Engaging online master’s students: PSMs in the digital world
The world is changing and, like every industry, academia is faced with coming up with new and interesting ways to reach students and provide them with quality education. A growing trend has been the explosion of online courses and programs, making returning to college or graduate school a far more convenient prospect for students, particularly those students who are already working and for whom a face-to-face education would be virtually impossible. So how can we create engaging programs with real hands-on training when we never get a chance to really interact in a live setting with our students?
This question was posed to me in 2013 when plans fell through for another proposed Professional Science Master’s (PSM) program at Cal U of PA and I was asked to put together a letter of intent for a 100% online PSM program in Applied Mathematics in less than two weeks to meet our deadline! My mind swam with not only the possibilities but also the problems. A plethora of questions loomed over my letter of intent: how could we really effectively teach higher level mathematics over the internet; how could we effectively engage students with real applied, hands-on training; how would (required) capstone experiences work with national and international students?
The answer was simple: we HAD to make this work for the online student. A program of this nature had real potential to reach into untapped markets of students who couldn’t attend a brick-and-mortar school because of work, families and life in general. This program could provide opportunities for people who had previously never considered graduate education. The idea was great, so we pressed on through market research, course development, degree proposals and budgeting to make the program a reality.
Our 100% online PSM in Applied Mathematics launched in June 2015 and is nearly 1 year old. We have learned a lot through the process of creating the program and even more after the program launched. Our first two instructors taught 10 week courses for our first summer session with approximately 12 students from our first cohort. They bravely set the pace for what would turn out to be a successful program in applied mathematics, growing within its first nine months to nearly 30 students. Using a variety of technology including pre-made videos, self-made videos, online homework systems and more, they taught our students how to manage databases and optimize operations.
In the fall and spring semesters, we moved our students’ focus to data. It was during these semesters that students would learn data mining, multivariate statistics and nonparametric statistics and it was me who had to teach it to them, completely online. I spent an entire summer recording videos of lectures, videos of me using software, software tutorials and building a massive online quiz and homework system in the Desire2Learn system so that students could work through a variety of problems to try out their newly learned skills.
Our greatest concern was not only being able to impart high level mathematical and statistical knowledge to students but doing so in a completely online environment. This meant that in addition to students learning the material, they also had to learn the technology used to deliver the course. We did find that building a “Launchpad” where all students can connect in discussion boards, find review materials, learn about their capstone experience in more depth and view videos on how to find, install and/or use learning tools in their PSM environment to be particularly helpful. This non-course D2L shell houses all of our student information and is a great place for program announcements. It serves as our virtual program office, where students can always stop by and find what they are looking for in a one-stop-shop.
In general, our feedback from students has been excellent! I am very excited to say that most of our students have indicated the courses to be well-constructed and user-friendly. We have gotten great feedback that students feel more confident with their math and statistical skills, particularly data analysis. Many of our students are now beginning to set up their capstone experiences and many have chosen a focus of data analytics as they have indicated that they now feel more confident with data handling than prior to entering the program. I think a great testament to student reception to our program is that we have not lost any students over the course of our first year!
So what is the takeaway from my experience with online PSMs? These are a great way to reach students that you previously would never have reached (we have students across the globe). However, online PSM programs do require a lot of up-front work. An extensive search of texts for our small offering of courses showed that none of them provided the online support that you can expect with undergraduate level courses. This left us to create all of the learning tools for our students. These courses required much more thought and effort to put together than the traditional online undergraduate math course. It was truly a challenge to put together sufficient course materials for master’s level courses to run smoothly; to have the appropriate amount of rigor without causing students undue stress. In the end, these are worth the effort. We will graduate our first cohort of students in August and we are glad to have played a part in enhancing their education and advancing their career.
Dr. Sovak was one of our featured speakers at ICTCM 2016. Access more than 30 dynamic sessions by registering through the virtual track. Or if you have an idea for next year, submit a proposal.
About the Author
Melissa Sovak, Ph.D., earned a Master of Science and her Ph.D. in statistics from the University of Pittsburgh and a Master of Science in Computational Mathematics from Duquesne University. Dr. Sovak also taught at both those schools and her research interests are statistics education and teaching methodology. She is extensively published on topics such as statistical reasoning and color models for image decomposition. She also has extensive experience as a market research analyst.