Studying the impact of COVID-19 on the European Air Transportation Network

The European Air Transportation Network was significantly impacted by the COVID-19 pandemic, resulting in an unprecedented loss of flight connections. Utilizing a combination of graph representation learning and time series analysis, this paper studies the evolution of both the global connectivity as well as the structure of the European Air Transportation Network from January 2020 to December 2022. Specifically, it finds strong differences in recovery rates for flights across six different market segments. In terms of network structure, the study finds that structural roles that are present in the pre-covid network have seen a loss in performance over the course of the pandemic, but have recovered to pre-covid levels. Using regional changes in structural roles, this study identifies Italy as the region with the strongest increase and the United Kingdom as the region with the strongest decrease in structural role, finding substantial differences in recovery rates per market segment. Lastly, this study pays special attention on the effect of the Russia-Ukrainian war on the European Air Transportation Network. © 2023 IEEE.

Characterizing the Entities in Harmful Memes: Who is the Hero, the Villain, the Victim?

Memes can sway people's opinions over social media as they combine visual and textual information in an easy-to-consume manner. Since memes instantly turn viral, it becomes crucial to infer their intent and potentially associated harmfulness to take timely measures as needed. A common problem associated with meme comprehension lies in detecting the entities referenced and characterizing the role of each of these entities. Here, we aim to understand whether the meme glorifies, vilifies, or victimizes each entity it refers to. To this end, we address the task of role identification of entities in harmful memes, i.e., detecting who is the 'hero', the 'villain', and the 'victim' in the meme, if any. We utilize HVVMemes - a memes dataset on US Politics and Covid-19 memes, released recently as part of the CONSTRAINT@ACL-2022 shared-task. It contains memes, entities referenced, and their associated roles: hero, villain, victim, and other. We further design VECTOR (Visual-semantic role dEteCToR), a robust multi-modal framework for the task, which integrates entity-based contextual information in the multi-modal representation and compare it to several standard unimodal (text-only or image-only) or multi-modal (image+text) models. Our experimental results show that our proposed model achieves an improvement of 4% over the best baseline and 1% over the best competing stand-alone submission from the shared-task. Besides divulging an extensive experimental setup with comparative analyses, we finally highlight the challenges encountered in addressing the complex task of semantic role labeling within memes. © 2023 Association for Computational Linguistics.

Studying dimensions of representation: introducing the Belgian RepResent panel (2019–2021)

This research note presents the RepResent Belgian Panel (RBP). The RBP is a voter panel survey consisting of four waves fielded to a sample of voters in Belgium around the May 2019 federal, regional, and European elections in Belgium. It provides unique data on about 250 variables for a quota sample of the same respondents, pre-2019 elections (N = 7351), post-2019 elections (N = 3909), one year after the elections (N = 1996), and 2 years after the elections (N = 1119). The RBP panel dataset was designed to analyse voters' political attitudes and behaviours, notably on different dimensions of democratic representation, and with a specific focus on democratic resentment (e.g. citizens' attitudes towards democracy such as distrust and alienation, but also behaviours such as abstention, protest, or voting for anti-establishment parties). Its longitudinal structure allows to explore the political dynamics at play in Belgium throughout the lengthy government formation process. Finally, the last two waves of the RBP were fielded during the Covid-19 pandemic, allowing to explore public opinion before and during this global crisis. The RBP should be of interest to scholars of public opinion and electoral studies. © 2023, The Author(s).

Towards Timeline Generation with Abstract Meaning Representation

Timeline summarization (TLS) is a challenging research task that requires researchers to distill extensive and intricate temporal data into a concise and easily comprehensible representation. This paper proposes a novel approach to timeline summarization using Meaning Representations (AMRs), a graphical representation of the text where the nodes are semantic concepts and the edges denote relationships between concepts. With AMR, sentences with different wordings, but similar semantics, have similar representations. To make use of this feature for timeline summarization, a two-step sentence selection method that leverages features extracted from both AMRs and the text is proposed. First, AMRs are generated for each sentence. Sentences are then filtered out by removing those with no named-entities and keeping the ones with the highest number of named-entities. In the next step, sentences to appear in the timeline are selected based on two scores: Inverse Document Frequency (IDF) of AMR nodes combined with the score obtained by applying a keyword extraction method to the text. Our experimental results on the TLS-Covid19 test collection demonstrate the potential of the proposed approach. © 2023 ACM.

