Monthly Archives: January 2018

Virtual Solar Grid comes online

Fig. 1: Modeled output of the Virtual Solar Grid
Fig. 2: A residential rooftop PV system.
If you care about finding renewable energy solutions to environmental problems, you probably would like to join an international community of Energy3D users to model existing or design new solar power systems in the real world and contribute them to the Virtual Solar Grid — a hypothetical power grid that I am developing from scratch to model and simulate interconnected solar energy systems and storage. My ultimate goal is to crowdsource an unprecedented fine-grained, time-dependent, and multi-scale computational model for anyone, believer or skeptic of renewables, to study how much of humanity's energy need can be met by solar power generation on the global scale — independent of any authority and in the spirit of citizen science. I have blogged about this ambitious plan before and I am finally pleased to announce that an alpha version of the Virtual Solar Grid has come online, of course, with a very humble beginning.

Fig. 3: The Micky Mouse solar farm in Orlando, FL.
Fig. 4: NOOR-1 parabolic troughs in Morocco.
As of the end of January, 2018, the Virtual Solar Grid has included 3D models of only a bit more than 100 solar energy systems, ranging from small rooftop photovoltaic solar panel arrays (10 kW) to large utility-scale concentrated solar power plants (100 MW) in multiple continents. At present, the Virtual Solar Grid has a lot of small systems in Massachusetts because we are working with many schools in the state.

With this initial capacity, the Virtual Solar Grid is capable of generating roughly 4 TWh per year, approximately 0.02% of all the electricity consumed by the entire world population in 2016 (a little more than 2 PWh). Although 0.02% is too minuscule to count, it nonetheless marks the starting point of our journey towards an important goal of engaging and supporting anyone to explore the solar energy potential of our planet with serious engineering design. In a sense, you can think of this work as inventing a "Power Minecraft" that would entice people to participate in a virtual quest for switching humanity's power supply to 100% renewable energy.

Fig. 5: Khi Solar One solar power tower in South Africa.
Fig. 6: PS 10 and PS 20 in Spain.
The critical infrastructure underlying the Virtual Solar Grid is our free, versatile Energy3D software that allows anyone from a middle school student to a graduate school student to model or design any photovoltaic or concentrated solar power systems, down to the exact location and specs of individual solar panels or heliostats. Performance analysis of solar power systems in Energy3D is based on a growing database of solar panel brand models and weather data sets for nearly 700 regions in every habitable continent. To construct a grid, micro or global, an Energy3D model can be geotagged — the geolocation is automatically set when you import a Google Maps image into an Energy3D model. Such a virtual model, when uploaded to the Virtual Solar Grid, will be deployed to a Google Maps application that shows exactly where it is in the world and how much electricity it produces at a given hour on a given day under average weather conditions. This information will be used to investigate how solar power and other renewables, with thermal and electric storage, can be used to provide base loads and meet peak demands for a power grid of an arbitrary size, so to speak.

Finally, it is important to note that the Virtual Solar Grid project is generously funded by the U.S. National Science Foundation through grant number #1721054. Their continuous support of my work is deeply appreciated.

Students Learn Genetics with Geniverse  

How well do students learn genetics concepts using Geniverse in their high school biology class?

Scarlett, the Geniverse female avatar, and Arrow the dragon journey to the remote Drake Breeder’s Guild.

With funding from the National Science Foundation, we sought to understand the contributions and challenges of teacher implementation of digital games by studying Geniverse, an immersive, game-like learning environment that infuses virtual experimentation in genetics with narrative elements. Our research, published in the Journal of Science Education and Technology, used a quasi-experimental design to study the replacement of existing high school biology genetics lessons with Geniverse over a three- to six-week period.

Students determine patterns of inheritance by breeding drakes, the model organism for dragons.

Results indicate that overall, students’ genetics learning increased significantly and was commensurate with genetics learning in comparison classrooms. In addition, when Geniverse was implemented as intended, student learning of genetics content was significantly greater than in the comparison, “business-as-usual” group. However, only 25% of students in the study progressed through the game to the minimum required level. Further, a wide range of levels of Geniverse implementation resulted in no significant difference between the groups as a whole.

