This thesis investigates whether the use of hand-held technology affects motivation and learning in science. An innovative mixed methods approach was used to provide new insights into an emerging area of research. First, two pilot observational studies were conducted, which aimed to establish how a school currently uses hand held dataloggers, and gain further insight into how learners respond to this technology. This was followed by a primarily quantitative experiment that was concerned with the role of data ownership and the impact of ‘seams’ on the transformation process of the collected data. The results indicated that a hands-on experience increased confidence among students in explaining their own data, as opposed to data collected by someone else. A third study was designed to compare how student motivation and learning were affected when carrying out the same inquiry task either with or without the support of dataloggers. The results revealed no difference in accuracy or motivation for learning. The final, fourth, study was a longitudinal study designed in collaboration with a secondary science teacher, comparing three conditions: the inclusion of cameras to support student reflection, the inclusion of both cameras and the use of dataloggers to support teaching, and a control condition where the lessons were not changed. This study found that inclusion of dataloggers into modules led to increased assessment scores, while the use of cameras indicated that students are adept at taking relevant photos, and did not suffer from an extensive novelty effect. The results highlighted the importance of using a range of methods and tools for teaching students. The thesis concludes with recommendations and future research ideas, including exploring how data is visualised and the role of physical context. Of key importance is that future work is conducted in collaboration with educators in the wild.

<p>This project aims to describe how workflow systems can integrate and make use of context information from context rich environments, to enhance the execution of workflow processes. Context information can for example be used to control transitions between activities, activity enactment and process/activity coordination. A dynamic contextual environment also requires that a workflow system is capable of responding to contextual events. A set of requirements for a context-aware workflow system, based on existing workflow standards, theory behind context-aware computing and activity theory, will be presented and elaborated. Prototypes, which illustrate how these requirements can be implemented in a standard based workflow system, are also provided. Based on the solutions presented in the prototypes, a new interface for a workflow enactment service is presented. This new interface serves as the link between the contextual environment and the workflow system. We also present a solution for handling context related exception states. The definition of basic terms in workflow systems are expanded to better support context-aware behaviour. Ideas and solutions for more complex requirements not met in our prototypes are also discussed, such as situated activity coordination.</p>

<p>This paper intends to describe the work and result of the design project Meet App. Meet App lets users interact around their current locations in a direct manner. The user experience is evaluated to get an understanding of the usefulness and interaction with this type of design. The project is related to the context-awareness research field where findings put the project in a greater whole. The result indicates usefulness and enjoyment interacting with the application, but because of the low number of participants the findings cannot be validated.</p>

This project aims to describe how workflow systems can integrate and make use of context information from context rich environments, to enhance the execution of workflow processes. Context information can for example be used to control transitions between activities, activity enactment and process/activity coordination. A dynamic contextual environment also requires that a workflow system is capable of responding to contextual events. A set of requirements for a context-aware workflow system, based on existing workflow standards, theory behind context-aware computing and activity theory, will be presented and elaborated. Prototypes, which illustrate how these requirements can be implemented in a standard based workflow system, are also provided. Based on the solutions presented in the prototypes, a new interface for a workflow enactment service is presented. This new interface serves as the link between the contextual environment and the workflow system. We also present a solution for handling context related exception states. The definition of basic terms in workflow systems are expanded to better support context-aware behaviour. Ideas and solutions for more complex requirements not met in our prototypes are also discussed, such as situated activity coordination.

Modern context-aware applications no longer justify their decisions based only on their own information but on the decisions and information of other applications in a similar context.  Acquiring context information of other entities in an distributed system is difficult task when using the current content centric solutions such as DHTs.  This project aims to build a distributed index that provides storage for the so called Presentities solely based on the state of their context information.  Furthermore, the stored Presentities must be efficiently accessible even if only some information of their current context is available. To fulfill these requirements the PAST DHT was extended to support range queries and modified to use points on a space-filling curve as index values. The simulation of the system has shown very good accuracy rates, on average 99%, for range queries by maintaining a logarithmic relationship to the amount of required messages sent in the DHT.  Problems have emerged from the lack of load balancing implemented into the used DHT, but it is still the case that the proposed method of using space-filling curves to build a context centric decentralized index is both sufficient and effective. Keywords: context awareness, indexing, space-flling curves, Hilbert curve,Pastry, PAST

Pervasive computing is an important trend today. It concerns devices and services in a smart space that interact with users in a simple, natural, and harmonious way. Many problems in this domain have been studied from different perspectives in various projects. However, one important characteristic of pervasive computing, which is how to make it non-intrusive so that users can focus on their tasks, has received little formal attention. Nowadays, many computing entities including smart devices, and software components, are involved in our daily lives, and users need to deal with them as well as with other people. Besides, people are easy to reach with multiple devices. We believe there should be a systematic way to help users avoid intrusive ones. We propose a model for posing and answering two questions: will an interaction intrude on its receiver if delivered, and given that the interaction is deliverable, how can it be delivered effectively and not too overtly? With this model, the intrusion problem is analyzed and the essential factors are identified. A quantitative approach is used, so that factors have quantitative values for comparison and computation. We also apply context to refine them in order to achieve better results. We then illustrate how to materialize the model and build a system whose design is inspired by the Jabber framework that includes a collection of standards, technologies, and projects for instant messaging. The discussion is at a general level that does not depend on Jabber. However, by choosing Jabber in implementation, we reuse existing software and technologies, and benefit from Jabber/XMPP standardization, its low entry barrier for application developers, and its rich community support. The main contributions of our work are two-fold. First, we propose a model for intrusiveness in pervasive computing. Second, we address the problem at the system level by designing and realizing it. We also make use of standardized instant-messaging technologies, more precisely Jabber, in the system instantiation to reuse existing software, making the system more flexible and extensible.

