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Posted on: Teaching Toolkit Tailgate
PEDAGOGICAL DESIGN
Driving Your Course with Your Driving Questions
Photo by Jon Tyson on Unsplash
Questions Driving You
Why did you choose the discipline you’re teaching and researching in now? What was it about its unique lens on the world that inspired you? Sometimes, in the rush to design syllabi and curriculum, and feeling buried by stacks of grading at points, it can be easy to forget the reasons we were driven to choose our disciplines in the first place. And just as these reasons inspired and inspire you, so too can they inspire students and provide a cohesion to your curriculum.
Questions Driving Your Course
Scholars have advocated for designing classroom work out of the very real inquiry and issues at the core of our academic disciplines. Applebee (1996) believes that our curriculum design should support the opportunity for our students to engage in the “conversations” that have built our disciplines and continue to sustain our inquiry within them. Bain (2004), in his study of what makes for the best college teaching, found some of the most impactful teachers to be the ones basing their courses out of the disciplinary questions that mattered to them. And McTighe and Wiggins (2005) suggest the use of what they call “essential questions” from your discipline to anchor your syllabus, teaching, and learning. Even in introductory courses, framing in this manner can help students be more active participants in their learning as they take up the very real current questions that the discipline seeks to answer outside the classroom. So, as you begin your course this week, we have four questions for you to ask yourself in an effort to drive your course with the questions driving you:
Why did you choose your discipline?: Answering this question can oftentimes help re-anchor you in the fundamental passion and inquiry at the core of your discipline and help you better see through the perspectives of your students. From there, you can identify the specific questions your discipline attempts to answer.
What questions does your discipline attempt to answer?: Here is where you can begin to stake some claims about the affordances and limits of your discipline’s view of the world. Does your discipline seek answers connected to literary interpretation and meaning-making? About the best ways to engineer physical structures? Your discipline no doubt asks and answers through specific lenses.
How are the questions in your discipline currently being asked in your discipline and out in the world?: Contemporary relevance can help with overall engagement, as students see how what they’re doing in your course may connect with present-day applications. This allows students to begin to answer the “so what?” about your course and why one may care to know the content and skills you’re engaging in.
How does your course help students ask or begin to ask the questions you identified in two and three above?: Your curriculum design choices are key. Provide opportunities for students to be anchored in the real inquiry and perspectives that matter most in your discipline. Make this inquiry explicit along the way. Your assessment choices are also important here, as you have the opportunity to provide real-world tasks for students that you and others in your discipline would engage in outside the classroom.
Resources
Applebee, A. N. (1996). Curriculum as Conversation: Transforming Traditions of Teaching and Learning. Chicago; London: University of Chicago Press.
Bain, K. (2004). What the Best College Teachers Do. Cambridge, Mass: Harvard University Press.
Wiggins, G., & McTighe, J. (2005). Understanding by Design, Expanded 2nd Edition. Alexandria, VA: Pearson.
Questions Driving You
Why did you choose the discipline you’re teaching and researching in now? What was it about its unique lens on the world that inspired you? Sometimes, in the rush to design syllabi and curriculum, and feeling buried by stacks of grading at points, it can be easy to forget the reasons we were driven to choose our disciplines in the first place. And just as these reasons inspired and inspire you, so too can they inspire students and provide a cohesion to your curriculum.
Questions Driving Your Course
Scholars have advocated for designing classroom work out of the very real inquiry and issues at the core of our academic disciplines. Applebee (1996) believes that our curriculum design should support the opportunity for our students to engage in the “conversations” that have built our disciplines and continue to sustain our inquiry within them. Bain (2004), in his study of what makes for the best college teaching, found some of the most impactful teachers to be the ones basing their courses out of the disciplinary questions that mattered to them. And McTighe and Wiggins (2005) suggest the use of what they call “essential questions” from your discipline to anchor your syllabus, teaching, and learning. Even in introductory courses, framing in this manner can help students be more active participants in their learning as they take up the very real current questions that the discipline seeks to answer outside the classroom. So, as you begin your course this week, we have four questions for you to ask yourself in an effort to drive your course with the questions driving you:
Why did you choose your discipline?: Answering this question can oftentimes help re-anchor you in the fundamental passion and inquiry at the core of your discipline and help you better see through the perspectives of your students. From there, you can identify the specific questions your discipline attempts to answer.
What questions does your discipline attempt to answer?: Here is where you can begin to stake some claims about the affordances and limits of your discipline’s view of the world. Does your discipline seek answers connected to literary interpretation and meaning-making? About the best ways to engineer physical structures? Your discipline no doubt asks and answers through specific lenses.
How are the questions in your discipline currently being asked in your discipline and out in the world?: Contemporary relevance can help with overall engagement, as students see how what they’re doing in your course may connect with present-day applications. This allows students to begin to answer the “so what?” about your course and why one may care to know the content and skills you’re engaging in.
How does your course help students ask or begin to ask the questions you identified in two and three above?: Your curriculum design choices are key. Provide opportunities for students to be anchored in the real inquiry and perspectives that matter most in your discipline. Make this inquiry explicit along the way. Your assessment choices are also important here, as you have the opportunity to provide real-world tasks for students that you and others in your discipline would engage in outside the classroom.
Resources
Applebee, A. N. (1996). Curriculum as Conversation: Transforming Traditions of Teaching and Learning. Chicago; London: University of Chicago Press.
Bain, K. (2004). What the Best College Teachers Do. Cambridge, Mass: Harvard University Press.
Wiggins, G., & McTighe, J. (2005). Understanding by Design, Expanded 2nd Edition. Alexandria, VA: Pearson.
Authored by:
Erik Skogsberg
Posted on: Teaching Toolkit Tailgate
Driving Your Course with Your Driving Questions
Photo by Jon Tyson on Unsplash
Questions Driving You
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Questions Driving You
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Authored by:
PEDAGOGICAL DESIGN
Thursday, Jul 30, 2020
Posted on: Teaching Toolkit Tailgate
PEDAGOGICAL DESIGN
Avoiding Learning Myths
Photo by Kimberly Farmer on Unsplash
The Learning Styles Myth
The Myth: “I’m a visual learner,” Similar to the left vs. right brain, another prevalent neuromyth in education is the belief that students have distinct learning styles–meaning that their ways of learning (i.e., visual, kinesthetic, auditory, etc) require different teaching practices [1].
The Facts: While some students may prefer different types of information delivery, there is no existing research to date to suggest that there is any benefit in teaching them in their preferred learning style [2]. In fact, everybody uses a mix of these styles, and some of us are dominant in one or the other. We may also use one style in a situation and another under different circumstances [1].
The Alternative: There is a variety of ways to engage students with the material they are learning. One of the most popular teaching methods that incorporates both student-centered learning and the multiple representations of information is the Universal Design for Learning (UDL). UDL is a set of principles that helps teachers design flexible learning environments that adapt to the variability of learners.
The Critical Window of Time for Learning Myth
The Myth: “I’m too old to learn this.” This misconception is often linked to the “myth of three,” which postulates that the brain only retains information during a critical period–rendering the first three years of a child’s life decisive for future development and success in life.
The Facts: While critical periods have been observed in animal behavior, scientists have agreed that these are not as delineated in human beings, and instead favor the term “sensitive periods” which can be impacted by many factors [3]. Instead, research in neuroscience shows that different brain systems showcase different types and amount of changes with experience. This is called plasticity–the capacity that the brain has to change through learning [4]. So while some skills can be acquired during optimal times (i.e., grammar rules), it doesn’t mean that exposure and training beyond that could not lead to changes and learning.
The Alternative: Many educators have been enthusiastic about the idea of a “growth mindset” in opposition to a fixed learning pathway. While the idea is popular, there is also growing concern that teachers might not have the resources to use the concept effectively in the classroom. For instance, a recent nationwide survey of K-12 teachers reported that 85% of them wanted more professional development in the area [5].
How to Avoid Neuromyths
Start with skepticism! Look beyond mere claims and dig a little deeper to research the science behind these claims. For instance, research shows that we get seduced by explanations that are accompanied by images of the brain, no matter how random they are. This doesn’t mean being a complete pessimist, but to try to strike a balance between popular facts and scientific research. Is the claim being sold as a cure-all? What does the evidence say? Does it sound too simple? One of the best ways to do so is to be informed and knowledgeable about the brain.
Resources
http://www.oecd.org/education/ceri/34926352.pdf
https://www.psychologicalscience.org/journals/pspi
http://www.oecd.org/education/ceri/neuromyth1.htm
https://www.edcan.ca/
https://www.edweek.org/media/ewrc_mindsetintheclassroom_sept2016.pdf
The Learning Styles Myth
The Myth: “I’m a visual learner,” Similar to the left vs. right brain, another prevalent neuromyth in education is the belief that students have distinct learning styles–meaning that their ways of learning (i.e., visual, kinesthetic, auditory, etc) require different teaching practices [1].
The Facts: While some students may prefer different types of information delivery, there is no existing research to date to suggest that there is any benefit in teaching them in their preferred learning style [2]. In fact, everybody uses a mix of these styles, and some of us are dominant in one or the other. We may also use one style in a situation and another under different circumstances [1].
The Alternative: There is a variety of ways to engage students with the material they are learning. One of the most popular teaching methods that incorporates both student-centered learning and the multiple representations of information is the Universal Design for Learning (UDL). UDL is a set of principles that helps teachers design flexible learning environments that adapt to the variability of learners.
The Critical Window of Time for Learning Myth
The Myth: “I’m too old to learn this.” This misconception is often linked to the “myth of three,” which postulates that the brain only retains information during a critical period–rendering the first three years of a child’s life decisive for future development and success in life.
The Facts: While critical periods have been observed in animal behavior, scientists have agreed that these are not as delineated in human beings, and instead favor the term “sensitive periods” which can be impacted by many factors [3]. Instead, research in neuroscience shows that different brain systems showcase different types and amount of changes with experience. This is called plasticity–the capacity that the brain has to change through learning [4]. So while some skills can be acquired during optimal times (i.e., grammar rules), it doesn’t mean that exposure and training beyond that could not lead to changes and learning.
