After articulating that my most dire need is to get funded, it may seem disjointed to embark on a series of blog posts about teaching, but there you have it, the life of a professor at a place that requires both research and teaching. I still contend that I will get fired from my job much more quickly for failure to teach a course than failure to get funded, so I must do something about the new preparation I have for the fall.
The new course, "Experimental Design and Data Analysis," is a graduate-only course with only a loose definition in the course catalog. It hasn't been taught for the past couple of years, and the faculty member who designed it has now left academia. So it is pretty much mine to do with what I'd like, and what I'd like to do is lead a course that teaches graduate students proper methods for designing field-based research projects and for analyzing data that comes from such projects. That's about the total amount of thought I'd given this course when it opened for registration, and now that I've got students enrolled and classes starting in less than 2 months, I need to put a bit more thought into the course design.
This is the first time I've had the opportunity to design a non-standard course, and the blankness of the slate, is, frankly, a little overwhelming. So I've decided that I'm going to work through SERC's course design tutorial, and blog it as I go along. I figure that the course is general enough that many of you probably have good ideas that you might willing to contribute. Plus, the course design blogging process seemed to work well for Kim, and I'm all about emulating examples of success.
Below the fold, I'll start the tutorial by examining what SERC calls the "course context and constraints." In later posts, I'll try to set goals, choose content to achieve those goals, develop a course plan, etc. At least that's what the tutorial tells me I'll do. I'll be blogging this is in near-real time as I plan the course, and your comments and ideas definitely have a chance to influence what the students experience in the fall.
Task 1.1a: What are the nuts and bolts of your course?
Does your course serve as a prerequisite for a subsequent course or does it prepare students for a standardized exam? If so, what? It does not serve as a prerequisite to any course, nor prepare them for any standardized exam. It helps fulfill a core requirement for PhD students in one program.
Challenges: Other than the catalog copy, there are no specific guidelines for the scope and content of the course. I've heard from the incoming students very different ideas about the course will cover, and these ideas seem to be originating from different colleagues.
Opportunities: With few restrictions, I could actually work to build the class that I think will be most useful to the students.
Does your course have prerequisites? If so, what are they?
The course is a graduate-only course serving students from 3 different graduate programs.
Challenges: The background of the students will be varied - some physical scientists, some engineers, and potentially some social scientists. I'll have to assume a limited common knowledge base, and cultural norms of each field might be substantially different from each other.
Opportunities: Graduate students are generally fairly independent, self-motivated, and interested in their topic of study. Having a diverse group of students may encourage wonderful cross-disciplinary thinking and interaction.
How big is your course, and what kinds of rooms are available for you to teach in?
I currently have 13 students enrolled. The 20-person room has immobile square tables that fit four students around them. (Picture lab benches with seating.) There's an overhead projector, blackboards, and a podium with a computer hooked up to a LCD projector.
Challenges: 13 is a prime number, so if we do group work, there will always be an extra person. (Maybe I can convince someone to drop?) I won't be able to rearrange desks/chairs for discussions in the round. When someone is up in the front, half the students are seated sideways trying to watch and take notes.
Opportunities: The class size is small enough for real class discussions to occur, yet large enough that if one or two people are absent or not participating, class won't be a flop. Group work is also easy to facilitate with the square tables. We can also mix lab and non-lab work easily over the course of a single class session without moving rooms.
Does your course have a lab and/or on-line component, and do you teach it?
The course meets for 3 hours, one day per week. I see no reason we can't use some of that time for lab/field work, if it meets the needs of the course. Similarly, I won't be hesitant to assign on-line work if it is appropriate. But no formal breakout of lab or on-line time exists.
What are your options for frequency and duration of class/lab meeting times?
The class meets for 3 hours, one day per week. I picked this schedule for maximum flexibility, and because it is pretty typical in one of the PhD programs that this course serves.
Challenges: Effectively using a 3 hour block, while not overwhelming the students or myself. Mixing learning modes - lecture, discussion, group work, etc - effectively. I know from past experience that I can plan too much for a single session and with only having the class meet once per week, I'd really like the sessions to be fairly contained modules. 20 minutes of overflow into the next week seems undesirable.
Opportunities: I *can* mix learning modes and activities within a single class session or give the students substantial in-class time to work on longer-term group projects. We can go into the field on or near campus and actually collect some data within a single session.
Task 1.1b: Who are your students, and what do they need?
Are your students majors (or potential majors), non-majors, or both?
The class is for graduate students at the MS and PhD level from three different programs that draw from three different undergraduate programs. Students will range from first semester MS students straight out of undergraduate degrees to 2nd or 3rd year PhD students.
Challenges: As mentioned above, having a class with such a diverse mix of student backgrounds may be a challenge, because disciplinary conventions will be different, as will the backgrounds of each student. They will also have variable levels of research experience, from essentially none, to having a thesis/dissertation project well underway.
Opportunities: By exposing students in these disciplines to each other early in their professional careers, perhaps they will do better cross-disciplinary work in the future. For the students with little research experience, maybe this class will teach them good habits before the bad habits have a chance to form. Students with more research experience may be able to share tales of "I tried this, and it didn't work."
