Exploring sketches as conceptual data: a semiological experiment on moods visualisation among architectural students

PurposeSketching is a creative skill that most architects develop over their long period of study and is considered an effective medium for communicating imaginative thinking and conceptual ideas in architecture. As a concept, mood is generally associated with imagining specific ambiance and spatial experience during the schematic phase of the architectural design process. While most architectural research on mood revolves around post-occupancy evaluation, colour effect and lighting comfort, few studies have been conducted to systematically investigate conceptual issues related to mood imagination. Besides, there has been little attempt to appreciate sketches as a reliable conceptual data source for architectural research.Design/methodology/approachTo bridge this knowledge gap, this paper explores a semiological analysis of mood visualisation using architectural sketches. By framing the experiment within the architecture education context, the paper begins by discussing the relationship between sketching, mood and semiology in architecture. The discussion continues by highlighting methodological issues in the design of our experiment. The experiment comprised architecture students from undergraduate and postgraduate programmes. Following the visual and textual data derived from the experiment, two semiological analyses, namely, mood sign analysis and mood signifier analysis, were conducted to understand their imaginative thinking.FindingsThe results revealed significant preferential differences between the students on the use of specific semiotic representation and design language to conceptualise their mood idea.Originality/valueAs a preliminary experiment, this study constitutes an early attempt to further explore potential research related to architectural sketches and the creative imagination that may be beneficial to designers, art psychologists, educators and researchers alike.

Using the QR code as a means of automating the process of accounting for attendance at educational classes

Nowadays, the technology of QR codes is one of the promising areas of development of the IT industry, which has found application in various industries, business areas, medicine, etc. In the field of education, QR codes are used to increase the interactivity of classes, provide additional multimedia content, conduct surveys and other control activities. This work presents the key features of QR codes, their architecture and main components. The use of QR codes in automating the process of accounting for students’ attendance is considered. A web application has been developed for teachers, the interface of which allows them to generate QR codes for academic disciplines. A mobile application with an integrated QR-code scanner was developed for students. All attendance data is recorded in the teacher’s electronic attendance register. A conceptual data model of the system is presented, as well as the main algorithms of its operation related to the generation and scanning of QR codes. The practice of using the developed system demonstrates the effectiveness of monitoring attendance data by promptly entering it into an electronic journal.

The Comparison of Education System in Australia and Indonesia

The education system is a method for directing the educational process. All aspects of learning must be regulated by the educational system. Because each country has a unique system, it is necessary to compare the education system in Indonesia to that of other countries in order to assess and evaluate it. This paper aims to explain and analyze differences in educational systems; and comparing the basic education curricula in Indonesia and Australia. This research is conceptual. Data collection methods are books, the internet, and journals. The study analysis was carried out by collecting and analyzing information about the education system in Indonesia and Australia. The results of the study show that: (1) Australia requires children to study for 10 years, while in Indonesia for 12 years, Australia holds a NAPLAN test and Indonesia holds a NE, and teacher qualifications must be undergraduate in Australia and Indonesia; (2) differences in the education system, among others, the level of material difficulty, assessment, rewards, learning atmosphere, teaching staff, education staff, and religious subjects; and (3) the curriculum in Indonesia has a relationship between education, customs, arts, and religions, meanwhile, the Australian curriculum is designed to support students to be successful, active, well-off and knowledgeable.

Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems

The COVID-19 pandemic made its mark on the entire world, upending economies, shifting work and education, and exposing deeply rooted inequities. A particularly vulnerable, yet less studied population includes our youngest children, ages zero to five, whose proximal and distal contexts have been exponentially affected with unknown impacts on health, education, and social-emotional well-being. Integrated administrative data systems could be important tools for understanding these impacts. This article has three aims to guide research on the impacts of COVID-19 for this critical population using integrated data systems (IDS). First, it presents a conceptual data model informed by developmental-ecological theory and epidemiological frameworks to study young children. This data model presents five developmental resilience pathways (i.e. early learning, safe and nurturing families, health, housing, and financial/employment) that include direct and indirect influencers related to COVID-19 impacts and the contexts and community supports that can affect outcomes. Second, the article outlines administrative datasets with relevant indicators that are commonly collected, could be integrated at the individual level, and include relevant linkages between children and families to facilitate research using the conceptual data model. Third, this paper provides specific considerations for research using the conceptual data model that acknowledge the highly-localised political response to COVID-19 in the US. It concludes with a call to action for the population data science community to use and expand IDS capacities to better understand the intermediate and long-term impacts of this pandemic on young children.

Functions of units, scales and quantitative data: Fundamental differences in numerical traceability between sciences

Quantitative data are generated differently. To justify inferences about real-world phenomena and establish secured knowledge bases, however, quantitative data generation must follow transparent principles applied consistently across sciences. Metrological frameworks of physical measurement build on two methodological principles that establish transparent, traceable—thus reproducible processes for assigning numerical values to measurands. Data generation traceability requires implementation of unbroken, documented measurand-result connections to justify attributing results to research objects. Numerical traceability requires documented connections of the assigned values to known quantitative standards to establish the results' public interpretability. This article focuses on numerical traceability. It explores how physical measurement units and scales are defined to establish an internationally shared understanding of physical quantities. The underlying principles are applied to scrutinise psychological and social-science practices of quantification. Analyses highlight heterogeneous notions of ‘units’ and ‘scales’ and identify four methodological functions; they serve as (1) ‘instruments’ enabling empirical interactions with study phenomena and properties; (2) structural data format; (3) conceptual data format; and (4) conventionally agreed reference quantities. These distinct functions, employed in different research stages, entail different (if any) rationales for assigning numerical values and for establishing their quantitative meaning. The common numerical recoding of scale categories in tests and questionnaires creates scores devoid of quantitative information. Quantitative meaning is created through numeral-number conflation and differential analyses, producing numerical values that lack systematic relations to known quantity standards regarding the study phenomena and properties. The findings highlight new directions for the conceptualisation and generation of quantitative data in psychology and social sciences.

Web Interoperability for Ontology Development and Support with crowd 2.0

In this work, we treat web interoperability in terms of interchanging ontologies (as knowledge models) within user-centred ontology engineering environments, involving visual and serialised representations of ontologies. To do this, we deal with the tool interoperability problem by re-using an enough expressive ontology-driven metamodel, named KF, proposed as a bridge for interchanging both knowledge models. We provide an extensible web framework, named crowd 2.0, unifying the standard conceptual data modelling languages for generating OWL 2 ontologies from semantic visualisations. Visual models are designed as UML, ER or ORM 2 diagrams, represented as KF instances, and finally, formalised as DL-based models. Reasoning results may be newly incorporated into the shared KF instance to be visualised in any of the provided languages.