A matrix factorization framework for jointly analyzing multiple nonnegative data sources

Nonnegative matrix factorization based methods provide one of the simplest and most effective approaches to text mining. However, their applicability is mainly limited to analyzing a single data source. In this chapter, we propose a novel joint matrix factorization framework which can jointly analyze multiple data sources by exploiting their shared and individual structures. The proposed framework is flexible to handle any arbitrary sharing configurations encountered in real world data. We derive an efficient algorithm for learning the factorization and show that its convergence is theoretically guaranteed. We demonstrate the utility and effectiveness of the proposed framework in two real-world applications—improving social media retrieval using auxiliary sources and cross-social media retrieval. Representing each social media source using their textual tags, for both applications, we show that retrieval performance exceeds the existing state-of-the-art techniques. The proposed solution provides a generic framework and can be applicable to a wider context in data mining wherever one needs to exploit mutual and individual knowledge present across multiple data sources.

Realising the potential: assessing professional learning through the integration of ePortfolios in Australian business education

This project will enable academic leadership of Australian Business and Management education programs to design into the curriculum, and best use, ePortfolios and associated technologies in assessing students' learning of highly valued professionally-based capabilities. The project will investigate and support the best ways of broadly and deeply embedding ePortfolios across entire undergraduate business and management education curricula. ePortfolios for enabling and assessing student learning is seen as a key means for integrating student learning across the curriculum and, therefore, creating a holistic learning experience. The project will work with Program Leaders across the sector through liaison with the Australian Business Deans Council (ABDC), Teaching and Learning Network to both draw in better practices and disseminate project findings as the project progresses through its key phases. These planned actions will lead to the progressive development of a Business Education ePortfolio Professional Learning Capabilities Assessment Framework.

Tackling disadvantage through student-centred learning - exploring 'Worlds of Work' in the Melbourne CBD

As the educational landscape increasingly mirrors deepening socio-economic cleavages within Australian society, the disparity in educational outcomes has been identified as one of the biggest challenges confronting secondary schooling. In contrast with most OECD countries, family background remains the most important determinant of educational achievement in Australia. More and more, schools are defined by location, reinforcing what has been dubbed the 'circular pattern of disadvantage'. At the same time, recognition of strong links between outcomes, socio economic status and location has elicited growing calls for systematic redefining of learning experiences and the public education framework. Focus on flexible, rigorous, community-oriented, person-centred learning opportunities has predicated multiple mentoring and youth schemes and has guided policy. Recognition of the need to re-engage Year 9 and 10 students underpinned development of VELS, for instance; it has also directed the programming priorities of Education Foundation Australia (EFA). This paper will discuss first, how schools perceive the programs have made a difference to both individual students and the curriculum offered in the schools, and second, how the experiences and activities provided through the program have changed the expectations and aspirations that many of the participants have in regard to how they perceive their future, their engagement with school and their careers. Both City Centre and Worlds of Work (WOW) program have received a very positive student response to real world activities that have demonstrably enhanced the development of reflective processes, interpersonal and social skills and social networks. Practical outcomes have included self-organised work experience, the development of mentor relationships and the re-engagement of some students with the schooling process. Interview data confirmed EFA's assessment that its programs have greatest impact when integrated into a school's curriculum rather than as "stand alone" electives.

Developement and evidencing achievement of graduate learning outcomes in Deakin University's enhanced mooc

