Updated September 2021: I'm currently looking for a new Ph.D. student.
Being a Ph.D. student in my lab is much more than merely conducting a research and writing a dissertation about it. It's more about leading an innovative research on a topic that has strongly to do with my lab's research. And an integral component of this process is writing academic papers and presenting in academic conferences. In English.
So, I've developed a task that will help you understand my perception of a Ph.D.-level research. It will also help me assess some of your academic qualities and skills that are required for such an endeavor. Below are the full guidelines; you're welcome to take the challenge and send me your outcome.
Computational thinking (CT) is the conceptual foundation required to define and solve real-world problems using algorithmic methods to reach solutions that are transferable and necessary to various contexts and disciplines (Shute, Sun, & Asbell-Clarke, 2017). It is considered as an important skill for today's learners that will become tomorrow's citizens.
There are many programs and activities that have been developed to promote CT at all age levels. Specifically, I'm interested in online learning environments for CT that include closed tasks for the learners to solve. Such environments include Kodetu, CodeMonkey, Hour of Code, and many more.
What's nice about online learning environments is that they usually automatically and constantly document users' actions; this data - stored in log files - keeps track on everything that happens within the system, in at least three dimensions: Which action was taken? Who took it? When it was taken? Having this information in hand, we can start researching various phenomena and constructs while using the methodology of Learning Analytics. (I urge you to take a look at the proceedings of past LAK conferences, just to get the spirit of this field.)
Here is a log file (.csv file, 18MB, >200K rows) drawn from Kodetu. It includes activity data of about 170 kids who participated in an experiment we held around June 2019. Each row logs a learner's action, either only a change in the code or submitting it. The columns are:
id - numerical identifier of the student;
Browser Timestamp - client-side time of the logged action [Epoch time];
DbTimestamp - server-side time of the logged action [Excel-friendly time];
Level - challenge number [1-10];
target - was the solution (if submitted) successful (i.e., did the astronaut hit the target?);
Pseucode - the learner's solution.
It's highly recommended to play the game (it's free) in order to better understand these fields. For more information on Kodetu, see (Eguiluz, Guenaga, Garaizar, & Olivares-Rodriguez, in press).
After having some understanding of the concept of CT (further reading may be of help) and after getting familiarize a bit with the log file, it is for you to think of a research question that may be studied with Kodetu (and possibly using other tools as well), using Learning Analytics. The research question should be well justified (based on the most updated literature) and should be accompanied by a clear description of a suggested methodology for answering it.
The product of this thinking challenge should be a 1-page document (1 inch = 25.4 mm margins on each side, size 10 Times New Roman font, single line spacing, 6-point spacing before a new paragraph), written in English, that includes the following:
Title that clearly describes the topic of the suggested research;
Full name and contact details;
Presentation of the problem (I mean, if there's no problem, there's nothing to research, right?) and its importance, citing the most relevant literature (probably no need in more than 3 citations);
Research question(s);
Suggested methodology, shortly and clearly described, in particularly referring to measures which are based on log files (but not necessarily solely to such);
Full references for the cited papers.
Please send me the final product by email, along with your CV.
Eguiliz, A., Guenaga, M., Garaizar, P., & Olivares-Rodriguez, C. (in press). Exploring the progression of early programmers in a set of computational thinking challenges via clickstream analysis. IEEE Transactions on Emerging Topics in Computing.
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158.