Professor for one year (week 48): Who does profit from MOOCs?

Actually, this blog post was scheduled for the first week of March. However, the topic is still relevant even a few weeks later. Just pretend it's early March 2014 (i.e., cold and rainy) while reading.

During our visit of US higher ed institutions last year, we met James P. Honan from Harvard's Grad School of Education. We discussed various things and also touched e-learning and MOOCs. Honan told us about his experiences as a teacher and consumer of e-learning courses and contents and then some musing started about the underlying principles of MOOCs. I will briefly follow up here.

From a didactically point of view, massive open online courses (MOOCs) are old wine in new skins. I wrote about this part in an earlier post. E-Learning courses hosted on servers of universities started around 2000, and courses supported by current technology are as old as TV. The only new aspect is the "massiveness". At a university, e-learning courses are offered to the students of a particular subject at a certain point of their studies enrolled at that specific university. So there might be several hundreds of students using the materials of a course.

Going "massive" and "open", those courses skip restrictions -- everybody can take part -- but no change in didactics might be involved. Allowing more than only a few hundred users to access the material may involve changes in server architecture, maybe clustering, but not necessarily in the general technology used for user interaction and the like.

However, someone has to run those servers and someone should be paid for maintenance. The first MOOCs were developed from scratch, not just scaled e-learning courses (there will be another post on this aspect, stay tuned) -- maybe the content providers would need some payment, too. But declaring those courses as "open" doesn't only mean everybody may join, but also means nobody should pay anything for taking part. So where should the money come from to pay development and maintenance?

Honan gave a hint when he told about the fear of teaching staff at universities: Attending a course may have two main reasons. People just are curious about a certain topic (a), or people have to acquire certain knowledge (due to job demands or the like) and that involves getting a certificate (b). For a certificate, attendees would have to do some sort of exam. And this exam would have to be assessed and graded by someone. And guess who is qualified for assessing and grading student work? Right, teaching staff.

So while in the early years of e-learning instructors feared to be replaced by machines, the advent of MOOCs makes instructors fear to be used for grading only. And in the end, to be replaced by cheap grading staff -- why should you need highly qualified academics when you can have people trained to grade certain exams only. MOOCs would not result in replacing humans, but in downgrading educators.

At the one hand, this nightmare might not become true to the extend instructors might expect -- similar to the fear of teachers being replaced be educational TV shows or e-learning courses --, but on the other hand, that's probably part of the business model of companies like Coursera, edX, or Udacity. Participation in MOOCs might be free, but to get a certificate you would have to pay -- part of this money might get down to the graders, but most of it will go to the company owners. Those certificates don't have to cost a fortune. Look at prices for apps -- as long as the audience is big enough, small fees are fine.

Of course, with "certificate" a mean any piece of paper stating that you passed the exam of this course. As soon as participants actively demand official certificates of the hosting institutions, e.g., from Stanford or the MIT, another question arises: How much is such a certificate worth? As an on-campus student, you would have to pay a lot of money -- if you would ever get accepted in the first place. However, nobody would pay several thousand dollars for an on-line course offered or developed by Stanford or MIT staff.

So maybe several hundred dollars? But wouldn't that be a hard competition for those Ivy League Universities? If I could get a prestigious certificate without moving to Stanford and without enormous debts, why should I even send an application to Stanford? But here we're already touching another topic.

Professor for one year (week 47): Teaching investment and payoff

This is the 47th post in the series "Professor for one Year."  Initially, I had planned to post something every week.  However, my year is over and I still have some weeks left in the series.  The topics for the missing posts are already planned, so the only thing I need is some time to write ...

Apropos of time:  How much time do you spend on teaching, including preparation, interacting with students, assessment, grading?  As I wrote two weeks ago and also in week 24, teaching did take up a lot of my time.  I argued that the time allocated to teaching -- including preparation and grading -- should be the same as the time students have to invest to take a particular class -- i.e., the ECTS credits should describe the amount of work students and instructors have to invest.  However, for a regular seminar with 9 ECTS credits, this would mean 18 hours per semester week.  So, no more than three courses (54 hours per week) and then you would have to do some of the other work in the non-lecture time aka semester break to stay at least somewhat healthy and within the regulatory framework of labor law (41 hours per week).

Let's have a look at the workload of professors; 39 to 41 hours per week include:

• administrative work (keeping track of all the different contracts for your PhD students and PostDocs, help with finding new researchers, mentoring your PhD students, hold staff meetings, etc.)
• committee activities at your local university (attend faculty meetings, serve on appointment committees, attend senate meetings, etc.)
• committee activities in your scientific community (attend meetings of societies, have some duties there, review for conferences and workshops, review for funding agencies, etc.)
• write grant proposals (you don't get much state or university money for staff)
• teaching
• doing research
• publish about research

There are studies on professoral activities, showing that professors work more than the 40 hours they get paid for, and that they spend only little time on activities one would usually associate with "being a professor" -- teaching and doing research.

Having a social live, too, and assuming that maybe you don't want to work every weekend, but roughly 50 hours per week -- of course, you think about some issues during your non-working time and you have ideas outside you office --, the question remains: which of the activities are really important and where could you spend less time?  You cannot cut on administrative work, but you could try to delegate some tasks.  Most of the committee activities at your university are related to the status of a professor, so no chance of delegating something there.  You can delegate tasks for your scientific community like reviewing conference or workshop papers -- however, as an author, you'd rather want to get feedback from senior researchers, not from PhD students, so this is a bit tricky.  You could hire someone for writing grant proposals and you could even let your PhD students and PostDocs write most of the articles on which you appear as co-author.  Even the research you could delegate to members of your group, at least part of it.  So you are the one who has ideas and then somebody else is experimenting if they are worth to be investigated much deeper -- for computational linguistics, this means that you find someone who does the programming along the lines of your roughly sketched new approach.  So most of the activities could be delegated to other people, and maybe the quality even improves because you profit from including more people and thus more ideas and more skills than one could have oneself.

And for teaching?  Oh, that's easy: You take the slides and exercises you developed years ago (or you even borrowed from somebody) and use them term after term without changes.  You find teaching assistants doing all the tutoring and exercises with students.  You cut short on mentoring: students have to come up with topics for theses themselves, and somehow they should know by then how to write a thesis, don't they?  This way, you can drastically reduce the time spent on teaching.  And to be honest, that's the most obvious way:  I didn't have duties in committees at the university during my year as professor, but even then, I could hardly keep up with my scientific community activities, and I did have absolutely no time to write grant proposals, do research, or even publish.  In other words: I had to invest almost all of my time in teaching and I definitely couldn't afford this for a real professorship.  On the positive side, I now have quite a teaching record, from which I can benefit in the future.  But honestly, I also enjoyed mentoring and advising students even though this takes up a lot of time.  And in the end it's the only way to have someone try an idea and report some results I might be able to use for proposals or further research (eventually resulting in publications, too).

However, having a teaching load as high as 9 SWS must result in reduced teaching effort, and thus in  lower-quality teaching as professors cannot afford investing most of their working hours in teaching. So one solution would be to value teaching more, or to reduce teaching load -- students then could expect good-quality teaching and mentoring.

Professor for one year (week 46): Writing research across borders

After teaching is over, I packed my suitcase and took the TGV to Paris.  I attended the Third Writing Research Across Borders (WRAB) conference which took place at the University of Paris-Ouest Nanterre la Defénse.

