Heathcote’s practice-led teaching: Pioneering research as well as pioneering pedagogy

It is widely recognized that Dorothy Heathcote was a dynamic and radical teacher who transformed and continually reinvented drama teaching. She did this by allowing her emerging thinking and understandings to flow from, and be tested by, regular and intensive ‘practicing’ in the classroom. In this way theoretical claims were grounded and evidenced in authentic classroom practice. And yet, for all her impact, it is rare to hear the claim that Heathcote’s pedagogic breakthroughs resulted from a legitimate research methodology. Clever and charismatic teaching yes; research no. One of the world’s best teachers certainly, but not a researcher; even though every lesson was experimental and every classroom was a site for discovery. This paper investigates that conundrum firstly by acknowledging that Heathcote’s practice-led teaching approach to discovery did not map comfortably on to the established educational research traditions of the day. It argues that traditional research methodologies, with their well-established protocols and methods, could not understand or embrace a research process which does its work by creating ‘fictional realities’ of openness, allegory and uncertainty. In recent years however it can be seen that Heathcote’s practice led-teaching, so essential for advancing the field, closely aligns with what many contemporary researchers are now calling practice-led research or practice as research or, in many Nordic countries, artistic research. A form of performative research, practice-led research has not emerged from the field of education but rather from the creative arts. Seeking to develop ways of researching creative practice which is deeply sympathetic and respectful of that practice, artist-researchers have developed practice-led research “which is initiated in practice, where questions, problems, challenges are identified and formed by the needs of practice and practitioners” (Grey, 1996). This sits comfortably with Heathcote’s classroom priority of “discovering by trial, error and testing; using available materials with respect for their nature, and being guided by this appreciation of their potential” (Heathcote, 1967). The paper will conclude by testing the dynamics of Heathcote’s practice-led teaching against the six conditions of practice-led research (Haseman&Mafe, 2011), a testing which will allow for a re-interpretation and re-housing of Dorothy Heathcote’s classroom-based teaching methodology as a form of performative research in its own right.

Supporting knowledge-intensive construction management tasks in BIM

The delivery of products and services for construction-based businesses is increasingly becoming knowledge-driven and information-intensive. The proliferation of building information modelling (BIM) has increased business opportunities as well as introduced new challenges for the architectural, engineering and construction and facilities management (AEC/FM) industry. As such, the effective use, sharing and exchange of building life cycle information and knowledge management in building design, construction, maintenance and operation assumes a position of paramount importance. This paper identifies a subset of construction management (CM) relevant knowledge for different design conditions of building components through a critical, comprehensive review of synthesized literature and other information gathering and knowledge acquisition techniques. It then explores how such domain knowledge can be formalized as ontologies and, subsequently, a query vocabulary in order to equip BIM users with the capacity to query digital models of a building for the retrieval of useful and relevant domain-specific information. The formalized construction knowledge is validated through interviews with domain experts in relation to four case study projects. Additionally, retrospective analyses of several design conditions are used to demonstrate the soundness (realism), completeness, and appeal of the knowledge base and query-based reasoning approach in relation to the state-of-the-art tools, Solibri Model Checker and Navisworks. The knowledge engineering process and the methods applied in this research for information representation and retrieval could provide useful mechanisms to leverage BIM in support of a number of knowledge intensive CM/FM tasks and functions.

[R_Clavijo_SanPrudencio] Intensive Program ERASMUS: TOPCART. Geometric Documentation of the Heritage (report of activities 2010-2011)

[EN] Data contained in this record come from the following accademic activity (from which it is possible to locate additional records related with the Monastery):

Intensive Program ERASMUS: TOPCART. Geometric Documentation of the Heritage (administrative and academic documentation)

[EN] This academic activity has been the origin of other work that are also located in this repository. The first one is the dataset of information about the geometry of the Monastery recorded during the two years of fieldwork, then some bachelor thesis and papers are listed:

Playful structure: a novel image of early years pedagogy for primary school classrooms

