Supporting Human Cognitive Writing Processes: Towards a Taxonomy of Writing Support Systems

In the field of natural language processing (NLP), advances in transformer architectures and large-scale language models have led to a plethora of designs and research on a new class of information systems (IS) called writing support systems, which help users plan, write, and revise their texts. Despite the growing interest in writing support systems in research, there needs to be more common knowledge about the different design elements of writing support systems. Our goal is, therefore, to develop a taxonomy to classify writing support systems into three main categories (technology, task/structure, and user). We evaluated and refined our taxonomy with seven interviewees with domain expertise, identified three clusters in the reviewed literature, and derived five archetypes of writing support system applications based on our categorization. Finally, we formulate a new research agenda to guide researchers in the development and evaluation of writing support systems

Machine learning in critical care: state-of-the-art and a sepsis case study

Background: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challenge of an extremely quick transformation into data-driven sciences. This challenge entails the daunting task of extracting usable knowledge from these data using algorithmic methods. In the medical context this may for instance realized through the design of medical decision support systems for diagnosis, prognosis and patient management. The intensive care unit (ICU), and by extension the whole area of critical care, is becoming one of the most data-driven clinical environments. Results: The increasing availability of complex and heterogeneous data at the point of patient attention in critical care environments makes the development of fresh approaches to data analysis almost compulsory. Computational Intelligence (CI) and Machine Learning (ML) methods can provide such approaches and have already shown their usefulness in addressing problems in this context. The current study has a dual goal: it is first a review of the state-of-the-art on the use and application of such methods in the field of critical care. Such review is presented from the viewpoint of the different subfields of critical care, but also from the viewpoint of the different available ML and CI techniques. The second goal is presenting a collection of results that illustrate the breath of possibilities opened by ML and CI methods using a single problem, the investigation of septic shock at the ICU. Conclusion: We have presented a structured state-of-the-art that illustrates the broad-ranging ways in which ML and CI methods can make a difference in problems affecting the manifold areas of critical care. The potential of ML and CI has been illustrated in detail through an example concerning the sepsis pathology. The new definitions of sepsis and the relevance of using the systemic inflammatory response syndrome (SIRS) in its diagnosis have been considered. Conditional independence models have been used to address this problem, showing that SIRS depends on both organ dysfunction measured through the Sequential Organ Failure (SOFA) score and the ICU outcome, thus concluding that SIRS should still be considered in the study of the pathophysiology of Sepsis. Current assessment of the risk of dead at the ICU lacks specificity. ML and CI techniques are shown to improve the assessment using both indicators already in place and other clinical variables that are routinely measured. Kernel methods in particular are shown to provide the best performance balance while being amenable to representation through graphical models, which increases their interpretability and, with it, their likelihood to be accepted in medical practice.Peer ReviewedPostprint (published version

A multilevel graph approach for IoT-based complex scenario management through situation awareness and semantic approaches

Modern reality and the environments in which we live are characterized by technology components geared toward automatic management through pervasive services. Thanks to the advent of the Internet of Things, such environments can provide information such as pollution levels, public transport conditions, efficiency of energy distribution networks, and identification of suspicious activities by generating complex scenarios. The profitable management of such scenarios can be performed through context modeling and methodologies that can extract and understand environmental information by preventing certain events through artificial intelligence techniques by increasing Situation Awareness. This paper focuses on developing a methodology with predictive capabilities and context adaptability for managing complex scenarios. The use of semantic and graph-based approaches, unlike many approaches used, leads to better integration of knowledge, resulting in improved system performance. In addition, such approaches allow understanding of what is happening in the system at a given time, enabling manipulation and integration of semantic information. Graph-based approaches chosen for this purpose are Ontologies, Context Dimension Trees, and Bayesian Networks, which are able to support the end-user or expert user in handling complex scenarios. The proposed methodology has been validated and applied to real complex scenarios based on the IoT paradigm. The proposed approach validation was conducted using open data from the city of London; a practical scenario case study was conducted in the field of automated management of a Smart Home. In both cases, the system achieved promising results

Software is Scholarship

This Article provides the first systematic account and justification of software applications as works of scholarship. Software is scholarship to the extent that software functionality is derived from scholarly research, software is used as a means to develop scholarship, or software is used as a medium to communicate scholarly ideas. Software applications are superior to articles and books for communicating scholarly ideas because software is not limited by the constraints of traditional written works. Software can communicate using a wide variety of textual components, graphical elements, and programmable interactivity that significantly enhance the ability to communicate scholarly concepts, arguments, and findings. This Article identifies four methods for software applications to enhance scholarly communication: app-ified argumentation that provides theoretical clarity, interactive toolkits that create rich qualitative studies, data visualizations that persuade using data, and policy tech that improves the ability to enact social change. Interactive software applications can enhance research agendas in the humanities and social sciences by making traditional, prose scholarship more thorough, persuasive, and analytically precise. Due to recent innovations, developing software for scholarly purposes is accessible to those that work in the humanities. Platforms for developing software have grown so sophisticated that they no longer require creators to write code to develop powerful, data rich, and well-designed interactive applications. Scholars should accordingly use and develop software to better communicate their ideas. By providing a framework for developing software as works of scholarship, this Article contributes to the field of digital humanities. To better understand this Article’s concept of scholarly software, I apply my conceptualization of scholarly software to legal scholarship and legal technology and discuss three case studies: LegalTech toolkits, voice recognition for automated contract drafting, and court data visualizations. Law is a fertile ground for the development of scholarly software because the core of legal reasoning consists of a formalistic, computational structure that is well-expressed through programmable applications. This Article contributes to legal scholarship by identifying how it can be enhanced through the creation of software applications

