The Adolescent Discouragement Indicator (ADI) was developed to assess the Adlerian construct of discouragement. The 75-item ADI contains five subscales corresponding to the five life tasks specified in Individual Psychology and is specifically designed to pinpoint the area and degree of adolescent discouragement. Item selection was based on ratings by five prominent Adlerians and item correlation with subscale scores. Age and sex norms for the ADI were established on 225 females and 299 males 12 to 18 years of age. Findings indicate that female adolescents are less discouraged than male adolescents on all scales except the love scale and both sexes reported the least amount of discouragment on the love scale. The only significant difference among the age groups is between the 13-year-olds and the 15, 16, and 17-year-olds on the love scale. An internal consistency coefficient of .95, a 2-week test-retest coefficient of .89, and a 4-week test-retest coefficient of .92 indicates that the ADI is a reliable instrument. Negative and significant (p < .001) correlations between the ADI and Social Interest Index (Greever, Tseng, & Friedland, 1973) and between the ADI and the Social Interest Scale (Crandall, 1975) contribute to construct validity and support Adler's belief that discouragement and social interest are inversely related. Results of behavioral and academic comparisons on a sample of adolescent males (N=57) seem to indicate a link between behavior, academic performance, and levels of discouragement. Results of factor analysis and interscale correlations are presented. Implications for further research include continued validation using behavioral criteria associated with discouragement, refinement of the subscales and establishment of score ranges to indicate when an adolescent is considered discouraged.

This study resulted in the development of the Discouragement Scale for Adults (DSA), an assessment instrument for the Adlerian construct of discouragement in adults more than 18 years of age. The DSA is a 60-item instrument that contains five sub-scales corresponding to five life tasks identified in Adlerian literature as work, love, society, self, and spirituality. Age, gender, and ethnicity norms were established for the DSA using a diverse sample (N=586). Additional normative data was developed with a presumed discouraged sample (N=47), and a special sample of traditional college students aged 18-27 years (N=531). Findings on the norm sample indicated that females are less discouraged than males on the Total DSA and on society and spirituality sub-scales. The 18-34 year old group was more discouraged than other age groups on the Total DSA and on work, society, and spirituality sub-scales. Presumed discouraged sample findings indicated that females were less discouraged than males on the society sub-scale. College student findings indicated that females were less discouraged than males on the Total DSA and sub-scales of love, society, spirituality, and work. A significant difference was found among ethnic groups in self sub-scales. Students with no absences per week were less discouraged than students with two absences per week. Students with lower grade point averages (GPA) were more discouraged on the Total DSA and work sub-scales. DSA internal consistency coefficients were .9392, .9496, and .9327 for norm, presumed discouraged, and college student samples respectively. Correlations between DSA and two social interest surveys reflect an inverse relationship between discouragement and social interest. Results indicate that the DSA is a useful assessment instrument for research and counseling purposes with college students. Further research should include greater geographical and ethnic diversity as well as validation among diverse college samples and non-traditional students. Additionally, a standard range of scores should be established to indicate varying levels of discouragement.

The study analyzed how parenting stress and discouragement affect stepfamily functioning. Whether the parent was a biological parent or stepparent, whether the stepparent was a stepmother or stepfather, or whether the marriage had been formed more or less than two years was also considered. One assumption made was that increased parenting stress and discouragement will lead to decreased family functioning. Other assumptions were that there will be more increased parenting stress and discouragement and decreased family functioning found in stepparents than biological parents, in stepmothers more than stepfathers, and in parents in families formed less than two years more than those in families formed more than two years. Complete data was collected from 30 subjects. Three instruments were used in the study. The Parenting Stress Index measures how much stress parents experience in areas relating to how they see their child and how they see themselves as parents. The Discouragement Scale for Adults was developed to measure the Adlerian concept of discouragement in an adult population. The Family Assessment Device measures how a family functions.

The aim of this thesis is an analysis of motivating and discouraging elements influencing the contentment of nursing staff of the Hospital in České Budějovice a.s. The theoretical part is focused on the motivation in general, that means what the known and used theories of motivation are. Furthermore I will introduce the profession of the nurse itself and its development. I will outline the system of rewarding and lifelong education and last but not least I will mention the burnout syndrome. In the practical part of the thesis I will evaluate the results of the survey of motivation, focusing mainly on the real motivations and discouragements for the nurses, I will compare various variables, ascertain their dependencies and confirm or disapprove my own stated hypothesizes. At the end of thesis, there is a discussion, where I analyse the results and I try to suggest possible solutions regarding the gained facts.

