Exceptional classroom management (CM) for face-to-face and online classes is vital to instructor success, and importantly, directly impacts students' ability to learn. Classroom conflict may disrupt an instructor's CM and can occur when a student is uncivil (e.g., sidetracks from lecture) or when an instructor misbehaves (e.g., antagonizes students). A small but meaningful line of work suggests that uncivil students and misbehaving teachers negatively impact the learning environment. However, no work has examined how the interaction between an uncivil student and misbehaving teacher impacts learning. As such, the purpose of the current study is to empirically investigate how teacher responses to student incivility impact cognitive learning in an online learning environment. The project evaluated approximately 252 undergraduate students via an online study. Participants watched a video of an online class in which the professor responds to an uncivil student in one of three different ways: antagonistically, positively, or neutrally. Participants then took a cognitive learning quiz based on the lecture and answered questions about their perception of the instructor, uncivil student, and the learning environment. Results of the one-way ANOVA suggest that how an instructor responded to student incivility did not significantly impact cognitive learning. Secondary analyses also indicated that participant perceptions of the instructor, uncivil student, and learning environment did not significantly relate to cognitive learning. Results of the current study evidence both convergence and divergence with prior work, highlighting the importance of continued experimental investigation of the impact instructor reactions to student incivilities has on learning.

No description available.

An ad hoc network adopts a decentralized unstructured networking model that depends on node cooperation for key network functionalities such as routing and medium access. The significance of node cooperation in ad hoc networks makes network survival particularly sensitive to insider node behavior. The presence of selfish or malicious nodes in an ad hoc network could greatly degrade the network performance and might even result in a total communication breakdown. Consequently, it is important for both security and performance reasons to discourage, expose, and react to such damaging misbehavior. Reputation management systems have been proposed to mitigate against such misbehavior in ad hoc networks. The functions of a reputation management system are to evaluate nodes' quality of behavior based on their cooperation (evaluation), distinguish between well-behaved and misbehaving nodes (detection), and appropriately react to misbehaving nodes (reaction). A significant number of reputation management systems have been proposed for ad hoc networks to date. However, there has been no attempt to consolidate all current research into a formal framework for reputation management systems. The lack of a formal framework is a potential weakness of the research field. For example, a formal comparison of proposed reputation management systems has remained difficult, mainly due to the lack of a formal framework upon which the comparison could be based. There is also a lack of formal metrics that could be used for quantitative evaluation and comparison of reputation management systems. Another major shortcoming in this research field is the assumption that the functions of reputation management (evaluation, detection, and reaction) are carried out homogeneously across time and space at different nodes. The dynamic nature of ad hoc networks causes node behavior to vary spatially and temporally due to changes in the local and network-wide conditions. Reputation management functions do not adapt to such changes, which may impact the system accuracy and promptness. We herein recognize an adaptive reputation management system as one where nodes carry out the reputation management functions heterogeneously across time and space according to the instantaneous perception of each of its surrounding network conditions. In this work, we address the above concerns. We develop a formal framework for reputation management systems upon which design, evaluation, and comparison of reputation management systems can be based. We define and discuss the different components of the framework and the interactions among them. We also define formal metrics for evaluation of reputation management systems. The metrics assess both, the effectiveness (security issues) of a reputation management system in detecting misbehavior and limiting its negative impact on the network, and its efficiency (performance issues) in terms of false positives and overhead exerted by the reputation management system on the network. We also develop ARMS, an autonomous reputation management system, based on the formal framework. The theoretical foundation of ARMS is based on the theory of Sequential Probability Ratio Test introduced by Wald. In ARMS, nodes independently and without cooperation manage their reputation management system functions. We then use ARMS to investigate adaptation in reputation management systems. We discuss some of the characteristics of an adaptive reputation management system such as sensitivity, adaptability, accuracy, and promptness. We consider how the choice of evaluation metric, typically employed by the evaluation function for assessment of node behavior, may impact the sensitivity and accuracy of node behavior evaluation. We evaluate the sensitivity and accuracy of node behavior evaluation using a number of metrics from the network and medium access layer. We then introduce a time-slotted approach to enhance the sensitivity of the evaluation function and show how the duration of an evaluation slot can adapt according to the network activity to enhance the system accuracy and promptness. We also show how the detection function can adapt to the network conditions by using the node's own behavior as a benchmark to set its detection parameters. To the best of our knowledge, this is the first work to explore the adaptation of the reputation management functions in ad hoc networks. / Ph. D.

