Students observe a virtual ocean basin and two adjacent continental margins. From the characteristics of the sea floor and adjacent land, students infer where plate boundaries might be present. They then predict where earthquakes and volcanoes might occur. Finally, they draw their inferred plate boundaries in cross section.

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This model-eliciting activity (MEA) challenges students to develop a model for predicting the characteristics of a person who has committed a crime. Students work with real data on shoe length, height, and gender to develop the model. Students write a report to the crime victim that identifies a suspect and justifies their decision. The activity sets the stage for students to learn about regression models, and reinforces their understanding of central tendency and variability. It is suggested that this activity be used prior to a formal introduction to linear relationships.

Explore landscape architecture construction materials, methods, and implementation practices through an interactive and simulated environment. Launch the link to view the desktop version or use a virtual reality device. The user can select a particular construction element to view real-life construction videos, 2D construction drawings, and construction phases through 3D representations. Be sure and notice the stormwater drainage animation located at the center of the courtyard with realistic sounds of rain and thunder. Videos and 2D construction drawings combined with the VR environment will allow users to get a realistic experience without physically being at a specific site.

Students will examine population density maps of the United States during the 1800s. They will learn about the Louisiana Purchase in 1803 to make and evaluate predictions about the changes in population density that resulted from this event, identifying shifts in boundaries and in areas of population density, and drawing conclusions. Students will then write a paragraph summarizing the impact of the Louisiana Purchase on the United States.

Students are presented with an engineering challenge: To design a sustainable guest village within the Saguaro National Park in Arizona. Through four lessons and six associated activities, they study ecological relationships with an emphasis on the Sonoran Desert. They examine species adaptations. They come to appreciate the complexity and balance that supports the exchange of energy and matter within food webs. Then students apply what they have learned about these natural relationships to the study of biomimicry and sustainable design. They study the flight patterns of birds and relate their functional design to aeronautical engineering. A computer simulation model is also incorporated into this unit and students use this program to examine perturbations within a simple ecosystem. The solution rests within the lessons and applications of this unit.

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:

"The first human spaceflight to Mars is expected to take place sometime within the next decade, and its success will be highly dependent on the health of its crew. The human microbiome, or the community of microorganisms inhabiting the body, has critical effects on human health, but how the journey to another planet will affect it has yet to be determined. During a space mission, the crew will experience microgravity, increased cosmic radiation, isolation, food limitations, and other stressors. While data from simulations and the International Space Station suggest that the human microbiome may be resilient to these conditions, frequent monitoring during the spaceflight will still be necessary to safeguard crew health. Microbiome perturbations will need to be actively prevented, and the establishment of a computer-based warning system will allow microbe-related disease to be quickly detected..."

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

Build equivalent fractions with different denominators. Match shapes and numbers to earn stars in the game. Challenge yourself on any level you like. Try to collect lots of stars!

Students learn about material balances, a fundamental concept of chemical engineering. They use stoichiometry to predict the mass of carbon dioxide that escapes after reacting measured quantities of sodium bicarbonate with dilute acetic acid. Students then produce the reactions of the chemicals in a small reactor made from a plastic water bottle and balloon.