This is an exploratory study and qualitative investigation of the social construction and enforcement of gender through social interactions with a specific focus on how gender policing is experienced within the LGBTQ community in Riverdale (pseudonym), the specific location of this study. Gender policing refers to the implicit and explicit feedback that one is accomplishing gender inappropriately according to contextual norms, expectations, and ideals, with the implied meaning that not conforming will result in real or assumed negative consequences. Two focus groups comprised of five people each who self-identified along the lesbian, gay, bisexual, transgender, and/or queer spectrum(s) in at least one context in their lives were used as the primary method for data collection. Inclusion criteria were based on those who identified with the LGBTQ community in Riverdale or who had had experiences in Riverdale in spaces that were predominantly LGBTQ. Focus group questions attempted to elicit participants' experiences within the LGBTQ community in Riverdale as they negotiated a sense of self in relation to others in the LGBTQ community. The content of the focus group discussions were analyzed using Interpretative Phenomenological Analysis (IPA) as described by Smith and Osborn (2003). This study illuminates how gender as a system of power is experienced and assigned meaning within interpersonal relationships in service of developing a social identity through inclusion within an LGBTQ community. Results from the data analysis yielded five broad themes: (a) gender oppression, (b) discouragement with community, (c) attempts to cope, (d) queer, and (e) change. These themes reflect narratives of oppression in the dominant culture and the impact of oppression on identity work in the LGBTQ community in a rural college town. Results are presented within the context of gender and gender policing on structural levels, interpersonal levels, and the level of internalized self-policing. Instances of gender policing on an interactional level were often associated with the assumed threat of social rejection and isolation and the experience of disappointment, pain, and disconnection. Results from this study support the literature on (a) the accomplishment of gender, (b) the maintenance of power differentials through the regulation of perceived differences between sex and gender categories, (c) the development of identity as group process, and (d) perceived problems within the LGBTQ community such as the maintenance of oppression and barriers to social change through the process of inclusion and exclusion.

The Discouragement Scale for Adults (DSA) was developed to assess for the Adlerian construct of discouragement in adults age 18 years and over. Data were collected from three samples: norm (n=586), presumed discouraged (n=47), and parents of children with craniofacial anomaly (n=105). Five subscales corresponding to life tasks identified in Adlerian literature as work, love, society, self-significance, and spirituality underlie the 60 item DSA. Item selection was based on ratings by five notable Adlerians and item correlations with scale scores. Gender, age, and ethnicity norms were established for the norm, presumed discouraged, and craniofacial samples. Across three samples, no significant ethnic differences were found. Normative findings indicated females are less discouraged than males on the Total DSA, the society and spirituality subscales. Age findings indicated the 18-34 year old sample is more discouraged than other ages on the Total DSA, the work, society, and spirituality subscales. Presumed discouraged findings indicated females are less discouraged than males on the society subscale. Craniofacial findings indicated females are less discouraged on the society subscale, but more discouraged on the self-significance subscale than males. Age findings indicated the 18-34 year old sample is more discouraged than other ages on the self subscale. Research on CPA parents' relationship status, CPA child's birth order, parental role of adult to CFA child, length of time the parent has cared for CFA child, the CFA child's age, CFA parent's education level, and CFA child's craniofacial anomaly diagnosis was conducted. Findings indicated birthmothers are less discouraged than birthfathers on the society subscale, but more discouraged on the self-significance subscale. Internal consistency ratings of the DSA were .9392, .9496, and .9365 for three samples. Correlations to measures of social interest were negative and significant, reflecting an inverse relationship between discouragement and social interest. Factor analysis and interscale correlations are presented. Future research could include continued instrument validation and establishment of score ranges to indicate adult discouragement.