This paper intends to describe the work and result of the design project Meet App. Meet App lets users interact around their current locations in a direct manner. The user experience is evaluated to get an understanding of the usefulness and interaction with this type of design. The project is related to the context-awareness research field where findings put the project in a greater whole. The result indicates usefulness and enjoyment interacting with the application, but because of the low number of participants the findings cannot be validated.

Pervasive computing is an important trend today. It concerns devices and services in a smart space that interact with users in a simple, natural, and harmonious way. Many problems in this domain have been studied from different perspectives in various projects. However, one important characteristic of pervasive computing, which is how to make it non-intrusive so that users can focus on their tasks, has received little formal attention. Nowadays, many computing entities including smart devices, and software components, are involved in our daily lives, and users need to deal with them as well as with other people. Besides, people are easy to reach with multiple devices. We believe there should be a systematic way to help users avoid intrusive ones. We propose a model for posing and answering two questions: will an interaction intrude on its receiver if delivered, and given that the interaction is deliverable, how can it be delivered effectively and not too overtly? With this model, the intrusion problem is analyzed and the essential factors are identified. A quantitative approach is used, so that factors have quantitative values for comparison and computation. We also apply context to refine them in order to achieve better results. We then illustrate how to materialize the model and build a system whose design is inspired by the Jabber framework that includes a collection of standards, technologies, and projects for instant messaging. The discussion is at a general level that does not depend on Jabber. However, by choosing Jabber in implementation, we reuse existing software and technologies, and benefit from Jabber/XMPP standardization, its low entry barrier for application developers, and its rich community support. The main contributions of our work are two-fold. First, we propose a model for intrusiveness in pervasive computing. Second, we address the problem at the system level by designing and realizing it. We also make use of standardized instant-messaging technologies, more precisely Jabber, in the system instantiation to reuse existing software, making the system more flexible and extensible.

Purpose: The purpose of our work is to develop a system for automatic contact tracing with the goal of identifying individuals who are most likely infected, even if we do not have direct diagnostic information on their health status. Control of the spread of respiratory pathogens (e.g. novel influenza viruses) in the population using vaccination is a challenging problem that requires quick identification of the infectious agent followed by large-scale production and administration of a vaccine. This takes a significant amount of time. A complementary approach to control transmission is contact tracing and quarantining, which are currently applied to sexually transmitted diseases (STDs). For STDs, identifying the contacts that might have led to disease transmission is relatively easy; however, for respiratory pathogens, the contacts that can lead to transmission include a huge number of face-to-face daily social interactions that are impossible to trace manually. Method: We developed a Bayesian network model to process context awareness proximity sensor information together with (possibly incomplete) diagnosis information to track the spread of disease in a population. Our model tracks real-time proximity contacts and can provide public health agencies with the probability of infection for each individual in the model. For testing our algorithm, we used a real-world mobile sensor dataset of 80 individuals, and we simulated an outbreak. Result: We ran several experiments where different sub-populations were ???infected??? and ???diagnosed.??? By using the contact information, our model was able to automatically identify individuals in the population who were likely to be infected even though they were not directly ???diagnosed??? with an illness. Conclusion: Automatic contact tracing for respiratory pathogens is a powerful idea, however we have identified several implementation challenges. The first challenge is scalability: we note that a contact tracing system with a hundred thousand individuals requires a Bayesian model with a billion nodes. Bayesian inference on models of this scale is an open problem and an active area of research. The second challenge is privacy protection: although the test data were collected in an academic setting, deploying any system will require appropriate safeguards for user privacy. Nonetheless, our work illustrates the potential for broader use of contact tracing for modelling and controlling disease transmission.

Mobile applications can benefit from increased awareness of the device's context. Unfortunately, existing solutions for inferring context require special purpose sensors or beacons on the mobile devices or in the physical environment. This requirement significantly limits the deployment of these solutions. In this thesis, I argue that mobile devices can infer a substantial amount of their context by leveraging their existing wireless interfaces to monitor ambient radio sources, such as GSM cell towers or WiFi access points. I focus on two important problems in context-aware computing: localization of mobile devices and detecting proximity between mobile devices for authentication purposes. Specifically, I present an accurate localization system based on fingerprinting of GSM signals. I show that the key to more accurate GSM localization is the use of wide signal strength fingerprints that include readings from a large number of base stations. Next, I present a method that addresses the key drawback of fingerprint-based localization systems - the need to collect extensive measurements to train the system in every target environment. Finally, I show how radio environment sensing can be used to secure the communication of devices that come within close proximity. Removing the need for additional hardware on the mobile devices and in the physical environment renders the approach that I present amenable for widespread deployment.