There has been an overwhelming lack of participation in computing among African American women. Music has previously been used as an approach to increase engagement and desire to persist in computer science education. The aim of the study is to understand if Black music can be used as a culturally relevant pedagogical approach to increasing engagement in computer science for African American college women. The participants will be African American women at an all-women’s HBCU in an introductory non-majors computer science course. The study is a between-groups study in which one computer science class is given a music project (treatment group) and another class (control group) has no music project. A survey instrument will be used to measure engagement, confidence, desire to persist in computer science, and self-efficacy among other things in these two groups. The study is awaiting IRB approval and to be conducted.

The use of robots as educational tools has shown to be an effective means of attracting students to science and technology related academic fields. By developing relatable robotic programs, an increase in interest in the field of technology will occur. For this work, researchers focus on the social interaction capabilities of a humanoid social robot, Pepper. The research leverages the Pepper robot platform using the Softbank NAOqi framework along with Google Cloud Speech platform to further develop speech and gesture patterns that will afford for a culturally rich engagement interactive experience. In this work, we will leverage the Pepper platform using the NAOqi framework to further develop speech and gesture patterns that will afford a culturally rich engagement interactive experience. By training culturally relevant vocabulary and gestures into the system, the robot will be able to identify verbal cues that will afford decisions on which language will best serve a particular engagement activity (ie. Social vs. formal, AAVE vs. Standard English). We will be testing this multi‐modal interaction technique by using the Peppers onboard visual system to immediately collect user experience data in the wild. 

There is significant research in the use of various technologies to assist with global disaster relief efforts. Due to the ability of robots to work long hours, go without food, water, shelter, resources that humans could not; makes them optimal for use in these specialized circumstances. This research aims to develop an trauma-informed assistive application for use in disaster relief on the Pepper semi-humanoid robot which is specifically designed with the ability to detect emotions. The researcher aims to create an empathetic link with humans and the Pepper robot, focusing on traumatic situations in which Pepper can be an assistant to those affected. Currently, this application is being developed using Choreographe platform to detect images and voice-based interactions. The robotic agent is programmed to identify vulnerable populations in a rescue situation, approach, engage and respond to different emotions that a person may express during the dialogue using natural language processing on the NaoQi platform. The expected outcomes from this work will include Pepper's ability to carry on a beneficial conversation with a human in a stressful situation and offer relevant assistance while also providing significant data for human response workers. We will demonstrate the functionality of the application as this research is still in progress.