This dissertation consists of three essays studying the theory of dynamic contest. This analysis mainly focuses on how the outcome and the optimal design in a dynamic contest varies on contest technology, heterogeneous players, contest architecture, and bias instruments. The first chapter outlines the dissertation by briefly discussing the motivations, methods, and main findings in the following chapters. Chapter 2 considers a situation in which two groups compete in a series of battles with complete information. Each group has multiple heterogeneous players. The group who first wins a predetermined number of battles wins a prize which is a public good for the winning group. A discriminatory state-dependent contest success function will be employed in each battle. We found that in the subgame perfect Nash equilibrium (equilibria), the lower valuation players can only exert effort in earlier battles, while the higher valuation players may exert effort throughout the entire series of battles. The typical discouragement effect in a multi-battle contest is mitigated when players compete as a group. We also provide two types of optimal contest designs that can fully resolve the free-rider problem in group contests. Chapter 3 investigates optimal contest design with multiple heterogeneous players. We allow the contest designer to have one or multiple/mixed objectives, which includes the following parts: the total effort; the winner's effort; the maximal effort; and the winning probability of the strongest player. We provide a one-size-fits-all contest design that is optimal given any objective function. In the optimal contest, the designer will have one of the weaker players exhaust the strongest in the contest with infinite battles. We obtain the required conditions on different contest frameworks (e.g., all-pay auctions and lottery contests) and bias instruments (e.g., head starts and multiplicative bias). This means the contest designer has multiple alternatives to design the optimal contest. The last chapter investigates a situation where two players compete in a series of sequential battles to win a prize. A player can obtain certain points by winning a single battle, and the available points may vary across the battles. The player who first obtains predetermined points wins the prize. We fully characterize the subgame perfect Nash equilibrium by describing the indifference continuation value interval. We found that when two players are symmetric, they only compete in the separating battle. In the general case, we found that winning a battle may not create any momentum when the weight of the battle is small. A small enough adjustment of a battle's weight will not change both players' incentive to win the battle. Increasing (or decreasing) a battle's weight weakly increases (or weakly decreases) both players' incentive to win. / Doctor of Philosophy / A contest in economics is defined as a situation in which players exert positive effort to win a prize. The effort can be money, time, energy, or any resource that is used in a competition. The prize can be monetary or other perks from winning a competition. In this dissertation, we explore dynamic multi-battle contests where the winner is not decided by one single competition but by a series of sequential competitions. For example, the US presidential primary begins sometime in January or February and ends about mid-June and candidates will compete in different states during the time. In NBA finals, the winner is decided by a best-of-seven contest. The team that first wins four games becomes the champion. In the second chapter, we explore multi-battle group contest in which each group has multiple heterogeneous players. The group who first wins a certain number of battles wins a prize. The prize is a public good within the winning group so players in the winning group can enjoy the prize regardless their effort. We found that players with high prize valuation will be discouraged in earlier battles due to high expected effort in later battles. This may make high-value players only exert effort in later and more decisive battles. The low-value players will exert effort in earlier battles and will free rider on high-value players in later battles. We also provide the optimal contest design that can fully resolve the free-rider problem. In the optimal contest design, the designer should completely balance two groups in every battle. In the third chapter, we explore the optimal contest design in the multi-battle contests with multiple heterogeneous players. The contest designer can have one or multiple/mixed objectives. We found a "one size fits all" multi-battle contest design that is optimal for various objective functions. In the optimal contest design, the designer should give different advantages to the strongest player and one of the weaker players. More specifically, the weaker player is easier to win each battle, while the strongest player needs to win fewer battles. This overturns the conventional wisdom that the advantage should be only given to the weaker players. In the fourth quarter, we explore the multi-battle contest that in which each battle has a different weight, that is, some battles may more or less important than others. We found that when a battle's weight is small, players may feel indifference between winning or losing the battle. Therefore, winning such battles will not create any momentum, and players tend to give up those battles by exerting no effort. We also found that when we increase or decrease a battle's weight, if the adjustment is small, it will not change players' incentive to win a battle. However, if the adjustment is large enough, it will increase or decrease players' incentive to win in the same direction.

