<p>Språket är en viktig del i matematikundervisningen. Forskning visar att språket är betydelsefullt för utvecklingen av ny kunskap och man har också kunnat se ett samband mellan språklig och matematisk förmåga. Undersökningar har dock visat att det ökade fokus på kommunikation och samspel inom matematikundervisningen som aktuell läroplan och kursplan förordar inte helt har slagit igenom inom skolan. För att ta reda på lärares syn på språkets betydelse i matematikundervisningen och även få en aktuell bild av undervisningssituationen ur ett språkligt perspektiv har en kvalitativ intervjuundersökning genomförts bland sex mellanstadielärare i en svensk kommun.</p><p>Undersökningen visar att samtliga intervjuade lärare anser att språket är viktigt i matematikundervisningen. Däremot skiljer det sig åt när det gäller vilken betydelse de anser att det har. Enskilt arbete utgör här, liksom i tidigare undersökningar, den största delen av undervisningen, även om hälften av lärarna aktivt arbetar med matematiska samtal eleverna emellan. En av de slutsatser som dras av undersökningen är att om kursplanens mål gällande en kommunikativ förmåga ska kunna uppnås, måste eleverna regelbundet få skriva, samtala och diskutera kring matematiska frågor.</p> / <p>Language is an important part of mathematics education. Research shows that language is significant for knowledge development and that there is a connection between linguistic and mathematical ability. Investigations have shown, though, that the increased focus on communication and pupil interaction within the mathematics education, recommended in the curriculum and syllabus, have not yet reached the desired effect. In order to find out about teachers’ views on the significance of language in mathematics education, and also to get an update of the current educational situation from a linguistic perspective, a qualitative investigation has been made among six primary-school teachers.</p><p>The investigation shows that all teachers interviewed believe language to be important in mathematics education. They do, however, differ in their opinions of where the significance lies. The main part of mathematics lessons is, as noted in previous investigations, used for individual schoolwork, even though half the group of teachers actively practise mathematical communication amongst the pupils. One of the conclusions that can be drawn from this investigation is that if the syllabus’ objective about communicative ability is to be achieved, the pupils must be allowed to write and discuss mathematical issues on a regular basis.</p>

Thesis (Ph.D. (English))--North-West University, Potchefstroom Campus, 2007.

