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At many universities, web lectures have become an integral part of the e‐learning portfolio over the last few years. While many aspects of the technology involved, like automatic recording techniques or innovative interfaces for replay, have evolved at a rapid pace, web lecturing has remained independent of other important developments such as Web 2.0. The aim of this paper is to exemplify and discuss the benefits web lecturing can gain from a Web 2.0 perspective.

The paper describes an implementation of three Web 2.0 features for the virtPresenter web lecture interface. These are time‐based social footprints, a mechanism for linking to user created bookmarks in a web lecture from external Web 2.0 applications and a special web lecture player that enables users to embed their own web lecture bookmarks in wikis or blogs.

The paper shows how conceptual and technical obstacles in bringing Web 2.0 features like social footprints to web lectures can be overcome. It also makes evident that linking web lectures in Web 2.0 systems require special adaptations due to the time‐based nature of web lectures. The technical discussion shows that many Web 2.0 features require feedback channels in order to communicate information back to servers (e.g. to understand how the content is used) and that most contemporary media players have to be modified in order to support feedback channels.

The paper shows that web lectures can benefit from Web 2.0 ideas and presents examples how Web 2.0 and web lectures can be brought together.

Web 2.0 is a popular trend that transforms the way in which the internet is used. This paper shows how web lectures can be enriched with Web 2.0 features and how they can be integrated with Web 2.0 systems by discussing three implementation examples.

The content, provided in learning management systems (LMS), is often text oriented as in a usual textbook, extended by some animations and links. Hands on activities and experiments are not possible. The paper aims to give an overview about the concept to couple smart simulation and assessment tools with an LMS to provide a more explorative approach to the learning content.

Interactive components, such as smart design tools and online laboratories are added to an LMS that allow exploring the learned content additionally to text parts interactively. The objective of this teaching concept is to empower the students to solve complex design tasks for digital systems and to validate the results. This requires on the one hand site knowledge about the mathematical background of the algorithms used by design tools, and on the other hand, experience from as much as possible examples. Commercial tools are too complex for teaching purposes and hide mostly the algorithms they use for the several design steps. That is why we have developed smart special tailored tools for each single design step that should be learned during a lesson.

These smart tools are very useful to support the process of understanding and learning by doing. Learners can explore the several design steps with own examples and get immediately feedback about the correct solutions.

The connection to an LMS allows us to record all students' relevant actions in the design process and to evaluate the student or to give individual tailored hints.

The paper introduces a new teaching concept that allows exploring the learned content interactively additionally to text parts.

The purpose of this paper is describing the seamless integration of the question‐answer interaction into automatic lecture recordings (ALRs). This includes the design and implementation of the question management (QM) software for a virtual camera team.

Coming from the human role model the interaction and its management to the virtual world is transferred and integrated it into a virtual camera team. All events are translated into sensor inputs which get processed by the virtual director and are used for the collaboration of the team in order to implement more complex cinematographic rules.

It is found that it is possible to record the whole interaction, to record the original voice of the questioner out of an audience without handing out a microphone or forcing him/her to walk to one, and to record a video of the questioner while asking. So, it is easier to follow a lecture recording as more details are recorded automatically.

First experiences on using this software clearly show the small weaknesses of the first version. As mentioned in the outlook, these are currently being addressed, e.g. by looking for a more natural interface.

The paper demonstrates how to use the question‐answer interaction as sensor input for an automatic lecture recording (ALR) system based on the roles of the according human originals. It ensures that many details of a lecture can be recorded seamlessly to keep the lecture context continuous and therefore to make the lecture recording more vivid and interesting.

Playing back recorded lectures on handheld devices offers interesting perspectives for learning, but suffers from small screen sizes. The purpose of this paper is to propose several semi‐automatic post‐processing steps in order to improve usability by providing a better readability and additional navigation functionality.

Several rather simple (and thus fast) statistical indicators were implemented and evaluated to detect certain events in a lecture recording that can be used in a semi‐automatic post‐processing approach.

The evaluations verify the quality of the analysis. By presenting an actual implementation, the paper demonstrates how these results can be used to improve visibility of the content and provide further navigation options, thus increasing overall usability.

This paper provides practical information on how to build a useful system for everyday usage in normal teaching scenarios. The paper presents different approaches illustrating initial steps for achieving better visualization and navigation functionality for lecture podcast – two issues that are essential for their usability but have not found much attention so far. This implementation demonstrates the usefulness and feasibility of the proposed techniques. Although the purpose of this article is rather on practical aspects than on presenting new research results, some of the observations can have implications for research in this area and some results illustrate important aspects and interesting research opportunities.

The purpose of this paper is to report an inter‐disciplinary experience in building a context‐aware system that provides adapted functionalities to inhabitants of a smart home. The paper focuses on the management of uncertainty that is intrinsic to pervasive computing systems.

The paper presents the principles that characterize the context‐aware architecture: the acceptability‐driven design, where privacy and acceptability are favored; the awareness of the gap between the reality of human activity and the capabilities of the capture process; the step‐by‐step abstraction of contextual information; the management of uncertainty imprecision and ignorance at individual‐ and cross‐layer levels. The paper presents the principles and describes the system architecture, focusing on the management of uncertainty.

The authors built a layered architecture that manages and propagates uncertainty, imprecision and ignorance, allowing the recognition of ambiguous contexts and the provision of adapted functionalities. The paper illustrates this architecture and an application leveraging it.

Future work will investigate the exploitation of feedback mechanisms and the recognition of context dynamics. These improvements will allow resolving inconsistencies and ambiguities in context information and improving the provision of functionalities in situations characterized by temporal developments.

The research aims at realizing the long‐term vision of smart homes that provide adapted functionalities to inhabitants: saving energy and improving comfort and quality of domestic life.

The paper introduces some principles that can be considered when designing a context‐aware system and presents an architecture that follows those principles. Researchers in the smart home and pervasive computing domains may consider this paper when designing their context‐aware architectures.