4
Leveraging Available Resources to Create
Greater Access to Research Opportunities
Course-based research can bring research experiences to larger numbers of students in cost-effective ways, but this approach requires a robust infrastructure to be successful and sustainable. In the second panel of the convocation, four speakers provided examples of courses that incorporate research, while also describing the availability of the infrastructure required to make those courses work. In each example—ranging from on-site sustainability research, to remote access to shared instrumentation, to accessing on-line databases, to “virtual internships”—students engage in activities available only in the context of research, but they do so through regular courses using available resources, demonstrating the widespread applicability of course-based research.
Using the Campus as the Lab
One way to make course-based research cost effective is to take advantage of the local resources that already exist. For example, the California State University system has created a partnership between faculty members and facilities management staff at its institutions to use the state university campuses as forums to explore sustainability concepts and theories (see also Box4-1). Known as The Campus as a Living Lab course,10 it involves students in design,
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10 Additional information is available at http://www.calstate.edu/cpdc/sustainability/liv-lab-grant/.
engineering, research, documentation, and public relations. It is a “holistic approach,” said Margot McDonald, architecture department head at Cal Poly-San Luis Obispo.11
As an example, she described a second-year architecture course at Cal Poly that serves about 120 students. The course was redesigned to create a focus on real world issues associated with design and building occupancy. Learning goals for students were to:
- Interpret a complex construction document set
- Perform on-site field measurements and direct observations of building performance
- Conduct a climate analysis
- Compare design intent to actual building performance
- Discuss findings with stakeholders
For example, students analyzed shading devices and day-lighting design in a new campus science building completed in 2013. Students worked with building drawings, performed field
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11 A similar effort aimed at community colleges is detailed in Cohen and Lovell, 2011.
measurements, and did a climate analysis. Pacific Gas and Electric lent students data loggers, light meters, and other measurement equipment, and much of the software used to do the computer analyses was free. Students developed a hypothesis to test, discussed findings among themselves, and presented their conclusions to the architects.
McDonald emphasized the availability of building designs, utility data, and other records for data mining. LEED (Leadership in Energy and Environmental Design) buildings are designed to collect data on building function. An extension of the Living Lab course has been a data repository from which students can download any non-proprietary data. The course organizers are now reaching out to other schools, software companies, other STEM educators, industry, and other disciplines to enhance outreach and engagement.
McDonald drew several lessons from the experience:
- The campus context provides an abundant and rich laboratory setting for data collection, analysis, and synthesis.
- The Living Lab course relates to students’ everyday experiences of occupied indoor and outdoor space to sharpen their observation skills.
- Even “bad” buildings provide great learning opportunities for students and professionals.
- Campus resources provide good access to data and documents for students to use.
In surveys, students commented positively on their experiences. For example, one student wrote, “Just being aware of these strategies should allow us to create a more suitable environment for future generations, and allow us to soften the impact of previously very wasteful practices in our field. I feel as though incorporating these practices into our projects is not only a great start to our introduction into the field, but also a start of finally realizing that these practices shouldn’t be supplemental to the overall process, but rather already incorporated into the design process.”
Sharing Instruments to Support Discovery-Based Research
The use of sophisticated analytical instruments in classes can have a major impact on students and is a common subject of proposals to government agencies like the National Science Foundation (NSF), noted Jeffrey Ryan, professor of geology and chair of the School of Geosciences at the University of South Florida. However, large analytical instruments typically are not in the classroom: they make specialized demands on such resources as space, they are expensive to maintain, and learning how to use them takes time, which is always in short supply in the undergraduate curriculum.
After a period as a geosciences program officer at NSF, Ryan began to look into ways to get the benefits of accessing and operating sophisticated instrumentation without having to own the equipment. Advances in technology already had been making remote instrumentation the norm in some fields, such as astronomy, and it was becoming more common in the geosciences. Some of the early adopters of remote access technologies in the geosciences used microbeam instruments, so Ryan requested grant support from NSF for a pilot study to use remotely operable electron probe micro-analyzers and scanning electron microscopes in two of his courses, one for majors and the other for introductory honors students (Figure 4-1).
The questions he wanted to answer were:
- Does in-class instrument use improve student confidence and interest in geoscience courses/content?
- Do these activities improve student learning of core course content?
- Do these activities foster interest and participation in undergraduate research?
- Do such activities contribute to student persistence, retention, and interest in graduate education?
