We found 80 results that contain "humans"
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A human resources management system or human resources information system or human capital managemen
A human resources management system or human resources information system or human capital management is a form of human resources software that combines a number of systems and processes to ensure the easy management of human resources, business processes and data.
NAVIGATING CONTEXT
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Human trafficking-considered modern-day slavery- is a global problem and is becoming increasingly pr
Human trafficking-considered modern-day slavery- is a global problem and is becoming increasingly prevalent across the World. Types and venues of trafficking in the United States Identifying victims of trafficking in healthcare settings Identifying warning signs of trafficking in healthcare settings for minors and adults Identifying resources for reporting suspected victims of human trafficking. The training requirement dictates a timeline beginning with the first renewal cycle for the period of 2017-2022. Let's talk more and research many areas, So join us by registering
The timeline for the training of individuals who are seeking initial nursing licensure - is 5 or more years of experience.
The timeline for the training of individuals who are seeking initial nursing licensure - is 5 or more years of experience.
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Artificial Intelligence
Since the invention of computers or machines, their capability to perform various tasks went on growing exponentially. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time.
A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.
A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.
ASSESSING LEARNING
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NLP tasks
Human language is filled with ambiguities that make it incredibly difficult to write software that accurately determines the intended meaning of text or voice data. Homonyms, homophones, sarcasm, idioms, metaphors, grammar and usage exceptions, variations in sentence structure—these just a few of the irregularities of human language that take humans years to learn, https://byjus.com/biology/flower/ but that programmers must teach natural language-driven applications to recognize and understand accurately from the start, if those applications are going to be useful.
https://byjus.com/biology/flower/ https://byjus.com/biology/flower/
Several NLP tasks break down human text and voice data in ways that help the computer make sense of what it's ingesting. Some of these tasks include the following:
Speech recognition, also called speech-to-text, is the task of reliably converting voice data into text data. Speech recognition is required for any application that follows voice commands or answers spoken questions. What makes speech recognition especially challenging is the way people talk—quickly, slurring words together, with varying emphasis and intonation, in different accents, and often using incorrect grammar.
Part of speech tagging, also called grammatical tagging, is the process of determining the part of speech of a particular word or piece of text based on its use and context. Part of speech identifies ‘make’ as a verb in ‘I can make a paper plane,’ and as a noun in ‘What make of car do you own?’
Word sense disambiguation is the selection of the meaning of a word with multiple meanings through a process of semantic analysis that determine the word that makes the most sense in the given context. For example, word sense disambiguation helps distinguish the meaning of the verb 'make' in ‘make the grade’ (achieve) vs. ‘make a bet’ (place).
Named entity recognition, or NEM, identifies words or phrases as useful entities. NEM identifies ‘Kentucky’ as a location or ‘Fred’ as a man's name.
Co-reference resolution is the task of identifying if and when two words refer to the same entity. The most common example is determining the person or object to which a certain pronoun refers (e.g., ‘she’ = ‘Mary’), but it can also involve identifying a metaphor or an idiom in the text (e.g., an instance in which 'bear' isn't an animal but a large hairy person).
Sentiment analysis attempts to extract subjective qualities—attitudes, emotions, sarcasm, confusion, suspicion—from text.
Natural language generation is sometimes described as the opposite of speech recognition or speech-to-text; it's the task of putting structured information into human language.
https://byjus.com/biology/flower/ https://byjus.com/biology/flower/
Several NLP tasks break down human text and voice data in ways that help the computer make sense of what it's ingesting. Some of these tasks include the following:
Speech recognition, also called speech-to-text, is the task of reliably converting voice data into text data. Speech recognition is required for any application that follows voice commands or answers spoken questions. What makes speech recognition especially challenging is the way people talk—quickly, slurring words together, with varying emphasis and intonation, in different accents, and often using incorrect grammar.
Part of speech tagging, also called grammatical tagging, is the process of determining the part of speech of a particular word or piece of text based on its use and context. Part of speech identifies ‘make’ as a verb in ‘I can make a paper plane,’ and as a noun in ‘What make of car do you own?’
Word sense disambiguation is the selection of the meaning of a word with multiple meanings through a process of semantic analysis that determine the word that makes the most sense in the given context. For example, word sense disambiguation helps distinguish the meaning of the verb 'make' in ‘make the grade’ (achieve) vs. ‘make a bet’ (place).