Turn-by-wire: Computationally mediated physical fabrication

Advances in digital fabrication have simultaneously created new capabilities while reinforcing outdated workflows that constrain how, and by whom, these fabrication tools are used. In this paper, we investigate how a new class of hybrid-controlled machines can collaborate with novice and expert users alike to yield a more lucid making experience. We demonstrate these ideas through our system, Turn-by-Wire. By combining the capabilities of a traditional lathe with haptic input controllers that modulate both position and force, we detail a series of novel interaction metaphors that invite a more fluid making process spanning digital, model-centric, computer control, and embodied, adaptive, human control. We evaluate our system through a user study and discuss how these concepts generalize to other fabrication tools

Artificial Intelligence in Education

Artificial Intelligence (AI) technologies have been researched in educational contexts for more than 30 years (Woolf 1988; Cumming and McDougall 2000; du Boulay 2016). More recently, commercial AI products have also entered the classroom. However, while many assume that Artificial Intelligence in Education (AIED) means students taught by robot teachers, the reality is more prosaic yet still has the potential to be transformative (Holmes et al. 2019). This chapter introduces AIED, an approach that has so far received little mainstream attention, both as a set of technologies and as a field of inquiry. It discusses AIED’s AI foundations, its use of models, its possible future, and the human context. It begins with some brief examples of AIED technologies

TEACHING CAD PROGRAMMING TO ARCHITECTURE STUDENTS

[Ensino da Programação CAD para Estudantes de Arquitetura] O objetivo deste trabalho é discutir a relevância da inclusão de uma disciplina de programação de computadores no currículo de Graduação em Arquitetura e urbanismo. Ele começa explicando como a programação tem sido aplicada em outros contextos educacionais com grande sucesso pedagógico, e descrevendo os princípios de Papert. Em seguida, é apresentado um resumo da evolução do CAD e três exemplos históricos de aplicações da programação no ensino de arquitetura são apresentados, seguidos por um exemplo contemporâneo de grande relevância. Finalmente, é proposta uma metodologia para o ensino de programação para arquitetos, com o objetivo de melhorar a qualidade dos projetos, tornando os conceitos arquitetônicos mais explícitos. Essa metodologia é baseada na experiência da autora de ensino de programação para alunos do curso de graduação em arquitetura na Universidade Estadual de Campinas. O trabalho termina com uma discussão sobre o papel da programação nos dias de hoje, quando a maioria dos programas de CAD são amigáveis. Como conclusão, sugere-se que a introdução da programação no currículo de CAD, dentro de um arcabouço teórico apropriado, pode vir a transformar o conceito de ensino da arquitetura. Palavras-chave: Computer programming; computer-aided design; architectural education. ABSTRACT The objective of this paper is to discuss the relevance of including the discipline of computer programming in the architectural curriculum. To do so I start by explaining how computer programming has been applied in other educational contexts with pedagogical success, describing Seymour Papert's principles. After that, I summarize the historical development of CAD and provide three historical examples of educational applications of computer programming in architecture, followed by a contemporary case that I find of particular relevance. Next, I propose a methodology for teaching programming for architects that aims at improving the quality of designs by making their concepts more explicit. This methodology is based on my own experience teaching computer programming for architecture students at undergraduate and graduate levels at the State University of Campinas, Brazil. The paper ends with a discussion about the role of programming nowadays, when most CAD software are user-friendly and do not require any knowledge of programming for improving performance. I conclude that the introduction of programming in the CAD curriculum within a proper conceptual framework may transform the concept of architectural education. Key-words: Computer programming; computer-aided design; architectural education.The objective of this paper is to discuss the relevance of including the discipline of computer programming in the architectural curriculum. To do so I start by explaining how computer programming has been applied in other educational contexts with pedagogical success, describing Seymour Papert's principles. After that, I summarize the historical development of CAD and provide three historical examples of educational applications of computer programming in architecture, followed by a contemporary case that I find of particular relevance. Next, I propose a methodology for teaching programming for architects that aims at improving the quality of designs by making their concepts more explicit. This methodology is based on my own experience teaching computer programming for architecture students at undergraduate and graduate levels at the State University of Campinas, Brazil. The paper ends with a discussion about the role of programming nowadays, when most CAD software are user-friendly and do not require any knowledge of programming for improving performance. I conclude that the introduction of programming in the CAD curriculum within a proper conceptual framework may transform the concept of architectural education. Key-words: Computer programming; computer-aided design; architectural education