113,413 research outputs found
Costruire l’alleanza scuola-famiglia nelle interazioni tra genitori e figli durante i compiti a casa : adottare lo “sguardo valutativo dell’insegnante” come pratica interattiva
No full text.Negli ultimi trent’anni, numerose ricerche nazionali e interazionali hanno presentato
come positivo e auspicabile il coinvolgimento dei genitori nelle esperienze scolastiche
dei figli (si veda ad esempio, Epstein, 1995; Milani, 2012). In questo vasto
panorama di ricerche, particolarmente influente è stato il lavoro di Joyce Epstein,
che ha proposto la nozione di “school-like families” (Epstein, 1995, p. 83) e con
essa l’idea che i genitori debbano duplicare la cultura e gli standard della scuola all’interno
della casa al fine di favorire l’apprendimento scolastico dei bambini.
In linea con queste ricerche, le politiche educative in diversi paesi occidentali
tra cui l’Italia hanno promosso la cosiddetta “alleanza scuola-famiglia”. Alla base
di questa nozione vi è l’idea che la l’allineamento tra scuola e famiglia e la sovrapposizione
tra le culture di queste fondamentali istituzioni educative sia cruciale
per promuovere motivazione, riuscita scolastica e inclusione sociale degli alunni.
Ad esempio, la Nota Miur 22.11.2012, prot. n. 3214 – Trasmissione Linee di indirizzo
“Partecipazione dei genitori e corresponsabilità educativa” sottolinea la necessità
di costruire una partnership educativa fondata su un’autentica condivisione
di valori tra genitori e insegnanti.
Nella costruzione della partnership tra scuola e famiglia, un ruolo fondamentale
viene svolto dai compiti a casa. In quanto attività che si realizza “sulla soglia”,
i compiti costituiscono un contesto privilegiato per osservare il “declinarsi concreto
dei rapporti tra scuola e famiglia” (Montalbetti, Lisimberti, 2020, p. 316), nonché
un luogo essenziale per costruire e consolidare l’alleanza (Colla, Caronia, 2020).
Eppure, proprio per la loro natura transcontestuale, i compiti possono essere non
solo una risorsa nella costruzione della partnership, ma anche un luogo dove vengono
agite vere e proprie “dis-alleanze educative” (Contini, 2012).
Alla luce di queste considerazioni, questo studio si concentra sui compiti a casa
e indaga le pratiche interattive attraverso cui i genitori mostrano il proprio orientamento
all’alleanza scuola-famiglia e la costruiscono discorsivamente in e attraverso
le conversazioni con i propri figli
A big step ahead in Metal Science and Technology through the application of Artificial Intelligence
No full textDigitalization is a key enabling factor of the dramatic transformation of metal industry since the 90-ies. Important applications were implemented since then, exploiting multi-physical modelling, complex real time process control and Machine Learning. This trend was further enhanced and accelerated by Industry 4.0. Digitalization implies harvesting impressive volumes of heterogeneous data, which need to be stored, processed and, mostly, interpreted to extract relevant information and “knowledge”. Knowledge means capability of interpreting data, of explaining and representing material transformation and product evolution during the different process stages considering complex interactions among process and product variables, including aspects still not perfectly understood. Artificial Intelligence supports knowledge extraction by enabling optimal process management and control, higher flexibility and product quality, stronger resource and energy efficiency, namely sustainability. Challenges and opportunities of enhancing metallurgical science and technology through Artificial intelligence are considered in this review
Teacher Martina wants you to write in cursive’ : parents invoking school morality in directive sequences during homework
No full textThe concept of ‘family–school partnership’ has been extensively investigated from a macro and theoretical perspective, but it is still little explored at the micro level of interaction. Based on video-recorded homework sessions collected in Italian family residences and drawing on conversation analysis, this paper shows how parents enact what constitutes the core meaning of the family–school partnership (i.e. the sharing of values between home and school). The analysis shows that parents invoke what they frame as ‘school
morality’ as an account in directive sequences. It is argued that, in so doing, parents increase their own entitlement while reducing the assertiveness of their directives. At the same time, they display their orientation towards aligning with school morality and discursively construct a moral order common to family and school
Objects that matter
No full textt has been two decades since the social-material turn in social interaction studies proved the heuristic limits of a logocentric analytical geography. In this paper, we focus on the performative function of objects in an underexplored learning activity: parent-assisted homework. Adopting a Conversation Analysis informed approach complemented by the ventriloquial perspective on communication, we illustrate how parent-assisted homework is accomplished through the multiple resources in the semiotic field. Particularly, we show how participants orient to and exploit the agency of materiality in interaction. In the conclusion we raise a socio-pedagogical issue concerning the cultural capital embedded in the learning environment as well as the parents’ competence in recognizing and exploiting it in ways that are aligned with the school culture.
