Multiple Perspectives on Academic Service-Learning Partnerships at the American University in Cairo: A Mixed Method Study

This mixed method study aimed to redress the gap in the literature on academic service-learning partnerships, especially in Eastern settings. It utilized Enos and Morton's (2003) theoretical framework to explore these partnerships at the American University in Cairo (AUC). Seventy-nine community partners, administrators, faculty members, and students from a diverse range of age, citizenship, racial, educational, and professional backgrounds participated in the study. Qualitative interviews were conducted with members of these four groups, and a survey with both close-ended and open-ended questions administered to students yielded 61 responses. Qualitative analyses revealed that the primary motivators for partners' engagement in service-learning partnerships included contributing to the community, enhancing students' learning and growth, and achieving the civic mission of the University. These partnerships were characterized by short-term relationships with partners' aspiring to progress toward long-term commitments. The challenges to these partnerships included issues pertaining to the institution, partnering organizations, culture, politics, pedagogy, students, and faculty members. Key strategies for improving these partnerships included institutionalizing service-learning in the University and cultivating an institutional culture supportive of community engagement. Quantitative analyses showed statistically significant relationships between students' scores on the Community Awareness and Interpersonal Effectiveness scales and their overall participation in community service activities inside and outside the classroom, as well as a statistically significant difference between their scores on the Community Awareness scale and department offering service-learning courses. The study's outcomes underscore the role of the local culture in shaping service-learning partnerships, as well as the role of both curricular and extracurricular activities in boosting students' awareness of their community and interpersonal effectiveness. Cultivating a culture of community engagement and building support mechanisms for engaged scholarship are among the critical steps required by public policy-makers in Egypt to promote service-learning in Egyptian higher education. Institutionalizing service-learning partnerships at AUC and enhancing the visibility of these partnerships on campus and in the community are essential to the future growth of these collaborations. Future studies should explore factors affecting community partners' satisfaction with these partnerships, top-down and bottom-up support to service-learning, the value of reflection to faculty members, and the influence of students' economic backgrounds on their involvement in service-learning partnerships.

Towards Closed-loop Deep Brain Stimulation: Behavior Recognition from Human STN

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. This thesis proposes novel detection and classification techniques for behavior recognition based on deep brain LFP. Behavior detection from such signals is the vital step in developing the next generation of closed-loop DBS devices. LFP recordings from 13 subjects are utilized in this study to design and evaluate our method. Recordings were performed during the surgery and the subjects were asked to perform various behavioral tasks. Various techniques are used understand how the behaviors modulate the STN. One method studies the time-frequency patterns in the STN LFP during the tasks. Another method measures the temporal inter-hemispheric connectivity of the STN as well as the connectivity between STN and Pre-frontal Cortex (PFC). Experimental results demonstrate that different behaviors create different m odulation patterns in STN and it’s connectivity. We use these patterns as features to classify behaviors. A method for single trial recognition of the patient’s current task is proposed. This method uses wavelet coefficients as features and support vector machine (SVM) as the classifier for recognition of a selection of behaviors: speech, motor, and random. The proposed method is 82.4% accurate for the binary classification and 73.2% for classifying three tasks. As the next step, a practical behavior detection method which asynchronously detects behaviors is proposed. This method does not use any priori knowledge of behavior onsets and is capable of asynchronously detect the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity and to detect the finger movements. Our experimental results using STN LFP recorded from eight patients with PD demonstrate this is a promising approach for behavior detection and developing novel closed-loop DBS systems.