<div> <p>According to self-determination theory (SDT), the extent to which students’ motivation is self-determined is critical for their academic performance. When self-determined, students learn because of personal interest or identification, out of a sense of volition, as opposed to pressure or indifference. SDT also proposes that self-determined academic motivation is facilitated when the learning environment supports the basic psychological needs for autonomy, relatedness, and competence. This model of social support à needs satisfaction à motivation à learning outcomes is termed the general self-determination theory model (hereafter the General Model), and numerous studies have provided support for it. </p> <p>However, the current evidence regarding the General Model is limited, in that no study to date has examined it in its full using within-individual methods. Between-individual analytical methods answer the question of whether a person with higher response on variable A is also more likely to report higher levels of B, whereas within-individual analytical methods answer the question of whether the same person is more likely to experience variable B when reporting experiences of A. Despite the popularity of between-individual methods in educational psychology, they may not be able to reveal the within-person relationships between variables, which are critical for understanding inner psychological processes and mechanisms. </p> <p>Therefore, the current study aims to apply a within-individual analytical approach to the General Model, using a large dataset collected at Purdue over several years. Specifically, in the current dataset, not only may a student provide multiple responses, but also the same classroom contain various students’ responses. Therefore, a cross-classified path model is used, such that the General Model is analyzed under the framework of “responses cross-classified under students and classrooms”. This model enables me to explain the variance-covariance matrix of the variables using the General Model on three levels: the situational (within-student and within-classroom) level, the student level, and the classroom level.</p> <p>Results generally supported the predictions of the General Model on the within-individual, within-classroom level. That is, for the same student, in the same classroom, when she or he experiences higher levels of autonomy support, they would also be more likely to have their psychological needs satisfied, and to study for self-determined reasons, which is then associated with higher perceived learning performance. Unexpected findings include the dominant effect of competence, the direct effects of learning climate and competence, and the lack of relationship between grades and other variables. The General Model is also largely replicated on the student- and classroom-levels.</p> <p>In addition, supplemental analyses showed that (1) although the general trend of motivation and perceived learning climate across one’s college life is null, the trend is moderated by major, such that students in business-related majors decrease in self-determined motivation and perceptions of autonomy support, whereas students in social sciences increase in self-determined motivation and perceptions of autonomy support; (2) there is limited and inconsistent support for a buffer effect, such that the higher autonomy and competence needs satisfaction students generally get, the lower their needs satisfaction in a specific classroom depends on the learning climate. Overall, the current research provides a comprehensive and multilevel understanding of the role of self-determination in the classroom.</p></div>

Today’s business world is highly dynamic, increasingly international, and marked by powerful corporations. Nonetheless, individual human beings shape the environment in which business takes place. In light of such surroundings, one increasingly important challenge for organizations is successful change management, which can only succeed with employees’ support. When facing a well-informed, interconnected array of stakeholders, companies must also tackle demands to take social responsibility. By combining various theoretical and methodological approaches, the present dissertation addressed these trends in four empirical papers. Study 1 and Study 2 considered the reactions of employees during organizational change. The first study investigated the connection between dispositional resistance to change and emotional exhaustion. In a multilevel model, work-unit level informational team climate and perceived organizational support were relevant moderators. Using fuzzy set qualitative comparative analysis (fsQCA), the second paper turned to factors associated with employees’ intended support for change. Drawing from the theory of planned behavior (Ajzen, 1991), it revealed relevant configurations of attitude, subjective norms, and perceived behavioral control. Study 3 focused on corporate social responsibility (CSR) and investigated which combinations of responsible and irresponsible activities, both recent and more historical, shape corporate reputation among the general public. Lastly, Study 4 expressly brought change management and CSR research together by showing that employees reacted more favorably to organizational change when their supervisors effectively communicated responsibility. Taken together, the present dissertation demonstrated that corporations can make a change through responsibility in order to favorably influence both stakeholder and business outcomes, thereby providing relevant implications for both research and practice.

