Syftet med arbetet är att undersöka en sångares kroppsliga gestaltning av ett musikstycke vid musikaliskt framträdande. Detta har undersökts genom videofilmning av framträdanden, och analyser av dessa med fokus på kroppsliga uttryck. Till detta har loggbok förts över tankar och händelser från framträdandena. I analysen av framträdandena har som teoretiskt perspektiv ett multimodalt designteoretiskt perspektiv använts. I resultatet presenteras hur olika resurser används, hur dessa resurser samspelar och hur de påverkar varandra. Det framkommer att den kroppsliga gestiken har två huvuduppgifter vid framträdanden, dels att vara stödjande för sångtekniken samt uttrycka och gestalta ett budskap. Det framkommer också att inre visuella bilder används, dels för att gestalta och förmedla ett budskap. I diskussionen diskuteras olika förutsättningar för framträdanden utifrån det designteoretiska perspektivet och den tidigare forskning som tagits upp i bakgrundskapitlet. / The purpose of this study is to examine the singer’s physical disposition when performing a piece of music. This has been investigated by video documented performances and analysis with a focus on bodily expressions. To transfer the thoughts and events from the different performances, I have used a logbook. The multi-modal design theory perspective has been used as a theoretical perspective in the analysis of the performances. The result shows how the various resources are used and how these resources interact and how they affect each other. The bodily gestures have two main tasks during the performances: to be supportive of vocal technique and to express and portray a message. Results emerge indicating that the internal visual images are used to partly portray and convey a message. In the discussion chapter different aspects for the performance are discussed based on the design theoretical perspective and the previous research raised in the background chapter.

Syftet med denna självobservationsstudie är att utforska tillvägagångssätt vid instudering av sång utifrån ett textfokus. I detta arbete beskrivs huvudsakligen tre metoder för sig och när de används kombinerat. Metoderna till instudering är lyssna, rösten och skriva.  Studien är baserat på sociokulturellt perspektivet samt annan relevant information om instudering. Metoden som används i arbetet är videor från övningstillfällen samt loggbok som antecknats efter varje övningstillfälle. Studien är baserad på mig själv där jag under två veckor fört 14 loggboksinlägg och två videoinspelningar när jag aktivt arbetar i 20 minuter per inlägg under hösten 2017. I resultatet visas hur jag använt de tre metoder som är min röst, skrift och hörseln som användes vid instudering av två olika sånger. Slutligen diskuteras resultatet i förhållande till bakrundskapitlet. / This self-observation purpose is to find new ways to learn song with text focus. The study presents three different methods for them self and when they are integrated in each other. The methods that been used is listening, The voice and writing. The study is based on Sociocultural perspective and other relevant research when it comes to studding songs. the method I’ve used for this study is video recording when I practise and notes from practise sessions. For two weeks, I gathered information and 14 practice sessions with two films. One session was 20 minutes each and was gather autumn 2017. Later on, in the result I will present how I used these three methods which are voice, writing and listening which I used to learn the two-different song. At the end the result will be discussed to the earlier research.

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

Syftet med studien är att få en fördjupad insikt i vad lärandet av sångtekniken neutral utan luftinnebär. För att undersöka detta har jag under en fem veckors period övat neutral utan lufti 20-30 minuter, tre dagar i veckan. Under och efter övningspassen har loggbok använts för att dokumentera nya upplevelser av lärandeprocessen och utöver detta har även 5 videodokumentationer av övningspass gjorts. I denna studie utgörs den teoretiska utgångspunkten av ett designteoretiskt perspektiv med fokus på vilka semiotiska resurser som används i lärandet. Studiens frågeställningar är: Vilka teckenskapande resurser används vid inlärningen av den nya funktionen så kalladneutral utan luft? Hur används dessa resurser? Resultatet visar att de viktigaste resurserna är kroppen och de sångtekniska elementen. Dessa resurser används för att åstadkomma ett stadigt och önskvärt resultat på ett oskadligt vis. I diskussionskapitlet diskuterar jag de resurser som krävts i inlärningen av sångtekniken neutral utan luft. / The purpose of the study is to gain a deepened insight in what the learning of the singing technique neutral without aircan mean. To study this I have practiced neutral without air20-30 minutes per day, three times a week over a five weeks’ period. During and after every practice session I have written a log to document new personal experiences of the learning process. In addition to this I have documented five practice sessions with a video camera. The theoretical perspective of this study is design theory with focus on the semiotic resources used during the learning process. The study’s research questions are: Which semiotic resources are used during learning the song technique known as neutral without air? How are these resources used? The results show that the most central resources that were used were the body and the vocal elements of the technique. These resources are used to achieve a steady and desirable result in an innocuously manner. In the discussion, I describe the necessary resources for the learning process of the song techniqueneutral without air.