The Alternative: Many educators have been enthusiastic about the idea of a “growth mindset” in opposition to a fixed learning pathway. While the idea is popular, there is also growing concern that teachers might not have the resources to use the concept effectively in the classroom. For instance, a recent nationwide survey of K-12 teachers reported that 85% of them wanted more professional development in the area [5].
How to Avoid Neuromyths
Start with skepticism! Look beyond mere claims and dig a little deeper to research the science behind these claims. For instance, research shows that we get seduced by explanations that are accompanied by images of the brain, no matter how random they are. This doesn’t mean being a complete pessimist, but to try to strike a balance between popular facts and scientific research. Is the claim being sold as a cure-all? What does the evidence say? Does it sound too simple? One of the best ways to do so is to be informed and knowledgeable about the brain.
Resources
http://www.oecd.org/education/ceri/34926352.pdf
https://www.psychologicalscience.org/journals/pspi
http://www.oecd.org/education/ceri/neuromyth1.htm
https://www.edcan.ca/
https://www.edweek.org/media/ewrc_mindsetintheclassroom_sept2016.pdf
Authored by:
Sarah Gretter
Posted on: Teaching Toolkit Tailgate
Avoiding Learning Myths
Photo by Kimberly Farmer on Unsplash
The Learning Styles Myt...
The Learning Styles Myt...
Authored by:
PEDAGOGICAL DESIGN
Thursday, Jul 30, 2020
Posted on: GenAI & Education
PEDAGOGICAL DESIGN
Complete Guide to Incorporating Generative AI in Your Syllabus
(Photo by Steve Johnson on Unsplash )
You can also access the Generative AI Syllabus Guide Playlist with this content broken down into the following sections. Table of Contents:
MSU Guidance and [Non]Permitted Uses
Developing and Communicating a Course-level Generative AI Use policy
Example Syllabus Statements for the Use of AI Tools in Your Course
Design For Generative AI (restrict, permit, require)
Design Around Generative AI (ban)
Example Statements from Current USA, Higher Education Educators
Developing your Scholarly and Ethical Approaches to Generative AI
Beyond Syllabi Language
Additional considerations to help you develop your generative AI philosophy (Watkins, 2022)
References
The following MSU-specifics should be used to inform your decisions...
Overall guidance: We collectively share the responsibility to uphold intellectual honesty and scholarly integrity. These are core principles that may be compromised by the misuse of GenAI tools, particularly when GenAI-generated content is presented as original, human-created work.
Permitted uses in Teaching & Learning: Instructors are expected to establish a course-specific guidance that defines the appropriate and inappropriate use of GenAI tools.
Students may only use GenAI tools to support their coursework in ways explicitly permitted by the instructor.
Non-permissible uses:
Do not Use GenAI to deliberately fabricate, falsify, impersonate, or mislead, unless explicitly approved for instruction or research in a controlled environment.
Do not Record or process sensitive, confidential, or regulated information withnon-MSU GenAI tools.
Do not Enter FERPA-protected student records, PII, PHI, financial, or HR data into unapproved tools; comply with MSU’s data policy and all regulations.
Do not Use export-controlled data or CUI with GenAI tools unless approved for MSU’s Regulated Research Enclave (RRE).
Developing and Communicating a Course-level Generative AI Use policy
A well-prepared course should be designed for ("restrict", "permit" or "require") or designed around ("ban") generative AI. Courses designed for AI should detail the ways and degrees to which generative AI use will be incorporated into activities and assessments. Courses designed for AI may incorporate AI for some activities and not others and depending on course AI may be explicitly excluded or included at different stages. Courses designed around AI may discuss impacts of generative AI as a topic but expectations are that students will not use these types of tools, and the course should be intentionally designed such that the use of generative AI would either not be conducive to the completion of assessments and activities, or such that the attempt to do so would prove overly cumbersome.
Regardless of your approach, communicating your expectations and rationale to learners is imperative.
Set clear expectations. Be clear in your syllabus about your policies for when, where, and how students should be using generative AI tools, and how to appropriately acknowledge (e.g., cite, reference) when they do use generative AI tools. If you are requiring students to use generative AI tools, these expectations should also be communicated in the syllabus and if students are incurring costs, these should be detailed in the course description on the Registrar’s website.
Regardless of your approach, you might include time for ethics discussions. Add time into your course to discuss the ethical implications of chatGPT and forthcoming AI systems. Talk with students about the ethics of using generative AI tools in your course, at your university, and within your discipline or profession. Don’t be afraid to discuss the gray areas where we do not yet have clear guidance or answers; gray areas are often the places where learning becomes most engaging.
Example Syllabus Statements for the Use of AI Tools in Your Course
There is no “one size fits all policy” for AI uses in higher education. Much like attendance/participation policies, GenAI course-level rules and statements will be determined by individual instructors, departments, and programs. The following resource is provided to assist you in developing coherent policies on the use of generative AI tools in your course, within MSU's guideline. Please adjust these examples to fit your particular context. Remember communication of your course generative AI policies should not only be listed in your syllabus, but also explicitly included in assignment descriptions where AI use is allowed or disallowed.
It is your responsibility as instructor to note and explain your individual course-level rule. A conversation with your department is highly recommended so that generative AI use in the classroom reflects broader use in the unit and discipline. If you have specific questions about writing your course rules, please reach out to the Center for Teaching and Learning Innovation.
Design For Generative AI
Restrict [This syllabus statement is useful when you are allowing the use of AI tools for certain purposes, but not for others. Adjust this statement to reflect your particular parameters of acceptable use. The following is an example.]
Example1:
The use of generative AI tools (e.g. ChatGPT, Dall-e, etc.) is permitted in this course for the following activities:
[insert permitted your course activities here*]
The use of generative AI tools is not permitted in this course for the following activities:
[insert not permitted your course activities here*]
You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge.
Example2: Taken, with slight modification, from Temple University’s Center for the Advancement of Teaching to demonstrate the kinds of permitted/restricted activity an instructor could denote.
The use of generative AI tools (e.g. ChatGPT, Dall-e, etc.) is permitted in this course for the following activities:
Brainstorming and refining your ideas;
Fine tuning your research questions;
Finding information on your topic;
Drafting an outline to organize your thoughts; and
Checking grammar and style.
The use of generative AI tools is not permitted in this course for the following activities:
Impersonating you in classroom contexts, such as by using the tool to compose discussion board prompts assigned to you or content that you put into a Zoom chat.
Completing group work that your group has assigned to you, unless it is mutually agreed within your group and in alignment with course policy that you may utilize the tool.
Writing a draft of a writing assignment.
Writing entire sentences, paragraphs or papers to complete class assignments.
You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge. For example, [Insert citation style for your discipline. See these resources for APA guidance, and for other citation formats.]. Any assignment that is found to have used generative AI tools in unauthorized ways [insert the penalty here*]. When in doubt about permitted usage, please ask for clarification.
Use permitted [This syllabus statement is useful when you are allowing, and perhaps encouraging, broad use of generative AI tools. Adjust this statement to reflect your particular parameters of acceptable use in your course. The following is an example.]
Example:
You are welcome to use generative AI tools (e.g. ChatGPT, Dall-e, etc.) in this class as doing so aligns with the course learning goal [insert the course learning goal use of AI aligns with here*]. You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge.
Use required [This syllabus statement is useful when you have certain assignments that will require that students use generative AI tools. Adjust this statement to reflect your particular parameters of acceptable use. The following is an example.]
Example:
You will be expected to use generative AI tools (e.g. ChatGPT, Dall-e, etc.) in this class as doing so aligns with the course learning goal [insert the course learning goal use of AI aligns with]. Our class will make use of the [insert name of tool(s) here*] tool, and you can gain access to it by [insert instructions for accessing tool(s) here*]. You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge.
Design Around Generative AI
Ban [This syllabus statement is useful when you are forbidding all use of generative AI tools for any purpose in your class. Adjust this statement to reflect your particular parameters of acceptable use. The following is an example.]
The use of generative AI tools (such as ChatGPT, DALL-E, etc.) is not permitted in this class; therefore, any use of AI tools for work in this class may be considered a violation of Michigan State University’s policy on academic integrity, the Spartan Code of Honor Academic Pledge andStudent Rights and Responsibilities, since the work is not your own. The use of unauthorized AI tools will result in [insert the penalty here*].
CONCERN: The ubiquity of generative AI tools, including their integration into Google search results and MS Office products, means that an outright generative AI ban is implausible for any activity that makes use of the Internet or MS Office Suite.
* It is highly recommended that you have conversations in your department about the appropriate penalties for unauthorized use of an AI. It is important to think about the appropriate level of penalty for first-time offenders and those who repeatedly violate your policies on the use of AI.
Example Statements from Current USA, Higher Education Educators
This collection of example statements are a compilation from a variety of sources including Faculty Learning Community (FLC) at Cleveland State University, Ohio University’s AI, ChatGPT and Teaching and Learning, and some of Michigan State University’s own educators! (If you have an example generative AI policy from your course that you’d be willing to share, please add it to the comments below or e-mail it to MSU Center for Teaching and Learning Innovation at teaching@msu.edu) NOTE: making your own course-level determination of "ban", "restrict", "permit", or "require" and using the sample language is the best, first place to start!
“AI (artificial intelligence) resources such as ChatGPT can be useful in a number of ways. Because it can also be abused, however, you are required to acknowledge use of AI in any work you submit for class. Text directly copied from AI sites must be treated as any other direct quote and properly cited. Other uses of AI must be clearly described at the end of your assignment.” -Claire Hughes-Lynch
“While AI tools can be useful for completing assignments and detecting plagiarism, it is important to use them responsibly and ethically. Practice based on these guidelines as a future or current K-12 teacher. The following are some guidelines for what not to do when using AI in your assignments and for plagiarism detection:
Do not rely solely on AI tools to complete assignments. It is important to understand the material and complete assignments on your own, using AI tools as a supplement rather than a replacement for your own work.
Do not use AI tools to plagiarize*. Using AI to generate or modify content to evade plagiarism detection is unethical and violates academic integrity.
