A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Australian higher education evaluation through assurance of learning

A collaborative research project conducted by five Australian universities inquired into the philosophy and motivation for Assurance of Learning (AoL) as a process of education evaluation. Associate Deans Teaching and Learning representing Business schools from twenty-five universities across Australia participated in telephone interviews. Data was analysed using NVIVO9. Results indicated that articulated rationale for AoL was both ensuring that students had acquired the attributes and skills the universities claimed they had, and the philosophy of continuous improvement. AoL was motivated both by ritualistic objectives to satisfy accreditation requirements and virtuous agendas for quality improvement. Closing-the-loop was emphasised, but was mostly wishful thinking for next steps beyond data collection and reporting. AoL was conceptualised as one element within the larger context of quality review, but there was no evidence of comprehensive frameworks or strategic plans.

Assurance of learning – are academics and senior management singing from the same hymn sheet?

Assurance of learning (AoL) is an important process in quality education, designed to measure the accomplishment of educational aims at the core of an institution’s programs, whilst encouraging faculty to continuously develop and improve the programs and courses. This paper reports on a study of Australian business schools to investigate current AoL practices through semi structured interviews with senior faculty leaders followed by focus group interviews with groups of senior program leaders and groups of academic teaching staff. Initial findings indicate there are significant challenges in encouraging academic staff to commit to the process and recognise the benefits of assuring learning. The differences in understanding between the various leaders and the academics were highlighted through the different focus groups. Leaders’ stressed strategic issues such as staff engagement and change, while academics focussed on process issues such as teaching graduate attributes and external accreditation. Understanding the differences in the perspectives of leaders and faculty is important, as without a shared understanding between the two groups, there is likely to be limited engagement, which creates difficulties in developing effective assurance of learning processes. Findings indicate that successful strategies developed to foster shared values on assurance of learning include: strong senior leaders’ commitment; developing champions among program and unit level staff; providing professional development opportunities; promoting and celebrating success and effectiveness; and ensuring an inclusive process with academics of all levels collaborating in the development and implementation of the process.

Enabling innovation and facilitating learning in kifs: the role of HRM practices

The aim of this paper is to contribute to our understanding of the link between HR practices, learning orientation and types of innovation in knowledge-intensive firms (KIFs). To this end, we first compiled a comprehensive overview of the existing literature on HR practices aimed at supporting innovation. On the basis of this literature, we then collected and analyzed data from a qualitative study of 19 Danish KIFs recognized for their innovation performance, focusing on links between the HR practices they use to support exploratory and exploitive learning behaviors to enhance incremental and/or radical innovation. The findings from this study demonstrate that KIFs utilize a range of HR practices that enable different learning orientations, based on the type of innovation compatible with their organizational goals.

Learning communities learning series

In 2008 the introduction of the National Assessment Program – Literacy and Numeracy (NAPLAN), combined with the publication of the international comparative analyses of student achievement data (such as the Programme of International Student Assessment (PISA) developed by the Organisation for Economic Co-operation and Development (OECD) and the Trends in International Mathematics and Science Study (TIMSS) of the International Association for the Evaluation of Educational Achievement (IEA)) highlighted a significant priority for Australian education by identifying low levels of equity.

Meaningful musical engagement : the potential impact of generative music systems on learning experiences

In order to create music, the student must establish a relationship with the musical materials. In this thesis, I examine the capacity of a generative music system called jam2jam to offer individuals a virtual musical play-space to explore. I outline the development of an iteration of software development named jam2jam blue and the evolution of a games-like user interface in the research design that jointly revealed the nature of this musical exploration. The findings suggest that the jam2jam blue interface provided an expressive gestural instrument to jam and experience musicmaking. By using the computer as an instrument, participants in this study were given access to meaningful musical experiences in both solo and ensemble situations and the researcher is allowed a view of their development of a relationship with the musical materials from the perspective of the individual participants. Through an iterative software development methodology, pedagogy and experience design were created simultaneously. The research reveals the potential for the jam2jam software to be used as a reflective tool for feedback and assessment purposes. The power of access to ensemble music making is realised though the participants’ virtual experiences which are brought into their physical space by sharing their experience with others. It is suggested that this interaction creates an environment conducive to self-initiated learning in which music is the language of interaction. The research concludes that the development of a relationship between the explorer and the musical materials is subject to the collaborative nature of the interaction through which the music is experienced.