What is behind the mask? Social representation of mask wearing

Background: During the COVID-19 pandemic, a preventive and widely mandatory use of face masks was a dominant segment of the infection prevention and control of the epidemic. Covering about 60-70% of the facial surface, face masks dramatically affect social interactions-especially emotion recognition, expression and mentalization. Difficulties in communication in the doctor-patient relationship become of paramount importance to the effectiveness of the healing work. This becomes even more critical when the patient suffers from a disorder characterized by a mentalization deficit. In our study, we use the theory of social representations to examine the contents with which mask wearing has become part of our everyday knowledge. Objectives: We aimed to explore the social representations of mask wearing considering its impact on interpersonal communication, in groups where the effectiveness of mutual understanding is critical. Methods: In our study, carried out during the second and third waves of the coronavirus epidemic in Hungary, we gave a free association task to the target word mask-wearing" in a group of medical doctors, and hospitalized somatic and psychiatric patients and healthy controls (total of 81 subjects, mean age 43.1 [13.83] years), then used the obtained associations to form semantic categories and to map the structure of social representations within the groups using a rank-frequency method. Results: The positive experience of safety and the negative experience of physiological discomfort caused by the facemasks were consistently central to the social representations of mask-wearing in all study groups. Differences were found between groups in terms of more mature elaborative categories, as well as anxiety, aggression, helplessness, damaged dependency needs, and forced conformity. Conclusions: The analysis of the social representations revealed ambivalent meanings of the mask wearing. Although there were significant differences in the structure of mask-related social representations, the mask was recognized as an "inconvenient but necessary" health protection measure in most of the groups studied. Based on the results, each group may be at risk in a different way or deal differently with the pandemic based on their specific representations. (PsycInfo Database Record (c) 2023 APA, all rights reserved) (Hungarian) Elmeleti hatter: A COVID-19-pandemia idejen a jarvanyugyi intezkedesek meghatarozo reszeve valt az arcmaszkok viselesenek preventiv es szeles koru alkalmazasa. Az arcmaszkok az arcfelulet mintegy 60-70%-at lefedve jelentosen befolyasoljak a szocialis interakciokat - kulonosen az erzelemfelismerest, erzelemkifejezest es mentalizalast. A kommunikacioban fellepo nehezsegek a gyogyito munka hatekonysaga szempontjabol kiemelt jelentoseguve valnak az orvos-beteg kapcsolatban. Ennek meg kritikusabb esetei azok a helyzetek, amikor a paciens mentalizacios deficittel jellemezheto zavarban szenved. Tanulmanyunkban a szocialis reprezentaciok elmeletet hasznaljuk annak vizsgalatara, hogy a maszkviseles milyen tartalmakkal valt a kozos tudas reszeve. Celkituzes: Vizsgalatunkban a maszkviseles szocialis reprezentaciojanak felterkepezeset tuztuk ki celul, figyelembe veve annak interperszonalis kommunikaciora gyakorolt hatasat, olyan csoportokban, ahol a kolcsonos megertes hatekonysaga kiemelt jelentoseggel bir. Modszerek: Kutatasunkban a koronavirus-jarvany masodik es harmadik magyarorszagi hullama idejen, orvos, szomatikus es pszichiatriai beteg csoportban, valamint kontrollcsoportban (osszesen 81 fo, atlageletkor 43,1 [SD = 13,83] ev) szabad asszociacios feladatot adtunk a maszkviseles" hivoszora. A nyert adatokbol szemantikus kategoriakat kepeztunk, majd ranggyakorisag-eljarassal felterkepeztuk a szocialis reprezentaciok szerkezetet az egyes csoportokon belul. Eredmenyek: A vizsgalati csoportok maszkhasznalathoz kapcsolodo szocialis reprezentaciojaban egysegesen kozponti elemkent jelent meg a maszkviseles altal nyujtott biztonsagelmeny, valamint a maszk zavaro testerzetet kelto hatasa. Kulonbseget talaltunk az egyes csoportok kozott elaborativ kategoriak megjelenese, illetve szorongas, agresszio, tehetetlenseg, serult dependenciaszukseglet, valamint a kenyszeru alkalmazkodas tekinteteben. Kovetkeztetesek: A maszkviseles szocialis reprezentaciojanak elemzese alapjan a maszkviseles ambivalens jelentestartalmakat hordoz. Bar a maszkviseleshez kapcsolodo szocialis reprezentaciok strukturajaban szamottevo kulonbsegek is mutatkoztak, ugyanakkor a legtobb vizsgalt csoportban a maszk a virusvedelem szempontjabol kenyelmetlen, de szukseges" eszkozkent kerult felismeresre. Az eredmenyek alapjan az egyes csoportok sajatos reprezentacioik alapjan eltero modokon lehetnek veszelyeztetettek, illetve kuzdhetnek meg a pandemia idejen kialakult helyzettel. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

