We found 483 results that contain "ai"
Posted on: #iteachmsu
How does generative AI work? -- 935
Generative AI starts with a prompt that could be in the form of a text, an image, a video, a design, musical notes, or any input that the AI system can process. Various AI algorithms then return new content in response to the prompt. Content can include essays, solutions to problems, or realistic fakes created from pictures or audio of a person.
Early versions of generative AI required submitting data via an API or an otherwise complicated process. Developers had to familiarize themselves with special tools and write applications using languages such as Python.
Now, pioneers in generative AI are developing better user experiences that let you describe a request in plain language. After an initial response, you can also customize the results with feedback about the style, tone and other elements you want the generated content to reflect.
Early versions of generative AI required submitting data via an API or an otherwise complicated process. Developers had to familiarize themselves with special tools and write applications using languages such as Python.
Now, pioneers in generative AI are developing better user experiences that let you describe a request in plain language. After an initial response, you can also customize the results with feedback about the style, tone and other elements you want the generated content to reflect.
NAVIGATING CONTEXT
Posted on: #iteachmsu
How this AI is starting a music playlist revolution
Machine-learning algorithms made possible by a combination of deep learning and artificial intelligence has dominated 2017. The dramatic rises in consumer expectation levels are also forcing businesses to simplify and personalize everything in a bid to remain relevant to their tech savvy customers.
We now have access to unlimited music to accompany us on our travels thanks to all-you-can-eat packages offered by the likes of Apple Music and Spotify. However, discovery algorithms on these digital services could never replace the art of manually creating your playlist, or could they?
We now have access to unlimited music to accompany us on our travels thanks to all-you-can-eat packages offered by the likes of Apple Music and Spotify. However, discovery algorithms on these digital services could never replace the art of manually creating your playlist, or could they?
ASSESSING LEARNING
Posted on: #iteachmsu
Aerobic Exercise & Resistance Training (Strength Work)
Aerobic Exercise & Resistance Training (Strength Work)
ASSESSING LEARNING
Posted on: #iteachmsu
Description is the pattern of narrative development that aims to make vivid a
Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes,Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes,Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes,Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes,Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes,Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes.
ASSESSING LEARNING
Posted on: #iteachmsu
PL-Description is the pattern of narrative development that aims to make vivid a
Description is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes, along with exposition, argumentation, and narration. In practice it would be difficult to write literature that drew on just one of the four basic modesDescription is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes, along with exposition, argumentation, and narration. In practice it would be difficult to write literature that drew on just one of the four basic modesDescription is the pattern of narrative development that aims to make vivid a place, object, character, or group. Description is one of four rhetorical modes, along with exposition, argumentation, and narration. In practice it would be difficult to write literature that drew on just one of the four basic modes.
ASSESSING LEARNING
Posted on: #iteachmsu
Playlist which contains assessment(Activities For Your Child’s Brain Development)
Activities For Your Child’s Brain Development
ASSESSING LEARNING
Posted on: #iteachmsu
Brainstorming Techniques to Generate Ideas for Every Situation
What’s the best way to brainstorm? While there are basic rules that make the process meaningful and effective, there are dozens of ways to inspire creative ideas. Many facilitators use more than one technique in a single brainstorming session to keep the creative juices flowing while supporting different styles of thought and expression.
ASSESSING LEARNING
Posted on: What are the 12 Agi...
The Agile Alliance defines 12 lightness principles for those who need to attain agility: Our highes
Edited: New: The Agile Alliance defines 12 lightness principles for those who need to attain agility:
Our highest priority is to satisfy the client through early and continuous delivery of valuable computer software.
Welcome dynamic necessities, even late in development. Agile Processes harness modification for the customer’s competitive advantage.
Deliver operating computer software often, from a pair of weeks to a couple of months, with a preference to the shorter timescale.
Business individuals and developers should work along daily throughout the project.
The build comes around actuated people. offer them the setting and support they have, and trust them to urge the task done.
the foremost economical and effective methodology of conveyancing info to and among a development team is face-to-face speech.
Working with computer software is the primary life of progress.
Agile processes promote property development. The sponsors, developers, and users will be able to maintain a relentless pace indefinitely.
Continuous attention to technical excellence and smart style enhances nimbleness.
Simplicity—the art of maximizing the number of work not done—is essential.
the most effective architectures, necessities, and styles emerge from self–organizing groups.
