Staff perspectives on the role of English proficiency in providing support services

A case study approach was applied to understand the challenges of offering support services to international students (IS) within a university setting. A social constructivist theoretical framework informed the collection and analysis of data. Perspectives from service providers - general and academic staff members and international students were triangulated. To date, 63 participants have been interviewed and preliminary findings show that although international students encounter a number of academic and socio-cultural difficulties during university transition, many do not access support services offered by university for various reasons including; perceived language and cultural barriers, unawareness, feeling uncomfortable; and avoiding any stigma associated with help-seeking. The data shows service providers too have reported difficulties when working with international students, such as cultural and language barriers, lack of staff, funding and training. The focus of the current paper will be on one of the major themes explicating these tensions, namely English proficiency which acts as a pervasive barrier for both staff service provision and students service utilisation. Implications of findings, recommendations for universities and direction for future research will be discussed in reference to this theme

Reasoning About Distributed Knowledge of Groups with Infinitely Many Agents

Spatial constraint systems (scs) are semantic structures for reasoning about spatial and epistemic information in concurrent systems. We develop the theory of scs to reason about the distributed information of potentially infinite groups. We characterize the notion of distributed information of a group of agents as the infimum of the set of join-preserving functions that represent the spaces of the agents in the group. We provide an alternative characterization of this notion as the greatest family of join-preserving functions that satisfy certain basic properties. We show compositionality results for these characterizations and conditions under which information that can be obtained by an infinite group can also be obtained by a finite group. Finally, we provide algorithms that compute the distributive group information of finite groups

A Formal Model for Polarization under Confirmation Bias in Social Networks

We describe a model for polarization in multi-agent systems based on Esteban and Ray's standard family of polarization measures from economics. Agents evolve by updating their beliefs (opinions) based on an underlying influence graph, as in the standard DeGroot model for social learning, but under a confirmation bias; i.e., a discounting of opinions of agents with dissimilar views. We show that even under this bias polarization eventually vanishes (converges to zero) if the influence graph is strongly-connected. If the influence graph is a regular symmetric circulation, we determine the unique belief value to which all agents converge. Our more insightful result establishes that, under some natural assumptions, if polarization does not eventually vanish then either there is a disconnected subgroup of agents, or some agent influences others more than she is influenced. We also prove that polarization does not necessarily vanish in weakly-connected graphs under confirmation bias. Furthermore, we show how our model relates to the classic DeGroot model for social learning. We illustrate our model with several simulations of a running example about polarization over vaccines and of other case studies. The theoretical results and simulations will provide insight into the phenomenon of polarization.Comment: arXiv admin note: substantial text overlap with arXiv:2104.11538, arXiv:2012.0270

Reasoning about knowledge and messages in asynchronous multi-agent systems

International audienceWe propose a variant of public announcement logic for asynchronous systems. To capture asynchrony, we introduce two different modal operators for sending and receiving messages. The natural approach to defining the semantics leads to a circular definition, but we describe two restricted cases in which we solve this problem. The first case requires the Kripke model representing the initial epistemic situation to be a finite tree, and the second one only allows announcements from the existential fragment. After establishing some validities, we study the model checking problem and the satisfiability problem in cases where the semantics is well-defined, and we provide several complexity results.

An Erlang Implementation of Multiparty Session Actors

By requiring co-ordination to take place using explicit message passing instead of relying on shared memory, actor-based programming languages have been shown to be effective tools for building reliable and fault-tolerant distributed systems. Although naturally communication-centric, communication patterns in actor-based applications remain informally specified, meaning that errors in communication are detected late, if at all. Multiparty session types are a formalism to describe, at a global level, the interactions between multiple communicating entities. This article describes the implementation of a prototype framework for monitoring Erlang/OTP gen_server applications against multiparty session types, showing how previous work on multiparty session actors can be adapted to a purely actor-based language, and how monitor violations and termination of session participants can be reported in line with the Erlang mantra of "let it fail". Finally, the framework is used to implement two case studies: an adaptation of a freely-available DNS server, and a chat server.Comment: In Proceedings ICE 2016, arXiv:1608.0313

Assessing Student Mindset, Interest, Participation, and Rapport in the Post-Pandemic Public Speaking Classroom: Effects of Modality Change and Communication Growth Mindset

The COVID-19 pandemic created an exigency for educators to reevaluate their approaches to the classroom with one major dimension being course modality. This study uses the Instructional Beliefs Model to examine the impacts of course modality (i.e., hybrid versus face-to-face formats) and students’ communication growth mindset on student engagement in the foundational public speaking course. Consistent with pre-COVID-19 findings, the results indicated that modality does not significantly impact student engagement, with one exception: higher cognitive interest scores were reported among students in the hybrid modality. Communication growth mindset associated positively with all student engagement variables examined: student interest–emotional, student interest–cognitive, participation, and class rapport. The findings offer tentative optimism about the promise of blended public speaking course modalities, and evidence for the necessity of mindset intervention to maximize student success

The LTS WorkBench

Labelled Transition Systems (LTSs) are a fundamental semantic model in many areas of informatics, especially concurrency theory. Yet, reasoning on LTSs and relations between their states can be difficult and elusive: very simple process algebra terms can give rise to a large (possibly infinite) number of intricate transitions and interactions. To ease this kind of study, we present LTSwb, a flexible and extensible LTS toolbox: this tutorial paper discusses its design and functionalities

Worlds of events: deduction with partial knowledge about causality

Interactions between internet users are mediated by their devices and the common support infrastructure in data centres. Keeping track of causality amongst actions that take place in this distributed system is key to provide a seamless interaction where effects follow causes. Tracking causality in large scale interactions is difficult due to the cost of keeping large quantities of metadata; even more challenging when dealing with resource-limited devices. In this paper, we focus on keeping partial knowledge on causality and address deduction from that knowledge.We provide the first proof-theoretic causality modelling for distributed partial knowledge. We prove computability and consistency results. We also prove that the partial knowledge gives rise to a weaker model than classical causality. We provide rules for offline deduction about causality and refute some related folklore. We define two notions of forward and backward bisimilarity between devices, using which we prove two important results. Namely, no matter the order of addition/ removal, two devices deduce similarly about causality so long as: (1) the same causal information is fed to both. (2) they start bisimilar and erase the same causal information. Thanks to our establishment of forward and backward bisimilarity, respectively, proofs of the latter two results work by simple induction on length.-This work was partially funded by the SyncFree project in the European Seventh Framework Programme under Grant Agreement 609551 and by the Erasmus Mundus Joint Doctorate Programme under Grant Agreement 2012-0030. Our special thanks to the SyncFree peers for their prolific comments on the early versions of this work. We would like to also thank the anonymous referees for their constructive discussion over the ICE forum.info:eu-repo/semantics/publishedVersio