Going live : building academic capacity in blended learning using web-conferencing technologies

This paper reports on a current initiative at Queensland University of Technology to provide timely, flexible and sustainable training and support to academic staff in blended learning and associated techno-pedagogies via a web-conferencing classroom and collaboration tool, Elluminate Live!. This technology was first introduced to QUT in 2008 as part of the university‘s ongoing commitment to meeting the learning needs of diverse student cohorts. The centralised Learning Design team, in collaboration with the university‘s department of eLearning Services, was given the task of providing training and support to academic staff in the effective use of the technology for teaching and learning, as part of the team‘s ongoing brief to support and enhance the provision of blended learning throughout the university. The resulting program, ―Learning Design Live‖ (LDL) is informed by Rogers‘ theory of innovation and diffusion (2003) and structured according to Wilson‘s framework for faculty development (2007). This paper discusses the program‘s design and structure, considers the program‘s impact on academic capacity in blended learning within the institution, and reflects on future directions for the program and emerging insights into blended learning and participant engagement for both staff and students.

Designing for collaborative learning spaces : an academic staff development pilot program

To prepare for the delivery of new Bachelor of Science units in collaborative learning spaces, academic and professional staff at Queensland University of Technology piloted an academic development program over the period of a semester. The program was informed by Rogers’ theory of innovation and diffusion (2003) and structured according to Wilson’s framework for faculty development (2007). Through a series of workshops and group mentoring activities, the program modelled inquiry-based learning in a collaborative learning space, and the participants designed and practiced the delivery of teaching activities. This paper provides a preliminary evaluation of the effectiveness of the pilot based on survey responses from participants, notes from the development team who coordinated the program and audience feedback from the final showcase session. The design and structure of the program is discussed as well as possible future directions.

Socially inclusive learning in a community setting

People with mental health problems, learning difficulties and poor literacy and numeracy are at risk of social exclusion including homelessness. They are often disconnected from the Vocational Education and Training (VET) system, with few opportunities for education and employment. Academic research has demonstrated a link between literacy and numeracy and social inclusion, however, the pathways to enact this are not well understood. This report presents insights into how a community based adult literacy program in West End, Brisbane, was first established and has since evolved into a successful model of what we are calling ‘socially inclusive learning’. The research informing the report was conducted as a twelve-month study from April 2013 to April 2014 funded through a partnership involving Anglicare Southern Queensland, A Place to Belong and the School of Public Health and Social Work, Queensland University of Technology. The research was conducted by Greg Marston and Jeffrey Johnson- Abdelmalik. The aim of the study was to clarify the principles, practice and methodology of the Reading and Writing group (hereafter RAW) and identify the characteristics of RAW that support the social inclusion of the individual being provided literacy learning. The questions guiding the research included: • What are the key principles and practices of the RAW model? • How does the acquisition of literacy and numeracy skills contribute to the recovery of people with mental health and other issues? • How can the acquisition of literacy and numeracy skills support people’s social inclusion, including achieving employment and further education outcomes? A related aim of the project was to document how this community based literacy and numeracy program operates so that other organisations with an interest in addressing similar needs can learn from the model, particularly organisations that co-locate support and education and organisations that adopt a recovery approach when working with people with mental health challenges and intellectual and psychiatric disabilities. The report highlights the background to RAW, the learning philosophy of RAW, the profile of the participants in the program and the various roles and responsibilities and structure that supports the work of RAW. The report presents perspectives from the teachers, student participants and tutors on how the group is designed and the principles implemented.

