This Weeks Science Data Literacy Links (4/1/12)

• Air Quality Egg by @EdBorden — Kickstarter
  This is a great example of how environmental sensors can be used to collect local data and feed into shared databases. It would be really interesting to think about what types of school science could be tied to this resource. Thanks to Stacey for bringing this to my attention.
  Tags: open, sensor, citizen, science

• nsf.gov – National Science Foundation (NSF) News – NSF Leads Federal Efforts In Big Dat…
  A press release from NSF about their new efforts related to big data. Lots of interesting stuff here.
  Tags: big, data, nsf

• US NSF – Dear Colleague Letter – Data-Intensive Education-Related Research Funding Oppo…
  Unfortunately, when you say big data in educational circles it applies only to data about educational outcomes not students tapping into scientific research data.
  Tags: big, data, education

• Australian National Data Service
  This looks like an interesting effort to make research data more accessible in Australia. I really like their slogan – ANDS enables the transformation of: Data that are: to Structured Collections that are: Unmanaged –> Managed Disconnected –> Connected Invisible –> Findable Single-use –> Reusable …so that Australian researchers can easily publish, discover, access and use research data.
  Tags: data, management, standards

• US NSF – Dear Colleague Letter – Data Citation (NSF12058)
  This is an interesting “dear colleague” letter from the NSF Geosciences Director that encourages researchers to engage in “data citation” so that the data is accessible to others.
  Tags: nsf, data, policy

• Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA)…
  This will be interesting to track. A joint call for proposals from NSF and NIH. From the call, “BIGDATA seeks proposals that develop and evaluate core technologies and tools that take advantage of available collections of large data sets to accelerate progress in science, biomedical research, and engineering.”
  Tags: big, data, nsf
• Cutting Edge: Emerging trends in biostatistics | AAAS MemberCentral
  This article discusses the important role that biostatistician play in dealing with the evolving world of big data in biological and biomedical research. Thanks to Ethel for sharing this.
  Tags: big, data, statistics

Posted from Diigo. The rest of Science data literacy resources group favorite links are here.

Making a Difference with Data – BQ Workshop

The BioQUEST Curriculum Consortium, a long standing biology education reform community, has recently announced that registration is now open for our 26th Annual Summer Faculty Workshop. [disclosure: I’ve been active in BioQUEST for over 15 years now!]

This year we will be focusing on “Making a Difference with Data” from June 16-22, 2012 at Goucher College in Baltimore, MD.

BioQUEST workshops have a well earned reputation for requiring a lot of work. They focus on the collaborative development of curriculum projects and bringing realistic science experiences into classrooms. This year’s workshop will kick off with three research investigations:

• Data Literacy through Modeling
• DryadLab: Ecology and Evolution Curricula Linked to Archived Research Data
• Using Geo-referenced Animal Observations for Inquiry

You can find more information about the opening workshops here.

Visit the workshop web page for more information.

President’s Science Advisors Recommend Improvements to Undergrad STEM Education

From the American Institute of Biological Sciences Public Policy Report. http://www.aibs.org/public-policy-reports/2012_02_13.html#031974

America needs to produce considerably more college graduates with degrees in science, technology, engineering, or mathematics (STEM) over the next decade, according to a new report by the President’s Council of Advisors on Science and Technology (PCAST). One million additional STEM professionals will be needed over the next decade to fill domestic demand for employees with scientific skills.

To meet this ambitious goal, the United States would need to increase the number of undergraduates who complete college with a STEM degree by about a third over current graduation rates.

…

To achieve higher retention rates, colleges should actively engage students in class and should replace standard lab coursework with discovery-based research opportunities. [emphasis added]

It sounds like we need to start dealing with real data in our classrooms. The call to emphasize “discovery-based research opportunities” was 1 of the 5 overarching recommendations. Heading over to the PCAST report you can find the following additional information related to this proposal in the executive summary.

