Investigating assistive technology to support memory for people with cognitive impairments

Technologies such as automobiles or mobile phones allow us to perform beyond our physical capabilities and travel faster or communicate over long distances. Technologies such as computers and calculators can also help us perform beyond our mental capabilities by storing and manipulating information that we would be unable to process or remember. In recent years there has been a growing interest in assistive technology for cognition (ATC) which can help people compensate for cognitive impairments. The aim of this thesis was to investigate ATC for memory to help people with memory difficulties which impacts independent functioning during everyday life. Chapter one argues that using both neuropsychological and human computing interaction theory and approaches is crucial when developing and researching ATC. Chapter two describes a systematic review and meta-analysis of studies which tested technology to aid memory for groups with ABI, stroke or degenerative disease. Good evidence was found supporting the efficacy of prompting devices which remind the user about a future intention at a set time. Chapter three looks at the prevalence of technologies and memory aids in current use by people with ABI and dementia and the factors that predicted this use. Pre-morbid use of technology, current use of non-tech aids and strategies and age (ABI group only) were the best predictors of this use. Based on the results, chapter four focuses on mobile phone based reminders for people with ABI. Focus groups were held with people with memory impairments after ABI and ABI caregivers (N=12) which discussed the barriers to uptake of mobile phone based reminding. Thematic analysis revealed six key themes that impact uptake of reminder apps; Perceived Need, Social Acceptability, Experience/Expectation, Desired Content and Functions, Cognitive Accessibility and Sensory/Motor Accessibility. The Perceived need theme described the difficulties with insight, motivation and memory which can prevent people from initially setting reminders on a smartphone. Chapter five investigates the efficacy and acceptability of unsolicited prompts (UPs) from a smartphone app (ForgetMeNot) to encourage people with ABI to set reminders. A single-case experimental design study evaluated use of the app over four weeks by three people with severe ABI living in a post-acute rehabilitation hospital. When six UPs were presented through the day from ForgetMeNot, daily reminder-setting and daily memory task completion increased compared to when using the app without the UPs. Chapter six investigates another barrier from chapter 4 – cognitive and sensory accessibility. A study is reported which shows that an app with ‘decision tree’ interface design (ApplTree) leads to more accurate reminder setting performance with no compromise of speed or independence (amount of guidance required) for people with ABI (n=14) compared to a calendar based interface. Chapter seven investigates the efficacy of a wearable reminding device (smartwatch) as a tool for delivering reminders set on a smartphone. Four community dwelling participants with memory difficulties following ABI were included in an ABA single case experimental design study. Three of the participants successfully used the smartwatch throughout the intervention weeks and these participants gave positive usability ratings. Two participants showed improved memory performance when using the smartwatch and all participants had marked decline in memory performance when the technology was removed. Chapter eight is a discussion which highlights the implications of these results for clinicians, researchers and designers.

4th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes

This is the fourth TAProViz workshop being run at the 13th International Conference on Business Process Management (BPM). The intention this year is to consolidate on the results of the previous successful workshops by further developing this important topic, identifying the key research topics of interest to the BPM visualization community. Towards this goal, the workshop topics were extended to human computer interaction and related domains. Submitted papers were evaluated by at least three program committee members, in a double blind manner, on the basis of significance, originality, technical quality and exposition. Three full and one position papers were accepted for presentation at the workshop. In addition, we invited a keynote speaker, Jakob Pinggera, a postdoctoral researcher at the Business Process Management Research Cluster at the University of Innsbruck, Austria.