Moving forwards with the aim of going backwards fast : high performance rowing as a learning environment

Background and Purpose: - This paper focuses on the learning culture within the high performance levels of rowing. In doing so, we explore the case of an individual’s learning as he moves across athletic, coaching and administrative functions. This exploration draws on a cultural learning framework and complementary theorisings related to reflexivity. Method - This study makes use of an intellectually, morally and collaboratively challenging approach whereby one member of the research team was also the sole participant of this study. The participant’s careers as a high performance athlete, coach and administrator, coupled with his experience in conducting empirical research presented a rare opportunity to engage in collaborative research (involving degrees of insider and outsider status for each of the research team). We acknowledge that others have looked to combine roles of coach / athlete / administrator with that of researcher however few (if any) have attempted to combine them all in one project. Moreover, coupled with the approach to reflexivity adopted in this study and the authorship contributions we consider this scholarly direction uncommon. Data were comprised of recorded research conversations, a subsequently constructed learning narrative, reflections on the narrative, a stimulated reflective piece from the participant, and a final (re)construction of the participant’s story. Accordingly, data were integrated through an iterative process of thematic analysis. Results - The cultural (i.e., the ways things get done) and structural (e.g., the rules and regulations) properties of high performance rowing were found to shape both the opportunities to be present (e.g., secure a place in the crew) and to learn (e.g., learn the skills required to perform at an Olympic level). However, the individual’s personal properties were brought to bear on re-shaping the constraints such that many limitations could be overcome. In keeping with the theory of learning cultures, the culture of rowing was found to position individuals (a coxswain in this case) differentially. In a similar manner, a range of structural features was found to be important in shaping the cultural and personal elements in performance contexts. For example, the ‘field of play’ was found to be important as a structural feature (i.e., inability of coach to communicate with athletes) in shaping the cultural and personal elements of learning in competition (e.g., positioning the coxswain as an in-boat coach and trusted crewmate). Finally, the cultural and structural elements in rowing appeared to be activated by the participant’s personal elements, most notably his orientation towards quality performance. Conclusion - The participant in this study was found to be driven by the project that he cares about most and at each turn he has bent his understanding of his sport back on itself to see if he can find opportunities to learn and subsequently explore ways to improve performance. The story here emphasises the importance of learner agency, and this is an aspect that has often been missing in recent theorising about learning. In this study, we find an agent using his ‘personal emergent powers to activate the resources in the culture and structure of his sport in an attempt to improve performance. We conclude from this account that this particular high performance rowing culture is one that provided support but nonetheless encouraged those involved, to ‘figure things out’ for themselves – be it as athletes, coaches and/or administrators.

Genome-wide interaction analysis reveals replicated epistatic effects on brain structure

The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

Flexible learning design in curriculum delivery promotes student engagement and develops metacognitive learners: An integrated review

Historically, university students have been the passive recipients of face-to-face instructor designed and led classes (Hudson, 2014; Myers et al., 2011). Technological advancement, however, has provided an opportunity for greater flexibility around educational structure; students are starting to expectmore fromtertiary education providers, specifically around the delivery and provision of education (Myers et al., 2011). For universities to meet the ever-changing needs of the student they need to consider the integration of flexible learning designs into their curricula. The consequent willingness of the faculty to rethink the design and delivery of curricula has seen a recent shift in the design and delivery of education. As universities strive to promote student engagement, active learning, and communities of enquiry, they are moving progressively towards flexible learning models, virtual interaction and student centric curricula (Heise and Himes, 2010; Hsu and Hsieh, 2011). The challenge this shift creates is how to best engage students throughout their studies in order to produce graduates with the skills necessary for societal and professional sustainability (Castle and McGuire, 2010). Despite a wealth of literature addressing this topic, there is a paucity of substantive, conclusive outcomes as to the efficacy of its full implementation and potential for producing capable learners. This integrative review therefore aims to inform curriculum delivery that is flexible, student centric and scaffolds learning. It also aims to identify whether this approach assists in the development of metacognitive learners.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

Rethinking Culture and Diversity in Early Childhood Preservice Teacher Education: Looking at Teaching and Learning Through an Interdisciplinary Lens