We discovered multiple reasons for low levels of student progression, including teacher difficulties managing students moving through the game at different speeds, challenges with teaching science via student-led inquiry and exploration rather than through teacher-led, whole-class instruction, as well as multiple issues around teaching with technology. To address these issues, two new NSF-funded projects, GeniGUIDE and GeniConnect, are investigating the use of real-time student tracking, data analytics, and scaffolding with an intelligent tutoring system to assist teachers with implementation.

Needed Math for the 21st Century STEM Workplace

There are three kinds of mathematics: the math that’s taught, the math that’s learned, and the math that’s needed in the 21st century STEM workplace. With support from the Advanced Technological Education Program at the National Science Foundation, Michael Hacker, Co-Director of the Center for STEM Research at Hofstra University, and I organized a conference to study why those three “maths” are not the same.

Held in Baltimore from January 12th through the 15th, the conference attracted 46 attendees drawn from three groups: math educators, STEM content instructors, and STEM employers. Three fields of STEM employment were represented: Information and Communication Technology, Biotechnology, and Advanced Manufacturing.

There is ample evidence (see, for example, “Still Searching: Job Vacancies and STEM Skills”) that companies in these and other STEM-related fields are finding it difficult to find qualified employees for entry-level jobs. This is due in part to the poor math skills of prospective candidates, and – perhaps even more telling – their lack of confidence in their ability to “do” math. In this context, the objective of the meeting was to solicit from employers examples of problems that prospective recruits often could not solve. The meeting would then collectively examine those problems, identify the underlying relevant mathematical concepts and skills, and explore possible explanations for why high school and even two- and four-year college graduates find the problems so challenging.

A complete reporting of the findings of the conference must await our analysis of the data we collected over the course of two days of intense discussion. However, it is already evident that real-world challenges, such as those described by the employers, differ from the math problems that most students encounter in formal school settings.

An example – one of many – may illuminate these differences.

An employee in a communications technology firm is tasked with providing a commercial space, consisting of several offices as well as other rooms, with wireless Internet access. The tools available consist mainly of access points and routers, the former connecting multiple devices using radio frequency communication, the latter directing information between those devices and an Internet service provider (ISP). Access points have a limited range and their locations must be selected so that those ranges overlap, providing connectivity to every device on the network as well as to one or more routers. Routers, in turn, require connectivity to the ISP.

At first glance, the problem seems simple enough: just place the access points close enough to one another so that their ranges overlap. But real-world complications soon arise.

To save money, the number of access points should be minimized. Further, they require power so installing them in some locations may result in wiring expenses. The range of each access point may be affected by the materials used for interior walls or by metallic structures such as elevators or vaults. Privacy and security concerns dictate that access to the network be restricted, as much as possible, to the premises of the customer. Some locations within those premises – e.g., conference rooms – may require greater bandwidth than others.

These and other real-world considerations are not, strictly speaking, mathematical in nature, but insofar as they constrain the set of acceptable solutions, they require mathematical skills – e.g., modeling – that may be foreign to many would-be network technicians. Moreover, although the calculations required consist primarily of arithmetic operations on numbers (signed integers, decimals, and fractions), the semantics behind these calculations – unit conversions, use of the Pythagorean Theorem to compute point-to-point distances, algorithms for computing overall costs – are not explicitly called out in the statement of the problem.

Thus, even though the problem appears to require no more than middle school math and Algebra 1, it differs from the problems commonly encountered in traditional classes in those subjects.

  • The statement of the problem does not contain all the information required to solve it and may in fact contain irrelevant information.
  • The mathematical concepts and skills required are not spelled out (in contrast to the problems found at the end of the chapter in a math textbook, all of which involve the specific concept covered in that chapter).
  • The problem is multi-step and involves multiple variables.
  • The problem may have many solutions of varying utility, rather than a single “right” one.

A major finding of the conference was that the kind of mathematics encountered in each of the three domains represented (ICT, biotech, and manufacturing) involved contextualized problems similar to the one described above. Thus, an important barrier to success in these fields may arise from the features of such problems that we have identified.

Are there ways in which educational technologies such as those pioneered, deployed, and investigated by the Concord Consortium could help students to acquire the relevant, contextualized problem-solving skills? A major outcome of the conference may turn out to be a number of proposals aimed at answering that question.