Grounding human vocabulary in robot perception through interaction

This thesis addresses the problem of word learning in computational agents. The motivation behind this work lies in the need to support language-based communication between service robots and their human users, as well as grounded reasoning using symbols relevant for the assigned tasks. The research focuses on the problem of grounding human vocabulary in robotic agent’s sensori-motor perception. Words have to be grounded in bodily experiences, which emphasizes the role of appropriate embodiments. On the other hand, language is a cultural product created and acquired through social interactions. This emphasizes the role of society as a source of linguistic input. Taking these aspects into account, an experimental scenario is set up where a human instructor teaches a robotic agent the names of the objects present in a visually shared environment. The agent grounds the names of these objects in visual perception. Word learning is an open-ended problem. Therefore, the learning architecture of the agent will have to be able to acquire words and categories in an openended manner. In this work, four learning architectures were designed that can be used by robotic agents for long-term and open-ended word and category acquisition. The learning methods used in these architectures are designed for incrementally scaling-up to larger sets of words and categories. A novel experimental evaluation methodology, that takes into account the openended nature of word learning, is proposed and applied. This methodology is based on the realization that a robot’s vocabulary will be limited by its discriminatory capacity which, in turn, depends on its sensors and perceptual capabilities. An extensive set of systematic experiments, in multiple experimental settings, was carried out to thoroughly evaluate the described learning approaches. The results indicate that all approaches were able to incrementally acquire new words and categories. Although some of the approaches could not scale-up to larger vocabularies, one approach was shown to learn up to 293 categories, with potential for learning many more.

Contributions to the contextualization of human-machine spoken interaction systems