Named entity recognition, or NEM, identifies words or phrases as useful entities. NEM identifies ‘Kentucky’ as a location or ‘Fred’ as a man's name.
Co-reference resolution is the task of identifying if and when two words refer to the same entity. The most common example is determining the person or object to which a certain pronoun refers (e.g., ‘she’ = ‘Mary’), but it can also involve identifying a metaphor or an idiom in the text (e.g., an instance in which 'bear' isn't an animal but a large hairy person).
Sentiment analysis attempts to extract subjective qualities—attitudes, emotions, sarcasm, confusion, suspicion—from text.
Natural language generation is sometimes described as the opposite of speech recognition or speech-to-text; it's the task of putting structured information into human language.
NAVIGATING CONTEXT
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The Importance of Native Plants
Plants are really important for the planet and for all living things. Plants absorb carbon dioxide and release oxygen from their leaves, which humans and other animals need to breathe. Living things need plants to live - they eat them and live in them. Plants help to clean water too.
ASSESSING LEARNING
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Artificial intelligence
Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with an intelligent being.The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.
ASSESSING LEARNING
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EXAMPLES OF ARTIFICIAL INTELLIGENCE IN USE TODAY
Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans. For example, speech recognition, problem-solving, learning, and planning.
Today, Artificial Intelligence is a very popular subject that is widely discussed in the technology and business circles. Many experts and industry analysts argue that AI or machine learning is the future – but if we look around, we are convinced that it’s not the future – it is the present.
With the advancement in technology, we are already connected to AI in one way or the other – whether it is Siri, Watson, or Alexa. Yes, the technology is in its initial phase and more and more companies are investing resources in machine learning, indicating a robust growth in AI products and apps in the near future.
The following statistics will give you an idea of growth!
– In 2014, more than $300 million was invested in AI startups, showing an increase of 300%, compared to the previous year (Bloomberg)
– By 2018, 6 billion connected devices will proactively ask for support. (Gartner)
– By the end of 2018, “customer digital assistants” will recognize customers by face and voice across channels and partners (Gartner)
Today, Artificial Intelligence is a very popular subject that is widely discussed in the technology and business circles. Many experts and industry analysts argue that AI or machine learning is the future – but if we look around, we are convinced that it’s not the future – it is the present.
With the advancement in technology, we are already connected to AI in one way or the other – whether it is Siri, Watson, or Alexa. Yes, the technology is in its initial phase and more and more companies are investing resources in machine learning, indicating a robust growth in AI products and apps in the near future.
The following statistics will give you an idea of growth!
– In 2014, more than $300 million was invested in AI startups, showing an increase of 300%, compared to the previous year (Bloomberg)
– By 2018, 6 billion connected devices will proactively ask for support. (Gartner)
– By the end of 2018, “customer digital assistants” will recognize customers by face and voice across channels and partners (Gartner)
ASSESSING LEARNING
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Human computer interaction (HCI)
Introduction
Humans interact with computers in any way the interface between humans and computers is crucial to facilitate this interaction. Desktop applications, internet browsers, handheld computers, ERP, and computer kiosks make use of the prevalent graphical user interfaces (GUI) of today.
Voice user interfaces (VUI) are used for speech recognition and synthesizing systems, and the emerging multi-modal and Graphical user interfaces (GUI) allow humans to engage with embodied character agents in a way that cannot be achieved with other interface paradigms. The growth in the human-computer interaction field has been in the quality of interaction, and indifferent branching in its history. Instead of designing regular interfaces, the different research branches have had a different focus on the concepts of multimodality rather than unimodality, intelligent adaptive interfaces rather than command/action based ones, and finally active rather than passive interfaces.
An important facet of HCI is user satisfaction (or simply End-User Computing Satisfaction). "Because human-computer interaction studies a human and a machine in communication, it draws from supporting knowledge on both the machine and the human side. On the machine side, techniques in computer graphics, operating systems, programming languages, and development environments are relevant.
Humans interact with computers in any way the interface between humans and computers is crucial to facilitate this interaction. Desktop applications, internet browsers, handheld computers, ERP, and computer kiosks make use of the prevalent graphical user interfaces (GUI) of today.
Voice user interfaces (VUI) are used for speech recognition and synthesizing systems, and the emerging multi-modal and Graphical user interfaces (GUI) allow humans to engage with embodied character agents in a way that cannot be achieved with other interface paradigms. The growth in the human-computer interaction field has been in the quality of interaction, and indifferent branching in its history. Instead of designing regular interfaces, the different research branches have had a different focus on the concepts of multimodality rather than unimodality, intelligent adaptive interfaces rather than command/action based ones, and finally active rather than passive interfaces.
