The Human Factor in Software Engineering

CreaRE 2015: Fifth International Workshop on Creativity in Requirements Engineering
https://sites.google.com/site/creare2015/

date: March 23, 2015
place: Essen (Germany)

*** Workshop Agenda ***
14:00-15:00 Kim Lauenroth: Creativity is not a talent, it is a way of operating! (Key Note)
15:00-15:30 Sebastian Adam and Marcus Trapp: Success Factors for Creativity Workshops in RE
16:00-16:30 Jennifer Horkoff and Neil Maiden: Creativity and Conceptual Modeling for Requirements Engineering
16:30-17:30 interactive session and discussion


*** Workshop topic, background and motivation ***
In the past five years, Requirements Engineering (RE) has been increasingly more recognized as creative activity. This is especially true in contexts of developing systems for application areas such as game design, crowdsourcing, assistive health-care, smart cities, and green computing. RE for those areas demands stakeholders to create visions of future software systems and to imagine all their implications. Creativity techniques that have been developed and used in other disciplines and areas of problem-solving, have the potential to be adapted and adopted in today’s RE, becoming the foundation for innovative RE processes addressing both problem analysis and solution design.

*** Goals of the workshop ***
The CreaRE series of workshops brings together RE practitioners and researches engaged in discussing the role of creativity in RE, the array of creativity techniques that can be applied to RE, and the ways in which creativity techniques from other disciplines can be leveraged in RE. Drawing upon the previous workshop editions, the intended purpose of the CREARE’15 workshop is to be a forum for the exchange of emerging ideas, experience and research results. It also aims at raising awareness in the RE community of the importance of creativity and creativity techniques.


*** CreaRE 2015 Program Committee ***
Sebastian Adam Fraunhofer Institut IESE, Germany
Dan Berry University of Waterloo, Canada
Thomas Herrmann Ruhr-University of Bochum, Germany
Eric Knauss Chalmers | University of Gothenburg, Sweden
Anitha PC Siemens AG, Erlangen, Germany
Kurt Schneider Leibniz University Hannover, Germany
Roel Wieringa University of Twente, The Netherlands
Konstantinos Zachos City University London, UK

*** Workshop Organizers ***
Andrea Herrmann, Herrmann & Ehrlich, Germany
Maya Daneva, University of Twente The Netherlands
Joerg Doerr, Fraunhofer IESE, Germany
Anne Hoffmann, Siemens, Germany

I like this article about the job and salary structure in science: How Academia Resembles a Drug Gang. In fact, this was the reason why after my PhD I left the scientific circus to find a stable employment with career paths and security.
However, then I found out what happens in a company when it is restructured. Or sold. Career paths disappear and when it comes to survival, then a family father's income is always more important than the income of the young woman who was employed a year ago.
So, I took a second jump into science and worked hard. During my PhD time, I just did my job, now I did much more than that. But the up-or-out-principle works without pity. And having worked in companies for 6.5 years was a large disadvantage.

OK, there is no use to cry about past times gone. I am now creating my own career path.

Recently, I read this motto, and I love it. Because when you invest time in a project, then you have believed in this project. And if it does not end as you expected, the idea probably still is as good as ever, but the form was not ideal. For instance, I have developed courses which I did not sell so far. One course became an e-learning course instead, another one will become a book soon. I still believe in the idea and do not want the idea and preparation to be lost. And finally: If the book sells great, people might want to experience the course in real, too. Anyway, I hate to dump 50-100 hours of work!

Here am I, back from winter lectures. I have been quite busy, giving lectures in three different towns! Recently, I restructured a course completely which I have held about ten times during the last three years. The last course evaluation was the last straw that broke the camel's back.

It was a well-designed course where each participant during these two days treated two out of six topics twice actively and consumed the rest twice by the presentations of their colleagues. So, if someone was with us mentally the whole time, (s)he was well prepared for the exam in the end. However, the students disliked the course. I was accused of being lazy and incompetent. This never happens to me in the other courses which are less interactive and less demanding. In fact, it is much easier for me to come with a powerpoint presentation and talk for two days through. There can be no surprises, no difficult questions, no discussions about why this student's solution is wrong or maybe not.