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-02-19T17:39:23Z No. of bitstreams: 1 roneypolatodecastro.pdf: 4463862 bytes, checksum: 79021d21dbd8ffe2a555c4bba6179d12 (MD5) / Rejected by Adriana Oliveira (adriana.oliveira@ufjf.edu.br), reason: "sujeitosdocentes "escreve junto mesmo? on 2016-02-26T13:53:53Z (GMT) / Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-02-26T14:12:56Z No. of bitstreams: 1 roneypolatodecastro.pdf: 4463862 bytes, checksum: 79021d21dbd8ffe2a555c4bba6179d12 (MD5) / Rejected by Adriana Oliveira (adriana.oliveira@ufjf.edu.br), reason: Favor verificar se o termo "sujeitosdocentes" está escrito junto na disertação on 2016-06-02T14:14:44Z (GMT) / Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-06-02T14:17:43Z No. of bitstreams: 1 roneypolatodecastro.pdf: 4463862 bytes, checksum: 79021d21dbd8ffe2a555c4bba6179d12 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-06-02T15:14:16Z (GMT) No. of bitstreams: 1 roneypolatodecastro.pdf: 4463862 bytes, checksum: 79021d21dbd8ffe2a555c4bba6179d12 (MD5) / Made available in DSpace on 2016-06-02T15:14:16Z (GMT). No. of bitstreams: 1 roneypolatodecastro.pdf: 4463862 bytes, checksum: 79021d21dbd8ffe2a555c4bba6179d12 (MD5) Previous issue date: 2014-11-27 / Experiência e constituição de sujeitosdocentes: relações de gênero, sexualidades e formação em Pedagogia – a tese tem como foco de análises as experiências construídas em uma disciplina do curso de Pedagogia, da Universidade Federal de Juiz de Fora, denominada “Tópicos Especiais: Gênero, Sexualidade e Educação”. O trabalho articula problematizações acerca da formação docente para essas temáticas com as experiências construídas na disciplina. As perspectivas que organizam as análises tomam como inspiração os estudos pós-estruturalistas das relações de gênero, sexualidades e educação e os estudos foucaultianos, em especial os escritos sobre experiência advindos do pensamento de Michel Foucault e do educador espanhol Jorge Larrosa. Nesta tese discuto algumas questões concernentes aos processos de formação docente nas universidades e as especificidades desse debate no que tange ao trabalho com as temáticas das relações de gênero e sexualidades em disciplinas de cursos de Licenciatura em Pedagogia. Outro foco é a discussão do principal dispositivo utilizado na pesquisa e na disciplina: os diários de bordo. Assim, apresento a proposta de uma narrativa que se constrói a partir da disciplina e da própria escrita como instância de produção de subjetividades. Na última seção da tese articulo problematizações acerca de temáticas discutidas na disciplina e tomadas pelas estudantes como questões a serem pensadas e, por conseguinte, a serem narradas nos diários de bordo. Discuto, desse modo, a questão das homossexualidades, atravessada pela heteronormatividade e pela homofobia; o discurso religioso-cristão como instância de assujeitamento e normatização moral; as relações de gênero, a constituição de subjetividades e as relações de poder que assujeitam e promovem o machismo e as violências contra as mulheres. Com as análises pretendo provocar questionamentos que atravessam as relações entre formação docente na universidade e as temáticas das relações de gênero e sexualidades. / Experience and constitution of docent subjetcs: relations of gender, sexualities and graduation in Pedagogy – this thesis is focused on the analyses concerning the experiences built in a discipline of the Federal University of Juiz de Fora Pedagogy course denominated “Special Topics: gender, sexualities and education”. The work articulates problematisations on the docent formation for those themes with the experiences built in the discipline. The perspectives under which the analyses are organised were inspired by the Post-structuralist studies of gender relations, sexualities and education of the foucaultian studies, specially the writings on the experiences from the tinking both of Michel Foucault and of the spanish educator Jorge Larossa. In this thesis I discuss questions concerning the processes of the docent formation in universities and the specificities of that debate regarding the work with the themes of relations of gender and sexualities in disciplines of the bachelor´s degree in Pedagogy. Another focus is the discussion of the main device utilized on the research: the logbook. Hence it is presented the proposal of a narrative constructed from the discipline and from the writing itself as an instance of subjectiveness production. In the last section of the thesis problematisations concerning the themes discussed and taken by the students are articulated as questions to be thought and, therefore, to be narrated on the logbooks. It is discussed, thus, the homosexuality issue crossed by the heteronormativity and homophobia; the christian-religious discourse as instance of subjection and moral normatization; the relations of gender, the constitution of subjectiveness and the relations of power to which a person is subjected and promote machismo and violence against women. With the analyses I intend to provoke questionings that cross the relations between docent formation in the university and the themes of gender relations and sexuality.