PQSCT: Pseudo-Siamese BERT for Concept Tagging With Both Questions and Solutions

The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which extracts knowledge index structures and knowledge representations for exercises. Unfortunately, to the best of our knowledge, existing tagging approaches based on exercise content either ignore multiple components of exercises, or ignore that exercises may contain multiple concepts. To this end, in this paper, we present a study of concept tagging. First, we propose an improved pre-trained BERT for concept tagging with both questions and solutions (QSCT). Specifically, we design a question-solution prediction task and apply the BERT encoder to combine questions and solutions, ultimately obtaining the final exercise representation through feature augmentation. Then, to further explore the relationship between questions and solutions, we extend the QSCT to a pseudo-siamese BERT for concept tagging with both questions and solutions (PQSCT). We optimize the feature fusion strategy, which integrates five different vector features from local and global into the final exercise representation. Finally, we conduct extensive experiments on real-world datasets, which clearly demonstrate the effectiveness of our proposed models for concept tagging. IEEE

An Interpretable Fake News Detection Method Based on Commonsense Knowledge Graph

Existing deep learning-based methods for detecting fake news are uninterpretable, and they do not use external knowledge related to the news. As a result, the authors of the paper propose a graph matching-based approach combined with external knowledge to detect fake news. The approach focuses on extracting commonsense knowledge from news texts through knowledge extraction, extracting background knowledge related to news content from a commonsense knowledge graph through entity extraction and entity disambiguation, using external knowledge as evidence for news identification, and interpreting the final identification results through such evidence. To achieve the identification of fake news containing commonsense errors, the algorithm uses random walks graph matching and compares the commonsense knowledge embedded in the news content with the relevant external knowledge in the commonsense knowledge graph. The news is then discriminated as true or false based on the results of the comparative analysis. From the experimental results, the method can achieve 91.07%, 85.00%, and 89.47% accuracy, precision, and recall rates, respectively, in the task of identifying fake news containing commonsense errors.

Discourses of the wandering Almajiri child as representation of the (post-) COVID generation

The African child is a curious phenomenon in a world of shrinking population and dramatic COVID-19 economic misfortune. Both of these global crises require a youthful generation of innovators and visionaries to promote new ways of regenerating the planet. Yet, as Africa represents the future in population acceleration and natural resources, the current demonization of the almajiri [pl. almajirai]-"Quranic child learner"-as a "super-spreader" in Nigeria symbolizes a disavowal of hope in the future of humanity as a whole. This negative portrayal has further highlighted the evident institutional failure to see children as victims of global inequality and to address the issue in ways that tackle the root causes of this migratory misadventure. The humanities have a role to play here, and in this essay, we will use both fictional and non-fictional narratives to trace the life chances of a class of youths who see their condition as faith, fate, and transitional. The permanence of their condition, we argue, is a relatively recent phenomenon brought about by the vicissitudes of displacement, alienation, and a culture of misplaced priorities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. All rights reserved.

Discourse Representation of COVID-19 in Editorial Columns in Jordanian Newspapers

This study aims to explore the discourse representation of COVID-19 in editorial columns in Jordanian newspapers. The corpus of the study consists of sixty-four editorial columns from three Jordanian newspapers, namely, Addustour, Al-Rai, and Al-Ghad during the period March to November, 2020. A thematic analysis was used in the data analysis to identify the themes represented by the Jordanian newspapers' editorials concerning COVID-19. A critical discourse analysis (CDA) was also adopted to understand the discourse representation strategies and discursive practices used by the Jordanian newspapers' editorial columns in their representation of COVID-19. The study has found that the editorials used thirteen themes in representing COVID-19, including pandemic, economic consequences, fighting COVID-19, abiding by health measures, crisis, danger, outbreak, lockdown, raising awareness, fear and worry, lifestyle changing, threat to humanity, and killing. Furthermore, the editorials used ten representational discourse strategies to represent COVID-19, namely, positive self-presentation, implication, actor description, authority, example/illustration, evidentiality, lexicalization, metaphor, negative other-presentation, and number game.