Computational Thinking in Biology: What is an InSPECT Dataflow Diagram?

Integrating computational thinking into core science content and practices is a major goal of our InSPECT project, which is developing hands-on high school biology investigations using simple electronic sensors with Internet of Things (IoT) connectivity—a far cry from the simple germination experiments students usually encounter.

An article in the Fall 2017 Concord Consortium newsletter (“Science Thinking for Tomorrow Today”) describes the overall InSPECT project. Let’s take a closer look at a unique and powerful component of the project: virtual programming using a dataflow diagram.

The Dataflow interface enables students to do virtual programming within the browser-based interface. 

Dataflow diagrams have been around since the 1970s. They’re a visual model of the “flow” of data through a system. InSPECT has created a diagramming environment called Dataflow, the first version of which was developed in partnership with Peter Sand at Manylabs, that is much more than boxes and arrows on a page; components come alive when wirelessly synced to sensors, whose numerical data are displayed on the screen in real time as it’s recorded.

An eco-column activity includes sensors plugged into a Raspberry Pi computer. Dataflow automates data collection and initiates actions, such as raising or lowering temperature.

InSPECT is piloting an eco-column activity that includes electronic sensors plugged into a low-cost Raspberry Pi computer the size of a credit card. The sensors collect data about conditions inside the eco-column chambers, such as humidity and oxygen levels, sending it wirelessly over the Internet to Dataflow, which can automate data collection 24 hours a day, uninterrupted and unattended.

With the addition of actuators, Dataflow also can be programmed to create actions based on the sensor data. Students control the real-world actuators by defining variables and setting up conditionals that are entered directly into Dataflow’s simple, visual interface, which can run in any browser on a Mac or PC platform. For example, students can program a Dataflow diagram to adjust the current to a Peltier cooler in order to tweak the temperature of an eco-chamber when the sensor reading becomes too low or too high.

Finally, students can visualize, analyze, and interpret their data by exporting it to one of Concord Consortium’s most popular tools, CODAP (Common Online Data Analysis Platform), a free web-based environment for data analysis. Dataflow can be embedded directly into CODAP.

The use of sensor technology is still new to many biology classes, but our early research is based on the idea that when students collect data in real time, they make a powerful connection to the concepts they are studying. Using Dataflow, students not only learn to design the experiment and control the variables, they come to understand dynamic ecological systems.

The InSPECT project is currently recruiting biology teachers for our fall 2018 and spring 2019 studies. Our goal is to explore how to support integrated science practices and computational thinking in biology. We have several labs to select from involving photosynthesis, respiration, seed germination, and/or plant growth in chambers that can be from three classes to four weeks long. If you’re interested, contact us at inspect@concord.org.

An Edited Google Doodle and a Genetics Mini-Mystery

Google’s Doodle on January 9 honored Har Gobind Khorana, a Nobel laureate whose work with DNA, RNA, and protein synthesis was seminal to deciphering the genetic code. Did anyone besides us (shout out to our own Eli Kosminsky!) notice that, midway through the day, the cartoon changed?

Google Doodle in the morning…

 

The same Doodle at night!

A comparison shows that the letters vanished from the paired strands draped across the doodle, leaving the flag-like bases letterless. A look at the letters depicted in the original doodle’s strands shows the letter “U,” for the base uracil, on both sides, making the drawing look like two paired strands of RNA. It’s the paired RNA strands that was the problem, we surmise. RNA, unlike DNA, comprises a single strand of nucleotide bases or “letters,” not a double strand (which, in the case of DNA, twists into the classic double-helix shape). By labeling both strands of the molecule with RNA letters, the doodle effectively depicted RNA as an extended double-stranded molecule, which is incorrect.

Removing the letters allowed the doodle to be interpreted correctly as showing the transcription of RNA from DNA, which is not only biologically relevant, it’s also a critical component of Khorana’s work. In fact, part of Khorana’s approach involved assiduously avoiding the now-classic behavior of some RNA sequences that might have been unintentionally represented in the original doodle—a strand folding back on itself, base-pairing to form obstinate structures that can actually prevent the reading and translation of the code by cellular enzymes. In addition, synthesizing custom-coded RNA strands was much more difficult than synthesizing DNA strands, so part of the time, Khorana cleverly synthesized DNA strands and allowed the cellular enzymes to make the RNA strands for him.

