Welcome to our new interview series “5 Questions with an HPCC Systems Community Member” where we will highlight some of our most prominent HPCC Systems community members. These are the people who are avid users of our open source platform and can offer real world expertise and best use information.
A doctoral candidate at Keiser University and a computer science instructor at Wayne State University, Itauma Itauma is an expert in learning analytics and uses HPCC Systems for his educational research. A consummate student, he has an undergraduate degree in electrical engineering and two master’s degrees: a Master of Science in computer engineering from Istanbul Technical University, majoring in human-robot interaction, and a Master of Science in computer science from Wayne State University, where he presented a thesis based on leveraging HPCC Systems for Big Data analytics.
We spoke with Itauma recently and took a deep dive into his work in educational research examining how HPCC Systems has enabled him to excel in his field.
Why have you pursued educational research?
In my academic journey and career, I have been an electrical engineer, computer engineer, roboticist, and a computer scientist. However, my passion has always been to explore ways in which students can be academically successful. As an adjunct professor teaching computer science courses, I saw that having an advanced degree does not necessarily translate to effective teaching. There was a gap. And I saw the key in education and education analysis.
Students have unique combinations of backgrounds, interests and strengths, which can be used to create optimized learning environments. So, to be an effective instructor, I saw the need to equip myself with the tools used by educators to create an effective learning environment.
If there was one thing that you would like to tell the world about your research, what would that be?
My current research project is examining how to increase enrollment in STEM programs among minority groups. I believe a balanced workforce leads to a more innovative society and with data analytics, the focus is on the long-term benefits of education and not just academic success. I also intend to use educational analytics to drive personalized learning. The word education has its root from educare, which means, to bring out that which lies within. So, one thing I hope to achieve is to harness the hidden talent in the world.
How would you say that HPCC Systems platform helped you in your education research?
HPCC Systems is a digital processing tool. By this, I mean, high volume, high velocity, or high variety information, that requires advanced analytics tools. Educational data sets are now increasing in volume, velocity and variety. Large volumes of heterogeneous learning data are being generated all around the world at a very rapid pace.
In analytics, key findings are discovered from generated data, and advanced digital analytics methods provide endless possibilities for personalized learning. HPCC Systems provides advanced and robust modeling and analytics, regardless of digital volume and hard disk space. Some traditional statistical packages have limitations when it comes to big data and advanced modeling. Being able to use HPCC Systems for simple statistical solutions is an advantage because as data size and complexity increases HPCC Systems still delivers.
If you were to highlight one aspect of HPCC Systems that you really like what would it be? Either on the platform or the community or both.
I like that the platform is open source, and it’s fillable and centered on the ECL programming language. ECL stands for Enterprise Control Language. It’s declarative, data centric, and highly extensive, enabling me to focus more on what I want to do and not how I want to do it. I find ECL very intuitive and robust in implementing the Selenium algorithms. I also find the HPCC Systems community very helpful and resourceful. I remember when I started learning ECL and was able to receive help instantly when I asked a question to the community.
What are the strengths of HPCC Systems versus other platforms you may have used?
There are other open source platforms for big data processing, but I have found HPCC Systems more intuitive, flexible and efficient. With big data platforms, using a MapReduce architecture, I must think about how data is being stored and transferred when implementing some machine learning algorithms. However, HPCC Systems handles that, which allows me to focus more on implementations of algorithms.
Want to hear more from Itauma’s interview with Flavio Villanustre, VP of Technology, LexisNexis Risk Solutions and HPCC Systems? Listen to the podcast linked below where Itauma continues to discuss his work in educational research using our platform, his opinion on HPCC Systems and our competitors, what he hopes for in the future, and more.