Studiens syfte är att få ta del av pedagogernas syn på hur de ser på sin förmåga att identifiera särbegåvade elever och matematiskt särbegåvade elever. Om de tycker att de har goda förutsättningar för att kunna identifiera dessa elever eller om de upplever något hinder i sin förmåga att identifiera dem. Jag har valt att använda mig utav en enkätstudie för att få svar på mina frågor. Webbenkäten är skickad till 3 små kommuner och jag valde enkäter istället för intervjuer för att jag ville få en större spridning och fler olika sorters pedagoger som svarade. Studien visar att många av pedagogerna vet vad begreppet särbegåvad innebär men att de själva känner att de har för lite kunskap inom ämnet. / The purpose of the study is to get the educators view on how they look upon their ability of identifying gifted pupils. If they feel that they have potential to be able to identify these pupils, or if they experience any hinders in their ability to identify them. I have chosen to use a survey to be able to get answers to my questions. The survey is sent to three small municipalities and I chose surveys instead of interviews because I wanted to have a wider distribution and several different kinds of educators answering. The study shows that many of the educators know the meaning of the concept of giftedness, but that they feel that they have lack knowledge on the subject.

The main objective of this research was to establish a model for emotional intelligence as a determinant of organisational climate. This model should help companies and organisational psychologists to better understand the interrelatedness of the two constructs in order to optimally enhance organisational performance. This research was conducted in a large organisation, utilising a large sample (n = 1 612) of employees in the financial services industry. During the first phase of this research, emotional intelligence was conceptualised from literature research within the trait paradigm and organisational climate as a molar construct. A theoretical model of emotional intelligence as a determinant of organisational climate was developed and suggested a link to organisational output. During the second phase of this research (empirical research), assessment instruments for emotional intelligence (the Gerber Emotional Intelligence Scale) and organisational climate (the High Performance Climate Questionnaire) were developed and validated. Thereafter an assessment instrument for work output was designed to test the link with performance. The structural equation model (SEM) produced a new best-fitting model of emotional intelligence, organisational climate and work output. The model indicates that emotional intelligence does not correlate with work output as expected, but organisational climate does correlates moderately with work output and explains almost 40% of the variance in work output. The strongest influence seems to flow from teamwork and management. The regression weights between emotional intelligence and organisational climate were trivial, although the model fit indices were all within an acceptable range. The researcher attributed the lack of support for the model to the characteristics of the employees of this type of organisation and concluded that emotional intelligence should not be seen as a determinant of organisational climate in this specific financial services sector. The results further indicate that significant differences exist between the organisational climate experiences of four biographical categories (race, position level, age and geographical region) and also for the categories of position level and age for work output. These differences need to be considered when developing future interventions. This research contributes towards a comprehensive understanding of the relationship between emotional intelligence, organisational climate and work output. The three newly developed questionnaires and the SEM could help researchers and practitioners to apply the research model in other industries and subsequently improve organisational outputs. / Industrial and Organisational Psychology / D. Comm. (Industrial and Organisational Psychology)

The main objective of this research was to establish a model for emotional intelligence as a determinant of organisational climate. This model should help companies and organisational psychologists to better understand the interrelatedness of the two constructs in order to optimally enhance organisational performance. This research was conducted in a large organisation, utilising a large sample (n = 1 612) of employees in the financial services industry. During the first phase of this research, emotional intelligence was conceptualised from literature research within the trait paradigm and organisational climate as a molar construct. A theoretical model of emotional intelligence as a determinant of organisational climate was developed and suggested a link to organisational output. During the second phase of this research (empirical research), assessment instruments for emotional intelligence (the Gerber Emotional Intelligence Scale) and organisational climate (the High Performance Climate Questionnaire) were developed and validated. Thereafter an assessment instrument for work output was designed to test the link with performance. The structural equation model (SEM) produced a new best-fitting model of emotional intelligence, organisational climate and work output. The model indicates that emotional intelligence does not correlate with work output as expected, but organisational climate does correlates moderately with work output and explains almost 40% of the variance in work output. The strongest influence seems to flow from teamwork and management. The regression weights between emotional intelligence and organisational climate were trivial, although the model fit indices were all within an acceptable range. The researcher attributed the lack of support for the model to the characteristics of the employees of this type of organisation and concluded that emotional intelligence should not be seen as a determinant of organisational climate in this specific financial services sector. The results further indicate that significant differences exist between the organisational climate experiences of four biographical categories (race, position level, age and geographical region) and also for the categories of position level and age for work output. These differences need to be considered when developing future interventions. This research contributes towards a comprehensive understanding of the relationship between emotional intelligence, organisational climate and work output. The three newly developed questionnaires and the SEM could help researchers and practitioners to apply the research model in other industries and subsequently improve organisational outputs. / Industrial and Organisational Psychology / D. Comm. (Industrial and Organisational Psychology)

<p>Drug discovery and development has experienced a tremendous growth in the recent</p> <p>years, and methods to accelerate the process are necessary as the demand for effective drugs</p> <p>to treat a wide range of diseases continue to increase. Nevertheless, the majority of conventional</p> <p>techniques are labor-intensive or have relatively low yields. As a result, academia</p> <p>and the pharmaceutical industry are continuously seeking for rapid and efficient methods to</p> <p>accelerate the drug discovery pipeline. Therefore, in order to expedite the drug discovery</p> <p>process, recent developments in physical and artificial intelligence models have been utilized</p> <p>extensively. However, the overarching problem is how to use these cutting-edge advancements</p> <p>in artificial intelligence to enhance drug discovery? Therefore, this dissertation work</p> <p>focused on developing and applying artificial intelligence and physical models to accelerate</p> <p>the drug discovery pipeline at different stages. As the first study reported in the dissertation,</p> <p>the potential to apply graph neural network-based machine learning architectures</p> <p>with the assistance of molecular modeling features to identify plausible drug leads out of</p> <p>structurally similar chemical databases is assessed. Then, the capability of applying molecular</p> <p>modeling methods including molecular docking and molecular dynamics simulations to</p> <p>identify prospective targets and biological pathways for small molecular drugs is discussed</p> <p>and evaluated in the following chapter. Further, the capability of applying state-of-the-art</p> <p>deep learning architectures such as multi-layer perceptron and recurrent neural networks</p> <p>to optimize the formulation development stage has been assessed. Moreover, this dissertation</p> <p>has contributed to assist functionality identification of unknown compounds using</p> <p>simple machine learning based computational frameworks. The developed omics data analysis</p> <p>pipeline is then discussed in order to comprehend the effects of a particular treatment</p> <p>on the proteome and lipidome levels of cells. In conclusion, the potential for developing and</p> <p>utilizing various artificial intelligence-based approaches to accelerate the drug discovery and</p> <p>development process is explored in this research. Thus, these collaborative studies intend</p> <p>to contribute to ongoing acceleration efforts and advancements in the drug discovery and</p> <p>development field.</p>