The emergence of transformer architectures in 2017 triggered a breakthrough in machine learning that today lets anyone create computer-generated essays, stories, pictures, music, videos, and programs from high-level prompts in natural language, all without the need to code. That has stimulated fervent discussion among educators about the implications of generative AI systems for curricula and teaching methods across a broad range of subjects. It has also raised questions of how to understand both these systems and the at times overstated claims made for them. This class will introduce the foundations of generative AI technology, and participants will explore new opportunities it enables for K–12 education. It will also describe and explore how an analytical frame of mind can help make clear the core issues underlying both the successes and failures of these systems. Much of the work will be project-based, involving implementing innovative teaching and learning tools and testing these with K–12 students and teachers.

Kibera, a poor community, in Nairobi, was a blank spot on the map until recently. This video from Penn State Public Broadcasting’s Geospatial Revolution shows how geospatial technology enabled residents to map resources to help their community.

Girls Who Code 3rd-5th
By: Khristina Polivanov - University of Nebraska-Lincoln, Copyright 2018 by Khristina Polivanov under Creative Commons Non-Commercial License. Individuals and organizations may copy, reproduce, distribute, and perform this work and alter or remix this work for non-commercial purposes only

NEBRASKA HONORS PROGRAM CLC EXPANDED LEARNING OPPORTUNITY CLUBS INFORMATION SHEET:
Name of Club: Girls Who Code

Age/Grade Level: 3rd-5th

Number of Attendees: (ideal number) Between 5 and 10; no more than 15

Goal of the Club: (learning objectives/outcomes) Encourage girls to be confident in themselves and their abilities while teaching them basic concepts used in computer science.

Resources: (Information for club provided by) Girls Who Code curriculum, Scratch tutorials, individual research

Content Areas: (check all that apply)

☐ Arts (Visual, Music, Theater & Performance)
☐ Literacy
☒ STEM (Science, Technology, Engineering & Math)
☐ Social Studies
☐ Wellness (Physical Education, Health, Nutrition & Character Education)
Outputs or final products: (Does the club have a final product/project to showcase to community?) There are a few Scratch and Made With Code projects that the girls can save on their account or a USB drive.

Introducing your Club/Activities: At the beginning of each club, we have a tech spotlight which highlights a woman in tech and what she’s known for (usually someone from computer science). We also have an icebreaker question about something random to get the girls’ attention and get them involved before jumping right into the activity for the day.

General Directions: If you’re unfamiliar with computer science, make sure to research or try the tutorial activities on your own so you are prepared for club. From there, each club is pretty structured in that you do the icebreaker question, a tech spotlight, and then the activity.

Tips/Tricks: If a girl doesn’t like an activity on a certain day, ask them what they’d like to see more of in the club; let the students know that you care about their opinion and that you want them to have fun. If the girls are really rowdy or get way off track, try to get them back into the activity, and if they don’t listen you can be a little more stern with them. Each group is different though, so make sure you find a balance. If you want your students to be able to save their work, make sure they can either create a Scratch account or have a folder on their computers they can save their projects to.

This course will explore innovations in information systems for health care delivery in developing countries, and focus not only on the importance of technology, but also on broader issues necessary for its success, such as quality improvement, project management, and leadership skills. 
This course is targeted toward individuals interested in designing or implementing a health information and communication technology (ICT) solution in the developing world. Implementing a health information technology project requires multidisciplinary teams. Thus, with this course, we hope to bring together individuals from a variety of disciplines—computer science, medicine, engineering, public health, policy, and business.
What you’ll learn:

Global health burden
Design thinking
Health informatics
Software development process
Evaluation and monitoring

This course is part of the Open Learning Library, which is free to use. You have the option to sign up and enroll in the course if you want to track your progress, or you can view and use all the materials without enrolling.

These materials include background for the instructor and a lab that engages student in an analysis of global inequality while learning and using the R language (a programming language for statistics). Students obtain data on the US and two other countries (one more developed and one less developed).

This course provides a challenging introduction to some of the central ideas of theoretical computer science. It attempts to present a vision of “computer science beyond computers”: that is, CS as a set of mathematical tools for understanding complex systems such as universes and minds. Beginning in antiquity—with Euclid’s algorithm and other ancient examples of computational thinking—the course will progress rapidly through propositional logic, Turing machines and computability, finite automata, Gödel’s theorems, efficient algorithms and reducibility, NP-completeness, the P versus NP problem, decision trees and other concrete computational models, the power of randomness, cryptography and one-way functions, computational theories of learning, interactive proofs, and quantum computing and the physical limits of computation. Class participation is essential, as the class will include discussion and debate about the implications of many of these ideas.

POGIL is a research-based instruction strategy comprising peer learning, development of process skills, and activities that are designed around the constructivist theory of learning cycles (pogil.org).

