University of California, Irvine. His research focuses on how theoretical insights and methodological innovations of network analysis enhance our understanding of how organizations function. He pioneered the concept of cognitive social structures, wherein individuals provide their perceptions of the network in which they are embedded. Empirically, he has related these perceived structures to organizational culture, turnover, reputations and power in organizations.Prof. Daniel P. Siewiorek, Carnegie Mellon University Professor Daniel P. Siewiorek is the Buhl University Professor of Electrical and Computer Engineering and Computer Science at Carnegie Mellon University. He has designed or been involved with the design of nine multiprocessor systems and has been a key contributor to the dependability design of over two dozen commercial computing systems. Dr. Siewiorek leads an interdisciplinary team that has designed and constructed over 20 generations of mobile computing systems. He has written nine textbooks in addition to over 475 papers. He is Director of the Quality of Life Technology NSF Engineering Research Center and previously served as Department Head of the Human Computer Interaction Institute. He has been the recipient of the AAEE Terman Award, the IEEE/ACM Eckert-Mauchly Award, and the ACM SIGMOBILE Outstanding Contributions Award. He is a Fellow of IEEE, ACM, and AAAS and is a member of the National Academy of Engineering. Dr. Asim Smailagic, Carnegie Mellon University Levels of Social Network Analysis and Small Team Problem Solving in the Classroom AbstractIn a collaborative learning environment, transfer of knowledge depends strongly on sociocultural factors including the interaction among the learners as well as the interactions with the instructor. An understanding of some of the factors that affect the dynamics of learners and learning can be gleaned through the use of social network analysis (SNA). Even a single time-slice of the social network of a class, which shows the social ties between the students, can reveal much about a student's position in the network, which may affect what and how a student learns and his/her problem solving ability. This paper presents a study of the levels of the social network of students in an engineering project course. The analysis is done in the context of a design task given to small teams of students. The quality of the final design is evaluated using a rubric that yields a quantifiable result. We relate the team members' perceptions of their network with the problem solving ability of the team.We found significant correlations between a team's project score and a team's balance as well as with the individual student's perception of their team balance, although the sample size was small. In this context, the balance of a team is the degree to which feelings are reciprocated, as discussed in Section 3. The perception of team balance, or the levels of the social network, is discussed in Section 6. The levels of social network analysis uncovers whether team mem...