At regular intervals, the team reflects on a way to become simpler, then tunes and adjusts its behavior consequently.
Our highest priority is to satisfy the client through early and continuous delivery of valuable computer software.
Welcome dynamic necessities, even late in development. Agile Processes harness modification for the customer’s competitive advantage.
Deliver operating computer software often, from a pair of weeks to a couple of months, with a preference to the shorter timescale.
Business individuals and developers should work along daily throughout the project.
The build comes around actuated people. offer them the setting and support they have, and trust them to urge the task done.
the foremost economical and effective methodology of conveyancing info to and among a development team is face-to-face speech.
Working with computer software is the primary life of progress.
Agile processes promote property development. The sponsors, developers, and users will be able to maintain a relentless pace indefinitely.
Continuous attention to technical excellence and smart style enhances nimbleness.
Simplicity—the art of maximizing the number of work not done—is essential.
the most effective architectures, necessities, and styles emerge from self–organizing groups.
At regular intervals, the team reflects on a way to become simpler, then tunes and adjusts its behavior consequently.
DISCIPLINARY CONTENT
Posted on: #iteachmsu
THE TOP MYTHS ABOUT ADVANCED AI
common myths
for Advanced
AI:A captivating conversation is taking place about the future of artificial intelligence and what it will/should mean for humanity. There are fascinating controversies where the world’s leading experts disagree, such as AI’s future impact on the job market; if/when human-level AI will be developed; whether this will lead to an intelligence explosion; and whether this is something we should welcome or fear. But there are also many examples of boring pseudo-controversies caused by people misunderstanding and talking past each other.
TIMELINE MYTHS
The first myth regards the timeline: how long will it take until machines greatly supersede human-level intelligence? A common misconception is that we know the answer with great certainty.
One popular myth is that we know we’ll get superhuman AI this century. In fact, history is full of technological over-hyping. Where are those fusion power plants and flying cars we were promised we’d have by now? AI has also been repeatedly over-hyped in the past, even by some of the founders of the field. For example, John McCarthy (who coined the term “artificial intelligence”), Marvin Minsky, Nathaniel Rochester, and Claude Shannon wrote this overly optimistic forecast about what could be accomplished during two months with stone-age computers: “We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College […] An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.”
CONTROVERSY MYTHS
Another common misconception is that the only people harboring concerns about AI and advocating AI safety research are Luddites who don’t know much about AI. When Stuart Russell, author of the standard AI textbook, mentioned this during his Puerto Rico talk, the audience laughed loudly. A related misconception is that supporting AI safety research is hugely controversial. In fact, to support a modest investment in AI safety research, people don’t need to be convinced that risks are high, merely non-negligible — just as a modest investment in home insurance is justified by a non-negligible probability of the home burning down.
for Advanced
AI:A captivating conversation is taking place about the future of artificial intelligence and what it will/should mean for humanity. There are fascinating controversies where the world’s leading experts disagree, such as AI’s future impact on the job market; if/when human-level AI will be developed; whether this will lead to an intelligence explosion; and whether this is something we should welcome or fear. But there are also many examples of boring pseudo-controversies caused by people misunderstanding and talking past each other.
TIMELINE MYTHS
The first myth regards the timeline: how long will it take until machines greatly supersede human-level intelligence? A common misconception is that we know the answer with great certainty.
One popular myth is that we know we’ll get superhuman AI this century. In fact, history is full of technological over-hyping. Where are those fusion power plants and flying cars we were promised we’d have by now? AI has also been repeatedly over-hyped in the past, even by some of the founders of the field. For example, John McCarthy (who coined the term “artificial intelligence”), Marvin Minsky, Nathaniel Rochester, and Claude Shannon wrote this overly optimistic forecast about what could be accomplished during two months with stone-age computers: “We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College […] An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.”
CONTROVERSY MYTHS
Another common misconception is that the only people harboring concerns about AI and advocating AI safety research are Luddites who don’t know much about AI. When Stuart Russell, author of the standard AI textbook, mentioned this during his Puerto Rico talk, the audience laughed loudly. A related misconception is that supporting AI safety research is hugely controversial. In fact, to support a modest investment in AI safety research, people don’t need to be convinced that risks are high, merely non-negligible — just as a modest investment in home insurance is justified by a non-negligible probability of the home burning down.