There is now a plethora of Massive Open On-line courses (MOOCs) offered worldwide. Whilst many MOOCs focus on discipline-specific content, little attention has been paid to how MOOCs can explicitly help participants develop generic employability skills such as communication, digital literacy, global citizenship and the like. Similarly little attention been paid to explicitly assuring the quality of MOOCs with respect to alignment with regulatory body standards. Deakin University's first MOOC, DeakinPrimer, is an introduction to humanitarian responses to 21st century disasters. It has been designed to assist participants to explicitly evidence generic or employability skills, some of Deakin's eight Graduate Learning Outcomes (GLOs) including communication, digital literacy, critical thinking and global citizenship. Other key features of DeakinPrimer include opportunities for networking with fellow participants and experts within the humanitarian field, and the opportunity to apply for credit towards the Graduate Certificate in International Community Development (level 8 in the Australian Qualifications Framework [AQF]) and for those with a prior Bachelor degree, the Masters in Humanitarian Assistance or the Masters of International Community Development (level 9 in the AQF). DeakinPrimer is designed as a test bed for a learning innovation, particularly micro-credentialing GLOs using digital badges to enable self and peer endorsement of evidence of learning. Badging is integrated in two ways. Firstly, DeakinPrimer participants build portfolios of learning artefacts associated with learning activities, then assess their work against a set of holistic, generic learning outcomes standards rubrics. If they judge their evidence as meeting the required standard, they can claim a badge (self endorsement) associated with particular GLOs. Secondly, participants can request and provide peer feedback and endorsement (using peer badges). The integration of self and peer review in the assessment tasks helps participants develop important employability skills, the ability to critically self-reflect on their own work and critically analyse the work of others and provide evidence-based feedback. DeakinPrimer is scheduled to commence in July 2013. This paper explains the way in which the course curricula has been designed to use technologies to enable participants to curate evidence of learning, and self and peer endorse such learning against defined standards.

The pedagogy of using video to develop reflective practice in learning to teach science

Purpose The purpose of this chapter is to identify the pedagogical approaches that foster critical reflection using video among the preservice teachers during tutorials. Methodology/approach The research is situated in a school-based teaching programme in which pairs of pre-service teachers taught small groups of primary aged children over a period of seven weeks. Volunteer pre-service teachers videotaped their lessons and selected video excerpts to share with their peers in the tutorial. The educator guided the preservice teachers’ reflection using the video. A case study drawing on interviews with pre-service teachers and audio recordings of tutorials, charted the development of pedagogical decisions made by the educators to promote reflection.Findings The pre-service teachers had difficulties undertaking deep reflection of their own and peers’ teaching practice. The response by educators was to promote collaboration among pre-service teachers by discussing specific aspects of the teaching in small groups and to use a jigsaw approach. This enabled a deeper analysis of particular elements of the lesson that were then integrated to produce a more holistic understanding of the teaching. The video data is most suitable for reflection and provides valuable evidence for pre-service teachers to develop their practice. Practical implications For pre-service teachers to develop effective skills to analyse their own practice they need to experience teaching in a safe but challenging environment, over a sustained period; have opportunities to develop a shared understanding of what constitutes quality teaching; have opportunities to critically analyse their teaching in discussion with peers and educators and be able to be guided by a framework of reflective strategies.

Is scholarship of teaching and learning in practical legal training a professional responsibility?

In Australia, applicants for admission to the legal profession must hold appropriate academic qualifications, and competently complete practical legal training (PLT). The author's research investigates institutional PLT practitioners' engagement with scholarship of teaching and learning (SoTL). The theoretical framework for the research draws on Bourdieu and Passeron's reflexive sociology of education and culture. This article focuses on responses to a paramount obligation proposition put to 34 PLT practitioners during semi-structured interviews: Might lawyers' paramount obligations to the court intersect with PLT practitioners' teaching and assessment practices? The proposition elicited responses and insights about field forces within the individual and organisational dimensions of teaching and learning in PLT. These include top-down/bottom-up pressures that impinge on PLT practitioners' engagement with SoTL.