Traditional introductory laboratory courses generally do not capture the creativity of STEM disciplines. They often involve repeating classical experiments to reproduce known results, rather than engaging students in experiments with the possibility of true discovery. Students may infer from such courses that STEM fields involve repeating what is known to have worked in the past rather than exploring the unknown. Engineering curricula in the first two years have long made use of design courses that engage student creativity. Recently, research courses in STEM subjects have been implemented at diverse institutions, including universities with large introductory course enrollments. These courses make individual ownership of projects and discovery feasible in a classroom setting, engaging students in authentic STEM experiences and enhancing learning and, therefore, they provide models for what should be more widely implemented.

In the body of the report it gets even more explicit.

Solving rea­world problems is far more inspiring and instructive than most of the STEM instruction that occurs in the first two years of college. Research experiences in the first two years of college enable students to choose majors based on the best and most creative aspects of STEM fields rather than on courses that do not reflect the nature of inquiry.

Every college student should be given the opportunity to generate scientific knowledge through research.

I don’t know much about how this sort a report might influence policy. There are also some pretty strong recommendations about funding priorities and support for teaching scholarship in the report. Anyway – I like the language it uses, hopefully it will have legs.

Do you use policy documents like this to help you make arguments with your colleagues? administration? students?

Extracting Data from eBird Occurrence Maps

If you are not already familiar with eBird and the myriad other data resources available at the Cornell Lab of Ornithology you should take a few minutes right now to have a quick look around. Among other things the lab coordinates massive citizen science projects, does interesting research, and creates data-rich investigative curriculum materials. These are all topics I plan to tackle in future posts, but for today my goal is to share some reflections about working with a data visualization of bird migrations.

eBird describes itself as a “real-time, online checklist program” where birders and other enthusiasts can record their bird observation data. Even more importantly, from my perspective, the accumulated citizen science data can be explored through a web interface or downloaded for local analysis. The recently released reference dataset 3.0 contains over 41 million records so we are talking about a rich data resource.

Today I’m focusing in on a sub-project of eBird where the observation data were used to build spatial models of species occurrence over time. The models predict occurrence at unsampled locations by combining the available observations for each species with environmental data. They describe the project here and have links to all the species maps. What a great set of resources. There is some natural history background for each species, the maps have county boundaries, and expected occurrence is shown for each week of the year.

What follows are my ruminations about some broad “working with data” messages I plan to emphasize when sharing these data with students.

Getting Oriented:
You always have to start out by investing some effort into getting oriented to the data resources. In order to get past what some people describe as the “look-see ain’t it pretty” level of engagement ask yourself these kinds of questions:

• What is being shown? Where does the data come from? In what ways is it limited? What are some of the broad patterns in the data? What types of similarities and differences are there between datasets (species). What are some biological questions that could be addressed with this data? Do I have technical questions about the data or visualization?

Looking at the data more systematically:
At first blush these data may seem difficult to work with – you can’t control the animation, you can only see one species at a time, and you don’t really have values to work with.

Take control of the data. I downloaded the animation (be sure to get the large map version) by right clicking on the image and saving it to my hard drive. On the Mac you can use the “Preview” application to open the file and you will see that you have a collection of 52 images that are easily navigate and manipulate. [I’d be very interested in suggestions for an equivalent software tool for dealing with animated gifs on a PC.]

Now it should be easier to extract some measurements from this data. Maybe you are interested in when species W arrives in county X? How many weeks is it there? How does that compare to species Y or county Z.

Other ways to quantify the data:
It is unfortunate that we don’t have the raw data underlying these maps but there are still ways to work with what we have. We can make measurements of distance, area, and color intensity pretty easily using an image analysis tool like ImageJ.

Getting more data:
This last suggestion involves going beyond the data at hand by seeking out other data sources. These models are based (in part) on observations recorded in eBird. The project provides other tools for extracting and visualize eBird data that would allow you to see some of the raw data or bring in other species that aren’t included in the occurrence maps project. There are also lots of sources for weather, climate, habitat, and land use data that might allow you to pursue more sophisticated research.