Authored by: Rupali
Assessing Learning
Posted on: #iteachmsu
How does generative AI work? -- 935
Generative AI starts with a prompt that could be in the form of a text, an image, a video, a design, musical notes, or any input that the AI system can process. Various AI algorithms then return new content in response to the prompt. Content can include essays, solutions to problems, or realistic fakes created from pictures or audio of a person.
Early versions of generative AI required submitting data via an API or an otherwise complicated process. Developers had to familiarize themselves with special tools and write applications using languages such as Python.
Now, pioneers in generative AI are developing better user experiences that let you describe a request in plain language. After an initial response, you can also customize the results with feedback about the style, tone and other elements you want the generated content to reflect.
Early versions of generative AI required submitting data via an API or an otherwise complicated process. Developers had to familiarize themselves with special tools and write applications using languages such as Python.
Now, pioneers in generative AI are developing better user experiences that let you describe a request in plain language. After an initial response, you can also customize the results with feedback about the style, tone and other elements you want the generated content to reflect.
Authored by: Vaishu
Navigating Context
Posted on: #iteachmsu
Develop and actively communicate your course-level generative AI policy
1. Consider how AI technology might compel you to revise your course assignments, quizzes, and tests to avoid encouraging unethical or dishonest use of generative AI. 2. Develop and integrate a generative AI policy throughout the course resources:
Provide clear definitions, expectations, and repercussions of what will happen if students violate the policy.
Explain the standards of academic integrity in the course, especially as related to use of AI technologies, and review the Integrity of Scholarship and Grades Policy.
Be clear about what types of AI are acceptable and what versions of the technology students can use or not use.
Put this policy into D2L and any assignment instructions consistently.
3. Discuss these expectations when talking about course policies at the beginning of the course and remind students about them as you discuss course assignments:
Take time to explain to students the pros and cons of generative AI technologies relative to your course.
Explain the development of your policy and make clear the values, ethics, and philosophies underpinning its development.
Explain the repercussions of not following the course policy and submit an Academic Dishonesty Report if needed.
4. If you want to integrate AI in the classroom as an allowed or required resource:
Consult with MSU IT guidance about recommendations for use and adoption of generative AI technology, including guidelines for keeping you and your data safe.
Determine if MSU already has access to the tools you desire for free, and if not available through MSU, consider the cost and availability of the resources you will allow or require, and go through MSU's procurement process.
If you want to require students to use an AI technology that comes with a cost, put the resource into the scheduling system as you would a textbook, so students know that is an anticipated cost to them.
Provide clear definitions, expectations, and repercussions of what will happen if students violate the policy.
Explain the standards of academic integrity in the course, especially as related to use of AI technologies, and review the Integrity of Scholarship and Grades Policy.
Be clear about what types of AI are acceptable and what versions of the technology students can use or not use.
Put this policy into D2L and any assignment instructions consistently.
3. Discuss these expectations when talking about course policies at the beginning of the course and remind students about them as you discuss course assignments:
Take time to explain to students the pros and cons of generative AI technologies relative to your course.
Explain the development of your policy and make clear the values, ethics, and philosophies underpinning its development.
Explain the repercussions of not following the course policy and submit an Academic Dishonesty Report if needed.
4. If you want to integrate AI in the classroom as an allowed or required resource:
Consult with MSU IT guidance about recommendations for use and adoption of generative AI technology, including guidelines for keeping you and your data safe.
Determine if MSU already has access to the tools you desire for free, and if not available through MSU, consider the cost and availability of the resources you will allow or require, and go through MSU's procurement process.
If you want to require students to use an AI technology that comes with a cost, put the resource into the scheduling system as you would a textbook, so students know that is an anticipated cost to them.
Authored by: Super admin user
Posted on: #iteachmsu
AI can turn spoken language into photorealistic sign language videos Read more: https://www.newscie
An AI that can produce photorealistic videos of sign language interpreters from speech could improve accessibility by removing the need for humans.
Ben Saunders at the University of Surrey, UK, and his colleagues used a neural network that converts spoken language into sign language. The system, called SignGAN, then maps these signs on to a 3D model of the human skeleton.