Do not assume that AI responses are always correct. It has been noted that AI can generate fake results.* Please see the plagiarism/academic integrity policy in the course syllabus.” -Selma Koc
“Intellectual honesty is vital to an academic community and for my fair evaluation of your work. All work submitted in this course must be your own, completed in accordance with the University’s academic regulations. Use of AI tools, including ChatGPT, is permitted in this course. Nevertheless, you are only encouraged to use AI tools to help brainstorm assignments or projects or to revise existing work you have written. It is solely your responsibility to make all submitted work your own, maintain academic integrity, and avoid any type of plagiarism. Be aware that the accuracy or quality of AI generated content may not meet the standards of this course, even if you only incorporate such content partially and after substantial paraphrasing, modification and/or editing. Also keep in mind that AI generated content may not provide appropriate or clear attribution to the author(s) of the original sources, while most written assignments in this course require you to find and incorporate highly relevant peer-reviewed scholarly publications following guidelines in the latest publication manual of the APA. Lastly, as your instructor, I reserve the right to use various plagiarism checking tools in evaluating your work, including those screening for AI-generated content, and impose consequences accordingly.” -Xiongyi Liu
“If you are ever unsure about whether collaboration with others, including using artificial intelligence, is allowed or not, please ask me right away. For the labs, although you may discuss them in groups (and try using AI), you must all create your own code, output and answers. Quizzes will be done in class and must be solely your own work. You alone are always responsible for the correctness of the final answers and assignments you submit.” - Emily Rauschert on AI as collaboration partner
“Chat GPT: The use of Chat GTP is neither encouraged nor prohibited from use on assignments for GAD 250. Chat GPT is quickly becoming a communication tool in most business settings. Therefore, if you choose to use Chat GPT for assignments, please be sure to revise the content for clarity, conciseness, and audience awareness. Chat GPT is simply a tool and should not be used as a way to produce first and only drafts. Every assignment submission will be graded using the rubric provided in the syllabus. Be aware that Chat GPT may not develop high-quality work that earns a passing grade. It is your responsibility to review and revise all work before submitting to the instructor.” -Leah Schell-Barber for a Business Communications Course
“Use of Generative AI, such as ChatGPT and Microsoft Bing-Chat, must maintain the highest standards of academic integrity and adhere to the OU Code of Student Conduct. The use of Generative AI should be seen as a tool to enhance academic research, not as a replacement for critical thinking and originality in assignments. Students are not permitted to submit assignments that have been fully or partially generated by AI unless explicitly stated in the assignment instructions. All work submitted must be the original work of the student. Any ideas garnered from Generative AI research must be acknowledged with proper in-text citation and reference. Students may be asked to save the AI chat as a PDF file for verification.” -Ohio University College of Business Generative AI Use for Academic Work Policy
“‘The policy of this class is that you must be the creator of all work you submit for a grade. The use of others’ work, or the use of intelligent agents, chat bots, or a.i. engines to create your work is a violation of this policy and will be addressed as per MSU and Broad College codes of conduct.’ - Jeremy Van Hof… Or, you might consider this, which I asked ChatGPT to write for me: ‘Sample Policy Language: Students should not use ChatGPT to complete course assignments or for any other academic activities. ChatGPT should be used as a supplemental resource and should not replace traditional academic activities.’ (ChatGPT per Jeremy Van Hof’s prompting)
Or this much longer version, also written by ChatGPT: ‘The following course policy statement prohibits the use of Artificial Intelligence (AI) for the’ completion of assignments and activities during the duration of the course. At the Broad College, we strive to create an academic environment where learning is the foremost priority. We strongly believe that learning is best achieved through the hard work and dedication of our students. As such, we prohibit the use of Artificial Intelligence (AI) for the completion of assignments and activities during the course. Our policy is in line with our commitment to providing a fair and equitable learning environment for all students. We believe that AI should not be used to substitute human effort, as it defeats the purpose of our educational goals, which are to encourage critical thinking and problem-solving. We understand that AI can be a useful tool in many contexts, and we do not discourage its use in other courses. However, in this course, we will not accept assignments or activities that have been completed through the use of AI. We expect our students to be honest and to complete their work independently. We will be monitoring student work closely to ensure compliance with this policy. Violations of this policy will be met with disciplinary sanctions. All students are expected to adhere to this policy and to abide by the standards of the University.’ (ChatGPT per Jeremy Van Hof’s prompting)” -Jeremy Van Hof, Broad College of Business
“I study AI. I research it in my role as faculty in the Experience Architecture and Professional & Public Writing majors. And I don’t think it’s inherently bad or scary, in the same way that a calculator isn’t bad/scary for math. Artificial intelligence technologies such as ChatGPT can be an excellent starting point and a place to begin inquiry. But they are not a replacement for human thinking and learning. Robots lack empathy and nuance. As such, here is my policy:
You may use AI as a tool, but you may not use AI to replace your own beautiful brain. That means that you may ask ChatGPT, for example, to give you a list of bands similar to one that you hear and appreciate in this course. You may ask ChatGPT to give you an overview of a punk scene in a geographic location at a particular time. You may ask it for the history of punk rock and punk cultures. You may ask it what happened to Sid Vicious.
But you may not ask it to write on your behalf, and you must not turn in anything that has been written by ChatGPT and pass it off as your own for any assignment in this class, including discussion responses, papers, and exams. If you do so, I will know, and that will lead to an uncomfortable moment–and to you failing the assignment.
This is not meant to be punitive. It’s meant to reinforce how much I value you and your ideas and your intellect. In a face-to-face environment, we would have a lengthy conversation about AI, ethics, and human learning. If you want to have that conversation, I’m happy to do so via Zoom–email me!” -Kate Birdsall, asynchronous US23 course on punk-rock politics
Developing your Scholarly and Ethical Approaches to Generative AI
Taken, with slight modification, from “Update Your Course Syllabus for chatGPT” by Ryan Watkins, Professor of Educational Technology Leadership, and Human-Technology Collaboration at George Washington University in Washington DC (2022), via Medium.
Beyond Syllabi Language
Communicate your perspective about AI use. In addition to syllabus statements, consider talking with your students about AI tools like ChatGPT. Regardless of your orientation to generative AI use, it is important that you clearly communicate your expectations with the introduction of each assignment/assessment.
Different levels of familiarity: As an emerging technology, students will have differing levels of familiarity with these tools. For instance, while ChatGPT can write a grammatically correct paper or appear to solve a math problem, it may be unreliable and limited in scope. Discuss with students the uses and limitations of AI tools more broadly in addition to your perspective on their use in your class.
Connect to critical thinking skills: AI tools have many implications beyond the classroom. Consider talking with students about how to be engaged-consumers of AI content (e.g., how to identify trusted sources, reading critically, privacy concerns). Discuss how you and colleagues use AI in your own work.
Adapt assessments. AI tools are emerging and it can be incredibly difficult to make any assessment completely free from AI interference. Beyond a syllabus statement, you may also consider adapting your assessments to help reduce the usefulness of AI products. However before revising any assignment, it’s helpful to reflect on what exactly you want students to get out of the experience and share your expectations with your students. Is it just the end product, or does the process of creating the product play a significant role?
Create assessments that allow students to develop ideas over time. Depending on your class size, consider scaffolding assessments to be completed in small components (e.g., proposal, annotated bibliography, outline, first draft, revised drafts).
Ask students to connect their writing to specific course materials or current events. Students can draw from the course textbook, additional readings on Moodle or Blackboard, and even class discussion boards or in-class discussions.
Incorporate personal experiences and reflections. Provide students with opportunities to connect what they are learning to their own lives and experiences—stories unique to each individual.
Incorporate Multimedia Assessments. Consider developing or adapting assessments to include multimedia submissions (e.g., audio or video components). Also, consider peer-review and social annotation tools like Eli Review or Google Docs for students to use when responding to assigned readings or other materials.
Use class time. Ask students to complete writing assignments during class time (e.g. complete reading reflections at the beginning of class, or use exit tickets). Asking students to organize their ideas by writing during class may also support student engagement in other class activities such as discussions and group work.
Get Creative With Your Assignments: Visit “Update Your Course Syllabus for chatGPT” by Ryan Watkins (Medium article) for 10 ideas for creative assignments adapted for a classroom with chatGPT. You can mitigate the risk of students using chatGPT to cheat, and at the same time improve their knowledge and skills for appropriately using new AI technologies inside and outside the classroom.
Additional considerations to help you develop your generative AI philosophy (Watkins, 2022)
Expand your options. Consider your repertoire of instructional strategies. Atsusi Hirumi offers a guide to research-grounded strategies for any classroom. These are not, however, “a la carte” menus; you must use all of the steps of any strategy to gain the evidence-based benefits.
Reflect on your values. As Tyler Cowen pointed out, there will be those who gain and those that lose with the emergence of chatGPT and other generative AI tools. This is as true for students as it is for faculty and instructors. Be ready to openly discuss the ethical implications of generative AI tools with your students, along with the value of what you are teaching and why learning these are important to their futures.
Consider time. As discussed during Bryan Alexander’s webinar, chatGPT and other generative AI tools offer a short-cut to individuals who are short on time. Examine your course schedule to determine if you are unknowingly pushing students to take short-cuts. Some instructors try to cover too much content in their courses already.
Remember, AI is not human. Be careful not to anthropomorphize chatGPT and other generative AI tools. ChatGPT is a language model, and if we anthropomorphize these technologies, then it will be much harder to understand their promise and perils. Murray Shanahan suggests that we avoid statements such as, “chatGPT knows…”, or “ChatGPT thinks…”; instead, use “According to chatGPT…” or “ChatGPT’s output…”.
Again, AI is likely to be a part of your students’ life to some extent this semester, so plan accordingly. Critically considering your course design in the context of generative AI is an important educator practice. Following the Provost’s call, MSU instructors are encouraged to 1) develop a course-level generative AI use policy and actively discuss with students about expectations for generative AI use in the work for your class, 2) promote equitable and inclusive use of the technology, and 3) work with colleagues across campus to determine ethical and scholarly applications of generative AI for preparing students to succeed in an evolving digital landscape. MSU does not currently have a university-wide policy on AI in the classroom, so it is your responsibility as instructor to note and explain your individual course policy. A conversation with your department is highly recommended so that generative AI use in the classroom reflects that in the discipline.