Syftet med denna självstudie har varit att undersöka min livsvärld när jag spelar a prima vista och syna de tankemönster som uppstår. Arbetet genomsyras av ett livsvärldsperspektiv och utgångspunkten är frågeställningarna: Hur upplever jag avistaspel samt Hur förändras min livsvärld under arbetets gång. Insamling av material har skett via en strukturerad processloggbok som förts efter varje dokumenterat avistapass. Dessa anteckningar tillsammans med frågeställningarna lägger sedan grund för resultatet som delas upp i två avsnitt. Det första, Upplevelser av a prima vista, redogör för betydelsen av sammanhang utifrån faktorerna Tid och plats, Material och progression samt Avista med sällskap. Jag redovisar i detta avsnitt återkommande mönster i upplevelsen av min avistaläsning som förhåller sig till dessa faktorer och synar vilket sammanhang som tycks gynna min övning bäst. Resultatets andra del, Min föränderliga livsvärld, beskriver sedan hur min livsvärld har förändrats under projektets gång. Detta redovisas utifrån rubrikerna: Tankemönster, Medvetenhet samt Motivation och nya tankemönster. I detta avsnitt går det att skildra en resa från att förknippa min prestation med jaget, till att se på avistaläsning som ett fristående fenomen där medveten övning hjälper mig framåt i utvecklingen. Slutligen knyts resultatet till bakomliggande litteratur och forskning i diskussionsavsnittet. Under rubriken a prima vista och övning diskuteras mina upplevelser i förhållande till färdigheter i avistaspel, därefter beskrivs min resa mot en ny livsvärld, där fokus ligger på känslomässiga aspekter och betydelsen av medvetenhet. / The purpose of this self-observation has been to see into my life-world while sight-reading sheet music for piano and to visualize the thinking patterns that arise followed by reflection. The work is permeated by a life-world perspective with following questions as starting point: How do I experience playing a prima vista and In which ways does my life-world change during the project. The material has been collected via a structured process logbook, which has been written in after every occasion. These notes along with the questions described above then shapes the result which is divided into two sections. The first section, Experiences during a prima vista explains the importance of context based on Time and place, Material and progression, and Playing a prima vista with someone watching. In this section, I report repeating patterns in the experience of my sight-reading that relate to these contexts and I also point out which context seems to benefit my exercise the best. The second section of the result My changeable life-world, then explains in which ways my life-world has changed during the project. Beneath the headings Thinking patterns, Awareness and New thinking patterns it is possible to see a journey from associating my achievements with my identity to looking at sight-reading as a phenomenon possible to manage by being aware while practicing. Lastly I relate the literature and researches to my result in a closing discussion. Under the headline a prima vista and practice I discuss my experiences and relate these to relevant skills during sight-reading, thereafter I describe my journey towards a new life-world where main topics are emotional aspects and the meaning of awareness.

Denna självobservationsstudie undersöker hur övande av instrument påverkar det psy- kiska måendet samt hur det psykiska måendet påverkar övningen. Syftet med arbetet är att undersöka hur mycket övning som ska planeras i för väg så att det gynnar mitt mående samtidigt som övningen är effektiv. Under tre veckors tid användes tre olika sätt att pla- nera övning för att senare kunna hitta mönster i mående och övningskvalitet. En vecka planerades övningen i för väg, en vecka planerades ingen övning utan all övning var spon- tan och baserad på motivation och lust, och en vecka kombinerades dessa sätt genom att planera en del övning i för väg men även lämna utrymme för spontan övning. Studien ut- går från det fenomenologiska perspektivet och frågeställningarna lyder Upplever jag att övningens kvalitet påverkar mitt psykiska mående, och i sådana fall på vilka sätt? Upplever jag att det finns psykiska aspekter som påverkar min övning, och i sådana fall på vilka sätt? och I vilka situationer upplever jag att jag har en bra balans mellan planerad respektive spontan övning som gynnar både min övning och mitt psykiska mående? I undersökningen dokumenterades tankar kring övningen i en ljudloggbok i samband med övningstillfällena och mitt psykiska mående dokumenterades i en applikation, i form av en digital dagbok. Detta dokumenterade material bearbetades med hjälp av tematisk analys. Det framkom- mer i resultatet att mitt mående ofta speglar hur övningen har gått och har jag mått dåligt innan övningen så har det ofta varit svårt att fokusera, vilket påverkade övningens kvali- tet. Det framkommer också att det fanns väldigt lite motivation till övning under veckan där jag planerade all övning i för väg samt veckan där ingen övning planerades i för väg. Under veckan där en del övning planerades i förväg och en del övning skedde spontant visade sig att spontan övning ofta skedde till följd av planerad uppvärmning/övning tidi- gare samma dag. / This self-observation study examines how practicing an instrument affects the mental state and how the mental state affects the practice. The purpose of the study is to investi- gate how much exercise should be planned in advance so that it benefits my well-being while the exercise is effective. During three weeks, three different ways of planning exer- cise were used in order to later find patterns in mood and exercise quality. One week the exercise was planned in advance, one week no exercise was planned but all exercise was spontaneous and based on motivation and desire, and one week these ways were com- bined by planning some exercise in advance but also leaving room for spontaneous exer- cise. The study is based on the phenomenological perspective and the questions are: Do I feel that the quality of the exercise affects my psychological well-being, and if so, in what ways? Do I feel that there are psychological aspects that affect my practice? If so, in what ways? and In which situations do I feel that I have a good balance between planned and spontaneous practice that benefits both my practice and my mental well-being? Thoughts about the exercise were documented in an audio log book in connection with the exercise sessions and my mental state was documented in an application, in the form of a digital diary. This documented material was processed using thematic analysis. It appears in the results that my mood often reflects how the exercise went and if I felt bad before the ex- ercise, it was often difficult to focus, which affected the quality of the exercise. It also ap- pears that there was very little motivation for exercise during the week where I planned all exercise in advance and the week where no exercise was planned in advance. During the week where some exercise was planned in advance and some exercise happened spontaneously, it turned out that spontaneous exercise often happened as a result of planned warm-up/exercise earlier the same day.