Saliency detection using hierarchical manifold learning

Saliency detection is critical to many applications in computer vision by eliminating redundant backgrounds. The saliency detection approaches can be divided into two categories, i.e., top-down and bottom-up. Among them, bottom-up models have attracted more attention due to their simple mechanisms. However, many existing bottom-up models are not robust to crowded backgrounds because of missing salient regions within feedforward frameworks which is often not effective for complex scenes. We tackle these problems by modifying and extending a bottom-up saliency detection model through three phases, (1) constructing a hierarchical sequence of images from the perspective of entropy, (2) estimated mid-level cues are used as feedback information, (3) subsequently generating saliency maps by global context and local uniqueness in a graph-based framework. We also compare the proposed bottom-up model with state-of-the-art approaches on two benchmark datasets to evaluate its saliency detection performance. The experimental results demonstrate that the proposed bottom-up saliency detection approach is not only robust to both cluttered and clean scenes, but also able to obtain objects with different scales.

Collaborative problem based learning in distance and mobile education

Since the early 1970s, Problem based Learning (PBL) in small groups is a prominent and innovative didactic approach with multiple facets, good practices and demonstrated effectiveness in many countries, for many different subjects and education/training programs, and in various settings (primary, secondary and higher tertiary education) (see e. g. Edens, 2000, Savery, 2006; Ertmer, Hmelo-Silver, 2015). However, this concept is not so much perceived in distance learning programs even though new technologies allow for better real-time collaboration in virtual classrooms and workspaces, mobile access to electronic learning resources via smart phones, and digital learning content like videos, podcasts or simulation tools. One reason for this might be the lack of conceptual frameworks and appropriate models for PBL in distance education. In this article, one prominent concept for designing PBL learning settings will be presented and its application in practice discussed: the 3C3R-Model of Hung (2006) defines a framework for Content, Context, and Connection (3C), which are interlinked through learner activities such as Researching, Reasoning and Reflecting (3R).Practical implications and examples for the design of appropriate distance learning designs based on this model will be presented and discussed with the audience.

Active video games - An opportunity for enhanced learning and positive health effects?

Active video games are an emerging genre of electronic games that provide engaging exercise experiences by combining physical exertion with interactive game play. As such they have attracted increased interest from health promotion professionals to reduce sedentary behavior, increase physical activity, and improve health outcomes such as body composition. However their potential for enhancing the educational experience has not been extensively explored. This paper provides a brief overview of active video game research to date and outlines opportunities for future research. Specifically, we highlight the need to develop a conceptual framework to better understand the determinants, mediators, moderators, and consequences of active video gaming and integrate learning and health outcomes. Wepropose that active video games can be a key part of a wider “digital” supportive environment where education and health researchers and professionals work with, rather than against, video game technologies to promote learning and health.

Support for assessment practice: developing the assessment design decisions framework

There are many excellent publications outlining features of assessment and feedback design in higher education. However, university educators often find these ideas challenging to realise in practice, as much of the literature focuses on institutional change rather than supporting academics. This paper describes the conceptual development of a practical framework designed to stimulate educators’ thinking when creating or modifying assessments. We explain the concepts that underpin this practical support, including the notions of ‘assessment decisions’ and ‘assessment design phases’, as informed by relevant literature and empirical data. We also present the outcome of this work. The Assessment Design Decisions Framework. This provides key considerations in six categories: purposes, contexts, tasks, interactions, feedback processes and learning outcomes. By tracing the development of the Framework, we highlight complex ways of thinking about assessment that are relevant to those who design and deliver assessment to tertiary students.

Emergent behaviour: learning from an artificially intelligent performing software agent

This research investigates the possibility for emergent choreographic behaviour to arise from the interactions between a human dancer and a learning, digital performing agent. The cognitive framework is extended through theories of distributed cognition to take into account the two interacting agents rather than a single agent and its environment. The Artificial Neural Network based performing agent demonstrated emergent dance behaviour when performing live with the human dancer. The agent was able to follow the dancer, create movement phrases based on what the dancer was performing and recognize short movement phrases, as a result of the interaction of the dancer’s motion captured movement data and the agent’s artificial neural network. This emergent behaviour was not explicitly programmed, but emerged as a result of the learning process and the interactions with the human dancer.

