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In recent years, we have seen a paradox. No matter how much the government strives to incorporate technology into classrooms as a learning resource for students, both national and international reports prove that this is a difficult aim to achieve purpose. Training both preservice and in-service teachers is vitally important for technology to become part of everyday school life. But to achieve this, we must move away from the techno-centric focus of technology. This chapter analyzes the importance of focusing on implementing technologies in the learning activities that teacher-trainers design to prepare preservice teachers. We describe seven types of activities: assimilative, informative management, applicative, communicative, productive, experiential, and evaluation. All of these technology-based learning activities, organized in learning sequences, potentially help teachers to come to terms with technological knowledge in their pedagogical content area.

In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.