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Therapists’ reactions towards patients are important for the therapeutic process, and is influenced by therapist and patient characteristics. This study aimed to improve the understanding of therapists’ emotional reactions by investigating if patients’ attachment and ability to mentalize predicted therapist countertransference in psychotherapy. Multilevel modeling was used to analyse 87 therapy-dyads in psychotherapy. Patient attachment, measured pre-treatment using self-reports, and mentalization operationalized as Reflective functioning (RF) were hypothesized to predict therapist self-reported emotional experiences (conceptualized as countertransference) over the complete treatment and in different treatment phases. Results showed that lower patient RF predicted more negative therapist countertransference in complete treatment. In the middle and final phases of therapy, lower RF predicted more negative countertransference, and higher RF predicted more positive countertransference. Higher level of avoidant attachment in patients predicted more relaxed therapist countertransference in the final phase of treatment. Findings indicate that patients’ mentalizing ability is important to consider in psychotherapy, as it has informational value for the therapeutic process. / Terapeuters reaktioner gentemot patienter är en viktig del i den psykoterapeutiska processen, och påverkas av terapeuters och patienters personliga egenskaper. Den här studien syftade till att utvidga förståelsen för terapeuters känslomässiga reaktioner genom att undersöka om patienters anknytning och mentaliseringsförmåga predicerar terapeuters motöverföring i psykoterapi. Multilevel-modeling användes för att analysera 87 behandlingsdyader i psykoterapi. Patienters anknytning, mätt innan behandling genom självskattning, och mentalisering operationaliserat som reflektivt fungerande (RF) förväntades predicera terapeuters självskattade emotionella upplevelser (konceptualiserat som motöverföring) över hela behandlingsperioden och i olika behandlingsfaser. Resultaten visade att lägre RF hos patienter predicerade mer negativ motöverföring hos terapeuter över hela behandlingsperioden. I mitten- och slutfaserna av terapin predicerade lägre RF mer negativ motöverföring, och högre RF predicerade mer positiv motöverföring. Högre nivåer av undvikande anknytning hos patienter predicerade mer avslappnad motöverföring hos terapeuter i slutfasen. Fynden indikerar att patienters mentaliseringsförmåga är viktigt att beakta i psykoterapi, eftersom det har informativt värde för den terapeutiska processen.

No description available.

Over the past few decades, the field of Enterprise Architecture has attracted researchers, and many Enterprise Architecture modeling frameworks have been proposed. However, in order to support the different needs, the different frameworks offer many different elements types that can be used to create an Enterprise Architecture. This abundance of elements can make it difficult for the end-user to differentiate between the usages of all the various elements in order to identify what elements they actually need. Therefore, this research analyzes existing Enterprise Architecture modeling frameworks and extract the common properties that exists in the different Enterprise Architecture modeling notations. In this study, we performed a Systematic Literature Review that aims at finding the most commonly used Enterprise Architecture modeling frameworks in the Enterprise Architecture literature. Additionally, the elements defined in these frameworks are used to create a taxonomy based on the similarities between the different Enterprise Architecture Frameworks. Our results showed that TOGAF, ArchiMate, DoDAF, and IAF are the most used modeling frameworks. Also, we managed to identify the common elements that are available in the different Enterprise Architecture Frameworks mentioned above and represent the common elements in a multilevel model. The findings of this study can make it easier for the end-user to pick the appropriate elements for their use cases, as it highlights the core elements of Enterprise Architecture modeling. Additionally, we showed how our model can be extended to support the needs of different domains. This thesis also forms the foundation for the development of an Enterprise Architecture modeling framework that can be customized and extended so that only the relevant elements are presented to the end-user. / Under de senaste decennierna har området för företagsarkitektur lockat forskare och många modelleringsramverk för företagsarkitektur har föreslagits.Men för att stödja de olika behoven erbjuder de olika ramverken många olikaelementtyper som kan användas för att skapa en företagsarkitektur. Dettaöverflöd av element kan göra det svårt för slutanvändaren att skilja mellananvändningen av alla de olika elementen för att specificera vilka element debehöver. Därför analyserar denna forskning existerande modelleringsramverkför företagsarkitektur och extraherar de gemensamma egenskaperna som finnsi de olika modelleringsnotationer för företagsarkitektur. I den här studiengenomförde vi en systematisk litteraturgenomgång som syftar till att hittade mest använda modelleringsramverk för företagsarkitektur i litteraturenav företagsarkitektur. Dessutom används de element som definieras i dessaramverk för att skapa en taxonomi baserad på likheterna mellan de olikaramverk för företagsarkitektur. Våra resultat visade att TOGAF, ArchiMate,DoDAF och IAF är de mest använda modelleringsramarna i de studier viundersökte. Sedan lyckades vi identifiera de gemensamma elementen som ärtillgängliga i de olika ramverk för företagsarkitektur som nämns ovan ochrepresentera de gemensamma elementen i en flernivåmodell. Resultaten avdenna studie kan göra det lättare för slutanvändaren att välja de lämpligaelementen för sina användningsfall, eftersom den belyser kärnelementen imodellering av bedriftsarkitektur. Dessutom visade vi hur vår modell kanutökas för att stödja behoven hos olika domäner. Dessutom tjänar dennaavhandling som en grund för utvecklingen av ett modelleringsramverk förföretagsarkitektur som kan anpassas och utökas så att endast de relevantaelementen presenteras för slutanvändaren.

