This exercise should be used after you think students know what AFM diagrams are and how they work. This is sort of a quiz -- to see if they can properly interpret the diagrams. There is no point moving on to real projects that involve AFM diagrams if the students don't understand the basics.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

This training course is an introduction to the use of the AFNI software suites for the analysis of functional MRI (fMRI) data. It is not intended as an introduction to how fMRI works but is aimed at people who are already doing fMRI data analysis, or those who will be in the near future. 
AFNI (Analysis of Functional NeuroImages) is a leading software suite of C, Python, and R programs and shell scripts, primarily developed for the analysis and display of anatomical and fMRI data. It is freely available for research purposes. 
This event was organized by the Center for Brains, Minds, and Machines (CBMM) Trainee Leadership Council.
CBMM is a multi-institutional NSF Science and Technology Center headquartered at MIT that is dedicated to developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding. CBMM brings together computer scientists, cognitive scientists, and neuroscientists to create a new field—the science and engineering of intelligence.

In this activity, students will explore 12 different career development events through a station activity. The purpose of this activity is for students to explore different educational and personal growth opportunities within agricultural education / FFA.Students will have 5 minutes to complete 5 general knowledge questions and 5 questions as a part of a practicum activity. Contests included in this lesson include: Agriscience (2022 theme), Agronomy, Ag Sales, Ag Mech & Tech, Environmental & Natural Resources, Farm & Agribusiness Management, Floriculture, Food Science, Livestock Management, Meat Evaluation, Nursery Landsdape, Vet Science. 

African American Studies 101 is a multidisciplinary course that embodies the empirical study of history, politics, culture, religion and other areas within the social sciences. The essential focus is on the life experiences of peoples of African descent in the United States and globally. The course integrates the works of scholars of ancient African civilization, New World enslavement of African Americans, economics, literature, arts, race, women studies, government and sport studies. Furthermore, through the interdisciplinary lifeline of African American Studies, this course will give special attention to black athleticism.

This course aims to familiarize students with major concepts and theories related to the study of the African Diaspora primarily, though not exclusively, in the Americas (North, South, and Central). This course links, compares, and contextualizes the historical experiences of African descendants in the U.S., the Caribbean, South America, and Africa within global processes of enslavement, colonialism, and systematic oppression. The course treats the African Diaspora as 1) historical phenomenon 2) a current condition of social, economic, and political life and 3) a way of imagining the future. We will explore theories of slavery, race, and capitalism; black resistance; post-emancipation economies and current-day neoliberalism; theories of gender; environmental justice in the African Diaspora; and theories of the black digital sphere.

An A-Frame Virtual Reality Programming activity for CS0 students. Part of the CUNY CS04All project.

In this activity students will learn how to respond to greetings, how to greet and how to chat shortly with other persons.

In this activity students will learn how to respond to greetings, how to greet and how to chat shortly with other persons.

This is a fact sheet defining OER, explaining the 5 Rs of OER, and discussing the relevance of OER to adult education.

Explores needs assessment as an applied research tool. Addresses definitions of types of needs assessment and compares needs assessment approaches. Applies research skills in the creation, design and implementation of a pilot needs assessment project focused around educational inequities.

Measurable Student Learning Outcomes
Evaluate varying definitions and types of needs assessment.
Compare similarities, differences and uses for five approaches to conducting needs assessment projects.
Apply applied research skills in the creation, design and implementation of a pilot needs assessment project.
Classify the findings about educational inequities and identify action/remedy through the implementation of a pilot assessment.

Description:

This is the online, interactive version of OpenIntro's Advanced High School Statistics (https://www.openintro.org/book/ahss/). It was developed by Emiliano Vega and Ralf Youtz of Portland Community College using PreTeXt.

Advanced High School Statistics covers a first course in statistics, providing an introduction to applied statistics that is clear, concise, and accessible. This book was written to align with the AP© Statistics Course Description, but it's also popular in non-AP courses and community colleges.

We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods:

1. Statistics is an applied field with a wide range of practical applications.

2. You don't have to be a math guru to learn from real, interesting data.

3. Data are messy, and statistical tools are imperfect. But, when you understand the strengths and weaknesses of these tools, you can use them to learn about the real world.

Adapting the song "A-Hunting We Will Go," students put a "whale" in a "pail" and even "take a little "bear" and hug it if we "dare"."

Machine vision. Data wrangling. Reinforcement learning. What do these terms even mean? In AI 101, MIT researcher Brandon Leshchinskiy offers an introduction to artificial intelligence that’s designed specifically for those with little to no background in the subject. The workshop starts with a summary of key concepts in AI, followed by an interactive exercise where participants train their own algorithm. Finally, it closes with a summary of key takeaways and Q/A. All are welcome!

This is a free, foundational online learning series for any teacher and educator interested in the groundbreaking world of artificial intelligence (AI) and its transformative potential in education. Partners Code.org, ETS, ISTE and Khan Academy are offering engaging sessions with renowned experts that will demystify AI, explore responsible implementation, address bias, and showcase how AI-powered learning can revolutionize student outcomes. Join us on this journey of exploration and empowerment, and unlock the future of teaching with and about AI.

Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website.