Navigating COVID-19 linguistic landscapes in Vancouver's North Shore: official signs, grassroots literacy artefacts, monolingualism, and discursive convergence

This article describes the changing linguistic landscape on the North Shore of Vancouver, British Columbia, Canada, during the first three months of the COVID-19 pandemic. I present an account of the visual representation of change along the area's parks and trails, which remained open for socially-distanced exercise during the province's lockdown. Following the principles of visual, walking ethnography, I walked through numerous locations, observing and recording the visual representations of the province's policies and discourses of lockdown and social distancing. Examples of change were most evident in the rapid addition to social space of top-down signs, characterised mainly by multimodality and monolingualism, strategically placed in ways that encouraged local people to abide by social-distancing. However, through this process of observation and exploration, I noticed grassroots semiotic artefacts such as illustrated stones with images and messages that complemented the official signs of the provincial government. As was the case with the official signs and messages, through a process of discursive convergence, these grassroots artefacts performed a role of conveying messages and discourses of social distancing, public pedagogy, and community care.

Muslim preachers' pandemics related discourses within social media: A corpus-based critical discourse analysis

Pandemics have been extensively represented in different discourse genres including journalistic discourse, media discourse, medical discourse, social media discourse, and academic discourse. This study explores the representation of COVID-19, Swine flu, and Monkey pox in the Arab Muslim preachers' discourses on Twitter and Facebook. The Muslim preachers' discourses remain one of the influential discourses that informs the ideology of its believers, as it is largely based on the Islamic authoritative discourses of the Quran and the Hadiths of Prophet Muhammad. The data set of 538 postings was generated through an extended observation of purposively recruited Arab Muslim non-mainstream scholars' postings on Facebook and Twitter from March 2019 to August 2022. The data were analyzed using corpus-based critical discourse analysis. The twofold analytical lens involving CL and CDA revealed that Muslim preachers frequently used ideological semantic patterns in communicating to the Muslim society at large regarding the pandemics. The utilized semantic patterns emerged as embedded in certain ideological frames established in the Islamic authoritative discourses of the Quran and the Hadiths of Prophet Muhammad. In their ideological representation of the pandemics, Muslim preachers framed the entire three pandemics mostly as the wrath of God. Religious scholars' postings cannot be considered an account of teaching and preaching;rather, they merely consume and produce Islamic ideology in a way to manipulate and influence Muslims' knowledge of existing reality by adding new meanings in line with the chosen ideological frames.

Healthy citizens, healthy democracies? A review of the literature

A growing literature over the past 10 years on health and political behavior has established health status as an important source of political inequality. Poor health reduces psychological engagement with politics and discourages political activity. This lowers incentives for governments to respond to the needs of those experiencing ill health and thereby perpetuates health disparities. In this review article, we provide a critical synthesis of the state of knowledge on the links between different aspects of health and political behavior. We also discuss the challenges confronting this research agenda, particularly with respect to measurement, theory, and establishing causality, along with suggestions for advancing the field. With the COVID-19 pandemic casting health disparities into sharp focus, understanding the sources of health biases in the political process, as well as their implications, is an important task that can bring us closer to the ideals of inclusive democracy.

Genomic representation predicts an asymptotic host adaptation of bat coronaviruses using deep learning.