The team also trained the AI on videos of real sign language interpreters, teaching it how to create a photorealistic video of anyone signing based off an image of …
Read more: https://www.newscientist.com/article/2261113-ai-can-turn-spoken-language-into-photorealistic-sign-language-videos/#ixzz6g1KMybts
Ben Saunders at the University of Surrey, UK, and his colleagues used a neural network that converts spoken language into sign language. The system, called SignGAN, then maps these signs on to a 3D model of the human skeleton.
The team also trained the AI on videos of real sign language interpreters, teaching it how to create a photorealistic video of anyone signing based off an image of …
Read more: https://www.newscientist.com/article/2261113-ai-can-turn-spoken-language-into-photorealistic-sign-language-videos/#ixzz6g1KMybts
Posted by: Greg Thomsan
Pedagogical Design
Posted on: #iteachmsu
Are there any advances in this direction that you think hold promise?
The basic idea of intelligence:An explosion is that once machines reach a certain level of intelligence, they’ll be able to work on AI just like we do and improve their own capabilities — redesign their own hardware and so on — and their intelligence will zoom off the charts. There’s an area emerging called “cyber-physical systems” about systems that couple computers to the real world. With a cyber-physical system, you’ve got a bunch of bits representing an air traffic control program, and then you’ve got some real airplanes, and what you care about is that no airplanes collide. You’re trying to prove a theorem about the combination of the bits and the physical world. What you would do is write a very conservative mathematical description of the physical world — airplanes can accelerate within such-and-such envelope — and your theorems would still be true in the real world as long as the real world is somewhere inside the envelope of behaviors.
Yet you’ve pointed out that it might not be mathematically possible to formally verify AI systems.
There’s a general problem of “undecidability” in a lot of questions you can ask about computer programs. Alan Turing showed that no computer program can decide whether any other possible program will eventually terminate and output an answer or get stuck in an infinite loop. So if you start out with one program, but it could rewrite itself to be any other program, then you have a problem, because you can’t prove that all possible other programs would satisfy some property.
Yet you’ve pointed out that it might not be mathematically possible to formally verify AI systems.
There’s a general problem of “undecidability” in a lot of questions you can ask about computer programs. Alan Turing showed that no computer program can decide whether any other possible program will eventually terminate and output an answer or get stuck in an infinite loop. So if you start out with one program, but it could rewrite itself to be any other program, then you have a problem, because you can’t prove that all possible other programs would satisfy some property.
Authored by: Rupali
Assessing Learning
Posted on: #iteachmsu
ADHD Misconceptions
https://www.sciencedaily.com/releases/2016/10/161013103134.htm
Attention-deficit hyperactivity disorder (ADHD) is a very common condition diagnosed mainly in children.
According to the Centers for Disease Control and Prevention (CDC), 6.4 million children between four and 17 years of age have been diagnosed with ADHD as of 2011.
This primer is designed to help you understand ADHD at a deeper level and combat misconceptions.
Fact: An ADHD diagnosis requires observations of numerous symptoms in multiple settings and evidence of significant impairment.
Children are inherently energetic, sometimes even rowdy. If unruly behavior is the only symptom, then it’s difficult for a professional to say that their problem is truly a mental illness.
“ADHD is a real mental disorder. There are a myriad of reasons why children are inattentive, such as anxiety or inadequate sleep, but a child with attention-deficit disorder (ADD) or ADHD does have a condition. Diagnosis will require observations of numerous symptoms in multiple settings and evidence of significant impairment.” - Joshua Cabrera, MD, clinical psychiatrist and assistant professor at the Texas A&M College of Medicine.
The main symptoms of ADHD are inattention, hyperactivity and impulsivity.
These can manifest in different ways: persistent fidgeting, being easily distracted or forgetful and difficulty waiting for a turn.
Attention-deficit hyperactivity disorder (ADHD) is a very common condition diagnosed mainly in children.
According to the Centers for Disease Control and Prevention (CDC), 6.4 million children between four and 17 years of age have been diagnosed with ADHD as of 2011.
This primer is designed to help you understand ADHD at a deeper level and combat misconceptions.
Fact: An ADHD diagnosis requires observations of numerous symptoms in multiple settings and evidence of significant impairment.
Children are inherently energetic, sometimes even rowdy. If unruly behavior is the only symptom, then it’s difficult for a professional to say that their problem is truly a mental illness.
