Repost: CRA Memo on Best Practices for Engaging Teaching Faculty in Research Computing Departments

Mark Guzdial noted today that the CRA has prepared its memo about teaching faculty in research departments.  For the past two years, I have been going to a CRA event at SIGCSE geared toward preparing this memo, so good to see its release.  I am thankful that at my institution, we have most of the things outlined in the memo and are treated roughly as equals to the tenure-track faculty.

Computer Scientists and Computers Usage

This post is built on a discussion I had with Dr. Thomas Benson and the recent blog post by Professor Janet Davis, I've got a POSSE.  Less directly, Professor Mark Guzdial has written several recent blog posts about parents wanting CS in high school, most recently this (where the point is raised that not everyone knows what this is).

What is it to be a computer scientist?  Is it just software development?  When I was first looking at colleges and I knew I wanted to program, I saw three majors that seemed appropriate: Computer Science, computer programming, and game development.  And from my uninformed perspective, Computer Science (CS) initially seemed the least applicable.  This was before Wikipedia, so how would one know what CS is?

Michael Hewner's PhD defense was a study of how undergrads perceive the field, as they learn and progress through the curriculum, do their views change?  I know my views changed; for example, functional programming was a complete unknown before matriculating.  By the completion of my undergraduate degree, I perceived that Computer Science has three pillars: systems, theory, and application.  I still view CS primarily from a programmer's lens and not a big tent view.

Indirectly, the Economist wrote about Programming Boot Camps where college grads go back to get a training in programming; however, "Critics also argue that no crash course can compare with a computer-science degree. They contend that three months’ study of algorithms and data structures is barely enough to get an entry-level job."  I both agree and disagree.  There is a further transformation of the economy coming whereby workers will .  One PL (programming language) researcher recently estimated that Excel is the most common programming language.  Can the worker using Excel do more or do it faster with VB or python or ...?

Are there nuances to the study of Computer Science in which students can focus further?  Clearly there are with the mere presence of electives.  Georgia Tech even groups similar electives into "threads".  Besides just electives, under a programmer-centric view of CS, software development involves more than just the strict programming aspect.  Even if CS is the "programming", a written program requires software engineering to maintain and manage its development and designers to prepare the UI (etc).

Thus CS might evolve more toward having a pre-CS major, and after the first two(?) years, students can then declare as Computer Science or Software Engineering or Human Computer Interaction or ....  So this is both less and more than Georgia Tech's threads, but an approach with similarities.  In common, this development of CS major(s) balances a concern of whether students have the fundamentals to succeed in areas related (i.e., programming, software development, and design) to their actual major, while allowing some greater depth and specialization.

This step is a maturing of the discipline.  No long just one major, but a school of majors.  CMU offers BS in CS, along with three other interdisciplinary majors.  Georgia Tech offers CS (with 8-choose-2 threads) and Computational Media.  Rose-Hulman offers both CS and Software Engineering.  (I am only citing the programs that I know about, not an exhaustive list).

Computer Science Diversity

I attended a top program in Computer Science, where the gender split was 60 / 40.  Then I worked for five years at a major company.  Therefore, my expectation is always that anyone regardless of their gender, race, etc can succeed in Computer Science.  Now, recently there was a short lived Barbie book about being a computer engineer.  Ignoring any semantics about Computer Science, Software Engineering, and Computer Engineering being different disciplines, the work still did not portray women in the more technical efforts.  I'd rather read a collegue's remix of the work.

In a different vein of diversity, as a white male, I have been regularly been excluded from tech events because I dislike the taste of alcohol.  Thus at the (especially) frequent events in industry settings where alcohol is served, I was not socializing with my colleagues, and instead would inevitably find myself back at my desk working.  As a consequence, I was effectively excluded from the event.  And now in academia, I find myself attending conferences, where the social events are also touted for serving alcohol.  I have no issue with serving alcohol, rather it is the near exclusivity of which the drink options trend that way.  Thus a recent article struck a chord in the continuing desirability of extending the options and respecting the decision (for whatever reason) to not drink alcohol.

Liberal Arts College Positions Mini-Seminar

In continuing my search and preparation for a faculty position, today I attended a mini-seminar by LADO faculty.  (LADO - liberal arts colleges with diversity officers)  Here are some points that were raised during the breakout and panel discussions:

Teaching:
- You will teach both upper-level courses, as well as "service" courses.  Service is a good term to describe the low-level / introductory courses, as the faculty are rotating through this service to the department.
- Try to setup the teaching schedule so that 1 day is free solely from research.
- Continue to revise courses so they are fresh and current, but also avoid constantly creating all new courses.
- Valuable to set aside "non-office hours" times, during which the door can be shut.
- Faculty will sit in on courses and additionally interview the students, as part of composing an evaluation of your teaching.