Early Childhood Education (ECE) has a long history of building foundations for children to achieve their full potential, enabling parents to participate in the economy while children are cared for, addressing poverty and disadvantage, and building individual, community and societal resources. In so doing, ECE has developed a set of cultural practices and ways of knowing that shape the field and the people who work within it. ECE, consequently, is frequently described as unique and special (Moss, 2006; Penn, 2011). This works to define and distinguish the field while, simultaneously, insulating it from other contexts, professions, and ideas. Recognising this dualism illuminates some of the risks and challenges of operating in an insular and isolated fashion. In the 21st century, there are new challenges for children, families and societies to which ECE must respond if it is to continue to be relevant. One major issue is how ECE contributes to transition towards more sustainable ways of living. Addressing this contemporary social problem is one from which Early Childhood teacher education has been largely absent (Davis & Elliott, 2014), despite the well recognised but often ignored role of education in contributing to sustainability. Because of its complexity, sustainability is sometimes referred to as a ‘wicked problem’ (Rittel & Webber, 1973; Australian Public Service Commission, 2007) requiring alternatives to ‘business as usual’ problem solving approaches. In this chapter, we propose that addressing such problems alongside disciplines other than Education enables the Early Childhood profession to have its eyes opened to new ways of thinking about our work, potentially liberating us from the limitations of our “unique” and idiosyncratic professional cultures. In our chapter, we focus on understandings of culture and diversity, looking to broaden these by exploring the different ‘cultures’ of the specialist fields of ECE and Design (in this project, we worked with students studying Architecture, Industrial Design, Landscape Architecture and Interior Design). We define culture not as it is typically represented, i.e. in relation to ideas and customs of particular ethnic and language groups, but to the ideas and practices of people working in different disciplines and professions. We assert that different specialisms have their own ‘cultural’ practices. Further, we propose that this kind of theoretical work helps us to reconsider ways in which ECE might be reframed and broadened to meet new challenges such as sustainability and as yet unknown future challenges and possibilities. We explore these matters by turning to preservice Early Childhood teacher education (in Australia) as a context in which traditional views of culture and diversity might be reconstructed. We are looking to push our specialist knowledge boundaries and to extend both preservice teachers and academics beyond their comfort zones by engaging in innovative interdisciplinary learning and teaching. We describe a case study of preservice Early Childhood teachers and designers working in collaborative teams, intersecting with a ‘real-world’ business partner. The joint learning task was the design of an early learning centre based on sustainable design principles and in which early Education for Sustainability (EfS) would be embedded Data were collected via focus group and individual interviews with students in ECE and Design. Our findings suggest that interdisciplinary teaching and learning holds considerable potential in dismantling taken-for-granted cultural practices, such that professional roles and identities might be reimagined and reconfigured. We conclude the chapter with provocations challenging the ways in which culture and diversity in the field of ECE might be reconsidered within teacher education.

Intercultural Learning and Hybridity in the Culture Laboratory

The number of immigrant students in vocational education and training is steadily increasing in Finland. This poses challenges for teachers and schools. This research focuses on emerging questions of intercultural learning in the context of immigrant training, and on a method the Culture Laboratory that was developed in an attempt to respond to the challenges. The main methodological and theoretical framework lies in cultural-historical activity theory, developmental work research, and in the concepts of the intercultural and hybridity. The empirical material consists of videotaped recordings of discussions in the Culture Laboratory. The five main research questions focused on the strengths and limitations of the Culture Laboratory as a tool for intercultural learning, the significance of disturbances in it, the potential of suggestions for intercultural learning, paper as a mediating artifact , and the concept of intercultural space. The findings showed that the Culture Laboratory offered a solid background for developing intercultural learning. The disturbances manifested revealed a multitude of scripts and activities. It was also suggested that the structure of expansive learning could start from externalization instead of internalization. The suggestions the participants made opened up a hybrid learning space for intercultural development, and offered a good springboard for new ideas. Learning in Paperland posed both challenges and opportunities for immigrant students, and different paper trails emerged. Intercultural space in the Culture Laboratory was a developmental zone in which a hybrid process of observing, comparing, and creating took place. Key words: intercultural learning, immigrant training, cultural-historical activity theory, developmental work research,

Student perception of a new integrated anatomy practical program: Does students' prior learning make a difference?

