Significant changes have taken place in higher education over dte past ten years. Learners are more liberated and want to be acknowledged as individuals with differences, and not expected to adapt their individual characteristics to fit in with the specific environment of the learning situation. A new emphasis is placed upon creating and sustaining learning environments that accommodate Ieamer needs and dte process of effective learning. Learners' individual needs include their need to learn how to learn and an acceptance of their individual differences as expressed in learning styles. Active Ieamer participation in dte learning process is necessary for effective learning to take place. Only dten can the desired outcome be reached. For a Ieamer to actively participate in the learning process, the Ieamer must know how to learn, and how to function as an independent Ieamer. To reach these goals, sound knowledge of individual differences in learning st;ytes is necessary. The impact of individual differences on education and the way they affect educational practice, future learning and academic achievement places the emphasis even more strongly on constant awareness, updatlng or change, improvement and development of the educational environment. The educator, as one of the role players in the educational environment, is the facilitator of learning, and should be empowered with a strong knowledge base regarding individual differences among both learners and educators, thus becoming more innovative and creative. Qualitative non-empirical research was undertaken. The aim of this research was to analyse and explore the concept learning style as well as to promote learning style awareness through assessment of learning st;ytes, and to provide an organised frame of reference to guide the learning process and provide for systematic education. Based on insight and knowledge gained through Inductive and deductive reasoning, The Learning Style Assessment Tool and a model for learning style promotion in higher education were constructed. The instrument enables learners and educators to assess their own learning st;ytes and identify their learning characteristics and preferences. The model can serve as a basis for acknowledging and accommodating learning styles in higher education. The desired outcome of this research is effective learning and quality education. / Health Studes / D. Litt. et Phil. (Advanced Nursing Sciences)

In this thesis, we have studied the problem of detecting automated Twitter accounts related to the Ukraine conflict using supervised learning. A striking problem with the collected data set is that it was initially lacking a ground truth. Traditionally, supervised learning approaches rely on manual annotation of training sets, but it incurs tedious work and becomes expensive for large and constantly changing collections. We present a novel approach to synthetically generate large amounts of labeled Twitter accounts for detection of automation using a rule-based classifier. It significantly reduces the effort and resources needed and speeds up the process of adapting classifiers to changes in the Twitter-domain. The classifiers were evaluated on a manually annotated test set of 1,000 Twitter accounts. The results show that rule-based classifier by itself achieves a precision of 94.6% and a recall of 52.9%. Furthermore, the results showed that classifiers based on supervised learning could learn from the synthetically generated labels. At best, the these machine learning based classifiers achieved a slightly lower precision of 94.1% compared to the rule-based classifier, but at a significantly better recall of 93.9% / Detta exjobb har undersökt problemet att detektera automatiserade Twitter-konton relaterade till Ukraina-konflikten genom att använda övervakade maskininlärningsmetoder. Ett slående problem med den insamlade datamängden var avsaknaden av träningsexempel. I övervakad maskininlärning brukar man traditionellt manuellt märka upp en träningsmängd. Detta medför dock långtråkigt arbete samt att det blir dyrt förstora och ständigt föränderliga datamängder. Vi presenterar en ny metod för att syntetiskt generera uppmärkt Twitter-data (klassifieringsetiketter) för detektering av automatiserade konton med en regel-baseradeklassificerare. Metoden medför en signifikant minskning av resurser och anstränging samt snabbar upp processen att anpassa klassificerare till förändringar i Twitter-domänen. En utvärdering av klassificerare utfördes på en manuellt uppmärkt testmängd bestående av 1,000 Twitter-konton. Resultaten visar att den regelbaserade klassificeraren på egen hand uppnår en precision på 94.6% och en recall på 52.9%. Vidare påvisar resultaten att klassificerare baserat på övervakad maskininlärning kunde lära sig från syntetiskt uppmärkt data. I bästa fall uppnår dessa maskininlärningsbaserade klassificerare en något lägre precision på 94.1%, jämfört med den regelbaserade klassificeraren, men med en betydligt bättre recall på 93.9%.

Text in English / The purpose of this study, was to identify and describe factors, which facilitate or impede learning in clinical learning settings. The study adopted an exploratory descriptive approach, incorporating both quantitative and qualitative designs. Data collection tool, comprised of two sections: Section 1 focused on demographic characteristics. While section 2 addressed study variables of clinical setting, staffing, patient care/ practice standards, nurse manager's commitment and interpersonal relationships. The last section had two parts; part 1 being close ended Likert type scale ranging from strongly agree to strongly disagree. Part 2, was open ended, and solicited respondents' feelings opinions and experiences on factors they perceived to facilitate or impede clinical learning. The findings indicate that the majority of settings studied did not provide adequate factors to facilitate clinical learning. Factors such as availability of learning experiences, acceptable unit organization, space and resource availability, and accessibility to students, adequate staffing with qualified staff who actively participate in teaching, appropriate and quality patient care role modelled, lecturer availability and involvement in clinical teaching, team building and inclusion of students in the team, committed nurse managers involved in students' learning, conducive relationships among staff, students and patients, comfort relationships, advocacy and creating conducive relationship by the nurse manager, were identified as necessary for learning. These factors however, were found to be either lacking, inadequate or inaccessible to students. Findings were based on data from a quota sample of 202 participants proportionately drawn from students, nurse managers and nurse lecturers. The study made recommendations to improve and enhance the conduciveness of clinical practice settings used for learning in Botswana. / Health Studies / D.Litt. et Phil. (Advanced Nursing Science)

Text in English / The purpose of this study, was to identify and describe factors, which facilitate or impede learning in clinical learning settings. The study adopted an exploratory descriptive approach, incorporating both quantitative and qualitative designs. Data collection tool, comprised of two sections: Section 1 focused on demographic characteristics. While section 2 addressed study variables of clinical setting, staffing, patient care/ practice standards, nurse manager's commitment and interpersonal relationships. The last section had two parts; part 1 being close ended Likert type scale ranging from strongly agree to strongly disagree. Part 2, was open ended, and solicited respondents' feelings opinions and experiences on factors they perceived to facilitate or impede clinical learning. The findings indicate that the majority of settings studied did not provide adequate factors to facilitate clinical learning. Factors such as availability of learning experiences, acceptable unit organization, space and resource availability, and accessibility to students, adequate staffing with qualified staff who actively participate in teaching, appropriate and quality patient care role modelled, lecturer availability and involvement in clinical teaching, team building and inclusion of students in the team, committed nurse managers involved in students' learning, conducive relationships among staff, students and patients, comfort relationships, advocacy and creating conducive relationship by the nurse manager, were identified as necessary for learning. These factors however, were found to be either lacking, inadequate or inaccessible to students. Findings were based on data from a quota sample of 202 participants proportionately drawn from students, nurse managers and nurse lecturers. The study made recommendations to improve and enhance the conduciveness of clinical practice settings used for learning in Botswana. / Health Studies / D.Litt. et Phil. (Advanced Nursing Science)