Learn through interactive problem solving – proven to be more effective than lectures. Enjoy interactive explorations written by award-winning teachers, researchers, and professionals. Brilliant guides you through an interactive exploration of concepts and principles, and helps you build your quantitative intuition. Learn frameworks for thinking and solving challenging problems, instead of memorizing formulas.

This course will serve as a two-week aggressively gentle introduction to programming for those students who lack background in the field. Specifically targeted at students with little or no programming experience, the course seeks to reach students who intend to take 6.001 in the Spring Term and feel they would struggle because they lack the necessary background. The main focus of the subject will be acquiring programming experience: instruction in programming fundamentals coupled with lots of practice problems. Lots of programming required, but lots of support provided.

The educator self-assessment can be used by districts to survey classroom teachers and specialists to see how computer science is currently being integrated into individual classrooms. The survey is organized by sections aligned to the Wisconsin CS standards, with individual response questions based on learning priorities within that standards. The results of this educator self-assessment could be used to see how and where CS standards are being taught, to address gaps in computer science instruction, and to identify areas in which educators need additional professional development.

The live Google Forms version can be found here: https://docs.google.com/forms/d/e/1FAIpQLSdkCcBwHv84UK1TXi0VgWngcE1JvCDAFuYq_ttSJ_d3sDVtug/viewform
Please contact CESA 11 if you would like an editable Google Form version.

The educator self-assessment can be used by districts to survey classroom teachers and specialists to see how computer science is currently being integrated into individual classrooms. The survey is organized by sections aligned to the Wisconsin CS standards, with individual response questions based on learning priorities within that standards. The results of this educator self-assessment could be used to see how and where CS standards are being taught, to address gaps in computer science instruction, and to identify areas in which educators need additional professional development.

The live Google Forms version can be found here: https://docs.google.com/forms/d/e/1FAIpQLScSo1-Q0y87e7dj7l-jGGLGeQUe-4dRmeItj9pDTPpEwcKU7A/viewform
Please contact CESA 11 if you would like an editable Google Form version.

The educator self-assessment can be used by districts to survey classroom teachers and specialists to see how computer science is currently being integrated into individual classrooms. The survey is organized by sections aligned to the Wisconsin CS standards, with individual response questions based on learning priorities within that standards. The results of this educator self-assessment could be used to see how and where CS standards are being taught, to address gaps in computer science instruction, and to identify areas in which educators need additional professional development.

The live Google Forms version can be found here: https://docs.google.com/forms/d/e/1FAIpQLSefXpaJkHLhTezTOLZrIEkFNiA5Hnn9JMXm7-1G1mjtXKqVvQ/viewform
Please contact CESA 11 if you would like an editable Google Form version.

The educator self-assessment can be used by districts to survey classroom teachers and specialists to see how computer science is currently being integrated into individual classrooms. The survey is organized by sections aligned to the Wisconsin CS standards, with individual response questions based on learning priorities within that standards. The results of this educator self-assessment could be used to see how and where CS standards are being taught, to address gaps in computer science instruction, and to identify areas in which educators need additional professional development.

The live Google Forms version can be found here: https://docs.google.com/forms/d/e/1FAIpQLSdrMI_EBnml293_X54QAXzWsS5UKbE9TAYdxx3ZXPO9YAH_zQ/viewform
Please contact CESA 11 if you would like an editable Google Form version.

These lesson plans are available for a variety of grade levels and subject areas. Plans are modular and contain both UnPlugged Activities and hands-on code-alongs that promote and reinforce computational thinking.

Learn about the Chandra X-Ray Observatory's telescope system, science instruments, and spacecraft system in this interactive activity adapted from NASA.

Code For Fun assembles, creates, reuses curricula, to provide educators with content they can use, and adjust based on their audience. Their lessons cover all the standards in the CS K-12 Framework and California K-12 Computer Science Standards.

Designed with inclusivity, cultural relevance, social justice and regional curriculum in mind, these coding & robotics programs are offered free to K-12 classrooms across subject areas.

From Code.org:

"The bridge from algorithms to programming can be a short one if students understand the difference between planning out a sequence and encoding that sequence into the appropriate language. This activity will help students gain experience reading and writing in shorthand code."

