Wie die meisten westlichen Streitkräfte, bewegt sich die Bundeswehr im Spannungsfeld zwischen hohem Personalbedarf und Fachkräftemangel. Durch ein Onlineassessment kann der Bewerbungsprozess dahingehend optimiert werden, dass fähiges Personal schneller gebunden wird. Onlineassessment hat diverse Vorteile, gleichzeitig sind damit jedoch Herausforderungen verbunden. Die wahrscheinlich größte ist es, Betrug zu minimieren, da Onlineassessment in einer weitestgehend unkontrollierten Umgebung stattfindet. Zur Entgegnung dieser Problematik dienen verschiedene Ansätze, wie beispielsweise große Itempools, wodurch einer Verbreitung der Lösung im Internet entgegengewirkt werden kann. Dieser Ansatz ist jedoch mit hohen Kosten verbunden. Automatische Itemgenerierung hingegen ermöglicht es, kostengünstig und zeiteffizient psychometrisch hochwertige Items zu erstellen. Aus diesem Grund wurden in der vorliegenden Arbeit zwei Arbeitsgedächtnistests mit automatischer Itemgenerierung für das Onlineassessment der Bundeswehr entwickelt und evaluiert, mit dem Ziel einer hohen prädiktiven Validität auf die Diagnostik vor Ort. In der ersten Studie (N = 330) wurde gezeigt, dass automatische Itemgenerierung für die entwickelten Arbeitsgedächtnistests eingesetzt werden kann. Hierbei wurden zudem zwei verschiedene zeitliche Varianten untersucht, wobei sich diejenige mit der längeren Stimulusrepräsentationszeit als vorteilhafter erwies. In der zweiten Studie (N = 621) wurden Nachweise für Reliabilität und Validität erbracht. Die Tests zeigten eine gute konvergente und diskriminante Validität. Zudem konnte einer der beiden Tests eine sehr gute prädiktive Validität aufweisen. Unter Gesamtberücksichtigung der Testgütekriterien wurde dieser Test schließlich für das Onlineassessment der Bundeswehr vorgeschlagen. Somit steht der Bundeswehr nun ein wissenschaftlich fundierter Arbeitsgedächtnistest für das Onlineassessment zur Verfügung. / Like most Western armed forces, the Bundeswehr faces both high personnel requirements and a shortage of skilled personnel. Online assessment can optimize the application process to ensure that capable personnel are retained more quickly. Online assessment has various advantages, but also challenges associated with it. Probably the biggest of these challenges is minimizing cheating, as online assessment takes place in a largely unsupervised environment. Various approaches are used to counter this problem, such as large item pools, which can be used to counter the dissemination of solutions on the Internet. However, this approach is associated with high costs. Automatic item generation, on the other hand, makes it possible to create psychometrically high-quality items in a cost-effective and time-efficient manner. For this reason, two working memory tests with automatic item generation for the German Armed Forces’ online assessment were developed and evaluated in the present study, with the aim of matching the high predictive validity of on-site diagnostics. The first study (N = 330) demonstrated that automatic item generation can be used for the developed working memory tests. Two different temporal variants were also investigated, with the longer stimulus presentation time proving to be more beneficial. The second study (N = 621) provided reliability and validity evidence. The tests showed good convergent and discriminant validity. In addition, one of the two tests demonstrated very good predictive validity. Taking into account the overall test quality criteria, this test was ultimately proposed for use in the German Armed Forces’ online assessment. Thus, the Bundeswehr now has a scientifically-grounded working memory test available for its online assessment.

