@phdthesis{,
    author = {Talić, Irma},
    title = {Uncovering Dynamics in Students' Academic Experiences in Everyday School Life},
    editor = {},
    booktitle = {},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2023},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {Educational Psychology; Multilevel Modeling; Experience Sampling Method; Students' Perceptions of Instructional Quality; Test Anxiety; Nested Factor Model},
    abstract = {Ratings obtained in psychological assessment often confound multiple sources of variances. This confounding can distort constructs' structural representation as well as their relations to other constructs. In three research articles, the present cumulative dissertation thus aimed at disentangling specific from general components in students' academic experiences in the classroom in three different ways. All articles drew on parts of the larger intensive longitudinal DynASCEL project data on German secondary school students attending the ninth and 10th grades of the highest ability track. The specific (versus general) components that were disentangled varied across articles, that is, domain-specificity (versus domain-generality) in Article 1, situation-specificity (versus habituality) in Article 2, and person-specificity (versus consensus) in Article 3. Specifically, in Article 1, a latent nested factor modeling approach was used to differentiate domain-specific from domain-general components in two dimensions of self-reported trait test anxiety (i.e., worry and emotionality) in the two domains of math and German as well as across domains (N = 348 students). In Article 2, state perceptions of three basic dimensions of instructional quality (teacher support, cognitive activation, classroom management) were assessed across a three-week period in four subjects, where situation-specific variance components were disentangled from habitual, trait-like components (N = 372 students, and nmathematics = 2,681, nphysics = 1,555, nGerman = 2,026, nEnglish = 1,835 observations) in two-level confirmatory factor analyses. Finally, Article 3 disentangled person-specific, idiosyncratic from class-room, consensual variance components in students’ state perceptions of instructional quality in math (N = 372 students, and nmathematics = 2,681 observations) in linear mixed effects models. Relations to crucial constructs (e.g., school grades) were dis-played in each article in two ways, that is (a) with and (b) without disentangling the different variance components such that the effect of differentiating the different components becomes apparent immediately. In doing so, the present dissertation enhanced the understanding of key educational constructs’ representation and their implications.},
    note = {},
    
    school = {Universität der Bundeswehr München},
    
}