In this case the instruments are at the Florida Center for Analytical Electron Microscopy on the campus of Florida International University in Miami. From Tampa, Ryan and his students used the probes to do traditional thin section petrography followed by microprobe study and electron microscopy. The courses were modified, in what Ryan called a “Full Monty intervention,” to support student projects using the instruments. Getting students up to speed on the machines was done in whole-class exercises via remote operation. Imagery could be downloaded to the web server in real time, and the machines could be operated as if they were in the same room as the operators. Students in the majors’ course did “serious discovery-based research,” said Ryan. The introductory course was more forensic in nature, in that students were expected to learn the origins of a sample.
Students had strong positive feelings about the new courses, saying that they felt empowered by the approach (Ryan, 2013). Learning gains were hard to measure because students were working at a higher level than the assessment tools available in the discipline, but at the very least, said Ryan, the new approach did no harm. Persistence and retention were excellent in the major’s course but not much different in the introductory course. “Most freshmen and sophomores come to USF as premed students, and nothing was going to make them not be doctors.” One outstanding question, said Ryan, is the “dosage” of such experiences that are needed for a beneficial impact.
The course for majors definitely facilitated subsequent involvement in research by students, Ryan observed. A quarter of the students in the course took follow-on courses. They also have requested that other courses be taught this way, and Ryan has personally taught three other such courses. Seven students expanded their in-course projects into research efforts presented at professional meetings, and six, so far, are pursuing graduate degrees.
Funding for the pilot program ended in 2010. Since then, the courses have had laboratory fees of about $30 per student to buy an hour of time on the microprobe or scanning electron microscope.
The program has been expanded to three other institutions: Florida International University, Florida Gulf Coast University, and Valencia College, which is a two-year college. The intervention now has different scales, including term projects, sets of related laboratory activities, single-laboratory demonstrations, and in-class demonstrations. Dissemination and expansion strategies include live interactive demonstrations of the project’s instructional strategies and the offer of a free day of instrument time with project staff if faculty members commit to conducting
a live remote exercise in their classroom. Similar programs could be envisioned with a wide variety of instruments across the other STEM disciplines.12
Learning from Big Data in Biology
The ability to generate large data sets often exceeds the ability to “mine” the data, and policies making many such data sets publicly available have opened up new opportunities for students. For example, between 2007 and 2013, the cost of sequencing DNA dropped 10,000-fold. This radical technological innovation has created tremendous opportunities to bring research-based courses to both college and high school classrooms, said David Micklos, founder of the DNA Learning Center at Cold Spring Harbor Laboratory.13
Many other sources of big data have become available in biology in addition to DNA sequences, ranging from other sources of molecular data to phenotypic descriptions to remote sensing of plants from drones. However, each form of data traditionally has had its own database, and converting them to a common platform has been difficult or impossible, Micklos noted. A recently developed tool called DNA Subway (Figure 4-2)14 offers a way to deal with many such data-handling issues in bioinformatics. It bundles several high-powered tools into an easy graphical user interface to assemble gene models, investigate genomes, work with phylogenetic trees, and analyze DNA barcodes.
DNA barcoding is a simple laboratory procedure that Micklos called the “do everything” research tool. Just as the unique pattern of bars in the universal product code identifies each consumer product, a short “DNA barcode” (about 600 nucleotides in length) is a unique DNA sequence that can potentially identify each species. Barcoding provides a single infrastructure that supports a very wide range of distributed projects—such as determining the species in a given ecosystem, or checking the labeling in a favorite sushi restaurant—and many of these projects can reach a satisfying endpoint in a single semester. Barcoding subsumes many important biological concepts and can integrate genetics, ecology, and conservation biology. It combines lab experimentation (extracting DNA, doing a PCR amplification of the appropriate region for sequencing) with bioinformatics (using that sequence to determine the species in a BLAST
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12 Many of the U.S. National Laboratories offer remote access to their instrumentation for scientists and students. For additional information see https://www.nomachine.com/node/2496. A Registry of Analytical Geochemistry Equipment is at http://serc.carleton.edu/NAGTWorkshops/petrology/instruments.html. The Southeastern North Carolina Regional Microanalytcal and Imaging Consortium (http://sencrmic.info/index.htm) is available for research and educational usage.
