-2/3, Switch-C, and their variants. They question the necessity and inevitability of such models, arguing that researchers must consider the potential risks and costs associated with this direction in NLP research. The authors highlight environmental costs, financial barriers, opportunity costs, and potential harms (e.g., stereotyping, extremist ideology propagation, wrongful arrest) that may arise from the use of these large-scale models.
Assigning AI: Seven Approaches for Students, with Prompts
This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools, despite their inherent risks and limitations. The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student, each with distinct pedagogical benefits and risks.

Ethics

EU guidelines on ethics in artificial intelligence: Context and implementation
Clearly lays out the seven key EU requirements for ethical Artificial Intelligence:
• human agency and oversight
• robustness and safety
• privacy and data governance
• transparency
• diversity, non-discrimination and fairness
• societal and environmental well-being
• accountability
ENAI Recommendations on the ethical use of Artificial Intelligence in Education

Citation

Generative Artificial Intelligence (AI): AI-generated content and citation
University of Waterloo ChatGPT and Generative Artificial Intelligence (AI) Research Guide - tab on how to cite when you use Generative Artificial Intelligence (AI) in your academic writing.
APA style blog: How to cite ChatGPT
MLA style blog: How do I cite generative AI in MLA style?

Generative AI Tools

There are hundreds of tools out there for use. In using them you are helping to train the tools and contributing data. It is likely that many of the tools that are free now will be subscription-based in the near future. A good way to learn is to try things out and question the results; fact check! And always cite properly.

Elicit
Elicit is a research assistant using language models like GPT-3 to automate parts of researchers’ workflows. Currently, the main workflow in Elicit is Literature Review. If you ask a question, Elicit will show relevant papers and summaries of key information about those papers in an easy-to-use table. Non-profit research lab.
Yoodli
An AI speech coach to aid in preparing for presentations and interviews.
Real or Fake Text
How good are you at knowing when text has been written by a computer? How many sentences can a computer write before it no longer has you fooled? A gamified way to determine if you can tell real from generated text.
Cat Bird AI image generator

Government Guidelines

Government of Canada Guide on the use of Generative AI
Provides preliminary guidance to federal institutions on their use of generative AI tools. This includes instances where these tools are deployed by federal institutions. It provides an overview of generative AI, identifies challenges and concerns relating to its use, puts forward principles for using it responsibly, and offers policy considerations and best practices.

Outlines the “FASTER” principles:

Fair: ensure that content from these tools does not include or amplify biases and that it complies with human rights, accessibility, and procedural and substantive fairness obligations
Accountable: take responsibility for the content generated by these tools. This includes making sure it is factual, legal, ethical, and compliant with the terms of use
Secure: ensure that the infrastructure and tools are appropriate for the security classification of the information and that privacy and personal information are protected
Transparent: identify content that has been produced using generative AI; notify users that they are interacting with an AI tool; document decisions and be able to provide explanations if tools are used to support decision-making
Educated: learn about the strengths, limitations and responsible use of the tools; learn how to create effective prompts and to identify potential weaknesses in the outputs
Relevant: make sure the use of generative AI tools supports user and organizational needs and contributes to improved outcomes for Canadians; identify appropriate tools for the task; AI tools aren’t the best choice in every situation

Principles for responsible, trustworthy and privacy-protective generative AI technologies
From the Office of the Privacy Commissioner of Canada

In the news

Blog posts

Plagiarism Witch Hunts Cause Harm
Dr. Sarah Elaine Eaton clearly lays out the harms being caused by plagiarism witch hunts and lays out what plagiarism is.
Accessibility of AI Interfaces
Review, by a Langara Assistive Technologist, of various AI Chatbots based on their accessibility.
How things are made
An academic's look at the use of ChatGPT, education, and labour. Links at the end to more good resources. February 5, 2023
On the Automation of “Care”
Dr. Maha Bali discusses ideas around decisions made by people of when to use AI as a shortcut and argues that: "We don’t automate what we care about." February 18, 2023
Teaching the Machine: Faculty weigh in on AI in the classroom
Recent statistics about AI use from Canadian post-secondary faculty. May 22, 2023
Developing Career-Ready Graduates: The Importance of AI Literacy Across the Curriculum
University of Florida is integrating AI into the undergraduate program. "AI Across the Curriculum," aims to engage students in an interdisciplinary manner that reflects real-world workplace environments. May 2023
Making ChatGPT detectors part of our education system prioritizes surveillance over trust
George Veletsianos, professor of education and Canada Research Chair in Innovative Learning and Technology at Royal Roads University discusses the harm caused by surveillance. April 27, 2023
How to Guide Faculty: Navigating the AI Avalanche in Higher Education as an Academic Administrator
Short and practical post on how to handle the kinds of disruptions in institutions that AI is causing. March 7, 2023
AI Text Generators and Teaching Writing: Starting Points for Inquiry
A list of collected resources that can serve as catalysts for inquiry, discussion, and collaborative research as faculty respond to this major change in the kind of writing assistance available to our students. Last updated February 14, 2023
BCcampus: Digital Pedagogy Toolbox: Let’s Make Friends with ChatGPT
In this sixth post in our Digital Pedagogy Toolbox blog series, Gwen Nguyen discusses the potential benefits artificial intelligence (AI) tools like ChatGPT can bring to the field of post-secondary education. February 22, 2023
BCcampus: ChatGPT and Open Education
A nice summary of issues around generative AI technologies and open education. Includes some key questions surrounding copyright. March 6, 2023
How AI Tools Both Help and Hinder Equity
The technology promises to assist students with disadvantages in developing skills needed for success. But AI also threatens to widen the education gap like no tech before it. An overview that touches on many key issues. June 5, 2023

Resources from Academic Institutions

AI in Education
The rapid developments in generative artificial intelligence tools are raising many questions for educators. While we expect things to keep changing fast, TRU’s Learning Technology and Innovation team and the Centre for Excellence in Learning and Teaching are working together to stay on top of developments and share emerging best practices with our community. We will continue updating this resource with support materials, so please check back frequently.
Resources and information aimed at faculty.
Teaching and Learning with Artificial Intelligence Apps
University of Calgary teaching and learning resource.
Assessment Design in an Era of Generative AI
UBC resources for assessment design.
Generative Artificial Intelligence in the Classroom
University of Toronto guidance on using AI technology in the classroom.
Centre for Research in Assessment & Digital Learning (CRADLE) - Deakin University Au.
The Centre for Research in Assessment and Digital Learning (CRADLE) researches assessment practices in the changing settings of education, which are increasingly embracing digital learning. Our aim is to improve and optimise learning in higher and professional education.
Specific suggestions from CRADLE research
Part of a series of shared research outcomes.