In the process of building a library data service (it’s called Digital Social Science Lab) at The Faculty Library of Social Sciences we have been in intense dialog with faculty members and students about which types of data tools we should provide instructions on.
The comprehensive software list contains programs like NVivo for qualitative data analysis, SPSS for quantitative data analysis, Gephi for mapping data and Python for web scraping. So far so good. But there has been a strong voice in all this that has been shouting for a more basic tool: Excel.
I won’t say that we have been ignoring this voice (which has been exclusive spoken by the students) but we had a strong conviction that Excel was something that the students was expected to master when they started at there study and if there didn’t know it, there had to pick up on it with there teachers or on there own. In other worlds: Not a library job.
But the voice of Excel among students just kept raising so we did two things:
1) Looked at what offers for Excel instructions and support the students had on campus.
2) Invited a group of students on coffee to have a chat on what there needs really was concerning Excel (most surveys we did just pointed at Excel but not for what purpose and on what level of instruction).
On the first matter it turned out that the Study and Career Consultancy at Social Sciences did two Excel intro’s a year and there were always overbooked. Concerning the talk with the students, it we learned that what there were looking for was not an introduction to Excel but more advanced features to handle data in Excel.
I was concerned about the basic library intro to Excel coz it seemed cost full and, in my opinion, it was not a core library task. But things suddenly got more interesting so we gonna roll with an Advanced Excel Course for Data Handling early next year and see how it goes. Focus will be import and export of data, data visualization, algorithms for handling and analyzing data and so on.
My question to the library community: Do you have an Excel introduction at you institution and if yes, what are you experiences? If not, what are your thoughts on this?
When thinking about giving Excel tutorials and intros, maybe this post from datacarpentry on common spreadsheet errors is worth considering: http://www.datacarpentry.org/spreadsheet-ecology-lesson/02-common-mistakes.html
As the nice Excel screenshot in your post illustrates, you can do a hell of a job with Excel — but using the data from an Excel spreadsheet for data analytics outside of Excel, making it machine readable, can be pure hell. (Unfortunately, I confess, I live there every single day…)
Excellent input Timo – thank you for this