37495 research outputs found
Sort by
“Asking for Help Feels Like a Weakness”: Factors Shaping First-Year Students’ Expectations of STEM Course Office Hours
Full text linkBackground
Office hours are one of the most ubiquitous resources for students in STEM courses. However, there has been only limited work examining what students think of STEM course office hours, and we are not aware of any past work that has examined (1) how students perceive STEM course office hours upon entering college, and (2) how these perceptions change over time and the factors that shape these perceptions and expectations of what will occur in office hours. Here, we utilize a longitudinal series of surveys to capture first-year students’ perceptions and expectancies for office hours at the beginning of college, after one semester, and at the end of their first year, drawing upon expectancy-value theory to situate our results. Results
We identify that most new first-year students enter college with moderate or high self-reported familiarity with office hours, and that the level of familiarity increases throughout the year. New first-year students hold a variety of conceptions about office hours, some correct (e.g., associating office hours as a space for getting help on course content) and some likely incorrect (e.g., office hours as an independent study hall), that likely shape students’ expectancies, perceived benefits, and costs of attending office hours. We also find that most new first-year students hold positive attitudes towards STEM course office hours, and that some students’ perceptions are likely shaped by some secondary schools implementing office hours during the COVID-19 pandemic. Finally, we determine that most students who attend office hours report them as helpful and increasing their self-efficacy in the course, with students providing a variety of reasons for how office hours impacted their self-confidence (e.g., through increased content knowledge, better relationship with the instructor, greater metacognitive reflection.). Conclusions
Our work provides the first examination of how new first-year students perceive STEM course office hours, and the first longitudinal study that tracks their changes in perception over time. We highlight implications and recommendations for STEM course instructors to increase their office hours engagement throughout, drawing upon our results and expectancy-value theory
Hyperspectral Band Selection via Heterogeneous Graph Convolutional Self-Representation Network
Full text linkHyperspectral image (HSI) band selection (BS) plays a crucial role in HSI dimensionality reduction, aiming to identify a representative subset of bands with minimal redundancy. However, conventional BS approaches primarily operate in the Euclidean domain, often overlooking the structural characteristics of pixels and spectral bands, such as spatial continuity and spectral dependencies. In addition, they handle each HSI as an integrated unit to harness implicit spatial information, disregarding spatial distribution variations across different homogeneous regions. To fully leverage structural information, this study introduces a novel BS method, termed the dual heterogeneous graph convolutional network with enhanced self-representation (ESR-HGCN), for HSI BS. The heterogeneous graph convolutional network (HGCN) and enhanced self-representation (ESR) serve as the two essential components of the proposed ESR-HGCN. To explore spatial features and the potential hidden interactions among spectral bands, we use the HGCN as the backbone network for heterogeneous graph-based HSI BS. Dual graphs at the pixel and band levels are separately constructed and integrated into the ESR module, where a sparsity constraint is enforced and the original Frobenius norm is replaced withℓ1- andℓ2,1-norm regularizations to achieve robust BS. Meanwhile, dual graph convolution operations are performed to separately extract spatial and spectral features, thereby seamlessly integrating spectral, spatial, and geometric information, offering significant advantages for HSI BS. Finally, an effective optimization scheme is developed to refine the proposed approach. Experimental findings on representative HSI datasets highlight the superiority of ESR-HGCN over state-of-the-art methods
The Future Intensification of Hydrological Extremes and Whiplashes in the Contiguous United States Increase Community Vulnerability
Full text linkHydroclimatic whiplash rapid shifts between drought and flood poses growing risks to U.S. communities. Here, we assess historical extremes and future projections using a normalized streamflow metric: the annual mean flow’s deviation from the 1981–2020 average, expressed as a fraction of that average. This metric is applied to United States Geological Survey records and Localized Constructed Analogs downscaled projections under Representative Concentration Pathways 4.5 and 8.5. Results reveal sharp regional disparities, with drought deficits exceeding 300% of normal flow during multi-year droughts. By linking hydrologic outcomes with the Federal Emergency Management Agency’s National Risk Index, we find that counties facing the deepest droughts also experience the highest annual losses and lowest resilience. Under the high-emissions scenario, sustained surpluses emerge only in already resilient regions. These findings highlight the urgent need for region-specific, adaptive water management to protect vulnerable populations from worsening climate extremes
Direct and Indirect Effects of Water-Table Levels on Redox-Active Organic Matter Reduction in an Alaskan Rich Fen
No full textRedox-active organic matter (RAOM) reduction is an important control on methane production in northern peatlands, but it is unclear how global climate change will affect RAOM reduction. We investigated the effects of water-table levels on RAOM reduction by leveraging a long-term water-table manipulation experiment in an Alaskan fen, which includes Lowered and Raised treatment plots relative to a Control. Common substrate peat was incubated in each plot during one summer of experimental manipulation and another summer of site-wide flooding. During experimental manipulation, common substrate RAOM was more reduced in the Raised plot than the Lowered plot at both 10–20 cm (19.1 ± 0.8 vs. 0.7 ± 0.3 μmol e− g−1 dw peat, p = 0.003) and 30–40 cm (18.0 ± 0.5 vs. 3.6 ± 1.2 μmol e− g−1 dw peat, p = 0.011). During site-wide flooding, differences in common substrate RAOM persisted with greater RAOM reduction in the Raised plot than both Control and Lowered plots (p \u3c 0.05) and greater methane production from Raised plot common substrate. A comparison of the chemical composition of Raised and Control peat during an anaerobic laboratory incubation showed that the compounds removed during microbial processing differed between plots with a higher double bond equivalence to carbon ratio for the Raised plot (0.54 ± 0.13) compared to the Control plot (0.44 ± 0.17). Together, these field and laboratory results suggest that long-term increases in water-table levels can have complex effects on RAOM beyond oxygen availability with the potential to impact methane production from northern peatlands. Plain Language Summary