There is a current debate in Swedish media regarding the negative aspects of Internet and social media, a debate which is also virtual in blogs and forums. This started with a post on the clothing company H&M’s Facebook page where a user was virtually attacked in an aggressive manner by other users. This kind of online behavior between customers can be seen as a new challenge for organizations, especially as social media is continuously growing.   We have investigated the area of misbehaving customers, also known as dysfunctional customer behavior, by looking into the theoretical area of knowledge transfer. Within knowledge transfer we have focused on the strategies codification, which concerns transferring knowledge from people-to-documents, and personalization, meaning transferring knowledge from people-to-people.   Previous studies within knowledge transfer has investigated this in relation to different contexts, including how different context affects the transfer, how knowledge is transferred between organizations or within specific industries or businesses. However, there is a lack of research regarding knowledge transfer in relation to customers misbehaving. Hence, the purpose of this study was to understand if and how organizations work with a codification and/or personalization strategy for transferring knowledge when handling dysfunctional customer behavior on social media. By comparing the organizations we investigated reasons and underlying factors for their way of transferring knowledge.   In order to fulfill the purpose we made a qualitative research with four companies that are active on social media. We conducted semi-structured interviews with respondents holding both managerial positions as well as with employees working practically with social media.   Our study showed that both codification and personalization are used as knowledge transfer strategies when dealing with customers that misbehave on social media. The codification strategy is pursued by the use of databases, information-systems, guidelines and documentation. These methods were used to make knowledge available for all employees and to make work more effective. The personalization strategy is followed by talking to each other in person, via telephone, email or chat. This knowledge transfer strategy was pursued to exchange ideas in order to receive input and advice from one another.   We also found that when dealing with customers behaving badly towards other customers on social media, personalization holds a higher usage than codification. Further our study showed that three underlying factors affect the usage of the codification and personalization strategy, namely, closeness, previous experience and available knowledge transfer sources.

We propose a simple, passive and deployable approach for fingerprinting traffic on the wired side as a solution for three critical stealth attacks in wireless networks. We focus on extracting traces of the 802.11 medium access control (MAC) protocol from the temporal arrival patterns of incoming traffic streams as seen on the wired side, to identify attacker behavior. Attacks addressed include unauthorized access points, selfish behavior at the MAC layer and MAC layer covert timing channels. We employ the Bayesian binning technique as a means of classifying between delay distributions. The scheme requires no change to the 802.11 nodes or protocol, exhibits minimal computational overhead and offers a single point of discovery. We evaluate our model using experiments and simulations.

To combat channel fading, cooperative communication achieves spatial diversity for the transmission between source and destination through the help of relay. However, if the relay behaves abnormally or maliciously and the destination is not aware, the diversity gain of the cooperative system will be significantly reduced, which degrades system performance. In our thesis, we consider an one-relay decode and forward cooperative network, and we assume that the relay may misbehave with a certain probability. If the relay is malicious, it will garble transmission signal, resulting in severe damage to cooperative system. In this work, we discuss three kinds of malicious behavior detection. More specifically, we adopt sequential detection to detect the behavior of relay. If tracing symbols are inserted among the source message, the destination detects malicious after extracting the received tracing symbols. We adopt log-likelihood ratio test to examine these tracing symbols, and then determine the behavior of relay. If the source does not transmit tracing symbols, the destination detects misbehavior according to the received data signal. Furthermore, we employ sequential detection to reduce detection time for a given probabilities of false alarm and miss detection. Through simulation results, for a certain target on probability of errors, our proposed methods can effectively reduce numbers of observations. On the other works, the destination can effectively detect misbehavior of relay, and eliminating the damage causes by malicious relay without requiring large numbers of observations.

