At SAGE Campus we like to speak to, and learn from, the people that take our courses. We’re fascinated to hear about our learners’ backgrounds, and how they intend to use their data science skills in the future. This week, we spoke to Ariel Quinio, a learner on Practical Data Management with R for Social Scientists.    

My interests in data analytics can be traced back to my earlier work experience as a research associate in an academic setting. I offered statistical consultation services and analysis for professors and resident physicians with multidisciplinary backgrounds who were conducting their own studies in the health social sciences.  

When I completed my doctorate, I thought I could do more by publishing my dissertation and to write more on topics related to the areas of my current research focusing on global migration and employment. My most recent studies have theoretical underpinnings of the social capital theory using critical discourse analysis, mixed-methods and the intersectional lens.

As a dedicated life-long learner, I am passionate in contributing to knowledge mobilization that promotes better understanding of how social inequalities and discrimination are reproduced and perpetuated through research studies that involve data analysis of complex individual socio-demographic characteristics and economic variables.

I was glad to hear about the SAGE online data science courses for social scientists. I enrolled on Practical Data Management with R as I continuously seek different ways of looking and analyzing my research data and to keep myself abreast with the current trends in data sciences.  

The most important part of the course for me, was mastering the R fundamentals including the five basic data structures, writing codes for looping and conditional statements (for loops and nested for loops), and the function templates. I would have liked more exercises on these components before moving on to more advanced topics in data management (tokenization, web scraping and parallelization). 

The instructor did an excellent job.  As a teacher, Matt Denny was detailed-oriented and employed a variety of teaching modalities including repetition to emphasize important aspect of the lesson, and illustration using examples to apply relevant concepts or procedures to follow.  Most of all, I liked the aura of politeness in the way he talked throughout the course while explaining a complex topic.  I think he has the qualities of a good teacher as evident during the concluding sections where he was able to inspire, motivate and encourage students to go beyond what this course has to offer.

Dr. Ariel Quinio
Ph.D. (Curriculum Studies and Teacher Development)
Ontario Institute for Studies in Education of the University of Toronto