Le premier chapitre soutient que dans ces économies om la qualité institutionnelle des lois sur les garanties et les faillites est faible, la collatéralisation excessive rend la prise de risque sous-optimalement plus couteuse pour les emprunteurs. Cela décourage le potentiel entrepreneurial et entrave ainsi la croissance potentielle de jeunes entreprises ayant un impact important sur la création d’emplois dans l’économie.Le deuxième chapitre met l’accent sur le canal de «déconnexion». La région du MENA est caractérisée par une proportion inhabituellement élevée d’entreprises qui n’ont pas besoin de financement. Ces entreprises sont moins susceptible de considérer l’accès au crédit comme une préoccupation majeure, sont moins susceptibles d’avoir acquis des immobilisations, et sont moins susceptibles de prévoir une opération de développement.Ces résultats tiennent également en tenant compte de l’ensemble des caractéristiques standard des entreprises. Nous étudions ensuite comment la politique de collatéralisation impact les performances des entreprises à travers le canal de «déconnexion». Dans le troisième chapitre, je passe à un échantillon de pays de l’OCDE. Une littérature croissante souligne le rôle du commerce avec les économies émergentes, en particulier la Chine, dans la destruction des emplois dans le secteur manufacturier comme le processus de désindustrialisation des les économies avancées. Cependant, pour quantifier la pertinence de l’exposition aux importations en provenances des marchés émergents, nous devons démêler le canal commercial du canal de productivité traditionnel. Dans ce chapitre, nous développons un modèle simple du changement structurel dans une économie ouverte pour en déduire des implications empiriques que nous analysons pour un échantillon de pays de l’OCDE. Dans les économies ouvertes, lorsque la croissance de la productivité de l’industrie nationale est plus rapide que celle des services,mais plus lente que celle de l’industrie étrangère, alors la part industrielle peut diminuer dans les économies avancées, tant en valeur ajoutée qu’en emploi. Nous appelons ce phénomène «double désindustrialisation». Nous trouvons des effets significatifs et quantitativement pertinents du commerce sur le changement structurel dans les économies avancées. En outre, alors que de nombreuses études étudient l’accélération de l’ampleur des importations en provenance de Chine depuis 2000 pour expliquer le modèle de désindustrialisation dans les économies avancées, nous soulignons que le changement de la composition des exportations chinoises vers les secteurs des technologies d’information et de communication et la naturante changeante du progrès technologique dans les économies émergentes pourrait contribuer à la compréhension du phénomène de désindustrialisation de l’après 2000. / This thesis investigates the role of collateral environment and trade exposure on the allocation of employment across firms and sectors. The first chapter argues that, in these economies with poor institutional quality of collateral and bankruptcy laws, aggressive collateralization makes the risk-taking behavior of borrowers suboptimally more costly. This discourages entrepreneurship and thus impedes the growth potential among young firms with a potentially high impact on job creation in the economy.Second chapter stresses the "disconnection" channel on the performance of firms when stringent collateral environment impedes the access of firms to financial system. Studying the 6 economies in MENA we observe region is characterized by an unusually highshare of firms that do not need external finance. These firms are less likely to view access to finance as a major concern, are less likely to have purchased fixed assets, andare less likely to plan further expansion. These findings also hold after accounting fora standard set of firm characteristics. In the third chapter, I move to a sample of OECD countries. A growing body of literature emphasizes the role of trade with emerging economies, especially with China, in job destruction in the manufacturing sectors andin the deindustrialization process currently seen in advanced economies. However, to quantify the relevance of exposure to imports from emerging markets, the trade channel needs to be disentangled from the traditional productivity channel. Developing asimple model of structural change in an open economy, I derive empirical implicationsto analyze for a sample of OECD countries. The model illustrates when productivity growth of domestic manufacturing is faster than that of services but slower than that of foreign manufacturing, the share of manufacturing in advanced economies may fall,both in terms of value added and of employment. I call this phenomenon "twin deindustrialization".My empirical results indicate significant and quantitatively relevant effects of trade on structural change in advanced economies. Furthermore, while many studies investigate the accelerating volume of imports from China post 2000 to explain the pattern of deindustrialization in advance economies, I stress that the shift in the composition of Chinese exports towards the ICT sectors and the changing nature of technological progress occurring in emerging economies are important considerations in understanding the pattern of deindustrialization in the post 2000 period.