By going to the NOAA Satellite and Information Service site and entering a zip code I was able to quickly identify 127 weather stations within 30 minutes of Hawk Mountain – a great place to observe hawk migrations in central PA.

Do you have strategies you use to help students get engage with data? Can you think of other ways to dig information out of the occurrence maps to address interesting biological questions?

You can learn a lot more about eBird here:
Wood, C., Sullivan, B., Iliff, M., Fink, D., & Kelling, S. (2011). eBird: Engaging Birders in Science and Conservation. PLoS Biology, 9(12), e1001220. Public Library of Science. Retrieved from http://dx.plos.org/10.1371/journal.pbio.1001220

I was reminded of these maps by a recent post on Flowing Data. “FlowingData explores how designers, statisticians, and computer scientists are using data to understand ourselves better – mainly through data visualization.”

Foldit: Gamification and Crowdsourcing as Science

Foldit, the online computer game for exploring protein structure, is back in the news with another Nature paper. In 2010 the group published a report on how their game environment was used to solve a protein structure – that is, predict a “biologically relevant native conformation” from an amino acid sequence. This time they report on a biological design challenge that had the community working to “enhance the activity of a computationally designed enzyme through the functional remodeling of its structure.” I’d recommend starting with the Nature News piece, “Victory for crowdsourced biomolecule design” because it provides a nice overview and it is publicly accessible. I’ll link to the two research articles through PubMed at the end of this post.

An aside: I mention that I’m linking to the papers at PubMed specifically because the full text of the articles are behind a paywall at Nature. The PubMed site provides public access to “author manuscripts” for many papers. The theme of open-access will be the focus of future posts but it is worth noting here that some of the “crowd” that contributed to this work will probably have trouble accessing the published reports of their efforts.

The Foldit project has received a lot of press and is a great launching point for brief discussions of two hot topics in science education: Crowdsourcing and gamification.

Crowdsourcing
Crowdsourcing can be loosely defined as harnessing the collective efforts of a diverse community to solve a problem. Clay Shirky really drew attention to the topic when he published, “Here Comes Everybody: The Power of Organizing Without Organizations” in 2009. More recently Michael Nielsen has focused the discussion by identifying important enablers of crowdsourcing in, “Reinventing Discovery: The New Era of Networked Science.” He provides nice descriptions of efforts like the Polymath Project and Galaxy Zoo and describes how they are redefining science.

The Foldit project has certainly gotten some traction from community input. They list “Foldit Players” as authors and you can search PubMed for “Players F” in the author field and see the publications they have accumulated. The Nature News piece includes these impressive numbers, “The game has 240,000 registered players, 2,200 of whom were active last week.” However, that works out to less 1% of the users being recently active. In fact, if you register 2,200 new users each week at the end of two years you will have 228,800 users. I would characterize the Foldit community as a gigantic number of interested people with a relatively small number of dedicated contributors. The supplement to their 2010 paper (see reference below) has lots of details about the community and they list everyone on their website – though I find the ranking systems confusing to sort through.

So, how might crowdsourcing inform science education?
I think that some of the greatest potential with respect to science education comes from the core activity of engaging learners in a community of practice. When you participate in crowdsourced science you are working toward a particular goal, operating within the norms of the community, and systematically exploring the phenomena at hand. But are they doing science? Are they learning about science? In a conference abstract titled, “Foldit Practice: Science or Gaming?” the authors describe engagement in a “hybrid space between scientific practice and gaming practice” where users “learn, talk, and do science as part and parcel to learning, talking, and playing.” Sounds pretty promising.

Gamification
Gamification is all about engaging users (hopefully learners) and focusing their attention on particular activities using game design principles. Much of the motivation in these environments is build around the pursuit of rewards like badges that confer status, or credits that can be used purchase virtual goods. If you don’t think this is a really big deal you might want to hop over to The Chronicle of Higher Education and read, “‘Badges’ Earned Online Pose Challenge to Traditional College Diplomas.” Like crowdsourcing, gamification is much bigger than science education but it is an important part of the 21st Century learning environment so we ignore it at our own peril.