WRAB takes place every third year, 2011 it was at the Georg Mason University in Washington, D.C., and 2008 at was hosted by the University of California Santa Barbara.  It is the biggest and most international conference on writing research I'm aware of.  The conferences organized by EARLI's SIG Writing (which take place every other year) are also international (i.e., not only European), but much smaller.

The number of participants, number of submitted and accepted proposals, and the number of concurrent sessions is constantly growing.  They actually had 26 parallel sessions!  It was almost impossible to find out which of the talks/presentations would be the most suitable one depending on your own interests.  There was a bit of Twitter traffic going on, so I could see that related topics would be discussed at various sessions all taking place at the same time.  The program was so dense and there were so many people, I draw the comparison to LREC (the International Conference on Language Resources and Evaluation), taking place every other year.  LREC is growing still and you can be sure to meet almost everybody from the NLP community there.  If LREC is the conference to be for NLP, then WRAB is the conference to be for writing research.

And WRAB shares another not so nice feature with LREC: Although you know that everybody is there (or you even searched the program for the name of some colleagues), you cannot meet someone during a coffee break or over lunch unless you actively make an appointment.  I like small- or mid-sized conferences better.

As I had no time to submit papers to NLP conferences during this year, those writing research conferences (and also conferences/workshops on linguistics) will be the only conferences I actively attend in 2014 -- you only have to submit a very short abstract, not a full paper.  At WRAB, I presented ongoing work on a systematic analysis of complex writing errors.  I argued to go a step further than current error analysis in writing research, NLP, or (second) language acquisition -- we have to consider the process that caused an error when classifying writing errors.  This way, we could on the one hand distinguish competence errors and performance errors and we could on the other hand come up with actual proposals on how to automatically prevent or correct certain types of errors.  Fortunately, I found a possibility to actually publish this -- I will give the details once the publication is a available.

I could meet colleagues from Europe and The Americas, we exchanged ideas and made loose appointments for SIG Writing's Conference on Writing Research in August.  So yes, the conference was successful.  As I already new that I would start at IMS in Stuttgart in April, I could tell people about my new affiliation and I made some loose collaboration and cooperation agreements.  I hope I can actually work on that in Stuttgart.

Professor for one year (week 45): Last week of teaching

Finally it's mid February and the last week of teaching is over.  This semester (Winter term 2013/2014), I taught four courses: on Computational Morphology aka XFST, on Computational Semantics aka Prolog, on Natural Language Processing, and on logging writing processes and exploring those data.

Except for the NLP course, I had to prepare everything from scratch.  There was material I could use and it definitely helped to "borrow" ideas and exercises for the two programming courses, but I spent all time with preparing slides (for all courses) and data (especially for the writing processes course) or assessing student solutions.

I also realized that I have to work on my elocution: When I teach two classes back-to-back, my voice is almost gone at the end of the day although I regularly sip some water.  Of course, one solution would be not to talk that much myself, but to let students contribute more.  However, staying focused for 90 minutes and trying to be louder than the 30 computers plus keyboarding noise and to keep students awake is stress to my voice.

As for the exams, I did different things:

• For the Prolog course, I had an exam similar to the Perl course last semester.  The grade is made up by points earned during the semester by submitting solutions for three exercises and then there is a final exam consisting of a more theoretical part to be answered on paper and a more practical part where students actually program.  I could assess the theoretical part while students worked on the programming tasks, nice multitasking.
• For the XFST course, students earned some points by solving three assignments during the semester, too.  And then they will submit small projects including documentation within 4 weeks.
• For the NLP course, students earned some points during the semester by submitting solutions for three assignments and then I had a classic written exam at the very last session.  Students had to answer one question per topic.  Looks like the handwriting of most students is more or less readable.
• For the writing process course, students had to work on a project during the second half of the semester.  They defined a small research question to investigate in groups of two, recorded a writing session for each person, and then explored the logged data and wrote a small report.  I will report on this experimental didactic setting at the next Conference on Writing Research in August. 

I could time the assessments for the three NLP-related courses so I had to come up with an assignment every week and I had to grade an assignment every week.  I preferred a constant but moderate workload instead of giving assignments to all three courses in the same week.  In every course, students had to read research papers (classics and recent ones) in groups and present the content to their colleagues.  Students also had to relate the paper they presented to the material presented or discussed before and they had to comment on whether or not they agree with the authors based on their prior knowledge and being almost full-fledged and approved linguists themselves (they where all master students except for the XFST course).

So teaching is over, I wait for the project submissions of two courses and I have to assess the written exam for NLP and the Prolog programs.  I hope to submit all grades by the end of March to actually finish all teaching stuff when my appointment in Konstanz ends.

Professor for one year (week 44): Publication speed

When you read a paper about "current research" or "recent findings" of a project, are you sure this project is still ongoing or finished only recently (considering the publication date and the date of reading)?  Are you really reading about current research, about something that the authors are currently working on?

If the paper appears as part of proceedings of a computer science or computational linguistics conference, it is fair to draw this conclusion. A paper published in fall 2005 most probably describes research from late 2004 or early 2005. The proceedings appear at the date of the conference at the very latest. Of course authors have to submit their final papers a few weeks in advance -- publishing with Springer, as we do for the Workshop on Systems and Frameworks for Computational Morphology (SFCM), requires editors to submit everything to eight weeks before the conference date, so authors have to submit their final paper roughly three months before the conference (and thus before the presentation of their work). That's pretty fast for an actually printed publication. It could be even faster for electronic publication only, reducing the time span to maybe one month.

However, if you look into other disciplines, publication speed is much slower. The last project at the University of Basel was somewhat interdisciplinary, involving linguistics and computational linguistics. So we went to conferences/workshops in both fields and we also published in both fields. As there are rarely proceedings for linguistic conferences that actually appear at the date of the conference, we usually submitted a paper to a call after the conference. Mostly, those papers appeared in edited volumes as part of a book series.

Due to different publication speed, the very first article we wrote (corresponding to the very first talk we gave during the project -- there had been talks on the topic before the project started) appeared after the project was finished. So everything we said about how to tackle various challenges and what we would like to achieve was published only when we already had those results. Which in general isn't that big of an issue if we would have published all other papers in a similar way: articles on single aspects of the project or on the outcome would appear later.

However, some of the more technical or NLP-related aspects we published at NLP-related conferences.  So we now have the strange situation, that the somewhat "starting" paper presented at a conference in April 2011 is published much later (mid 2013) than papers on the infrastructure we developed and used (fall 2012). Someone trying to follow the project thus has a hard timer figuring out what to conclude from which publication.

Late publications are often due to slow processes during submission (extension of deadlines on request of other authors), during review, during revision and resubmission, during editing, and then during actual printing or putting it online.  Together with Robert Dale I wrote a handbook chapter which finally appeared now, in February 2014.  The whole book project started in early 2011 (probably even earlier as there probably had been negotiations with the publisher first).  We submitted our chapter on time, received two reviews and submitted a revised version (i.e., the final version!) in October 2012.  And now, one and a half years later, we finally got the printed book.  In the meantime I changed universities twice (from Basel to Konstanz to Stuttgart).  So I had to report a change in affiliation, author bio, e-mail and postal address twice.  If I wouldn't have reported those changes, the editors wouldn't have been able to reach me to ask me look at the galley proofs. (In the end, the publisher send the book to a totally strange address I never reported, anyway ...)

For most of the delays in various processes, explanations can be found.  Sometimes someone gets sick, but most of the time it is due to poor production processes.  Submitting articles in MS word format with graphics and tables as separate files forces the editor/copy editor to spend a lot of time actually producing appropriately running text including figures and tables.  Marking keywords manually on paper slows down indexing extremely.  And so it goes on and on.

