WalkNRide: contextualising feedback in physical activity trackers

Increasing levels of sedentarism and obesity, along with advances in sensor technologies have instigated a market for wearable activity trackers, electronic devices that sense users’ physical activity levels with the goals of self-monitoring and behaviour change. Nowadays, activity trackers are one of the most desirable technologies, making up for a market of over $230 million in 2013. However, despite the spike of users’ interest, activity trackers have been shown to lose their appeal over time, with a recent survey suggesting that one out of three users discard the tracker in the course of the first six months of use. The question we pose is: how can we design activity tracker so that users’ interests is sustained over the long term? Our design approach focuses on contextualising physical activity. We do this through sensing users’ locations and activities (such as being still, walking or commuting through a car, bus or other means) and thus providing innovative ways of presenting feedback on users. This thesis presents the design and evaluation of WalkNRide, a physical activity tracker for Google Android. Through a longitudinal field study of WalkNRide, we attempt to inquire into the factors that drive the adoption (or non-adoption) of the tool as well as the ways in which the use of the tool contributes towards habit formation.

New advances in aircraft MRO services: data mining enhancement

Aircraft Maintenance, Repair and Overhaul (MRO) agencies rely largely on row-data based quotation systems to select the best suppliers for the customers (airlines). The data quantity and quality becomes a key issue to determining the success of an MRO job, since we need to ensure we achieve cost and quality benchmarks. This paper introduces a data mining approach to create an MRO quotation system that enhances the data quantity and data quality, and enables significantly more precise MRO job quotations. Regular Expression was utilized to analyse descriptive textual feedback (i.e. engineer’s reports) in order to extract more referable highly normalised data for job quotation. A text mining based key influencer analysis function enables the user to proactively select sub-parts, defects and possible solutions to make queries more accurate. Implementation results show that system data would improve cost quotation in 40% of MRO jobs, would reduce service cost without causing a drop in service quality.

Improving aircraft maintenance, repair, and overhaul: A novel text mining approach

Aircraft Maintenance, Repair and Overhaul (MRO) feedback commonly includes an engineer’s complex text-based inspection report. Capturing and normalizing the content of these textual descriptions is vital to cost and quality benchmarking, and provides information to facilitate continuous improvement of MRO process and analytics. As data analysis and mining tools requires highly normalized data, raw textual data is inadequate. This paper offers a textual-mining solution to efficiently analyse bulk textual feedback data. Despite replacement of the same parts and/or sub-parts, the actual service cost for the same repair is often distinctly different from similar previously jobs. Regular expression algorithms were incorporated with an aircraft MRO glossary dictionary in order to help provide additional information concerning the reason for cost variation. Professional terms and conventions were included within the dictionary to avoid ambiguity and improve the outcome of the result. Testing results show that most descriptive inspection reports can be appropriately interpreted, allowing extraction of highly normalized data. This additional normalized data strongly supports data analysis and data mining, whilst also increasing the accuracy of future quotation costing. This solution has been effectively used by a large aircraft MRO agency with positive results.

Using textual analysis with Concept Inventories to identify root causes of misconceptions

Engineers must have deep and accurate conceptual understanding of their field and Concept inventories (CIs) are one method of assessing conceptual understanding and providing formative feedback. Current CI tests use Multiple Choice Questions (MCQ) to identify misconceptions and have undergone reliability and validity testing to assess conceptual understanding. However, they do not readily provide the diagnostic information about students’ reasoning and therefore do not effectively point to specific actions that can be taken to improve student learning. We piloted the textual component of our diagnostic CI on electrical engineering students using items from the signals and systems CI. We then analysed the textual responses using automated lexical analysis software to test the effectiveness of these types of software and interviewed the students regarding their experience using the textual component. Results from the automated text analysis revealed that students held both incorrect and correct ideas for certain conceptual areas and provided indications of student misconceptions. User feedback also revealed that the inclusion of the textual component is helpful to students in assessing and reflecting on their own understanding.

Digital oral feedback written assignments as professional learning for teacher educators : a collaborative self-study.

Allan Luke (2008) uses a “pedagogical economy where literacy education is taken as a cultural gift”. This paper reports on the digital oral feedback provided to pre-service teachers in a literacy unit and explores the pedagogical gift this feedback is to the teacher educators marking this work. Rather than mark their written work as individual lecturers, we collaboratively read the assignment and recorded the sound file of the conversation around each assignment. We then participated in another conversation with a critical friend, which enabled us to explore the impact of this form of assessment on our professional identities as teacher educators. We found these conversations provided a rich context for our professional learning about ourselves as teacher educators, as well as specific content knowledge we both brought to the teaching of this unit. We found we were working as a team to provide more in-depth feedback of the assessment criteria for each assignment than we did with written feedback. Through this dialogical feedback we were able to construct the pre-service teachers' assignments as an important textual gift in our collaborative professional learning about assessment, and in exploring our beliefs and practices as teacher educators.

Vocativos e o traço basicamente orientador da interação na Gramática Textual-Interativa

Within Textual-interactive Grammar, discourse markers are defined through a particular combination of linguistic features. One of them concerns the interactive role of discourse markers, and it is called “basic orientation of interaction”. As other authors have shown, this feature applies to expressions that play the following functions: Checking, Feedback, Injunction or Initiation. In this paper, we try to demonstrate that the feature under consideration also applies to Vocatives.

Semi-supervised learning for relevance feedback on image retrieval tasks

Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts required by these methods tend to increase as well, demanding approaches for reducing the need of user interactions. In this context, this paper proposes a semi-supervised learning algorithm for relevance feedback to be used in image retrieval tasks. The proposed semi-supervised algorithm aims at using both supervised and unsupervised approaches simultaneously. While a supervised step is performed using the information collected from the user feedback, an unsupervised step exploits the intrinsic dataset structure, which is represented in terms of ranked lists of images. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture descriptors and different datasets. The proposed approach was also evaluated on multimodal retrieval tasks, considering visual and textual descriptors. Experimental results demonstrate the effectiveness of the proposed approach.

Navigating 21st Century multimodal textual environments: a case study of digital literacy

In the 21st century young people live and learn in a technological world that is fast paced and in a constant state of change. As technology becomes more and more accessible outside of the classroom,educators are challenged to re-consider the literacy skills required to be successfully literate. Enacting literacy teaching and learning in and for the 21st century requires teachers to update their pedagogicalknowledge, skills and contextual understanding of the world children live and learn in. This chapter offers a brief overview of the Australian Curriculum, locating it within a 21st century learning discourse.The authors interpret and analyse one young student’s creation of a digital text in a movie modality. Attention is paid to how the case study teacher created meaningful digital literacy learning experiences and opportunities for children to create and interact in social, multimodal textual environments, both within and beyond the school.

Automated Feedback for 'Fill in the Gap' Programming Exercises

Timely feedback is a vital component in the learning process. It is especially important for beginner students in Information Technology since many have not yet formed an effective internal model of a computer that they can use to construct viable knowledge. Research has shown that learning efficiency is increased if immediate feedback is provided for students. Automatic analysis of student programs has the potential to provide immediate feedback for students and to assist teaching staff in the marking process. This paper describes a “fill in the gap” programming analysis framework which tests students’ solutions and gives feedback on their correctness, detects logic errors and provides hints on how to fix these errors. Currently, the framework is being used with the Environment for Learning to Programming (ELP) system at Queensland University of Technology (QUT); however, the framework can be integrated into any existing online learning environment or programming Integrated Development Environment (IDE)