The design and development of spoken interaction systems has been a thoroughly studied research scope for the last decades. The aim is to obtain systems with the ability to interact with human agents with a high degree of naturalness and efficiency, allowing them to carry out the actions they desire using speech, as it is the most natural means of communication between humans. To achieve that degree of naturalness, it is not enough to endow systems with the ability to accurately understand the user’s utterances and to properly react to them, even considering the information provided by the user in his or her previous interactions. The system has also to be aware of the evolution of the conditions under which the interaction takes place, in order to act the most coherent way as possible at each moment. Consequently, one of the most important features of the system is that it has to be context-aware. This context awareness of the system can be reflected in the modification of the behaviour of the system taking into account the current situation of the interaction. For instance, the system should decide which action it has to carry out, or the way to perform it, depending on the user that requests it, on the way that the user addresses the system, on the characteristics of the environment in which the interaction takes place, and so on. In other words, the system has to adapt its behaviour to these evolving elements of the interaction. Moreover that adaptation has to be carried out, if possible, in such a way that the user: i) does not perceive that the system has to make any additional effort, or to devote interaction time to perform tasks other than carrying out the requested actions, and ii) does not have to provide the system with any additional information to carry out the adaptation, which could imply a lesser efficiency of the interaction, since users should devote several interactions only to allow the system to become adapted. In the state-of-the-art spoken dialogue systems, researchers have proposed several disparate strategies to adapt the elements of the system to different conditions of the interaction (such as the acoustic characteristics of a specific user’s speech, the actions previously requested, and so on). Nevertheless, to our knowledge there is not any consensus on the procedures to carry out these adaptation. The approaches are to an extent unrelated from one another, in the sense that each one considers different pieces of information, and the treatment of that information is different taking into account the adaptation carried out. In this regard, the main contributions of this Thesis are the following ones: Definition of a contextualization framework. We propose a unified approach that can cover any strategy to adapt the behaviour of a dialogue system to the conditions of the interaction (i.e. the context). In our theoretical definition of the contextualization framework we consider the system’s context as all the sources of variability present at any time of the interaction, either those ones related to the environment in which the interaction takes place, or to the human agent that addresses the system at each moment. Our proposal relies on three aspects that any contextualization approach should fulfill: plasticity (i.e. the system has to be able to modify its behaviour in the most proactive way taking into account the conditions under which the interaction takes place), adaptivity (i.e. the system has also to be able to consider the most appropriate sources of information at each moment, both environmental and user- and dialogue-dependent, to effectively adapt to the conditions aforementioned), and transparency (i.e. the system has to carry out the contextualizaton-related tasks in such a way that the user neither perceives them nor has to do any effort in providing the system with any information that it needs to perform that contextualization). Additionally, we could include a generality aspect to our proposed framework: the main features of the framework should be easy to adopt in any dialogue system, regardless of the solution proposed to manage the dialogue. Once we define the theoretical basis of our contextualization framework, we propose two cases of study on its application in a spoken dialogue system. We focus on two aspects of the interaction: the contextualization of the speech recognition models, and the incorporation of user-specific information into the dialogue flow. One of the modules of a dialogue system that is more prone to be contextualized is the speech recognition system. This module makes use of several models to emit a recognition hypothesis from the user’s speech signal. Generally speaking, a recognition system considers two types of models: an acoustic one (that models each of the phonemes that the recognition system has to consider) and a linguistic one (that models the sequences of words that make sense for the system). In this work we contextualize the language model of the recognition system in such a way that it takes into account the information provided by the user in both his or her current utterance and in the previous ones. These utterances convey information useful to help the system in the recognition of the next utterance. The contextualization approach that we propose consists of a dynamic adaptation of the language model that is used by the recognition system. We carry out this adaptation by means of a linear interpolation between several models. Instead of training the best interpolation weights, we make them dependent on the conditions of the dialogue. In our approach, the system itself will obtain these weights as a function of the reliability of the different elements of information available, such as the semantic concepts extracted from the user’s utterance, the actions that he or she wants to carry out, the information provided in the previous interactions, and so on. One of the aspects more frequently addressed in Human-Computer Interaction research is the inclusion of user specific characteristics into the information structures managed by the system. The idea is to take into account the features that make each user different from the others in order to offer to each particular user different services (or the same service, but in a different way). We could consider this approach as a user-dependent contextualization of the system. In our work we propose the definition of a user model that contains all the information of each user that could be potentially useful to the system at a given moment of the interaction. In particular we will analyze the actions that each user carries out throughout his or her interaction. The objective is to determine which of these actions become the preferences of that user. We represent the specific information of each user as a feature vector. Each of the characteristics that the system will take into account has a confidence score associated. With these elements, we propose a probabilistic definition of a user preference, as the action whose likelihood of being addressed by the user is greater than the one for the rest of actions. To include the user dependent information into the dialogue flow, we modify the information structures on which the dialogue manager relies to retrieve information that could be needed to solve the actions addressed by the user. Usage preferences become another source of contextual information that will be considered by the system towards a more efficient interaction (since the new information source will help to decrease the need of the system to ask users for additional information, thus reducing the number of turns needed to carry out a specific action). To test the benefits of the contextualization framework that we propose, we carry out an evaluation of the two strategies aforementioned. We gather several performance metrics, both objective and subjective, that allow us to compare the improvements of a contextualized system against the baseline one. We will also gather the user’s opinions as regards their perceptions on the behaviour of the system, and its degree of adaptation to the specific features of each interaction. Resumen El diseño y el desarrollo de sistemas de interacción hablada ha sido objeto de profundo estudio durante las pasadas décadas. El propósito es la consecución de sistemas con la capacidad de interactuar con agentes humanos con un alto grado de eficiencia y naturalidad. De esta manera, los usuarios pueden desempeñar las tareas que deseen empleando la voz, que es el medio de comunicación más natural para los humanos. A fin de alcanzar el grado de naturalidad deseado, no basta con dotar a los