While there is evidence that science and non-science background students display small differences in performance in basic and clinical sciences, early in a 4-year, graduate entry medical program, this lessens with time. With respect to anatomy knowledge, there are no comparable data as to the impact previous anatomy experience has on the student perception of the anatomy practical learning environment. A study survey was designed to evaluate student perception of the anatomy practical program and its impact on student learning, for the initial cohort of a new medical school. The survey comprised 19 statements requiring a response using a 5-point Likert scale, in addition to a free text opportunity to provide opinion of the perceived educational value of the anatomy practical program. The response rate for a total cohort of 82 students was 89%. The anatomy practical program was highly valued by the students in aiding their learning of anatomy, as indicated by the high mean scores for all statements (range: 4.04-4.7). There was a significant difference between the students who had and had not studied a science course prior to entering medicine, with respect to statements that addressed aspects of the course related to its structure, organization, variety of resources, linkage to problem-based learning cases, and fairness of assessment. Nonscience students were more positive compared to those who had studied science before (P levels ranging from 0.004 to 0.035). Students less experienced in anatomy were more challenged in prioritizing core curricular knowledge. © 2011 Wiley-Liss, Inc.

A Geometric Algorithm for Learning Oblique Decision Trees

In this paper we present a novel algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess goodness of hyperplanes at each node. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy, based on some recent variants of SVM, to assess the hyperplanes in such a way that the geometric structure in the data is taken into account. We show through empirical studies that our method is effective.

Discriminative learning of Bayesian networks via factorized conditional log-likelihood

We propose an efficient and parameter-free scoring criterion, the factorized conditional log-likelihood (ˆfCLL), for learning Bayesian network classifiers. The proposed score is an approximation of the conditional log-likelihood criterion. The approximation is devised in order to guarantee decomposability over the network structure, as well as efficient estimation of the optimal parameters, achieving the same time and space complexity as the traditional log-likelihood scoring criterion. The resulting criterion has an information-theoretic interpretation based on interaction information, which exhibits its discriminative nature. To evaluate the performance of the proposed criterion, we present an empirical comparison with state-of-the-art classifiers. Results on a large suite of benchmark data sets from the UCI repository show that ˆfCLL-trained classifiers achieve at least as good accuracy as the best compared classifiers, using significantly less computational resources.

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.

Structural Alignment based Kernels for Protein Structure Classification

Structural alignments are the most widely used tools for comparing proteins with low sequence similarity. The main contribution of this paper is to derive various kernels on proteins from structural alignments, which do not use sequence information. Central to the kernels is a novel alignment algorithm which matches substructures of fixed size using spectral graph matching techniques. We derive positive semi-definite kernels which capture the notion of similarity between substructures. Using these as base more sophisticated kernels on protein structures are proposed. To empirically evaluate the kernels we used a 40% sequence non-redundant structures from 15 different SCOP superfamilies. The kernels when used with SVMs show competitive performance with CE, a state of the art structure comparison program.

Feature selection for unsupervised learning

In this paper, we present a methodology for identifying best features from a large feature space. In high dimensional feature space nearest neighbor search is meaningless. In this feature space we see quality and performance issue with nearest neighbor search. Many data mining algorithms use nearest neighbor search. So instead of doing nearest neighbor search using all the features we need to select relevant features. We propose feature selection using Non-negative Matrix Factorization(NMF) and its application to nearest neighbor search. Recent clustering algorithm based on Locally Consistent Concept Factorization(LCCF) shows better quality of document clustering by using local geometrical and discriminating structure of the data. By using our feature selection method we have shown further improvement of performance in the clustering.