CU Denver ORS CRC -- Pedagogical Intervention Recommender System (TABY 2.0) -- Towards Effective and Engaging Remote Teaching Experience

Background: We would have seen the best of online education in the past year and a half during the pandemic. Almost everyone who is learning was doing so remotely through several online platforms like Zoom, Teams, etc. Yet, we have seen the struggling remote education systems despite all its advantages including the flexibility and health safety assurance. The shortcomings include deterioration of physical and mental health and non-realization of social needs, deterioration of the quality of academic activities, peer-to-peer and learner-to-educator interactions, group activities outside classroom, etc. According to a recent survey conducted by National Center for Education Statistics, enrollment has declined about 4 percent at colleges and universities nationwide. This trend has disproportionately affected minoritized students including those who are majoring in STEM fields and will exacerbate the already existing opportunity gap due to the pandemic. In this phase II CRC proposal, we plan to test and scale TABY 2.0 (Teaching Assistant Bot for You) focusing on undergraduate STEM majors at the University of Colorado Denver (CU Denver) and guided by our Phase I work (TABY 1.0).

Proposed Collaborative Research and its impacts: We propose TABY 2.0 (Teaching Assistant Bot for You), an extension to our pilot-tested pedagogical tool which besides measuring student interactions and engagements in a synchronous remote classroom environment more efficiently, will be able to assist course designers and instructors in remote and virtual learning environments by leveraging image understanding, logic reasoning, speech to text recognition and natural language processing technology that will fuel a robust content recommendation tool. We plan to emphasize on developing robust machine learning method that addresses two scenarios: i) limited availability of comprehensive dataset that otherwise could be used to learn patterns of the teaching and how to encourage engagements, ii) a commonsense reasoning approach that ties with our existing knowledge of the norms of the classroom, effective pedagogy, and contingencies the educators employ in everyday teaching. We will work on knowledge representation of the literatures on approximating student engagement that draws upon the community of inquiry model to address the cognitive, social, and teaching presence in online/virtual learning environments. We draw upon the work of other researchers (Gupta, 2015) that drew upon facial recognition feature extraction, context-based inference, and suitable machine learning methods in MOOCs (Massive Open Online Courses). Our project will extend this body of work by adding new data sets with analytics including students’ engagement with course materials (e.g., readings, videos, peer-to-peer interactions etc.) to provide a contextual data set that is supported with the facial gesture-based engagement detection data sets we collected in our pilot study. We plan to implement this new tool in the ongoing virtual (synchronous and asynchronous) as well as hybrid courses. To start with, we will work with 50+ STEM declared Freshman students including (CS) at CU Denver who will be enrolled in various online courses. We specifically plan on recruiting first generation students and other minoritized students. We plan to examine the impact of incorporating TABY 2.0 on student engagement in these courses by assisting the course instructors.

Data management plan: The COMIRB/IRB application (Protocol #: 20-2803) has been approved during TABY phase 1 development and we collected preliminary data that indicated that a Phase II exploration is worth pursuing. We will be able to continue to collect additional data sets pertinent to this proposed project starting Fall 2021 and specifically focus on minoritized STEM majors and their engagement with online learning environments.

Sponsor Creative Research Collaborative Grants of the Office of Research Services at University of Colorado Denver ORS link

Collaborators

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