24 April 2015

Under-appreciated Texas wildflowers

In my ongoing quest to balance the computational aspect of my work, I've been working with the East Texas Master Naturalists to continue developing their herbarium collection of local, native plants. It's been a great synergistic relationship: they teach me about native species, and I've been setting up their herbarium database as a series of spreadsheets and documents in Google Drive.

We met this morning out at The Nature Center, a Texas Parks & Wildlife facility that houses the herbarium and has meeting space. This very wet spring has led to an abundance of iconic Texas wildflowers, like bluebonnets and primroses. Much to my delight, I also found some of my favorite spiderworts growing nearby. It's been several years since I did serious plant collections, but I still managed to spot them on a roadside on my way from campus this morning. I apparently haven't lost my skill at picking out the flower color and growth habit from the multitudes of flowers blooming right now. This beauty (picture to right) is a great example of Tradescantia ohiensis, one of the very widespread species of erect Tradescantia. Each individual flower only lasts a day before deliquescing (melting), but the plant will keep blooming until next fall, as long as it doesn't get fried in the Texas heat.

While visiting with my old friend T. ohiensis, I took the opportunity to scratch another itch that's been in my mind for several weeks now. I've been absolutely awestruck by the thistles growing on the roadsides this spring. The picture (to the left) doesn't do it justice, but these plants are almost five feet tall, and covered in menacing, spiky leaves. There appear to be several species of Cirsium here in Texas, and I'm looking forward to seeing more examples of these monsters.

While perhaps not as charismatic as other wildflowers, these two examples get a thumbs up from me as particularly cool plant species.

30 March 2015

Data Carpentry hackathon for genomics

I'm pleased to report back from the Data Carpentry (DC) genomics hackathon, which I attended last week with ~26 other folks at Cold Spring Harbor Labs in New York. The goal of this meeting was to develop modules for a DC workshop focused on analysis of next-generation sequencing and other genomic data. The original DC lessons were designed for a very general audience using ecological data, so we were tasked with outlining, organizing, and starting to write materials for a two-day workshop specifically for genomics.

Each of the following points could be thoroughly explored in their own post, but here are a few highlights from this meeting:

  • Attendees were a great mix of biology researchers and educators from a range of institutions (research intensive, primarily undergraduate), computer scientists, and assessment specialists. This meant we were pulling from a broad range of skills, and incorporating multiple perspectives in planning.
  • The length of the meeting (2.5 days) allowed us to get a running start on actually developing materials (GitHub repos here prefaced with "genomics"). In addition to "intro to Unix" material that would largely remain constant from the original DC lesson, we started developing six modules that cover a general genomics workflow: setting up a project, getting to know your data, data wrangling (QC and alignment), analysis and visualization, and cloud/HPC. I personally found it remarkable and gratifying to see so much attention paid to the initial preparatory stages of a project.
  • Numerous folks emphasized the importance of understanding your target audience. Some of these discussions related to the assumed skill level (or pre-requisites) for workshop attendees. Other conversations related the need to accommodate particular cultural or gender issues while teaching to make the learning environment comfortable for everyone. 
  • What makes DC workshops special and distinct from other courses? In developing the modules described above, we talked about the distinction between Software Carpentry and Data Carpentry, as well as if and when instructors should be expected to teach about biology (rather than computing/data analysis). The general consensus is that the focus of DC on telling a narrative about data means we should be emphasizing "best practices" for improving productivity and reproducibility, rather than advocating for particular types of analyses. That being said, there is ample opportunity during lessons to model rigorous methods, as well as provide extra resources for students to improve their skills in experimental design and statistical reasoning.
  • A particularly challenging aspect of developing such resources is assessment of student improvement following a workshop. It's challenging to evaluate how much students will retain after such a short period of time (2 days), as well as whether these skills will transfer over to their research methods. One breakout group focused on developing a strategy for surveying students prior to and directly following a workshop to measure immediate learning, as well as 3-6 months following to measure long-term gains. We targeted question formats that would address student learning in terms of the following areas: declarative knowledge (Can you recall this fact?), skills (Can you write this code?), and attitude (Will you use this skill?).

