Deepening the mathematical knowledge of secondary mathematics teachers who lack tertiary mathematics qualifications

A professional learning program for unqualified practising secondary mathematics teachers regarding senior secondary mathematics teaching is described in this paper. The VCE (Victorian Certificate of Education) mathematics professional learning program for senior secondary mathematics was designed for practising secondary teachers of mathematics who had no experience of teaching advanced senior secondary mathematics and who had not completed the recommended qualifications. Professional learning episodes, artefacts and reflections of three teachers who participated in the program are analysed to identify the development of these teachers' mathematical and pedagogical content knowledge (PCK). The PCK framework developed by Chick et al. was used to analyse teachers' knowledge, and the cases of teachers' knowledge presented in the paper illustrate the entwining of knowledge of mathematics and knowledge of teaching and learning The findings indicate that a program designed for senior secondary mathematics can enable practising teachers to deepen and broaden their understanding of junior secondary mathematical pedagogy.

Leading the quality management of online learning environments in Australian higher education

The paper presents the findings of the first year of a nationally funded Australian Learning and Teaching Council (ALTC) project on the quality management of online learning environments by and through distributed leadership. The project is being undertaken by five Australian universities with major commitments to online and distance education. Each university, however, has a distinctive location, history and profile in the sector. The first year of the project has seen the development of a quality management framework with six interrelated elements. The framework is being applied, refined and validated in the second year of the project. Allied with the development of the framework, was the conduct of focus groups at each of the five partner institutions in the middle of the first year. These focus groups composed a range of staff involved collectively in the leadership of the organisation's online learning environment. Prominence was given to the nature and value of strategic planning, due diligence conducted in selecting and mainstreaming technologies, evaluation approaches informing decision making, and the various relationships between different leadership levels and domains. A number of key issues which emerged relating to the elements identified in the framework are examined.

A review of online learning in supervised neural networks

Learning in neural networks can broadly be divided into two categories, viz., off-line (or batch) learning and online (or incremental) learning. In this paper, a review of a variety of supervised neural networks with online learning capabilities is presented. Specifically, we focus on articles published in main indexed journals in the past 10 years (2003–2013). We examine a number of key neural network architectures, which include feedforward neural networks, recurrent neural networks, fuzzy neural networks, and other related networks. How the online learning methodologies are incorporated into these networks is exemplified, and how they are applied to solving problems in different domains is highlighted. A summary of the review that covers different network architectures and their applications is presented.

Shifts in thinking and practice: reflecting on an applied learning programme

The implementation of the first iteration of a curriculum for an applied learning programme for police trainers received a hostile response from participants. It was perceived as irrelevant and supplanting, rather than augmenting, trainers’ fixed and untested training practices. This paper presents the reflections on my journey as a nonpolice person straddling an outsider-insider position while challenging that which is taken-for-granted and introducing an educative intent, as opposed to a doctrinal, technical intent, to police training. On a daily basis I simultaneously work within and against the prevailing D/discourses and dominant subcultures, while establishing and nurturing relationships with police trainers: being teacher, coach and ‘critical friend’. The response to the second and now third iterations of the learning programme has been increasingly positive, revealing shifts in trainers’ thinking and practice.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Measuring the influence of Cooperative Learning and Project Based Learning on problem solvin skill.

The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The second hypothesis was focused on testing if students with higher rates in problem solving competence obtain better results in their academic performance. The results indicated that active learning methodologies do not produce any significant change in the generic competence ?problem solving? during the period analysed. Concerning this, we consider that students should work with these methodologies for a longer period, besides having a specific training. Nevertheless, a close correlation between problem solving self appraisal and academic performance has been detected.

Survey on integration of Applied Geology and Geomorphology in Civil Engineering curricula in the framework of the European Higher Education Area (EHEA) by using practical trips