13 Additional information is available at https://www.dnalc.org/.
14 Additional information is available at http://dnasubway.iplantcollaborative.org/.
search, for example) and provides opportunities for student discovery and publication of novel findings.
The most exciting thing about DNA barcoding, said Micklos, is that it quickly brings students to the frontiers of scientific knowledge. “Are these two things the same species or different species? How do mutations alter DNA sequence? How can DNA or protein sequences be used to show relationships between different organisms? Typically, when they can’t figure something out, students blame themselves and feel that their knowledge is short. But in DNA barcoding, they can very easily see that it is not their fault but that in fact they are at the edge of scientific knowledge.” That realization can be very exciting for students!
An integrated biochemical/bioinformatics workflow can bring together all the materials needed to do barcoding as PDFs or online. DNA can be extracted easily and cheaply from almost
everything that is or once was alive, and the required sequence can be amplified by PCR.15 Students can get DNA sequences back from commercial sequencing labs in 24 to 48 hours, after which they can start to analyze and manipulate those sequences using DNA Subway. They can import sequences from elsewhere into DNA Subway, search for sequence matches, and build phylogenetic trees. In the end, they often can submit their own data to such databases as GenBank. 16
In one project, students from around New York City, including high school and college students, high school teachers, and college faculty members, looked at organisms in the urban environment, including plants, animals, and fungi. In another example, students discovered that “shark fin soup” from restaurants often contains winter skate rather than shark, and they discovered a novel sequence that was submitted to GenBank. Another project found that gingko products sold as traditional Chinese medicine often do not contain any gingko. Students used DNA barcoding to look at the diversity of ants in a Bronx park, identifying seven different species, and developed a phylogenetic tree for one case.
The other example Micklos cited, called Barcode Long Island,17 took place at summer camps from 2012 to 2014. This project supported 600 student projects engaging 1,800 students, trained 240 students as peer mentors, and studied Long Island biodiversity along with the impact of this approach to discovery-based research on students and teachers. This project utilized a supercomputer at the Texas Advanced Computing Center (the seventh largest computer in the world) to analyze the data. Projects of this sort, which help to provide information to the local community, or tackle specific local needs, can be especially engaging to students (Box 4-2).
DNA barcoding, and other genomics projects, now offer biology students opportunities to work with the same data at the same time and with the same tools as research scientists, said Micklos. “[With this access] many of us who are mainly educators in primarily undergraduate institutions are doing research that’s every bit as good as the research in Research One institutions, and coming along are lots of students.” However, taking advantage of this capability means living with several paradigm shifts, he said, including the transition from limited data to unlimited data, the transition from a world where hypotheses are underdetermined by data to a
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15 The need for PCR technology may present a barrier for some high school teachers to adopt this approach although a number of loaner programs exist. For a list of many such programs, see https://www.google.com/search?q=PCR+loaner+programs+for+high+schools.
16 Sponsored by the National Institutes of Health, GenBank is an annotated collection of all publicly available DNA sequences that is updated daily and with new releases every two months. GenBank provides and encourages access within the scientific community to the most up to date and comprehensive DNA sequence information. It places no restrictions on the use or distribution of the data contained within it. Additional information is available at http://www.ncbi.nlm.nih.gov/genbank/.
17 Additional information is available at http://www.barcodeli.org/.
world where data are underdetermined by hypotheses, and the move from reductive biology to constructive biology. Students and faculty members will need to be retrained to think about how to utilize high-performance computing. “There is plenty of capacity to do biology on supercomputers, on things called cluster computers, and in the cloud, like the Amazon cloud, but
most biology faculty don’t know where it is or how to use it.” Biology as a whole also will need to train and incorporate data scientists in research teams to cope with the era of big data, Micklos said (see also National Research Council, 2009). While challenging, successfully making this transition can provide valuable access to freely available data and tools, making it relatively inexpensive to provide research experiences for students.