A presente pesquisa aborda uma investigação interdisciplinar (Educação e Computação) sobre estudos que estabeleceram como foco a influência da afetividade na educação e sobre como reconhecer o desânimo do aluno em interação em um ambiente virtual de ensino e aprendizagem (AVEA) utilizando mineração de dados educacionais (MDE). A afetividade pode influenciar na aprendizagem do aluno, principalmente com relação aos aspectos negativos, frustrações, sensações de solidão, desânimo, fazendo com que o aluno possa, inclusive, desistir de um curso, tornando-se uma problemática no ensino. Identificar esses aspectos em cursos à distância torna-se desafiador para o professor devido à distância temporal e assincronicidade desse meio. Nos cursos à distância, essa possibilidade pode ser permitida através das análises dos dados das interações do aluno no ambiente, porém, o volume de dados existentes torna-se muito grande para ser analisado pelo professor, fazendo com que seja mais difícil realizar essa identificação. Na busca por identificar o estado de ânimo desanimado, esta tese apresenta um Modelo de Predição do Desânimo baseado em comportamento observável e autorrelato armazenados em AVEA, utilizando regras de associação. Para desenvolver o Modelo de Predição do aluno, as variáveis comportamentais indicadoras do desânimo foram evidenciadas na pesquisa, bem como a utilização dos fundamentos e instrumento de Scherer para identificação dos estados afetivos, mais precisamente do estado de ânimo desanimado, que duram por longos períodos, possibilitando sua identificação após determinados fatos terem ocorrido no processo de aprendizagem, o que possibilitou ter uma metodologia de acompanhamento do aluno. As regras de associação foram descobertas devido ao potencial da MDE, que, além de propiciar a inferência e predição, pode ser usada para fornecer apoio tanto ao professor, no processo de ensino e acompanhamento do aluno, quanto ao aluno, no processo de aprendizagem. Nesse contexto, a pesquisa é aplicada ao processo de ensino e aprendizagem utilizando como procedimento técnico experimentos para coleta de dados. Foram feitos experimentos com aplicação de técnicas computacionais para apoio à inferência e geração do modelo de predição. Em cada experimento onde se aplicou a MDE, as melhores regras foram escolhidas com base nas medidas de interesse e presença do estado de ânimo desanimado. A partir dessas melhores regras, uma validação foi realizada em um novo experimento propondo o Modelo de Predição do aluno desanimado em interação no AVEA Moodle. Além de apresentar o Modelo de Predição do Aluno Desanimado, este modelo foi implementado e integrado como ferramenta computacional à plataforma Moodle. A pesquisa justifica-se na medida em que apresenta inovação tecnológica para investigar a influência da afetividade na aprendizagem dentro do contexto da Educação a Distância (EAD) e aplica técnicas computacionais desenvolvendo um Modelo de Predição do Aluno Desanimado, que fornece para o professor uma visão geral do modelo e melhor acompanhamento de seus alunos, através de dashboard, contribuindo na sua prática docente. Logo, a tese apresenta como destaque inovador um produto de pesquisa com utilidade na prática docente no ensino superior, principalmente em cursos EAD, para o reconhecimento de aspectos relacionados à afetividade no contexto educacional. Através da ferramenta computacional, um melhor acompanhamento de alunos desanimados em interação em AVEA pode ser feito pelo professor, permitindo a este fomentar uma metodologia de acompanhamento desses alunos, a fim de minimizar futuras evasões, bem como desistências em cursos e disciplinas, beneficiando a comunidade acadêmica. / This research addresses an interdisciplinary research (Education and Computer) on studies that established focus on the influence of affectivity in education and how to recognize the dismay of student interaction in a virtual teaching and learning environment (VTLE) using educational data mining (EDM). Affection can influence student learning, particularly with respect to the negative, frustration, feelings of loneliness, discouragement, causing the student can even give up a course, becoming a problematic teaching. Identify these aspects in distance courses becomes challenging for the teacher due to the temporal distance and asynchronicity that medium. In distance learning courses, this possibility may be permitted by the data analysis of student interactions in the environment, however, the amount of data becomes too large to be analyzed by the teacher, making it more difficult to carry out such identification. In seeking to identify the state of despondent mood, this thesis presents a prediction model of the observable behavior-based Discouragement and self-report stored in VTLE using association rules. To develop the prediction model student, the indicator behavioral variables of discouragement were evident in the research, and the use of the grounds and Scherer tool to identify the affective states, specifically the state of despondent mood that last for long periods, enabling identification after certain events have occurred in the learning process, making it possible to have a follow-up methodology of the student. Association rules were discovered due to the potential of the EAW, which, besides providing the inference and prediction, can be used to provide support to both the teacher in the teaching and monitoring of the student as the student in the learning process. In this context, the research is applied to the teaching and learning process using