This study empirically compares the Classical Test Theory (CTT) and the Partial Credit Model (PCM) of Rasch focusing on the invariance of item parameters. The invariance concept which is the consequence of the principle of specific objectivity was tested in both CTT and PCM using the results of learners who wrote the National Senior Certificate (NSC) Mathematics examinations in 2010. The difficulty levels of the test items were estimated from the independent samples of learn- ers. The same sample of learners used in the calibration of the difficulty levels of the test items in the PCM model were also used in the calibration of the difficulty levels of the test items in CTT model. The estimates of the difficulty levels of the test items were done using RUMM2030 in the case of PCM while SAS was used in the case of CTT. RUMM2030 and SAS are both the statistical softwares. The analysis of variance (ANOVA) was used to compare the four different design groups of test takers. In cases where the ANOVA showed a significant difference between the means of the design groups, the Tukeys groupings was used to establish where the difference came from. The research findings were that the test items' difficulty parameter estimates based on the CTT theoretical framework were not invariant across the different independent sample groups. The over- all findings from this study were that the CTT theoretical framework was unable to produce item difficulty invariant parameter estimates. The PCM estimates were very stable in the sense that for most of the items, there was no significant difference between the means of at least three design groups and the one that deviated from the rest did not deviate that much. The item parameters of the group that was representative of the population (proportional allocation) and the one where the same number of learners (50 learners) was taken from different performance categories did not differ significantly for all the items except for item 6.6 in examination question paper 2. It is apparent that for the test item parameters to be invariant of the group of test takers in PCM, the group of test takers must be heterogeneous and each performance category needed to be big enough for the proper calibration of item parameters. The higher values of the estimated item parameters in CTT were consistently found in the sample that was dominated by the high proficient learners in Mathematics ("bad") and the lowest values were consistently calculated in the design group that was dominated by the less proficient learners. This phenomenon was not apparent in the Rasch model. / Mathematical Sciences / M.Sc. (Statistics)

Each year thousands of students enrol in introductory statistics courses at universities throughout Australia, bringing with them formal and informal statistical knowledge and reasoning, as well as a wide range of basic numeracy skills, mathematical inclinations and attitudes towards statistics, which have the potential to impact on their ability to develop statistically. This research develops and investigates measures of each of these components for students at the interface of secondary and tertiary education, and investigates the relationships that exist between them, and a range of background variables. The focus of the research is on measuring and analysing levels and abilities in statistical reasoning for a range of students at the tertiary interface, with particular interest also in investigating their basic numeracy skills and how these may or may not link with statistical reasoning allowing for other variables and factors. Information from three cohorts in an introductory data analysis course, whose focus is real data investigations, provides basis for the research. This course is compulsory for all students in degree programs associated with all sciences or mathematics. The research discusses and reports on the development of questionnaires to measure numeracy and statistical reasoning and the students' attitudes and reflections on their prior school experiences with statistics. Students' attitudes are found to be generally positive, particularly with regard to their self-efficacy. They are also in no doubt as to the links that exist between mathematics and statistics. The Numeracy Questionnaire, developed to measure pre-calculus skills relevant to an introductory data analysis course which emphasises real data investigations, demonstrates that many students who have completed a basic algebra and calculus senior school subject struggle with skills which are in the pre-senior curricula. Direct examination of the responses helps to understand where and why difficulties tend to occur. Rasch analysis is used to validate the questionnaire and assist in the description of levels of skill. General linear models demonstrate that a student's numeracy score depends on the result obtained in senior mathematics, whether or not the student is a mathematics student, gender, whether or not higher level mathematics has been studied, self-efficacy and year. The research indicates that either the pre-senior curricula need strengthening or that exposure to mathematics beyond the core senior course is required to establish confidence with basic skills particularly when applied to new contexts and multi- step situations. The Statistical Reasoning Questionnaire (SRQ) is developed for use in the Australian context at the secondary/tertiary interface. As with the Numeracy Questionnaire, detailed examination of the responses provides much insight into the range and features of statistical reasoning at this level. Rasch analyses, both dichotomous and polychotomous, are used to establish the appropriateness of this instrument as a measuring tool at this level. The polychotomous, Rasch partial credit model is also used to define a new approach to scoring a statistical reasoning instrument and enables development and application of a hierarchical model and measures levels of statistical reasoning appropriate at the school/tertiary interface. General linear models indicate that numeracy is a highly significant predictor of statistical reasoning allowing for all other variables including tertiary entrance score and students' backgrounds and self-efficacy. Further investigation demonstrates that this relationship is not limited to more difficult or overtly mathematical items on the SRQ. Performance on the end of semester component of assessment in the course is shown to depend on statistical reasoning at the beginning of semester as measured by the partial credit model, allowing for all other variables. Because of the dominance of the relationship between statistical reasoning (as measured by the SRQ) and numeracy on entry, some further analysis of the end of semester assessment is carried out. This includes noting the higher attrition rates for students with less mathematical backgrounds and lower numeracy.