“ADHD is a real mental disorder. There are a myriad of reasons why children are inattentive, such as anxiety or inadequate sleep, but a child with attention-deficit disorder (ADD) or ADHD does have a condition. Diagnosis will require observations of numerous symptoms in multiple settings and evidence of significant impairment.” - Joshua Cabrera, MD, clinical psychiatrist and assistant professor at the Texas A&M College of Medicine.
The main symptoms of ADHD are inattention, hyperactivity and impulsivity.
These can manifest in different ways: persistent fidgeting, being easily distracted or forgetful and difficulty waiting for a turn.
Authored by: Viju
Disciplinary Content
Posted on: #iteachmsu
India vs England, LIVE Cricket Score Updates, 2nd Test Match Day 1 at Lord’s: Rain delays toss, pitches still under cover
Live Cricket Score Updates, India vs England: Rain has delayed the toss as Virat Kohli-led India eye redemption against England in the second Test of their five-match series at Lord’s on Thursday.
Live Updates: The toss was delayed due to rain as India face England in the second Test at Lord’s. The visitors trail 1-0 after they were beaten in the first encounter at Edgbaston and Virat Kohli & Co will look to produce a better show on a ground where they have won just 2 out of their last 17 Test matches. Kohli will be banking on his top-order batsmen to fire after a disappointing show in the first Test and the visitors can opt for a second spin option in Kuldeep Yadav. For England, Ollie Pope will be making his debut with Moeen Ali possibly playing alongside Adil Rashid in the spin department.
Live Updates: The toss was delayed due to rain as India face England in the second Test at Lord’s. The visitors trail 1-0 after they were beaten in the first encounter at Edgbaston and Virat Kohli & Co will look to produce a better show on a ground where they have won just 2 out of their last 17 Test matches. Kohli will be banking on his top-order batsmen to fire after a disappointing show in the first Test and the visitors can opt for a second spin option in Kuldeep Yadav. For England, Ollie Pope will be making his debut with Moeen Ali possibly playing alongside Adil Rashid in the spin department.
Posted by: Chathuri Super admin..
Navigating Context
Posted on: #iteachmsu
Categorization of Artificial Intelligence
Categories of AI
Artificial intelligence:
can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it answers it for you.
Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.
Artificial intelligence:
can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it answers it for you.
Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.
Authored by: Rupali
Assessing Learning
Posted on: #iteachmsu
A super-intelligent AI will be extremely good at accomplishing its goals, and if those goals aren’t aligned with ours, we have a problem.
You’re probably not an evil ant-hater who steps on ants out of malice, but if you’re in charge of a hydroelectric green energy project and there’s an anthill in the region to be flooded, too bad for the ants.
A key goal of AI safety research is to never place humanity in the position of those ants.
You’re probably not an evil ant-hater who steps on ants out of malice, but if you’re in charge of a hydroelectric green energy project and there’s an anthill in the region to be flooded, too bad for the ants.
A key goal of AI safety research is to never place humanity in the position of those ants.
Posted by: Rupali Jagtap
Posted on: #iteachmsu
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include learning, reasoning, and perception.
link: https://www.youtube.com/watch?v=oV74Najm6Nc
Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include learning, reasoning, and perception.
link: https://www.youtube.com/watch?v=oV74Najm6Nc
Posted by: Rupali Jagtap
Posted on: #iteachmsu
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Posted by: Rupali Jagtap
Assessing Learning
Posted on: #iteachmsu
The primary aim of Global Citizenship Education (GCED) is nurturing respect for all, building a sense of belonging to common humanity, and helping learners become responsible and active global citizens. GCED aims to empower learners to assume active roles to face and resolve global challenges and to become proactive contributors to a more peaceful, tolerant, inclusive,
Posted by: Chathuri Super admin..
Assessing Learning
Posted on: #iteachmsu
Artificial intelligence (AI) aims to or is required to synthesize goal-orientated processes such as problem-solving, decision-making, environmental adaptation, learning, and communication found in humans and animals.
https://www.w3.org/TR/UNDERSTANDING-WCAG20/visual-audio-contrast-scale.html
artificial intelligence research has been necessarily cross-disciplinary, drawing on areas of expertise such as applied mathematics, symbolic logic, semiotics, electrical engineering, neurophysiology, and social intelligence.
https://www.w3.org/TR/UNDERSTANDING-WCAG20/visual-audio-contrast-scale.html
artificial intelligence research has been necessarily cross-disciplinary, drawing on areas of expertise such as applied mathematics, symbolic logic, semiotics, electrical engineering, neurophysiology, and social intelligence.