Given the electronic tools we have today in document processing and document engineering, there is no real reason for slow publication speed.  Apart from the discussion on open access and how authors can make an impact by preferring open access publishers, authors can influence the speed of publication by choosing publishers or publishing methods with reasonable processing speed.

Professor for one year (week 43): Will there be research after your PhD?

This week, the new Rektor of the University of Zurich started his job.  There were several articles and interviews in various newspapers, where he announced what he wants to do next and what his long-term goals are.  In one article in the NZZ am Sonntag, one sentence struck me: "Wirklich geforscht habe er zuletzt als Doktorand" (The last time he did serious research was as a doctoral student).  And he apparently regrets that.

This statement made me wonder: What's your task as postdoc or as professor? When it's not research,  is it about writing grant and project proposals for other people only?  Is it mainly about teaching (looking at the workload, you could think so, I will comment on that in a later post)?  Or are your days filled with more administrative stuff, the higher your professional rank is?

There are several indicators that in fact, postdocs and professors acquire the money to then hire some doctoral student(s) to carry out the research the applicants have a genuine interest in.  For example, with the Swiss National Science Foundation, postdocs cannot submit proposals where they actually would carry out the research themselves (except for the Ambizione program, but that has specific requirements and is part of the career track, not of the project track).  You can submit a proposal and then hire someone -- but the proposal will be evaluated against the applicant's research profile.  The  DFG (German Research Foundation) recently introduced an instrument where you can apply for a grant for your own position as postdoc.  So this looks a bit better.

On the other hand: As a doctoral student, you are not eligible to submit proposals, so you have to find a postdoc or a professor who submits a project proposal you can then carry out.

Given that proposal writing is a serious but tedious task, there is of course less time to actually do some research.  Some universities in Germany have decided that some professors (rank W1 and sometimes even rank W2) cannot negotiate about academic personnel -- there simply will be no academic personnel, you have to write proposals to hopefully acquire third-party money to hire a teaching assistant or a doctoral student.  Isn't that weird?  Public universities are funded by tax payers, so shouldn't that cover all costs to run a university including all personnel needed?  Third-party funding today makes up almost a quarter of the budget of German universities.  On the one hand, it's a good sign: researchers find people who think the proposed research is worth funding it.  But it's also a bad sign: The state is only able (or willing) to fund three quarters of universities' budgets.  But that's more of a political discussion, I think.

However, there seems to be the general perception, that after your doctoral studies, there will be no time for serious research.  I recently heard the conversation of two PhD students: A just submitted his thesis and told B that he would have liked to investigate a slightly different topic, but his supervisor told him not to do so because of the risk of failure -- his research could have produced negative results.  They both agreed that this would have been more interesting and even more fun than to do something one could somehow even predict the results.  And then B concluded: "Only doctoral students do real science, so why don't they let us do risky things?  After your dissertation, you will not be able to really investigate something anymore."  Isn't that weird?  It seems to be widely accepted that your scientific life won't include research after you defended your dissertation; at the same time, it is assumed that you can only do "real" research if you've obtained a PhD, i.e., submit research proposals ...

I really have some research interests in computational morphology, computational phraseology, and writing technology where I would appreciate the help of master students or doctoral students, but where I would also like to explore some things myself -- even if this includes tedious annotation or hacking.  That's fun and only this way you can really discover something new.  I definitely aim to facilitate research by coordinating and managing projects, but I would still like to be part of the actual investigation.

Professor for one year (week 42): Ich hab Vertrag

OK, the title of this week's post is a quote or a reference to German soccer speak.  Mostly it's used to express that one has an ongoing contract.  However, I can now officially announce that I signed a new contract this week for when my year as substituting professor ends.

I will join the Institute for Natural Language Processing (IMS) in Stuttgart on April first (this is hopefully not a bad sign!).  It's only a 18-months contract, but I hope there will be a possibility for an extension.  I will do some teaching, coordination work for the Stuttgart CLARIN-D center, and I will continue research on phrasemes, morphological components, and writing technology.  At least, that's the plan.

What is most important: My academic adventures will go on after March 30, that's really good news. But there is a catch: We have to move.  But this is a different adventure.

Professor for one year (week 41): What's in your syllabus?

It's evaluation time again and one of my students wrote in the free form field "What else would you like to comment on":  "I don't know the learning objectives.  I searched the slides and didn't find anything."

I was offended: Why didn't she (it's a girls-only class) ask?  Of course it is in the short description of the class in the Learning Management System (we use ILIAS).  Of course it is in the short description of the class which instructors have to provide to be listed in the study management system where you find schedules, instructor information, etc.  Of course it is on the slides for the very first session -- I always have a proper slide titled "Learning objectives."

But somehow, she had missed the information.  So maybe one slide, five bullet points, or two paragraphs are not enough.

In the study management system, it looks like this:

You find all relevant information, it looks a bit structured, but no explicit learning objectives are given.  They are somehow hidden in the description field.  Instructors are asked to provide certain information (language of the course, material used, kind of exams), but they are not explicitly asked to provide learning objectives.  Maybe there should be even an extra field.

When I realized that other information is missing, too, I looked around how other instructors write a syllabus.  As a case in point I looked for writing related courses and found these:

• EngLit 2570: Materialities of Writing by Annette Vee (Spring 2014)
• English 353: Technical Editing by Cheryl E. Ball (Spring 2012)
• E501: Theories of Composition by Carrie A. Lamanna (fall 2013)

All of them have extensive descriptions on what the course is about, what students will do, what's the motivation behind this course, comments on literature or other material used, etc.  Carrie Lamanna and Cheryl Ball have long explanations about the assignments: What do students have to do, how will the assignments be graded, and how do single assignments contribute to the final grade.  I do communicate these information, too, but I rather announce it in class and don't write it down to be read before the course starts.

Additionally, you can read the instructions for each assignment.   I only have this when I hand out the assignment.  As I found the syllabi after the courses had taken place, I cannot say if the assignments had been published before the courses started or if they had been added once at a time.

Of course it's great to find these sources and be able to use them as inspiration for your own course, but on the other hand, it means you cannot re-use those material for the next course (when I teach a similar course at another university, I often re-use assignments as there is only very little chance that students from university A have friends at university B who took my course).  And the instructors probably didn't use an LMS -- I don't think you put everything in your LMS and have an elaborate website.

If all material had been set up before the course start, this means a lot of preparation effort.  There are lists on which papers to read for which session, sometimes with comments even.  Although I have a schedule concerning which topic to cover in which session, I often search for papers one or two weeks before a particular session.  Maybe I should think about this and really invest a reasonable amount of time in proper preparation for the next classes.  Of course it helps if you teach a course for the second, third, etc. time -- you only have to look for new papers for a certain topic, but you already have all canonical material and you know how to proceed and what works in class.

What I really would like to adopt is the kind of course policy Cheryl Ball has in her syllabus.  It's an explicit list of what students can expect from this class and the instructor, and a very clear statement of what the instructor expects from the students to make this course a success for both parties.

I especially like her comments on grades: "Everyone in this class starts with a B/C.  How you participate changes that grade higher or lower."  And then follow a lot of actions influencing the grade positively or negatively.  For programming courses, when you actually can check student answers against a sample solution, grading might be a bit easier and more formally.  But in courses where there is no single right answer for an assignment, grading is much harder and usually students try to argue about grades.  So a policy on what influences the grade in a positive or negative way is really helpful -- and there should be no room for discussion left.  Everybody knows the consequences of their actions in class.