Playful structure is a new pedagogic image representing a more balanced and integrated perspective on early years pedagogy, aiming to blend apparent dichotomies and contradictions and to sustain and evolve play-based practice beyond Year 1. Playful structure invites teachers and children to initiate and maintain a degree of playfulness in the child’s whole learning experience, even when the learning intentions demand a supportive structure. Thus, playfulness becomes characteristic of the interaction between adult and the child and not just characteristic of child-initiated versus adult-initiated activities, or of play-time versus task-time. The paper is based on intensive observations and interviews with teachers in Northern Ireland who participated in a play-based and informal curriculum. This paper explains how playful structure rests on complementary processes of infusion of structure into play-based activities and infusion of playfulness into more structured activities, illustrated by cameos. ‘Infusion’ suggests the subtle blending process that allows apparent dichotomies and contradictions to be resolved in practice.

Knowledge representation for data integration and exploration in translational medicine

Tese de doutoramento, Informática (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2014

Relocating the personal : a critical writing pedagogy

Addressing the current and growing interest in the personal, the self, and the autobiographical not only in the teaching of writing, but also across many disciplinary and subject fields, Relocating the Personal describes a rich array of practical approaches to teaching the personal in settings where it has been excluded." "The author argues for the teaching of writing as a political project in schools and communities, and for a notion of the personal which is not simply equated with voice. The construct of narrative is preferred, because it allows teachers to examine all personal writing as a representation and not the same thing as the writer's life. Strategies are developed for examining how experience is portrayed and how it might be written differently, with material effects on both the personal text and the writer's person.

The book incorporates the latest theories of critical and genre literacy as it develops four teaching cases in different education contexts (secondary, undergraduate, graduate, and adult/community).

Knowing schooling, identity and pedagogy visually

This research produced in one region in Ghana examines the production of educational practices, relations of power and student experiences within teaching and non-teaching spaces in junior secondary settings. The strength of the visual approach in interrogating school cultural norms and the problematising of the tangled complexities of knowing about schooling, identity and pedagogy are outlined. An important aspect of the study is the foregrounding of educational practice as a social act occurring in response to historical circumstances and changing social contexts (Brown & Jones, 2001). We see this work as an important step towards democratization of the research relationship and empowerment of students to contribute to the way they are educated. But also we are wary of how representation through visual methods also can 'frame' participants and the researchers. We recognise that one way to uncover how school practices are exemplified in Ghana is to put students in the middle of researching their experiences. In this way, our research moved from constructing students as simply consumers of adult designed and managed products to practices based on democratic participation (Thomson & Gunter, 2007). Throughout the research journey we were guided by the fact that knowledge is not neutral or to be discovered. Culture and communicative processes are essential determinants of reality. In this study the students as researchers, produced photographs that trigger dialectical conversations of students’ perspectives that foreground their experiences at school. This enabled us to digress from dominant positivistic empiricism to a more legitimate ethical practice, and understanding of the intricacies of educational practice, the norms and structures that underpin everyday actions in schools.

The role of representation in teaching and learning ideas about matter

The research described in this paper is designed around the notion that learning involves the recognition and development of students’ representational resources. This paper describes a classroom sequence in Ideas about Matter that focuses on representations and their negotiation, and reports on the effectiveness of this perspective in guiding teaching, and in providing further insight into student learning. Classroom sequences involving two experienced teachers (2008, Year 8 students) and an inexperienced teacher (2010, Year 7 students) were videotaped using a combined focus on the teacher and groups of students. Video analysis software was used to code the variety of representations used teachers and students, and sequences of representational negotiation. The paper reports on the effect of this approach on teacher pedagogy and on student learning of Ideas about Matter. The paper will present data from video of classroom activities, students’ work samples, student and teacher interviews and pre and post-unit testing, to explore what a representational focus might entail in teaching Ideas about Matter, and the role of representations in learning and reasoning and exploring scientific ideas.

