In a project partially supported by research grant PANN20_00690 to Italy's CINI National Lab "Informatica e Scuola", we compared the effectiveness of two alternative instructional methods applied to scaffold the learning of iterations for children at grades 2-3. Eight university groups across the Country collaboratively run the project in two successive rounds throughout the year 2022. Teachers' feedback collected across the two rounds helped fine-tune the deployment of the interventions. The experiment results show that the two alternative interventions have measurable outcome differences in the short term.

We consider Social Distance Games (SDGs), that is cluster formation games in which the utility of each agent only depends on the composition of the cluster she belongs to, proportionally to her harmonic centrality, i.e., to the average inverse distance from the other agents in the cluster. Under a non-cooperative perspective, we adopt Nash stable outcomes, in which no agent can improve her utility by unilaterally changing her coalition, as the target solution concept. Although a Nash equilibrium for a SDG can always be computed in polynomial time, we obtain a negative result concerning the game convergence and we prove that computing a Nash equilibrium that maximizes the social welfare is NP-hard by a polynomial time reduction from the NP-complete Restricted Exact Cover by 3-Sets problem. We then focus on the performance of Nash equilibria and provide matching upper bound and lower bounds on the price of anarchy of Θ(n), where n is the number of nodes of the underlying graph. Moreover, we show that there exists a class of SDGs having a lower bound on the price of stability of 6/5 − ε, for any ε > 0. Finally, we characterize the price of stability 5 of SDGs for graphs with girth 4 and girth at least 5, the girth being the length of the shortest cycle in the graph.

We consider Social Distance Games (SDGs), that is cluster formation games in which agent utilities are proportional to their harmonic centralities in the respective coalitions, i.e., to the average inverse distance from the other agents. We adopt Nash stable outcomes, that is states in which no agent can improve her utility by unilaterally changing her coalition, as the target solution concept. Although SDGs always admit a Nash equilibrium, we prove that it is NP-hard to find a social welfare maximizing one and obtain a negative result concerning the game convergence. We then focus on the performance of Nash equilibria and provide matching upper bound and lower bounds on the price of anarchy of Θ(n), where n is the number of nodes of the underlying graph, and a lower bound on the price of stability of 6/5 - ε. Finally, we characterize the price of stability of SDGs for graphs with girth 4 and girth at least 5.

In this paper we consider the problem of sharing the costs of multicast transmissions in ad hoc wireless networks. Assuming that the receiving users are selfish, we provide strategy- proof mechanisms that are either optimally budget balanced or efficient for the case in which the distance-power gradient α =1 or the stations belong to a ne-dimensional Euclidean space.Then, by extending to multicasting previous results on wireless broadcasting,we show the existence of efficiently computable 2(3 d.1)-approximate budget balance mechanisms in any d -dimensional space for every α ≥ d.

Vector clocks are the appropriate mechanism used to track causality among the events produced by a distributed computation. Traditional implementations of vector clocks require application messages to piggyback a vector of n integers (where n is the number of processes). This paper investigates the tracking of the causality relation on a subset of events (namely, the events that are defined as "relevant" from the application point of view) in a context where communication channels are not required to be FIFO, and where there is no a priori information on the connectivity of the communication graph or the communication pattern. More specifically, the paper proposes a suite of simple and efficient implementations of vector clocks that address the reduction of the size of message timestamps, i.e., they do their best to have message timestamps whose size is less than n. The relevance of such a suite of protocols is twofold. From a practical side, it constitutes the core of an adaptive timestamping software layer that can used by underlying applications. From a theoretical side, it provides a comprehensive view that helps better understand distributed causality-tracking mechanisms.