Blackboard Ultra: What's New? Artificial Intelligence (AI) refers to the simulation human intelligence in machines or computers that are programmed to undertake tasks usually thought to require human cognitive processes and decision-making capabilities. Generative artificial intelligence is a subset of AI that utilizes machine learning models to create new, original content, such as images, text, or music, based on patterns and structures learned from existing data. A prominent model type used by generative AI is the large language model (LLM). ChatGPT, is a type of generative AI system that can produce natural language texts based on a given input, such as a prompt, a keyword, or a query. What's New? Blackboard trained chatbot is here. Click the link below to get Blackboard answers! Blackboard Support Assistant Generative AI Basics How does Generative AI work? How to Deal with AI Tools Challenges? Banning AI tools should not be an option, as it would not be effective, and it could infringe on academic freedom. Nevertheless, we can do many things. Here are a few examples: WPU should establish a task force to look at this issue and have university-wide discussions on how we should address the concerns created by these AI tools and how to adapt to the new technology. We might need new guidance on the appropriate use of AI assistance for course assignments. AI literacy. Both faculty and students need to understand the capabilities and limitations of AI tools, as well as the potential consequences of using them. Help faculty familiarize themselves with popular AI tools such as ChatGPT (and language models) to explore how to use these tools to enhance teaching methods as well as the implications of these tools. Adopt AI tools, harness their potential, and redesign teaching and learning. Take preventive measures in the current academic semester to minimize academic integrity concerns and avert the risks of the new AI tools. Preventive Measures for Faculty Reiterate the honor code and academic integrity and invite students into the conversation. Openly discuss the ethical implications of using ChatGPT and other AI apps with them. Develop and deploy AI writing protocols ethically and strategically within our curricula. Update the syllabus. Update the statements about academic integrity and plagiarism to include ChatGPT and other AI systems. Establish clear rules and expectations about the use of AI tools. Faculty should be clear in their syllabi about their policies for using ChatGPT. For example, do not allow students to use AI tools when taking quizzes, tests, and exams, and require students to appropriately acknowledge (e.g. cite AI outputs and treat them as content developed by a third party, offer rules of citation) when they do use ChatGPT in other course assignments. Using proctored exam tools such as Respondus LockDown Browser and Monitor. Crafting questions and designs that cannot be plagiarized by chatbots or chatbots would have difficulties to handle, such as students’ own lives and current events. Encourage students’ personal reflection and connect with students’ own experiences in their assignments and discussions. Giving less take-home, open-book assignments, which now seem vulnerable to chatbots. Opt for in-class assignments, handwritten papers, group work, and oral exams. Redesign courses, making changes such as more oral exams, group work, and handwritten assessment. Focusing on process rather than product. Scaffolding learning and allowing students to explain their thinking and make learning visible along the way are strategies that may help you confirm student originality. Use AI generated text detection software, as detailed below. > AI Tools to help detect AI-generated texts Currently, several detection tools are available and can be used by faculty to identify AI-generated texts. GPT-2 Output Detector The online demo of the GPT-2 output detector model lets you paste texts into a box and immediately see the likelihood that the text was written by AI. According to research from OpenAI, the tool has a relatively high detection rate, but “needs to be paired with metadata-based approaches, human judgment, and public education to be more effective.” GLTR (giant language model test room) The GLTR demo enables forensic inspection of the visual footprint of a language model on input text to detect whether a text could be real or fake. It is a collaborative effort by the MIT-IBM Watson AI lab and Harvard NLP. GPTZeroDeveloped by Edward Tian, a Princeton University student, GPTZero measures randomness in sentences (“perplexity”) plus overall randomness (“burstiness”) to calculate the probability that the text was written by ChatGPT. Watermarking (coming soon)The ChatGPT developer OpenAI is trying to address the problem by watermarking all ChatGPT text. “Basically, whenever GPT generates some long text, we want there to be an otherwise unnoticeable secret signal in its choices of words, which you can use to prove later that, yes, this came from GPT” (OpenAI guest researcher Scott Aaronson). How about SafeAssign?SafeAssign checks the papers against a database of previously submitted papers, the internet, journals, and other sources to detect plagiarism. But AI-generated text is essentially unique as AI create sentences based on a statistical analysis of words in the database they are using to generate new sentences with. Hence, SafeAssign cannot detect AI-generated text unless a more sophisticated algorithm is used that is specifically designed to identify patterns and characteristics of text generated by language models. Opportunities While AI tools pose serious challenges to how we teach and how students learn, they also offer us opportunities and the potential to reimagine teaching to facilitate student learning and achieve our intended outcomes better. But this short document is focused what we need do now. I will write a more detailed report later on this part. Generally speaking, WPU could use AI tools to improve the education experience for its students and faculty in many potential