Introduction: Coronaviruses (CoVs) are naturally found in bats and can occasionally cause infection and transmission in humans and other mammals. Our study aimed to build a deep learning (DL) method to predict the adaptation of bat CoVs to other mammals. Methods: The CoV genome was represented with a method of dinucleotide composition representation (DCR) for the two main viral genes, ORF1ab and Spike. DCR features were first analyzed for their distribution among adaptive hosts and then trained with a DL classifier of convolutional neural networks (CNN) to predict the adaptation of bat CoVs. Results and discussion: The results demonstrated inter-host separation and intra-host clustering of DCR-represented CoVs for six host types: Artiodactyla, Carnivora, Chiroptera, Primates, Rodentia/Lagomorpha, and Suiformes. The DCR-based CNN with five host labels (without Chiroptera) predicted a dominant adaptation of bat CoVs to Artiodactyla hosts, then to Carnivora and Rodentia/Lagomorpha mammals, and later to primates. Moreover, a linear asymptotic adaptation of all CoVs (except Suiformes) from Artiodactyla to Carnivora and Rodentia/Lagomorpha and then to Primates indicates an asymptotic bats-other mammals-human adaptation. Conclusion: Genomic dinucleotides represented as DCR indicate a host-specific separation, and clustering predicts a linear asymptotic adaptation shift of bat CoVs from other mammals to humans via deep learning.

Transforming perception of space in the pandemic agenda: From real space to virtual space

Due to the COVID-19, a lot has changed regarding daily routines. Homes have become an extension of the public sphere. Because of the pandemic, people's daily roles have moved mainly into the home via the internet and this shift has created a new multi-role situation. Within the scope of the study, an online semistructured interview was conducted to examine people's experiences of the new representations of the house. The findings in this case study were evaluated with the literature and discussed under these headings: representation of self and representation of space. The study showed that;house, as the new representation space, has become a part of the social identity shared with the public. Objects seen by the camera served as an indicator of self-representation. The privacy of the home was disturbed by the host of the public. The house has become a place where many identities have to exist together. Interviews show that the home's effect on representation cannot be denied. The house is now both a private and a public space, hosting many formal and informal activities. Moreover, while at home, many personal and spatial representations have been transferred to the virtual world. The COVID-19 pandemic has made the home a part of the public space. However, the house is not designed to function as a public space and acts as an insufficient representation of self and place. If daily life continues with a focus on home, the house should be redesigned by the new representations it hosts. © 2023, Istanbul Teknik Universitesi, Faculty of Architecture. All rights reserved.

How to Deal with a Bully: Debility, Non-Production, and Radical Care

This article examines how resistance toward capitalism's temporal bullying is performed in contemporary art and activism. It addresses the relationship between creativity, institutions, and empowerment. Building on the conceptual work of Croatian artist Mladen Stilinović (1947–2016), the article explores several aesthetic presentations of resistive temporalities we identify as non-production. The case studies of non-production herein marshaled affirm a performance of resistance that centers discussion of radicality in self-consciously interdependent care networks, ostensibly available to all disabled and nondisabled individuals. This care ethic claps back at the idea of self-optimization and fiduciary endurance amidst economic regimes of exploitation as virtuous. In the place of 'wellness,' this article affirms new directions in care and mutual aid, as premised on queer, crip, and feminist portrayals of disability praxis and pedagogy.

Interactive digital narrative (IDN)—new ways to represent complexity and facilitate digitally empowered citizens

In this overview paper, we consider interactive digital narratives (IDN) as a means to represent and enable understanding of complex topics both at the public level (e.g. global warming, the COVID-19 pandemic, migration, or e-mobility) and at the personal level (trauma and other mental health issues, interpersonal relationships). We discuss scholarly, artistic, and non-fiction approaches to complexity, point out limitations of traditional media to represent complex issues, and describe the foundational advantages of IDN in this regard, using the SPP model as a conceptual lens. Then, we describe the problem space of IDN for complexity, and what aspects need further work in order to more fully realise the potential of IDN to represent complex topic in education and public communication.

Accurate and fast clade assignment via deep learning and frequency chaos game representation.