So I hope to have enough time before the next teaching appointment to spend more time for preparation and start actual teaching a bit more relaxed.

Professor for one year (week 40): How to drop out

With the Bologna process, teaching got a bit more structured than it was before: Students have to sign up for classes, they have to prove they learned something for each course, etc.  Even before Bologna, there were occasions when students had to sign up: There were always obligatory seminars with too few places, so you had to put your name on a list (on paper, of course) or be there one hour or more before it started to make sure you could attend this seminar.

Today, we've gotten rid of paper lists and we now have electronic tools where students can "book" classes -- everything has become very service-oriented.  However, there are different approaches on how and when to book a class.  In Basel and Zurich, booking starts some weeks before the beginning of the semester and ends two or three weeks after the first lesson.  It is thus possible for students to step back without any harm after attending a course for some weeks; but within four weeks into teaching, lecturers know who is a regular attendee and who will take part in the exam.  So from week 4 on, you can plan actual group work.

In Konstanz, students can attend classes without prior booking -- they have to sign up for the respective ILIAS course, though.  They have to sign up for the exam in the middle of the semester and can do so for two or three more weeks.  As an instructor, you only get to know who is interested in actually doing the exam when the semester is almost over!

Students have a lot of time deciding if they like your class or not.  Which is OK, but has a major drawback: I usually have some group work in my classes which are part of the exam.  So if one of the group members decides to not to be interested in this class anymore, the group is shrinking or even reduced to one student.  Which makes no sense and we then need to find other solutions for the left over group members.

What is even more annoying:  Students often drop out without sending a note to their colleagues or to me.  So for some weeks nobody knows whether someone is sick or has left the class.

Most universities also have introduced compulsory attendance, which is a bit strange when you consider that students are grown-ups with a certain interest in the subject.  However, you have to count heads every lesson and make sure everyone who should be there actually is there.  Students are allowed to skip up to two lessons (out of 14 or 15) without any negative consequences -- if they are seriously sick or have other duties (going to the WK [annual refresher course of the Swiss Army] or participating in an excursion) negotiations will start.  However, I always tell students to drop me a short note when they cannot attend a lesson -- it may have an impact on what we do in class.  Most of the students send me an e-mail or tell me in person if they cannot come the next week for whatever reason.  So this works quite well.

However, some students don't tell you when they cannot show up for the next lesson and they also don't tell if they decided to drop out.  In small institutes with only a few instructors and classes each semester, you always see those students again.  And it's a bit awkward attending one class but having skipped the other one.  At least I would feel a bit awkward, but when I ask students if they had been sick the other day in the other class, I sometimes hear: "Oh, I've decided to drop out, it's too much, I wanted to tell you, really!  And, it's not about you, really!"

Maybe I have to change my attitude and see myself as a service provider, not a mentor:  Attending a class or not is not about the subject or the instructor, it's just about balancing costs and benefits.  And when there's no "contract," there are no commitments, you just leave.

Professor for one year (week 38 and 39): Professional health pattern

The last teaching week in 2013, I was quite happy to still feel good.  I didn't catch a cold so far although a lot of people got sick around me.  But then came Christmas and a two weeks break.  And guess what?  After three days off (I slept longer, started to read one of the books from my ever growing to-read-shelf, had nice walkings in almost sunny weather, no class preparations, checking my e-mail accounts only once a day, ...), I first faced a sore throat and that was the end of my holidays. 

As usual, I had a really bad cold and couldn't enjoy my vacation as much as I hoped to.  But I could have probably guessed it:  There seems to be a professional health pattern with teachers/instructors.  Everybody thinks they have a lot of vacation and in general don't do much.  However, comes vacation, they get sick and don't do all the exciting stuff they planned to do.  We do everything to not get sick during a lecture period, we try all kinds of household remedy to fight first signs of sore throats, colds of even flu.  We actually give classes on crutches or with really bad back aches.  We even try to schedule surgeries and long-term treatments to take place during vacation and live on painkillers until then.

You can probably guess the profession of patients when looking at when they get sick -- people facing health problems during their vacation are most probably teaching somewhere.

However, we could enjoy a few Winter days at the Baltic Sea:

It looks a bit like a Caspar David Friedrich painting, doesn't it?

Professor for one year (week 37): Winter term break

Some weeks ago, I commented on term dates and my feelings towards winter term.  Actually, it's not 4 but 6 weeks of teaching after New Year.  This means, the Christmas/New Year break is roughly in the middle of winter term.

I felt uncomfortable with teaching after New Year, but this was mainly due to having still contact with colleagues teaching in Switzerland.  I don't feel exhausted the way I usually feel at the end of a semester, i.e., like this owl posted on Facebook some time ago:

In fact, having a break in the middle of the term offers some chances:

• I will start the second part of the term with a repetition/summary.  When there's no break, I usually don't do this because I'm hesitant to "lose" a session while there is so much students should get to know/practice.
• Students have a bit more time for "homeworks." And I hope this pays off with respect to quality.  Usually, they have two weeks for submitting assignments.  I don't include the days of the Christmas/New Year break.
• I have some time to unwind and I hope to be not as exhausted as usually at the end of the term.

However, it still feels odd that the week after Winter term in Konstanz ends, Spring term in Switzerland starts. So I'm very happy to have no teaching appointment in Switzerland for Spring.

Professor for one year (week 36): Being cheered

Last weekend, I had a non-academic adventure: I ran the Silvesterlauf in Zurich.  I was one of the Happy Runners, which means I did the four big rounds in 60 to 70 minutes, summing up to 10km.

I love long-distance running, I did the Berlin Marathon several times and I ran some of the races as part of the ZüriLaufCup over the past years.  I will never win my age group, in fact, I'm always in the last quarter or sometimes even at the very end of a race.  But guess what: That's perfect!

People cheer for the very first runners, but those are usually very fast; so as viewer, you can hardly identify them.  And they are so focused, they won't realize who is cheering and what people are shouting.  In the middle field, it's mostly extremely crowded and runners hear a lot of cheering and shouting -- it's hard to identify the viewers who are actually cheering for you.

When it comes to the last runners, the situation is easy to grasp.  Runners are slower and only a few at a time, viewers can easily read the names on the number bib -- the Swiss print the actual number consisting of digits and the first name, most of the time the name even in a bigger font (Germans don't print the name or only in a very small font, so nobody can read it).  And viewers like it when runners react to their cheering.  There is a lot of high-fiving at the end of the field.  And even the marshals are a bit relaxed and cheer for you.  I served as marshal for the marathon part of the Zurich IronMan a few times, so I know both perspectives.

Of course, people pronounce my name differently, depending on the cultural background, or it's even changed into "Christin".  As long as it's close enough to the original, I take it as cheering for me -- when I hear "Natalie" or "Beat", then I know there are still runners following me. 

So the last Silversterlauf was a one-hour cheer-up -- you hardly find this in academia.  Recieving notifications for accepted papers or grants isn't as exciting as being cheered by completely foreigners all the way.  Or when was the last time somebody rung a big cowbell (Treichel) just for you as you ran up the Rennweg? 

Professor for one year (week 35): Should everybody know how to program?

This post is the report, I wrote for the GPP 2013.