The primary objective of this study was to explore the influence of parental support on antisocial behavior among 1514 adolescents from Sarasota County (Florida). An integrated multilevel approach was developed considering elements of the social support paradigm and social learning theory. Using Hierarchical Linear Modeling (HLM), the results suggest that both paternal and maternal support were significant factors in the prevention of antisocial behavior. However, paternal support demonstrated to be stronger when students justified school misbehavior. At the school level, the findings suggest that the influence of parental support to reduce antisocial behavior competes with favorable definitions toward crime learned by youngsters from society and deviant peers.

La littérature en gestion des organisations est riche de travaux témoignant de pratiques transgressives en entreprise, aux motivations très diverses, mais qui souvent, sont le résultat d’initiatives individuelles. Rares sont les exemples de transgression collective en milieu professionnel, reposant sur un désaccord commun d’un aspect de l’organisation du travail.A partir d’une observation participante rétrospective au niveau d’un service d’une multinationale, je me suis interrogé sur ce phénomène qui peut être considéré de prime abord comme une forme de déviance, mais dont l’enquête de terrain cherche à montrer l’importance de l’impact des tensions organisationnelles et des comportements managériaux.Cette thèse a pour objectif de comprendre comment un groupe est parvenu à bâtir une action transgressive commune et à concilier les exigences contradictoires imposées par l’environnement, en étudiant les concepts de la coopération, de la connivence et du secret. / Organizational management has extensively studied organizational misbehaviors and their motivations, which often are initiated by individuals. Examples of collective deviance at work, based on a mutual disagreement on how to conduct a task, are unusual.Following a retrospective participant observation within a multinational department, I questioned this action which could be considered at first as a deviance. However I demonstrate based on fieldwork, that this action is the result of influences of organizational tensions and managerial behaviors.This thesis aims to understand how a group of individuals succeed in organizing a transgressive collective action, and how they conciliate with working requirements, using concepts such as cooperation, connivance and secret.

abstract: This dissertation historicizes the contemporary notions of student misbehavior through a critical study of 19th-century teacher manuals. Instead of reading the texts of the manuals as a window into the experiences of the past, I consider the manuals as discursive operations that enacted practices and ideals. In drawing upon historiographical and analytical methods inspired by Michel Foucault and Sara Ahmed, I explore how the intersection of student misbehavior with teacher pedagogy and disciplinary procedures enact “modes of subjection” (Foucault, 1995) and “affective orientations” (Ahmed, 2006) in the modernization of teacher pedagogy and schooling. I argue that the archive of manuals demonstrates the entanglement of student subjectivity and affect with modernizing regimes of governmentality and the marketplace. I equally argue that the modes of student misbehavior present in the archive provide avenues and strategies for thinking outside contemporary developmental and clinical framing of misbehavior. It is in rethinking misbehavior outside of contemporary frameworks that this dissertation provides an opportunity to reconsider how the boundaries of schooling and school participation might radically open up toward more diversity, inclusivity, and equity. / Dissertation/Thesis / Doctoral Dissertation Learning, Literacies and Technologies 2020

The aim of this paper is to investigate EFL (English as a Foreign Language) students’ acceptance of teacher interventions to disruptive behavior in the classroom. As a method, qualitative research was conducted, including a collection of qualitative and quantitative data through a questionnaire, as well as a qualitative analysis. The respondents to the questionnaire were grade 7-9 students, located in the southern part of Sweden. The results indicate that the two interventions which both research and the study’s participants accepted, were Shorter recess and Quiet reprimand. Further, the interventions which research and the respondents somewhat agreed on, were Ignore, Stare, Approach and Parents/principal. Lastly, the two interventions which research and the participants disagreed on, were Stop it and Other room. There is a need for more research on students’ acceptance of interventions; therefore, we recommend future researchers to investigate it further.