  We collected a new dataset that includes approximately eight hours of
audiovisual recordings of a group of students and their self-evaluation scores
for classroom engagement. The dataset and data analysis scripts are available
on our open-source repository. We developed baseline face-based and
group-activity-based image and video recognition models. Our image models yield
45-85% test accuracy with face-area inputs on person-based classification task.
Our video models achieved up to 71% test accuracy on group-level prediction
using group activity video inputs. In this technical report, we shared the
details of our end-to-end human-centered engagement analysis pipeline from data
collection to model development.