Virtual Internships to Support Learning
The learning sciences have revealed that “authentic learning” makes a difference in the lives of learners, said David Shaffer, professor in the Department of Educational Psychology at the University of Wisconsin, Madison. Authentic learning combines acquisition of skills, knowledge, identity, values, and epistemology into what he called an “epistemic frame” that can guide practice. Scientists and other people who solve complex problems in communities of practice know how to link their ways of knowing with their ways of doing. And one way they learn how to do this is through practice during their education, whether through residencies, internships, moot courts, design studios, capstone courses, or research experiences. These experiences allow learners to have discussions with their peers and mentors and then reflect on what they have learned and what they have done. “It’s this cycle of action and reflection on actions that, progressively through the practicum, builds the “reflection in action” of a mature practitioner.” (See also Box 4-3)
Shaffer and his colleagues have used these ideas from the learning sciences to create virtual internships—simulated experiences that give students the opportunity to take action, reflect on that action, and develop ways of thinking about real-world practice. One simulation, for example, lets students play the role of intern at an engineering company that manufactures membranes for dialysis machines. The students conduct research on a material used for filtration membranes given the specifications requested by consultants with the company. They create simulated devices to test the materials and develop a final prototype. In teams, they determine which attributes of the material are most important and prepare a presentation that justifies their design choices. They also can communicate with live design advisers, who model how professional engineers work, help the students when they get stuck, and push them to reflect on their work. The program has been used by students ages 16 to 18 in high school classes and by first-year college engineering students (Shaffer, 2007; Chesler et al., 2013; Arastoopour et al., 2014; Chesler et al., 2015).
Real internships or real research experiences have some obvious advantages, Shaffer acknowledged, including real-world experience and work on immediate problems. But virtual internships offer realistic experiences with tractable problems. Further, in real internships, practice may be compromised and mentoring may be inconsistent, which is not the case in virtual internships. In real internships, Shaffer observed, “you could spend most of your internship doing the conceptual equivalent of washing beakers or test tubes. In the virtual internship, we know that the practice is authentic because we have designed it that way.” And, because students are under the supervision of faculty connected with the program, consistency of mentoring experiences are likely less variable. Real internships are also difficult to scale, whereas virtual internships are easy to scale, being available online.
“Of course, no one is arguing that we should just do virtual internships,” Shaffer said. “Obviously, the best of both worlds is to have both of these experiences. The point is that virtual internships can be a useful tool.” Virtual internships can be written for many different contexts, can interface with real instruments and data to provide more real-world experience, and can lead to real-world extensions of the internship that build on a student’s new knowledge and skills.
Shaffer provided data on more than 1,250 students who have done virtual internships in engineering and ecology at five universities (Shaffer, 2007; Chesler et al., 2013; Arastoopour et al., 2014; Chesler et al., 2015). Not only did the students tend to learn basic engineering concepts
better, they also maintained greater commitment and confidence in engineering, especially among the women, than a control group. Students reported positive responses to virtual internships, and the positive responses increased from the first internship to the second.
Because the computer programs used in virtual internships can record every keystroke and every decision made in navigating through the application, they also produce a wealth of data about the actions students take and the connections they make among the skills, knowledge, identity, values, and epistemology of their fields. For example, these data demonstrate that more experienced engineers rely more heavily on data and think more deeply about design considerations compared to novices (Shaffer, 2007; Chesler et al., 2013; Arastoopour et al., 2014; Chesler et al., 2015) The data also are available in real time as students work their way through an internship, allowing for ongoing modifications of the experience.
Finally, Shaffer noted that the development and use of virtual internships can boost collaborations among faculty members, disciplines, and institutions, which in turn can transform the education of students.
Educational Challenges To Leveraging Available Resources
A topic that arose during the discussion session (see Chapter 7 for a full summary of the discussions) centered on whether students should be put to work on a specific research problem or have more open-ended choices about which options to pursue. Speaking of virtual internships, Shaffer pointed to the advantages of having a defined range of options, along with the resources,
people, tools, and expectations needed to explore one or more of those options. Typically, such options converge on a specific kind of outcome, he said, though not necessarily a specific answer. The availability of big data sets also creates options for students to pursue, Ryan noted. They can either explore a data set or develop new data to analyze within the context of the larger data set.
Finally, an interesting conversation following this panel centered on Institutional Review Boards (IRBs), which can impose restrictions on education research that make it difficult to gather data from students and therefore assess and develop effective educational interventions. Shaffer pointed out that IRBs can sometimes be overzealous in finding potential dangers in educational research; this is particularly true at universities that conduct medical research. However, exemptions exist for research that takes place as part of an ordinary educational experience. One solution is to educate IRB members about the nature of educational research so that they do not perceive dangers where none exist. A National Research Council committee has studied this problem and has issued recommendations designed to balance respect for the individuals whose consent to participate makes research possible, with respect for the social benefits that productive research communities make possible (NRC, 2014a).
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