You can explore how to decode the genetic code yourself using our DNA/RNA simulator!* How would you determine the number of bases (letters) in each DNA word? You can design DNA and RNA sequences that clearly answer this question, and then move on to figuring out how to use your own sequences to reveal the code.

Transcription

The process of transcription. Note that only the red RNA strand includes “U” for Uracil, so the original Doodle’s labels didn’t make sense.

Translation

The process of translation. Here, the top base pairs are passed in by tRNA, and don’t form a strand at all, so this doesn’t match the original Doodle either.

* This Next-Generation Molecular Workbench model was developed thanks to a generous grant from Google.org.

Concord Consortium Publishes Important Research in Educational Technology

Nine publications illuminate our research in educational technology in 2017. Learn about engineering design tools that may help bridge the design-science gap (#5), a systems modeling tool that supports students in the NGSS practice of developing and using models and the crosscutting concept of systems (#1), an Earth science curriculum that increases student scientific argumentation abilities (#6), the relative ease of creating hierarchical data structures (#9), automated analysis of collaborative problem solving in electronics (#8), and more.

1. New systems modeling tool supports students

The NGSS identify systems and system models as one of the crosscutting concepts, and developing and using models as one of the science and engineering practices. However, students do not naturally engage in systems thinking or in building models to make sense of phenomena. The Concord Consortium and Michigan State University developed a free, web-based, open-source systems modeling tool called SageModeler and a curricular approach designed to support students and teachers in engaging in systems modeling.

Damelin, D., Krajcik, J., McIntyre, C., & Bielik, T. (2017). Students making system models: An accessible approach. Science Scope, 40(5), 78-82.

2. Students should face the unknown and engage in frontier science questions

Students should see science as an ongoing process rather than as a collection of facts. Six High-Adventure Science curriculum modules provide an opportunity to bring contemporary science and the process of doing science into the classroom. Interactive, dynamic models help students make sense of complex Earth systems. Embedded assessments prompt students to interpret data to make scientific arguments and evaluate claims while considering the uncertainty inherent in frontier science.

Pallant, A. (2017). High-Adventure Science: Exploring evidence, models, and uncertainty related to questions facing scientists today. The Earth Scientist, 33, 23-28.

3. Automated feedback helps students write scientific arguments

Automated scoring and feedback support students’ construction of written scientific arguments while learning about factors that affect climate change. Results showed that 77% of students made revisions to their open-ended argumentation responses after receiving feedback. Students who revised had significantly higher final scores than those who did not, and each revision was associated with an increase on the final scores.

Zhu, M., Lee, H.-S., Wang, T., Liu, O. L., Belur, V., & Pallant, A. (2017). Investigating the impact of automated feedback on students’ scientific argumentation. International Journal of Science Education, 1–21.

4. Review of research on women’s underrepresentation in computing fields

This literature review synthesizes research on women’s underrepresentation in computing fields across four life stages: 1) pre-high school; 2) high school; 3) college major choice and persistence; and 4) postbaccalaureate employment. Access to and use of computing resources at the pre-high school and high school levels are associated with gender differences in interest and attitudes toward computing. In college, environmental context contributes to whether students will major in computing, while a sense of belonging and self-efficacy as well as departmental culture play a role in persistence in computing fields. Work-life conflict, occupational culture, and mentoring/networking opportunities play a role in women’s participation in the computing workforce.

Main, J. B., & Schimpf, C. (2017). The underrepresentation of women in computing fields: A synthesis of literature using a life course perspective. IEEE Transactions on Education, 60(4), 296-304.

5. Students improve knowledge by designing with robust engineering tools

Eighty-three 9th grade students completed an energy-efficient home design challenge using our Energy3D software. Students substantially improved their knowledge. Their learning gains were positively associated with three types of design actions—representation, analysis, and reflection—measured by the cumulative counts of computer logs. These findings suggest that tools are not passive components in a learning environment, but shape design processes and learning paths, and offer possibilities to help bridge the design-science gap.