Introduction

Being a computational linguist, I was trained in programming as well as in linguistics.  After school in the mid-nineties, I couldn't decide whether to focus on linguistics (or nowadays "humanities") or computer science/math (or nowadays "STEM").  So I was quite happy to be able to focus on both when studying computational linguistics.  I always loved algorithms, abstraction -- and yes, I also loved Latin.  Maybe that's a rare combination, but in today's world it turns out to be quite handy.

One aspect of the 2013 GPP motto "University and Society -- Meeting Expectations?" is the aspect of university as the institution to prepare students to be successfull in today's society.  In the last decade, we saw the emergence of more and more electronic devices, "digital" is one of the buzzwords in several scientific fields, technology becomes pervasive.  We speak of the "Generation Y" as being "digital natives."  However, if we look how today's students use technology, they are only users, they are not creators.  They often even don't know how to configure programs.

Douglas Rushkoff in his book Program or be Programmed argues that everybody should know how to program to understand today's technology and to be able to control it instead of becoming a slave of the electronic devices surrounding us.  So my personal focus in the GPP 2013 was to explore how universities support or enable learning to program.  Of course students in computer science (CS) and related fields (like computational linguistics) are trained in programming, but I was interested in courses for non-CS students.

Answers from US professors

During our visit in the US, I asked my question at two places explicitely and I got two different answers. 

At North Eastern University, Dr. Neenah Estrella-Luna, an assistant academic specialist,  as she described herself, argued that indeed, computer literacy would be a valuable topic to teach considering that university should empower students to deal with current challenges.  However, she admitted that there are no courses offered to all students, not to mention being required.  My question was understood as asking about "teaching students how to program." 

At swissnex in Boston, we met Dr. James Honan, senior lecturer at the John F. Kennedy School of Government at Harvard.  He understood my question differently and answered that students would keep faculty busy and push them to use more technology.  He talked about MOOCs before and probably this influenced his answer.  However, his statement made clear that there is a view of "computer literacy" as "being able to use devices", including the expectation that instructors offer digital content and e-learning material.

At this moment, I was a bit disappointed.  Either the necessity of teaching and learning how to program is not recognized, or, when it is recognized, it is impossible to offer such courses for all students.

While at the MIT, we visited the Media Lab and the "Lifelong Kindergarten" headed by Professor Mitchel Resnick.  We got an introduction into scratch, the programming language and online community intended to teach kids how to program using a game concept.  They learn abstraction, algorithmics, and data structures while they play with code snippets, interact with other kids around the world, and program their own games and worlds.  It's an advanced model of learning the concept of recursion while playing "Towers of Hanoi."  I was aware of scratch before and I really enjoyed seeing some demos and talking to the researchers involved in designing and implementing scratch.  I think using games as a vehicle for teaching important concepts is a good strategy -- the users aren't probably not even aware that they acquire valuable knowledge they will use later in school, in university, and in their jobs.

Situation in Switzerland

On the morning of the day I took my flight to Boston, I took part in a meeting of an experts panel on CS competencies of the Hasler Foundation in Berne.  The foundation is working towards a proposal for a general subject "Computer Science" at Swiss schools.  Currently, some schools in some cantons offer CS as supplementary subject (in German: Ergänzungsfach).  However, this subject is often taught as it was in the 1990s: students learn how to use certain software, they don't learn to program, they don't learn about abstraction, algorithms, and data structures.  In the publication "informatik@gymnasium", published by the Hasler foundation through NZZ Libro (note that the German version of this book is already sold out!), the authors argue that CS and using software are two differnt things and that school should teach students the basics of CS to prepare future citizens to cope with everyday life.  It is probably a long way to achieve this goal, but it's a goal worth all the effort.

However, here we talk about serious teaching, not about fun instruction as in the case of scratch.

Answers from the Web

After coming home, I searched the web for comments about computer literacy and opinions or activities on teaching programming.  Bill Gates, in a questions session at Microsoft's Faculty Summit, confirmed that there is indeed a "gap between how computer scientists use computers to automate their lives and how most people don't really know how to use them effectively."

Larry Hardesty talks about the "programmable world" that surrounds us and that will change the world as we know it by making the distinctions between virtual and physical objects obsolete.  To make good use of the new world, we should be able to understand opportunities and challenges (and issues) and how to manage them.

In England, efforts are on their way to teach algortithms to primary school kids.  The government acknowledges the need to "catch up with the world's best education systems."  However, this new curriculum is still under development and the teacher's union isn't sure about when would be a good starting point to introduce it -- they object to only react to governmental decisions.  According to Sean Coughlan it will include computing defined as:

Computing will teach pupils how to write code. Pupils aged five to seven will be expected to "understand what algorithms are" and to "create and debug simple programs". By the age of 11, pupils will have to "design, use and evaluate computational abstractions that model the state and behaviour of real-world problems and physical systems".

It would be great if England could manage to design and actually implement this aspect.

And there are discussions going on in the emerging field of "Digital Humanities": In a twitter post, Jan Hecker-Stampehl (@heckerstampehl) asks "Should humanities scholars learn to program or trust that the programmers in DH projects will understand them?", obviously not aware of the more than 30-year old answer, Jacques Froger gave 1970 (Froger, J. (1970). La critique des textes et l'ordinateur. Vigiliae Christianae 24 (3), 210-217.), as Michael Piotrowski responds:

Il n'est pas indispensable que le philologue établisse lui-même le programme, encore que ce soit infiniment souhaitable ; il devrait au moins connaître assez le langage de programmation pour contrôler le travail du technicien ; en effet, l'expérience m'a appris qu'il ne faut pas s'en remettre les yeux fermés aux électroniciens, mal préparés par leur formation mathématique à se faire une idée juste de problèmes concrets qui se posent dans la domaine de la philologie.

(English: It is not absolutely necessary that the philologist writes the program himself, even though it would be extremely desirable; but he must at least know the programming language, so that he is able to check the work of the technician; in fact, experience has taught me that one should not blindly rely on the electronics people, whose mathematical training has hardly prepared them for fully understanding the concrete problems encountered in the domain of philology. (translation by Piotrowski))

However, even in fields where you would expect learning to program to be part of the curriculum, it is rather rare, as the blog post by Philip Guo shows.  He argues: "If you're a scientist or engineer, programming can enable you to work 10 to 100 times faster and to come up with more creative solutions than your colleagues who don't know how to program."  Students would need more concrete motivation than only arguing that programming helps them become an empowered citizen (the argument Estrella-Luna used at North Eastern).  Guo accepts that programming tools, i.e., text editors, should be improved to foster programming, but in the meantime we should focus on teaching students programming skills to support creative problem solving.

Selena Larson emphasizes the need to teach programming to students in schools already.  She supports the Hour of Code initiative during Computer Education Week 2013, following a similar strategy as scratch: Using games and fun figures, kids should understand basic principles and get an idea about what it means to program.

Conclusion

Studies by professional assocations like the ACM (Association of Computing Machinery) regularly show an increasing number of jobs requiring programming knowledge.  They also show that there is a lack of people with appropriate skills meeting these requirements.  So there is an urgent need in society. 

As I agree that school would be an appropriate place to start teaching basic concepts of CS, university should be the place to empower students to actually program.  Maybe learning to program, acquiring knowledge about algorithms and data structures should be a required course in every curriculum.  I strongly support the statement made by Steve Jobs in an interview in 1995 saying "It teaches you how to think.  I view computer science as a liberal art.  It should be something that everybody learns."

However, we are still on the way to implementing those ideas into education, be it in school or at university.  If we have the chance to support initiatives like the Hour of Code or panels and experts groups designing curricula, those of us having the respective knowledge, should take part and see this as opportunity to serve society.