An important facet of HCI is user satisfaction (or simply End-User Computing Satisfaction). "Because human-computer interaction studies a human and a machine in communication, it draws from supporting knowledge on both the machine and the human side. On the machine side, techniques in computer graphics, operating systems, programming languages, and development environments are relevant.
Authored by: Rupali
Assessing Learning
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Human trafficking-considered modern-day
Human trafficking-considered modern-day slavery- is a global
A Team Leader leads, monitors, and supervises a group of employees to achieve goals that contribute to the growth of the organization. Team Leaders motivate and inspire their team by creating an environment that promotes positive communication, encourages bonding of team members, and demonstrates flexibility.
A Team Leader leads, monitors, and supervises a group of employees to achieve goals that contribute to the growth of the organization. Team Leaders motivate and inspire their team by creating an environment that promotes positive communication, encourages bonding of team members, and demonstrates flexibility.
Posted by: Chathuri Super admin..
Disciplinary Content
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robot pet that can interact with humans.
In the intersection of space travel and robotics, Jihee Kim introduces Laika — a concept design for a life-like, AI robot pet that can interact with humans. Laika has been designed for upcoming space projects such as NASA’s Artemis and Moon to Mars missions set for 2025-2030, envisioned as the ultimate companion for space explorers as it caters to both their physical and emotional well-being while they are away from home. Unlike the aggressive robotic dogs currently available on the market, Jihee Kim has designed Laika with a friendly and organic finish that enables it to connect to its human counterpart on an emotional level when in use while monitoring their health conditions and assisting them in emergencies. Beyond space missions, this approachable design allows Laika to integrate into domestic contexts.
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URL : https://www.designboom.com/technology/life-like-ai-robot-dog-laika-space-travelers-jihee-kim-11-19-2023/
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URL : https://www.designboom.com/technology/life-like-ai-robot-dog-laika-space-travelers-jihee-kim-11-19-2023/
Authored by: Vijayalaxmi vishwanath mali
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Human trafficking-considered modern-day slavery- is a global problem and is becoming increasingly pr
Human trafficking-considered modern-day slavery- is a global problem and is becoming increasingly prevalent across the World. Types and venues of trafficking in the United States Identifying victims of trafficking in healthcare settings Identifying warning signs of trafficking in healthcare settings for minors and adults Identifying resources for reporting suspected victims of human trafficking. The training requirement dictates a timeline beginning with the first renewal cycle for the period of 2017-2022. Let's talk more and research many areas, So join us by registering The timeline for the training of individuals who are seeking initial nursing licensure - is 5 or more years of experience.
Posted by: Vijayalaxmi Vishavnathkam Santosh Mali
Posted on: #iteachmsu

Human trafficking-considered modern-day slavery- is a global problem and is becoming increasingly pr
Human trafficking-considered modern-day slavery- is a global problem and is becoming increasingly prevalent across the World. Types and venues of trafficking in the United States Identifying victims of trafficking in healthcare settings Identifying warning signs of trafficking in healthcare settings for minors and adults Identifying resources for reporting suspected victims of human trafficking. The training requirement dictates a timeline beginning with the first renewal cycle for the period of 2017-2022. Let's talk more and research many areas, So join us by registering
The timeline for the training of individuals who are seeking initial nursing licensure - is 5 or more years of experience.
The timeline for the training of individuals who are seeking initial nursing licensure - is 5 or more years of experience.
Posted by: Super Admin
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Beyond space missions, this approachable design allows Laika to integrate into domestic contexts.
In the intersection of space travel and robotics, Jihee Kim introduces Laika — a concept design for a life-like, AI robot pet that can interact with humans. Laika has been designed for upcoming space projects such as NASA’s Artemis and Moon to Mars missions set for 2025-2030, envisioned as the ultimate companion for space explorers as it caters to both their physical and emotional well-being while they are away from home. Unlike the aggressive robotic dogs currently available on the market, Jihee Kim has designed Laika with a friendly and organic finish that enables it to connect to its human counterpart on an emotional level when in use while monitoring their health conditions and assisting them in emergencies. Beyond space missions, this approachable design allows Laika to integrate into domestic contexts.