The engineer must have sufficient theoretical knowledge to be applied to solve specific problems, with the necessary capacity to simplify these approaches, and taking into account factors such as speed, simplicity, quality and economy. In Geology, its ultimate goal is the exploration of the history of the geological events through observation, deduction, reasoning and, in exceptional cases by the direct underground exploration or experimentation. Experimentation is very limited in Geology. Reproduction laboratory of certain phenomena or geological processes is difficult because both time and space become a large scale. For this reason, some Earth Sciences are in a nearly descriptive stage whereas others closest to the experimental, Geophysics and Geochemistry, have assimilated progress experienced by the physics and chemistry. Thus, Anglo-Saxon countries clearly separate Engineering Geology from Geological Engineering, i.e. Applied Geology to the Geological Engineering concepts. Although there is a big professional overlap, the first one corresponds to scientific approach, while the last one corresponds to a technological one. Applied Geology to Engineering could be defined as the Science and Applied Geology to the design, construction and performance of engineering infrastructures in and field geology discipline. There has been much discussion on the primacy of theory over practice. Today prevails the exaggeration of practice, but you get good workers and routine and mediocre teachers. This idea forgets too that teaching problem is a problem of right balance. The approach of the action lines on the European Higher Education Area (EHEA) framework provides for such balance. Applied Geology subject represents the first real contact with the physical environment with the practice profession and works. Besides, the situation of the topic in the first trace of Study Plans for many students implies the link to other subjects and topics of the career (tunnels, dams, groundwater, roads, etc). This work analyses in depth the justification of such practical trips. It shows the criteria and methods of planning and the result which manifests itself in pupils. Once practical trips experience developed, the objective work tries to know about results and changes on student’s motivation in learning perspective. This is done regardless of the outcome of their knowledge achievements assessed properly and they are not subject to such work. For this objective, it has been designed a survey about their motivation before and after trip. Survey was made by the Unidad Docente de Geología Aplicada of the Departamento de Ingeniería y Morfología del Terreno (Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos, Universidad Politécnica de Madrid). It was completely anonymous. Its objective was to collect the opinion of the student as a key agent of learning and teaching of the subject. All the work takes place under new teaching/learning criteria approach at the European framework in Higher Education. The results are exceptionally good with 90% of student’s participation and with very high scores in a number of questions as the itineraries, teachers and visited places (range of 4.5 to 4.2 in a 5 points scale). The majority of students are very satisfied (average of 4.5 in a 5 points scale).

The interaction of economic and pedagogical ideals in the context of workplace learning in Germany: a framework for empirical research – inspired by business ethics

As an effect of marketisation, the importance of workplace learning in Germany has increased. The article follows up on the long-standing discourse around the question of how economic and pedagogical ideals interact in this context. In order to develop a theoretical framework for empirical research, three major positions of the discipline of business ethics are introduced. Business ethics in more abstract ways deals with the very same question, namely how do ideas such as profit orientation interact with other norms and values? The new perspectives show that the discourse has been hitherto based on a specific understanding of economy. In order to derive an empirical answer to the research question, the question is re-formulated as follows: Which values are inherent in the decisions taken? Consequently, it suggests using the concept of ‘rationalities of justification’ for empirical research. The article shows how this concept can be applied by conducting a test run. (DIPF/Orig.)

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.

A PHENOMENOLOGY OF MIMETIC LEARNING AND MULTIMODAL COGNITION: INTEGRATING EXPERIENTIAL KNOWLEDGE INTO PROGRAMS IN RHETORIC, COMPOSITION, AND TECHNICAL COMMUNICATION

My dissertation emphasizes a cognitive account of multimodality that explicitly integrates experiential knowledge work into the rhetorical pedagogy that informs so many composition and technical communication programs. In these disciplines, multimodality is widely conceived in terms of what Gunther Kress calls “socialsemiotic” modes of communication shaped primarily by culture. In the cognitive and neurolinguistic theories of Vittorio Gallese and George Lakoff, however, multimodality is described as a key characteristic of our bodies’ sensory-motor systems which link perception to action and action to meaning, grounding all communicative acts in knowledge shaped through body-engaged experience. I argue that this “situated” account of cognition – which closely approximates Maurice Merleau-Ponty’s phenomenology of perception, a major framework for my study – has pedagogical precedence in the mimetic pedagogy that informed ancient Sophistic rhetorical training, and I reveal that training’s multimodal dimensions through a phenomenological exegesis of the concept mimesis. Plato’s denigration of the mimetic tradition and his elevation of conceptual contemplation through reason, out of which developed the classic Cartesian separation of mind from body, resulted in a general degradation of experiential knowledge in Western education. But with the recent introduction into college classrooms of digital technologies and multimedia communication tools, renewed emphasis is being placed on the “hands-on” nature of inventive and productive praxis, necessitating a revision of methods of instruction and assessment that have traditionally privileged the acquisition of conceptual over experiential knowledge. The model of multimodality I construct from Merleau-Ponty’s phenomenology, ancient Sophistic rhetorical pedagogy, and current neuroscientific accounts of situated cognition insists on recognizing the significant role knowledges we acquire experientially play in our reading and writing, speaking and listening, discerning and designing practices.