Complex networks have been successfully employed to represent different levels of biological systems, ranging from gene regulation to protein-protein interactions and metabolism. Network-based research has mainly focused on identifying unifying structural properties, including small average path length, large clustering coefficient, heavy-tail degree distribution, and hierarchical organization, viewed as requirements for efficient and robust system architectures. Existing studies estimate the significance of network properties using a generic randomization scheme - a Markov-chain switching algorithm - which generates unrealistic reactions in metabolic networks, as it does not account for the physical principles underlying metabolism. Therefore, it is unclear whether the properties identified with this generic approach are related to the functions of metabolic networks. Within this doctoral thesis, I have developed an algorithm for mass-balanced randomization of metabolic networks, which runs in polynomial time and samples networks almost uniformly at random. The properties of biological systems result from two fundamental origins: ubiquitous physical principles and a complex history of evolutionary pressure. The latter determines the cellular functions and abilities required for an organism’s survival. Consequently, the functionally important properties of biological systems result from evolutionary pressure. By employing randomization under physical constraints, the salient structural properties, i.e., the smallworld property, degree distributions, and biosynthetic capabilities of six metabolic networks from all kingdoms of life are shown to be independent of physical constraints, and thus likely to be related to evolution and functional organization of metabolism. This stands in stark contrast to the results obtained from the commonly applied switching algorithm. In addition, a novel network property is devised to quantify the importance of reactions by simulating the impact of their knockout. The relevance of the identified reactions is verified by the findings of existing experimental studies demonstrating the severity of the respective knockouts. The results suggest that the novel property may be used to determine the reactions important for viability of organisms. Next, the algorithm is employed to analyze the dependence between mass balance and thermodynamic properties of Escherichia coli metabolism. The thermodynamic landscape in the vicinity of the metabolic network reveals two regimes of randomized networks: those with thermodynamically favorable reactions, similar to the original network, and those with less favorable reactions. The results suggest that there is an intrinsic dependency between thermodynamic favorability and evolutionary optimization. The method is further extended to optimizing metabolic pathways by introducing novel chemically feasibly reactions. The results suggest that, in three organisms of biotechnological importance, introduction of the identified reactions may allow for optimizing their growth. The approach is general and allows identifying chemical reactions which modulate the performance with respect to any given objective function, such as the production of valuable compounds or the targeted suppression of pathway activity. These theoretical developments can find applications in metabolic engineering or disease treatment. The developed randomization method proposes a novel approach to measuring the significance of biological network properties, and establishes a connection between large-scale approaches and biological function. The results may provide important insights into the functional principles of metabolic networks, and open up new possibilities for their engineering. / In der Systembiologie und Bioinformatik wurden in den letzten Jahren immer komplexere Netzwerke zur Beschreibung verschiedener biologischer Prozesse, wie Genregulation, Protein-Interaktionen und Stoffwechsel (Metabolismus) rekonstruiert. Ein Hauptziel der Forschung besteht darin, die strukturellen Eigenschaften von Netzwerken für Vorhersagen über deren Funktion nutzbar zu machen, also eine Verbindung zwischen Netzwerkeigenschaften und Funktion herzustellen. Die netzwerkbasierte Forschung zielte bisher vor allem darauf ab, gemeinsame Eigenschaften von Netzwerken unterschiedlichen Ursprungs zu entdecken. Dazu zählen die durchschnittliche Länge von Verbindungen im Netzwerk, die Häufigkeit redundanter Verbindungen, oder die hierarchische Organisation der Netzwerke, welche als Voraussetzungen für effiziente Kommunikationswege und Robustheit angesehen werden. Dabei muss zunächst bestimmt werden, welche Eigenschaften für die Funktion eines Netzwerks von besonderer Bedeutung (Signifikanz) sind. Die bisherigen Studien verwenden dafür eine Methode zur Erzeugung von Zufallsnetzwerken, welche bei der Anwendung auf Stoffwechselnetzwerke unrealistische chemische Reaktionen erzeugt, da sie physikalische Prinzipien missachtet. Es ist daher fraglich, ob die Eigenschaften von Stoffwechselnetzwerken, welche mit dieser generischen Methode identifiziert werden, von Bedeutung für dessen biologische Funktion sind, und somit für aussagekräftige Vorhersagen in der Biologie verwendet werden können. In meiner Dissertation habe ich eine Methode zur Erzeugung von Zufallsnetzwerken entwickelt, welche physikalische Grundprinzipien berücksichtigt, und somit eine realistische Bewertung der Signifikanz von Netzwerkeigenschaften ermöglicht. Die Ergebnisse zeigen anhand der Stoffwechselnetzwerke von sechs Organismen, dass viele der meistuntersuchten Netzwerkeigenschaften, wie das Kleine-Welt-Phänomen und die Vorhersage der Biosynthese von Stoffwechselprodukten, von herausragender Bedeutung für deren biologische Funktion sind, und somit für Vorhersagen und Modellierung verwendet werden können. Die Methode ermöglicht die Identifikation von chemischen Reaktionen, welche wahrscheinlich von lebenswichtiger Bedeutung für den Organismus sind. Weiterhin erlaubt die Methode die Vorhersage von bisher unbekannten, aber physikalisch möglichen Reaktionen, welche spezifische Zellfunktionen, wie erhöhtes Wachstum in Mikroorganismen, ermöglichen könnten. Die Methode bietet einen neuartigen Ansatz zur Bestimmung der funktional relevanten Eigenschaften biologischer Netzwerke, und eröffnet neue Möglichkeiten für deren Manipulation.

Språket är en viktig del i matematikundervisningen. Forskning visar att språket är betydelsefullt för utvecklingen av ny kunskap och man har också kunnat se ett samband mellan språklig och matematisk förmåga. Undersökningar har dock visat att det ökade fokus på kommunikation och samspel inom matematikundervisningen som aktuell läroplan och kursplan förordar inte helt har slagit igenom inom skolan. För att ta reda på lärares syn på språkets betydelse i matematikundervisningen och även få en aktuell bild av undervisningssituationen ur ett språkligt perspektiv har en kvalitativ intervjuundersökning genomförts bland sex mellanstadielärare i en svensk kommun. Undersökningen visar att samtliga intervjuade lärare anser att språket är viktigt i matematikundervisningen. Däremot skiljer det sig åt när det gäller vilken betydelse de anser att det har. Enskilt arbete utgör här, liksom i tidigare undersökningar, den största delen av undervisningen, även om hälften av lärarna aktivt arbetar med matematiska samtal eleverna emellan. En av de slutsatser som dras av undersökningen är att om kursplanens mål gällande en kommunikativ förmåga ska kunna uppnås, måste eleverna regelbundet få skriva, samtala och diskutera kring matematiska frågor. / Language is an important part of mathematics education. Research shows that language is significant for knowledge development and that there is a connection between linguistic and mathematical ability. Investigations have shown, though, that the increased focus on communication and pupil interaction within the mathematics education, recommended in the curriculum and syllabus, have not yet reached the desired effect. In order to find out about teachers’ views on the significance of language in mathematics education, and also to get an update of the current educational situation from a linguistic perspective, a qualitative investigation has been made among six primary-school teachers. The investigation shows that all teachers interviewed believe language to be important in mathematics education. They do, however, differ in their opinions of where the significance lies. The main part of mathematics lessons is, as noted in previous investigations, used for individual schoolwork, even though half the group of teachers actively practise mathematical communication amongst the pupils. One of the conclusions that can be drawn from this investigation is that if the syllabus’ objective about communicative ability is to be achieved, the pupils must be allowed to write and discuss mathematical issues on a regular basis.

