Refine
Document Type
- Article (4)
- Doctoral Thesis (1)
Language
- English (5)
Has Fulltext
- yes (5)
Is part of the Bibliography
- no (5)
Keywords
- economics (2)
- eye-tracking (2)
- 900 GeV (1)
- ALICE (1)
- Critical Online Reasoning Assessment (1)
- LHC (1)
- PYTHIA (1)
- Transverse momentum (1)
- corpus study (1)
- epistemic network analysis (1)
Learning to solve graph tasks is one of the key prerequisites of acquiring domain-specific knowledge in most study domains. Analyses of graph understanding often use eye-tracking and focus on analyzing how much time students spend gazing at particular areas of a graph—Areas of Interest (AOIs). To gain a deeper insight into students’ task-solving process, we argue that the gaze shifts between students’ fixations on different AOIs (so-termed transitions) also need to be included in holistic analyses of graph understanding that consider the importance of transitions for the task-solving process. Thus, we introduced Epistemic Network Analysis (ENA) as a novel approach to analyze eye-tracking data of 23 university students who solved eight multiple-choice graph tasks in physics and economics. ENA is a method for quantifying, visualizing, and interpreting network data allowing a weighted analysis of the gaze patterns of both correct and incorrect graph task solvers considering the interrelations between fixations and transitions. After an analysis of the differences in the number of fixations and the number of single transitions between correct and incorrect solvers, we conducted an ENA for each task. We demonstrate that an isolated analysis of fixations and transitions provides only a limited insight into graph solving behavior. In contrast, ENA identifies differences between the gaze patterns of students who solved the graph tasks correctly and incorrectly across the multiple graph tasks. For instance, incorrect solvers shifted their gaze from the graph to the x-axis and from the question to the graph comparatively more often than correct solvers. The results indicate that incorrect solvers often have problems transferring textual information into graphical information and rely more on partly irrelevant parts of a graph. Finally, we discuss how the findings can be used to design experimental studies and for innovative instructional procedures in higher education
Most elements heavier than iron are synthesized in stars during neutron capture reactions in the r- and s-process. The s-process nucleosynthesis is composed of the main and weak component. While the s-process is considered to be well understood, further investigations using nucleosynthesis simulations rely on measured neutron capture cross sections as crucial input parameters. Neutron capture cross sections
relevant for the s-process can be measured using various experimental methods. A prominent example is the activation method relying on the 7Li(p,n)7Be reaction as a neutron source, which has the advantage of high neutron intensities and is able to create a quasi-stellar neutron spectrum at kBT = 25 keV. Other neutron sources able to provide quasi-stellar spectra at different energies suffer from lower neutron intensities. Simulations using the PINO tool suggest the neutron activation of samples with different neutron spectra, provided by the 7Li(p,n)7Be reaction, and a subsequent linear combination of the obtained spectrum-averaged cross sections
to determine the Maxwellian-averaged cross section (MACS) at various energies of astrophysical relevance. To investigate the accuracy of the PINO tool at proton energies between the neutron emission threshold at Ep = 1880.4 keV and 2800 keV,
measurements of the 7Li(p,n)7Be neutron fields are presented, which were carried out at the PTB Ion Accelerator Facility at the Physikalisch-Technische Bundesanstalt in Braunschweig. The neutron fields of ten different proton energies were measured.
The presented neutron fields show a good agreement at proton energies Ep = 1887, 1897, 1907, 1912 and 2100 keV. For the other proton energies, E p = 2000, 2200, 2300, 2500, and 2800 keV, differences between measurement and simulation were found and discussed. The obtained results can be used to benchmark and adapt the PINO tool and provide crucial information for further improvement of the neutron activation method for astrophysics.
An application for the 7Li(p,n)7Be neutron fields is presented as an activation experiment campaign of gallium, an element that is mostly produced during the weak s-process in massive stars. The available cross section data for the 69,71Ga(n,γ)
reactions, mostly determined by activation measurements, show differences up toa factor of three. To improve the data situation, activation measurements were carried out using the 7Li(p,n)7Be reaction. The neutron capture cross sections for
a quasi-stellar neutron spectrum at kBT = 25 keV were determined for 69Ga and 71Ga.
The ongoing digitalization of educational resources and the use of the internet lead to a steady increase of potentially available learning media. However, many of the media which are used for educational purposes have not been designed specifically for teaching and learning. Usually, linguistic criteria of readability and comprehensibility as well as content-related criteria are used independently to assess and compare the quality of educational media. This also holds true for educational media used in economics. This article aims to improve the analysis of textual learning media used in economic education by drawing on threshold concepts. Threshold concepts are key terms in knowledge acquisition within a domain. From a linguistic perspective, however, threshold concepts are instances of specialized vocabularies, exhibiting particular linguistic features. In three kinds of (German) resources, namely in textbooks, in newspapers, and on Wikipedia, we investigate the distributive profiles of 63 threshold concepts identified in economics education (which have been collected from threshold concept research). We looked at the threshold concepts' frequency distribution, their compound distribution, and their network structure within the three kinds of resources. The two main findings of our analysis show that firstly, the three kinds of resources can indeed be distinguished in terms of their threshold concepts' profiles. Secondly, Wikipedia definitely shows stronger associative connections between economic threshold concepts than the other sources. We discuss the findings in relation to adequate media use for teaching and learning—not only in economic education.
The inclusive charged particle transverse momentum distribution is measured in proton–proton collisions at s=900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region (|η|<0.8) over the transverse momentum range 0.15<pT<10 GeV/c. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for |η|<0.8 is 〈pT〉INEL=0.483±0.001 (stat.)±0.007 (syst.) GeV/c and 〈pT〉NSD=0.489±0.001 (stat.)±0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger 〈pT〉 than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.
To successfully learn using open Internet resources, students must be able to critically search, evaluate and select online information, and verify sources. Defined as critical online reasoning (COR), this construct is operationalized on two levels in our study: (1) the student level using the newly developed Critical Online Reasoning Assessment (CORA), and (2) the online information processing level using event log data, including gaze durations and fixations. The written responses of 32 students for one CORA task were scored by three independent raters. The resulting score was operationalized as “task performance,” whereas the gaze fixations and durations were defined as indicators of “process performance.” Following a person-oriented approach, we conducted a process mining (PM) analysis, as well as a latent class analysis (LCA) to test whether—following the dual-process theory—the undergraduates could be distinguished into two groups based on both their process and task performance. Using PM, the process performance of all 32 students was visualized and compared, indicating two distinct response process patterns. One group of students (11), defined as “strategic information processers,” processed online information more comprehensively, as well as more efficiently, which was also reflected in their higher task scores. In contrast, the distributions of the process performance variables for the other group (21), defined as “avoidance information processers,” indicated a poorer process performance, which was also reflected in their lower task scores. In the LCA, where two student groups were empirically distinguished by combining the process performance indicators and the task score as a joint discriminant criterion, we confirmed these two COR profiles, which were reflected in high vs. low process and task performances. The estimated parameters indicated that high-performing students were significantly more efficient at conducting strategic information processing, as reflected in their higher process performance. These findings are so far based on quantitative analyses using event log data. To enable a more differentiated analysis of students’ visual attention dynamics, more in-depth qualitative research of the identified student profiles in terms of COR will be required.