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ASEE Connections

September 2018




In This Issue:

Products & Programs

North Carolina State University wins 2018 NCEES Engineering Education Award

UC Davis College of Engineering
Innovating new solutions to nourish and feed the world

Newark Element 14
Now offering educators support with samples & more

Stevens Institute of Technology
Preventing Concussions Requires Serious Brain Power

Stevens Institute of Technology
Empowering impactful global innovation in engineering

ASEE Promotion:

ASEE's Exclusive New "Engineering Education Suppliers Guide"
A new online resource designed specifically to help engineering educators locate products and services for the classroom and research.
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By Daodao Wang

The accompanying graphic explores the most recent engineering undergraduate student-to-tenure track-faculty ratios—both by discipline for the top three fields with the most graduates, and by Carnegie Classification. The numbers on the graphic represent the number of students for each faculty member. It is noteworthy that schools offering master’s degrees but not Ph.D.s have the highest ratios of students to faculty for all disciplines. While Computer Engineering has a high ratio within “B.A.” and “M.A.” schools, it also has the lowest ratio within the “Other” school category.

1 BA = Baccalaureate Colleges, MA = Master's Colleges and Universities, PhD = Doctorate-granting Universities, Other = Associates Colleges + Special Focus Institutions + Uncategorized Institutions



II. North Carolina State University wins 2018 NCEES Engineering Education Award
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Biomedical engineering department takes $25,000 grand prize for pediatric brain surgery project

The 2018 NCEES Engineering Education Award $25,000 grand prize went to the North Carolina State University UNC/NCSU Joint Department of Biomedical Engineering for their submission, Enabling Pediatric Brain Surgery through Head Stabilization. The team collaborated with clinicians and engineering professionals to design a device that allows for complete skull immobilization for pediatric patients during neurosurgery. This innovation allows for the use of neuronavigation technology, opening new possibilities for treatment in pediatric neurosurgery.

The NCEES Engineering Education Award is awarded each year to college programs that connect students, faculty, and professional engineers in collaborative projects. “The Engineering Education Award promotes projects that involve team collaboration,” said NCEES Engineering Education Award juror Michael Smith, D.Eng. “In the world of engineering, you can’t get things done without the expertise of others in the field, so the projects create an opportunity for students to work together and with professional engineers to address ideas that are innovative.”

A jury selected this year’s winners, which also include seven $10,000 awards. The jury was composed of engineering educators, members of state engineering licensing boards, and representatives from several engineering-related societies.

Looking to 2019
NCEES invites EAC/ABET-accredited programs from all engineering disciplines to compete for the 2019 awards by submitting projects that integrate professional practice and education. Projects must be in progress or completed by March 12, 2019. The entry deadline is May 1, 2019. Learn about NCEES Engineering Education Award project ideas, evaluation criteria, and more at ncees.org/award.



III. UC Davis College of Engineering: innovating new solutions to nourish and feed the world
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The UC Davis College of Engineering is a pioneer in food engineering research with experts in developing food processing technologies, improving food nutritional quality and digestibility, advancing food safety, postharvest engineering, and repurposing food waste. These efforts help us continue to discover and innovate new solutions to nourish and feed the world.

Our new Food Engineering Laboratory represents the result of strong interdisciplinary collaboration between departments and colleges at UC Davis and allows our faculty and students to accelerate cutting-edge research in food engineering.

The College of Engineering is also home to the UC Davis Coffee Center, the first multidisciplinary university research center to address the challenges and needs of the coffee industry through a holistic approach to coffee science and education.

Our researchers and educators are recognized leaders in sustainability of food, energy and water, as well as infrastructure. Their efforts improve the lives of people in California, the nation and the world


UC Davis College of Engineering by the Numbers
   • #1 for percent of women faculty among top 50 engineering programs (American Society for Engineering Education)

   • 1st post-harvest coffee research center in the U.S.
   • 1st full-body PET scanner in the world
   • 222 total faculty, including 15 National Academy members
   • 4,690 undergraduate students
       o 30 percent women
       o 23 percent underrepresented groups
   • 1,112 graduate students
       o 489 M.S.
       o 745 Ph.D.

Learn more about the UC Davis College of Engineering and connect with us on Twitter.



IV. Stevens Institute of Technology
sponsored content

Researchers at Stevens Institute of Technology are shedding new light on brain damage from concussions and other neurological conditions.

They are combining advanced neuroimaging techniques with athletic field studies and computer simulations to understand and study the motion of the brain within the skull.

The results will inform researchers on how to develop better diagnostic, therapeutic and preventative tools for concussions.

Learn more.