A shuman beings, we are continuously struggling to comprehend the mechanism of dierent natural systems. Many times, we face a complex system where the emergent properties of the system at a global level can not be explained by a simple aggregation of the system's components at the micro-level. To better understand the macroscopic system eects, we try to model microscopic events and their interactions. In order to do so, we rely on specialized tools to connect local mechanisms with global phenomena. One such tool is network theory. Networks provide a powerful way of modeling and analyzing complex systems based on interacting elements. The interaction pattern links the elements of the system together and provides a structure that controls how information permeates throughout the system. For example, the passing of information about job opportunities in a society depends on how social ties are organized. The interaction pattern, therefore, often is essential for reconstructing and understanding the global-scale properties of the system. In this thesis, I describe tools and models of network theory that we use and develop to analyze the organization of social or transportation systems. More specifically, we explore complex networks by asking two general questions: First, which mechanistic theoretical models can better explain network formation or spreading processes on networks? And second, what are the signi cant functional units of real networks? For modeling, for example, we introduce a simple agent-based model that considers interacting agents in dynamic networks that in the quest for information generate groups. With the model, we found that the network and the agents' perception are interchangeable; the global network structure and the local information pathways are so entangled that one can be recovered from the other one. For investigating signi cant functional units of a system, we detect, model, and analyze signi cant communities of the network. Previously introduced methods of significance analysis suer from oversimpli ed sampling schemes. We have remedied their shortcomings by proposing two dierent approaches: rst by introducing link prediction and second by using more data when they are available. With link prediction, we can detect statistically signi cant communities in large sparse networks. We test this method on real networks, the sparse network of the European Court of Justice case law, for example, to detect signi cant and insigni cant areas of law. In the presence of large data, on the other hand, we can investigate how underlying assumptions of each method aect the results of the signi cance analysis. We used this approach to investigate dierent methods for detecting signi cant communities of time-evolving networks. We found that, when we highlight and summarize important structural changes in a network, the methods that maintain more dependencies in signi cance analysis can predict structural changes earlier. In summary, we have tried to model the systems with as simple rules as possible to better understand the global properties of the system. We always found that maintaing information about the network structure is essential for explaining important phenomena on the global scale. We conclude that the interaction pattern between interconnected units, the network, is crucial for understanding the global behavior of complex systems because it keeps the system integrated. And remember, everything is connected, albeit not always directly.

The current study examines the behaviors of four adverse impact measurements: the 4/5ths rule, two tests of significance (ZD and ZIR), and a newly developed AI measurement (Lnadj). Upon the suggestion of the Office of Federal Contract Compliance Program Manual about the sensitivity of the assessment of AI when the sample size is very large (Office of Federal Contract Compliance Programs, 2002), Lnadj is a new statistic that has been developed and proposed as an alternative practical significance test to the 4/5ths rule. The results indicated that, unlike the 4/5ths rule and other tests for adverse impact, Lnadj is an index of practical significance that is less sensitive to differences across selection conditions that are not supposed to affect tests of adverse impact. Furthermore, Lnadj decreases Type I error rates when there is a small d value and Type II error rates when there is moderate to large d value.

Teams can be a fundamental part of an organisational structure. A virtual team is characterised by having its team members spread across different locations, but they remain interdependent in their tasks. Nowadays, virtual teams have become more common as it is an effective way to share resources and remain competitive on the market. However, as virtual teams being a relatively new concept, it is still in need of a well-defined role of leadership. Recently, researchers have begun to realise that certain key factors exists within virtual leadership that facilitate and drive the success of teamwork within the virtual environment. For example, in order to function, a virtual team is dependent on technology, which classifies as a factor of virtual leadership. Other factors are communication, goal setting, leadership behaviour, and trust. The purpose of this paper is to investigate the significance of trust within virtual teams in Swedish organisations. Furthermore, it is also the aim of this thesis to investigate trust as a factor of virtual leadership and its relation to other factors of effective virtual leadership. To evaluate the significance of trust as a factor of leadership, we collected data by doing semi-structured interviews with four representatives from four organisations. This work process is influenced by a hermeneutic epistemology and we report our findings from these interviews in a narrative manner. Furthermore, we have adopted an inductive approach similar to grounded theory in order to analyse the data and to reach our conclusions. Our point of origin was that trust is the most significant of the leadership factors. However, our thesis concludes that communication is in fact the more significant of the different factors of virtual leadership. Without proper communication, none of the other factors carries any substance. Good communication yields trust and so does the other factors if they are well executed through proper communication. In that sense, all factors are interdependent within Swedish Organisations.