Learning through the affordances of representation construction

In this chapter we draw upon several theoretical perspectives and past research into language and learning in science, to develop a framework to characterize how and why student engagement in representation construction practices supports learning in science.

The `knowledge-intensive development' agenda and equitable access to knowledge: higher education in Ethiopia

In light of the normative assumption of the role of knowledge in economic productivity and in response to strong exogenous policy orientations (mainly from the World Bank), the government of Ethiopia has restructured and expanded the higher education (HE) subsystem since the late 1990s. In critically analysing selected policy documents, this article seeks to understand the seemingly unlinked agendas of strengthening the role of HE in supporting the knowledge-intensive development agenda and the representation of the problem of inequality in access to and success in HE. It has been shown that the economic value of knowledge has been echoed in the reforms of Ethiopia, and that the problem of inequality has been superficially represented just as inequality of access while serious challenges that hinder participation and success of women, non-traditional students and ethnically and regionally disadvantaged groups remain unchallenged. Hence, the analysis indicates that under a situation of unequal opportunity to knowledge, the knowledge-intensive development agenda appears to be empty policy rhetoric.

Deconstructing religious identity, difference, and belonging : implications for anti-racist pedagogy

Increasing numbers of Australians identify with a multiplicity of religion groups or have no religious affiliation. Despite this, the representation of religious groups other than Christian—and the implications of this for anti-racist pedagogy in Australian schools—is seldom explored. This article interrogates the ways in which the most prominent of these minority religious groups (Buddhist, Hindu, Muslim, Jewish) were spoken about in two Melbourne newspapers and considers the implications of this interrogation for multicultural pedagogy in globally integrated local school contexts, such as those in Australia. Methodologies of social cultural theory and critical discourse analysis (CDA) are used to investigate newspaper discussions from the different viewpoints of their experiential, systemic, and normative focus. I find that notions of religious identity described in the media are stylized in form and an almost-silent normative self-identity is defined against clichéd typologies made within a crucible of race, identity, and belonging.

Visual communication design as a form of public pedagogy

This paper identifies visual communication design as a form of public pedagogy. Communication design practices aim to achieve the successful transmission of a message to a recipient in a visual mode. Understanding the theories and practices of visual communication design can assist in enhancing the reception of the communication, as these practices become a tool to increase the effectiveness of learning in a public space. To demonstrate this, I will use the example of museums as an informal place of public learning, and argue design, and in particular visual communication design strategies, are extremely important in the creation of successful learning. If participants are not engaged or entertained, their capacity for learning will diminish. Engagement depends on the representation of the information and the successful interpretation of that information by the visitor. Further, this paper will emphasize the vital role communication design plays in all forms of public pedagogy, not just within the museum context. However, non-designers create many public learning environments and although this paper argues the benefits of communication design to increasing the effectiveness of learning, it recognizes the narrow opportunities of applying this knowledge.

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Electronic medical record (EMR) offers promises for novel analytics. However, manual feature engineering from EMR is labor intensive because EMR is complex - it contains temporal, mixed-type and multimodal data packed in irregular episodes. We present a computational framework to harness EMR with minimal human supervision via restricted Boltzmann machine (RBM). The framework derives a new representation of medical objects by embedding them in a low-dimensional vector space. This new representation facilitates algebraic and statistical manipulations such as projection onto 2D plane (thereby offering intuitive visualization), object grouping (hence enabling automated phenotyping), and risk stratification. To enhance model interpretability, we introduced two constraints into model parameters: (a) nonnegative coefficients, and (b) structural smoothness. These result in a novel model called eNRBM (EMR-driven nonnegative RBM). We demonstrate the capability of the eNRBM on a cohort of 7578 mental health patients under suicide risk assessment. The derived representation not only shows clinically meaningful feature grouping but also facilitates short-term risk stratification. The F-scores, 0.21 for moderate-risk and 0.36 for high-risk, are significantly higher than those obtained by clinicians and competitive with the results obtained by support vector machines.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.