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This blog- or rather its predecessor Google site (now defunct)- originally began in 2009 as an auxiliary tool to communicate on-line with my students in the Universidad Nacional Abierta of Venezuela (UNA), a distance education university where I teach math and statistics. The original purpose of that site was to post grades, some bibliography and model exams as well as some announcements- all in all a very modest and limited educational application of information technology. In time, I began to publish some entries dealing with frequently asked questions, but mostly as a time-saving device for me, as I would point my students to this content.
I soon saw that the Google site platform was not so well suited for this purpose and so moved this site to the present blogger platform. I would still continue to use the new blogger site fundamentally as a repository and to post various clarifications of math and statistics related topics that came up in the subjects I teach. Throughout this time, I had become passionate about R programming and its use to learn math and statistics (I myself having benefited greatly in this regard), and so I would occasionally throw in a post or two with examples of R programming to broaden my student's horizons, although still keeping in line with the course contents. Alas, despite these entries (some with very original content in my opinion), my readership did not grow as I intended and the blog very much lay dormant until some time recently.
I soon saw that the Google site platform was not so well suited for this purpose and so moved this site to the present blogger platform. I would still continue to use the new blogger site fundamentally as a repository and to post various clarifications of math and statistics related topics that came up in the subjects I teach. Throughout this time, I had become passionate about R programming and its use to learn math and statistics (I myself having benefited greatly in this regard), and so I would occasionally throw in a post or two with examples of R programming to broaden my student's horizons, although still keeping in line with the course contents. Alas, despite these entries (some with very original content in my opinion), my readership did not grow as I intended and the blog very much lay dormant until some time recently.
Although somewhat disillusioned by my blog's traffic and the uninterested reception of these posts among my students, my interest in R programming and its applications in college-level mathematics and statistics education did not waver. For example, I developed an R library called estUNA oriented towards students of statistics courses that could be used on RWeb servers on-line. This would permit students to accomplish the computational activities of the statistics projects and use the data sets issued for the UNA courses each semester, on-line and without having to download and install R on their computers.
The intent of estUNA was to make R use and its characeristic console work flow accessible to students with no programming background and very little computer skills by easy to understand function names in Spanish, by including the datasets directly in the library, thereby relieving the student of complicated data conversion and loading procedures, and even by allowing the student to use R and estUNA on a browser on-line without having to download and install R, let alone additional R packages. Throughout these years, I have blogged about this "R solution" for students in my blog, sometimes with detailed examples of its use in various statistical analyses that are topics dealt with in UNA statistics courses.
Another interesting tool I developed in R is HEVASU. Before going into that, I must very briefly explain the Universidad Nacional Abierta's educational and organizational model. The UNA is a nationwide university distance education institution in which course contents and plans are centralized and created by specialized personnel in Caracas. The actual interactions between students and the institution takes place in local and regional centers across the country where students enroll and consult with professors like myself, who act more as facilitators than as teachers in regular classrooms.
In this distance educational model, students are given books (in paper) and detailed course plans including schedules for presential exams. Thereafter, most of the instruction is self instruction and we teacher/facilitators intervene when the student calls upon us for consultation. If this seems like a blast to the past for some readers acquainted with MOOCs and more modern ideas of distance education, eLearning, and the like- well, in my opinion it is too, but that is another topic I'll be blogging about in future posts.
HEVASU was originally an R application I made for myself to simplify the creation of student lists every semester in Excel format for each of my subjects and other associated bookkeeping tasks which makes part of the drudgery of every teacher's profession. Every trimester, we have to fill out activity reports with numbers of how many students came to consultation classified by subjects and undergraduate programs, numbers of graded exams and projects, etc. The original intent of HEVASU was to automate the creation of these reports in Word and pdf formats. In time, I added other functionalities like automated creation of certificates for the UNA introductory course by integrating with LaTeX, all of this in a GUI application done solely in R.