On the eve of the 17th anniversary of the 9/11 terrorist attacks earlier this month, Homeland Security Secretary Kirstjen Nielsen told an audience at George Washington University that sophisticated cyberweapons and hackers now pose a greater risk to U.S. security than physical attacks, the Washington Post reports. “DHS was founded 15 years ago to prevent another 9/11,” she said. “I believe an attack of that magnitude is now more likely to reach us online than on an airplane. Our digital lives are in danger like never before.” Nielsen urged state election officials to do more to secure their voting systems. A month earlier, the Associated Press reported that Republicans and Democrats alike had criticized the Trump administration for failing to have a clear national policy to safeguard upcoming elections. Nielsen, however, vowed her agency would not allow another “direct attack on our democracy,” the Post says. DHS has added electronic monitoring sensors to districts that comprise 90 percent of registered voters, but Nielsen urged state officials to also create printed records of digital ballots to ensure there’s a paper trail of votes that can be audited. To be sure, she said, physical weapons also remain a worry, and there is a growing technological element to those, too. Nielsen said she loses sleep over worries that terrorist could use drones to attack cities and infrastructure with conventional bombs or chemical weapons, according to the Post. “This isn’t sci-fi anymore.” Nielsen urged Congress to give DHS more authority to track and intercept “dangerous drones.”


A deal between the Republican and Democratic congressional campaign committees that would have banned House candidates from using hacked or stolen materials in their campaigns this fall fell apart earlier this month, the New York Times reports. The two committees worked over the summer on the pact and were apparently close to an agreement, the Times says. During the 2016 elections, Democratic Party documents were stolen by Russian hackers and released. The sticking point, sources told the Times, was how to treat hacked materials that enter the public domain through news and other sources. The GOP committee felt that House candidates should be free to use information that arises out of news reports, but the Democrats said allowing that exception would make the agreement too flimsy. The draft agreement would have also included a pledge not to abet any hacking efforts, not to seek out stolen materials and to report contacts from foreign agents to law-enforcement agencies, the paper reports. The Republican committee says it withdrew from the talks because the Democrats’ chairman had shown bad faith by talking to the Wall Street Journal about the status of the supposedly secret negotiations. But, the Times points out, the GOP chairman publicly acknowledged the negotiations last June. The Democrats pledged to abide by the terms of the pact anyway. The Republican chairman told the Times its members wouldn’t use hacked materials.





Artificial intelligence can be applied wherever data are processed. Engineers in multiple fields should learn to test and improve it.

By Vivek Wadhwa

In 1957, Herbert A. Simon predicted that within 10 years a digital computer would be the world’s chess champion. That didn’t happen until 1996. In the 1970s, Marvin Minsky predicted that “in from three to eight years we will have a machine with the general intelligence of an average human being.” Forty-five years later, our self-driving cars aren’t ready to ensure us crash-free transportation.

With artificial intelligence, we have always had great hopes and dashed expectations. But don’t be fooled: AI is here now. It may not be the stuff of science fiction yet, but it has incredible applications in science and engineering—everywhere there are large amounts of data.

Today’s AI systems attempt to reproduce the functioning of the human brain’s neural networks using a technique called deep learning, in which information is processed in layers and the connections between these layers are strengthened based on what is learned. If you tell an AI device exactly what you want it to learn and provide it with clearly labeled examples, it analyzes the patterns in those data and stores them for future application. The accuracy of its patterns depends on data, so the more examples you give it, the more useful it becomes.

The key difference between AI and the statistical analysis tools that engineers use is that an AI system keeps learning and improving itself. AI has applications in every area in which data are processed and decisions required. Wired magazine’s founding executive editor, Kevin Kelly, likens AI to electricity: a cheap, reliable, industrial-grade digital smartness running behind everything. He writes: “It will enliven inert objects, much as electricity did more than a century ago. Everything that we formerly electrified we will now cognitize. This new utilitarian AI will also augment us individually as people (deepening our memory, speeding our recognition) and collectively as a species. There is almost nothing we can think of that cannot be made new, different, or interesting by infusing it with some extra IQ.”

Businesses are already infusing AI into their products and using it to analyze the vast amounts of data they are gathering. With it, they can reduce fraud, make better forecasts, and improve operations. Google, Amazon, and Apple’s voice assistants use AI to converse with us and learn all they can to serve up better ads. Amazon is using AI not only to make recommendations on what products we should purchase but also to improve the operations of its warehouses, manage inventory, and assess the quality of fruits and vegetables it delivers.

Unfortunately, with AI, malicious players can also invade our privacy, facilitate the rigging of elections, and spread misinformation. Computer science and electronic engineering are the core AI disciplines, but the technology can be applied widely, from chaos theory to image processing and fault detection. Engineers in multiple fields should learn how to create and test AI systems, make them work more efficiently, and use them to solve a wide range of problems.

Of course, there are limits to AI. An AI device is only as good as the data it receives, and it is able to interpret data only within the narrow confines of the supplied context. It doesn’t “understand” what it has analyzed, so it is unable to apply its analysis to scenarios in other contexts. And it can’t distinguish causation from correlation. AI is more like an Excel spreadsheet on steroids than like a thinker.

The bigger issue with this form of AI is that what it has learned remains a mystery—a set of indefinable responses to data. Once a neural network has been trained, not even its designer knows exactly how it is doing what it does. It is a black box, and this can create problems in explaining the reasons for a conclusion.

The technology is rapidly advancing, however, and AI developers are working on correcting its shortcomings. There is no reason to wait. AI needs to be an integral part of every engineer’s tool kit.