I was initially on the fence about whether to apply for the hackathon. I'm a first year professor wallowing in the murky depths of teaching a new course, and my overtaxed brain was whispering that maybe it would cause too much stress. My gut, thankfully, doesn't always listen to my brain. Moreover, the class I'm piloting this semester is an undergraduate bioinformatics class focused on genomics, so the DC hackathon fit naturally into my preparation for the last few weeks of the semester. I'm looking forward to reporting back soon about my semester-long class is wrapping up, as well as my first teaching experience for Software Carpentry workshop in a few weeks.

18 December 2014

Formal address.

Right after finishing my PhD, I started preparations to move to North Carolina to begin a job as a postdoctoral researcher. My mother accompanied me on a preliminary scouting trip to find an apartment. I was baffled and a little amused when she made sure potential landlords and leasing agents knew I was "Dr." Kate Hertweck.

My title has never really felt comfortable to me. I certainly feel like I earned it, but I don't necessarily feel compelled for other folks to address me as such. I added "PhD" to my email signature, along with my affiliation, and that seemed to suit my electronic communication needs. It took over a year before I stopped laughing when people introduced me in person using it. Now that I'm a professor, I still don't introduce myself using that title. More often than not, however, I find myself needing to clarify to various folks on (and off) campus that I am, indeed, a Doctor of Philosophy.

I've taught classes as both a graduate student and postdoc, and until now I've been comfortable with students referring to me by my first name. As I'm writing the lab manual for my class next semester, though, I'm constantly second-guessing my choices in how to reference myself. The generic "your instructor" seems so sterile and unnecessary, given that I'm writing documents specifically about me and my class. But what is a better option?

Of course, I'm a resource junkie, so I took a few minutes to look at what other folks think about this topic. I grabbed blog posts from NeuroDojo and Small Pond Science and articles from Slate and Inside Higher Ed. I was really serious about learning things, so I even read the comments. Here are the options I've discovered for how students may choose to address me:
  1. Dr. Hertweck
  2. Professor Hertweck
  3. Doctor Professor Hertweck
  4. Dr. Kate
  5. Kate
  6. Dr. Hert (pronounced "hurt")
  7. Ma'am
  8. Ms. Hertweck
  9. Mrs. Hertweck
With such a plethora of options, I definitely feel like I need to at least narrow it down for students. I find the last two to be unacceptable, and #7 to be somewhat distasteful (although I often feel compelled to address other folks as such, and it's rather unavoidable here in the South). #3 has too many syllables, with #2 almost too many. #6 exists only to amuse me. But still, I'm straddling the fence over whether to prefer formal or informal names. I've even considered offering all remaining options to students, and keeping track on which they choose (I really do like collecting data). 

I recognize all the arguments for different forms of address. The argument from NeuroDojo resonates with my personal philosophy of science. However, I'm a young, early-career female, so I may need to impose more authority on students. There doesn't seem to be a clear standard in my department, either. Moreover, when my mom introduced me as a doctor when looking for apartments, it actually made a difference (my application fee was waived). I dislike using that type of privilege, but I need to admit that it does occur.

I suppose I've spent a lot of time thinking about this particular topic because it represents a very tangible manifestation of my uncertainty with my new job description. What's appropriate clothing for me to wear to work? How formal should my language be? Moreover, how do all of these considerations interact with my own personal preferences and sense of self? If any of this sounds familiar, it's because I pondered the same issues of personal feelings vs. perceived expectations in my last post. I suspect that this current post will also not be the last.

15 December 2014

Struggling with assessment.

I'm in the final throes of course design for my bioinformatics class next semester. I've already written a bit about planning the course, and a little about my problems convincing students to take it. I've spent a lot of time getting the computer lab up and running, and a lot of time preparing course materials. Although I still need a few more students to enroll, I'm fairly certain I'll actually get to teach the course (and hey, if it doesn't make this semester, there's always two years from now? *eye roll*).

Here's where I am in planning. I've got a lecture that meets for three hours a week on Tuesday and Thursday mornings, and a lab that meets for three hours Thursday evening. Lecture is about general theories and concepts, while lab is about implementation of that content in coding and data analysis. The course content is split into two sections: the first six weeks is what I call the Bioinformatics Framework, where we talk about bioinformatics as a field of research/applications, managing data, developing pipelines, and hypothesis testing. The second part of the class is Applied Bioinformatics, where we'll cover several "vignettes" of bioinformatics applications, like sequence alignment, clustering/phylogenetics, and genome assembly. I'm pretty comfortable with this plan, including how it relates to my objectives for student learning.