Pragmatics, perceptions and strategies in Chinese college English learning

This study investigated Chinese College English students. perceptions of pragmatics, their pragmatic competence in selected speech acts, strategies they employed in acquiring pragmatic knowledge, as well as their general approach to learning English as a foreign language. The research was triggered by a national curriculum initiative that prioritizes the need for College English students to enhance their ability to use English effectively in different social interactions (Chinese College English Education and Supervisory Committee, 2007). The traditional "grammar-translation" and "examination-oriented" method is believed to have reduced Chinese College English students to what is dubbed "mute" and "deaf" language learners (Zhang, 2008; Zhao, 2009). Many students lack pragmatic knowledge on how to interpret discourse by relating utterances to their meanings, understanding the intention of language users, and how language is used in specific settings (Bachman & Palmer, 1996, 2010). There is an increasing body of literature on awareness-raising of the importance of pragmatic knowledge and strategies for classroom instruction. However, to date, researchers have tended to focus largely on the teaching of pragmatics, rather than on how students acquire pragmatic competence (Bardovi-Harlig & Dornyei, 1998; Du, 2004; Hou, 2007; Ruan, 2007; Schauer, 2009). It is this gap in the research that this study fills, with a focus on different types of pragmatic knowledge, learner perceptions of such knowledge, and learning strategies that College English students employ in the process of learning English in general, and pragmatics in particular. Three strands of theories of second language acquisition (Ellis, 1985, 1994): pragmatics (Levinson, 1983; Mey, 2001; Yule, 1996), intercultural communications (Kramsch, 1998; Samovar & Porter, 1997; Samovar, Porter & McDaniel, 2009) and English as a lingua franca (ELF) (Canagarajah, 2006; Firth, 1996; Pennycook, 2010) were employed to establish a conceptual framework for data collection and analyses. Key constructs derived from the three related theories helped to form a typology for a detailed examination and theorization of the empirical evidence gathered from different sources. Four research instruments: a questionnaire (N=237), Discourse Completion Tasks (DCTs) (N=55), focus group interviews (N=18), and a textbook tasks analysis were employed to collect data for this systematic inquiry. Data collected by different instruments were analyzed and compared by way of a triangulation to enhance its validity and reliability. Major findings derived from different sources highlighted that, although College English students were grammatically advanced language learners, they displayed limited pragmatic knowledge and a highly restricted repertoire of language learning strategies. The majority of the respondents, however, believed that pragmatic knowledge was as important as linguistic knowledge in the process of developing communicative competence for interaction in different contexts. It was argued that a combination of a less than sufficient English proficiency, limited knowledge of pragmatics, inadequate language materials and tasks, and a small stock of language learning strategies, were a major hindrance to effective learning and communication, resulting in pragmatic failures in many intercultural communication situations. As the first systematic study of how Chinese College English students learned pragmatics, the research provided a solid empirical base for developing a tentative model for the learning of pragmatics in a College English classroom in China and similar educational contexts. The model was strengthened by a unique combination of theories of pragmatics, intercultural communication and ELF. Findings from this research provided insights into how Chinese College English students perceived pragmatics in the English as foreign language (EFL) curriculum, the processes of learning, as well as strategies they utilized in developing linguistic and pragmatic knowledge and competence.

Contextualising learning for a real-world university: how an inverted curriculum in the first year can help better student retention

An identified issue within higher education is the high rates of student attrition after the first year, especially in the STEM disciplines. To address this issue, it is essential to reexamine and redesign the first year curriculum to engage and retain the students' interests while also scaffolding their learning experience. This session reports on an initiative based on the principles of the “inverted curriculum” within the Bachelor of Technology (BIT) course at the Queensland University of Technology (QUT) that began in 2009 and has resulted in a reduction in first-year attrition rates from 18% in 2008 to 10% in 2009 and 2010 despite a growth in student intake of 15% to 40% in the past two years. We present the process and methods that helped achieve this and initiate a discussion on the innovations that are possible within this concept of inverted curriculum and how it can be implemented.

Meta-evaluation to improve learning, evaluation capacity development and sustainability : Findings from a participatory evaluation project in Nepal

Recent studies suggest that meta-evaluation can be valuable in developing new approaches to evaluation, building evaluation capacities, and enhancing organizational learning. These new extensions of the concept of meta-evaluation are significant, given the growing emphasis on improving the quality and effectiveness of evaluation practices in the South Asian region. Following a review of the literature, this paper presents a case study of the use of concurrent meta-evaluation in the four-year project Assessing Communication for Social Change which developed and trialled a participatory impact assessment methodology in collaboration with a development communication Non-government organization (NGO) in Nepal. Key objectives of the meta-evaluation included to: continuously develop, adapt and improve the impact assessment methodology, Monitoring and Evaluation (M&E) systems and process and other project activities; identify impacts of the project; and build capacities in critical reflection and review. Our analysis indicates that this meta-evaluation was essential to understanding various constraints related to the organizational context that affected the success of the project and the development of improved M&E systems and capacities within the NGO. We identified several limitations of our meta-evaluation methods, which were balanced by the strengths of other methods. Our case study suggests that as well as assessing the quality, credibility and value of evaluation practices, meta-evaluations need to focus on important contextual issues that can have significant impacts on the outcomes of participatory evaluation projects. They include hierarchical organizational cultures, communication barriers, power/knowledge relations, and the time and resources available. Meta-evaluations also need to consider wider issues such as the sustainability of evaluation systems and approaches.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.