ways, for example: 1) Personalized learning, 2) Grading and feedback, 3) Tutoring and support, 4) Student advisement, 5) Research, 6) Administration and management (students recruitment, registration, etc.) We should encourage faculty to conduct productive experimentation and explore pedagogical possibilities. The university might also need to establish a task force and university-wide discussion on how to take advantage of AI tools to enhance teaching and promote learning. Genrative AI Tools for Faculty Content Creation ChatGPT Claude Gemini CoPilot Images & Art Creation Dall-e-2 CoPilo Designer Freepik Leonardo Bria Openart Pebblely Playground Lasco Stable Diffusion Video Creation Supercreator Runway Lumiere 3D Shuffll Fliki Synthesia Video Reemix Audio Creation Altered Voicemod Krisp Programming | Coding Autoregex Lightning AI Consultations Personal Productivity Notion AI Albus SlidesAI AI Detection Tools GPT-2 Detector GLTR GPTZero Writefull Content at Scale Research Paperpal Scholarcy Scispace Lesson Planning CoPilot Lesson Plans Decktopus Prompt Engeering Prompt engineering involves crafting specific instructions or questions to guide a computer program in generating desired content effectively. Within the world of generative artificial intelligence (AI), prompt engineering allows users to leverage AI models -often referred to as language models (LMs) and the natural language processing (NLP, or the instructions that allow computers to interact with humans) capabilities of those models to generate customized content that is designed according to the specifics of the prompt. Elements of a Prompt A prompt can contain any of the following elements: Task: A summary of what you want the prompt to do. Usually starts with an action verb such as, Create, Summaraize, Explore, Analyze, Write, Recommend, Argue, Explain, etc. Format: The type or format of the response/output, such as Opinion, Outline, Blogpost, Spreadsheet, Press release, Leagal brief, etc. Voice: Setting a specific role for a given prompt increases the likelihood of more accurate information, including like a HR director, using martketing language, in style of previous press release, respond as you are king from 17th, etc. Context: Additional information or context that guides the model towards producing better outputs/responses, something like, serious, funnny, for UG students, etc. Resources on Prompt Engeering The Perfect Prompt: A Prompt Engineering Cheat Sheet This comprehensive cheat sheet, created by Maximilian Vogel and published in The Generator, serves as a quick-reference guide for various aspects of prompt engineering. It is designed to be a detailed resource for both beginners and seasoned users. OpenAI’s Prompt Engineering Guide This guide provides comprehensive documentation on prompt engineering, covering various techniques and best practices for crafting effective prompts. It is an excellent starting point for anyone looking to understand the fundamentals of prompt engineering. GitHub’s General Guidelines for AI Prompts The repository "awesome-gpt-prompt-engineering" on GitHub is a curated list of resources and examples for prompt engineering, providing a community-driven approach to learning. Top Tools for Prompt Engineering 2024: Unlock Creativity! Introduces top prompt engineering tools represent various applications, from marketplaces and models to development frameworks and optimization platforms. Prompt Library from Anthropic Anthropic's Prompt Library is a valuable resource for obtaining task-specific, optimized prompts. It is particularly useful for those looking to apply prompt engineering techniques to specific use cases. Courses on Prompt Engeering Prompt Engineering for ChatGPT This 6-module course introduces students to the patterns and approaches for writing effective prompts for large language models. ChatGPT Prompt Engineering for Developers Offered by DeepLearning.AI in collaboration with OpenAI, this video course is designed specifically for developers. It provides practical insights and hands-on experience in creating and optimizing prompts for ChatGPT. YouTube: There are numerous free courses and tutorials available on YouTube, such as the Prompt Engineering Course: How To Effectively Use ChatGPT & Other AI Language Models Aleksandar Popovic, which cover the basics and advanced techniques of prompt engineering. Prompt Examples OpenAI: Examples Ethan Mollick, Professor at Wharton: Using AI to Implement Effective Teaching Strategies in Classrooms: Five Strategies, Including Prompts Assigning AI: Seven Approaches for Students, with Prompts AI Prompts for Teaching: A Spellboo This recourse describes excellent use cases and strategies for effectively using Generative AI tools in teaching and learning. ChatGPT and Generative AI - Seb Dianati and Suman Laudari In a series of 4 articles published in Times Higher Education, the authors look at 100 ways to use ChatGPT in higher education. Each article shares 25 prompts: 25 applications in teaching and assessment 25 applications to support student engagement How to support university administrative tasks 151 The Best ChatGPT Prompts for Academic Writing To Enhance Academic Writing Skills A Structured Guide to using ChatGPT Prompts for academic writing. ChatGPT Cheat Sheet - 100+ Prompts to Unlock All the Power of ChatGPT ChatGPT: Jasper AI Cheat Sheet by Artificial Corner. Genreative AI in Teaching Challenges The immediate challenge facing faculty is the fear of cheating on student assignments, tests, and exams. In fact, the ChatGPT-generated answers to assignments, tests, and exams were already used to cheat by some WPU students in the fall of 2022. This undermines academic integrity and makes it difficult for faculty to assess student understanding and progress. In the Spring 2022 semester and beyond, we can expect much more such instances. WPU needs to act and adjust to protect academic integrity quickly. How to Deal with AI Tools Challenges? Banning AI tools should not be an option, as it would not be effective, and it could infringe on academic