Television history: archives, excavation and the future. A discussion

This article considers possible futures for television (TV) studies, imagining how the discipline might evolve more productively over the next 10 years and what practical steps are necessary to move towards those outcomes. Conducted as a round-table discussion between leading figures in television history and archives, the debate focuses on the critical issue of archives, considering and responding to questions of access/inaccessibility, texts/contexts, commercial/symbolic value, impact and relevance. These questions reflect recurrent concerns when selecting case studies for historical TV research projects: how difficult is it to access the material (when it survives)? What obstacles might be faced (copyright, costs, etc.) when disseminating findings to a wider public? The relationship between the roles of ‘researcher’ and ‘archivist’ appears closer and more mutually supportive in TV studies than in other academic disciplines, with many people in practice straddling the traditional divide between the two roles, combining specialisms that serve to further scholarship and learning as well as the preservation of, and broad public engagements with, collections. The Research Excellence Framework’s imperative for academic researchers to achieve ‘impact’ in broader society encourages active and creative collaboration with those based in public organizations, such as the British Film Institute (BFI), who have a remit to reach a wider public. The discussion identifies various problems and successes experienced in collaboration between the academic, public and commercial sectors in the course of recent and ongoing research projects in TV studies.

Cooperative or collaborative learning: Is there a difference in university students’ perceptions?

The hypothesis that the same educational objective, raised as cooperative or collaborative learning in university teaching does not affect students’ perceptions of the learning model, leads this study. It analyses the reflections of two students groups of engineering that shared the same educational goals implemented through two different methodological active learning strategies: Simulation as cooperative learning strategy and Problem-based Learning as a collaborative one. The different number of participants per group (eighty-five and sixty-five, respectively) as well as the use of two active learning strategies, either collaborative or cooperative, did not show differences in the results from a qualitative perspective.

Handmade Education : Interactive Food for Children`s Learning

Back to the early age of human history, Human thought of food as any substance that provides nutrition for the body. Man needed to hunt animals for food. Nowadays, Food is consumed not just to stop hunger of the body, but it also feeds the souls. Food has already been used for many other objectives apart from eating such as for artistic creations and creative marketing campaigns. Likewise, this research will also show a new perspective of food – Food as an educational material for children.

Copying to be Different: Violent Dissident Irish Republican Learning

While the impact of the Troubles retains centrality within much of Northern Irish political life, the spectre of almost daily violence is becoming a more distant memory. Peace has come to the region. In spite of this, however, there are those who wish to maintain the utility of violence to achieve their stated aims. Most dominant amongst these are the violent dissident republican groups. No longer is their existence solely defined by their desire to bring about a united Ireland. In order to have any opportunity of longevity, they must first legitimise their continued existence, and in turn distance themselves from their former Provisional comrades. This paper assesses how groups, such as the Continuity IRA, Óglaigh na hÉireann and the IRA/New IRA utilise the lessons learned from their Provisional history to differentiate themselves from the politicised dominance of Sinn Féin. This evaluation is carried out through the analysis of interviews with leadership and rank and file members of both political and paramilitary dissident groupings, which is complimented by the analysis of the Violent Dissident Republican (VDR) events database. These sources are supplemented with the assessment of organisational statements, from 2007 to the present day. The article focuses on violent, and non-violent, learning.

Cultural and linguistic context and lexical inferencing in English language learning: A case study

In an increasingly multilingual world, English language has kept a marked predominance as a global language. In many countries, English is the primary choice for foreign language learning. There is a long history of research in English language learning. The same applies for research in reading. A main interest since the 1970s has been the reading strategy defined as inferencing or guessing the meaning of unknown words from context. Inferencing has ben widely researched, however, the results and conclusions seem to be mixed. While some agree that inferencing is a useful strategy, others doubt its usefulness. Nevertheless, most of the research seem to agree that the cultural background affects comprehension and inferencing. While most of these studies have been done with texts and contexts created by the researches, little has been done using natural prose. The present study will attempt to further clarify the process of inferencing and the effects of the text’s cultural context and the linguistic background of the reader using a text that has not been created by the researcher. The participants of the study are 40 international students from Turku, Finland. Their linguistic background was obtained through a questionnaire and proved to be diverse. Think aloud protocols were performed to investigate their inferencing process and find connections between their inferences, comments, the text, and their linguistic background. The results show that: some inferences were made based on the participants’ world knowledge, experience, other languages, and English language knowledge; other inferences and comments were made based on the text, its use of language and vocabulary, and few cues provided by the author. The results from the present study and previous research seem to show that: 1) linguistic background is a source of information for inferencing but is not a major source; 2) the cultural context of the text affected the inferences made by the participants according to their closeness or distance from it.