Professor for one year (week 34): GPP2013 aka higher education bootcamp

This year, I could take part in the Global Perspectives Programme (sorry for the British spelling) -- GPP2013 --, a joint program by the University of Basel and Virginia Tech.  In Basel, we were 8 participants (mostly PhD students) from Chemistry, Law, Sports Medicine, and Computational Linguistics (that's me).  We met in March for a kick-off and started our social-media journey: setting up blogs, joining Facebook and LinkedIn groups, creating a Twitter account, becoming familiar with document sharing applications (Adam, a Moodle clone in Basel, and Scholar, a Sakai clone at Virginia Tech). 

We subscribed to three groups working on aspects of this years topic "University and Society -- Meeting expectations?"  Those groups were formed by participants from Basel and Virginia Tech.  However, we didn't invest much in this groupwork before meeting in person when the Virginia Tech participants visited Switzerland in early June.  They were based in Riva San Vitale (TI) and visited several universities in Switzerland, France (Strasbourg), and Italy (Milano).  We could join them for two days in Riva San Vitale, got to know each other, and started exploring the topic.  Similar to us, the US participants came from different scientific fields and were at different stages in their academic career -- there was no postdoc, though.

In the middle of June, we flew to Boston to start our visit of US institutions of Higher Education.  An two days in Boston, we visited Northeastern University, Boston College, swissnex (where we met James Hanson from Harvard), and the MIT.  On the evening of the second day, we were supposed to travel to Blacksburg.  However, due to bad weather conditions, our flight was delayed and we spent a few hours at a bar at the Boston airport before taking the last flight to Charlotte.  We slept a few hours in a motel and then took the first flight to Roanoke Regional Airport -- of course we couldn't access our luggage, so we had to come up with innovative solutions for cleaning contact lenses and brushing teeth.

Our colleagues from VT picked us up at the airport and gave us a ride to Blacksburg.  I guess nobody slept in the vans, we chatted a few hours and arrived at the campus quite exhausted and looking for a shower.  However, we started exploring the campus immediately, looking at student housing, meeting with faculty, and trying to make a good impression.  In the afternoon we visited the New River Community College and then we headed back to the VT campus to finally get a shower and dress up for the formal reception.

We started the next day with a working breakfast, discussing how to present group work outcomes at the Swiss embassy in Washington, D.C. at the end of the day.  Then we took the vans again to go to Washington, D.C, and to visit two other universities on the way: George Mason University and Virginia University.  More and more, the journey turned into an academic bootcamp: We had less and less time to meet with faculty at each station -- and thus needed to shorten our introductions and ask short and precise questions -- and finally we dressed for the formal reception at the Air and Space Smithsonian (we could take part in welcoming the crew of the Solar Impuse who had almost finished their journey across America a few days before) within 15 minutes on the George Mason parking lot.  And I think we all looked great and behaved well!

The next morning, our colleagues from VT drove us to the Swiss embassy in Washington, D.C., where we presented the outcomes of our group work and posed some answers and even more questions to the audience.  We had a lively discussion during this official session and then we had lunch at the embassy.  It was very nice to continue discussions we had to cut short during our trip -- people from George Mason University and from Virginia Tech attended the meeting.

After coffee, it was over.  We had to find our way back to the hotel on our own -- of course nobody was prepared which subway to take or even knew in what part of the city the embassy was located.  Later we met for a final dinner and a short debriefing and then we started our trips home (some of us with a stop over in New York, some stayed a bit longer in Washington, D.C.).

A few weeks ago, we had the final closure of GPP2013 at the Institute for European Global Studies in Basel.  We had met before during summer for attending doctoral defenses or birthday parties.  We have become friends, and this is probably due to those bonding experiences during the GPP bootcamp.  I really enjoyed this experience!  And yes, I would do it again.

Professor for one year (week 33): Coding is the new Latin

A few days ago, I tweeted this:

With a link to a short statement by Steve Jobs.  Two sentences in his statement triggered this tweet:

• "It teaches you how to think." (with "it" referring to learning how to program)
• "I view computer science as a liberal art."

And I added a follow up tweet stating that Latin and Algorithms and Data Structures should be required for all studies at a University.

Initially, both tweets are an reaction to the initiative Hour of Code, which is simply great.

However, the more I think about it -- and look at my Twitter timeline following Digital Humanities conferences over the last weeks --, the more I believe that coding actually IS the new Latin already;  it just hasn't hit universities while Latin is on it's way out of universities (fewer and fewer study programs require proper knowledge of Latin).

When you look for arguments supporting Latin for everybody, you find:

• It's fun.
• It's the basis of European languages, you learn other foreign languages much easier if you know Latin.
• It's the basis of European languages, you gain competencies in your native language.
• It teaches you how to think.
• You learn a lot about logic and abstraction.
• There's no better way to learn grammar.
• It's part of our (European) cultural heritage.
• It teaches you how the world works today.

If you look closely, a lot of those arguments are valid for programming, too:

• It's fun.
• It teaches you how the world works today.
• It teaches you how to think.
• You learn a lot about logic and abstraction.

And that's basically, what Steve Jobs was referring to.  And I agree, although there is a learning curve, you can do a lot with programming, even as a beginner.  It is a kind of craft, you have to practise a lot; but it's also a kind of art, you can enjoy it while doing it and you can enjoy the final product.

Usually, it's "critical thinking" what we want to trigger in students, but I think "being able to abstract" is a more appropriate goal.  And probably a prerequisite to critical thinking -- you have to discover large lines of arguments, you have to abstract from singular examples, you should see commonalities and general discrepancies before making your own arguments and expressing pros and cons.  Being trained in logical thinking and abstraction helps you to do so.  And there is no better way to learn those two than via learning Latin, math, or programming. 

Actually, there might be another link between Latin and programming -- it's a kind of closed community of those who know it.  Therefore a programming language could be seen as a kind of "code" -- i.e., a "cipher" --, and you have to be an insider to decipher it and grasp the true meaning.  It's a kind of jargon spoken and understand in a closed group.  Maybe people referring to "programming" as "coding" are not aware of the ambiguity of "code," but I think the sense of "speaking an encrypted language" is a valuable one.

There's already a lot of research literature with respect to "code literacy," also emphasizing that you should learn how to program to become part of "the club of the privy."  And of course discourse following the book Program or be Programmed by Douglas Rushkoff supports this view.  In this regard, the term "hacker" -- often used as a derogatory term by society, but as a badge of honor for expert programmers in hacker culture (see the definition of "hacker" in the Jargon File) -- could even become a synonym for "member of the new elite."

Professor for one year (week 32): Postdoc programs

In 2012 and 2013, I could take part in the PostDoc Program (PDP) of the University of Zurich.  Eighteen postdocs had been chosen in a competitive selection process.  We met for six workshops during these two years.  Coming from several disciplines, such as film studies, forensic medicine, politics, biology, linguistics, and computational linguistics, we couldn't share experiences and knowledge on a scientific level, but rather our experiences about being a postdoc in general.  Some of us had experiences in interdisciplinary research, some of us had experiences in highly structured environments like chemistry labs.  And all of us had good and bad experiences with supervisors and research assistants.

Being part of this program meant meeting people with very different backgrounds but a common goal: to become a professor in the near future.  The program is meant to help participants to estimate and increase their success in academic careers, to find ways to promote themselves, to understand and play by the rules of academia, and to get to a point where they can successfully apply for professorship.