Posted by: Rupali Jagtap
Assessing Learning
Host: MSU Libraries
MSU Family Weekend: Game Labs Open House
For MSU Family Weekend, stop by the Libraries' game labs for some down-time fun. The Gerald M Kline Digital and Multimedia Center (Main Library 4 West) is home to game labs for study and recreation alike! Console games from our collection or yours may be played by individuals or groups in our fully equipped video game labs.
For parking information visit http://maps.msu.edu/interactive.
If you have questions about accessibility or need to request accommodations, please email lib.dl.accessibility@msu.edu.
Navigating Context
Host: CTLI
To Be Read: Educator Edition
If you're anything like us, you probably have a long list of "to be read" books. We know that engaging in book discussions fosters a culture of curiosity and intellectual growth, reinforcing the idea that learning is a lifelong journey enriched by the exchange of ideas and insights with others. It is our hope that through thoughtful dialogue and shared reflections on relevant literature, educators not only enhance their own practices but also contribute to a dynamic community that benefits both their students and MSU broadly.
Goals for this program:
Cultivate a curiosity for continuous learning by engaging discussions of relevant teaching & learning publications
Enhance instructional practices and professional growth through the exchange of ideas and insights gained from shared reflections
Contribute to a collaborative community of educators that supports mutual development necessary to provide high-quality, evidence-based learning experiences across all modes of instruction.
Navigating Context
Host: MSU Libraries
Research Facilitation Network Lightning talks: Research Support Services at MSU
Join us for insightful talks about research support services available at Michigan State. This session will highlight units assisting researchers throughout their research life cycle. Bring your questions and support needs to contribute to the discussion.
Meeting information: Zoom, September 16 from 3-4PM
Register here!
Navigating Context
Host: MSU Libraries
Intro to Modeling for 3D Printing: TinkerCad Zipper Pull
Get creative with 3D printing in this hands-on beginner workshop at the MSU Libraries Hollander Makerspace—a space where all students can explore, design, and make.
You’ll learn how 3D printing works, design your own custom zipper pull using simple modeling tools in Tinkercad, and watch it print before your eyes. No experience needed—we’ll guide you step by step as you combine shapes to bring your design to life. Your custom zipper pull is yours to keep—use it to fix a broken zipper, personalize your gear, or show off your new tech skills!
Attendees will need to arrive with or be willing to make a free Tinkercad account with a valid email address.
Navigating Context
Host: MSU Libraries
MSU Libraries and The Poetry Room present Olivia Gatwood
Join the MSU Libraries and Lansing’s The Poetry Room for an afternoon of poetry, connection and conversation celebrating student, alumni and community voices. The event opens with performances from the MSU Poetry Club alongside recent alumni, spotlighting emerging talent and the power of being heard. The showcase will be followed by acclaimed poet, author and viral sensation Olivia Gatwood, whose work blends humor, intimacy and sharp social insight. Gatwood will share poems as well as excerpts from her 2024 novel “Whoever You Are, Honey,” offering an unfiltered look into her craft and creative journey. The afternoon will conclude with a Q&A — a mix of moderated conversation and audience participation — creating a rare opportunity to connect with one of today’s most dynamic literary voices.
Olivia Gatwood is the author of two poetry collections, “New American Best Friend” and “Life of the Party,” and co-writer of Adele’s music video “I Drink Wine.” She has received international recognition for her poetry, writing workshops and work as a Title IX-compliant educator in sexual assault prevention and recovery. Her performances have been featured on HBO, MTV, VH1, the BBC and more, with poems appearing in “The Poetry Foundation,” “Lambda Literary” and “The Missouri Review.” Originally from Albuquerque, she now lives in Los Angeles.
Event is free and open to all.
Navigating Context
Host: MSU Libraries
Data Management Plans: Yes, you need one and here is how to create them
An overview of why data management plans are important and often required, and how to develop one. We will look at the items commonly included in all data management plans regardless of agency/institutional requirements, some examples of specific funding agency templates and review what resources are available to help you draft your plan.
Navigating Context