as a technical procedure experiments to collect data. experiments were made with application of computational techniques to support the inference and generation of the prediction model. In each experiment where we applied the MED, the best rules were chosen based on measures of interest and presence in the state of despondent mood. From these best rules, a validation was performed on a new experiment proposing the Prediction Model discouraged student interaction in VTLE Moodle. In addition to presenting the Prediction Model of Student Discouraged, this model was implemented and integrated as a computational tool to the Moodle platform. The research is justified in that it presents technological innovation to investigate the influence of affect on learning within the education context Distance Learning and applies computational techniques developing a prediction model Discouraged Student, which provides for the teacher a view general model and better monitoring of their students through dashboard, contributing to their teaching practice. Therefore, the thesis shows how innovative highlight a research product to use in teaching practice in higher education, especially in distance education courses, for the recognition of aspects related to affectivity in the educational context. Through computational tool for better monitoring of disheartened students interacting in VTLE it can be done by the teacher, allowing him to promote a follow-up methodology of these students in order to minimize future evasions and dropouts courses and disciplines, benefiting the community academic. / Esta investigación se ocupa de una investigación interdisciplinaria (Educación e Informática) en los que se estableció el enfoque sobre la influencia de la afectividad en la educación y cómo reconocer la consternación de la interacción del estudiante en un entorno virtual de enseñanza aprendizaje (AVEA) utilizando la minería de datos educativa (MDE). El afecto puede influir en el aprendizaje del estudiante, en particular con respecto a la negativa, frustración, sentimientos de soledad, desánimo, haciendo que el estudiante puede incluso renunciar a un curso, convirtiéndose en una enseñanza problemática. Identificar estos aspectos en los cursos a distancia se convierte en un reto para el maestro debido a la distancia temporal y asincronía ese medio. En los cursos de enseñanza a distancia, esta posibilidad puede ser permitido por el análisis de los datos de las interacciones de los estudiantes en el ambiente, sin embargo, la cantidad de datos es demasiado grande para ser analizados por el profesor, lo que hace más difícil llevar a cabo dicha identificación. Al tratar de identificar el estado de ánimo deprimido, esta tesis presenta un modelo de predicción del desaliento observables basada en el comportamiento y auto-informe almacenado en AVEA las reglas de asociación. Para desarrollar el estudiante modelo de predicción, las variables de comportamiento del indicador de desaliento eran evidentes en la investigación, y el uso de los terrenos y Scherer herramienta para identificar los estados afectivos, específicamente el estado de ánimo deprimido que duran por largos períodos de tiempo, que permite la identificación después de ciertos acontecimientos se han producido en el proceso de aprendizaje, por lo que es posible tener una metodología de seguimiento del estudiante. Reglas de asociación fueron descubiertos debido al potencial de la orden de detención europea, que, además de proporcionar la inferencia y la predicción, se puede utilizar para proporcionar apoyo tanto a la maestra en la enseñanza y el seguimiento del alumno como estudiante en el proceso de aprendizaje. En este contexto, la investigación se aplica al proceso de enseñanza y aprendizaje mediante experimentos como un procedimiento técnico para recopilar datos. experimentos se hicieron con la aplicación de técnicas computacionales para apoyar la inferencia y la generación del modelo de predicción. En cada experimento en el que se aplicó el MDE, las mejores reglas fueron elegidos en base a medidas de interés y presencia en el estado de ánimo deprimido. A partir de estas mejores reglas, una validación se realizó en un nuevo experimento que propone la interacción de los estudiantes desalentado modelo de predicción de AVEA Moodle. Además de presentar el Modelo de Predicción del Estudiante Desalentado, este modelo fue implementado e integrado como una herramienta computacional para la plataforma Moodle. La investigación se justifica porque presenta la innovación tecnológica para investigar la influencia del efecto sobre el aprendizaje en el contexto de la educación a distancia (EAD) y aplica técnicas computacionales en desarrollo un modelo de predicción de Estudiantes Desalentado, que prevé el profesor una vista modelo general y un mejor seguimiento de sus estudiantes a través de tablero de instrumentos, contribuyendo a su práctica docente. Por lo tanto, la tesis muestra cómo destacado innovador de un producto de investigación a utilizar en la práctica docente en la enseñanza superior, sobre todo en los cursos de educación a distancia, para el reconocimiento de los aspectos relacionados con la afectividad en el contexto educativo. A través de la herramienta computacional para un mejor seguimiento de los estudiantes desanimados que interactúan en AVEA se puede hacer por el profesor, lo que le permite promover una metodología de seguimiento de estos estudiantes con el fin de reducir al mínimo las evasivas y abandonos futuros cursos y disciplinas, en beneficio de la comunidad académica.

