Chapter 4treats the fundamentals of radio propagation path loss, also known as large-scale fading. A wide range of practical radio propagation models are presented, and the fundamental theories of reflection, scattering, and diffraction are presented with many examples. These propagation mechanisms give rise to level of coverage and interference experienced in any wireless network, and, in urban environments, it is shown how the radar cross-section and ray tracing models can give accurate prediction of large-scale path loss in a mobile communication system. Shadowing is also considered, and the log-normal distribution is found to describe the shadowing about the distance-dependent mean signal level. Statistical approaches to quantifying outage are provided.

Scaffolding is the support provided to students by the learning environment, which includes the teacher but also curricular design, technological tools, and classroom social practices. Scaffolding is a social encounter between a teacher and a student and can involve tutoring and mentoring, but is more effective when both teacher and learner participate jointly in a complex and authentic disciplinary practice. Scaffolding simplifies a task so that it is within reach of the learner; it supports learners in participating in authentic disciplinary practices even before they have mastered the discipline; it helps learners focus on the most important aspects of the problem. Effective scaffolding is adaptable and contingent on the learner’s evolving understanding – the degree of structure should be gradually reduced or “faded.” This can be done by inferring a learner’s current understanding using digital traces or dynamic software.

This chapter outlines the tight connections between multimedia learning and worked examples in that worked examples can make multimedia learning more effective, and applying instructional multimedia guidelines makes learning from worked examples more effective. The to-be-expected effect sizes when using worked examples are discussed, and the theoretical rationale of the worked-example effect is explained (e.g., example study replaces unproductive learning by problem-solving). In addition, a set of instructional guidelines for optimizing learning from worked examples is derived from findings on factors that moderate the worked-example effect, such as fading worked steps or including incorrectly worked examples. Furthermore, the theoretical implications of the general pattern of findings on worked examples are discussed (e.g., with respect to the role of generative learning or extraneous processing). Finally, important questions to be addressed in further research are proposed.