In this media-rich, self-paced lesson, students explore the industries that produce and rely on advanced technology and assess how their goals and interests may make them well suited for a career in this cutting-edge sector.

The Play Make Learn Conference is a place for collaboration and discovery in the design, research and practice of playful learning, games for learning and positive social impact, making and makerspaces, STEAM education, and arts in education. PML creates an inspirational space for preK-12 educators, designers, developers, innovators, librarians, museum professionals, makers, and researchers to tinker together, share knowledge, and celebrate one another’s work.

"I created this site to make it a little easier for parents, teachers and students to find resources, games, and have additional resources to support online learning without having to create a bunch of new accounts or remember a bunch of passwords. This is a database of links to free educational pre-K-12th grade games and research tools with no log ins or sign ups or memberships required. This site is aligned to Common Core Standards, teacher and parent needs and student interests.
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I invite you to explore and play and to maybe learn something new."

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"This site came about in early 2020 when schools around the country started to close, due to COVID 19. I saw online that there were a lot of resources that families could access, but felt that the choices were overwhelming to parents and kids who were looking for some fun and educational things to do online. I narrowed down the sources and put them onto a manageable site that is easy for kids and parents to use. The use of technology is encouraged in schools and at home in order to support student engagement. With technology, I hope to inspire the STEM leaders and innovators of tomorrow.

All of the links on this site are aligned with the Common Core Standards and are all age appropriate. With these links, all materials are free to use, without having to sign up or register for anything. I hope that you enjoy exploring these sites."
-Ms. Krystal
Youth Services Coordinator

An introduction to the basic principles of computer systems with emphasis on the use of rigorous techniques as an aid to understanding and building modern computing systems. Particular attention paid to concurrent and distributed systems. Topics include: specification and verification, concurrent algorithms, synchronization, naming, Networking, replication techniques (including distributed cache management), and principles and algorithms for achieving reliability.

Coding for the AWGN channel; block and convolutional codes; lattice and trellis codes; capacity-approaching codes; equalization of linear Gaussian channels; linear, decision-feedback, and MLSD equalization; precoding; multicarrier modulation; and topics in wireless communication.

This course is an introduction to the design, analysis, and fundamental limits of wireless transmission systems. Topics to be covered include: wireless channel and system models; fading and diversity; resource management and power control; multiple-antenna and MIMO systems; space-time codes and decoding algorithms; multiple-access techniques and multiuser detection; broadcast codes and precoding; cellular and ad-hoc network topologies; OFDM and ultrawideband systems; and architectural issues.

Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of "The Ten Things Everyone Should Know About Science". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget. The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.

In computer science, program analysis is used to determine the behavior of computer programs. Flow charts are an important tool for understanding how programs work by tracing control flow. Control flow is a graphical representation of the logic present in the program. In this lesson, students learn about, design and create flow charts for different scenarios, including a game based on the Battleship® created by Hasbro©. In the associated activity, Flow Charting App Inventor, students apply their knowledge from this lesson and gain experience with a software application called App Inventor. This lesson and its associated activity can be stand-alone or used as a launching point for the Android Acceleration Application unit or any lesson involving App Inventor.

In this two-part lesson, we will build on what you’ve learned about Working with Webpages, learning how to remove the HTML markup from the webpage of Benjamin Bowsey’s 1780 criminal trial transcript. We will achieve this by using a variety of string operators, string methods and close reading skills. We introduce looping and branching so that programs can repeat tasks and test for certain conditions, making it possible to separate the content from the HTML tags. Finally, we convert content from a long string to a list of words that can later be sorted, indexed, and counted.

In this lesson you will learn how to manipulate text files using Python. This includes opening, closing, reading from, and writing to .txt files.

The next few lessons will involve downloading a web page from the Internet and reorganizing the contents into useful chunks of information. You will be doing most of your work using Python code written and executed in Komodo Edit.

This course covers the entire family of programming languages, starting with an introduction to programming languages in general and a discussion of the features and functionality that make up a modern programming language. Upon successful completion of this course, the student will be able to: identify the common concepts used to create programming languages; compare and contrast factors and commands that affect the programming state illustrate how execution ordering affects programming; identify the basic objects and constructs in Object-Oriented Programming; explain the characteristics of pure functional functions in functional programming; describe the structures and components utilized in logical programming. (Computer Science 404)

Unlike some other textbooks, this one does not follow a top-down narrative. Rather it has the flow of a conversation, with backtracking. We will often build up programs incrementally, just as a pair of programmers would. We will include mistakes, not because I don’t know the answer, but because this is the best way for you to learn. Including mistakes makes it impossible for you to read passively: you must instead engage with the material, because you can never be sure of the veracity of what you’re reading.

The main programming language used in this book is Racket. Like with all operating systems, however, Racket actually supports a host of programming languages, so you must tell Racket which language you’re programming in.

This textbook has been used in classes at: Brown University, Cal Poly, Columbus State University, Northeastern University, NYU, Reed College, UC-San Diego, UC-Santa Cruz, University of Rhode Island, University of Utah, Westmont College, Williams College, and Worcester Polytechnic Institute.

Principles of functional, imperative, and logic programming languages. Meta-circular interpreters, semantics (operational and denotational), type systems (polymorphism, inference, and abstract types), object oriented programming, modules, and multiprocessing. Case studies of contemporary programming languages. Programming experience and background in language implementation required. From the course home page: The course involves substantial programming assignments and problem sets as well as a significant amount of reading. The course uses the SCHEME+ programming language for all of its assignments.

In this culminating activity of the unit, students bring together everything they've learned in order to write the code to solve the Grand Challenge. The code solution takes two images captured by robots and combines them to create an image that can be focused at different distances, similar to the way that humans can focus either near or far. They write in a derivative of C++ called QT; all code is listed in this activity.

The goal of this book is to provide an Informatics-oriented introduction to programming. The primary difference between a computer science approach and the Informatics approach taken in this book is a greater focus on using Python to solve data analysis problems common in the world of Informatics.

Principles of mass transport and electrical signal generation for biological membranes, cells, and tissues. Mass transport through membranes: diffusion, osmosis, chemically mediated, and active transport. Electric properties of cells: ion transport; equilibrium, resting, and action potentials. Kinetic and molecular properties of single voltage-gated ion channels. Laboratory and computer exercises illustrate the concepts. For juniors and seniors. Students engage in extensive written and oral communication exercises.

Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.

Detection and measurement of radio and optical signals encountered in communications, astronomy, remote sensing, instrumentation, and radar. Statistical analysis of signal processing systems, including radiometers, spectrometers, interferometers, and digital correlation systems. Matched filters and ambiguity functions. Communications channel performance. Measurement of random electromagnetic fields. Angular filtering properties of antennas, interferometers, and aperture synthesis systems. Radiative transfer and parameter estimation.

Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical foundations of the concept will be followed by a discussion of two or three relevant research papers in computer vision, medical and biological imaging, that use the concept in different ways. We will aim to understand the fundamental techniques and to recognize situations in which these techniques promise to improve the quality of the analysis.