freedom. Nevertheless, we can do many things. Here are a few examples: WPU should establish a task force to look at this issue and have university-wide discussions on how we should address the concerns created by these AI tools and how to adapt to the new technology. We might need new guidance on the appropriate use of AI assistance for course assignments. AI literacy. Both faculty and students need to understand the capabilities and limitations of AI tools, as well as the potential consequences of using them. Help faculty familiarize themselves with popular AI tools such as ChatGPT (and language models) to explore how to use these tools to enhance teaching methods as well as the implications of these tools. Adopt AI tools, harness their potential, and redesign teaching and learning. Take preventive measures in the current academic semester to minimize academic integrity concerns and avert the risks of the new AI tools. Preventive Measures for Faculty Reiterate the honor code and academic integrity and invite students into the conversation. Openly discuss the ethical implications of using ChatGPT and other AI apps with them. Develop and deploy AI writing protocols ethically and strategically within our curricula. Update the syllabus. Update the statements about academic integrity and plagiarism to include ChatGPT and other AI systems. Establish clear rules and expectations about the use of AI tools. Faculty should be clear in their syllabi about their policies for using ChatGPT. For example, do not allow students to use AI tools when taking quizzes, tests, and exams, and require students to appropriately acknowledge (e.g. cite AI outputs and treat them as content developed by a third party, offer rules of citation) when they do use ChatGPT in other course assignments. Using proctored exam tools such as Respondus LockDown Browser and Monitor. Crafting questions and designs that cannot be plagiarized by chatbots or chatbots would have difficulties to handle, such as students’ own lives and current events. Encourage students’ personal reflection and connect with students’ own experiences in their assignments and discussions. Giving less take-home, open-book assignments, which now seem vulnerable to chatbots. Opt for in-class assignments, handwritten papers, group work, and oral exams. Redesign courses, making changes such as more oral exams, group work, and handwritten assessment. Focusing on process rather than product. Scaffolding learning and allowing students to explain their thinking and make learning visible along the way are strategies that may help you confirm student originality. Use AI generated text detection software, as detailed below. > AI Tools to help detect AI-generated texts Currently, several detection tools are available and can be used by faculty to identify AI-generated texts. GPT-2 Output Detector The online demo of the GPT-2 output detector model lets you paste texts into a box and immediately see the likelihood that the text was written by AI. According to research from OpenAI, the tool has a relatively high detection rate, but “needs to be paired with metadata-based approaches, human judgment, and public education to be more effective.” GLTR (giant language model test room) The GLTR demo enables forensic inspection of the visual footprint of a language model on input text to detect whether a text could be real or fake. It is a collaborative effort by the MIT-IBM Watson AI lab and Harvard NLP. GPTZeroDeveloped by Edward Tian, a Princeton University student, GPTZero measures randomness in sentences (“perplexity”) plus overall randomness (“burstiness”) to calculate the probability that the text was written by ChatGPT. Watermarking (coming soon)The ChatGPT developer OpenAI is trying to address the problem by watermarking all ChatGPT text. “Basically, whenever GPT generates some long text, we want there to be an otherwise unnoticeable secret signal in its choices of words, which you can use to prove later that, yes, this came from GPT” (OpenAI guest researcher Scott Aaronson). How about SafeAssign?SafeAssign checks the papers against a database of previously submitted papers, the internet, journals, and other sources to detect plagiarism. But AI-generated text is essentially unique as AI create sentences based on a statistical analysis of words in the database they are using to generate new sentences with. Hence, SafeAssign cannot detect AI-generated text unless a more sophisticated algorithm is used that is specifically designed to identify patterns and characteristics of text generated by language models. Opportunities While AI tools pose serious challenges to how we teach and how students learn, they also offer us opportunities and the potential to reimagine teaching to facilitate student learning and achieve our intended outcomes better. But this short document is focused what we need do now. I will write a more detailed report later on this part. Generally speaking, WPU could use AI tools to improve the education experience for its students and faculty in many potential ways, for example: 1) Personalized learning, 2) Grading and feedback, 3) Tutoring and support, 4) Student advisement, 5) Research, 6) Administration and management (students recruitment, registration, etc.) We should encourage faculty to conduct productive experimentation and explore pedagogical possibilities. The university might also need to establish a task force and university-wide discussion on how to take advantage of AI tools to enhance teaching and promote learning. Generative AI Guideline Coming soon Generative AI Webinars and Workshops Generative AI Training Opportunities CTT team can assist you on adopting these feature on your teaching area. Please use one of the followig options to get connected. Webinars Workshops Consultations Walk-in Generative AI Resources Recordings on the Genrative AI Sessions Recordings of Webinars on Generative AI AI Assistant in Blackboard Genreative AI Tools and Prompt Engineering Generative AI and Academic Integrity Recordings of Workshops on Generative AI Coming soon.