Guided Inquiry Activities for Programming Language Concepts is a collection of activities intended to support the use of POGIL in intermediate-level undergraduate computer science courses on functional programming and the implementation of programming languages.

Disclaimer: These activities have not yet undergone the peer-review process of The POGIL Project and so cannot be labeled "POGIL activities" ; however, they are designed based on the POGIL approach to designing activities.

The projects in this guide use a student-driven approach to learning. Instead of simply learning about AI through videos or lectures, the students completing these projects are active participants in their AI exploration. In the process, students work directly with innovative AI technologies, participate in “unplugged” activities that further their understanding of how AI technologies work, and create various authentic products—from machine learning models to video games—to demonstrate their learning.

Project 1: Programming with Machine Learning
Project 2: AI-Powered Players in Video Games
Project 3: Using AI for Robotic Motion Planning
Project 4: Machine Learning as a Service

Visit the ISTE website with all the free practical guides for engaging students in AI creation: https://www.iste.org/areas-of-focus/AI-in-education

ISTE and GM have partnered to create Hands-On AI Projects for the Classroom guides to provide educators with a variety of activities to teach students about AI across various grade levels and subject areas. Each guide includes background information for teachers and student-driven project ideas that relate to subject-area standards. The hands-on activities in the guides range from “unplugged” projects to explore the basic concepts of how AI works to creating chatbots and simple video games with AI, allowing students to work directly with innovative AI technologies and demonstrate their learning. 

This class introduces the student to the use of small telescopes, either for formal research or as a hobby.
This course covers background for and techniques of visual observation, electronic imaging, and spectroscopy of the Moon, planets, satellites, stars, and brighter deep-space objects. Weekly outdoor observing sessions using 8-inch diameter telescopes when weather permits. Indoor sessions introduce needed skills. Introduction to contemporary observational astronomy including astronomical computing, image and data processing, and how astronomers work. Student must maintain a careful and complete written log which is graded. (Limited enrollment with priority to freshmen. Consumes an entire evening each week; 100% attendance at observing sessions required to pass.)

This class introduces the student to the use of small telescopes, either for formal research or as a hobby.
This course covers background for and techniques of visual observation, electronic imaging, and spectroscopy of the Moon, planets, satellites, stars, and brighter deep-space objects. Weekly outdoor observing sessions using 8-inch diameter telescopes when weather permits. Indoor sessions introduce needed skills. Introduction to contemporary observational astronomy including astronomical computing, image and data processing, and how astronomers work. Student must maintain a careful and complete written log which is graded. (Limited enrollment with priority to freshmen. Consumes an entire evening each week; 100% attendance at observing sessions required to pass.)

This lesson gets students thinking about the ways computer hardware and software affect our daily lives.

Students use a hurricane tracking map to measure the distance from a specific latitude and longitude location of the eye of a hurricane to a city. Then they use the map's scale factor to convert the distance to miles. They also apply the distance formula by creating an x-y coordinate plane on the map. Students are challenged to analyze what data might be used by computer science engineers to write code that generates hurricane tracking models. Then students analyze a MATLAB® computer code that uses the distance formula repetitively to generate a table of data that tracks a hurricane at specific time intervals. Students come to realize that using a computer program to generate the calculations (instead of by hand) is very advantageous for a dynamic situation like tracking storm movements. Their inspection of some MATLAB code helps them understand how it communicates what to do using mathematical formulas, logical instructions and repeated tasks. They also conclude that the example program is too simplistic to really be a useful tool; useful computer model tools must necessarily be much more complex.

ObjectivesSTUDENTS WILL:Define the words HexadecimalSuccessfully convert binary and decimal to hexadecimalCreate a basic hexadecimal chartFully understand the characteristics and functions of the ascii tableAgendaActivities Note taking Create hexadecimal chart/table Practice WSReview WS Homework: Ascii Table exploration and completion of the observation WS (see file)

Hodges’ Health Career (Care Domains) Model provides a conceptual framework upon which users can map problems, issues and solutions across four knowledge domains: Interpersonal; Sociological; Scientific; & Political (Autonomy). The public may also be taught to use the model, enabling engagement, understanding and concordance in planning and outcome evaluation.

Brian Hodges' original notes, a resources page and links (800+) are included. Additional material on health informatics and the potential role of visualization in care assessment and evaluation can also be found.

In April 2006 a blog related to Hodges' model was created: 'Welcome to the QUAD':

http://hodges-model.blogspot.com/

The blog includes a bibliography and a growing archive of posts that are also tagged. There are plans to create a new website using the content management system Drupal. There is an eclectic mix posts that includes examples of using the domains of the model.

You can contact Peter Jones at h2cmng @ yahoo.co.uk and through twitter:

http://twitter.com/h2cm

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.