A multilevel mixture IRT (MMixIRT) model for DIF analysis has been proposed as a solution to gain greater insight on the source of nuisance factors which reduce the reliability and validity of educational assessments. The purpose of this study was to investigate the efficacy of a MMix2PL model in detecting DIF across a broad set of conditions in hierarchically structured, dichotomous data. Monte Carlo simulation was performed to generate examinee response data with conditions common in the field of education. These include (a) two instrument lengths, (b) nine hierarchically structured sample sizes, (c) four latent class features, and (d) eight distinct DIF characteristics, thus allowing for an examination with 576 unique data conditions. DIF analysis was performed using an iterative IRT-based ordinal logistic regression technique, with the focal group identified through estimation of latent classes from a multilevel mixture model. For computational efficiency in analyzing 50 replications for each condition, model parameters were recovered using maximum likelihood estimation (MLE) with the expectation maximization algorithm. Performance of the MMix2PL model for DIF analysis was evaluated by (a) the accuracy in recovering the true class structure, (b) the accuracy of membership classification, and (c) the sensitivity in detecting DIF items and Type I error rates. Results from this study demonstrate that the model is predominantly influenced by instrument length and separation between the class mean abilities, referred to as impact. Enumeration accuracy improved by an average of 40% when analyzing the short 10-item instrument, but with 100 clusters enumeration accuracy was high regardless of the number of items. Classification accuracy was substantially influenced by the presence of impact. Under conditions with no impact, classification was unsuccessful as the matching between model-based class assignments and examinees' true classes averaged only 53.2%. At best, with impact of one standard deviation, classification accuracy averaged between 66.5% to 70.3%. Misclassification errors were then propagated forward to influence the performance of the DIF analysis. Detection power was poor, averaging only 0.34 across the analysis iterations that reached convergence. Additionally, the short 10-item instrument proved challenging for MLE, a condition in which a Bayesian estimation method appears necessary. Finally, this paper provides recommendations on data conditions which improve performance of the MMix2PL model for DIF analysis. Additionally, suggestions for several improvements to the MMix2PL analysis process, which have potential to improve the feasibility of the model for DIF analysis, are summarized.

Social media use is ubiquitous, especially among young adults. Negative consequences of social media use has been associated with engaging in upward social comparisons with others on social media. The current paper presents a series of two studies that seek to understand the nuances of social comparisons as they occur while browsing social media. In Study 1 (N = 161) we tested whether upward social comparisons would be less harmful when the comparer focuses on the similarities, rather than differences, with the comparison target. We observed a marginal interaction indicating that when thinking about similarities with the target, upward comparisons were slightly less detrimental to self-evaluations, than when thinking about differences. Study 2 (N = 320) tested other potential moderators of upward social comparisons suggested by traditional theories of social comparison to see if they would apply to a social media context. We predicted when a participant rates the comparison target to be more similar (vs. different) and distant (vs. close) and the domain to be more attainable (vs. less attainable), upward social comparisons will be less harmful to self-evaluations. Neither similarity nor closeness were significant moderators. Multilevel models showed a significant interaction between upward comparisons and attainability on self-evaluations (p < .001). Simple slopes indicated viewing the domain as attainable amplified the harmful effects of upward social comparisons on self-evaluations compared to viewing the domain as less attainable. These results are contrary to our predictions and suggest that traditional theories of social comparisons may not apply to a social media context. We also investigated how the target of the social comparison would impact the experience of the social comparison and its impact on self-evaluations. Results from Study 2 showed that participants who made comparisons with distant others (celebrities/strangers) were more likely to have higher upward social comparison scores, lower levels of similarity and closeness and view the domain as less attainable. These results display when we could expect harmful consequences following making a social comparison with a celebrity or stranger while viewing Instagram, posts. Study limitations and advantages are discussed along with future research to be explored.

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As K12 online learning continues to grow across the nation, the population of online students, much like the population of face-to face students, continues to change. As the online student population becomes increasingly diverse, not only in terms of race, but in terms of religion, sexual orientation and socioeconomic status, research must be undertaken to assess the level of preparation that K12 online teachers have in terms of teaching this population. This dissertation intends to serve as a baseline analysis, providing information on K12 online teachers' knowledge of the types of student characteristics and identities that may be present in their online students, as well as their abilities to meet the needs of these increasingly diverse students. Using the MAKSS-T survey measure and framed within the lens of Bourdieu's field theory, this study found that while K12 online teachers feel as if they have a "good" understanding of a number of possible characteristics and identities in their online students, that terms related to sexual orientation were not as well understood. Additionally, teachers felt "good" in terms of their skills in addressing the unique needs of these students. However, teachers felt weakest in their ability to critique multicultural research. Teachers also noted that they do not feel adequately prepared to handle this changing population and desire additional training in this area.