Teachers’ judgement accuracy of word problems and influencing task features

The ability to judge accurately the difficulty of mathematical tasks is considered as a central facet of the diagnostic competence of mathematics teachers. An underlying reason is that the accurate judgement of task difficulty is the basis for achieving an optimal level of instruction for the learning group. Although a lot of studies have already investigated the judgement accuracy and the influence of additional factors, like teacher knowledge, there is a lack of a detailed look at the task features as possible influencing factors. Therefore, in the present study, we first investigated the judgement accuracy of word problems with fractions. Afterwards, by means of theoretical varied task features and an empirical study with 153 6th graders as well as 64 prospective teachers, we explored differences in the tasks regarding the judgement accuracy.This research was funded by the Ministry of Science, Research and Arts of Baden-Wuerttemberg within the Research Training Group “Diagnostic Competences of Teachers”

Dynamisches Testen der Lesekompetenz. Theoretische Grundlagen, Konzeption und Testentwicklung. Projekt Dynamisches Testen

Dynamische Tests gelten insbesondere im Bildungssektor als Alternative zu herkömmlichen Tests. Für den Bereich der Lesekompetenz fehlen bislang jedoch gesicherte Erkenntnisse, die die diagnostische Gute eines dynamischen Lesekompetenztests belegen können. Der hier vorliegende Beitrag bietet einen theoretischen Überbau für die Entwicklung eines solchen dynamischen Lesekompetenztests und informiert zudem (nicht immer chronologisch) über grundlegende Schritte der Testentwicklung sowie erste Ergebnisse der Testkonstruktion. (DIPF/Orig.

Projection image-to-image translation in hybrid X-ray/MR imaging

The potential benefit of hybrid X-ray and MR imaging in the interventional environment is large due to the combination of fast imaging with high contrast variety. However, a vast amount of existing image enhancement methods requires the image information of both modalities to be present in the same domain. To unlock this potential, we present a solution to image-to-image translation from MR projections to corresponding X-ray projection images. The approach is based on a state-of-the-art image generator network that is modified to fit the specific application. Furthermore, we propose the inclusion of a gradient map in the loss function to allow the network to emphasize high-frequency details in image generation. Our approach is capable of creating X-ray projection images with natural appearance. Additionally, our extensions show clear improvement compared to the baseline method.Comment: In proceedings of SPIE Medical Imaging 201

The Relation between Interests and Grades : Path Analyses in Primary School Age

Within the school context substantial correlations between interests and grades are well documented, but the causal ordering still remains unclear. The paper examines how the relation between interests and grades over several measurement waves in elementary school age can be characterized, whether gender differences in the pattern of effects can be shown, and whether the effects are school-subject-specific. The present analysis follows N = 1.199 students in the 3rd Grade over a year and a half. It can be shown that grading determines the level of future interests but not vice versa. Thereby, the pattern of results concerning interests and grades is similar for boys and girls. The effects of grades on subsequent interests are mostly school-subject-specific

Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging

Hybrid X-ray and magnetic resonance (MR) imaging promises large potential in interventional medical imaging applications due to the broad variety of contrast of MRI combined with fast imaging of X-ray-based modalities. To fully utilize the potential of the vast amount of existing image enhancement techniques, the corresponding information from both modalities must be present in the same domain. For image-guided interventional procedures, X-ray fluoroscopy has proven to be the modality of choice. Synthesizing one modality from another in this case is an ill-posed problem due to ambiguous signal and overlapping structures in projective geometry. To take on these challenges, we present a learning-based solution to MR to X-ray projection-to-projection translation. We propose an image generator network that focuses on high representation capacity in higher resolution layers to allow for accurate synthesis of fine details in the projection images. Additionally, a weighting scheme in the loss computation that favors high-frequency structures is proposed to focus on the important details and contours in projection imaging. The proposed extensions prove valuable in generating X-ray projection images with natural appearance. Our approach achieves a deviation from the ground truth of only 6% and structural similarity measure of 0.913 ± 0.005. In particular the high frequency weighting assists in generating projection images with sharp appearance and reduces erroneously synthesized fine details