Ritu Chaturvedi

Headshot of Ritu Chaturvedi
Assistant Professor
School of Computer Science
Email: 
chaturvr@uoguelph.ca
Phone number: 
(519) 824-4120 ext. 53986
Office: 
REYN 2211
Available positions for grads/undergrads/postdoctoral fellows: 
Yes

Education and Employment Background

Dr. Ritu Chaturvedi received her PhD from the University of Windsor. Between 2016 and 2017, she held a position as an Assistant Professor (Teaching Stream) at the University of Toronto, Mississauga. Chaturvedi joined the School of Computer Science at the University of Guelph in 2017 where she is now an Assistant Professor.


Research Themes

Chaturvedi’s research is focused broadly on data mining and predictive modeling, particularly educational data mining that caters to web-based tutoring systems such as Intelligent Tutoring Systems. Much of her work focuses on topics in teaching and learning. Recent areas of focus include:

  1. Web-based Tutoring Systems. With the recent global pandemic, online teaching and learning has become prevalent and, as a result, web-based online tutoring systems have become important. Chaturvedi is interested in exploring the utility of such systems, and in evaluating whether they are helpful or if they may cause cognitive overload. To explore this question, Chaturvedi applies an algorithm called Clustering Examples based on Relevance, which organizes a collection of worked-out examples into coherent clusters, relevant to the learning concepts covered.
  2. Data mining in other areas of application. Chaturvedi is interested in techniques, tools, and research to automatically extract information and meaning for large data repositories, with a specific focus on education. For example, she has applied data mining techniques to intelligent tutoring systems. Besides education, her interests are also in other areas such as opinion mining (for example, extracting sentiments from COVID-related tweets).
  3. Computer Science Education. To pusue her interest and passion in teaching, Chaturvedi completed the one-year "Inquire certificate 2019-2020 and presented her work titled “Pseudo-Flipped Teaching Method for Large Programming Classes” at the TLI conference this year on June 12th (2019 - 2020). She implements this method in the large programming classes that she teaches and has received tremendous appreciation and support from students in the past.

Highlights

  • Outstanding contribution to student experience, Professor Recognition Program 2021, Residence Services, University of Guelph
  • Information and Communications Technology Council of Canada & BioTalent: Work Integrated Learning Digital Program funding, Co-principal investigator, 2019
  • The Physical Science and Engineering Education Research Centre funding, Co-principal investigator, 2018
  • Excellence in Sessional Teaching, University of Windsor, 2012, 2014