sistemas de la abilidad de comprender las intervenciones de los usuarios y reaccionar a ellas de manera apropiada (teniendo en consideración, incluso, la información proporcionada en previas interacciones). Adicionalmente, el sistema ha de ser consciente de las condiciones bajo las cuales transcurre la interacción, así como de la evolución de las mismas, de tal manera que pueda actuar de la manera más coherente en cada instante de la interacción. En consecuencia, una de las características primordiales del sistema es que debe ser sensible al contexto. Esta capacidad del sistema de conocer y emplear el contexto de la interacción puede verse reflejada en la modificación de su comportamiento debida a las características actuales de la interacción. Por ejemplo, el sistema debería decidir cuál es la acción más apropiada, o la mejor manera de llevarla a término, dependiendo del usuario que la solicita, del modo en el que lo hace, etcétera. En otras palabras, el sistema ha de adaptar su comportamiento a tales elementos mutables (o dinámicos) de la interacción. Dos características adicionales son requeridas a dicha adaptación: i) el usuario no ha de percibir que el sistema dedica recursos (temporales o computacionales) a realizar tareas distintas a las que aquél le solicita, y ii) el usuario no ha de dedicar esfuerzo alguno a proporcionar al sistema información adicional para llevar a cabo la interacción. Esto último implicaría una menor eficiencia de la interacción, puesto que los usuarios deberían dedicar parte de la misma a proporcionar información al sistema para su adaptación, sin ningún beneficio inmediato. En los sistemas de diálogo hablado propuestos en la literatura, se han propuesto diferentes estrategias para llevar a cabo la adaptación de los elementos del sistema a las diferentes condiciones de la interacción (tales como las características acústicas del habla de un usuario particular, o a las acciones a las que se ha referido con anterioridad). Sin embargo, no existe una estrategia fija para proceder a dicha adaptación, sino que las mismas no suelen guardar una relación entre sí. En este sentido, cada una de ellas tiene en cuenta distintas fuentes de información, la cual es tratada de manera diferente en función de las características de la adaptación buscada. Teniendo en cuenta lo anterior, las contribuciones principales de esta Tesis son las siguientes: Definición de un marco de contextualización. Proponemos un criterio unificador que pueda cubrir cualquier estrategia de adaptación del comportamiento de un sistema de diálogo a las condiciones de la interacción (esto es, el contexto de la misma). En nuestra definición teórica del marco de contextualización consideramos el contexto del sistema como todas aquellas fuentes de variabilidad presentes en cualquier instante de la interacción, ya estén relacionadas con el entorno en el que tiene lugar la interacción, ya dependan del agente humano que se dirige al sistema en cada momento. Nuestra propuesta se basa en tres aspectos que cualquier estrategia de contextualización debería cumplir: plasticidad (es decir, el sistema ha de ser capaz de modificar su comportamiento de la manera más proactiva posible, teniendo en cuenta las condiciones en las que tiene lugar la interacción), adaptabilidad (esto es, el sistema ha de ser capaz de considerar la información oportuna en cada instante, ya dependa del entorno o del usuario, de tal manera que adecúe su comportamiento de manera eficaz a las condiciones mencionadas), y transparencia (que implica que el sistema ha de desarrollar las tareas relacionadas con la contextualización de tal manera que el usuario no perciba la manera en que dichas tareas se llevan a cabo, ni tampoco deba proporcionar al sistema con información adicional alguna). De manera adicional, incluiremos en el marco propuesto el aspecto de la generalidad: las características del marco de contextualización han de ser portables a cualquier sistema de diálogo, con independencia de la solución propuesta en los mismos para gestionar el diálogo. Una vez hemos definido las características de alto nivel de nuestro marco de contextualización, proponemos dos estrategias de aplicación del mismo a un sistema de diálogo hablado. Nos centraremos en dos aspectos de la interacción a adaptar: los modelos empleados en el reconocimiento de habla, y la incorporación de información específica de cada usuario en el flujo de diálogo. Uno de los módulos de un sistema de diálogo más susceptible de ser contextualizado es el sistema de reconocimiento de habla. Este módulo hace uso de varios modelos para generar una hipótesis de reconocimiento a partir de la señal de habla. En general, un sistema de reconocimiento emplea dos tipos de modelos: uno acústico (que modela cada uno de los fonemas considerados por el reconocedor) y uno lingüístico (que modela las secuencias de palabras que tienen sentido desde el punto de vista de la interacción). En este trabajo contextualizamos el modelo lingüístico del reconocedor de habla, de tal manera que tenga en cuenta la información proporcionada por el usuario, tanto en su intervención actual como en las previas. Estas intervenciones contienen información (semántica y/o discursiva) que puede contribuir a un mejor reconocimiento de las subsiguientes intervenciones del usuario. La estrategia de contextualización propuesta consiste en una adaptación dinámica del modelo de lenguaje empleado en el reconocedor de habla. Dicha adaptación se lleva a cabo mediante una interpolación lineal entre diferentes modelos. En lugar de entrenar los mejores pesos de interpolación, proponemos hacer los mismos dependientes de las condiciones actuales de cada diálogo. El propio sistema obtendrá estos pesos como función de la disponibilidad y relevancia de las diferentes fuentes de información disponibles, tales como los conceptos semánticos extraídos a partir de la intervención del usuario, o las acciones que el mismo desea ejecutar. Uno de los aspectos más comúnmente analizados en la investigación de la Interacción Persona-Máquina es la inclusión de las características específicas de cada usuario en las estructuras de información empleadas por el sistema. El objetivo es tener en cuenta los aspectos que diferencian a cada usuario, de tal manera que el sistema pueda ofrecer a cada uno de ellos el servicio más apropiado (o un mismo servicio, pero de la manera más adecuada a cada usuario). Podemos considerar esta estrategia como una contextualización dependiente del usuario. En este trabajo proponemos la definición de un modelo de usuario que contenga toda la información relativa a cada usuario, que pueda ser potencialmente utilizada por el sistema en un momento determinado de la interacción. En particular, analizaremos aquellas acciones que cada usuario decide ejecutar a lo largo de sus diálogos con el sistema. Nuestro objetivo es determinar cuáles de dichas acciones se convierten en las preferencias de cada usuario. La información de cada usuario quedará representada mediante un vector de características, cada una de las cuales tendrá asociado un valor de confianza. Con ambos elementos proponemos una definición probabilística de una preferencia de uso, como aquella acción cuya verosimilitud es mayor que la del resto de acciones solicitadas por el usuario. A fin de incluir la información dependiente de usuario en el flujo de diálogo, llevamos a cabo una modificación de las estructuras de información en las que se apoya el gestor de diálogo para recuperar información necesaria para resolver ciertos diálogos. En dicha modificación las preferencias de cada usuario pasarán a ser una fuente adicional de información contextual, que será tenida en cuenta por el sistema en aras de una interacción más eficiente (puesto que la nueva fuente de información contribuirá a reducir la necesidad del sistema de solicitar al usuario información adicional, dando lugar en consecuencia a una reducción del número de intervenciones necesarias para llevar a cabo una acción determinada). Para determinar los beneficios de las aplicaciones del marco de contextualización propuesto, llevamos a cabo una evaluación de un sistema de diálogo que incluye las estrategias mencionadas. Hemos recogido diversas métricas, tanto objetivas como subjetivas, que nos permiten determinar las mejoras aportadas por un sistema contextualizado en comparación con el sistema sin contextualizar. De igual manera, hemos recogido las opiniones de los participantes en la evaluación acerca de su percepción del comportamiento del sistema, y de su capacidad de adaptación a las condiciones concretas de cada interacción.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

