Social Network Analysis (SNA) has evolved as a popular, standard method for modeling meaningful, often hidden structural relationships in communities. Existing SNA tools often involve extensive pre-processing or intensive programming skills that can challenge practitioners and students alike. NodeXL, an open-source template for Microsoft Excel, offers a potentially low-barrier-to-entry framework for teaching and learning SNA. We present the findings of 2 user studies of 21 graduate students who engaged in SNA using NodeXL. We found NodeXL to be an effective tool for a diverse set of users, and significantly, a tightly integrated metrics/visualization tool that can spark insight and facilitate sense-making for students of SNA. Our presentation will focus on the unique features that made NodeXL learnable and usable. After a brief overview of the NodeXL tool, we will describe our research methodology, based on Multi-dimensional In-depth Long-term Case studies (MILCs), an approach that enables effective evaluations of complex visual analytics tools. We will discuss NetViz Nirvana, layout principles that can increase the readability and interpretative power of social network visualizations, and present a sample of visualizations produced by the students. Finally, we will offer lessons learned for educators, researchers, and developers of SNA tools such as NodeXL.