Chao, J., Xie, C., Nourian, S., Chen, G., Bailey, S., Goldstein, M. H., Purzer, S., Adams, R. S., & Tutwiler, M. S. (2017). Bridging the design-science gap with tools: Science learning and design behaviors in a simulated environment for engineering design. Journal of Research in Science Teaching, 54(8), 1049-1096.

6. Students improve their scientific argumentation skills

Making energy choices means considering multiple factors, exploring competing ideas, and reaching conclusions based on the best available evidence. Our High-Adventure Science project created a free online energy module in which students compare the effects of energy sources on land use, air quality, and water quality using interactive models, real-world data on energy production and consumption, and scaffolded argumentation tasks. We analyzed pre- and post-test responses to argumentation items for 1,573 students from three middle schools and seven high schools. Students significantly improved their scientific argumentation abilities after using the energy module.

Pallant, A., Pryputniewicz, S. & Lee, H-S. (2017). The future of energy. The Science Teacher, 84(3), 61-68.

7. Students learn about sustainability

Educators must figure out how to prepare students to think about complex systems and sustainability. We elucidate a set of design principles used to create online curriculum modules related to Earth’s systems and sustainability and give examples from the High-Adventure Science module “Can we feed the growing population?” The module includes interactive, computer-based, dynamic Earth systems models that enable students to track changes over time. Embedded prompts help students focus on stocks and flows within the system, and identify important resources in the models, explain the processes that change the availability of the stock, and explore real-world examples.

Pallant, A., & Lee, H. S. (2017). Teaching sustainability through systems dynamics: Exploring stocks and flows embedded in dynamic computer models of an agricultural system. Journal of Geoscience Education, 65(2), 146-157.

8. Automated analysis sheds light on collaborative problem solving

The Teaching Teamwork project created an online simulated electronic circuit, running on multiple computers, to assess students’ abilities to work together as a team. Modifications to the circuit made by any team member, insofar as they alter the behavior of the circuit, can affect measurements made by the others. We log all relevant student actions, including calculations, measurements, online student communications, and alterations made by the students to the circuit itself. Automated analysis of the resulting data sheds light on the problem-solving strategy of each team.

Horwitz, P., von Davier, A., Chamberlain, J., Koon, A., Andrews, J., & McIntyre, C. (2017). Teaching Teamwork: Electronics instruction in a collaborative environment. Community College Journal of Research and Practice, 41(6), 341-343.

9. Students understand how to structure data

In this study participants were presented with diagrams of traffic on two roads with information about eight attributes (e.g., type of vehicle, its speed and direction) and asked to record and organize the data to assist city planners in its analysis. Overall, 79% of their data sheets successfully encoded the data. Even 62% of the middle school students created a structure that could hold the critical information from the diagrams. Students were more likely to create nested data structures than they were to produce one flat table, suggesting that hierarchical structures might be more intuitive and easier to interpret than flat tables.

Konold, C., Finzer, W., & Kreetong, K. (2017). Modeling as a core component of structuring data. Statistics Education Research Journal, 16(2), 191-212.

The Concord Consortium’s Top 10 News Stories from 2017

The year 2017 was a significant one for the Concord Consortium. Even though we lost our founder—and an amazing friend, colleague, mentor, and collaborator—our memories of Robert Tinker and his work resonate in an enduring way. Not many people can say they’ve worked with a legend. But anyone who knew our beloved founder recognized they were in the presence of a brilliant mind and a person with genuine compassion. While Bob’s passing on June 21, 2017, is a source of sadness for us all, we honor his legacy every day through our work. Share your memory of how Bob inspired you (and read stories of the many people Bob inspired).

Here, we share our year’s top 10 news stories.

1. Data Science Education Leaps into the Future

We jump-started the new field of data science education to bring about effective learning with and about data. In February 2017 we convened the Data Science Education Technology conference in Berkeley, California—right next to our West Coast office—with over 100 thought leaders from organizations around the U.S. and six continents. We’ve also hosted over a dozen meetups and webinars since that seminal event. We’re planning our schedule for 2018 and invite you to help us bring about the data science education revolution.

2. We Publish Influential Research and Analysis

We published authoritative articles in the Earth Scientist, the International Journal of Science EducationIEEE Transactions on Education, the Journal of Research in Science Teaching, the Science Teacher, the Journal of Geoscience Education, the Community College Journal of Research and Practice, the Statistics Education Research Journal, and Science Scope. We’re looking forward to 2018, too, with several papers scheduled to be published in the New Year.