We talked about different perspectives on teaching and research and about strategic decisions concerning the next career steps.  Each of the two-day workshops was a sometimes welcome, sometimes disruptive break in our daily routine.  Some of us had to answer calls and e-mail messages during breaks or return to the office immediately after the workshops.

However, without the workshops, I would not have sat down for a few hours to reflect on my career as it had went until today or to plan which steps to take and where to invest in order to gain new skills.  We could discuss strategies and tactics for moving towards professorship and try out interview situations and trial lectures. The six workshops on application training, funding, leadership, career paths, publication strategies, and competencies and skills where lead by experts in the field -- professors, coaches, members of the ERC review board, etc.  And all shared their knowledge and encouraged us to ask everything what we always wanted to know.

Of course you could find most of the information by searching the web, but without the course context, I wouldn't have invested the time to do so.  On the workshop days, we could spend the whole day on "daydreaming" a scientific career and got to know what happens behind the closed doors of search committees or funding boards.  And with every workshop going by, I got even more convinced that this is exactly the career I dream of: self-determined research and teaching, leading a research group, advancing the field and the scientific community, and being part of the academic discourse -- with the "field" referring, in my case, to Computational Linguistics and Writing Research.

The program finished in September 2013, but we managed to maintain regular meetings as a group.  I really hope we can continue do this for quite some time, even if some of us start  moving to other universities in other cities and countries.

If you ever have the chance to attend a workshop on career training or even a whole series, don't hesitate to apply.  It may seem a lot of time to invest (and you need all the time you can get to publish, don't you?), but it's totally worth it!

During the program I also found a mentor, supporting me in strengthening and polishing my application documents.  He isn't a member of "my" scientific community, and although it felt a bit odd at the beginning, I really enjoyed those meetings -- I was forced to think about wordings and he helped me to look at my achievements from an outside perspective.  I really appreciated this mentorship!  If you have the chance to engage in a mentorship relation, I totally recommend it.  My mentor even told me that he chose to act as mentor for junior scientists because he had made this experience as a mentee before and he liked it a lot.  That's a great attitude, and I hope that one day I myself can support mentees on their way towards an academic career.

Professor for one year (week 31): Supervising students

Currently, I supervise three students as "first supervisor;" last term, I was the "second supervisor" for three students.  Two students write their BA thesis and one student writes her MA thesis.  I won't report on their topics, but on the supervision as such.  As second supervisor, I only have to read and grade the thesis, as first supervisor, I'm responsible for a good topic and I'm the person students contact for help.

Actually, I don't differentiate whether I supervise BA or MA theses or term papers -- there are only gradual differences with respect to the amount of time to invest, the number of words or pages to produce, and the kind of topic.  At all levels, I expect students to come up with a proposal first; they should define themselves which topic they work on for the next few weeks (or months in case of MA theses).  We discuss the proposal and then they have to write a one-page abstract defining their research question, what kind of material to use or to produce, and they also should list first literature references.  I don't expect them to read 24/7, but they should investigate relevant literature for their topic.  Then we discuss this abstract and refine the research question.  I also point them to unmentioned papers or journals and book series they should consider consulting.  And then I send them off to work.

Usually, there is a fixed date for handing in the thesis or the seminar paper.  When half of the time is over, I invite the students for another meeting.  A few days before, they send me everything they have produced so far.  At this point in the process, it's time to have a look at the structure of the text, even if some sections are still to be written.  The list of references they want to cite should be nearly complete.  This appointment forces them to actually write something and not spend time procrastinating.  There is a strong correlation: Students with little and/or poor text half way through their paper, usually hand in poor final versions.  They underestimate the time needed for revising, editing, and printing (university regulations often require printed theses).

Sometimes, students see those two appointments (preparing a proposal and discussing it, and sending mid-way material and discussing it) as some kind of cruelty.  However, it helps them a lot in focusing on their topic, developing critical thinking, and producing high-quality texts.  After grading their work, students can also make an appointment to get detailed feedback.  

When I teach seminars where several students write a paper, I often make some of these appointments a group activity:  students report on their research question in the first session, we discuss how to define a good hypothesis and how and where to find relevant literature.  In the half-time session, students report on their progress and the group comments on whether to refine (expand or narrow) the research question or their ambitions.  That's also a perfect opportunity to realize that all the others also struggle a bit, didn't manage to write as much text as they expected, etc.

Interestingly, the Department of Linguistics at the University of Konstanz recently developed a checklist for BA students:  they should reflect on the competencies required to write a thesis (including writing competencies) and they should prepare a one-page abstract before looking for a supervisor.  The checklist is intended to help students define a topic and become aware of all the skills involved when writing a thesis, and the filled-out list should inform potential supervisors about the students.  As for me, I don't need this list, its elements are part of my supervision style anyway.  However, preparing such a checklist is a sign for aiming at a somewhat more homogeneous supervision for all students, but you could also see it as an indication that not all potential supervisors have a real interest in mentoring students.

What's your supervision style?

Professor for one year (week 30): Device naming systems

Last week, I wrote about my private geek devices.  And I mentioned the names they have:

• heinz (the black MacBook)
• horst (the router)
• herbert (the old Toshiba)
• gunther (the other router)
• fred (the new MacBook Air)
• marlene (the old MacBook Air)
• waltraud (the work computers used for E-Learning and OldPhras)
• berta (my Nokia 6700 c)
• Fräulein Meier (the iPad)
• tippse (the Bluetooth keyboard currently paired with Heinz)

There is actually an Internet Request for Comment (RFC) on "Choosing a Name for Your Computer" (RFC 1178) from 1990.  It points out that "[e]xperience has taught us that it is as easy to choose bad names as it is to choose good ones," and goes on to list a few do's and don'ts, such as: don't use long names, don't use your own name, use words that are rarely used, use theme names.

Well, my list of names is balanced with respect to gender and age.  I don't follow a specific naming system (so no theme names), but usually come up with a name when I unbox the device.  A black MacBook just looks very maculine, while the first-generation MacBook Air surely is a feminine device because of the shape.

"marlene" and "waltraud" allude to Marlene Jaschke, my favorite stage personality of the comedian Jutta Wübbe, and her budgie.  I actually knew the name for my iPad even before unboxing it -- I wanted a meaningful signature instead of the default "sent from my iPad" signature and now it says "Von Fräulein Meier verschickt" ("sent by Fräulein Meier"). "tippse" is a derogatory term for a typist.

"heinz", "horst", and "herbert" are references to my northern German heritage.  You use those names to refer to "someone" (similar to "Tom, Dick, and Harry" in English) -- you also can refer to several unknown people by naming them Horst1, Horst2, and so on. "fred" is just another northern German male name -- as the MacBook Air is thin, it had to be a short name, and a male one because of its angular shape.

The computers I used while working at the Institute of Informatics and later the Institute of Computational Linguistics at the University of Zurich were named:

• keywest (when it it was a Sun workstation, until ca. 2006)
• renamed to sylt
• caipi (when it was replaced by an iMac)
• gnaegi (when I moved caipi to another office, the colloquial term for the Swiss Army Trikothemd 75, a light olive-green jumper, named after former Federal Councilor and minister of defense Rudolf Gnägi, who introduced it)

When almost everybody worked with a Sun, there was a naming system in place: workstations were named after islands (e.g., keywest, sylt, poel, utopia) and servers were named after famous composers' first names (e.g., alban, arvo, igor, gustav, nikolai, bela).  When the workstations were replaced by Macs, cocktail names were used.  So at that time, they followed themes.  However, the admins only gave names to desktop Macs.  MacBooks usually got names following the pattern "username's MacBook" -- not very creative and no theme anymore.