A presente pesquisa aborda uma investigação interdisciplinar (Educação e Computação) sobre estudos que estabeleceram como foco a influência da afetividade na educação e sobre como reconhecer o desânimo do aluno em interação em um ambiente virtual de ensino e aprendizagem (AVEA) utilizando mineração de dados educacionais (MDE). A afetividade pode influenciar na aprendizagem do aluno, principalmente com relação aos aspectos negativos, frustrações, sensações de solidão, desânimo, fazendo com que o aluno possa, inclusive, desistir de um curso, tornando-se uma problemática no ensino. Identificar esses aspectos em cursos à distância torna-se desafiador para o professor devido à distância temporal e assincronicidade desse meio. Nos cursos à distância, essa possibilidade pode ser permitida através das análises dos dados das interações do aluno no ambiente, porém, o volume de dados existentes torna-se muito grande para ser analisado pelo professor, fazendo com que seja mais difícil realizar essa identificação. Na busca por identificar o estado de ânimo desanimado, esta tese apresenta um Modelo de Predição do Desânimo baseado em comportamento observável e autorrelato armazenados em AVEA, utilizando regras de associação. Para desenvolver o Modelo de Predição do aluno, as variáveis comportamentais indicadoras do desânimo foram evidenciadas na pesquisa, bem como a utilização dos fundamentos e instrumento de Scherer para identificação dos estados afetivos, mais precisamente do estado de ânimo desanimado, que duram por longos períodos, possibilitando sua identificação após determinados fatos terem ocorrido no processo de aprendizagem, o que possibilitou ter uma metodologia de acompanhamento do aluno. As regras de associação foram descobertas devido ao potencial da MDE, que, além de propiciar a inferência e predição, pode ser usada para fornecer apoio tanto ao professor, no processo de ensino e acompanhamento do aluno, quanto ao aluno, no processo de aprendizagem. Nesse contexto, a pesquisa é aplicada ao processo de ensino e aprendizagem utilizando como procedimento técnico experimentos para coleta de dados. Foram feitos experimentos com aplicação de técnicas computacionais para apoio à inferência e geração do modelo de predição. Em cada experimento onde se aplicou a MDE, as melhores regras foram escolhidas com base nas medidas de interesse e presença do estado de ânimo desanimado. A partir dessas melhores regras, uma validação foi realizada em um novo experimento propondo o Modelo de Predição do aluno desanimado em interação no AVEA Moodle. Além de apresentar o Modelo de Predição do Aluno Desanimado, este modelo foi implementado e integrado como ferramenta computacional à plataforma Moodle. A pesquisa justifica-se na medida em que apresenta inovação tecnológica para investigar a influência da afetividade na aprendizagem dentro do contexto da Educação a Distância (EAD) e aplica técnicas computacionais desenvolvendo um Modelo de Predição do Aluno Desanimado, que fornece para o professor uma visão geral do modelo e melhor acompanhamento de seus alunos, através de dashboard, contribuindo na sua prática docente. Logo, a tese apresenta como destaque inovador um produto de pesquisa com utilidade na prática docente no ensino superior, principalmente em cursos EAD, para o reconhecimento de aspectos relacionados à afetividade no contexto educacional. Através da ferramenta computacional, um melhor acompanhamento de alunos desanimados em interação em AVEA pode ser feito pelo professor, permitindo a este fomentar uma metodologia de acompanhamento desses alunos, a fim de minimizar futuras evasões, bem como desistências em cursos e disciplinas, beneficiando a comunidade acadêmica. / This research addresses an interdisciplinary research (Education and Computer) on studies that established focus on the influence of affectivity in education and how to recognize the dismay of student interaction in a virtual teaching and learning environment (VTLE) using educational data mining (EDM). Affection can influence student learning, particularly with respect to the negative, frustration, feelings of loneliness, discouragement, causing the student can even give up a course, becoming a problematic teaching. Identify these aspects in distance courses becomes challenging for the teacher due to the temporal distance and asynchronicity that medium. In distance learning courses, this possibility may be permitted by the data analysis of student interactions in the environment, however, the amount of data becomes too large to be analyzed by the teacher, making it more difficult to carry out such identification. In seeking to identify the state of despondent mood, this thesis presents a prediction model of the observable behavior-based Discouragement and self-report stored in VTLE using association rules. To develop the prediction model student, the indicator behavioral variables of discouragement were evident in the research, and the use of the grounds and Scherer tool to identify the affective states, specifically the state of despondent mood that last for long periods, enabling identification after certain events have occurred in the learning process, making it possible to have a follow-up methodology of the student. Association rules were discovered due to the potential of the EAW, which, besides providing the inference and prediction, can be used to provide support to both the teacher in the teaching and monitoring of the student as the student in the learning process. In this context, the research is applied to the teaching and learning process using