My last big hurdle in course preparation is finalizing how I will assess student performance (i.e., giving grades). Because the class is based on skills development but also incorporates interdisciplinary thinking (biology + computer science), I'll need to implement a variety of assignment formats. I'm planning at least one formative assessment for students to turn in each week to make sure everyone's on the same page. I'm also going to have each student do a class project: researching a type of bioinformatic analysis not covered in class (like protein structure/folding, network analysis, metabolomics, etc). They will present their findings on the major challenges, methods, and applications in that topic to the class, so we'll get a broader feeling for research topics than what I'll have time to cover.

My problem is that I need to be able to explain exactly what students learned during the semester (summative assessment). This is partly for my own ability to track student performance, but also for reporting to departmental and university groups. However, I appear to have developed an allergy to things called "exams" (the most common form of summative assessment). I get anxious just thinking about having to write, administer, and grade an exam.

Azuki beans. They are pretty,
but I am no bean (or point) counter.
(thanks Wikimedia Commons)
I met with a fantastic instructional designer (Leslie Lindsey) from the aptly-named Office of Instructional Design last week, and we talked about different approaches to evaluating student performance. She validated me in my belief that I can give a course that does not include exam-based assessment. She helped me realize that my aversion to exams seems to be a fear of the reductionism of simply counting points to assess student learning, which seems to be required to give a final letter grade in the class. What she said to me blew my mind: "Think of assessments as a way of collecting data about student performance."

Oh, the irony! I'm teaching a class on using computers to analyze biological data and I failed to realize that assessing student performance and assigning grades is just another data analysis problem. I was getting bogged down in my imagined obligations as a professor, and not thinking about this enough as a data analysis problem. My problem is largely semantic, and perhaps I just need to think about offering a different kind of exam, designed to emphasize the things I value as a professor. I value steady, consistent effort by students throughout the semester, even if it means I need to keep up with grading on a weekly basis. I value student comprehension that allows conceptual synthesis and connection between topics, but understand this may take more time than is allowed in a class period. I don't want my need for data collection to adversely affect student grades when there are other, better means of assessing their understanding.

Ultimately, I've decided to use an evaluation strategy based on "units of assessment" that are graded on a similar (but adjustable and specifiable) rubric. Weekly assignments in both lecture and lab will count as 1 unit each. Research projects for each class will have multiple parts, each of which counts as 1 unit. For lecture, I'll have a day each for both the first and second part of the course for students to perform summative assessments. These assessments will include two parts (one in-class, one out-of-class) which count as 1 unit each. That means the summative assessments are weighted as a bit more important than weekly assessments. I'll average the rubric scores throughout the semester and convert to a letter grade. This seems much more palatable to me than assigning absolute point values or weighted percentages to every type of assessment. Also, I'm hoping it will capture student performance much more authentically than grading based on exams that occur on a few days throughout the semester.

I don't know if this makes sense to anyone else, but it's starting to make sense in my head?

12 December 2014

Departmental holiday parties, then and now.

My PhD advisor, Chris Pires, sent me this picture via email a few days ago. It's the two of us at our first holiday party at University of Missouri, during my first year of graduate school in 2005. I think we won trivia or something, and got an awesome grab bag of "prizes" that included slightly broken garden shears?

Picture courtesy of Melody Kroll

My first UT Tyler Dept of Biology holiday party was today at lunch. I must not have really changed much over the last decade, because I still took leftover food (mainly dessert, because priorities). I'm also dressed a bit better than in the picture above, not necessarily because my fashion sense has changed, but so I can go to commencement tonight. I haven't participated in commencement since I graduated from high school (although I did attend my big brother's Ph.D graduation last spring). Onwards and upwards!

Now if only I could finish my class plan for bioinformatics next semester...

06 December 2014

Geeking out about acorns on the local news.

My university has a pretty decent relationship with the local news. Reporters fairly frequently contact the public relations office, seeking out an authority (i.e., professor) on the topic of the story they're preparing. A few folks in my department appear in news stories on a semi-regular basis, mostly offering facts and opinions on issues tangentially related to their areas of expertise.

I wasn't entirely surprised, therefore, when I got a phone call from the public relations office a few days ago, asking if I'd be willing to talk to a reporter. I was initially apprehensive, as I'm still trying to get my bearings in my new home state and wasn't sure I wanted to be put on the spot if asked about something controversial. I had no need for fear, though: I'd been recommended as someone who could talk about why it was there seemed to be such a large acorn crop this year.

