Process data recording students’ interactions with digital assessment items are available in digital educational assessments and have become a focus of cognitive scientists to analyze inquiry skills during problem solving. This study examines the inquiry behaviors of using tools (i.e., resource tabs) in short response construction items from the 2019 National Assessment of Educational Progress science assessment. We visualized the occurrence times and durations of response construction behaviors and tool use behaviors and conducted correlation analyses and mixed-effects regressions between the count (and duration) of tool use behaviors and item scores. The results reveal that tool use behaviors are significantly associated with item scores and probabilities of finishing the whole block the problem; increasing tool use durations or counts increases the chances of getting higher scores, but it also increases the chances of not finishing the block. This study exemplifies how to use process data to investigate scientific inquiry skills.

This paper reviews the existing literature on categorical perception of sounds and colors in different animals including humans. We highlight that categorical perception is a combination of nature and nurture; to be specific, categorical perception is innate with a phylogenetic root, but it can also be modified by postnatal experience. We also suggest that language is not wholly the basis for categorical perception, as what Sapir-Whorf hypothesis posits; instead, language is one type of experience that can affect the nurture part of categorical perception across domains and modalities in humans.

The Shockley-Queisser limit describes the maximum solar energy conversion efficiency achievable for a particular material and is the standard by which new photovoltaic technologies are compared. This limit is based on the principle of detailed balance, which equates the photon flux into a device to the particle flux (photons or electrons) out of that device. Nanostructured solar cells represent a novel class of photovoltaic devices, and questions have been raised about whether or not they can exceed the Shockley-Queisser limit. Here we show that single-junction nanostructured solar cells have a theoretical maximum efficiency of ∼42% under AM 1.5 solar illumination. While this exceeds the efficiency of a non-concentrating planar device, it does not exceed the Shockley-Queisser limit for a planar device with optical concentration. We consider the effect of diffuse illumination and find that with optical concentration from the nanostructures of only × 1,000, an efficiency of 35.5% is achievable even with 25% diffuse illumination. We conclude that nanostructured solar cells offer an important route towards higher efficiency photovoltaic devices through a built-in optical concentration.

Many technological applications in photonics require devices to function reliably under extreme conditions, including high temperatures. To this end, materials and structures with thermally stable optical properties are indispensable. State-of-the-art thermal photonic devices based on nanostructures suffer from severe surface diffusion-induced degradation, and the operational temperatures are often restricted. Here, we report on a thermo-optically stable superabsorber composed of bilayer refractory dielectric materials. The device features an average absorptivity ∼95% over >500 nm bandwidth in the near-infrared regime, with minimal temperature dependence up to 1500 °C. Our results demonstrate an alternative pathway to achieve high-temperature thermo-optically stable photonic devices.

Computer-based educational assessments often include questions with a drag-and-drop response. Logged data obtainedfrom drag-and-drop responses allow us to go beyond scores, investigating the response strategies test-takers use to reachan answer. There is no previously published research on strategies used by test-takers in answering drag-and-drop ques-tions. We tested 476 MTurk participants under five conditions where key design features of mathematics questions weremanipulated. Regardless of the design manipulations, participants mostly used one of the two possible systematic responsestrategies. Using PRIMs cognitive architecture (Taatgen, 2013), we constructed computational cognitive models to sim-ulate the differences between these two strategies. The models were able to capture participants reaction time patterns.Our conclusion based on the models is that most participants apply a cognitively less demanding strategy by offloadingcognition on action, which is in line with the idea of strategy selection as rational metareasoning (Falk & Griffiths, 2017).

Neural mechanisms behind noun and verb processing are ubiquitously separate, yet it remains controversial which factor, syntax or semantics, is behind such separation. We conducted an ERP study using Chinese sentences with a specific construction, noun phrase + mei (“not/no”) + noun/verb/noun-verb-ambiguous-word, and excluding other grammatical or syntactic factors that could hint at the target words’ part-of-speech. Results showed significantly distinct P200, N400 and P600 between noun and verb processing in native speakers, indicating that semantic factors are essential for the differentiated neural mechanisms behind noun and verb processing. Similar results were also found between noun-verb-ambiguous-word and noun processing, but not between noun-verb-ambiguous-word and verb processing, suggesting that lacking clues on part-of-speech makes the dynamic properties of the ambiguous words more salient than the static ones, thus causing interpretation of such words more likely as verbs. This further elaborates the crucial role of semantic factors in noun and verb processing.

Process data (e.g., logs of actions, keystrokes, times, or eye tracks) recording students interactions with digital assessmentsare available in many digital educational assessments. They have become the primary focus of cognitive scientists todetect and analyze students strategies during problem solving. This study developed a Sankey diagram-based methodto visualize process data of multiple-choice items. Such diagram has been widely adopted in industry and ecology totrace flow of information, energy, or resource. Using released items from the 2017 National Assessment of EducationalProgress Mathematics Tests, we illustrated how to use such a diagram to elucidate frequent answer formulation patternsof students, their common mistakes, and estimated probabilities of reaching correct/wrong answers at various answeringstages. These help reveal the problem solving strategies adopted by students and their underlying cognitive processes.Assessment developers, teachers, and students could use such insights to improve assessments and learning outcomes forconfusing concepts.

Purpose

Heating of gradient coils and passive shim components is a common cause of instability in the B₀ field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.

Method

A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).

Results

Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.

Discussion

This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.