References
This resource is collated from multiple sites, publications, and authors with some modification for MSU context and links to MSU specific resources. Educators should always defer to University policy and guidelines.
MSU Office of Student Support & Accountability Faculty Resources, including Academic Dishonesty Report form.
Watkins, R. (2022) Update Your Course Syllabus for chatGPT. Educational Technology Leadership, The George Washington University via Medium: https://medium.com/@rwatkins_7167/updating-your-course-syllabus-for-chatgpt-965f4b57b003
Center for the Advancement of Teaching (2023). Sample Syllabus Statements for the Use of AI Tools in Your Course. Temple University
Center for Teaching & Learning (2023) How Do I Consider the Impact of AI Tools like ChatGPT in My Courses?. University of Massachusetts Amherst. https://www.umass.edu/ctl/how-do-i-consider-impact-ai-tools-chatgpt-my-courses
Center for Teaching, Learning and Assessment (2023). AI, ChatGPT and Teaching and Learning. Ohio University. https://www.ohio.edu/center-teaching-learning/instructor-resources/chat-gpt
Office of Teaching, Learning, and Technology. (2023). Artificial Intelligence Tools and Teaching. Iowa University. https://teach.its.uiowa.edu/artificial-intelligence-tools-and-teaching
Center for New Designs in Learning and Scholarship (2023). Chat GPT and Artificial Intelligence Tools. Georgetown University. https://cndls.georgetown.edu/ai-composition-tools/#privacy-and-data-collection
Office for Faculty Excellence (2023). Practical Responses to ChatGPT. Montclair State University. https://www.montclair.edu/faculty-excellence/practical-responses-to-chat-gpt/
Teaching and Learning at Cleveland State University by Center for Faculty Excellence is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
You can also access the Generative AI Syllabus Guide Playlist with this content broken down into the following sections. Table of Contents:
MSU Guidance and [Non]Permitted Uses
Developing and Communicating a Course-level Generative AI Use policy
Example Syllabus Statements for the Use of AI Tools in Your Course
Design For Generative AI (restrict, permit, require)
Design Around Generative AI (ban)
Example Statements from Current USA, Higher Education Educators
Developing your Scholarly and Ethical Approaches to Generative AI
Beyond Syllabi Language
Additional considerations to help you develop your generative AI philosophy (Watkins, 2022)
References
The following MSU-specifics should be used to inform your decisions...
Overall guidance: We collectively share the responsibility to uphold intellectual honesty and scholarly integrity. These are core principles that may be compromised by the misuse of GenAI tools, particularly when GenAI-generated content is presented as original, human-created work.
Permitted uses in Teaching & Learning: Instructors are expected to establish a course-specific guidance that defines the appropriate and inappropriate use of GenAI tools.
Students may only use GenAI tools to support their coursework in ways explicitly permitted by the instructor.
Non-permissible uses:
Do not Use GenAI to deliberately fabricate, falsify, impersonate, or mislead, unless explicitly approved for instruction or research in a controlled environment.
Do not Record or process sensitive, confidential, or regulated information withnon-MSU GenAI tools.
Do not Enter FERPA-protected student records, PII, PHI, financial, or HR data into unapproved tools; comply with MSU’s data policy and all regulations.
Do not Use export-controlled data or CUI with GenAI tools unless approved for MSU’s Regulated Research Enclave (RRE).
Developing and Communicating a Course-level Generative AI Use policy
A well-prepared course should be designed for ("restrict", "permit" or "require") or designed around ("ban") generative AI. Courses designed for AI should detail the ways and degrees to which generative AI use will be incorporated into activities and assessments. Courses designed for AI may incorporate AI for some activities and not others and depending on course AI may be explicitly excluded or included at different stages. Courses designed around AI may discuss impacts of generative AI as a topic but expectations are that students will not use these types of tools, and the course should be intentionally designed such that the use of generative AI would either not be conducive to the completion of assessments and activities, or such that the attempt to do so would prove overly cumbersome.
Regardless of your approach, communicating your expectations and rationale to learners is imperative.
Set clear expectations. Be clear in your syllabus about your policies for when, where, and how students should be using generative AI tools, and how to appropriately acknowledge (e.g., cite, reference) when they do use generative AI tools. If you are requiring students to use generative AI tools, these expectations should also be communicated in the syllabus and if students are incurring costs, these should be detailed in the course description on the Registrar’s website.
Regardless of your approach, you might include time for ethics discussions. Add time into your course to discuss the ethical implications of chatGPT and forthcoming AI systems. Talk with students about the ethics of using generative AI tools in your course, at your university, and within your discipline or profession. Don’t be afraid to discuss the gray areas where we do not yet have clear guidance or answers; gray areas are often the places where learning becomes most engaging.
Example Syllabus Statements for the Use of AI Tools in Your Course
There is no “one size fits all policy” for AI uses in higher education. Much like attendance/participation policies, GenAI course-level rules and statements will be determined by individual instructors, departments, and programs. The following resource is provided to assist you in developing coherent policies on the use of generative AI tools in your course, within MSU's guideline. Please adjust these examples to fit your particular context. Remember communication of your course generative AI policies should not only be listed in your syllabus, but also explicitly included in assignment descriptions where AI use is allowed or disallowed.
It is your responsibility as instructor to note and explain your individual course-level rule. A conversation with your department is highly recommended so that generative AI use in the classroom reflects broader use in the unit and discipline. If you have specific questions about writing your course rules, please reach out to the Center for Teaching and Learning Innovation.
Design For Generative AI
Restrict [This syllabus statement is useful when you are allowing the use of AI tools for certain purposes, but not for others. Adjust this statement to reflect your particular parameters of acceptable use. The following is an example.]
Example1:
The use of generative AI tools (e.g. ChatGPT, Dall-e, etc.) is permitted in this course for the following activities:
[insert permitted your course activities here*]
The use of generative AI tools is not permitted in this course for the following activities:
[insert not permitted your course activities here*]
You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge.
Example2: Taken, with slight modification, from Temple University’s Center for the Advancement of Teaching to demonstrate the kinds of permitted/restricted activity an instructor could denote.
The use of generative AI tools (e.g. ChatGPT, Dall-e, etc.) is permitted in this course for the following activities:
Brainstorming and refining your ideas;
Fine tuning your research questions;
Finding information on your topic;
Drafting an outline to organize your thoughts; and
Checking grammar and style.
The use of generative AI tools is not permitted in this course for the following activities:
Impersonating you in classroom contexts, such as by using the tool to compose discussion board prompts assigned to you or content that you put into a Zoom chat.
Completing group work that your group has assigned to you, unless it is mutually agreed within your group and in alignment with course policy that you may utilize the tool.
Writing a draft of a writing assignment.
Writing entire sentences, paragraphs or papers to complete class assignments.
You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge. For example, [Insert citation style for your discipline. See these resources for APA guidance, and for other citation formats.]. Any assignment that is found to have used generative AI tools in unauthorized ways [insert the penalty here*]. When in doubt about permitted usage, please ask for clarification.
Use permitted [This syllabus statement is useful when you are allowing, and perhaps encouraging, broad use of generative AI tools. Adjust this statement to reflect your particular parameters of acceptable use in your course. The following is an example.]
Example:
You are welcome to use generative AI tools (e.g. ChatGPT, Dall-e, etc.) in this class as doing so aligns with the course learning goal [insert the course learning goal use of AI aligns with here*]. You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge.
Use required [This syllabus statement is useful when you have certain assignments that will require that students use generative AI tools. Adjust this statement to reflect your particular parameters of acceptable use. The following is an example.]
Example:
You will be expected to use generative AI tools (e.g. ChatGPT, Dall-e, etc.) in this class as doing so aligns with the course learning goal [insert the course learning goal use of AI aligns with]. Our class will make use of the [insert name of tool(s) here*] tool, and you can gain access to it by [insert instructions for accessing tool(s) here*]. You are responsible for the information you submit based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content). Your use of AI tools must be properly documented and cited in order to stay within university policies on academic integrity and the Spartan Code of Honor Academic Pledge.
Design Around Generative AI
Ban [This syllabus statement is useful when you are forbidding all use of generative AI tools for any purpose in your class. Adjust this statement to reflect your particular parameters of acceptable use. The following is an example.]
The use of generative AI tools (such as ChatGPT, DALL-E, etc.) is not permitted in this class; therefore, any use of AI tools for work in this class may be considered a violation of Michigan State University’s policy on academic integrity, the Spartan Code of Honor Academic Pledge andStudent Rights and Responsibilities, since the work is not your own. The use of unauthorized AI tools will result in [insert the penalty here*].
CONCERN: The ubiquity of generative AI tools, including their integration into Google search results and MS Office products, means that an outright generative AI ban is implausible for any activity that makes use of the Internet or MS Office Suite.
* It is highly recommended that you have conversations in your department about the appropriate penalties for unauthorized use of an AI. It is important to think about the appropriate level of penalty for first-time offenders and those who repeatedly violate your policies on the use of AI.
Example Statements from Current USA, Higher Education Educators
This collection of example statements are a compilation from a variety of sources including Faculty Learning Community (FLC) at Cleveland State University, Ohio University’s AI, ChatGPT and Teaching and Learning, and some of Michigan State University’s own educators! (If you have an example generative AI policy from your course that you’d be willing to share, please add it to the comments below or e-mail it to MSU Center for Teaching and Learning Innovation at teaching@msu.edu) NOTE: making your own course-level determination of "ban", "restrict", "permit", or "require" and using the sample language is the best, first place to start!