I can talk for days, and talk and talk and talk. But in the pedagogic course, we learned that we must not do this. We must make the course participants work. They must do exercise after exercise and discover the knowledge themselves.

Finally, it did not work. I will forget everything I learned in this course. The students want ex-cathedra teaching. It is less risky. When they do an exercise, they assume that it is wrong anyway. And if their colleagues present something, they, too, assume that it is wrong and not worth being listened. And when they come to a course, they do not expect to learn something there. They expect that they can write their emails there and plan for the exam preparation some days later.

So, in the completely revised version, I did my presentations most of the time and a very short case study exercise in addition, to have some change. That was completely OK and they liked listening to me and taking notes and all this school-like setting.

End of the story: I am back at ex-cathedra teaching. I do not know on which weak scientific basis trainers are taught to torture their participants by making them work. When the participants do the exercises, this is mainly out of mere politeness, not because they love it. Doing an exercise creates stress for them, like an exam. There is always the risk they do something wrong and loose their face in front of the whole group. Who loves this?

I do not completely give up hope to find some really genial, innovative trick for teaching. But for the moment, it is OK for me to stand and talk all day.

Mentoring usually means that a young person learns from someone with more experience. More experience means that there is more knowledge, and this knowledge can then flow to the person who has less.

Reverse mentoring, instead, works the other way round: The experienced person learns from the younger one. How is this possible? In German, we know the word "Betriebsblindheit" which can be translated as "routine-blinded". This means that experts have learned to see things in only one way. New, unexperienced persons see things differently. Of course, a new or different sight is not always better. But it might. And the discussion about why things are as they are, can be helpful to assure whether you really know what you are doing and whether it still makes sense, whether it makes sense in any case etc.

The term of reverse mentoring, however, is regularly used in cases where older people learn from younger about topics where the young persons really have more experience, for instance about new media.


Experiences from Lufthansa and T-Systems (in German): http://www.personalwirtschaft.de/media/Personalwirtschaft_neu_161209/Produktfamilie/Jahrbuch%20PE/Jahrbuch_2011_Beitrag_ReverseMentoring.pdf

I am currently implementing some key learnings from my own gender studies performed 2013. For instance, in gender studies it is found that women in informatics work on "soft topics" preferably. This might sound nice, because women have a natural gift for soft topics. But this is nonsense. I am more talented for hard facts, statistics, numbers, formulas. The soft topics are fascinating me because they are even more complex than mechnical research questions because soft skills and emotions are more difficult to measure and enhance the complexity of statistical treatment.

The harm that is done by women moving to soft topics is in that these topics have a low prestige. Producing code is valued most in informatics. This means that people who do this have a higher prestige, this work is better paid and it is easier to get funding for such work as a freelancer or as a scientist.

I wondered why this could happen that during my 20 years of work life I drifted from hard topics like programming, simulations and numerical calculations to requirements engineering. Was it a completely free choice? No. I remember jobs where suddently I was told to keep my hands from the code, in order not to damage anything. When I asked to get programming tasks, I was told this was not possible because I had never written any code before and it is too difficult for me to learn. This was not true, but prejudice beats facts. When the boss says programming is too difficult for me, I must not touch the code.

Why I write this is the following: I kept my eyes open. The world is full of opportunities and we can choose. Currently, I am preparing for a programming course, a course about IT security and for a Matlab Simulink course. Welcome back, my good old friends! Differential equations, vehicle models, graphics, DOS attacks! I am feeling like in the good old times of my studies when colourful formulas were telling me their secrets and I calculated air planes in the flight or cold metal falling into warm liquids. I am on my way back to hard topics...

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No, I did not leave Internet. I just was busy with the lecture start. Right now, I was verifying whether I really defined an unsolvable task when I asked a student to prepare a presentation about JAutoDoc. He said that he found nothing about it. It was not a YouTube. Ehm? In fact, there is ONE YouTube video about JAutoDoc. And finally, there are even more possibilities to do online research about JAutoDoc than YouTube. YouTube is neither a search machine nor a university library. Not all the world's knowledge is documented at YouTube, you know?
He said that if I find more than he did, then I am quite good at research. Oh yes, I am quite good at this! *grin*