Automated Essay Scoring in Argumentative Writing: DeBERTeachingAssistant

Automated Essay scoring has been explored as a research and industry problem for over 50 years. It has drawn a lot of attention from the NLP community because of its clear educational value as a research area that can engender the creation of valuable time-saving tools for educators around the world. Yet, these tools are generally focused on detecting good grammar, spelling mistakes, and organization quality but tend to fail at incorporating persuasiveness features in their final assessment. The responsibility to give actionable feedback to the student to improve the strength of their arguments is left solely on the teacher's shoulders. In this work, we present a transformer-based architecture capable of achieving above-human accuracy in annotating argumentative writing discourse elements for their persuasiveness quality and we expand on planned future work investigating the explainability of our model so that actionable feedback can be offered to the student and thus potentially enable a partnership between the teacher's advice and the machine's advice.

Automated Camera-Based Estimation of Rehabilitation Criteria Following ACL Reconstruction

Anterior cruciate ligament (ACL) reconstruction necessitates months of rehabilitation, during which a clinician evaluates whether a patient is ready to return to sports or occupation. Due to their time- and cost-intensive nature, these screenings to assess progress are unavailable to many. This paper introduces an automated, markerless, camera-based method for estimating rehabilitation criteria following ACL reconstruction. To evaluate the performance of this novel technique, data were collected weekly from 12 subjects as they used a leg press over the course of a 12-week rehabilitation period. The proposed camera-based method for estimating displacement and force was compared to encoder and force plate measurements. The leg press displacement and force values were estimated with 89.7% and 85.3% accuracy, respectively. These values were then used to calculate lower-limb symmetry and to track patient progress over time.