“AI (artificial intelligence) resources such as ChatGPT can be useful in a number of ways. Because it can also be abused, however, you are required to acknowledge use of AI in any work you submit for class. Text directly copied from AI sites must be treated as any other direct quote and properly cited. Other uses of AI must be clearly described at the end of your assignment.” -Claire Hughes-Lynch
“While AI tools can be useful for completing assignments and detecting plagiarism, it is important to use them responsibly and ethically. Practice based on these guidelines as a future or current K-12 teacher. The following are some guidelines for what not to do when using AI in your assignments and for plagiarism detection:
Do not rely solely on AI tools to complete assignments. It is important to understand the material and complete assignments on your own, using AI tools as a supplement rather than a replacement for your own work.
Do not use AI tools to plagiarize*. Using AI to generate or modify content to evade plagiarism detection is unethical and violates academic integrity.
Do not assume that AI responses are always correct. It has been noted that AI can generate fake results.* Please see the plagiarism/academic integrity policy in the course syllabus.” -Selma Koc
“Intellectual honesty is vital to an academic community and for my fair evaluation of your work. All work submitted in this course must be your own, completed in accordance with the University’s academic regulations. Use of AI tools, including ChatGPT, is permitted in this course. Nevertheless, you are only encouraged to use AI tools to help brainstorm assignments or projects or to revise existing work you have written. It is solely your responsibility to make all submitted work your own, maintain academic integrity, and avoid any type of plagiarism. Be aware that the accuracy or quality of AI generated content may not meet the standards of this course, even if you only incorporate such content partially and after substantial paraphrasing, modification and/or editing. Also keep in mind that AI generated content may not provide appropriate or clear attribution to the author(s) of the original sources, while most written assignments in this course require you to find and incorporate highly relevant peer-reviewed scholarly publications following guidelines in the latest publication manual of the APA. Lastly, as your instructor, I reserve the right to use various plagiarism checking tools in evaluating your work, including those screening for AI-generated content, and impose consequences accordingly.” -Xiongyi Liu
“If you are ever unsure about whether collaboration with others, including using artificial intelligence, is allowed or not, please ask me right away. For the labs, although you may discuss them in groups (and try using AI), you must all create your own code, output and answers. Quizzes will be done in class and must be solely your own work. You alone are always responsible for the correctness of the final answers and assignments you submit.” - Emily Rauschert on AI as collaboration partner
“Chat GPT: The use of Chat GTP is neither encouraged nor prohibited from use on assignments for GAD 250. Chat GPT is quickly becoming a communication tool in most business settings. Therefore, if you choose to use Chat GPT for assignments, please be sure to revise the content for clarity, conciseness, and audience awareness. Chat GPT is simply a tool and should not be used as a way to produce first and only drafts. Every assignment submission will be graded using the rubric provided in the syllabus. Be aware that Chat GPT may not develop high-quality work that earns a passing grade. It is your responsibility to review and revise all work before submitting to the instructor.” -Leah Schell-Barber for a Business Communications Course
“Use of Generative AI, such as ChatGPT and Microsoft Bing-Chat, must maintain the highest standards of academic integrity and adhere to the OU Code of Student Conduct. The use of Generative AI should be seen as a tool to enhance academic research, not as a replacement for critical thinking and originality in assignments. Students are not permitted to submit assignments that have been fully or partially generated by AI unless explicitly stated in the assignment instructions. All work submitted must be the original work of the student. Any ideas garnered from Generative AI research must be acknowledged with proper in-text citation and reference. Students may be asked to save the AI chat as a PDF file for verification.” -Ohio University College of Business Generative AI Use for Academic Work Policy
“‘The policy of this class is that you must be the creator of all work you submit for a grade. The use of others’ work, or the use of intelligent agents, chat bots, or a.i. engines to create your work is a violation of this policy and will be addressed as per MSU and Broad College codes of conduct.’ - Jeremy Van Hof… Or, you might consider this, which I asked ChatGPT to write for me: ‘Sample Policy Language: Students should not use ChatGPT to complete course assignments or for any other academic activities. ChatGPT should be used as a supplemental resource and should not replace traditional academic activities.’ (ChatGPT per Jeremy Van Hof’s prompting)
Or this much longer version, also written by ChatGPT: ‘The following course policy statement prohibits the use of Artificial Intelligence (AI) for the’ completion of assignments and activities during the duration of the course. At the Broad College, we strive to create an academic environment where learning is the foremost priority. We strongly believe that learning is best achieved through the hard work and dedication of our students. As such, we prohibit the use of Artificial Intelligence (AI) for the completion of assignments and activities during the course. Our policy is in line with our commitment to providing a fair and equitable learning environment for all students. We believe that AI should not be used to substitute human effort, as it defeats the purpose of our educational goals, which are to encourage critical thinking and problem-solving. We understand that AI can be a useful tool in many contexts, and we do not discourage its use in other courses. However, in this course, we will not accept assignments or activities that have been completed through the use of AI. We expect our students to be honest and to complete their work independently. We will be monitoring student work closely to ensure compliance with this policy. Violations of this policy will be met with disciplinary sanctions. All students are expected to adhere to this policy and to abide by the standards of the University.’ (ChatGPT per Jeremy Van Hof’s prompting)” -Jeremy Van Hof, Broad College of Business
“I study AI. I research it in my role as faculty in the Experience Architecture and Professional & Public Writing majors. And I don’t think it’s inherently bad or scary, in the same way that a calculator isn’t bad/scary for math. Artificial intelligence technologies such as ChatGPT can be an excellent starting point and a place to begin inquiry. But they are not a replacement for human thinking and learning. Robots lack empathy and nuance. As such, here is my policy:
You may use AI as a tool, but you may not use AI to replace your own beautiful brain. That means that you may ask ChatGPT, for example, to give you a list of bands similar to one that you hear and appreciate in this course. You may ask ChatGPT to give you an overview of a punk scene in a geographic location at a particular time. You may ask it for the history of punk rock and punk cultures. You may ask it what happened to Sid Vicious.
But you may not ask it to write on your behalf, and you must not turn in anything that has been written by ChatGPT and pass it off as your own for any assignment in this class, including discussion responses, papers, and exams. If you do so, I will know, and that will lead to an uncomfortable moment–and to you failing the assignment.
This is not meant to be punitive. It’s meant to reinforce how much I value you and your ideas and your intellect. In a face-to-face environment, we would have a lengthy conversation about AI, ethics, and human learning. If you want to have that conversation, I’m happy to do so via Zoom–email me!” -Kate Birdsall, asynchronous US23 course on punk-rock politics
Developing your Scholarly and Ethical Approaches to Generative AI
Taken, with slight modification, from “Update Your Course Syllabus for chatGPT” by Ryan Watkins, Professor of Educational Technology Leadership, and Human-Technology Collaboration at George Washington University in Washington DC (2022), via Medium.
Beyond Syllabi Language
Communicate your perspective about AI use. In addition to syllabus statements, consider talking with your students about AI tools like ChatGPT. Regardless of your orientation to generative AI use, it is important that you clearly communicate your expectations with the introduction of each assignment/assessment.
Different levels of familiarity: As an emerging technology, students will have differing levels of familiarity with these tools. For instance, while ChatGPT can write a grammatically correct paper or appear to solve a math problem, it may be unreliable and limited in scope. Discuss with students the uses and limitations of AI tools more broadly in addition to your perspective on their use in your class.
Connect to critical thinking skills: AI tools have many implications beyond the classroom. Consider talking with students about how to be engaged-consumers of AI content (e.g., how to identify trusted sources, reading critically, privacy concerns). Discuss how you and colleagues use AI in your own work.
Adapt assessments. AI tools are emerging and it can be incredibly difficult to make any assessment completely free from AI interference. Beyond a syllabus statement, you may also consider adapting your assessments to help reduce the usefulness of AI products. However before revising any assignment, it’s helpful to reflect on what exactly you want students to get out of the experience and share your expectations with your students. Is it just the end product, or does the process of creating the product play a significant role?
Create assessments that allow students to develop ideas over time. Depending on your class size, consider scaffolding assessments to be completed in small components (e.g., proposal, annotated bibliography, outline, first draft, revised drafts).
Ask students to connect their writing to specific course materials or current events. Students can draw from the course textbook, additional readings on Moodle or Blackboard, and even class discussion boards or in-class discussions.
Incorporate personal experiences and reflections. Provide students with opportunities to connect what they are learning to their own lives and experiences—stories unique to each individual.
Incorporate Multimedia Assessments. Consider developing or adapting assessments to include multimedia submissions (e.g., audio or video components). Also, consider peer-review and social annotation tools like Eli Review or Google Docs for students to use when responding to assigned readings or other materials.
Use class time. Ask students to complete writing assignments during class time (e.g. complete reading reflections at the beginning of class, or use exit tickets). Asking students to organize their ideas by writing during class may also support student engagement in other class activities such as discussions and group work.
Get Creative With Your Assignments: Visit “Update Your Course Syllabus for chatGPT” by Ryan Watkins (Medium article) for 10 ideas for creative assignments adapted for a classroom with chatGPT. You can mitigate the risk of students using chatGPT to cheat, and at the same time improve their knowledge and skills for appropriately using new AI technologies inside and outside the classroom.
Additional considerations to help you develop your generative AI philosophy (Watkins, 2022)
Expand your options. Consider your repertoire of instructional strategies. Atsusi Hirumi offers a guide to research-grounded strategies for any classroom. These are not, however, “a la carte” menus; you must use all of the steps of any strategy to gain the evidence-based benefits.
Reflect on your values. As Tyler Cowen pointed out, there will be those who gain and those that lose with the emergence of chatGPT and other generative AI tools. This is as true for students as it is for faculty and instructors. Be ready to openly discuss the ethical implications of generative AI tools with your students, along with the value of what you are teaching and why learning these are important to their futures.
Consider time. As discussed during Bryan Alexander’s webinar, chatGPT and other generative AI tools offer a short-cut to individuals who are short on time. Examine your course schedule to determine if you are unknowingly pushing students to take short-cuts. Some instructors try to cover too much content in their courses already.
