Past Event! Note: this event has already taken place.
| When: | Wednesday, June 16th, 2021 |
| Time: | 12:00 pm — 1:00 pm |
| Location: | Online via Zoom |
| Audience: | Anyone |
| Contact: | FacultyofEngineeringandDesign@carleton.ca |
Since the start of the COVID-19 pandemic, online learning has quickly risen to the forefront of education worldwide, becoming an integral component of the student experience at all levels. While remote-based learning has enabled education to continue from home, Learning Management Systems (LMS) utilized at both the secondary and post-secondary level present a unique set of challenges relating to course delivery and the overall online experience for students.
With that in mind, researchers at Carleton are currently investigating how data analytics could play a key role in enhancing student experience within LMS as they carry out day-to-day learning activities. Using a hybrid artificial intelligence model that combines machine learning techniques with classic statistical methods to identify data patterns and learning trends, valuable insights could be provided to both students and professors, with the potential to deliver in-depth analysis and anonymized feedback for students in quasi-real time.
In this talk, Data Science master’s student Alexis Amezaga and Prof. Omair Shafiq of Carleton’s School of Information Technology will discuss their work towards developing a plug-in for online LMS with the potential to provide professors with greater data analysis tools, in order to help them identify learning trends and other key indicators that can better equip educators to adjust their course delivery in ways that directly benefit students and their online learning experience.
About the Speakers
Alexis Amezaga is a master’s student in Data Science at Carleton University. Before joining Carleton, he was a professor of Physics in the Faculty of Science at Universidad Austral de Chile from 2005 to 2014. His current research interests include the use of hybrid deep learning approaches for analyzing and predicting sequential data, and applications of other machine learning techniques to optimization problems.
Dr. Omair Shafiq is an Assistant Professor in Carleton’s School of Information Technology. His research interests include data modeling, big data analytics, services computing, machine learning and cloud computing. In June 2020, he was awarded a CU COVID-19 Rapid Research Response Grant, titled: Are they Effectively Learning? Enhancing Student Learning Experience Using LMS Analytics Amid and Post-COVID-19 Pandemic.
About the Series
Ingenious Talks is a special speaker series from the Faculty of Engineering and Design that engages the community in discussions of timely and innovative ideas in engineering, design and technology.