The COVID-19 crisis has strongly affected the school system. In Italy, at-distance forms of didactics have been activated, changing the physiognomy of schools in terms of social interaction, practices and the identity of the individuals. In this paper, we address the issue of how teachers are facing the crisis: our focus is on assessment, as a key variable catalyzing personal history; beliefs; the interface between students; teachers and the school system. We study teachers’ beliefs as part of their identities and assessment as a fundamental variable of beliefs. A qualitative content analysis of the open-ended answers to an online questionnaire is carried out to understand the main characteristics associated with assessment by teachers and the obstacles to overcome in the context of long distance learning (LDL). The data show that teachers did not identify valid assessment methods for LDL during the lockdown, especially due to the lack of control over the students. A misconception emerges concerning the definition of formative assessment together with a new awareness of the possibilities offered by digital technologies regarding the individualization of didactics. This study helps to understand which teachers’ beliefs are related to assessment are and how they are shaped.

The GeomBot is a drawing robot that combines the well-known strengths and opportunities offered by Scratch with those of Papert’s original robotic drawing-turtle. In this study we look at the GeomBot as a physical programmable artifact around which action research with a group of teachers and a researcher was carried out with the aim of designing, implementing and discussing geometry activities for primary school classes. The aim of this article is to investigate teachers’ positioning and perspectives with respect to the activities and the educational environment emerging around the Geombot in the action research. The action research meetings between September 2018 and June 2019 included nine primary school teachers from seven different Italian schools, who met regularly with the first author. After the design and experimentation sessions, in June 2019, the teachers shared their experiences during a final meeting and group discussion guided by the first author. The data collected from the teachers were analyzed using cultural categories from the Semiotic Systems of Cultural Signification, theorized by the Theory of Objectification, to identify the most significant features defining the teachers’ perspectives and identity. The seven emergent features cover teachers’ positioning with respect to: forms of rationality and language and languages: sensuous cognition and the use of ideal and material semiotic resources; accepted teaching practices, problems and situations; mathematical knowledge; the conception of the student; social interaction and forms of rationality; ethical issues; technology.

In this article, grounded in the concept of interpretative knowledge (IK), which is well known in the literature, we introduce and discuss the construct of semiotic interpretative knowledge (SIK). This theoretical tool unfolds the interpretation of conceptual knowledge into a broader construct that intertwines the use of semiotic representations with the manifold aspects of mathematical learning. In the first part of the article, we first introduce Duval’s semio-cognitive approach, in which semiotics is the element characterizing the specific cognitive functioning of mathematics. On the basis of some classic examples from the relevant literature, we then show the necessity of introducing the semiotic component into IK to expand the interpretive power of the teacher. In the second part of the article, through the analysis of six episodes involving students with a specific learning disorder (SLD) engaged in mathematical activities, we show how the development of the teacher’s SIK emerges as a necessary condition for the implementation of inclusive teaching practices. This permits us to face the research question focused on how SIK allows us to understand the student’s behavior in a special needs educational context and provide effective feedback. In this sense, SIK is shown to be an intrinsic prerequisite of inclusive teaching, thus extending the concept of IK to the components of pedagogical content knowledge (PCK).

We present a theoretical study that allows us to attempt framing in an embodied perspective the effectiveness of the drawing robot GGBot in the learning of geometry. The aim of the article is to set the intertwining of activity, semiotics, perception, and knowledge at the crossover of Radford’s theory of objectification (TO) and Borba and Villareal’s notion of humans-with-media. Such a crossover is articulated in four building blocks: (1) processes of objectification and the role of semiotic means of objectification, where we state that digital artifacts such as the GGBot change the topology of the semiotic means of objectification; (2) cognition is sensuous and learning is a process of domestication of the eye, where perception is theoretically shaped by the interaction with GGBot; (3) GGBot and humans-with-media, where we outline new thinking collectives and their modes of activity; (4) domestication of the eye triggered by transitions between domains of activity. Each building block of our theoretical discussion is empirically anchored to four episodes involving primary school students’ learning geometrical figures using the GGBot. To conclude, we focus on two basic concepts of geometrical thinking that unfold in the shift between domains.

The mere development of a software to predict University dropout is not sufficient for its effective implementation in the academic context. In order to exploit it as a tool supporting decision-making, such a software should be provided with information necessary for its integration into the decision-making processes of University governance. In this work, we present a predictive tool, at the state of the art, providing a functional description of its integration through practical examples. In addition, we propose a simplified scheme to guide the reasoning on the software, which we structure according to the following processes: the learning of the machine, the choice of the representation of dropout and the interpretation of the results. Finally, we share some considerations addressing education designers and institutional decision-makers on the management of interventions inspired by the prediction of freshmen academic outcome. Modelli predittivi per politiche efficaci contro l'abbandono dell’università. Lo sviluppo di un software per predire l’abbandono della carriera universitaria non è sufficiente affinché questo venga implementato in modo efficace nel contesto accademico. Per essere sfruttato come strumento di supporto alle decisioni, il software dovrebbe essere fornito con le informazioni necessarie alla sua integrazione nei processi decisionali della governance di ateneo. In questo lavoro, presentiamo uno strumento predittivo allo stato dell’arte, fornendone una descrizione funzionale alla sua integrazione, attraverso esempi concreti. Inoltre, proponiamo uno schema semplificato per guidare il ragionamento sul software, che strutturiamo nei seguenti processi: l’apprendimento della macchina, la scelta della rappresentazione dell’abbandono e l’interpretazione dei risultati. Infine, condividiamo alcune considerazioni rivolgendoci ai progettisti dell’educazione e agli institutional decision-makers circa la gestione degli interventi ispirati dalla previsione dell’abbandono delle matricole.