Foldit has all sorts of reward systems built in. There are soloist and evolver rankings based on points you earn working independently or by evolving someone else’s solution. There are a series of introductory puzzles that teach you how to operate the interface and outline some of the biochemistry basics that frame the evaluation of different protein structural confirmations. The basic heuristics, pack the protein, hide the hydrophobics, and clear the clashes nicely capture a lot of the big ideas involved in understanding the basics of protein folding and the puzzles really pull you in with their interactivity and immediate feedback.

So, how might gamification inform science education?
I think that the biggest impact of gamification is going to come in providing learners with opportunities to practice basic procedures outside of class time. For tasks that can be easily evaluated by a computer it should be possible to combine immediate feedback and repetition in a way that allows students to independently hone those basic skills. Like the push to invert classrooms by minimizing lecture gamification may play an important role in opening up class time for collaboration and more complex problem solving. There will, of course, be many pedagogically limited applications of game design. Particularly worrisome is the inherent competitive structure in any games that may interfere with the development of more robust, collaborative learning strategies.

Are you an optimist/realist/pessimist about the educational impacts of crowdsourcing and gamification? How do you think we can help guide their use to support science education outcomes we value?

Thanks to Kristin for bringing the Foldit article to my attention.

Foldit publications:
Victory for crowdsourced biomolecule design (22 January 2012)
Increased Diels-Alderase activity through backbone remodeling guided by Foldit players (22 January 2012)
Predicting protein structures with a multiplayer online game (5 August 2010)

Recommended Reading: Rethinking AP Biology

David Knuffke has just published a short essay titled “Rethinking AP Biology” in US News & World Report. The article describes the ways that his laboratory units are evolving in response to the ongoing redesign of the Advanced Placement biology curriculum. In a nutshell, David is moving from activities that “are essentially guaranteed to succeed,” toward labs that provide students with opportunities to “research their own questions, construct their own hypotheses, conduct their own experiments, and present their findings to their peers.” He uses “failure” as a theme to explore the shifts in the labs’ structure and the students’ experiences. It sounds horrible doesn’t it? We all fear failure. Advanced Placement courses, in particular, are not designed for failure.

However, as David points out, doing science involves dealing with failure. By promoting classroom inquiry the new AP biology labs will reflect important features of doing biological research – including the increased probability of failure. Methods may not work as planned, results may not support your hypotheses, and sometimes you and your colleagues will come to different conclusions from the same data. In the face of these kinds of failures scientists, and students engaging in classroom inquiry, are forced to reexamine their assumptions, check their data, argue about experiments, and dream up new ways to test their ideas. In his essay David describes some “uneasiness” that his students experience working on inquiry labs where they are, “for the first time, being given the opportunity to fail in their labs.” Instead of focusing on protecting his students by making sure that everything is successful David now sees his role as, “a coach of the scientific process and [I] provide them with materials, methods, mentoring, and supervision.”

AP biology is on the cusp of a major reform. A section of the new AP Biology Curriculum Framework titled, “The Emphasis on Science Practices” states:

A practice is a way to coordinate knowledge and skills in order to accomplish a goal or task. The science practices enable students to establish lines of evidence and use them to develop and refine testable explanations and predictions of natural phenomena. Because content, inquiry and reasoning are equally important in AP Biology, each learning objective described in the concept outline combines content with inquiry and reasoning skills described in the science practices.

This is a pretty strong statement about making space for understanding science as a way of knowing. This commitment to curriculum reform is reinforced by structural changes like reducing the breadth of the content covered, and cutting the number of lab activities required by one third without changing the amount of time students spend on lab work.

Many AP teachers will feel like they have failed as they struggle to adjust their teaching to reflect these new expectations. Some parents will fail to appreciate these changes when their kids describe chaotic classrooms where groups are working on different research projects where no one really knows what the answer is. Administrators may fail to recognize how much support their teachers need to implement the new curriculum. Hopefully, these failures, like the myriad setbacks, false starts, and puzzling results that every scientist is familiar with, will be incorporated into the process of building a more robust understanding. Teachers, students, parents, and administrators will need to work together and invest in these new learning environments as the AP community makes a bold move to lead science education reform.