Re-viewing history: antiquaries, the graphic arts and Scotland's lost geographies, c.1660-1820

This thesis examines topographical art depicting Scotland’s natural scenery and built environments, architecture, antiquities and signs of modern improvement, made during the period 1660 to 1820. It sets out to demonstrate that topography and topographical art was not exclusively antiquarian in nature, but ranged across various fields of learning and practice. It included the work of artists, geographers, cartographers, travel writers, poets, landscape gardeners, military surveyors, naturalists and historians who were concerned with representing the country’s varied, and often contentious, histories within an increasingly modernising present. The visual images that are considered here were forms of knowledge that found expression in drawings, paintings and engravings, elevations, views and plans. They were made on military surveys and picturesque tours, and were often intended to be included alongside written texts, both published and unpublished, frequently connecting with travels, tours, memoirs, essays and correspondence. It will also be argued that topography was a social practice, involving networks of artists, collectors, publishers and writers, who exchanged information in drawings and letters in a nationwide, and often increasingly commercial enterprise. This thesis will explore some of the strands of such a vast network of picture-making that existed in Scotland, and Britain, between 1660 and 1820, as visual images were circulated, copied, recycled and adapted, and topographical and antiquarian visual culture emerges as a complex, synoptic form of inquiry.

Geography, History and Natural Sciences: an interdisciplinary teaching approach with GIS

Geographic Information System (GIS) is a technology that deals with location to support better representations and decision making. It has a long tradition in several planning areas, such as urbanism, environment, riskiness, transportation, archeology or tourism. In academics context higher education has followed that evolution. Despite of their potentialities in education, GIS technologies at the elementary and secondary have been underused. Empowering graduates to learn with GIS and to manipulate spatial data can effectively facilitate the teaching of critical thinking. Likewise it has been recognized that GIS tools can be incorporated as an interdisciplinary pedagogical tool. Nevertheless more practical examples on how GIS tools can enhance teaching and learning process, namely to promote interdisciplinary approaches. The proposed paper presents some results obtained from the project “Each thing in its place: the science in time and space”. This project results from the effort of three professors of Geography, History and Natural Sciences in the context of Didactics of World Knowledge curricular unit to enhance interdisciplinarity through Geographic Information Technologies (GIT). Implemented during the last three years this action-research project developed the research practice using GIS to create an interdisciplinary attitude in the future primary education teachers. More than teaching GIS the authors were focused on teaching with GIS to create an integrated vision where spatial data representation linked the space, the time and natural sciences. Accumulated experience reveals that those technologies can motivate students to learn and facilitating teacher’s interdisciplinary work.

Learning to construct our identities over the life course: a study with lesbian, gay, bisexual and transgender adults in Scotland