Global climate change is expected to affect peatland processes that control the production of greenhouse gases including methane. One key, understudied process is the microbial use of organic molecules as electron acceptors during respiration (called organic matter reduction) in these oxygen-limited environments. To better understand peatland response to global climate change, we studied how long-term differences in water-table levels in an Alaskan fen would affect organic matter reduction. We incubated a well-mixed peat sample in three different water-table manipulation plots and found that organic matter reduction closely followed water-table level, but that legacy water-table levels still had an effect on these organic molecules even when all plots were completely flooded. Plots that had experienced higher water-table levels and higher organic matter reduction also had higher rates of methane production. Our results from in situ porewater chemistry and laboratory incubations of peat suggest that the differences in organic matter reduction observed at the peat surface may be due to a change in how microbes process carbon following long-term water-table changes. Taken together, these findings show that long-term changes to peatland water-table levels can have lasting effects on processes controlling peatland carbon cycling
Phi Beta Kappa, Psi of California Chapter, Induction Ceremony 2025
No full texthttps://digitalcommons.chapman.edu/pbk_induction_ceremony_2025/1022/thumbnail.jp
Phi Beta Kappa, Psi of California Chapter, Induction Ceremony 2025
No full texthttps://digitalcommons.chapman.edu/pbk_induction_ceremony_2025/1027/thumbnail.jp
Property Rights in the Face of Historic Injustice
No full textIt seems natural to adopt a historical approach when it comes to property titles: When property titles have a clean history, they are to be respected as a matter of justice; when they do not have a clean history, for example, in cases of prior theft, they must be returned to the original owners or their descendants. But the historical approach has serious drawbacks. This paper presents an alternative. Starting from the idea that property rights must be stable, we offer an account of why historic injustices sometimes do, but sometimes do not, undermine current titles. This account offers a standard of better or worse claims, and maintains that current titles are not undermined unless there are contestants who can put forward comparatively better claims
Holy Day Surveys and Political Attitudes in Israel
Full text linkResearchers regularly use large survey studies to examine public political opinion. Surveys running over days and months will necessarily incorporate religious occasions that can introduce variation in public opinion. Using recent survey data from Israel, this study demonstrates that giving surveys on religious occasions (e.g., the Sabbath, Hannukah, Sukkot) can elicit different opinion responses. These effects are found among both religious and non-religious respondents. While incorporating these fluctuations is realistic in longer-term surveys, surveys fielded in a short window inadvertently drawing heavily on a holiday or holy day sample may bias their findings. This study thus urges researchers to be cognizant of ambient religious context when conducting survey studies
A Practical Guide to Grade Adjustment or Curving for Pharmacy and Other Professional Health Programs
Full text linkThe peer-reviewed literature on the adjustment or curving of assessments in health profession programs is almost non-existent. This communication aims to present potential methods of grade adjustment for individual questions or entire assessments. Simulated data for a 25-item assessment were used as an example to analyze the effects of different methods of grade adjustment on students’ scores. Grade adjustments were made by adjusting the points for individual questions or the scores for the entire assessment. Adjustment for the individual questions was carried out by dropping the question, adding points to those who missed the question, or adding a bonus point to all students. Grade adjustment methods for the entire assessment included adjusting the mean or mean plus distribution (i.e., standard deviation) of the assessment score. Different methods of grade adjustments or curving for individual questions or the entire assessment resulted in drastically different outcomes for individual students’ scores. The justifications for selecting the appropriate method for adjustment of the individual scores are presented based on item analysis statistics. Curving or adjusting the score for the entire exam may be justified when there is a need for consistency in grade distribution among the assessments across the years or different sections of the course. Although methods for adjustment of grades are relatively easy to implement, instructors should have reasonable educational justification for deciding whether to adjust grades or which method to use
Editorial: Machine Learning Advancements in Pharmacology: Transforming Drug Discovery and Healthcare
Full text linkIn recent years, the integration of machine learning (ML) into pharmacology has revolutionized how we approach drug discovery, disease modeling, and therapeutic development. By leveraging vast datasets and computational power, ML has enabled researchers to uncover patterns, predict outcomes, and accelerate drug development processes that were previously unimaginable. This Research Topic on \u27Machine Learning Advancements in Pharmacology\u27 features five impactful studies that highlight the diverse applications and potential of ML in this field. These contributions, encompassing original research and a systematic review, exemplify the transformative role of ML in addressing some of the most pressing challenges in pharmacology