Age, technology prior experience and ease of use: Who's doing what?

Designers often assume that their users will have some digital technological prior experience. We examined these levels of prior experience by surveying frequency and ease of technology use with a range of technology products. 362 people participated as part of a UK nationwide larger survey of people's capabilities and characteristics to inform product design. We found that frequency and self-reported ease of use are indeed correlated for all of the products. Furthermore, both frequency and ease of use declined significantly with age for most of the products. In fact, 29% of the over 65s had never or rarely used any of the products, except for digital TV. We conclude that interfaces need to be designed carefully to avoid implicit assumptions about users' previous technology use.

Primary students’ interpretation of maps : gesture use and mapping knowledge

Maps are used to represent three-dimensional space and are integral to a range of everyday experiences. They are increasingly used in mathematics, being prominent both in school curricula and as a form of assessing students understanding of mathematics ideas. In order to successfully interpret maps, students need to be able to understand that maps: represent space, have their own perspective and scale, and their own set of symbols and texts. Despite the fact that maps have an increased prevalence in society and school, there is evidence to suggest that students have difficulty interpreting maps. This study investigated 43 primary-aged students’ (aged 9-12 years) verbal and gestural behaviours as they engaged with and solved map tasks. Within a multiliteracies framework that focuses on spatial, visual, linguistic, and gestural elements, the study investigated how students interpret map tasks. Specifically, the study sought to understand students’ skills and approaches used to solving map tasks and the gestural behaviours they utilised as they engaged with map tasks. The investigation was undertaken using the Knowledge Discovery in Data (KDD) design. The design of this study capitalised on existing research data to carry out a more detailed analysis of students’ interpretation of map tasks. Video data from an existing data set was reorganised according to two distinct episodes—Task Solution and Task Explanation—and analysed within the multiliteracies framework. Content Analysis was used with these data and through anticipatory data reduction techniques, patterns of behaviour were identified in relation to each specific map task by looking at task solution, task correctness and gesture use. The findings of this study revealed that students had a relatively sound understanding of general mapping knowledge such as identifying landmarks, using keys, compass points and coordinates. However, their understanding of mathematical concepts pertinent to map tasks including location, direction, and movement were less developed. Successful students were able to interpret the map tasks and apply relevant mathematical understanding to navigate the spatial demands of the map tasks while the unsuccessful students were only able to interpret and understand basic map conventions. In terms of their gesture use, the more difficult the task, the more likely students were to exhibit gestural behaviours to solve the task. The most common form of gestural behaviour was deictic, that is a pointing gesture. Deictic gestures not only aided the students capacity to explain how they solved the map tasks but they were also a tool which assisted them to navigate and monitor their spatial movements when solving the tasks. There were a number of implications for theory, learning and teaching, and test and curriculum design arising from the study. From a theoretical perspective, the findings of the study suggest that gesturing is an important element of multimodal engagement in mapping tasks. In terms of teaching and learning, implications include the need for students to utilise gesturing techniques when first faced with new or novel map tasks. As students become more proficient in solving such tasks, they should be encouraged to move beyond a reliance on such gesture use in order to progress to more sophisticated understandings of map tasks. Additionally, teachers need to provide students with opportunities to interpret and attend to multiple modes of information when interpreting map tasks.

Re-use of domain knowledge to provide confidence for adoption of off-site manufacturing for construction in Australia

Many construction industry decision-makers believe there is a lack of off-site manufacture (OSM) adoption for non-residential construction in Australia. Identification of construction business process was considered imperative in order to assist decision-makers to increase OSM utilisation. The premise that domain knowledge can be re-used to provide an intervention point in the construction process led a team of researchers to construct simple base-line process models for the complete construction process, segmented into six phases. Sixteen domain knowledge industry experts were asked to review the construction phase base-line models to answer the question “Where in the process illustrated by this base-line model phase is an OSM task?”. Through an iterative and generative process a number of off-site manufacture intervention points were identified and integrated into the process models. The re-use of industry expert domain knowledge provided suggestions for new ways to do basic tasks thus facilitating changes to current practice. It is expected that implementation of the new processes will lead to systemic industry change and thus a growth in productivity due to increased adoption of OSM.

Effects of providing prior experience of a feedlot environment on the performance of feedlot cattle

Cattle sourced for feedlots from extensive properties will generally have little experience of conditions to which they will be exposed in feedlots, eg close contact with humans, confinement, crowding and feed in troughs. Such conditions can result in stress (Fell 1994) which can have adverse effects on health and performance (Moberg 1985). This experiment determined the effect of prior exposure to aspects of a feedlot environment on the feedlot performance of Bos indicus steers. 21st Biennial Conference. 8 - 12 July 1996. University of Queensland. Brisbane.

Facets of prior experience and the effectiveness of inclusive design

Research in inclusive design has shown the importance of prior experience for the usability of interactive products. Prior experience, however, is an ill-defined and inconsistently used construct. A number of different definitions and operationalisations of experience exist, but the differing power of these operationalisations to predict the usability of products for older users has rarely been investigated systematically. This study seeks to fill that gap. It is argued that the construct of experience has at least three components. It is proposed that two of these components, exposure and competence, are directly relevant for the current discussion about prior experience in inclusive design and that they can predict to different degrees the usability of a product for older users. In an empirical study, these facets of expertise are each operationalised on three levels of specificity and their impact on usability is assessed. The results show that measures of competence predict usability variables more strongly than measures of exposure and that levels of medium and high specificity are the best predictors. The application of inclusive design principles to a redesigned version of a ticket vending machine-although not resulting in a difference of overall usability-changed the impact of prior experience on usability measures implying an enhanced inclusiveness of the redesign with regard to prior experience. The implications of these findings for the effectiveness of inclusive design for older users are discussed. © 2013 Springer-Verlag Berlin Heidelberg.

A Computational Model for the Acquisition and Use of Phonological Knowledge

Does knowledge of language consist of symbolic rules? How do children learn and use their linguistic knowledge? To elucidate these questions, we present a computational model that acquires phonological knowledge from a corpus of common English nouns and verbs. In our model the phonological knowledge is encapsulated as boolean constraints operating on classical linguistic representations of speech sounds in term of distinctive features. The learning algorithm compiles a corpus of words into increasingly sophisticated constraints. The algorithm is incremental, greedy, and fast. It yields one-shot learning of phonological constraints from a few examples. Our system exhibits behavior similar to that of young children learning phonological knowledge. As a bonus the constraints can be interpreted as classical linguistic rules. The computational model can be implemented by a surprisingly simple hardware mechanism. Our mechanism also sheds light on a fundamental AI question: How are signals related to symbols?