I usually begin with a story about lying on a cot looking up at the stars on a dark night in the mountains, seeing countless stars and the hazy Milky Way stretching across the sky. I talk about how they seem to be part of a celestial dome rising very high above me, and I note that I do not have any way to know, as I am looking at the stars above me, how far they are away from me. I talk about how ancient people used and envisioned the stars. I mention the experiment with the Hubble Space Telescope in which the "darkest" and most empty part of space was imaged, and found to contain countless distant galaxies (search on "Hubble deep field" or go to http://www.stsci.edu/ftp/science/hdf/hdf.html).
I mention that this often leads people to consider how insignificant they are in the scheme of things. My feeling is that you are only as significant (or insignificant) as your actions make you.
I then talk a bit about how we now know that "visible" matter is organized into atoms, which are very, very small. In a way, they are like the stars in that they seem to be incomprehensibly small, while stars seem to be incomprehensibly large and distant. I then pose the question, "How does the part of this world that we observe and experience on a daily basis fit into a physical reality that spans from the incomprehensibly small to the incomprehensibly large?"
I pass-out the blank worksheet "Comparison of Lengths Relevant to Our Universe" to every student, and have them organize into groups of 2-3. The task is to fill-in the exponents corresponding to 9 distances listed in a box on the page, and to locate those distances on the logarithmic scale. I give them a couple of minutes to start working with the page, and then interrupt to ask what they need help with. This usually involves determining one of the lengths involving light years on the board. I let them complete the tasks in their small groups, then I ask group representatives to call-out their results.
Working from a set of correct answers, we then discuss the scale. For example, we note that there is a greater difference (in orders of magnitude) between the size of a proton or electron versus the size of a hydrogen atom, and the height of a person and the peak elevation of Mt. Everest. It is usually noted that humans fall near the middle of the length spectrum of the universe, which was also noted by Primack and Abrams (2006). Some students place great importance on this. I tend to note that there is a practical limitation to the size of individual cells that will have predictable functions (they need to be larger than the length scale governed by quantum mechanics) and constraints on the upper size limit of organisms made of cells, which determines where we are on the scale.

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Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost exclusively use classical block designs. Our aim with this article is to bring the existing methodology of group sequential designs to the attention of researchers in the preclinical field and to clearly illustrate its potential utility. Group sequential designs can offer higher efficiency than traditional methods and are increasingly used in clinical trials. Using simulation of data, we demonstrate that group sequential designs have the potential to improve the efficiency of experimental studies, even when sample sizes are very small, as is currently prevalent in preclinical experimental biomedicine. When simulating data with a large effect size of d = 1 and a sample size of n = 18 per group, sequential frequentist analysis consumes in the long run only around 80% of the planned number of experimental units. In larger trials (n = 36 per group), additional stopping rules for futility lead to the saving of resources of up to 30% compared to block designs. We argue that these savings should be invested to increase sample sizes and hence power, since the currently underpowered experiments in preclinical biomedicine are a major threat to the value and predictiveness in this research domain.

This activity is a classroom investigation where students predict, explore and evaluate what happens to water as it travels through the water cycle.

Module DescriptionThis educational module provides an engaging introduction to two pivotal topics within the field of information technology: Machine Learning and Data Science. Designed for students, the module emphasizes the practical applications, processes, and ethical considerations of these technologies while equipping learners with the foundational knowledge necessary to understand their roles in today’s data-driven world. By exploring both machine learning and data science, students will gain insights into how these fields work together to drive innovation across various industries.Section 1: Machine LearningMachine learning is a branch of artificial intelligence that enables systems to learn from data and make predictions without being explicitly programmed. This section will highlight its transformative impact on industries such as healthcare, finance, and entertainment, demonstrating the increasing relevance of machine learning in everyday applications.Section 2: Data ScienceData science is an interdisciplinary field that combines statistics, computer science, and domain expertise to derive insights from data. This section will explain how data science underpins machine learning by ensuring that data is collected, cleaned, and analyzed effectively.

Information visualization is concerned with the visual and interactive representation of abstract and possibly complex datasets. As we encounter growing datasets in various sectors there is an increasing need to develop effective methods for making sense of data. Information visualization relies on computational means and our perceptual system to help reveal otherwise invisible patterns and gain new insights. Across various fields, there is great hope in the power of visualization to turn complex data into informative, engaging, and maybe even attractive forms. However, it typically takes several steps of data preparation and processing before a given dataset can be meaningfully visualized. While visualizations can indeed provide novel and useful perspectives on data, they can also obscure or misrepresent certain aspects of a phenomenon. Thus it is essential to develop a critical literacy towards the rhetoric of information visualization. One of the best ways to develop this literacy is to learn how to create visualizations! The tutorials offer a practical approach to working with data and to create interactive visualizations.