When I studied at Friedrich-Alexander University, the computers in the lab of the Department of Computational Linguistics (CLUE) were named after planets -- or what they assumed to be planets -- e.g., saturn, uranus, sol, terra.  Later that was changed into a naming scheme "clueXX" (with XX being the last part of the IP address).  I worked with clue21, IIRC.

In Konstanz, the iMacs in the computational linguistics lab are named after Roman emperors (e.g., augustus, vespasian, domitian, hadrian, titus, aurel, caesar) and the Mac minis after comic figures (e.g., professor-x, wicked, quicksilver, iron-lad, aurora, captain-ultra, lightspeed).  Also theme-naming here.

Names for my partner's devices at home also follow a theme: Greek mythological figures (e.g., gaia, selene, themis).  However, when I think about this theme-naming recommendation, I do follow a theme: I name my devices according to the first impression they make.

What is your naming theme?

Professor for one year (week 29): Devices galore -- am I a geek?

How many electronic devices do you use regularly?  When you go to a conference or attend a meeting, the first thing participants ask for is Internet access -- and then coffee.  So organizers estimate the number of participants, add some tolerance and then order a certain number of WiFi accounts.  When you look around, almost everybody uses a laptop.  But people have a laptop and a tablet.  So you should double the number of accounts.  And then almost everybody uses their smart phone, too.  Which triples the original estimate.  I don't have a smart phone, but I too travel with laptop and tablet (mostly because I always have to prepare some longer texts for which I prefer a real keyboard and Emacs -- while you can use an external keyboard with an iPad, Emacs is not available for iPad).

When I survey my home office, I discover a high number of computers per square meter:  A black MacBook from 2004 named Heinz, a MacBook Air from 2008 (the rounded-edge model) named Marlene, a MacBook Air from 2013 (the sharp-edge model) named Fred.  Then there is my partner's late-2008 model MacBook (named Themis) and a Celeron PC running NetBSD (named Eurus) we use for scanning -- so we do have a scanner, too (no name for this one!).  All in 10 square meters.  We have a cable modem, which is connected to an AirPort Express wireless router named Horst and a printer named Gaia also connected to the wireless network via a second AirPort Express named Gunther.  And then there are Fräulein Meier, the iPad, Laurin, the iPad Mini, Tippse, my Apple Wireless Keyboard, and Berta, my Nokia phone, floating about the entire apartment.  That's a lot and everybody is talking to everybody via WiFi or Bluetooth!  And in a corner, there is still Herbert, my old Toshiba Satellite notebook from 2001.

I use Heinz for iTunes mainly, I haven't quite finished the migration from Marlene to Fred yet -- Marlene was kind of a lemon, she got a new SSD, but this didn't fix the unexpected crashes and her refusal to install updates.  At my previous jobs, I always had a computer, too.  As I sometimes had several employments at the same times, this almost doubled the number of computers I used regularly: A Sun and later an iMac (with alternating names because of network changes) at the University of Zurich, a Dell laptop at the University of Applied Sciences Northwestern Switzerland named Waltraud, and after that an iMac at the University of Basel also named Waltraud.

Switching computers requires data management, like deciding where and how to access e-mail messages, and where to store documents -- I used the versioning system CVS with the repository stored on the network at UZH, so I could check out and commit drafts from anywhere.  In Konstanz, I decided to use only Fred and not another computer -- I'm also running out of names, but more on this next week -- and asked for a big screen only.

Professor for one year (week 28): Another German compound process: Reisekostenrückerstattung (travel reimbursement)

Last week, I wrote about my conference tour this fall.  As this tour had no private aspects, it was a "Dienstreise" (business trip) and in that case, you can get a reimbursement for your traveling costs -- train or plane, hotel, conference fees, etc.  In German, that's "Reisekostenrückerstattung" and it's not only a compound, it's also complex.

In Konstanz, you have to fill this two-page form: 

It first asks for your address and some personal data and your bank account in the left part of the first page -- this part is easy.  Then you find seven points of instruction how to fill out the reverse side.  Generally, if you need complex instructions for a form, it's a badly designed form.  So this is a first hint that the whole process might not be an easy one.

You have to state when and where you started your travel, when and where it ended and when the "Dienstgeschäft" -- the reason for your travel -- started and ended.  If you remember last week's post, I started my tour in Paris (not my usual "Dienststelle" (place of employment) nor my "Wohnort" (residence) and neither in one of the corresponding countries) and it ended in Zurich (my residence, but a different country than my "Dienstort").  I went from Paris to Berlin to Zurich (for a short stop-over and exchange of cloths) to Florence -- so from France to Germany to Switzerland to Italy.  I crossed three borders and I would have to state the exact time when I crossed which border -- I never heard the captain of a plane announcing that just now we would be crossing a border, so I invented a time.  For the hotel where you stayed you have to justify why you stayed in exactly this hotel.  Of course for Florence and Berlin it's "Nähe zum Dienstgeschäft, Einsparung von Fahrtkosten" -- it wouldn't have been possible to commute.  But these boxes look like check boxes, not radio buttons, so should I also tick other possibilities?  But it was different for Berlin and for Florence.  But then, these boxes are identical to the ones you have to choose for the end point and starting point of your travels and here it's impossible to start from two or more places at the same time, so maybe they are both radio buttons.  I treat them this way.

Interestingly, if you don't travel by train, bus, or plane but by "Kfz" (motor vehicle), you have to state the "Hubraum" (engine displacement) -- up to 600ccm or more.  There are probably different reimbursement rules depending on whether you go by Harley or by VW van.

You have to input the amount of money you spent, but no currency is given.  So do I have to convert expense in CHF and US$ to € or just state them?  I chose the latter and wait what will happen.

For comparison, this is the form the Institute of Informatics at the University of Zurich uses:

Yes, apart from stating address and bank account, it's a simple table where you insert the kind of expense you asking reimbursement for.  And it's even assumed that you might have had expenses in different currencies.  It's a simple single-page form.  You might invent other layouts for this form, but the important part is that you don't spend hours with filling the form.  The German Department at the University of Basel had a similar simple document.  For reimbursements by the Swiss Academy of Humanities and Social Sciences there isn't even a form, you submit receipts for all your expenses, state your bank account and address and that's it.

And don't forget to add your "Dienstreisegenehmigung" (business trip approval).  For this I had to fill an even worse designed two-page document beforehand asking all kind of things -- but not about estimated costs.  It has even more explanations and the parts to be filled out by you are scattered to the two pages.

You even have to fill this document for trips you won't ask for reimbursement.  I guess the main reason for those approvals are insurance issues: You have insurance at your place of employment, but for all other places you need a private insurance.  So if something happens outside your office, the employers insurance is responsible only if he approved that it was necessary that you had to be outside your office.  It's different in Switzerland: As soon as you work more than 8 hours a week, you're insured via the employer for accidents inside and outside your office ("Berufsunfall- und Nichtberufsunfallversicherung").  So there is no need to get official approval to meet with colleagues or clients for a meeting outside your office -- you only need to get approval in case you ask for reimbursement of travel costs as different grants or accounts might be used to cover your expenses.

I guess the more badly-designed documents you have to fill, the more you get accustomed to fill them without thinking.  But this is no good excuse to design poor documents!  And I even haven't mentioned the language used in those forms -- it is far from plain language.  There is much room for improvement from a document design point of view.