Surely this may strike you as a strange application to do in R, being a language oriented mainly towards statistical and quantitative analysis. Why R and not some other language like Python? Well, it had begun to dawn on me that all this data, collected semester after semester with detailed information about when and which students come to me for consultation on what subjects, when and who comes to take presential exams, what course objectives do they master, etc. was a valuable data to mine and analyze. Surely, I could have still done HEVASU in some other language and the actual statistical analyses in R, but my idea then was to integrate all that into a single application. Nevertheless, in the process I learnt a great deal about GUI programming in R, pdf to text conversion using regular expressions and automated report and certificates generation all which are aspects I'll be blogging about too.
I had by then taken a few MOOCs myself on the topic of Data Analysis and Machine Learning (including an excellent one by Professor Abu Mustafa of Caltech). Additionally, the massive aspect of MOOCs themselves and their potentiality for using student micro-events data to derive powerful educational insights, not to mention the revolutionary global democratization of knowledge that these courses made possible fueled my interest in alternative and emergent paradigms of distance education and my hunger for large data sets on which I could practice these newly acquired techniques. The intent of HEVASU was to produce these large data sets.
This led me to another idea: why not implement formative, quiz-type evaluations on-line to tap into another source of big data? What are the contents and question items most difficult to students about which I should post entries on my blog? What are their patterns for engaging in these on-line quizzes and how does that relate to their eventual success (or failure) in the course? To begin, I chose Mathematics 1, a common course to various undergraduate programs that I believed was critical in student prosecution. I sculpted the quiz generator myself using Javascript and integrated it into this blog.
The on-line quiz system is currently available here and if you want to try it out, use my dummy user ID - 12345678 and select the learning objective for the quiz (currently only the first five). After hitting the submit button you'll see a quiz with five multiple-choice questions. After answering (or not) these questions the student will receive detailed feedback on their errors and where they must look in the book for similar problems or clarifications.
This on-line quiz tool significantly boosted traffic to my site. I must say that it is unique in my University and as far as I'm aware of, there's nothing like it even on the Moodle platforms that the UNA's central level is creating for some courses. Besides being of value to my students' learning process, for me it represents a possibility for creating yet another large dataset. All data on which individuals take the quizzes, when, what questions came up, for which objective, what were the answers the student gave for those questions, gets collected real-time in a Google Doc Sheet via Google Forms integration with my site. I'll be blogging here about the process of creating this on-line quiz tool too.
Although my traffic has increased dramatically, I must say I'm still not happy with my blog. Recently I've come to the realization that blogging about my personal experiences and continuing learning process in using computer technology for instructional and educational purposes, specifically in a distance education environment might be of interest to a wider global audience. To do that, I had to broaden my blog to make it bilingual. While still tending to my UNA public in Spanish, I will now also write to an English-speaking audience.
I realize that all this story about how I basically crafted my own technological solutions to instructional problems by a process of trial and error may strike you as a re-invention of the wheel. Maybe in other universities or educational institutions (distance or not), the computer tools are already created and there's not much for the facilitator to do but to apply them.
Even so, this could be of value to you because: 1) It proves that an you as an individual, without having a whole IT department at your disposal, can create this using commonly available and free technology, 2) this allows you to tap into the data that you and your students generate, 3) you can tailor these tools to your particular educational setting and 4) this will enable people, both teachers and students, in underdeveloped countries to become actors in global knowledge economies. But my approach comes at a cost- you have to be willing to learn a little bit more beyond office applications use. You have to be willing to learn how to code. Nonetheless I assure you your efforts will be paid off.
Of course, I'll also be blogging to students, presenting various case studies in math, statistics and even other subject areas with a computational approach (using R) which they themselves can explore and engage in, or simply blogging about math and statistics topics which commonly pose difficulties to college students. I'll also be blogging about data visualization topics and the use of state of the art quantitative techniques available in the extensive R package system as I come into contact and begin to learn about these myself. This is quite an ambitious and formidable blogging program, to be sure. So when does this blog begin? It begins right now!