BACKGROUND: Since the beginning of the coronavirus disease 2019 pandemic, there has been an explosion of sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, making it the most widely sequenced virus in the history. Several databases and tools have been created to keep track of genome sequences and variants of the virus; most notably, the GISAID platform hosts millions of complete genome sequences, and it is continuously expanding every day. A challenging task is the development of fast and accurate tools that are able to distinguish between the different SARS-CoV-2 variants and assign them to a clade. RESULTS: In this article, we leverage the frequency chaos game representation (FCGR) and convolutional neural networks (CNNs) to develop an original method that learns how to classify genome sequences that we implement into CouGaR-g, a tool for the clade assignment problem on SARS-CoV-2 sequences. On a testing subset of the GISAID, CouGaR-g achieved an $96.29\%$ overall accuracy, while a similar tool, Covidex, obtained a $77,12\%$ overall accuracy. As far as we know, our method is the first using deep learning and FCGR for intraspecies classification. Furthermore, by using some feature importance methods, CouGaR-g allows to identify k-mers that match SARS-CoV-2 marker variants. CONCLUSIONS: By combining FCGR and CNNs, we develop a method that achieves a better accuracy than Covidex (which is based on random forest) for clade assignment of SARS-CoV-2 genome sequences, also thanks to our training on a much larger dataset, with comparable running times. Our method implemented in CouGaR-g is able to detect k-mers that capture relevant biological information that distinguishes the clades, known as marker variants. AVAILABILITY: The trained models can be tested online providing a FASTA file (with 1 or multiple sequences) at https://huggingface.co/spaces/BIASLab/sars-cov-2-classification-fcgr. CouGaR-g is also available at https://github.com/AlgoLab/CouGaR-g under the GPL.

Diversity and inclusion in clinical trials: Evolution throughout the development of an mRNA COVID-19 vaccine.

Despite the importance of equitable representation in clinical trials, disparities persist with racial and ethnic minorities remaining largely underrepresented in trial populations. During the coronavirus disease 2019 (COVID-19) pandemic, wherein disease disproportionately affected racial and ethnic minority groups, the necessity for diverse and inclusive representation in clinical trials has been further highlighted. Considering the urgent need for a safe and efficacious vaccine, COVID-19 vaccine clinical trials faced marked challenges in rapidly enrolling participants without forgoing diverse representation. In this perspective, we summarize Moderna's approach toward achieving equitable representation in mRNA-1273 COVID-19 vaccine clinical trials, including the COVID-19 efficacy (COVE) study, a large, randomized, controlled, phase 3 trial of mRNA-1273 safety and efficacy in adults. We describe the dynamics of enrollment diversity throughout the COVE trial and the need for continuous, efficient monitoring and rapid pivoting from initial approaches to address early challenges. Insights gained from our varied and evolved initiatives provide key learnings toward achieving equitable representation in clinical trials, including establishing and listening to a Diversity and Inclusion Advisory Committee, repeatedly engaging with key stakeholders on the necessity for diverse representation, creating and disseminating inclusive materials to all trial participants, establishing methods to raise awareness for interested participants, and enhancing transparency with trial participants to build trust. This work shows that diversity and inclusion in clinical trials can be attained even in the most extreme circumstances and highlights the importance of efforts toward building trust and empowering racial and ethnic minorities with the knowledge to make informed medical treatment decisions.

Conversation between Pandemics through Art. Social Imaginaries of Hiv/Aids and Covid-19, Care and Affections

This research presents a study of the artistic practices that treat the pandemics social imaginaries of HIV and COVID-19. The main target is analyzing the main artistic strategies that have been implemented in relationship with the social's representation of the illness from the perspective of the cares and the affections having in mind the connections and frictions that have been stablished with the pandemic's contexts. It's considered that, during the first decades of the HIV pandemic takes place, from the artistic point of view, emancipatory attempts that had an important impact in the social and the artistic and it study if some of this strategy has been present in the artistic practices about COVID-19 taking care of the evolution and the transformations experimented in the actual context. A qualitative methodology has been implemented, with an inductive-interpretive focus and it starts with a study of the multiple cases that allows to determine a series of categories that works like a cartography mode from which offers an analysis of the studied practices. The research manifests the potential of art for contradict some of the bases of the social imaginary of the infective illness pandemic in the contemporary and for building a tool of action in the social, in collaboration with other disciplines.

Finding a New Order through Remote Teaching

Adversity takes us out of our comfort zone and leads us in search of solutions to face it. That was the case with remote teaching, that came to solve problems faced by education during the Covid-19 pandemic. The apparent chaos caused by the urgent need for change in the teaching methods, gradually revealed to be ordered and promising in some aspect. It is this new order that we will address in this paper: the intensification of the individualized instruction. The experience described here occurred with a freshman class of the Interior Design course at the School of Fine Arts at the Federal University of Rio de Janeiro, UFRJ. The course's conduction underwent changes according to the student's responses, based on John Dewey's technic of thought construction and Jean Piaget's method of critical exploration. The experiment exposes a way to apply remote teaching to detect how each student learns the topics given in class, when it is presented to the class in a collective way, then guide each one through the appropriated path for them.