I think that David’s essay is important and I highly recommend that you read it. He has begun engaging the public in what will probably be the most visible and important discussion of biology education over the next several years. Remember, Advance Placement courses are designed to be equivalent to introductory college-level courses. There is a huge potential for this new biology framework to “trickle-up” and drive reform in undergraduate education.

Do you teach AP Bio? What questions do you have about the new curriculum? Do you think thing will really change?

Disclosure –
David and I have collaborated on a curriculum writing project within the last year.

Science Prize for Inquiry-Based Instruction

I hadn’t realized that the Science Prize for Online Resources in Education (SPORE) awards have been around for two full years already. Since 2009 the American Association for the Advancement of Science (AAAS) has selected projects each month that “best promote science education” and invited them to publish descriptions of their resources in the journal Science. The recognition and publicity that the SPORE awards provide have been an important contribution to science education. You can see the collection of essays from SPORE prize winners here.

In 2012 AAAS is changing the emphasis (and name) of the contest to focus more on inquiry teaching modules. The first Science Prize for Inquiry Based Instruction (IBI) winner has just been announced. Bruce Alberts, the editor-in-chief of Science, has written an editorial introducing this years winners titled, “Teaching Real Science.” In the editorial Alberts characterizes the goal of the award thusly, “to make it much easier for teachers everywhere to provide their students with laboratory experiences that mirror the open-ended explorations of scientists, instead of the traditional “cookbook” labs where students follow instructions to a predetermined result.”

The nomination information for the 2013 contest has also been posted. While 2012 will focus on college level science teaching, the 2013 awards will be broadened to include advanced high school and introductory undergraduate science and engineering.

There is some really nice language in the application including:

Science and engineering education are being redefined in ways that encourage all students to actively experience “science as inquiry” and “engineering as design under constraint.” And, for the first time, it is possible for advanced high school and undergraduate students to work with some of the same data and tools as practicing scientists and engineers. How can science and engineering education capitalize on these new and unprecedented opportunities?

The resource must contain no copyright restrictions.

We define a module as a coherent unit that requires between 8 and 50 hours of student work, including in-class activities and work done outside of class.

See the 2013 nomination information for details about the rules of eligibility and deadlines.

This is great stuff – lots of space for real work with data and national promotion of high quality models. I’ll be eagerly looking forward to each month’s winner.

Have you used any of the resources from the SPORE Prize recipients? Are you planning to nominate anyone for the 2013 prize cycle?

Welcome to the Learning to Swim blog

Hello World

I’m calling this blog Learning to Swim because I think it is an appropriate metaphor for the situation we find ourselves in as biology educators. Science is changing. Information and communication technologies are changing. The workplace is changing. Science education is changing (albeit slowly). In this blog I hope to focus on an important slice of this complex landscape – the use of scientific data in teaching and learning biology.

I would argue that adopting a data-centric focus to thinking about science education reform is important for three broad reasons. First, data is becoming more prevalent in all aspects of our lives. Second, data is at the center of understanding science as a way of knowing. Third, we – educators, students, curriculum specialists, publishers, administrators, and others – are entering uncharted waters when we think about data playing a central role in science education. The vast majority of our educational experiences have involved classrooms that approximate data deserts. The deluge of data that is emerging provides us with phenomenal opportunities to engage students in realistic biological inquiry. The deluge also poses vexing challenges as we try to figure out how to work effectively in this new environment.

I am not going to claim that I have answers to these challenges. However, I am committed to digging in to explore some of the hard problems we face when we try to take advantage of rich data to support deep biological understanding. I hope you will join me. The water may appear to be deep, cold, and choppy but I’m sure with a little effort we can learn to swim in it.

You can follow this link to more posts about this blog.

Are you using data in your classroom? What kinds of resources would be most useful to help you reach your teaching goals?