The theory of environment.

Contains errata slip.

Designing interaction for local communications : an urban screen study

This paper discusses the ongoing design and use of a digital community noticeboard situated in a suburban hub. The design intention is to engage residents, collect and display local information and communications, and spark discussion. A key contribution is an understanding of Situated Display navigation that aids retrieval from a long-term collection created by and for suburban community, and engaging qualities of this collection.

Mineralized human primary osteoblast matrices as a model system to analyse interactions of prostate cancer cells with the bone microenvironment

Prostate cancer metastasis is reliant on the reciprocal interactions between cancer cells and the bone niche/micro-environment. The production of suitable matrices to study metastasis, carcinogenesis and in particular prostate cancer/bone micro-environment interaction has been limited to specific protein matrices or matrix secreted by immortalised cell lines that may have undergone transformation processes altering signaling pathways and modifying gene or receptor expression. We hypothesize that matrices produced by primary human osteoblasts are a suitable means to develop an in vitro model system for bone metastasis research mimicking in vivo conditions. We have used a decellularized matrix secreted from primary human osteoblasts as a model for prostate cancer function in the bone micro-environment. We show that this collagen I rich matrix is of fibrillar appearance, highly mineralized, and contains proteins, such as osteocalcin, osteonectin and osteopontin, and growth factors characteristic of bone extracellular matrix (ECM). LNCaP and PC3 cells grown on this matrix, adhere strongly, proliferate, and express markers consistent with a loss of epithelial phenotype. Moreover, growth of these cells on the matrix is accompanied by the induction of genes associated with attachment, migration, increased invasive potential, Ca2+ signaling and osteolysis. In summary, we show that growth of prostate cancer cells on matrices produced by primary human osteoblasts mimics key features of prostate cancer bone metastases and thus is a suitable model system to study the tumor/bone micro-environment interaction in this disease.