In the past few years we have seen the near collapse of the world financial system, and we still have yet to find solutions for world poverty or the food crisis. People have started looking for new solutions in order to solve these problems and are considering new employment options besides the traditional for-profit business sector. Employees are increasingly looking for work in organizations that have a more sustainable approach to business. One organization type that fits these criteria is a social business. Most of the research in social entrepreneurship and social businesses, however, has concentrated on the social entrepreneur and the entrepreneurial process so far. Only few studies have explored the employee side. Similarly, research on perceived employee motivation has mainly concentrated on the traditional for-profit businesses and on non-profit organizations. Although employee motivation is considered as crucial to the success of any business, perceived employee motivation in established social businesses has scarcely been researched yet. The purpose of this thesis is to understand why people choose to work in a social business, and what motivates them to work there. This research was conducted as a single case study following Stake (1995). It was carried out in the Helsinki Metropolitan Area Reuse Centre Ltd in Finland. In order to achieve our goal, we have found it helpful to combine relevant motivation theories such as intrinsic motivation, task significance, prosocial motivation, value congruence, and meaningfulness, with current social business theories. As a result of our research, we have developed a model that elaborates how employees make their decision on employment and what influences their perceived motivation. Our findings suggest that both, the distinct business model and the mission of a social business have a great impact on people’s choice of employment. Moreover, the company values, which are partly derived from the mission of a social business, also influence prospective employees’ choice of employment. In addition, the employees’ educational background impacts their choice as their values reflect their education. They are also looking for such work, whose content fits their education. In our study we have tried to point out that perceived employee motivation in a social business is also strongly influenced by value congruence. Moreover, the perceived meaningfulness that derives from the social business’ mission has an impact on the perceived employee motivation. The employees feel that their work is positively affecting people, society, and the environment, which results in task significance and prosocial motivation. Finally, the flexibility of the work, the ability to influence the work content, and the work atmosphere, are also shown to exercise a great influence on perceived employee motivation.

Research shows that policing is mostly sedentary but physically and mentally demanding tasks occur and that policing includes factors like police inherent stress which may impair the health of police officers. Research has also found that physical exercise can play an important part for coping with these negative elements associated with policing. The overall purpose of this study is to contribute knowledge about the importance of physical exercise for policemen. The study is based on five semi-structured interviews with police officer’s working with emergency response. The result shows that physical exercise had importance for the tasks performed during emergency responses, the police officer’s health as well as short- and longterm mental factors like reduced stress. The result also showed that the demands of policing had impacts on the officer’s exercise and it also demonstrated that the policemen didn’t exercise during work hours mostly due to regulations and organizational barriers.

Attention deficit hyperactivity disorder (ADHD) is a source of diagnostic and intervention confusion and uncertainty for practitioners and parents. Questions creating some of the confusion were answered in a series of three studies. The sample was parent and teacher behavioral ratings for 389 children and 502 adolescents with ADHD and 3131 children and 3161 adolescents without ADHD in public and private schools and mental health clinics in forty states. In the first study, data was derived from participant T-scores on the Behavior Assessment System for Children (2nd ed.) to evaluate the construct validity using first and second order factor analyses. Sufficient construct validity was established. In the second study, descriptive discriminant analyses (DDA) and item level ANOVAs were used to investigate whether behaviors that discriminate between the target (i.e., ADHD) and comparison groups were associated with the primary symptoms, comorbid conditions, functional impairment, or some combination of the three. Analyses were completed using subscale T-scores and individual item scores from the target and comparison groups. Results were compared to determine if the behaviors that discriminated between the groups were consistent across developmental stages and between parents and teachers as raters. Primary symptoms, comorbid conditions, and functional impairment explained the variance as rated by parents and teachers. Primary symptoms were found to be the strongest discriminators of children and adolescents as rated by parents. Atypicality explained the largest variance (72.25%) between children and learning problems explained the largest variance (64.32%) between adolescents when rated by teachers. The third study was a literature review of intervention studies to increase the academic performance of youth with ADHD in light of the statistical significance controversy. Fifty-one single subject and group design studies of academic, behavioral, multimodal and parent training were found. Both sides of the statistical significance controversy were summarized. The method of result reporting for 23 group design studies was investigated. Seventy-seven percent of the studies reported results as ?significant? with 26% reporting effect sizes. Researchers are encouraged to report effect sizes and explicitly compare results to previous studies in order to establish replicability for ease of educator interpretation.