Vivek Wadhwa is a Distinguished Fellow and adjunct professor at Carnegie Mellon University College of Engineering’s Silicon Valley campus.





Students’ viewing patterns point the way to more effecient hybrid instruction

By Benjamin Ahn and Devayan Bir

The hybrid course format, which teaches students through a combination of online videos and face-to-face instruction, has gained popularity in the engineering education community over the past few years. For faculty members to produce engaging experiences that ultimately improve student outcomes, it is important to understand how students use the required videos. This study examined the video-viewing behavior and reasons for deciding to watch or not watch videos among students in a sophomore-level Mechanics of Materials (MoM) course.

Two types of videos were developed for the course, which covered 34 topics over a 16-week semester: lecture videos and example problem/solution videos. The lecture videos provided overviews and rationales for topics, fundamental concepts, relevant theories, applied assumptions, and equations needed to solve solid mechanics problems. Example problem/solution videos presented systematic approaches students can use to solve solid mechanics problems. The 165 engineering students in the course were asked to watch the assigned videos prior to coming to class.

Results from descriptive and correlation analyses showed that students’ average viewing time per video was over eight minutes (80 percent of the total length) for lecture videos and four minutes (77 percent of the total length) for the example problem/solution videos. The number of times played and the percentage of completed views for each video was the same for videos lasting one minute or 22 minutes. Videos covering difficult topics were played more often. The number of views began to increase two days before exams, with the highest number of views occurring on exam days.

Findings from inductive analysis using students’ open-ended written responses indicated that students watched videos to understand and clarify concepts, prepare questions to ask in class, complete in-class assignments and homework, and review for exams. Reasons given for not watching videos included difficulty concentrating when watching long videos, insufficient details in the videos to learn materials in depth, different preferred styles of learning, and information overload in a short amount of time.

Based on this study, we suggest five strategies for creating effective videos in required sophomore-level large-enrollment engineering courses. First, create separate videos for lectures and example problems for each topic covered in the course. This approach allows students to take breaks from either lecture or example problem videos. They know what to expect when they play a video and can decide which videos to play depending on their needs. The approach also allows faculty members to produce shorter videos and add example problem videos as needed.

Second, educate students early in the semester about the purpose of the videos to ensure that their expectations are in line with the video contents. In this course, the lecture videos were not intended to cover textbook content or derive equations but rather to motivate students to learn a topic, provide a topic overview, and show the key concepts necessary for solving problems.

Third, create one video for each example problem and ensure that it explains important concepts and offers a detailed approach to solving the problem. Students prefer example videos that explain why certain equations are appropriate for a given problem, clarify assumptions that have been made, and describe how a problem resembles or is dissimilar to previously discussed problems.

Fourth, keep an eye on the number of plays for each video throughout the semester. Doing so allows instructors to detect what is confusing or interesting to students and decide whether and how to make course adjustments. They might, for instance, provide additional example problem/solution videos, spend more time explaining concepts in class, or give additional in-class example problems.

Fifth, provide quizzes as incentives for students to watch videos. In this course, short in-class concept-check quizzes accounted for 3 percent of the final grade, which encouraged students to watch videos before classes. The quizzes in combination with videos allowed for rich discussions early in the class period. These led nicely into the class’s mini-lecture or in-class assignments.


Benjamin Ahn is an assistant professor of aerospace engineering at Iowa State University, where Devayan Bir is a Ph.D. student in aerospace engineering. This article is excerpted from “Student Interactions With Online Videos in a Large Hybrid Mechanics of Materials Course” in the Spring 2018 Advances in Engineering Education.




Job–hunting? Here are a few current openings:





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COVER: SERVICE—Community and humanitarian projects are increasingly entering the engineering curriculum.

FEATURE: UNFRIENDLY SKIES—Cramped aircraft make travel tough for people with disabilities.

FEATURE: TEACHING TOOLBOX—Weak spatial skills can be permanently corrected.





ASEE Executive Director Norman Fortenberry was recently named to the NASA Advisory Council Ad Hoc Task Force on STEM Education. From NASA’s site: “NASA supports the country’s educators who play a key role in preparing the minds that will manage and lead the nation’s laboratories and research centers of tomorrow. To prepare the agency’s future workforce and leverage the agency’s unique resources, it partners with other agencies, and collaborates with the Education community.”

NASA Advisory Council Ad Hoc Task Force on STEM Education


ABSTRACT SUBMISSIONS OPEN SEPT. 4 for ASEE’s 126th Annual Conference & Exposition at the Tampa Convention Center, Tampa, Fla., June 15 – 19, 2019. See the Call for Papers (you may need to log on to the website as a member).


The second Collaborative Network for Engineering and Computing Diversity (CoNECD) conference will be April 14 – 17, 2019 at the Marriott CrystalGateway outside Washington D.C. The Deadline to Submit your Abstract is October 1, 2018 at 23:59 EDT. See the Call for Papers, and Authors’ Kit. To submit an abstract, you'll need to be logged in to ASEE. See presentations from the 2018 conference.




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