as a technical procedure experiments to collect data. experiments were made with application of computational techniques to support the inference and generation of the prediction model. In each experiment where we applied the MED, the best rules were chosen based on measures of interest and presence in the state of despondent mood. From these best rules, a validation was performed on a new experiment proposing the Prediction Model discouraged student interaction in VTLE Moodle. In addition to presenting the Prediction Model of Student Discouraged, this model was implemented and integrated as a computational tool to the Moodle platform. The research is justified in that it presents technological innovation to investigate the influence of affect on learning within the education context Distance Learning and applies computational techniques developing a prediction model Discouraged Student, which provides for the teacher a view general model and better monitoring of their students through dashboard, contributing to their teaching practice. Therefore, the thesis shows how innovative highlight a research product to use in teaching practice in higher education, especially in distance education courses, for the recognition of aspects related to affectivity in the educational context. Through computational tool for better monitoring of disheartened students interacting in VTLE it can be done by the teacher, allowing him to promote a follow-up methodology of these students in order to minimize future evasions and dropouts courses and disciplines, benefiting the community academic. / Esta investigación se ocupa de una investigación interdisciplinaria (Educación e Informática) en los que se estableció el enfoque sobre la influencia de la afectividad en la educación y cómo reconocer la consternación de la interacción del estudiante en un entorno virtual de enseñanza aprendizaje (AVEA) utilizando la minería de datos educativa (MDE). El afecto puede influir en el aprendizaje del estudiante, en particular con respecto a la negativa, frustración, sentimientos de soledad, desánimo, haciendo que el estudiante puede incluso renunciar a un curso, convirtiéndose en una enseñanza problemática. Identificar estos aspectos en los cursos a distancia se convierte en un reto para el maestro debido a la distancia temporal y asincronía ese medio. En los cursos de enseñanza a distancia, esta posibilidad puede ser permitido por el análisis de los datos de las interacciones de los estudiantes en el ambiente, sin embargo, la cantidad de datos es demasiado grande para ser analizados por el profesor, lo que hace más difícil llevar a cabo dicha identificación. Al tratar de identificar el estado de ánimo deprimido, esta tesis presenta un modelo de predicción del desaliento observables basada en el comportamiento y auto-informe almacenado en AVEA las reglas de asociación. Para desarrollar el estudiante modelo de predicción, las variables de comportamiento del indicador de desaliento eran evidentes en la investigación, y el uso de los terrenos y Scherer herramienta para identificar los estados afectivos, específicamente el estado de ánimo deprimido que duran por largos períodos de tiempo, que permite la identificación después de ciertos acontecimientos se han producido en el proceso de aprendizaje, por lo que es posible tener una metodología de seguimiento del estudiante. Reglas de asociación fueron descubiertos debido al potencial de la orden de detención europea, que, además de proporcionar la inferencia y la predicción, se puede utilizar para proporcionar apoyo tanto a la maestra en la enseñanza y el seguimiento del alumno como estudiante en el proceso de aprendizaje. En este contexto, la investigación se aplica al proceso de enseñanza y aprendizaje mediante experimentos como un procedimiento técnico para recopilar datos. experimentos se hicieron con la aplicación de técnicas computacionales para apoyar la inferencia y la generación del modelo de predicción. En cada experimento en el que se aplicó el MDE, las mejores reglas fueron elegidos en base a medidas de interés y presencia en el estado de ánimo deprimido. A partir de estas mejores reglas, una validación se realizó en un nuevo experimento que propone la interacción de los estudiantes desalentado modelo de predicción de AVEA Moodle. Además de presentar el Modelo de Predicción del Estudiante Desalentado, este modelo fue implementado e integrado como una herramienta computacional para la plataforma Moodle. La investigación se justifica porque presenta la innovación tecnológica para investigar la influencia del efecto sobre el aprendizaje en el contexto de la educación a distancia (EAD) y aplica técnicas computacionales en desarrollo un modelo de predicción de Estudiantes Desalentado, que prevé el profesor una vista modelo general y un mejor seguimiento de sus estudiantes a través de tablero de instrumentos, contribuyendo a su práctica docente. Por lo tanto, la tesis muestra cómo destacado innovador de un producto de investigación a utilizar en la práctica docente en la enseñanza superior, sobre todo en los cursos de educación a distancia, para el reconocimiento de los aspectos relacionados con la afectividad en el contexto educativo. A través de la herramienta computacional para un mejor seguimiento de los estudiantes desanimados que interactúan en AVEA se puede hacer por el profesor, lo que le permite promover una metodología de seguimiento de estos estudiantes con el fin de reducir al mínimo las evasivas y abandonos futuros cursos y disciplinas, en beneficio de la comunidad académica.