Design Elements of Online Delivery of Data Science Courses

Dr. Ceni Babaoglu, Assistant Program Director, Data Science, and Professor at The G. Raymond Chang School of Continuing Education, Toronto Metropolitan University

Dr. Ceni Babaoglu, Assistant Program Director, Data Science, and Professor at The G. Raymond Chang School of Continuing Education, Toronto Metropolitan University

The advancement in data science, machine learning, and predictive analytics has given rise to a wide range of applications for various types of data such as images, video and audio, text, web, and social media content in an increasing number of public and private sectors. The skills to analyze enormous quantities of data and recommend strategic decision-making are crucial in the modern workplace. This puts data science credentials among highly in-demand qualifications. Online continuing education, especially for highly technical fields like data science, brings unique challenges for both educators and learners.

The students joining an interdisciplinary field like data science have diverse backgrounds and learning needs with one common goal; becoming proficient in data science and acquiring employability skills that require rigorous training. Navigating through the jargon of programming concepts, statistical techniques, algorithms, and data structures can be overwhelming for learners. A key element of the course design to meet this challenge is to integrate theory with practical applications. For instance, conceptual understanding of hypothesis testing and the statistical significance of data-driven decisions should be grounded in relatable real-world problems and datasets. In my experience, the key is to start with simple and small steps but gradually broaden the scope and depth of topics in a systematic way. This approach helps learners build an understanding of data modeling techniques and internalize important background knowledge, identify critical patterns, relate ideas, and apply them to develop data-driven solutions.

The G. Raymond Chang School of Continuing Education at Toronto Metropolitan University is based in one of the most multicultural and diverse cities in the world, Toronto, Ontario. Addressing the diverse backgrounds and learning needs of learners, I design courses that offer easy access to resources in both synchronous and asynchronous modes of interaction.

“Synergizing both synchronous and asynchronous modalities help increase learner engagement and success rate, especially in remote learning settings”

The asynchronous components employ a modern learning management system to establish a fully integrated virtual learning platform. A topic-wise organization of the course materials is provided with ease of navigation between related concepts and techniques. I incorporate principles of universal design for learning allowing access to content in text, audio-visual and interactive formats. Learners can independently watch pre-recorded, and close-captioned video lectures; access reading materials, and make use of self-assessment activities. Learners are also provided with interaction modalities such as discussion forums which enable them to engage with their instructors and peers.

The synchronous components of the courses provide a friendly and supported environment for learners to participate in a guided discussion. I use these live sessions to show them the big picture by demonstrating “the why before the how”, relating the current topic and its real-world applications. This approach sparks motivation and curiosity, encouraging learners to interact and engage in a meaningful dialogue with me, the teaching assistants, and their classmates. The live sessions also provide me with feedback on learners’ engagement and understanding of the topic at hand. Live sessions are essential for fostering their engagement, and maintaining momentum and motivation throughout the course. I also use synchronous sessions to provide experiential learning opportunities to learners as they carry out hands-on lab exercises involving real-world datasets and problem scenarios.

Synergizing both synchronous and asynchronous modalities help increase learner engagement and success rate, especially in remote learning settings. The interactive design of the courses builds a strong instructor-learner connection which allows learners to collaborate, solve problems, evaluate, reflect, and share their knowledge. 

I believe that active and involved learning transforms online classes into a community of continuous learners who can easily access information, confidently build an important knowledge base, and readily apply it to real-world data science problems.

Predictive Analytics

Learning Management

Machine Learning