Remember, AI is not human. Be careful not to anthropomorphize chatGPT and other generative AI tools. ChatGPT is a language model, and if we anthropomorphize these technologies, then it will be much harder to understand their promise and perils. Murray Shanahan suggests that we avoid statements such as, “chatGPT knows…”, or “ChatGPT thinks…”; instead, use “According to chatGPT…” or “ChatGPT’s output…”.
Again, AI is likely to be a part of your students’ life to some extent this semester, so plan accordingly. Critically considering your course design in the context of generative AI is an important educator practice. Following the Provost’s call, MSU instructors are encouraged to 1) develop a course-level generative AI use policy and actively discuss with students about expectations for generative AI use in the work for your class, 2) promote equitable and inclusive use of the technology, and 3) work with colleagues across campus to determine ethical and scholarly applications of generative AI for preparing students to succeed in an evolving digital landscape. MSU does not currently have a university-wide policy on AI in the classroom, so it is your responsibility as instructor to note and explain your individual course policy. A conversation with your department is highly recommended so that generative AI use in the classroom reflects that in the discipline.
References
This resource is collated from multiple sites, publications, and authors with some modification for MSU context and links to MSU specific resources. Educators should always defer to University policy and guidelines.
MSU Office of Student Support & Accountability Faculty Resources, including Academic Dishonesty Report form.
Watkins, R. (2022) Update Your Course Syllabus for chatGPT. Educational Technology Leadership, The George Washington University via Medium: https://medium.com/@rwatkins_7167/updating-your-course-syllabus-for-chatgpt-965f4b57b003
Center for the Advancement of Teaching (2023). Sample Syllabus Statements for the Use of AI Tools in Your Course. Temple University
Center for Teaching & Learning (2023) How Do I Consider the Impact of AI Tools like ChatGPT in My Courses?. University of Massachusetts Amherst. https://www.umass.edu/ctl/how-do-i-consider-impact-ai-tools-chatgpt-my-courses
Center for Teaching, Learning and Assessment (2023). AI, ChatGPT and Teaching and Learning. Ohio University. https://www.ohio.edu/center-teaching-learning/instructor-resources/chat-gpt
Office of Teaching, Learning, and Technology. (2023). Artificial Intelligence Tools and Teaching. Iowa University. https://teach.its.uiowa.edu/artificial-intelligence-tools-and-teaching
Center for New Designs in Learning and Scholarship (2023). Chat GPT and Artificial Intelligence Tools. Georgetown University. https://cndls.georgetown.edu/ai-composition-tools/#privacy-and-data-collection
Office for Faculty Excellence (2023). Practical Responses to ChatGPT. Montclair State University. https://www.montclair.edu/faculty-excellence/practical-responses-to-chat-gpt/
Teaching and Learning at Cleveland State University by Center for Faculty Excellence is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Posted by:
Makena Neal
Posted on: GenAI & Education
Complete Guide to Incorporating Generative AI in Your Syllabus
(Photo by Steve Johnson on Unsplash )
You can also access the Gener...
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Posted by:
PEDAGOGICAL DESIGN
Monday, Aug 18, 2025
Posted on: Teaching Toolkit Tailgate
PEDAGOGICAL DESIGN
Using Mind Maps for Learning
Photo by Sigmund on Unsplash
What Are Mind Maps?
Mind maps are visual representations of concepts. They begin with the main idea or topic in the middle. Then key words or images radiate outward to increasingly specific examples or tangent ideas.
Why Are Mind Maps Useful?
Mind maps aid retention and recall. Multiple works discuss the importance of linking new material to existing information to retain and later recall the new material. Since mind maps are personalized and encourage multiple connections, they assist with this process.
Mind maps also help with higher-order processing. Students can apply key concepts by providing examples, usually at the end of branches. They can analyze and summarize key points. Creating an idea web requires reducing information to a few key words or images. When you trace a branch from the center outward you can reduce a broad topic to a concrete and specific example. Linking branch concepts succinctly ties together elements.
Students can use mind maps to assemble and create essays. The activity of making multiple connections between similarly themed concepts can suggest different orders for papers and help smooth transitions. Mind maps can also demonstrate areas where more detail is needed or where a student may have a particular interest worth exploring. Thus, idea webs can be used in the brainstorming or revision stages of writing.
Potential Mind Map Challenges
Some students may have little experience with idea webs. You must take the time to introduce how to create them. Introducing the context, why mind maps are useful, is also important
Mind maps can be highly personal. Acclimating students to mind maps by describing how they can be created and why they are important is not the only challenge in implementing them in a classroom. Without similar prior knowledge or experiences certain connections may not make sense to other individuals. For this reason I have found it more useful to have students create their own maps rather than lead a discussion around one already created.
Students may feel uncomfortable with the nonlinear nature of how ideas are presented.. Students may prefer static, limited connections when learning new material. While idea webs ultimately help create order between concepts by demonstrating the links, the free-flow nature can sometimes overwhelm. Reminding students how to read mind maps, from the inside outward, can help. Repeated exposure to idea webs also helps build familiarity, leading to more comfort with their use. Of course, not all tools work for all students.
Many students will benefit from the fact that mind maps present material and connections visually. Mind maps foster connections between concepts and new and learned content. These links can assist with retention and in developing high-order learning.
What Are Mind Maps?
Mind maps are visual representations of concepts. They begin with the main idea or topic in the middle. Then key words or images radiate outward to increasingly specific examples or tangent ideas.
Why Are Mind Maps Useful?
Mind maps aid retention and recall. Multiple works discuss the importance of linking new material to existing information to retain and later recall the new material. Since mind maps are personalized and encourage multiple connections, they assist with this process.
Mind maps also help with higher-order processing. Students can apply key concepts by providing examples, usually at the end of branches. They can analyze and summarize key points. Creating an idea web requires reducing information to a few key words or images. When you trace a branch from the center outward you can reduce a broad topic to a concrete and specific example. Linking branch concepts succinctly ties together elements.
Students can use mind maps to assemble and create essays. The activity of making multiple connections between similarly themed concepts can suggest different orders for papers and help smooth transitions. Mind maps can also demonstrate areas where more detail is needed or where a student may have a particular interest worth exploring. Thus, idea webs can be used in the brainstorming or revision stages of writing.
Potential Mind Map Challenges
Some students may have little experience with idea webs. You must take the time to introduce how to create them. Introducing the context, why mind maps are useful, is also important
Mind maps can be highly personal. Acclimating students to mind maps by describing how they can be created and why they are important is not the only challenge in implementing them in a classroom. Without similar prior knowledge or experiences certain connections may not make sense to other individuals. For this reason I have found it more useful to have students create their own maps rather than lead a discussion around one already created.
Students may feel uncomfortable with the nonlinear nature of how ideas are presented.. Students may prefer static, limited connections when learning new material. While idea webs ultimately help create order between concepts by demonstrating the links, the free-flow nature can sometimes overwhelm. Reminding students how to read mind maps, from the inside outward, can help. Repeated exposure to idea webs also helps build familiarity, leading to more comfort with their use. Of course, not all tools work for all students.
Many students will benefit from the fact that mind maps present material and connections visually. Mind maps foster connections between concepts and new and learned content. These links can assist with retention and in developing high-order learning.
Authored by:
Danielle Kaminski
Posted on: Teaching Toolkit Tailgate
Using Mind Maps for Learning
Photo by Sigmund on Unsplash
What Are Mind Maps?
Mind...
What Are Mind Maps?
Mind...
Authored by:
PEDAGOGICAL DESIGN
Tuesday, Jul 14, 2020
Posted on: Teaching Toolkit Tailgate
PEDAGOGICAL DESIGN
Lighten Your Load: 3 Ways to Make Group Feedback More Efficient
Photo by Tony Hand on Unsplash
While individual feedback can be useful for attending to specific aspects of individual students’ work, we’ve found students sometimes exhibit similar strengths and challenges. These are moments when your time might be better used identifying commonalities across a class and using these commonalities as teaching opportunities. Below, find three different ways to effectively structure group feedback.
Identify Class Patterns (Teacher-to-Class Feedback): Much of the labor of providing responses to students comes from writing to each student individually. It can help to identify when individual responses are necessary, when responses to an entire class might be more pedagogically efficient, and when to deliver feedback to an entire class. To do this, we:
Read through projects and identify patterns. For example, in a recent project we assigned, we found many students were performing well in terms of citing sources and crafting mechanically correct sentences, but had similar problems with organization and offering critical analysis. Because of the pervasiveness of his concerns, we interpreted these issues as something worth spending time on in class.
Address comments to the whole class. We do qualify our feedback, noting that not all students have the same strengths and weaknesses, but that what we are identifying are general patterns.
Offer to meet students individually during office hours if they have questions. Having identified specific concerns, these meetings often run much quicker than they would without specific goals.
Redistribute the Labor of Identifying Patterns (Student-to-Class Feedback): We’ve already recommended redistributing the labor of offering individualized feedback. You can do the same thing by asking students to identify patterns across the class’ work. To do this, we:
Model feedback! We told you this before, we are telling you now, and you should tell yourself this over and over again. By modeling feedback (i.e. walking through the ways you would respond to a project), you are teaching students how to respond to each other, as well as how to read and understand your comments.
Give students projects to assess. This helps students get a fuller view of the work being done across the class, allowing them to begin to notice patterns and to think about their work in relation to the work done by their classmates.
Ask students to look for patterns. We found there are several good ways to have students identify patterns: he sometimes asks students to identify strengths and weaknesses from a corpus of work; or, closer to high-stakes evaluations (or grading moments), we’ll ask them to rate performance along a specific evaluation criterion.
Ask students to generalize. What do strong projects do? What about weaker projects? Have students articulate moves that make strong projects strong. This is a place where you can intervene and offer your perspective about what makes work succeed in your class, (especially in relation to specific evaluation criteria).
Ask students to develop revision strategies. Once your class has articulated the features of good performance, ask students to and develop specific strategies for revising their own work.
Facilitate Student-to-Student Feedback (Small Group Feedback): If you like peer review but are having mixed results, structuring smaller groups of students (2-3) could help you guide student responses to the whole group. To do this, we:
Ask students to identify problems. Heather typically asks students to choose no more than three struggles from their project (“I am having a little trouble organizing my paragraphs”) or process (“I am not sure how to revise my argument”). This gives small group members (and you) specific ways to give feedback.