Identifying inorganic material affinity classes for peptide sequences based on context learning

There is a growing interest in identifying inorganic material affinity classes for peptide sequences due to the development of bionanotechnology and its wide applications. In particular, a selective model capable of learning cross-material affinity patterns can help us design peptide sequences with desired binding selectivity for one inorganic material over another. However, as a newly emerging topic, there are several distinct challenges of it that limit the performance of many existing peptide sequence classification algorithms. In this paper, we propose a novel framework to identify affinity classes for peptide sequences across inorganic materials. After enlarging our dataset by simulating peptide sequences, we use a context learning based method to obtain the vector representation of each amino acid and each peptide sequence. By analyzing the structure and affinity class of each peptide sequence, we are able to capture the semantics of amino acids and peptide sequences in a vector space. At the last step we train our classifier based on these vector features and the heuristic rules. The construction of our models gives us the potential to overcome the challenges of this task and the empirical results show the effectiveness of our models.

Prosper: A new framework for positive education

Positive psychology is the study of the conditions and processes that contribute to optimal flourishing in people, groups and organisations. This paper outlines the PROSPER framework, an organising tool for the implementation of Positive Education, a relatively new direction which represents the application of Positive Psychology research to educational contexts. The word ‘PROSPER’ communicates the purpose of the framework and is also an acronym that highlights the seven key elements that have been identified as contributing to wellbeing: Positivity, Relationships, Outcomes, Strengths, Purpose, Engagement, and Resilience. Confirmatory data on the usefulness of the PROSPER framework, obtained through surveys conducted with researchers from the Institute of Positive Psychology and Education (ACU) and fifty-four educators from four different schools, is presented and discussed. A rationale for the inclusion of the seven components is provided and the PROSPER framework is then further supported by reference to the evidence-informed school and classroom practices that contribute to student wellbeing and achievement and help to build schools as enabling institutions.

Good practice guidelines for curriculum, supervision and assessment of final year engineering projects and AQF8 learning outcomes

Undergraduate engineering programs require final year students to complete capstone final year projects and demonstrate that they can integrate knowledge, skills and professional graduate attributes developed during the program at Australian Qualification Framework, level 8 (AQF8) outcomes. Literature shows that currently there is no guarantee of consistency for curriculum, supervision and assessment practices of FYEPs. Practices differ greatly between universities and littlework has been initiated that seeks to identify good practice, highlighting the need for the development of guidelines for curriculum, supervision and assessment of FYEPs. This workshop is designed to share and disseminate the good practice guidelines that have been developed on curriculum, supervision and assessment of Final Year Engineering Projects as a part of phase 2 of the project ‘Assessing Final Year Engineering Projects (FYEPs): Ensuring Learning and Teaching Standards and AQF8 Outcomes’ funded by the Australian Office for Learning and Teaching (OLT) with people working in the area of FYEPs. The guidelines typically apply to four year undergraduate engineering degrees with embedded Honours and support achievement of AQF8learning outcomes. The project team has 7 partner Universities – Central Queensland University (the lead), University of Technology Sydney, University of Adelaide, Curtin University, Deakin University, University of Tasmania and RMIT University.Participants will be invited to reflect on and evaluate guidelines and findings derived from FYEP coordinators, supervisors and the wider literature and to consider the ways in which these findings might lead to improvements in their practice.

Integrating internet-of-things with the power of cloud computing and the intelligence of big Data analytics- a three layered approach

This paper is written through the vision on integrating Internet-of-Things (IoT) with the power of Cloud Computing and the intelligence of Big Data analytics. But integration of all these three cutting edge technologies is complex to understand. In this research we first provide a security centric view of three layered approach for understanding the technology, gaps and security issues. Then with a series of lab experiments on different hardware, we have collected performance data from all these three layers, combined these data together and finally applied modern machine learning algorithms to distinguish 18 different activities and cyber-attacks. From our experiments we find classification algorithm RandomForest can identify 93.9% attacks and activities in this complex environment. From the existing literature, no one has ever attempted similar experiment for cyber-attack detection for IoT neither with performance data nor with a three layered approach.