The tutorials require basic familiarity with statistics and programming. They come as Jupyter notebooks containing both human-readable explanations as well as computable code. The code blocks in the tutorials are written in Python, which you should either have already some experience with or a keen curiosity for. The tutorials make frequent use of the data analysis library Pandas, the visualization library Altair, and a range of other packages. You can view the tutorials as webpages, open and run them on Google Colab, or download the Jupyter notebook files to edit and run them locally.

By the end of this unit, teachers should be able to:

Knowledge deepening 4- (a) Operation of general-purpose software packages appropriate to the subject taught by teachers, such as digital conceptualization, data analysis, simulation-based role-playing, and available references over the Internet.

Deepening Knowledge 4-(b) Assessing the accuracy and usefulness of web resources in support of the associated project-based learning process in the academic field.

بنهاية هذه الوحدة ، يجب أن يكون المعلمون قادرين على:

تعميق المعرفة 4- (أ) تشغيل حزم البرامج ذات الأغراض العامة المناسبة للمادة التي يدرسها المعلمون ، مثل التصور الرقمي وتحليل البيانات ولعب الأدوار القائم على المحاكاة والمراجع المتاحة عبر الإنترنت.

تعميق المعرفة 4- (ب) تقييم دقة وفائدة موارد الويب في دعم عملية التعلم القائم على المشاريع المرتبطة في المجال الأكاديمي.

STUDENT ACTIVITY – 1st – NGSSThis is a distance-learning lesson students can complete at home.Some living things and their offspring have traits that are similar, but not exactly alike. Students will identify the traits of plants in the outdoors and predict what the traits of their offspring would be.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. .

This is a lesson plan that allows students to engage on a field trip that simulates the experience of being a slave and traveling on the underground railroad. They will participate in a discussion after the field trip to review what was learned and critically discuss their understandings and findings from the field trip.

Students conduct their own research to discover and understand the methods designed by engineers and used by scientists to analyze or validate the molecular structure of DNA, proteins and enzymes, as well as basic information about gel electrophoresis and DNA identification. In this computer-based activity, students investigate particular molecular imaging technologies, such as x-ray, atomic force microscopy, transmission electron microscopy, and create short PowerPoint presentations that address key points. The presentations include their own explanations of the difference between molecular imaging and gel electrophoresis.

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:

"The ongoing Covid-19 pandemic has highlighted the importance of streamlining regulatory approval of medical products and technologies. Computational medicine, an emerging field integrating computational imaging and modelling, offers a pathway to refine, reduce, or replace otherwise costly and lengthy clinical trials – allowing them to be performed computationally, or in-silico. But reduced cost and time are only two benefits of in-silico trials. By performing trials on virtual populations, investigators can thoroughly explore extreme but plausible conditions that would not be feasible or ethical to consider in conventional clinical trials. They can also reduce the risk of human harm and the need for animal experiments. However, because in-silico trials are a new approach, the question of whether they can genuinely first replicate, and then expand upon, conventional trial results remains..."

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

This course emphasizes concepts and techniques for solving integral equations from an applied mathematics perspective. Material is selected from the following topics: Volterra and Fredholm equations, Fredholm theory, the Hilbert-Schmidt theorem; Wiener-Hopf Method; Wiener-Hopf Method and partial differential equations; the Hilbert Problem and singular integral equations of Cauchy type; inverse scattering transform; and group theory. Examples are taken from fluid and solid mechanics, acoustics, quantum mechanics, and other applications.

This course uses reaction kinetics, batch reactor analysis, batch distillation, batch operations scheduling, safety analysis, and the ABACUSS process simulator to introduce process design and analysis techniques.
Acknowledgements
The materials for the Fall 2006 offering of this course were drawn extensively from the materials that Professor Paul Barton used while teaching this course in past years. We are indebted to him for his long service to 10.490.