Nos travaux portent sur l’objet d’observation scientifique suivant : mesure et lisibilité de la performance globale et durable, appliqué au champ des organisations de l’économie sociale et solidaire.Notre objectif est de démontrer qu’il est possible de créer un système de contrôle de gestion de la performance globale et durable (PFGD), qui intègre les diverses dimensions visibles et cachées de la performance économique et sociale des organisations de l’économie sociale et solidaire, tout en contribuant à augmenter la lisibilité de la PFGD auprès des parties prenantes internes et externes.Nous commençons notre exposé autour de la question des enjeux de la mesure de la performance globale et durable (désormais PFGD), avec un focus spécifique sur notre champ composé des organisations de l’économie sociale et solidaire (désormais OESS). Ensuite, parmi les différentes approches abordées, nous concentrons notre analyse sur l’ingénierie de la mesure socio-économique. Au regard de notre problématique, cette approche semble proposer des éléments de réponse à la fois sur la globalité et la durabilité de la performance, mais aussi sur sa lisibilité pour les parties prenantes. La deuxième partie de notre thèse présente notre proposition, qui prend la forme d’un outil spécifique du système de contrôle de gestion socio-économique : le tableau de bord de pilotage et de mesure de la PFGD. D’une part, nos résultats détaillent les dégradations de la PFGD, rendues visibles par une approche qualimétrique d’explicitation des coûts et des performances cachés. D’autre part, nous expliciterons de manière qualitative les différentes illustrations du manque d’intégration de la PFGD. Enfin, nous proposons un modèle, ainsi qu’un exemple de tableau de bord, qui intègrent à la fois une visibilité accrue de la PFGD, ainsi qu’une lisibilité augmentée pour les parties prenantes internes et externes. / Nos travaux portent sur l’objet d’observation scientifique suivant : mesure et lisibilité de la performance globale et durable, appliqué au champ des organisations de l’économie sociale et solidaire.Notre objectif est de démontrer qu’il est possible de créer un système de contrôle de gestion de la performance globale et durable (PFGD), qui intègre les diverses dimensions visibles et cachées de la performance économique et sociale des organisations de l’économie sociale et solidaire, tout en contribuant à augmenter la lisibilité de la PFGD auprès des parties prenantes internes et externes.Nous commençons notre exposé autour de la question des enjeux de la mesure de la performance globale et durable (désormais PFGD), avec un focus spécifique sur notre champ composé des organisations de l’économie sociale et solidaire (désormais OESS). Ensuite, parmi les différentes approches abordées, nous concentrons notre analyse sur l’ingénierie de la mesure socio-économique. Au regard de notre problématique, cette approche semble proposer des éléments de réponse à la fois sur la globalité et la durabilité de la performance, mais aussi sur sa lisibilité pour les parties prenantes. La deuxième partie de notre thèse présente notre proposition, qui prend la forme d’un outil spécifique du système de contrôle de gestion socio-économique : le tableau de bord de pilotage et de mesure de la PFGD. D’une part, nos résultats détaillent les dégradations de la PFGD, rendues visibles par une approche qualimétrique d’explicitation des coûts et des performances cachés. D’autre part, nous expliciterons de manière qualitative les différentes illustrations du manque d’intégration de la PFGD. Enfin, nous proposons un modèle, ainsi qu’un exemple de tableau de bord, qui intègrent à la fois une visibilité accrue de la PFGD, ainsi qu’une lisibilité augmentée pour les parties prenantes internes et externes.