Key words:
Algorithm
Debugging

This video from NASA describes the detailed computer modeling used to predict that colliding neutron stars can produce gamma-ray bursts similar to those associated with black holes.

Students will use the Scratch Jr. app to create, compare and contrast characters. This introductory lesson will include the foundational skills students will need to begin using Scratch Jr., so it makes a great "first project" with students.Pre-requisites-Have a device available for each student (Note: instructions are written for iPad, but the app is available on Android and ChromeOS devices as well).-Ensure that the app "Scratch Jr." is installed on all of the devices. This is a free app in the iOS App Store, Google Play Store, or Chrome Web Store.-Read through this lesson plan. The teacher will be directing students through each step along the way, so familiarize yourself with the end product.

This course introduces the compilation process, presenting foundational topics on formal languages and outline each of the essential compiler steps: scanning, parsing, translation and semantic analysis, code generation, and optimization. Upon successful completion of this course, the student will be able to: describe the compilation process and explain the function of the components that comprise the structure of a compiler; apply concepts of formal languages and finite-state machines to the translation of computer languages; identify the compiler techniques, methods, and tools that are applicable to other software applications; describe the challenges and state-of-the-practice of compiler theory and practice. This free course may be completed online at any time. (Computer Science 304)

This course is offered to graduates and is a project-oriented course to teach new methodologies for designing multi-million-gate CMOS VLSI chips using high-level synthesis tools in conjunction with standard commercial EDA tools. The emphasis is on modular and robust designs, reusable modules, correctness by construction, architectural exploration, and meeting the area, timing, and power constraints within standard cell and FPGA frameworks.

Physics, modeling, application, and technology of compound semiconductors (primarily III-Vs) in electronic, optoelectronic, and photonic devices and integrated circuits. Topics: properties, preparation, and processing of compound semiconductors; theory and practice of heterojunctions, quantum structures, and pseudomorphic strained layers; metal-semiconductor field effect transistors (MESFETs); heterojunction field effect transistors (HFETs) and bipolar transistors (HBTs); and optoelectronic devices.

Theory for programmers. Introduction to programming and computability theory based on a term-rewriting, "substitution" model of computation by Scheme programs with side-effects. Computation as algebraic manipulation: provable and valid inequalities for multivariate polynomials. Scheme evaluation as algebraic manipulation and term rewriting theory. Paradoxes from self-application and introduction to formal programming semantics. Undecidability of the Halting Problem for Scheme. Properties of recursively enumerable sets, leading to Incompleteness Theorems for Scheme equivalences. Introduction to logic for program specification and verification. Hilbert's Tenth Problem. Alternate years. 6.844 is a graduate introduction to programming theory, logic of programming, and computability, with the programming language Scheme used to crystallize computability constructions and as an object of study itself. Topics covered include: programming and computability theory based on a term-rewriting, "substitution" model of computation by Scheme programs with side-effects; computation as algebraic manipulation: Scheme evaluation as algebraic manipulation and term rewriting theory; paradoxes from self-application and introduction to formal programming semantics; undecidability of the Halting Problem for Scheme; properties of recursively enumerable sets, leading to Incompleteness Theorems for Scheme equivalences; logic for program specification and verification; and Hilbert's Tenth Problem.

This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, students will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes? What are the inductive principles that allow us to acquire new knowledge from the interaction of prior knowledge with observed data? What kinds of data must be available to human learners, and what kinds of innate knowledge (if any) must they have?

Why has it been easier to develop a vaccine to eliminate polio than to control influenza or AIDS? Has there been natural selection for a 'language gene'? Why are there no animals with wheels? When does 'maximizing fitness' lead to evolutionary extinction? How are sex and parasites related? Why don't snakes eat grass? Why don't we have eyes in the back of our heads? How does modern genomics illustrate and challenge the field? This course analyzes evolution from a computational, modeling, and engineering perspective. The course has extensive hands-on laboratory exercises in model-building and analyzing evolutionary data.

Study and discussion of computational approaches and algorithms for contemporary problems in functional genomics. Topics include DNA chip design, experimental data normalization, expression data representation standards, proteomics, gene clustering, self-organizing maps, Boolean networks, statistical graph models, Bayesian network models, continuous dynamic models, statistical metrics for model validation, model elaboration, experiment planning, and the computational complexity of functional genomics problems.