Will the students in your course go on to be professionals in your discipline or (in the case of a course for majors) your subdiscipline?
Some of the students in the course will go on to be professionals in my discipline. The others will go on to be professionals in related disciplines. Some may go on to be academics or researchers, but others will go on to be practitioners (consulting, industry, government). In any case, as graduate students they are expected to conduct original research and could benefit from this class directly in the course of their graduate study.
Challenges: I want to make sure to teach them good, professional methods of experimental design and data analysis that are applicable in both the academic setting and the professional setting. Therefore, what I teach can't entirely be for those who will always have access to Elsevier subscriptions and the latest research results, but should be applicable to people out in the field who may have little information on hand before having to make a decision how to proceed. But that may be asking a bit too much for a course that spans so many disciplines.
Opportunities: As graduate students, they have a better vision of their professional futures than undergraduate students typically do. They also are at some stage of doing their own research project. Therefore, they may be easily motivated to learn good techniques in the course, because they should know if they don't learn them now they'll have teach themselves those techniques later.
In what way might your students use what they have learned in your course in the future?
As above, these students will all be conducting independent research as part of their graduate education. Experimental design and data analysis are necessary requirements of almost any research project. Too often, research gets designed in an ad hoc fashion, and then the data are limited in their ability to answer the interesting questions. I'm sure that some of the grad students may already be experiencing this problem with their own research. I'd like to lead a course that reduces this problem for future research projects.
What is the demography of students in your course in terms of age, race, gender, and ethnicity?
The students will be a mixture of American English speakers and international students with English as a second language. The fluency of the international students can be variable. The class will be ~85% male.
Opportunities: International collaboration and diverse workplaces are increasingly common. Working in groups will give them experience and help them figure out strategies for working with people different from themselves.
Are most students in residence at the school or do they commute?
All of the students will be commuter students. Some may be part-time graduate students with significant work responsibilities aside from their graduate classes and research. Some students may have significant family responsibilities on top of school (and maybe work). Other students will meet the traditional graduate student demographic of being single and having TA/RA positions to cover their basic bills.
Challenges: Having students work together outside of class time can be a challenge if they have work/family responsibilities. Having students do field work can be a challenge if transportation is required or if monitoring over a diel cycle is necessary.
Opportunities: At some point, almost everyone is trying to balance a professional career with other high-priority demands. Perhaps I can encourage them to find ways around these challenges, by using things like Google documents to collaborate.
What percentage of students in your course have high-speed computer access outside the campus library/computing center?
Hopefully all of my students have high-speed computer/Internet access through their home departments/advisors. If not, our department hosts a computer lab which will be available to the students.
Task 1.1c: What is the support structure for your course?
Are graders, TAs, or other assistants available?
No. Everything must be manageable by me alone on top of everything else I need to do.
Are you the default computer troubleshooter, or do students have other support staff to turn to if they run into difficulty with a computer problem related to your course?
It depends. I would hope they would turn to each other or their advisors/lab groups for help with technical topics that might be related to their own research projects, but I would be the default computer person for problems with course management software (if I use it) or problem sets involving a particular piece of software (if I do them).
Does your campus have writing, quantitative literacy, or oral communications skills centers that can provide supplemental help/instruction for students?
We have a writing center, and I suspect we have something to help non-natively-English speakers, but I don't what it is.
Are there professionals on your campus who can help faculty members with assessment?
We have a teaching center that offers workshops of varying utility. They may also be available for individual consultations, but if they are, it is not well advertised.
I'm going to try to get the next module done today and ready to post for tomorrow. I know it will be more interesting reading/writing than this one, because in it I am supposed to set the over arching goals for the course.
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Ooh, a topic dear to my heart. The most basic skill to teach is probably how to formulate a testable hypothesis. Then, teach people to graph their results before they start doing stats. Bad science makes for great initial case studies.
Wow, this is pretty awesome. I'm hoping to propose and teach a course very much like this soon, so I will be following this series closely. Thanks for doing this!
I don't have much to say, but this: I had many "round-table" seminar style grad classes in a room with the essentially immobile desks you speak of. That never deterred us from gathering around them in a semi-oval for class discussions. So don't let the structure of the desks guide whether or not you can move the chairs around. Do it anyway! It always worked out fine for us.
SW - this is incredibly timely because I am RIGHT NOW taking a workshop on statistical analysis of wildlife density estimates -- how you do the data analysis AND how you design your surveys for good analysis. They go hand in hand. When I taught a course like yours (but for undergrads and it focused on data analysis more than data collection), I made sure I had some good data sets for them to practice on -- it was important to have realistic but good data for the group to wet their teeth on.
Here's one thought that I've never succeeded in keeping in mind, but which has always seemed like a good idea: are there any ways in which you can have them collect preliminary data that you could use, later on, in the process of developing the skills to build their own projects?
Oooh, I look forward to following this! I really enjoy skills teaching - I currently teach a course called 'Problem Solving and Research Design' in one of our Master's programmes, and find it incredibly rewarding. I look forward to seeing what you choose to do!
As someone about to start as a graduate student in a PhD program I also find this interesting. I have been teaching middle school for 3 years and I am very familiar with course design for that age group. This will be an interesting thread to follow as I transition back into student-hood.