Effective interventions are imperative for students who are at-risk for academic failure. Response to Intervention (RTI), a service delivery framework, is gaining momentum in schools as it aims to provide effective and appropriate interventions of varying degrees. Frequently used in the form of a three-tier process, RTI addresses academic and behavioral deficits for students first at a school-wide level; next, at an individualized level; and finally, at a more intense individualized level. This study examined the effects of video self-modeling (VSM) as a Tier 2 RTI for two students in general education classrooms. Both students exhibited low rates of on-task behavior and were considered at-risk for academic failure. The first participant received intervention prior to his general education first grade math lesson. The second participant received intervention prior to his general education sixth grade writing lesson. The results of the study indicate that this method of intervention has potential. In spite of uncontrollable confounding variables, both participants' average on-task behavior minimally increased (by 6 and 3 percentage points respectively) over the course of intervention. Neither student was referred for Tier 3 interventions nor was classified as having a disability. Video self-modeling as a Tier 2 intervention may provide substantial instruction for students with learning deficits, thus reducing the number of individuals referred for special education services.

Music performance anxiety (MPA) is a significant concern for musicians of all ages, levels of mastery, and genders (Kenny, 2011). Whereas the anxiety-performance relationship has been well researched in athletes, similar research with musicians is sparse (Nordin-Bates, 2012). In the present research, video feed-forward self-modeling (FF-SM video) was explored as an intervention for use by musicians. FF-SM involves video-editing, typically, to depict a level of master performance higher than that yet attained by the individual. Although video FF-SM has been used successfully with athletes (Ste-Marie, Rymal, Vertes, & Martini, 2011) to increase self-efficacy and improve performance, its use has not yet been explored with musicians. In the present study, Bandura’s Self-efficacy Theory (1977) was used as a framework to explore whether FF-SM videos would increase self-efficacy, lower anxiety, and improve performance in adolescent musicians who self-reported MPA. Twelve string musicians, aged 13 to 18 years, who self-reported MPA took part in a two-week intervention where in one week they practiced with the use of a FF-SM video and in the alternate week they practiced without the video. At the end of each week, participants performed the selected repertoire from their video. Video FF-SM significantly increased musicians’ self-efficacy but only for those musicians who viewed the video in the second week. No changes in anxiety or performance levels were observed. Zimmerman’s triadic self-regulation model is used to explain the cyclical pattern of self-efficacy benefits. It is concluded that the FF-SM video can be an effective tool to increase self-efficacy for musicians who self-report MPA, but that an enactive experience is first needed for those benefits to occur. Research extended over a longer time frame is recommended in order to examine whether influences on anxiety and performance would emerge at a later time.

Les réseaux de télécommunications deviennent de plus en plus complexes, notamment de par la multiplicité des technologies mises en œuvre, leur couverture géographique grandissante, la croissance du trafic en quantité et en variété, mais aussi de par l’évolution des services fournis par les opérateurs. Tout ceci contribue à rendre la gestion de ces réseaux de plus en plus lourde, complexe, génératrice d’erreurs et donc coûteuse pour les opérateurs. On place derrière le terme « réseaux autonome » l’ensemble des solutions visant à rendre la gestion de ce réseau plus autonome. L’objectif de cette thèse est de contribuer à la réalisation de certaines fonctions autonomiques dans les réseaux de télécommunications. Nous proposons une stratégie pour automatiser la gestion des pannes tout en couvrant les différents segments du réseau et les services de bout en bout déployés au-dessus. Il s’agit d’une approche basée modèle qui adresse les deux difficultés du diagnostic basé modèle à savoir : a) la façon d'obtenir un tel modèle, adapté à un réseau donné à un moment donné, en particulier si l'on souhaite capturer plusieurs couches réseau et segments et b) comment raisonner sur un modèle potentiellement énorme, si l'on veut gérer un réseau national par exemple. Pour répondre à la première difficulté, nous proposons un nouveau concept : l’auto-modélisation qui consiste d’abord à construire les différentes familles de modèles génériques, puis à identifier à la volée les instances de ces modèles qui sont déployées dans le réseau géré. La seconde difficulté est adressée grâce à un moteur d’auto-diagnostic actif, basé sur le formalisme des réseaux Bayésiens et qui consiste à raisonner sur un fragment du modèle du réseau qui est augmenté progressivement en utilisant la capacité d’auto-modélisation: des observations sont collectées et des tests réalisés jusqu’à ce que les fautes soient localisées avec une certitude suffisante. Cette approche de diagnostic actif a été expérimentée pour réaliser une gestion multi-couches et multi-segments des alarmes dans un réseau IMS. / While modern networks and services are continuously growing in scale, complexity and heterogeneity, the management of such systems is reaching the limits of human capabilities. Technically and economically, more automation of the classical management tasks is needed. This has triggered a significant research effort, gathered under the terms self-management and autonomic networking. The aim of this thesis is to contribute to the realization of some self-management properties in telecommunication networks. We propose an approach to automatize the management of faults, covering the different segments of a network, and the end-to-end services deployed over them. This is a model-based approach addressing the two weaknesses of model-based diagnosis namely: a) how to derive such a model, suited to a given network at a given time, in particular if one wishes to capture several network layers and segments and b) how to reason a potentially huge model, if one wishes to manage a nation-wide network for example. To address the first point, we propose a new concept called self-modeling that formulates off-line generic patterns of the model, and identifies on-line the instances of these patterns that are deployed in the managed network. The second point is addressed by an active self-diagnosis engine, based on a Bayesian network formalism, that consists in reasoning on a progressively growing fragment of the network model, relying on the self-modeling ability: more observations are collected and new tests are performed until the faults are localized with sufficient confidence. This active diagnosis approach has been experimented to perform cross-layer and cross-segment alarm management on an IMS network.

