Apart from handling the website and social media sides of the lab; I focus mainly on compiling data to use from ExecEd’s Canvas site and social media outlets.

I am most passionate about seeing the product of what we do. Working with a tangible source of data and working on the algorithms which format that information into usable data makes me appreciate seeing a nice graph or curve from the messy reality in the end.

The biggest challenge in what I do is the constant learning required to get what information we want. There is no one-fits-all solution to the problems we face, and so I end up spending a small portion of my time accomplishing large amounts of things, and a large portion of my time learning about small details required to put all the parts together.

I have been working with Yoshie and the team for 2 years now, as a research assistant. I help with data cleaning, analysis, and occasionally with literature reviews using my knowledge of Excel, R, and other software.

I am most passionate about the idea of exploring the unknown – handling new parameters and navigating through the myriad of data points to discover something new is quite exciting.

Data cleaning for me is sometimes bottle-necked by lack of software functionalities, and results in manual inputting, which can be very time-consuming.

The ROL team congratulates Kevin on his Graduation and wishes him good luck for his next adventure.

I have conducted research for and supported many quantitative and qualitative analytics projects over the years, including determining competitive social media efficacy, conducting social network analyses from survey data, and creating a comprehensive regression model to forecast enrollment patterns on both a micro and macro level.

Apart from teasing out the key insights from a large data set that initially might seem random and chaotic, I am most passionate about figuring out how to tell a compelling story from the data because it challenges me every time and forces me to think outside the box.

The biggest challenge by far that I face in data analytics is cleaning the data. Often the data that we get is messy or has not been collected in the way that we want (or is missing key aspects that we need for the analysis). For example, when doing the social network analysis with Gephi, we ran into several roadblocks when converting the XML files into CSV files readable by Gephi.

The ROL team congratulates Ryo on his Graduation and wishes him good luck for his next adventure.

The presentation about our laboratory work at Salesforce Higher Education Summit in Austin, Texas is now available at the link.

Currently, I am a Graduate Research Assistant at the lab. I have analyzed text in participants’ applications and built both a B2B model and individual enrollment prediction model.

My passion about data analytics is using my research work to find the story behind data. I can translate scientific ideas into my findings and make understandable insights.

The biggest challenge I have faced in data analytics is applying the theoretical methodology I have learned in class to real-world data and build the model. Fitting different models and finding which one is the best to describe real-world trends is challenging and exciting.

Analytics means being one with data. And working with data gives one a thorough and extensive understanding of the entire business and all related processes. My experience at the lab has taught me immensely – from learning the internal processes in the education industry to learning new software and analytical techniques for various analyses. Yoshie’s guidance has proven to be immensely useful throughout the journey.

A British economist once said that if one tortures data enough, it will confess. These confessions jumping onto us teach us a lot about the consumer’s thought process and how he interacts on various fronts before making an important decision. It is such insights derived from data and building a story connecting them that really excite me and drag me to work every morning.

There is an ocean of data surrounding us and various things can be explored if data is viewed from various angles. It is a challenge to not lose sight of the task at hand. Data pouring over from many different sources adds to the challenge.

This last Friday, the Return on Learning Lab’s own Yoshie Tomozumi spoke at the Salesforce HE Summit at the Hilton Austin on serving learners better through data analytics. Thanks for all those who came out!

Our lab work will be presented at the Salesforce Higher Ed Summit, April 28th. Join us and see what’s new in the Return on Learning Lab!

During the past six months, the most important thing I have learned is the importance of translation from scientific idea to the findings or explanations that the general public can easily understand. The biggest challenge throughout has been the lack of desired data and imperfection of the collected data. Most of the time, it takes longer to clean the data than to actually do the analysis. However, the result was always exciting. Being able to extract information from the raw data and being able to see the impact of the findings are the most important motivation that I would keep me doing this work every day.

Reflections on the data analytics work

What is one key learning take away from your research work?
The key take away for my research work is to understand the story behind data; only then could we develop valuable insight. For example, different programs have different targeting participants with different behavior patterns. We need to know what causes these differences and what kinds of analysis could have potential value. The best way to understand is to communicate with people who are more familiar with the problem.

What is the biggest challenge you have faced while you work?
The biggest challenge I have faced while working is how to effectively deliver the analytical findings to an audience with business/management background. On one hand, the findings are in most cases not conclusive, which is the nature of real-world data. On the other hand, it would be more important to discuss more about the logic and business insight instead of algorithms. So the presentation techniques are critical.

What excites you most in your research work?
The most exciting part is to know our work is actually making an impact. Our suggestions for data collection, payment collection, marketing strategies, our findings of participants’ activity pattern, and our suggestions for the future prediction and matching system will make CBS ExecEd as a whole a more efficient platform, and boost the revenue.

Pick one image that best describes the nature of research work you have done.
This picture is a word cloud for research, which corresponds with my text analysis study. Research is an exploratory process and researchers will develop a comprehensive set of skills. It is challenging, rewarding and really thought provoking.