Research:
- Recruiting undergraduates earlier for research to have time to train them, so that they will later be able to contribute.
- You can still collaborate and have broad impact through research with faculty at other more research-focused institutions.
- Grant proposals can also be keyed "RUI" (research at undergraduate institutions)
- Regular funding for sabbatical leaves, first often after the renewal of the 3-year contract.  This leave is focused on research and may be held at R1 or other institutions.
- Startup package is present to cover the transition to grant-based funding.
- Research lab costs are significantly lower at these institutions, as funds are not required for grad students, post docs, etc.
- Schools are looking for faculty hires that add diversity to the research available.

Service:
- Service is a component, but is much smaller than teaching and scholarship.  So be cautious about accepting invitations to committees, in terms of time commitment.  The service time can provide valuable insight to the functioning of the institution, as well as possible collaboration with collegues in other departments.
- You will be chair of your department someday.

Other:
- Many liberal arts institutions are located in small towns.
- Take the time to customize the cover letter.  Do you really want and care about this job?

Preparing for Academic Jobs

I went to a recent seminar about the preparation and practice of finding an academic job.  The following summarizes the answers given by the panelists, each of whom was giving his or her opinion.  The short version is that your letters of recommendation are key.  They are the summary of your skills and qualifications by your (future) peers.  The panelists are all research-oriented faculty, which may skew some of the opinions provided.  One quality resource on teaching jobs can be found here.

Most important things in a candidate:
- Publications (some in the right places)
- Letters (don't really lie)
- Fulfilling the needs of the department
- Put "top" school in middle of interview schedule, chance to work out mistakes but not be burned out
- Energized / excited about place
- In 1:1 with faculty, only discuss own research for half of time (~15min)
- Be formal (jacket, etc)
- Prep work with faculty letter writers (explain research, plans, etc)
- Ability to connect across areas (your own area will get you the interview, the other areas will get you the offer)
- Talent, passion, impact in research
- Have a set of questions for 1:1 time of "do you have any questions?"

Things to avoid:
- Wrong / bad job talk (did you target the right audience, and yet convey knowledge in subfield)
- Attitude (arrogance that job is yours, or desperation about finding a job)
- Two interviews in one week

Letters of Recommendations:
- Especially letters from externals
- Prepare a statement of contributions (what have you really done / achieved?)

Things to focus on:
- Take risks in your research
- Network and get your name out / aware of

Postdoc versus Second Tier:
- Find collaboration and mentoring in a postdoctoral position
- It depends

Non-Research:
- Still except some quality research
- Your research talk is a demonstration of teaching

Deciding on schools to apply:
- Location
- Areas of Focus

Packages:
- Find packages from previous applicants

Computer Science Education: Student Conceptions

I'm sitting in Michael Hewner's thesis defense on "Student Conceptions About the Field of Computer Science". And I think there are some interesting points raised that are worth reflecting on. Let's start with summary questions.

Who would be considered a Computer Scientist?

How does a student choose his or her particular focus in Computer Science?

Do misconceptions about Computer Science affect the student's education?

Students have three conceptions about what Computer Science is, which were first derived from interviews and reaffirmed through a 100 student survey. The Theory-view (8%) is that Computer Science is mostly concerned with a theoretical view of computers, where the mathematical basis and understanding is dominant (although there may then exist a related field of Software Engineering). The Programming-view (41%) is that all Computer Science is about programs, where one is either analyzing the basis of or the direct work on programming. The Broad-view (27%) is that Computer Science is a giant umbrella of disciplines where computers are involved. A final 23% of the survey responses were without clear category, which may be due to the limitation of the original interviews. All conceptions view algorithms and data structures as a vital component to Computer Science.

Students use enjoyment of classes as the dominant metric of whether they have an affinity for the area. Ironically, one of the two dominant courses in my undergraduate education (15-213) was offered at 9am, which would commonly be viewed as an unpleasant time. Since students use enjoyment as their metric, students are not particularly affected by their misconceptions about what the course(s) contains.

Clearly then, the enjoyability of a course can then affect the taking of subsequent courses. Which in future work, there may be an exploration of whether course enjoyment effects (like scheduled time) has an effect on enrollment in follow-on courses in subsequent semesters. Furthermore, many students trust the curriculum as providing an adequate preparation for practicing Computer Science, which is to say that they are prepared as long as they satisfy the requirements regardless of any attempt to have a focus in their course selection. Should the curriculum then have unpleasant courses to force students into specializing?

For myself, I am a holder of the Programming-view (perhaps based on being a paid programmer), as I view Computer Science to be centered on programs and the act of programming. The field is directed toward understanding programs and how to program well. Computer Science is informed in part through Mathematics by providing a basis for understanding of algorithms and data structures, of which programs are fundamentally composed. Many fields, like Bio-Informatics, are related and rely on Computer Science, but are not Computer Science.

Repost Are you a Programmer

Consider the question, what percentage of programs are released to the public (either commercial or open source)? Even excluding student assignments, this percentage may be far lower than one might think. My expectations are biased by having many friends at Apple, Facebook, Google, and Microsoft. But thinking further, I spent 10-20% of my time as a salaried employee doing just that, writing little programs. These coding projects were intended to help me do my job faster, which was contributing to a commercial software product.

This is my introduction to a piece of career advice regarding being a Computer Scientist (*cough* programmer), Don't Call Yourself a Programmer.