Understanding the language environments of early learners is critical in facilitating school success. Increasingly large scale projects (e.g., Providence Talks, Bridging the Word Gap) are investigating the language environments of young children in an attempt to better understand and facilitate language acquisition and development. The primary tool used to collect and analyze data related to the language environments of young learners is the LENA digital language processor (DLP). LENA allows for the continuous capture of language, primarily focused on a single child to adult interactions for up to 16 hrs. Subsequent analysis of the audio using spoken language technology (SLT) provides meaningful metrics such as total adult word count and conversational turns. One shortcoming of collecting continuous audio alone is that the physical context of adult-to-child or child-to-child communication is lost. In this study, we describe our recent data collection effort which combines the LENA and Ubisense sensors to allow for simultaneous capture of both spacial information along with speech and time. We are particularly interested in researching the relationship between the physical and language environments of children. In this study, we describe our collection methodology, results from initial probe experiments and our latest efforts in developing relevant SLT metrics. The new data and techniques described in this study can help in developing a richer understanding of how physical environments promote or encourage communication in early childhood classrooms. In theory, such speech and location technology can contribute to the design of future learning spaces specifically designed for typically developing children, or those with or At risk for disabilities.