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!

07 November 2014

How did I get here? Learning to love research.

I grew up in southern Indiana, in an area stuck mid-way between small town and big city (Evansville). I thought biology and music were both pretty cool in high school. I applied to colleges in a haphazard way, auditioning on flute for some schools, and checking out biology programs at others. I eventually ended up at Western Kentucky University, mostly because of the generous academic scholarship they offered me and the WKU Forensics (Speech and Debate) team. I had competed in high school, and had lots of friends who were also on the team, so it seemed like fun thing to do. After spending so much time my first semester practicing, traveling, and competing for speech, I declared my major in my second semester as something like "corporate and organizational communications," although I really lacked an understanding of what a job in such a field would entail. I stuck with a minor in biology, since I'd already taken a semester of introductory classes. My reasoning for this adjustment was that, although biology was interesting, I didn't want to be a doctor. Moreover, I literally couldn't imagine spending years of my life working on the same biological research question. 

That spring, I went to a departmental seminar for biology because I thought it sounded interesting. My professor for introductory biology, Larry Alice, saw me there and suggested I start working for him doing research. Not one to balk at offered opportunities, I relented and started learning how to sequence DNA to determine the evolutionary relationships among species of grass. It only took a semester of actually performing research to realize how gratifying it can be. I switched my major to biology within a few months, this time keeping communications (and also history) as minors.

05 November 2014

Casting a wide net.

I was fortunate as a post-doc at NESCent to have a huge community of like-minded scholars to help me develop intellectually. I'm still very fortunate to be surrounded by folks doing awesome research, but I was hired specifically to fill a missing niche (bioinformatics) in the department. That means I need to work extra hard to find ways to connect with my new students and colleagues. While my skills are definitely desired and I have lots to contribute, many things I'm doing simply haven't been done here before, so I'm thinking creatively about how to fit in on campus. I'm doing my best to think broadly (cast a wide net), while at the same time focusing my time and energy on tasks that will have an impact (and hopefully catch a few big fish).

The benefit of working as a bioinformaticist is that I can work with anyone who has data (hint: that means pretty much everyone). My specialty as a genomicist also makes me well suited for the emerging interests of other folks on campus. I've been sitting down to talk to lots of folks about opportunities for collaboration on such projects. It's incredibly interesting to learn about different model systems, and gratifying to know that I can contribute to such a breadth of projects. At the very least, I can save folks time by providing a bit of information in current genome assembly methods, for instance.

It's easy enough to work with folks in other science departments, but I've been casting an even wider net. I was delighted when a friend from the history department came over for a chat about filtering data. He had a large digital dataset of documents and was looking through them for a particular type of data. Luckily, that type of data was always described with a particular string of text. Three lines of bash scripting later, and we managed to save him days of work. I've long been interested in these broad approaches to academia, and even attended a THATCamp meeting at NCState several months back. My brain works best when building connections between seemingly disparate ideas, so a little bit of my time in pursuing small projects like that helps keep me happy.

The unexpected returns are also nice: getting to know folks over in nursing, for example, let me know about better ways to teach in ways for which they are distinguished: applied methods (for which bioinformatics certainly applies) as well as online classes. At the risk of extending the metaphor too far, casting a wide net is making the fishing expedition of research and academia more appealing to me.