Lift@Weimar : sustainable interaction with food, technology, and the city (Workshop)

This workshop explores innovative approaches to understanding and cultivating sustainable food culture in urban environments via human-computer-interaction (HCI) design and ubiquitous technologies. We perceive the city as an intersecting network of people, place, and technology in constant transformation. Our 2009 OZCHI workshop, Hungry 24/7? HCI Design for Sustainable Food Culture, opened a new space for discussion on this intersection amongst researchers and practitioners from diverse backgrounds including academia, government, industry, and non-for-profit organisations. Building on the past success, this new instalment of the workshop series takes a more refined view on mobile human-food interaction and the role of interactive media in engaging citizens to cultivate more sustainable everyday human-food interactions on the go. Interactive media in this sense is distributed, pervasive, and embedded in the city as a network. The workshop addresses environmental, health, and social domains of sustainability by bringing together insights across disciplines to discuss conceptual and design approaches in orchestrating mobility and interaction of people and food in the city as a network of people, place, technology, and food.

Modelling the activation of words in human memory : the spreading activation, spooky-activation-at-a-distance and the entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. The spreading activation, spooky-action-at-a-distance and entanglement models have all been used to model the activation of a word. Recently a hypothesis was put forward that the mean activation levels of the respective models are as follows: Spreading � Entanglment � Spooking-action-at-a-distance This article investigates this hypothesis by means of a substantial empirical analysis of each model using the University of South Florida word association, rhyme and word norms.

Negotiation theory and application in the business environment

This chapter introduces different theoretical approaches to negotiation and provides an explanation of these differing frameworks. While the action of a negotiation centres on the background research undertaken and what happens at the negotiation table, there is a need to know what principles and assumptions are informing these activities. Theories offer a way of understanding the underlying structures, processes and relationships of negotiation. Further, negotiation theories also assist with focusing attention on the 'basis of the bargain' and provide a standpoint from which to judge offers and counter-offers during the negotiation.

Eat Cook Grow : Mixing Human-Computer Interactions with Human-Food Interactions

Food has been a major agenda in political, socio-cultural, and environmental domains throughout history. The significance of food has been particularly highlighted in recent years with the growing public awareness of the unfolding impacts of climate change, challenging our understanding, practice, and expectations of our relationship with food. Parallel to this development has been the rise of web applications such as blogs, wikis, video and photo sharing sites, and social networking systems that are arguably more open, collaborative, and personalisable. These so-called ‘Web 2.0’ technologies have contributed to a more participatory Internet experience than what had previously been possible. An increasing number of these social applications are now available on mobile technologies where they take advantage of device-specific features such as sensors, location and context awareness, further expanding potential for the culture of participation and creativity. This international volume assembles a diverse collection of book chapters that contribute towards exploring and better understanding the opportunities and challenges provided by tools, interfaces, methods, and practices of social and mobile technology to enable engagement with people and creativity in the domain of food in contemporary society. It brings together an international group of academics and practitioners from a diverse range of disciplines such as computing and engineering, social sciences, digital media and human-computer interaction to critically examine a range of applications of social and mobile technology, such as social networking, mobile interaction, wikis, twitter, blogging, mapping, shared displays and urban screens, and their impact to foster a better understanding and practice of environmentally, socio-culturally, economically, and health-wise sustainable food culture.