Ask students to respond to group member concerns. Whether their responses are physically on a group member’s paper, embedded as a digital comment, or written in a brief response memo, ask all small group members to read and respond to each other’s concerns.
Meet with small groups and facilitate feedback. Have a student share their concerns, ask their group members to provide feedback, and facilitate any questions that come up from the discussion. This could range from how to apply specific feedback to their writing or sometimes what to do if feedback from group members don’t seem helpful.
While individual feedback can be useful for attending to specific aspects of individual students’ work, we’ve found students sometimes exhibit similar strengths and challenges. These are moments when your time might be better used identifying commonalities across a class and using these commonalities as teaching opportunities. Below, find three different ways to effectively structure group feedback.
Identify Class Patterns (Teacher-to-Class Feedback): Much of the labor of providing responses to students comes from writing to each student individually. It can help to identify when individual responses are necessary, when responses to an entire class might be more pedagogically efficient, and when to deliver feedback to an entire class. To do this, we:
Read through projects and identify patterns. For example, in a recent project we assigned, we found many students were performing well in terms of citing sources and crafting mechanically correct sentences, but had similar problems with organization and offering critical analysis. Because of the pervasiveness of his concerns, we interpreted these issues as something worth spending time on in class.
Address comments to the whole class. We do qualify our feedback, noting that not all students have the same strengths and weaknesses, but that what we are identifying are general patterns.
Offer to meet students individually during office hours if they have questions. Having identified specific concerns, these meetings often run much quicker than they would without specific goals.
Redistribute the Labor of Identifying Patterns (Student-to-Class Feedback): We’ve already recommended redistributing the labor of offering individualized feedback. You can do the same thing by asking students to identify patterns across the class’ work. To do this, we:
Model feedback! We told you this before, we are telling you now, and you should tell yourself this over and over again. By modeling feedback (i.e. walking through the ways you would respond to a project), you are teaching students how to respond to each other, as well as how to read and understand your comments.
Give students projects to assess. This helps students get a fuller view of the work being done across the class, allowing them to begin to notice patterns and to think about their work in relation to the work done by their classmates.
Ask students to look for patterns. We found there are several good ways to have students identify patterns: he sometimes asks students to identify strengths and weaknesses from a corpus of work; or, closer to high-stakes evaluations (or grading moments), we’ll ask them to rate performance along a specific evaluation criterion.
Ask students to generalize. What do strong projects do? What about weaker projects? Have students articulate moves that make strong projects strong. This is a place where you can intervene and offer your perspective about what makes work succeed in your class, (especially in relation to specific evaluation criteria).
Ask students to develop revision strategies. Once your class has articulated the features of good performance, ask students to and develop specific strategies for revising their own work.
Facilitate Student-to-Student Feedback (Small Group Feedback): If you like peer review but are having mixed results, structuring smaller groups of students (2-3) could help you guide student responses to the whole group. To do this, we:
Ask students to identify problems. Heather typically asks students to choose no more than three struggles from their project (“I am having a little trouble organizing my paragraphs”) or process (“I am not sure how to revise my argument”). This gives small group members (and you) specific ways to give feedback.
Ask students to respond to group member concerns. Whether their responses are physically on a group member’s paper, embedded as a digital comment, or written in a brief response memo, ask all small group members to read and respond to each other’s concerns.
Meet with small groups and facilitate feedback. Have a student share their concerns, ask their group members to provide feedback, and facilitate any questions that come up from the discussion. This could range from how to apply specific feedback to their writing or sometimes what to do if feedback from group members don’t seem helpful.
Authored by:
Heather Noel Turner & Matt Gomes
Posted on: Teaching Toolkit Tailgate
Lighten Your Load: 3 Ways to Make Group Feedback More Efficient
Photo by Tony Hand on Unsplash
While individual feedback can...
While individual feedback can...
Authored by:
PEDAGOGICAL DESIGN
Tuesday, Jul 14, 2020
Posted on: Teaching Toolkit Tailgate
PEDAGOGICAL DESIGN
Facilitating Independent Group Projects
Photo by Annie Spratt on Unsplash
Issue #1: Students Don’t See the Value of Independent Projects
Tips
Emphasize the real-world skills that students gain. This can be particularly valuable for students who aren’t necessarily interested in the subject matter but can see the benefits they gain in other areas, such as problem solving and managing a team.
Explain how each component of the independent project emulates a real practice in the discipline. This communicates to your students that you are putting them through this experience to help them develop their competencies, not to waste their time.
Treat every pitfall as a lesson, not as an opportunity to point out deficiencies. If something goes wrong, help the students figure out a way to move forward. Then, ask the students what they learned from the experience (e.g., how to better communicate, the value of a contingency plan, time management) and how they might strategize differently if confronted with a similar situation.
Issue #2: Designing and Conducting Independent Projects is Overwhelming
Tips
Break down the project into manageable goals. Create a guide for students that details out the specific steps that lead to the end product, which includes due dates for smaller components of the project. This will help students feel competent as they achieve each small task and to better manage their time.
Provide iterative feedback. If the only evaluation students receive on their work is their final project grade, they don’t have the opportunity to improve and learn along the way. Checking in with students as they reach each small goal allows both students and instructor to keep track of progress and to make adjustments if a group has gotten off-course.
Take time in class to praise students for their progress. Students may have trouble perceiving their accomplishments, so bringing them up will help to increase student confidence moving forward with the project.
Help groups work through challenges in a structured manner. Ask groups to bring up challenges they have encountered lately, and run a brainstorming session with the entire class to overcome these challenges. Often, other groups will have encountered similar challenges, so working through them together helps students feel more competent and build a sense of community among classmates.
Issue #3: Group Members do not Contribute Equally
Tips
Have students create a team contract. Provide students with a general template for a group contract with space to detail procedures for written communication among teammates, goals for the project, and consequences for group members who don’t pull their weight. All students should contribute to the creation of the contract and sign it. If an issue arises at any point during the project, the group has a clear path forward to correct the issue.
Build in opportunities for every member to contribute. The threat of being held individually accountable is often enough motivation for students to pull their weight. Take time in class to consult with each group individually or run brainstorming sessions with the entire class, asking individual students to share their experience or discuss project results.
Issue #4: Group Members Have Disparate Goals
Tips
Form groups based on mutual interests. Ask students to sit in different sections of the classroom based on potential project topics, then organize the students into groups based on their “interest zone.” An added bonus to this approach is that student groups will automatically have something in common, which can help them form social bonds and increase the enjoyment of working together.
Make time at the start of the project for students to discuss goals. Talking about how the project might relate to their goals for the course, their undergraduate education, and/or their career helps students understand the motivations of their teammates. When group members understand each other’s motivations, they can adjust their expectations and support the achievement of a variety of goals.
While your students may not enjoy the long hours, issues with teammates, and frustrations that accompany the independent group project, they may come to appreciate the lessons learned from their experiences. An example of working through a road block on their project could become a scenario they describe in a job interview. Dealing with an uncooperative group member could inform their approach to team management in their career. Engaging in inquiry could become the foundation for a student’s decision to pursue graduate school. Keep these outcomes in mind, and make every effort to put a positive spin on student progress.
Issue #1: Students Don’t See the Value of Independent Projects
Tips
Emphasize the real-world skills that students gain. This can be particularly valuable for students who aren’t necessarily interested in the subject matter but can see the benefits they gain in other areas, such as problem solving and managing a team.
Explain how each component of the independent project emulates a real practice in the discipline. This communicates to your students that you are putting them through this experience to help them develop their competencies, not to waste their time.
Treat every pitfall as a lesson, not as an opportunity to point out deficiencies. If something goes wrong, help the students figure out a way to move forward. Then, ask the students what they learned from the experience (e.g., how to better communicate, the value of a contingency plan, time management) and how they might strategize differently if confronted with a similar situation.
Issue #2: Designing and Conducting Independent Projects is Overwhelming
Tips
Break down the project into manageable goals. Create a guide for students that details out the specific steps that lead to the end product, which includes due dates for smaller components of the project. This will help students feel competent as they achieve each small task and to better manage their time.
Provide iterative feedback. If the only evaluation students receive on their work is their final project grade, they don’t have the opportunity to improve and learn along the way. Checking in with students as they reach each small goal allows both students and instructor to keep track of progress and to make adjustments if a group has gotten off-course.
Take time in class to praise students for their progress. Students may have trouble perceiving their accomplishments, so bringing them up will help to increase student confidence moving forward with the project.
Help groups work through challenges in a structured manner. Ask groups to bring up challenges they have encountered lately, and run a brainstorming session with the entire class to overcome these challenges. Often, other groups will have encountered similar challenges, so working through them together helps students feel more competent and build a sense of community among classmates.
Issue #3: Group Members do not Contribute Equally
Tips
Have students create a team contract. Provide students with a general template for a group contract with space to detail procedures for written communication among teammates, goals for the project, and consequences for group members who don’t pull their weight. All students should contribute to the creation of the contract and sign it. If an issue arises at any point during the project, the group has a clear path forward to correct the issue.
Build in opportunities for every member to contribute. The threat of being held individually accountable is often enough motivation for students to pull their weight. Take time in class to consult with each group individually or run brainstorming sessions with the entire class, asking individual students to share their experience or discuss project results.
Issue #4: Group Members Have Disparate Goals
Tips
Form groups based on mutual interests. Ask students to sit in different sections of the classroom based on potential project topics, then organize the students into groups based on their “interest zone.” An added bonus to this approach is that student groups will automatically have something in common, which can help them form social bonds and increase the enjoyment of working together.
Make time at the start of the project for students to discuss goals. Talking about how the project might relate to their goals for the course, their undergraduate education, and/or their career helps students understand the motivations of their teammates. When group members understand each other’s motivations, they can adjust their expectations and support the achievement of a variety of goals.
