In this open-ended, hands-on activity that provides practice in engineering data analysis, students are given gait signature metric (GSM) data for known people types (adults and children). Working in teams, they analyze the data and develop models that they believe represent the data. They test their models against similar, but unknown (to the students) data to see how accurate their models are in predicting adult vs. child human subjects given known GSM data. They manipulate and graph data in Excel® to conduct their analyses.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Advancements in metagenomic technology have been a boon to research but may encroach on people’s expectation of privacy. A staggering amount of information can be derived from the cells we leave behind on everyday surfaces, and our ability to interpret this information to learn about YOU will only grow with time. While these advancements are not likely to ever be 100% accurate, they present a potential avenue for discrimination. Genetic privacy is not a new concept, and in the US and elsewhere, there are laws protecting people from some discrimination based on genomic-derived data, but metagenomics is not covered by the existing laws and requires its own ethical and legal scrutiny. Our world is rapidly becoming one with ubiquitous genetic, molecular, and data profiling. In that world, privacy will be difficult to protect unless statutes and laws are brought up to date with the advancement in biotechnology..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Workshop overview for the Data Carpentry genomics curriculum. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This workshop teaches data management and analysis for genomics research including: best practices for organization of bioinformatics projects and data, use of command-line utilities, use of command-line tools to analyze sequence quality and perform variant calling, and connecting to and using cloud computing. This workshop is designed to be taught over two full days of instruction. Please note that workshop materials for working with Genomics data in R are in “alpha” development. These lessons are available for review and for informal teaching experiences, but are not yet part of The Carpentries’ official lesson offerings. Interested in teaching these materials? We have an onboarding video and accompanying slides available to prepare Instructors to teach these lessons. After watching this video, please contact team@carpentries.org so that we can record your status as an onboarded Instructor. Instructors who have completed onboarding will be given priority status for teaching at centrally-organized Data Carpentry Genomics workshops.

Students take on the role of geographers and civil engineers and use a device enabled with the global positioning system (GPS) to locate geocache locations via a number of waypoints. Teams save their data points, upload them to geographic information systems (GIS) software, such as Google Earth, and create scale drawings of their explorations while solving problems of area, perimeter and rates. The activity is unique in its integration of technology for solving mathematical problems and asks students to relate GPS and GIS to engineering.

Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. Interested in teaching these materials? We have an onboarding video available to prepare Instructors to teach these lessons. After watching this video, please contact team@carpentries.org so that we can record your status as an onboarded Instructor. Instructors who have completed onboarding will be given priority status for teaching at centrally-organized Data Carpentry Geospatial workshops.

List of all charts available from Our World in Data related to Germany
Free to use with attribution!

This 10-day module builds on Grade 2 concepts about data, graphing, and line plots. The two topics in this module focus on generating and analyzing categorical and measurement data.  By the end of the module, students are working with a mixture of scaled picture graphs, bar graphs, and line plots to problem solve using both categorical and measurement data.

Find the rest of the EngageNY Mathematics resources at https://archive.org/details/engageny-mathematics.

Student facing mathematics units. Covers area and surface area, ratios, dividing fractions, arithmetic in base ten, expressions and equations, rational numbers, and data sets/distributions.

Student-facing 8th grade math resources. Covers transformations & congruence, slope, similarity, linear relationships, associations in data, volume, functions, scientific notation, the pythagorean theorem and irrational numbers.

STUDENT ACTIVITY - 3rd - GA/TXThis is a distance-learning lesson students can complete at home. Students will measure plants and create bar graphs to compare data to actual mature plant heights.This activity was created by Out Teach (out-teach.org), a nonprofit providing outdoor experiential learning to transform Science education for students in under-served communities.

Students will measure plants and create bar graphs to compare data to actual mature plant heights.

Students analyze their social networks using graph theory. They gather data on their own social relationships, either from Facebook interactions or the interactions they have throughout the course of a day, recording it in Microsoft Excel and using Cytoscape (a free, downloadable application) to generate social network graphs that visually illustrate the key persons (nodes) and connections between them (edges). The nodes in the Cytoscape graphs are color-coded and sized according to the importance of the node (in this activity, nodes are people in students' social networks). After the analysis, the graphs are further examined to see what can be learned from the visual representation. Students gain practice with graph theory vocabulary, including node, edge, betweeness centrality and degree on interaction, and learn about a range of engineering applications of graph theory.

This activity is designed to support a variety of STEM concepts: scientific method, making predictions, gathering and analyzing data, and developing conclusions based on experimentation. This activity draws on active student engagement, and is useful in many STEM content areas.

This activity is designed to support a variety of STEM concepts: scientific method, making predictions, gathering and analyzing data, and developing conclusions based on experimentation. This activity draws on active student engagement, and is useful in many STEM content areas.

This activity is designed to support a variety of STEM concepts: scientific method, making predictions, gathering and analyzing data, and developing conclusions based on experimentation. This activity draws on active student engagement, and is useful in many STEM content areas.

In a multi-week experiment, student groups gather data from the photobioreactors that they build to investigate growth conditions that make algae thrive best. Using plastic soda bottles, pond water and fish tank aerators, they vary the amount of carbon dioxide (or nutrients or sunlight, as an extension) available to the microalgae. They compare growth in aerated vs. non-aerated conditions. They measure growth by comparing the color of their algae cultures in the bottles to a color indicator scale. Then they graph and analyze the collected data to see which had the fastest growth. Students learn how plants biorecycle carbon dioxide into organic carbon (part of the carbon cycle) and how engineers apply their understanding of this process to maximize biofuel production.

Green computer will be one of the major contributions, which will break down the 'digital divide', the electronic gulf that separates the information rich from the information poor.

"Pre" extension - The first extension creates programming to ask the user for values that are needed to figure out the frequency of individuals showing the recessive trait. This is THE one number needed to calculate all the other frequencies. The frequency of individuals showing the recessive trait is the only one that can be observed in a population BUT it is not always given in the word problem.
"Post" extension - The second will take the frequencies and apply them to an actual population number to generate actual numbers of individuals of the 3 genotypes and numbers of each allele … in that population.

This site is dedicated to making high value health data more accessible to entrepreneurs, researchers, and policy makers in the hopes of better health outcomes for all.

This resource provides both the Childrens and Adult Hope Scales in English and Spanish. This Hope Scale is referenced in the "Administering the Hope Scale Community Toolkit" resource. The Hope Scale is the tool that a practioner measures hope with.