3. We Embraced Our Creative Side and Reached Out to You

We embraced our creative side, and collaborated with Blenderbox to create a website that invites users to explore our work and use our free digital resources. Two jam-packed newsletters offered visionary commentary as well as practical instruction. We expanded our blog, and reached out to many more of you through Twitter and Facebook. Keep your shares and comments coming.

Energy3D can be used to design four types of concentrated solar power plants: solar power towers, linear Fresnel reflectors, parabolic troughs, and parabolic dishes.

4. General Motors Awards $200,000 Grant

General Motors is committed to powering its worldwide factories and offices with 100% renewable energy by 2050. The company furthered its commitment by awarding the Concord Consortium a $200,000 grant to promote engineering education using renewable energy as a learning context and artificial intelligence as a teaching assistant. The project will use our signature Energy3D software, an easy-to-use CAD tool for designing and simulating solar power systems.

5. What a Busy Year Presenting on the Road

We presented our free resources and research at over 25 sessions at NSTA, NARST, AERA, ISTE, BLC, American Society for Engineering Education, NSTA STEM Forum & Expo, MAST, EdSurge, International Dialogue on STEM 2017, and ISDDE2017, plus the Global Education & Skills Forum in Dubai and the International Conference on Tangible, Embedded, and Embodied Interactions in Japan. Phew! At AERA 2018 we’ll host a special session to honor the work and legacy of Bob Tinker called “Deeply Digital Learning: The Influence of Robert Tinker on STEM Education and the Learning Sciences.”

Students can explore and evaluate the condition of their local watershed using the free, web-based Model My Watershed application.

6. We Won!

Congratulations to the WikiWatershed online toolkit, which includes the Model My Watershed app developed in collaboration with the Stroud Water Research Center. It was awarded the 2017 Governor’s Award for Environmental Excellence by the Pennsylvania Department of Environmental Protection. And our Water SCIENCE project won a facilitators’ choice award in the National Science Foundation’s STEM for All Video Showcase.

7. We Partnered with Publishers to Bring STEM Inquiry Activities to More Students

  • We continued our partnership with McGraw-Hill Education to create engaging simulations for their Inspire Science elementary science curriculum. These simulations allow students to explore questions in ways that scientists and engineers do, and cover a variety of topic areas in K-5 science.
  • We incorporated our Next-Generation Molecular Workbench into PASCO’s Essential Chemistry textbook as fully interactive simulations that challenge students to explore topics in chemistry such as chemical reactions and particle motion.

If you’re interested in creating a groundbreaking STEM curriculum or pursuing an innovative new idea together, we’re excited to explore the possibilities with you.

     

8. Twenty-four Hours of Pandemonium and Prototypes

Our East and West Coast offices got together in July for a “FedEx day,” so called because the goal is to develop a blizzard of new prototypes and innovations in 24 hours and deliver them overnight! We developed prototypes for blocks-based programming in augmented reality (imagine Scratch/StarLogo, but with printable blocks that connect like puzzle pieces); a collaborative ecology game based on a tangible user interface; an internal project dashboard (think Intranet on steroids); an agent-based convection model; a way to connect real-time sensor data from our offices directly into our data exploration tool CODAP; and an open-source editor for activity transcripts. Plus President Chad Dorsey got out his power tools and built a picnic table that turns into a bench — almost Transformer-worthy.

    

   

9. Six New Employees Sign On

We welcomed six fabulous new employees in our Concord, MA, and Emeryville, CA, offices: Tom Farmer, Lisa Hardy, Eli Kosminsky, Andrea Krehbiel, Joyce Massicotte, and Judi Raiff. Want to join our growing family? We’re hiring!

10. Thirty-One Projects Research and Develop Educational Technology and Curriculum

Through 31 research projects with countless amazing collaborators, we’re extending our pioneering work in the field of probeware and other tools for inquiry and continuing to develop award-winning STEM models and simulations. We’re taking the lead in new areas, including data science education, analytics and feedback, and engineering and science connections. And we’re exploring and creating cutting-edge new tools and technologies for tomorrow’s learners in our innovation lab.