Image :
video link : Embedded URL test :
Table :
Sr NO
Assignee
Task
Cat 1
Rohit
Test 1
Cat 2
Shweta
Test 2
Numbering :
Number 1
Number 2
Bullets :
Bullets 1
Bullets 2
Bullets 3
URL : https://www.designboom.com/technology/life-like-ai-robot-dog-laika-space-travelers-jihee-kim-11-19-2023/
Image :
video link : Embedded URL test :
Table :
Sr NO
Assignee
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Cat 1
Rohit
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Cat 2
Shweta
Test 2
Numbering :
Number 1
Number 2
Bullets :
Bullets 1
Bullets 2
Bullets 3
URL : https://www.designboom.com/technology/life-like-ai-robot-dog-laika-space-travelers-jihee-kim-11-19-2023/
Authored by: vijayalaxmi vishwanath mali
Posted on: #iteachmsu
You're Not Welcome Here: How Social Distancing Can Destroy The Global Economy
It's what people are being asked to tell each other. Less than 10 days ago, London banned people who live in different households from meeting each other indoors, to stop the spread of the coronavirus.
"Nobody wants to see more restrictions, but this is deemed to be necessary in order to protect Londoners' lives," London Mayor Sadiq Khan told the London Assembly.
Taking away the welcome mat is key to cutting off the path of the coronavirus. From the beginning of the pandemic, cities, states, and countries have banned each other. And now, eight months into lockdowns that have led to immense stress and fatigue among people, some places around the world are introducing even more draconian measures.24
The path toward recovery continues to be inherently antisocial and runs counter to how humans interact, live lives, and conduct their business. This unwelcome policy — which has already harmed families, societies, and economies — has the potential to lead to a tectonic shift in how the world functions in the foreseeable future.
"Nobody wants to see more restrictions, but this is deemed to be necessary in order to protect Londoners' lives," London Mayor Sadiq Khan told the London Assembly.
Taking away the welcome mat is key to cutting off the path of the coronavirus. From the beginning of the pandemic, cities, states, and countries have banned each other. And now, eight months into lockdowns that have led to immense stress and fatigue among people, some places around the world are introducing even more draconian measures.24
The path toward recovery continues to be inherently antisocial and runs counter to how humans interact, live lives, and conduct their business. This unwelcome policy — which has already harmed families, societies, and economies — has the potential to lead to a tectonic shift in how the world functions in the foreseeable future.
Authored by: PALLAVI GOGOI
Disciplinary Content
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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
Machine-generated data is information automatically generated by a computer process, application, or other mechanism without the active intervention of a human. While the term dates back over fifty years,[1] there is some current indecision as to the scope of the term. Monash Research's Curt Monash defines it as "data that was produced entirely by machines OR data that is more about observing humans than recording their choices."[2] Meanwhile, Daniel Abadi, CS Professor at Yale, proposes a narrower definition, "Machine-generated data is data that is generated as a result of a decision of an independent computational agent or a measurement of an event that is not caused by a human action."[3] Regardless of definition differences, both exclude data manually entered by a person.[4] Machine-generated data crosses all industry sectors. Often and increasingly, humans are unaware their actions are generating the data.[
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Assessing Learning
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The robot misconception is related to the myth that machines can’t control humans.
Intelligence enables control: humans control tigers not because we are stronger, but because we are smarter. This means that if we cede our position as smartest on our planet, it’s possible that we might also cede control.
Intelligence enables control: humans control tigers not because we are stronger, but because we are smarter. This means that if we cede our position as smartest on our planet, it’s possible that we might also cede control.
Posted by: Chathuri Super admin..
Assessing Learning
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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

Second post
: 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 (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: Roni Smith
Navigating Context
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Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, speech recognition, problem-solving, learning, and planning.
Posted by: Rupali Jagtap
Assessing Learning
Posted on: #iteachmsu
The concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep learning techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.
Posted by: Rupali Jagtap
Assessing Learning
Host: MSU Libraries
Our Daily Work/Our Daily Lives
Our Daily Work/Our Daily Lives - Fall 2025 Brownbag Series
DAVID MCCARTHY
MSU RESIDENTIAL COLLEGE IN THE ARTS AND HUMANITIES
Good Workers, Government Workers: Public Memory and the Murrah Building Bombing
A monumental twelve-foot-by-fifteen-foot quilt commemorating eighty-nine federal workers murdered in the bombing of the Murrah Federal Building in 1995 was the result of a collaborative, nationwide effort organized by the American Federation of Government Employees (AFGE). Originally intended for the newly rebuilt federal building in Oklahoma City, the quilt was instead added to the collections of the MSU Museum, where it has been stored for twenty-five years. A new exhibit of the quilt opens this October at the MSU Union.