This research examined the effects of self-regulated strategy development (SRSD), a cognitive strategy instructional method, on opinion writing by third grade students with learning disabilities. A video self-modeling (VSM) component was added to the SRSD method. A multiple probe across participants, single-subject design was used to determine the effectiveness of the SRSD instructional strategy, (POW + TREE), in combination with video self-modeling. Data from various components of writing, including essay elements, length of responses, time spent writing, and overall writing quality, were collected and assessed to determine the effectiveness of the intervention. All students who received the intervention improved their overall writing performance on opinion essays as measured by the number of opinion essay elements, including topic sentence, reasons, examples, and ending. During the maintenance phase of the intervention, students who received a VSM booster session increased their total number of opinion essay elements back to mastery levels.

This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in delivering behavioral interventions for young children on the autism spectrum.

Les réseaux actuels servent millions de clients mobiles et ils se caractérisent par équipement hétérogène et protocoles de transport et de gestion hétérogènes, et des outils de gestion verticaux, qui sont très difficiles à intégrer dans leur infrastructure. La gestion de pannes est loin d’être automatisée et intelligent, ou un 40 % des alarmes sont redondantes et seulement un 1 ou 2% des alarmes sont corrélées au plus dans un centre opérationnel. Ça indique qu’il y a un débordement significatif des alarmes vers les adminis-trateurs humains, a comme conséquence un haut OPEX vue la nécessité d’embaucher de personnel expert pour accomplir les tâches de gestion de pannes. Comme conclusion, le niveau actuel d’automatisation dans les tâches de gestion de pannes dans réseaux télécoms n’est pas adéquat du tout pour adresser les réseaux programmables, lesquels promettent la programmation des ressources et la flexibilité afin de réduire le time-to-market des nouveaux services. L’automatisation de la gestion des pannes devient de plus en plus nécessaire avec l’arrivée des réseaux programmables, SDN (Software-Defined Networking), NFV (Network Functions Virtualization) et le Cloud. En effet, ces paradigmes accélèrent la convergence entre les domaines des réseaux et la IT, laquelle accélère de plus en plus la transformation des réseaux télécoms actuels en menant à repenser les opérations de gestion de réseau et des services, en particulier les opérations de gestion de fautes. Cette thèse envisage l’application des principes d’autoréparation en infrastructures basées sur SDN et NFV, en focalisant sur l’autodiagnostic comme facilitateur principal des principes d’autoréparation. Le coeur de cette thèse c’est la conception d’une approche de diagnostic qui soit capable de diagnostiquer de manière continuée les services dynamiques virtualisés et leurs dépendances des ressources virtuels (VNFs et liens virtuels) mais aussi les dépendances de ceux ressources virtuels de la infrastructure physique en-dessous, en prenant en compte la mobilité, la dynamicite, le partage de ressources à l’infrastructure en-dessous / Current networks serve billions of mobile customer devices. They encompass heterogeneous equipment, transport and manage-ment protocols, and vertical management tools, which are very difficult and costly to integrate. Fault management operations are far from being automated and intelligent, where around 40% of alarms are redundant only around 1-2% of alarms are correlated at most in a medium-size operational center. This indicates that there is a significant alarm overflow for human administrators, which inherently derives in high OPEX due to the increasingly need to employ high-skilled people to perform fault management tasks. In conclusion, the current level of automation in fault management tasks in Telcos networks is not at all adequate for programmable networks, which promise a high degree of programmability and flexibility to reduce the time-to-market. Automation on fault management is more necessary with the advent of programmable networks, led by with SDN (Software-Defined Networking), NFV (Network Functions Virtualization) and the Cloud. Indeed, the arise of those paradigms accelerates the convergence between networks and IT realms, which as consequence, is accelerating faster and faster the transformation of cur-rent networks leading to rethink network and service management and operations, in particular fault management operations. This thesis envisages the application of self-healing principles in SDN and NFV combined infrastructures, by focusing on self-diagnosis tasks as main enabler of self-healing. The core of thesis is to devise a self-diagnosis approach able to diagnose at run-time the dynamic virtualized networking services and their dependencies from the virtualized resources (VNFs and virtual links) but also the dependencies of those virtualized resources from the underlying network infrastructure, taking into account the mobility, dynamicity, and sharing of resources in the underlying infrastructure

本研究は，視聴する映像を学習者自身で選択させることによる運動学習効果を検討する事が目的であった．本研究の結果，学習者自身が映像を選択する事で，実験者によって選ばれた映像を視聴した場合と比較して，映像と学習者の運動イメージとの認知的な一致度を高めた．さらに，観察角度や選択の方法の違いが運動学習の向上に寄与する事を明らかにした．これらの知見は，運動指導や体育授業における映像の視聴方法や選び方といった提供方法の提案に繋がるだろう． / This study aimed to examine the motor learning effects of allowing learners to choose their own footage to watch. As a result, this study showed that the learner's chosen footage enhanced the cognitive consistency between the video and the learner's motor imagery, compared to the case in which the experimenter chosen video was shown. Furthermore, we found that differences in observational angle and the method of choice contributed to the improvement of motor learning. These findings would be led to propose a method of providing the video, such as how to watch them and how to choose them on a motor instruction and physical education. / 博士(スポーツ健康科学) / Doctor of Philosophy in Health and Sports Science / 同志社大学 / Doshisha University