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Continuous norming methods have seldom been subjected to scientific review. In this simulation study, we compared parametric with semi-parametric continuous norming methods in psychometric tests by constructing a fictitious population model within which a latent ability increases with age across seven age groups. We drew samples of different sizes (n = 50, 75, 100, 150, 250, 500 and 1,000 per age group) and simulated the results of an easy, medium, and difficult test scale based on Item Response Theory (IRT). We subjected the resulting data to different continuous norming methods and compared the data fit under the different test conditions with a representative cross-validation dataset of n = 10,000 per age group. The most significant differences were found in suboptimal (i.e., too easy or too difficult) test scales and in ability levels that were far from the population mean. We discuss the results with regard to the selection of the appropriate modeling techniques in psychometric test construction, the required sample sizes, and the requirement to report appropriate quantitative and qualitative test quality criteria for continuous norming methods in test manuals.
Studieren stellt hohe Anforderungen an selbstregulatorische Fähigkeiten und eigenverantwortlichen Umgang mit schwierigen Situationen. Aus den zusätzlichen sprachlichen Barrieren für ausländische Studierende erwachsen spezifische selbstregulatorische Aufgaben, wie der Umgang mit Verständnisproblemen in Vorlesungen. Da hierfür bisher kaum geeignete Erhebungsinstrumente existieren, versucht ScenEx diese Lücke zu schließen. Der Test erfasst das metakognitive Strategiewissen in sprachlich herausfordernden Situationen im Studienalltag. Anhand einer Stichprobe von 290 ausländischen Studierenden im ersten Fachsemester wird die psychometrische Qualität und interne Struktur des Instruments überprüft. ScenEx zeigt eine zufriedenstellende interne Konsistenz und gute Itemfit-Kennwerte, erwartungskonform liegen lokale stochastische Abhängigkeiten der Aufgaben innerhalb der Szenarien vor. Eine konfirmatorische Faktorenanalyse bestätigt die Grobstruktur der Szenarien und des Gesamtscores des Tests. Das Verfahren ist für die weitere Entwicklung der Sprachkompetenz über die anfängliche Sprachfähigkeit hinaus prädiktiv. ScenEx erweist sich insgesamt als ein reliables und valides Instrument zur Erfassung des Strategiewissens in schwierigen Situationen im Studium.
Die raschen Fortschritte der medizinischen, insbesondere der genetischen Diagnostik sind für Eltern von Kindern mit Behinderung Fluch und Segen zugleich: Einerseits stellt Unsicherheit hinsichtlich der Ursache der Behinderung für Eltern eine massive Belastung dar, die den Coping-Prozess wesentlich erschwert. Die Ausschöpfung der diagnostischen Möglichkeiten und das dann mögliche Auffinden des Grundes der Behinderung kann den effektiven Einsatz von Bewältigungsstrategien wesentlich erleichtern. Vorgeburtlich dagegen führt ein mit denselben Diagnosemethoden erhobener auffälliger Befund aufgrund des Mangels an therapeutischen Möglichkeiten sehr häufig zum Abbruch der Schwangerschaft. Mittels einer Fragebogenstudie an 925 Eltern von Kindern mit Down-Syndrom, Eltern von Kindern mit einem Kind mit geistiger Behinderung unklarer Ursache und Eltern nicht-behinderter Kinder wurde untersucht, ob diese Entwicklung zur Herausbildung eines neo-eugenischen Automatismus von pränataler Diagnose und Schwangerschaftsabbruch führt, als dessen Folge Menschen mit angeborener Behinderung als „vermeidbare Last“ erscheinen und Eltern von Kindern mit angeborenen Behinderungen gesellschaftlich ausgegrenzt werden.
One of the major drawbacks in the implementation of intelligent tutoring systems is the limited capacity to process natural language and to automatically deal with unexpected or unknown vocabulary. Latent Semantic Analysis (LSA) is a statistical technique of automatic language processing, which can attenuate the “language barrier” between humans and tutoring systems. LSA-based intelligent tutoring systems address the goals of modelling human tutoring dialogues (AutoTutor), enhancing text comprehension and summarisation skills (State-The-Essence, Summary Street®, conText, Apex), training of comprehension strategies (iStart, a French system in development) and improving story and essay writing (Write To Learn, Select-a-Kibitzer, StoryStation). The systems are reviewed concerning their efficacy in modelling skilled human tutors and regarding their effects on the learner.
Reading fluency is a major determinant of reading comprehension but depends on moderating factors such as auditory working memory (AWM), word recognition and sentence reading skills. We investigated how word and sentence reading skills relate to reading comprehension differentially across the first 6 years of schooling and tested which reading variable best predicted teacher judgements. We conducted our research in a rather transparent language, namely, German, drawing on two different data sets. The first was derived from the normative sample of a reading comprehension test (ELFE-II), including 2056 first to sixth graders with readings tests at the word, sentence and text level. The second sample included 114 students from second to fourth grade. The latter completed a series of tests that measured word and sentence reading fluency, pseudoword reading, AWM, reading comprehension, self-concept and teacher ratings. We analysed the data via hierarchical regression analyses to predict reading comprehension and teacher judgements. The impact of reading fluency was strongest in second and third grade, afterwards superseded by sentence comprehension. AWM significantly contributed to reading comprehension independently of reading fluency, whereas basic decoding skills disappeared after considering fluency. Students' AWM and reading comprehension predicted teacher judgements on reading fluency. Reading comprehension judgements depended both on the students' self-concept and reading comprehension. Our results underline that the role of word reading accuracy for reading comprehension quickly diminishes during elementary school and that teachers base their assessments mainly on the current reading comprehension skill.
The ability to spell words correctly is a key competence for educational and professional achievement. Economical procedures are essential to identifying children with spelling problems as early as possible. Given the strong evidence showing that reading and spelling are based on the same orthographic knowledge, error-detection tasks (EDTs) could be considered such an economical procedure. Although EDTs are widely used in English-speaking countries, the few studies in German-speaking countries investigated only pupils in secondary school. The present study investigated N = 1,513 children in elementary school. We predicted spelling competencies (measured by dictation or gap-fill dictation) based on an EDT via linear regression. Error-detection abilities significantly predicted spelling competencies (R² between .509 and .679), indicating a strong connection. Predictive values in identifying children with poor spelling abilities with an EDT proved to be sufficient. Error detection for the assessment of spelling skills is therefore a valid instrument for transparent languages as well.