A cross-discipline and collaborative approach to identifying the predictors of environmentally friendly and health protective behaviour

Background. As a society, our interaction with the environment is having a negative impact on human health. For example, an increase in car use for short trips, over walking or cycling, has contributed to an increase in obesity, diabetes and poor heart health and also contributes to pollution, which is associated with asthma and other respiratory diseases. In order to change the nature of that interaction, to be more positive and healthy, it is recommended that individuals adopt a range of environmentally friendly behaviours (such as walking for transport and reducing the use of plastics). Effective interventions aimed at increasing such behaviours will need to be evidence based and there is a need for the rapid communication of information from the point of research, into policy and practice. Further, a number of health disciplines, including psychology and public health, share a common mission to promote health and well-being. Therefore, the objective of this project is to take a cross-discipline and collaborative approach to reveal psychological mechanisms driving environmentally friendly behaviour. This objective is further divided into three broad aims, the first of which is to take a cross-discipline and collaborative approach to research. The second aim is to explore and identify the salient beliefs which most strongly predict environmentally friendly behaviour. The third aim is to build an augmented model to explain environmentally friendly behaviour. The thesis builds on the understanding that an interdisciplinary collaborative approach will facilitate the rapid transfer of knowledge to inform behaviour change interventions. Methods. The application of this approach involved two surveys which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in collaboration with an expert panel comprising academics, industry professionals and government representatives, a self-administered, Theory of Planned Behaviour (TPB) based, mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay Region (Queensland, Australia). This survey explored specific beliefs including attitudes, norms, perceived control, intention and behaviour, as well as environmental altruism and green identity, in relation to walking for transport and switching off lights when not in use. Following analysis of the mail survey data and based on feedback from participants and key stakeholders, an internet survey was employed (N=451) to explore two additional behaviours, switching off appliances at the wall when not in use, and shopping with reusable bags. This work is presented as a series of interrelated publications which address each of the research aims. Presentation of Findings. Chapter five of this thesis consists of a published paper which addresses the first aim of the research and outlines the collaborative and multidisciplinary approach employed in the mail survey. The paper argued that forging alliances with those who are in a position to immediately utilise the findings of research has the potential to improve the quality and timely communication of research. Illustrating this timely communication, Chapter six comprises a report presented to Moreton Bay Regional Council (MBRC). This report addresses aim's one and two. The report contains a summary of participation in a range of environmentally friendly behaviours and identifies the beliefs which most strongly predicted walking for transport and switching off lights (from the mail survey). These salient beliefs were then recommended as targets for interventions and included: participants believing that they might save money; that their neighbours also switch off lights; that it would be inconvenient to walk for transport and that their closest friend also walks for transport. Chapter seven also addresses the second aim and presents a published conference paper in which the salient beliefs predicting the four specified behaviours (from both surveys) are identified and potential applications for intervention are discussed. Again, a range of TPB based beliefs, including descriptive normative beliefs, were predictive of environmentally friendly behaviour. This paper was also provided to MBRC, along with recommendations for applying the findings. For example, as descriptive normative beliefs were consistently correlated with environmentally friendly behaviour, local councils could engage in marketing and interventions (workshops, letter box drops, internet promotions) which encourage parents and friends to model, rather than simply encourage, environmentally friendly behaviour. The final two papers, presented in Chapters eight and nine, addresses the third aim of the project. These papers each present two behaviours together to inform a TPB based theoretical model with which to predict environmentally friendly behaviour. A generalised model is presented, which is found to predict the four specific behaviours under investigation. The role of demographics was explored across each of the behaviour specific models. It was found that some behaviour's differ by age, gender, income or education. In particular, adjusted models predicted more of the variance in walking for transport amongst younger participants and females. Adjusted models predicted more variance in switching off lights amongst those with a bachelor degree or higher and predicted more variance in switching off appliances amongst those on a higher income. Adjusted models predicted more variance in shopping with reusable bags for males, people 40 years or older, those on a higher income and those with a bachelor degree or higher. However, model structure and general predictability was relatively consistent overall. The models provide a general theoretical framework from which to better understand the motives and predictors of environmentally friendly behaviour. Conclusion. This research has provided an example of the benefits of a collaborative interdisciplinary approach. It has identified a number of salient beliefs which can be targeted for social marketing campaigns and educational initiatives; and these findings, along with recommendations, have been passed on to a local council to be used as part of their ongoing community engagement programs. Finally, the research has informed a practical model, as well as behaviour specific models, for predicting sustainable living behaviours. Such models can highlight important core constructs from which targeted interventions can be designed. Therefore, this research represents an important step in undertaking collaborative approaches to improving population health through human-environment interactions.