Join online here. The password is odwodl.
Navigating Context
Host: MSU Libraries
Intro to Anatomage @ DSL: Drop-In Session
Come learn about the Anatomage Table! The Anatomage Table is the only fully segmented real human 3D anatomy platform, and you can drop in to check out, test it out, and think about how you can use it for your curriculum, courses, research support, and to enhance the student experience.
Navigating Context
Host: CTLI
Supporting Student Success Through Early Warning: Strategies for Graduate Teaching Assistants
On behalf of the GREAT office at The Graduate School, check out Supporting Student Success Through Early Warning: Strategies for Graduate Teaching Assistants
Date: Wednesday, September 10, 2025 - 11:00am to 12:00pm
Location: Zoom
Audience: Current Graduate Students & Postdocs
This interactive session is designed to support Graduate Teaching Assistants in recognizing and responding to early signs that students may be in need of support. Participants will explore their role in MSU’s early warning efforts and develop practical strategies to promote academic engagement, connection, and timely support. The session will include discussion of common indicators that students may be facing challenges affecting their educational success, strategies for effective communication, and how to use campus resources and reporting tools like EASE to provide timely support.
Facilitator(s):
Kanchan Pavangadkar, Director of Student Success for the College of Agriculture and Natural Resources (CANR)
Dwight Handspike, Director of Academic Advising & Student Success Initiatives, Undergraduate Academic Services, Broad College of Business
Samantha Zill, Human Biology & Pre-Health Advisor, Michigan State University, College of Natural Science
Maria O'Connell, University Innovation Alliance Fellow, Undergraduate Student Success Strategic Initiatives Manager, Office of Undergraduate Education
Register Here
**Zoom link will be sent closer to the workshop date.
Navigating Context
EXPIRED
Host: MSU Libraries
Renaissances, Revivals, and Records
Throughout history, humans have been finding ways to revive, rebirth, and reconstruct their favorite artistic practices. Music has been one of the greatest playgrounds for these types of explorations. In acts that both pay homage to the past and push the craft forward, renaissances have revolved around time periods, genres, and even mediums. Join us for an interactive listening party where we take a closer look at some iconic musical revivals, ask how we got here, and wonder where we might go next.
Curated and hosted by: Lilly Korkontzelos, MSU Music Library Student Assistant and master’s student in Music Theory
Location: Music Library (4th Floor West)
Navigating Context
EXPIRED
Host: MSU Libraries
Annual Digital Humanities THATCamp 2025
Greetings from the MSU Digital Humanities Community!
Please share the following invitation with your faculty colleagues, students, and staff.
We would like to invite you and your colleagues to join us for the annual Digital Humanities THATCamp, taking place on Thursday, August 21st from 8:30AM - 3:00PM in the Digital Scholarship Lab of the MSU Main Library (Second Floor, West).
*Light breakfast, lunch will be served. Please join us for an Ice Cream Social from 3:15PM-4:30PM. Location outdoors, TBD.
Please register here.
What is THATCamp?
THATCamp stands for “The Humanities and Technology Camp.” It is an unconference: an open, less formal meeting where humanists and technologists of all skill levels learn and build together in sessions proposed on the spot (From: http://thatcamp.org/about).
Who is THATCamp for?
This day-long, in person, fun, unconference is a fantastic opportunity for people on campus, whether formally a part of the DH@MSU community or not, to gather, learn from each other, and make connections to carry forward into the academic year. We welcome:
Members of the DH@MSU community, old and new
Students in the Digital Humanities undergraduate minor or graduate certificate, and students interested in the minor/certificate
Humanists who are engaged in digital and computer-assisted research, teaching, and creation
Anyone doing or interested in exploring work in the digital, especially (but not exclusively) in the areas of arts, humanities, and social sciences
Why THATCamp MSU?
DH@MSU is continuing our annual THATCamp each August targeted at MSU faculty, staff, and students for a few reasons:
To bring people back together after the summer
To introduce new folks to the DH@MSU community
Share knowledge, expertise, and skills among the community
Build connections between community members for future collaborations, troubleshooting, and ice cream social time.
THATCamp is FREE! Please register here.
Please direct any questions to Max Evjen (evjendav@msu.edu).
Navigating Context
EXPIRED