As Akila narrates the story, students follow the girls and her little brother, Jabari, who communicates with the girls through the tablet. They crack codes and ciphers and solve puzzles. They also learn the history of cryptology and basics of cybersecurity to help the girls escape the cyberworld.
Dorothy, Alan and the comic book characters work to crack a briefcase password using a letter found on a spy. Meanwhile, students participating in the curriculum work to crack the code via a simulation. Students learn that social engineering is a process hackers use to figure out passwords based on personal information such as a birth dates or names of family members.
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A Research Practice Partnership, UDL4CS aims to build sustainable partnerships among districts across the country around the shared problem of practice of fostering equitable K-8 CS education and meaningful inclusion of students with disabilities. The team, led by Israel, will examine the current level of inclusion of K-12 students with disabilities and explore the barriers to inclusion that are unique and shared among districts. Based on the findings, the team will create web-based professional development resources to build the capacity of CS educators and equip them with the tools to support all learners.
For nearly two decades, the Lastinger Center has been on the leading edge of educational innovations. Its members have consistently worked to maintain a connection to existing needs for a variety of educators and learners alike, and to forecast educational trends. Long ahead of the spring of 2020, center researchers had identified an increased demand for quality online educational tools, which were accentuated by responses the coronavirus.
Our goal is to help companies worldwide save lives and save money by reducing accidents. Because 60% of the workforce does not have access to computers, our goal is to help organizations utilize technology to reach their safety goals. Therefore, in the last year our business pivoted to building technology solutions for safety training and communication. We have developed Safety Board games, a Safety Games app for iPhone, and 2-way rapid communication &lquot;Safety Nuggets&rquot; of learning. The launch of our &lquot;sister site&rquot; www.21stCenturySafety.com is planned for September 2014. The project we are submitting will compliment the mix of technologies by providing &lquot;simulation/gaming&rquot; as an alternative learning tool to traditional stand-up presentation. We have identified one OSHA compliance topic that has the largest audience not only in the US, but worldwide: chemical safety. Project Goals: Educate the workforce to handle dangerous chemicals
Enable the employee to access training materials without the use of a computer
Evaluate the retention of information learned in simulation game
Develop an engaging learning experience where the employee is motivated to take the training course because it is fun and engaging
Dashboards are a useful tool in manufacturing. They can display the rightinformation presented in the right way to every level of the organizationwhile reducing the time spent creating and distributing reports.They are a good solution, but still need design and programming to createand keep them running. If some changes or additions are necessary, it willbe necessary to get time of programmers or IT resources involved.Our proposed solution is an automatic dashboard generator that gets processdata from a database, and depending on settings will display customizedsets of data to specific users. The elements to be displayed for each userwill be defined by himself or the system administrator, but no programmingwill be necessary to make any changes. The dashboards will be presented viaa web server and presented in an app for tablets and a web site.
For this project, you will be constructing a general purpose frameworkto enable scientists to rapidly run a standard battery of tests onsocial media datasets. The framework will integrate the functionalityof several existing tools into a single data processing pipeline andprovide visualizations of the data for the researchers. Python is thepreferred development language for the project. Data to be processedwill be stored in a mixture of csv, MySQL, and mongoDB files.The first part of the analysis will consist of constructing social networksshowing the connections between the different people in the dataset.These networks will be multiplex networks, consisting of multiple types oflinks between people. The framework should be able to compute standardnetwork centrality metrics and visualize them in a file format supported byGephi ( ).The second part of the analysis will consist of evaluating the performanceof different supervised and unsupervised machine learning classifiers atpredicting variables in the dataset. These classifiers will beimplemented using the Wekatoolkit, and the framework will merely provide a wrapper around Weka.The third part of the analysis will be in creating an API for researchersto run their own customized algorithms. We will provide several examplecommunity detection algorithms for detecting tightly connected subgroups ofnodes. The demonstration dataset for this project was extracted from the Travianmultiplayer strategy game by Drs. Rolf Wigand and Nitin Agrawal from theUniversity of Arkansas.This project is sponsored by the Intelligent Agents Lab, directed by Dr. Gita Sukthankar. SandiaNational Labs is the project partner and undergrads with US citizenship mayhave the option to continue to a summer internship.