To date, adult educational research has had a limited focus on lesbian, gay, bisexual and transgendered (LGBT) adults and the learning processes in which they engage across the life course. Adopting a biographical and life history methodology, this study aimed to critically explore the potentially distinctive nature and impact of how, when and where LGBT adults learn to construct their identities over their lives. In-depth, semi-structured interviews, dialogue and discussion with LGBT individuals and groups provided rich narratives that reflect shifting, diverse and multiple ways of identifying and living as LGBT. Participants engage in learning in unique ways that play a significant role in the construction and expression of such identities, that in turn influence how, when and where learning happens. Framed largely by complex heteronormative forces, learning can have a negative, distortive impact that deeply troubles any balanced, positive sense of being LGBT, leading to self- censoring, alienation and in some cases, hopelessness. However, learning is also more positively experiential, critically reflective, inventive and queer in nature. This can transform how participants understand their sexual identities and the lifewide spaces in which they learn, engendering agency and resilience. Intersectional perspectives reveal learning that participants struggle with, but can reconcile the disjuncture between evolving LGBT and other myriad identities as parents, Christians, teachers, nurses, academics, activists and retirees. The study’s main contributions lie in three areas. A focus on LGBT experience can contribute to the creation of new opportunities to develop intergenerational learning processes. The study also extends the possibilities for greater criticality in older adult education theory, research and practice, based on the continued, rich learning in which participants engage post-work and in later life. Combined with this, there is scope to further explore the nature of ‘life-deep learning’ for other societal groups, brought by combined religious, moral, ideological and social learning that guides action, beliefs, values, and expression of identity. The LGBT adults in this study demonstrate engagement in distinct forms of life-deep learning to navigate social and moral opprobrium. From this they gain hope, self-respect, empathy with others, and deeper self-knowledge.

e-Math Workshops : a forum for exchanging experiences of mathematics e-learning at university level

We report here about a series of international workshops on e-learning of mathematics at university level, which have been jointly organized by the three publicly funded open universities in the Iberian Peninsula and which have taken place annually since 2009. The history, achievements and prospects for the future of this initiative will be addressed.

Community School of São Miguel de Machede: A decade of Learning

the Community School of São Miguel de Machede exists since 1998. A model of Community Education has been developed in this decade of existence, which not being confined to the frequent profiles of the most common approaches in Adult Education, has been the result of a process of symbiosis between a practice that normally precedes the conceptualization and a thought which has always expressed the concern of interpreting and enrich that practice. Setting on a model of learning based on the PADéCA – Program of Helping the Development of the Capacity to Learn, proposed by Berbaum (1988), the Community School of São Miguel de Machede has been developing several activities centred on a fundamental concern: to create easy and qualified accesses, in this community (council of Evora), so that the respective members can learn to exercise their principal rights of citizenship, in the territory where they live and in a circumstance of equality of opportunities in relation to the remaining fellow countrymen. Being a project with a decade of life, it is now possible to speak of a history full of stories and learning experiences, which occurred as a result of a rich interaction between the initial thoughts and impulses of the theoretical approaches and a reality full of unexpectedness, mutability and humanity resulting from the complexity that a living community presents, with a history and a present, but not always with clear and positive idea about the respective future.

DIGITAL HISTORY: DESIGNING VIRTUAL ENVIRONMENTS THAT SUPPORT CRITICAL THINKING AND IDEA EXCHANGE, MOTIVATE AND ENGAGE USERS

Thesis (Master, Education) -- Queen's University, 2016-08-29 15:56:53.748

Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare

The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

Detecting social patterns within 20th century documentary photos: a deep learning based approach

The job of a historian is to understand what happened in the past, resorting in many cases to written documents as a firsthand source of information. Text, however, does not amount to the only source of knowledge. Pictorial representations, in fact, have also accompanied the main events of the historical timeline. In particular, the opportunity of visually representing circumstances has bloomed since the invention of photography, with the possibility of capturing in real-time the occurrence of a specific events. Thanks to the widespread use of digital technologies (e.g. smartphones and digital cameras), networking capabilities and consequent availability of multimedia content, the academic and industrial research communities have developed artificial intelligence (AI) paradigms with the aim of inferring, transferring and creating new layers of information from images, videos, etc. Now, while AI communities are devoting much of their attention to analyze digital images, from an historical research standpoint more interesting results may be obtained analyzing analog images representing the pre-digital era. Within the aforementioned scenario, the aim of this work is to analyze a collection of analog documentary photographs, building upon state-of-the-art deep learning techniques. In particular, the analysis carried out in this thesis aims at producing two following results: (a) produce the date of an image, and, (b) recognizing its background socio-cultural context,as defined by a group of historical-sociological researchers. Given these premises, the contribution of this work amounts to: (i) the introduction of an historical dataset including images of “Family Album” among all the twentieth century, (ii) the introduction of a new classification task regarding the identification of the socio-cultural context of an image, (iii) the exploitation of different deep learning architectures to perform the image dating and the image socio-cultural context classification.

Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.