Keywords: socio-materiality, agency, homework, parent-child interaction, ventriloquial perspectiv
AI Data Analysis and SOM for the Monitoring and Improvement of Quality in Rolled Steel Bars
No full textIn the steel sector, within the production of high value hot rolled long products, assessment of components health and compliance with quality targets are fundamental aspects that need to be ensured. In this paper, an AI–based system for monitoring the conditions of the rolling process of bars with round section and estimating the final bars ovality is presented. The developed system, based on a Self Organising Map, is trained and evaluated by using data coming from a real plant and pre–processed by means of advanced AI techniques. The system allows monitoring a wide range of process variables affecting the ovality issue and actively supports plant operators in the task of avoiding quality–critical conditions and possible machine faults
Integration of structural and energetic non destructive diagnostics: dynamics of air fluxes by IR thermography
No full textHistorical buildings represent an important part of the Cultural Heritage and they sum up to more than half of the buildings present in Europe. Those structures are often characterized by structural and energetic deficiencies because of the poor or lack of maintenance. NDT can provide a great aid to the knowledge of the building. Numerical evaluations need great deal of precise experimental data. In addition, about techniques applicable with energetic aims and there is no experience of possible limitations when applying them on historic buildings where the uncertainties are many more. In an effort to further develop existing diagnostic techniques and testing procedures, in this work an IR thermography experimental application is outlined for the purpose of dynamically tracing air movements in an indoors environment. By using paper stripes hanging from the ceiling, it was possible to survey the air temperature at different heights, in different climatic conditions and to obtain horizontal and vertical temperature maps of high precision
Beyond school-related learning : parent-child homework talk as a morality building activity
No full textFamily interactions constitute an arena for children's moral development: it is indeed through ordinary talk, and shared, task-oriented activities that children are socialized into moral orders and culturally informed ways of thinking and acting. Drawing on a video-based study on the everyday life of 19 middle-class families and adopting a discourse analytic approach, the paper sheds light on the socializing function of a domestic activity: homework. We illustrate that, when it unfolds as a family activity, the issues at stake go far beyond its school-oriented goals: homework provides ‘ethical affordances’ that make relevant moral talk whereby parents introduce children to some unquestioned principles such as homework must be done neatly and it is part of the child's duties. We contend that, by participating in morally loaded homework interactions, children are socialized not only into a school-aligned cultural list concerning what is right and what is wrong about homework, but moreover into a constitutive, taken-for-granted pillar of human sociality: the moral assessability of human conduct, i.e., its being subject to evaluations informed by the ‘right vs. wrong’ category. Implications for teacher training and parent education programs are discussed in the conclusion
(Eds.) Report D6-3 Case study 3: Palazzo Malvezzi
No full textThis report shows the activities carried out during the project SMooHS, at the 3rd case study, Malvezzi Palace in Bologna, Italy
Automatic steel grades design for Jominy profile achievement through neural networks and genetic algorithms
No full textThe paper proposes an approach to the design of the chemical composition of steel, which is based on neural networks and genetic algorithms and aims at achieving a desired hardenability behavior possibly matching other constraints related to the steel production. Hardenability is a mechanical feature of steel, which is extremely relevant for a wide range of steel applications and refers to the steel capability to improve its hardness following a heat treatment. In the proposed approach, a neural-network-based predictor of the so-called Jominy hardenability profile is exploited, and an optimization problem is formulated, where the optimization function allows taking into account both the desired accuracy in meeting the target Jominy profile and other constraint. The optimization is performed through genetic algorithms. Numerical results are presented and discussed, showing the efficiency of the proposed approach together with its flexibility and easy customization with respect to the user demands and production objectives
A Novel Approach to Jominy Profile Prediction Based on 1D Convolutional Neural Networks and Autoencoders that Supports Transfer Learning
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