This study empirically compares the Classical Test Theory (CTT) and the Partial Credit Model (PCM) of Rasch focusing on the invariance of item parameters. The invariance concept which is the consequence of the principle of specific objectivity was tested in both CTT and PCM using the results of learners who wrote the National Senior Certificate (NSC) Mathematics examinations in 2010. The difficulty levels of the test items were estimated from the independent samples of learn- ers. The same sample of learners used in the calibration of the difficulty levels of the test items in the PCM model were also used in the calibration of the difficulty levels of the test items in CTT model. The estimates of the difficulty levels of the test items were done using RUMM2030 in the case of PCM while SAS was used in the case of CTT. RUMM2030 and SAS are both the statistical softwares. The analysis of variance (ANOVA) was used to compare the four different design groups of test takers. In cases where the ANOVA showed a significant difference between the means of the design groups, the Tukeys groupings was used to establish where the difference came from. The research findings were that the test items' difficulty parameter estimates based on the CTT theoretical framework were not invariant across the different independent sample groups. The over- all findings from this study were that the CTT theoretical framework was unable to produce item difficulty invariant parameter estimates. The PCM estimates were very stable in the sense that for most of the items, there was no significant difference between the means of at least three design groups and the one that deviated from the rest did not deviate that much. The item parameters of the group that was representative of the population (proportional allocation) and the one where the same number of learners (50 learners) was taken from different performance categories did not differ significantly for all the items except for item 6.6 in examination question paper 2. It is apparent that for the test item parameters to be invariant of the group of test takers in PCM, the group of test takers must be heterogeneous and each performance category needed to be big enough for the proper calibration of item parameters. The higher values of the estimated item parameters in CTT were consistently found in the sample that was dominated by the high proficient learners in Mathematics ("bad") and the lowest values were consistently calculated in the design group that was dominated by the less proficient learners. This phenomenon was not apparent in the Rasch model. / Mathematical Sciences / M.Sc. (Statistics)

This study used the TIMSS 2011 International Database to investigate predictors of 8th-grade mathematics achievement across three countries that represent a wide range of cultures and levels of mathematics achievement: Chinese Taipei, Ghana, and the United States. A review of literature on predictors of mathematics achievement yielded variables in four major contexts of learning—a student’s home, beliefs, school, and classroom. The variables of home that were investigated are home possessions for learning, parent education, and parents’ expectations and involvement in their children’s education. The variables of student beliefs were self-confidence in mathematics and the value of mathematics. The variables of school were school climate, school resources, administrator leadership, and school socioeconomic status. Finally, the variables of the classroom are access and equity, curriculum, tools and technology, assessment, and teacher professionalism. A 2-level hierarchical linear model was used to investigate relationships between the predictors for learning mathematics and 8th-grade mathematics achievement. Level 1 represented the relationships among the student-level variables, and Level 2 represented the school-level variables. In Chinese Taipei, statistically significant predictors of mathematics achievement in the final model included variables from the domains of home resources, student beliefs, school climate, and school socioeconomic status. In Ghana, both student-beliefs variables had statistically significant relationships with mathematics achievement, and one school climate and one school socioeconomic status variable each was found statistically significant. The U.S. had statistically significant predictors in the domains of home resources, student beliefs, school socioeconomic status, classroom-level access and equity, classroom assessment, and teacher professionalism. This study extends previous research in several ways. It includes a review of classic and recent literature regarding predictors of mathematics achievement; 17 scales using the Rasch partial credit model were developed to measure predictors of mathematics achievement; and the results of this study may be used to examine the relationships between the independent variables of this study and middle-grades mathematics achievement in countries similar to the 3 in this study to reinforce and support variables that contribute to student achievement.