Abstract: On a typical day, humans brush teeth, read, eat, converse ... and type passwords. This last task seems to be overly time-consuming (multiple attempts, frequent resets) and insecure --- passwords are often compromised. We desire passwords that are HUMANLY USABLE, i.e., easy to generate when needed, and SECURE, i.e., any single password is hard to crack, but even knowing several passwords doesn't allow an adversary infer others. Is this possible? How? How to even measure human effort? These questions lead us to ask what (protocols and algorithms) humans can compute and cannot compute. We present a model for measuring the complexity of human computation, and apply it in a rigorous framework for password generation.
Abstract: Alternating projection algorithms have been independently discovered, and have made a significant impact, in diverse areas of science and engineering. They remain of great interest and current activity in convex optimization, and were independently discovered for general-purpose integer programming (IP) in 2005. Their use has been one component of the major advances in IP technology that now make IP a valuable and practical tool for solution of large-scale industrial problems. An essential element of the success of these methods is the application of randomization within the alternating projection framework. Since their first discovery for IP, the methods have been improved and extended in a number of directions. In this talk, we will give an overview of recent activity in these methods, including two new ideas for improving their performance.
The untold hours you invest in your assignments are hopefully buffing out your coding chops to make you invincible. If you come into the exam with a rock-solid command of pointers and memory, you are absolutely ready to crush the exam. However, it is possible to have successfully completed the assignments without mastering the material. We see students that "debug code into existence", use trial and error experimentation, have deep dependence on tools, require continual access to the course staff, brute force through permutations of * & and typecasts, and so on. If this is you, you want to rethink your strategy. By dint of effort, you may end up with a working program that earns a high score, but if the methods don't lead to comprehension, you won't be able to reproduce these results and will have a very difficult time with exams. It's not that you aren't working hard-- far from it, you may be investing more time in the assignments than most, but you need to adjust your strategy to get more out of the time you are spending. The goal of an assignment is not to get the program to work, one way or another, it is about developing an understanding how and why it works, and being able to take that understanding and write similar code in any environment, including one that doesn't have the luxury of a compiler/debugger/Valgrind/TA/sanitycheck to tell your whether the code is correct or not.
You may be on top of most of the material, but some issues remain hazy. There is a difference between a "pretty good" understanding and having the concepts completely dialed. If you're spending a lot of exam time pawing through your materials and puzzling through the concepts, it suggests that there is an opportunity to fortify your foundation beforehand. Or consider: are the errors in your answers borne out of carelessness or indicative of more significant knowledge gaps? It takes courage to be honest with yourself, it's tempting to label every mistake as an oversight: "I just forgot to use char** here instead of char*". Being a level of indirection off may be syntactically small but is conceptually enormous. The fully-formed scar tissue from completely wrestling pointers into submission is a powerful reminder to never make those mistakes again. A more iffy understanding can crack under pressure. Use the exam results to find where your expertise is lacking so you know where you need to shore it up.
The exam results could mean you're not that comfortable in the testing environment. You crank out great assignments, you thoroughly understand the material, but in the exam you get flustered, mis-read the instructions, budget your time poorly, get sloppy, or all of the above. This effects may be overcome by more practice in test-like conditions (longhand, on paper, no tools, time limits). Working on your test-taking skills won't do much for your real-world competence (as it is already good), but it could improve your course grade and these skills may also be of use in interviews. If you're sure that it's just testing prowess that you're lacking, I recommend an approach in moderation -- review your exam, introspect on what happened, brainstorm tactics for next time, do some practice -- but don't let it make you crazy. If you're confident about what you are learning, can you make your peace with the nature of the artifact captured on an exam and let it go? Lucky for us, CS as a field is an incredible meritocracy. If you have good ideas, know how to solve problems, are willing to work hard, can meet deadlines, and communicate effectively, you'll have people begging you to work for them, regardless of the impressiveness of your pedigree/transcript. One of the best colleagues I've had was a dropout from Berkeley (a fact I never let him forget :-) He is a coding ninja, architectural genius, inspiring leader, and all-around nice guy who I'd follow anywhere. Did I mention he dropped out from Cal? I admire someone who couldn't even hack it at Cal? Sheesh! 2ff7e9595c
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