Technological tools for science classrooms : choosing and using for productive and sustainable teaching and learning experiences

In this age of rapidly evolving technology, teachers are encouraged to adopt ICTs by government, syllabus, school management, and parents. Indeed, it is an expectation that teachers will incorporate technologies into their classroom teaching practices to enhance the learning experiences and outcomes of their students. In particular, regarding the science classroom, a subject that traditionally incorporates hands-on experiments and practicals, the integration of modern technologies should be a major feature. Although myriad studies report on technologies that enhance students’ learning outcomes in science, there is a dearth of literature on how teachers go about selecting technologies for use in the science classroom. Teachers can feel ill prepared to assess the range of available choices and might feel pressured and somewhat overwhelmed by the avalanche of new developments thrust before them in marketing literature and teaching journals. The consequences of making bad decisions are costly in terms of money, time and teacher confidence. Additionally, no research to date has identified what technologies science teachers use on a regular basis, and whether some purchased technologies have proven to be too problematic, preventing their sustained use and possible wider adoption. The primary aim of this study was to provide research-based guidance to teachers to aid their decision-making in choosing technologies for the science classroom. The study unfolded in several phases. The first phase of the project involved survey and interview data from teachers in relation to the technologies they currently use in their science classrooms and the frequency of their use. These data were coded and analysed using Grounded Theory of Corbin and Strauss, and resulted in the development of a PETTaL model that captured the salient factors of the data. This model incorporated usability theory from the Human Computer Interaction literature, and education theory and models such as Mishra and Koehler’s (2006) TPACK model, where the grounded data indicated these issues. The PETTaL model identifies Power (school management, syllabus etc.), Environment (classroom / learning setting), Teacher (personal characteristics, experience, epistemology), Technology (usability, versatility etc.,) and Learners (academic ability, diversity, behaviour etc.,) as fields that can impact the use of technology in science classrooms. The PETTaL model was used to create a Predictive Evaluation Tool (PET): a tool designed to assist teachers in choosing technologies, particularly for science teaching and learning. The evolution of the PET was cyclical (employing agile development methodology), involving repeated testing with in-service and pre-service teachers at each iteration, and incorporating their comments i ii in subsequent versions. Once no new suggestions were forthcoming, the PET was tested with eight in-service teachers, and the results showed that the PET outcomes obtained by (experienced) teachers concurred with their instinctive evaluations. They felt the PET would be a valuable tool when considering new technology, and it would be particularly useful as a means of communicating perceived value between colleagues and between budget holders and requestors during the acquisition process. It is hoped that the PET could make the tacit knowledge acquired by experienced teachers about technology use in classrooms explicit to novice teachers. Additionally, the PET could be used as a research tool to discover a teachers’ professional development needs. Therefore, the outcomes of this study can aid a teacher in the process of selecting educationally productive and sustainable new technology for their science classrooms. This study has produced an instrument for assisting teachers in the decision-making process associated with the use of new technologies for the science classroom. The instrument is generic in that it can be applied to all subject areas. Further, this study has produced a powerful model that extends the TPACK model, which is currently extensively employed to assess teachers’ use of technology in the classroom. The PETTaL model grounded in data from this study, responds to the calls in the literature for TPACK’s further development. As a theoretical model, PETTaL has the potential to serve as a framework for the development of a teacher’s reflective practice (either self evaluation or critical evaluation of observed teaching practices). Additionally, PETTaL has the potential for aiding the formulation of a teacher’s personal professional development plan. It will be the basis for further studies in this field.

Habituated interaction and social objects

In this position paper we draw from critical approaches to the concept of habit from cultural theory to argue that considering the sociality of everyday objects might be productive for understanding and designing for habituated interaction within the emerging Internet of Things.