"Heck yeah!" I thought, and calmly agreed to meet with the reporter that afternoon. I spent a few minutes doing a quick literature search. As I suspected, there's a decent amount of literature on that very topic. I made a list of talking points, including a few general notes about plant biology/ecology:

  1. Acorns are the fruit of the oak tree, created by the fertilization of a female flower by pollen from a male flower.
  2. Multiple factors can affect the development of an acorn, including how many flowers of each type are produced, effectiveness of pollination, and whether the tree has resources to dedicate to developing lots of fruits.
  3. The factors above are, in turn, dependent on temperature, amount of sunlight, and levels of precipitation.
  4. Acorn production (masting) also varies temporally (through years), spatially (across geography), and by species (some oak species produce more/larger acorns).
  5. This summer has been particularly cool and wet compared to the past (I checked average temperature and precipitation for the month of July for 2011-2014), so perhaps those conditions favor more acorn production.
  6. Trees are large and can't move, so resource allocations from previous years can affect acorn production in subsequent years.
The interview took about 15 minutes. We went outside and stood near some conveniently located oaks near my building. Of course, the talking points I had planned were shuffled around and reframed depending on the questions he asked, but I think I covered everything listed above and more (acorns are food for wildlife, they do eventually grow into trees, etc). Then the reporter grabbed a totally awkward shot of me walking down a path looking at leaves.

It's totally cringe worthy, but I know at least my dad will want the link, so you can see how my talking points above translated into the final story here: KLTV News, Why so many acorns this fall?

Lessons learned: keep makeup and a blazer in my office, to prepare for next time. Be a more careful about preparing appropriate sound-bites. I was also surprised to learn how much trouble the reporter had getting someone to talk to him about this; a number of arborists in town completely blew him off. I thought it was super cool! That's probably a good thing, because the public relations representative said at the end of the interview, "Great! I can add you to the list to talk about plant stuff!"

Great, indeed. Let's call this "service to the university." 

04 December 2014

A catalysis meeting on long term experimental evolution.

Travel makes it easy to let blog posts slip away without being fully formed, written, and posted. Now that the semester is winding down, I'm going to try and follow through with writing the backlog of posts that have been piling up from my adventures over the last few weeks. Today's report is about the first part of my trip back to NESCent and North Carolina the week before Thanksgiving.

The catalysis meeting I attended on long term experimental evolution (you can read a little more about the meeting and participants here) was not only fantastic but also the last NESCent will host (more on this in a later post). Although the topic is outside of my main research interests, I answered the solicitation to participate in this meeting because of some research I've been doing with Joe Graves, Michael Rose and colleagues on experimentally evolved Drosophila populations. Moreover, there seem to be some really interesting opportunities to explore robustness of analytical methods using experimental evolution data, which is of particular interest to me.

Here are the things I found compelling about this meeting:
  1. Meeting organizers set the tone. Rob Lanfear, the main organizer, put together a fantastic webpage and started a Mendeley group so we could share literature beforehand.
  2. The participants were diverse. Forty four percent of attendees were female. There were graduate students, postdocs, early career scientists, and senior researchers present, and folks came from all over the world. Model systems included microbes, invertebrates, fish and trees. 
  3. We capitalized on the group's diversity. As an early career scientist, I was pleased to develop relationships with a number of other folks starting faculty jobs at similar institutions. As a group, I was gratified to hear well-respected, senior scientists describing junior scientists' research as "brilliant." There were multiple types of interactions incorporated into the meetings such that folks who were hesitant to speak in full-group discussions could still contribute ideas. In short, this meeting exhibited many aspects of scientific discourse that are overlooked, but which I value deeply.
  4. Attendees were invested in the meeting itself. Part of the meeting was structured (or perhaps more accurately, unstructured) as an "unconference," with participants determining topics for talks and group discussions on the fly. Despite this free-form format, folks in this group were very interested in talking about broader research ideas, rather than pushing their own agendas.
I left the meeting with a much wider and deeper understanding of experimental evolution as an active field of research, as well as a better grasp on different ways of thinking about the process of science and its limitations. I was also grateful to participate in one last meeting of this type at NESCent...stay tuned for my next post to hear more about that!