While your students may not enjoy the long hours, issues with teammates, and frustrations that accompany the independent group project, they may come to appreciate the lessons learned from their experiences. An example of working through a road block on their project could become a scenario they describe in a job interview. Dealing with an uncooperative group member could inform their approach to team management in their career. Engaging in inquiry could become the foundation for a student’s decision to pursue graduate school. Keep these outcomes in mind, and make every effort to put a positive spin on student progress.
Authored by:
Kateri Salk
Posted on: Teaching Toolkit Tailgate
Facilitating Independent Group Projects
Photo by Annie Spratt on Unsplash
Issue #1: Students Don’t S...
Issue #1: Students Don’t S...
Authored by:
PEDAGOGICAL DESIGN
Tuesday, Jul 14, 2020
Posted on: Teaching Toolkit Tailgate
PEDAGOGICAL DESIGN
Cooperative Learning in Action
Photo by Brooke Cagle on Unsplash
The key to successfully implementing cooperative learning is aligning it with learning objectives. Cooperative learning activities aren’t extras, but essential steps toward optimal learning. Some topics could include concepts that will be emphasized on the exam, big ideas for the day, and items that are difficult for students to master. The better integrated these activities are, the easier it will be to select approaches that meet your overall course objectives.
It may seem like an intimidating task to implement cooperative learning in a lecture-based course. Completely redesigning a course involves significant time and effort, and graduate student assistants often don’t have the freedom to dictate the classroom structure. The good news is that cooperative learning can be incorporated into courses in small, low-stakes ways. The following are three strategies that can be integrated into your curriculum next semester and accomplished within 5-15 minutes. I would suggest starting here:
Think-pair-share
Instructors pose a question or discussion topic (e.g., “Based on what you know about global wind and ocean currents, describe why the wave height in the Southern Ocean is an average of two meters higher than in the Equatorial Pacific”). Instructors then give students individual reflection time to process the question and to think about their answer. Following this silent period, students are then asked to pair up with another student to discuss their answer and to resolve any differences (if there is a correct answer to the question). The class can then come together as a large group once again, and the instructor can call on individual groups to share their discussions. This approach encourages students to explore and demonstrate their understanding of key concepts prior to a high-stakes exam in a way that is not possible in a lecture format.
Bonus: The pair step is a great opportunity for the instructor to walk throughout the room to monitor the discussion groups and connect with students on a more individual basis. The share step can be used to assess the distribution of ideas among students and identify sticky points that may require additional attention. This approach also allows students to speak up in class after vetting their thoughts with another student, which helps to decrease public speaking anxiety.
Minute Paper
Similarly to the think-pair-share activity, instructors pose a question or discussion topic. Instructors then provide time (typically under three minutes) for students to write down their ideas . This could be specified as anything from a “brain dump” (e.g., “Discuss the factors that dictate the growth of algae in the Arctic Ocean”) to a more structured form (“e.g., How would you design an experiment to measure the effect of temperature and light on algal growth in the Arctic Ocean?”). Students can then team up into small groups to discuss their answers and come to a consensus or perspective on the major ideas from the question. Following small group time, a few groups can be asked to report out to the whole class about their discussion.
Bonus: Positive interdependence can be achieved by assigning group members specific roles (e.g., recorder, checker, task manager, and spokesperson). These roles can be rotated each time the activity is used to allow students to practice each communication skill.
Jigsaw
This learning strategy works well for course concepts that can be split up into separate yet interconnected parts. Each part thus represents a piece of the puzzle, and the complete puzzle requires each individual piece to be complete. The jigsaw approach is split into two steps: the expert group meeting and the jigsaw group meeting. In the expert group meeting, instructors split students into small groups that are each assigned one part of the relevant content. Expert groups are assigned to discuss their “puzzle piece” and to achieve a consensus or mastery of their component. Expert groups are then dissolved and new jigsaw groups are formed, made up of one person from each expert group. In the jigsaw group meeting, each “expert ambassador” has a chance to report to the group about his or her piece of the puzzle. Jigsaw groups are then assigned the task of connecting each component to form a complete picture of the concept.
Bonus: Keep in mind that this method, while rich in discussion opportunities, requires the most logistical planning and organizational support of the three strategies outlined. For further reading, see https://www.jigsaw.org.
The key to successfully implementing cooperative learning is aligning it with learning objectives. Cooperative learning activities aren’t extras, but essential steps toward optimal learning. Some topics could include concepts that will be emphasized on the exam, big ideas for the day, and items that are difficult for students to master. The better integrated these activities are, the easier it will be to select approaches that meet your overall course objectives.
It may seem like an intimidating task to implement cooperative learning in a lecture-based course. Completely redesigning a course involves significant time and effort, and graduate student assistants often don’t have the freedom to dictate the classroom structure. The good news is that cooperative learning can be incorporated into courses in small, low-stakes ways. The following are three strategies that can be integrated into your curriculum next semester and accomplished within 5-15 minutes. I would suggest starting here:
Think-pair-share
Instructors pose a question or discussion topic (e.g., “Based on what you know about global wind and ocean currents, describe why the wave height in the Southern Ocean is an average of two meters higher than in the Equatorial Pacific”). Instructors then give students individual reflection time to process the question and to think about their answer. Following this silent period, students are then asked to pair up with another student to discuss their answer and to resolve any differences (if there is a correct answer to the question). The class can then come together as a large group once again, and the instructor can call on individual groups to share their discussions. This approach encourages students to explore and demonstrate their understanding of key concepts prior to a high-stakes exam in a way that is not possible in a lecture format.
Bonus: The pair step is a great opportunity for the instructor to walk throughout the room to monitor the discussion groups and connect with students on a more individual basis. The share step can be used to assess the distribution of ideas among students and identify sticky points that may require additional attention. This approach also allows students to speak up in class after vetting their thoughts with another student, which helps to decrease public speaking anxiety.
Minute Paper
Similarly to the think-pair-share activity, instructors pose a question or discussion topic. Instructors then provide time (typically under three minutes) for students to write down their ideas . This could be specified as anything from a “brain dump” (e.g., “Discuss the factors that dictate the growth of algae in the Arctic Ocean”) to a more structured form (“e.g., How would you design an experiment to measure the effect of temperature and light on algal growth in the Arctic Ocean?”). Students can then team up into small groups to discuss their answers and come to a consensus or perspective on the major ideas from the question. Following small group time, a few groups can be asked to report out to the whole class about their discussion.
Bonus: Positive interdependence can be achieved by assigning group members specific roles (e.g., recorder, checker, task manager, and spokesperson). These roles can be rotated each time the activity is used to allow students to practice each communication skill.
Jigsaw
This learning strategy works well for course concepts that can be split up into separate yet interconnected parts. Each part thus represents a piece of the puzzle, and the complete puzzle requires each individual piece to be complete. The jigsaw approach is split into two steps: the expert group meeting and the jigsaw group meeting. In the expert group meeting, instructors split students into small groups that are each assigned one part of the relevant content. Expert groups are assigned to discuss their “puzzle piece” and to achieve a consensus or mastery of their component. Expert groups are then dissolved and new jigsaw groups are formed, made up of one person from each expert group. In the jigsaw group meeting, each “expert ambassador” has a chance to report to the group about his or her piece of the puzzle. Jigsaw groups are then assigned the task of connecting each component to form a complete picture of the concept.
Bonus: Keep in mind that this method, while rich in discussion opportunities, requires the most logistical planning and organizational support of the three strategies outlined. For further reading, see https://www.jigsaw.org.
Authored by:
Kateri Salk
Posted on: Teaching Toolkit Tailgate
Cooperative Learning in Action
Photo by Brooke Cagle on Unsplash
The key to successfully im...
The key to successfully im...
Authored by:
PEDAGOGICAL DESIGN
Tuesday, Jul 14, 2020
Posted on: #iteachmsu
Multimodal Blended Events Handbook — Determining Event Type (Part 4 of 14)
Once you have a clear purpose and vision and have a proper understanding of your attendees and participants, along with their mental models, it’s time to determine which type of event will best serve your initiative. This is a major part of the event planning process.
The three options include the following:
In-person: This type of event is attended in-person and that takes place in a physical A pure in-person event offers zero digital resources, content, or experiences. For this type of event, a person must be physically present in order to partake and/or participate.
Virtual: Per HootSuite, “A virtual event is any organized meet-up that takes place online rather than in a physical location.” This option, whose growth was spurred by needs during the pandemic, is said to be here to stay — to the extent that participation and adoption is expected to increase 10-fold by 2030 (Source: PRNewswire).
Hybrid: According to com, hybrid events “combine both in- person and virtual experiences.” In other words, a hybrid event includes sessions people will attend physically, while having the option to partake of virtual events and content as they choose. For some, the ability to pick and choose from a plethora of content and experiences is the best of both worlds.
The following factors can help you decide which type of event to hold:
Physical locations of attendees/participants
Need for and ability to provide remote access
Attendance constraints
Presenting live recorded/on-demand vs. both types of content
Please note that in-person events require securing a venue to hold or conduct said event, while shifting to a virtual or hybrid format will require having access to and securing one or more platforms via which to house the event.
The three options include the following:
In-person: This type of event is attended in-person and that takes place in a physical A pure in-person event offers zero digital resources, content, or experiences. For this type of event, a person must be physically present in order to partake and/or participate.
Virtual: Per HootSuite, “A virtual event is any organized meet-up that takes place online rather than in a physical location.” This option, whose growth was spurred by needs during the pandemic, is said to be here to stay — to the extent that participation and adoption is expected to increase 10-fold by 2030 (Source: PRNewswire).
Hybrid: According to com, hybrid events “combine both in- person and virtual experiences.” In other words, a hybrid event includes sessions people will attend physically, while having the option to partake of virtual events and content as they choose. For some, the ability to pick and choose from a plethora of content and experiences is the best of both worlds.
The following factors can help you decide which type of event to hold:
Physical locations of attendees/participants
Need for and ability to provide remote access
Attendance constraints
Presenting live recorded/on-demand vs. both types of content
Please note that in-person events require securing a venue to hold or conduct said event, while shifting to a virtual or hybrid format will require having access to and securing one or more platforms via which to house the event.
Authored by:
Darren Hood