The Evergreen State College

Large Language Models (LLMs) have been used to aide student learning across a multitude of domains such as computer science, data science, and mathematics. While these chatbots show promise, they may not perform well when quality student data is unavailable. Hint generation for cybersecurity can be feasible with the technology we have today if we make the right simplifications. First, we need human-in-the-loop systems because the training data used to train general LLMs may not cover cybersecurity well. Second, using modular agents allows us to access dynamic data that are outside the training dataset and add specificity to the hints. In this paper, we leverage n8n, an agent deployment service, to establish the connections between our agents and Discord, the messaging system that our classroom uses to offer students a streamlined learning experience when working on interactive cybersecurity exercises. The system has undergone initial pilot testing, Hints provided were sufficient to propel students forward and make progress on their assigned work, in most cases.

Ecological studies of many pelagic, deep-sea animals are often limited due to their remote habitats and sampling constraints. In the eastern tropical Pacific, numerous studies have been published about the distribution of demersal fishes across the region, yet studies for midwater taxa are lacking. Here, we utilized visual survey transects from an area targeted for polymetallic nodule mining to examine the drivers behind the distribution of two mesopelagic predators, snipe eels (family Nemichthyidae) and sawtooth eels (family Serrivomeridae). Additionally, we compared the vertical distributions of their prey and examined whether the two eels displayed different behaviors in situ. Time of day was not a statistically significant driver of eel distribution, although the shallowest observations were during the night, indicating that some in the populations of Nemichthyidae and Serrivomeridae had migrated weakly to the upper 200 m. Eel distributions were found to be affected by both depth and dissolved oxygen, with Nemichthyidae observed in shallower and lower oxygenated waters and Serrivomeridae in deeper and more oxygenated ones. Two prey taxa (families Euphausiidae and Sergestidae) were abundant at shallower transect depths, which likely drives the distribution of Nemichthyidae, as pelagic crustaceans constitute their primary prey. In terms of behavior, Serrivomeridae were more active and were oriented primarily vertically, suggesting that Nemichthyidae may be less active or under lower predation pressure due to the hypoxic environment in which they occur. This work highlights the importance of visual surveys in obtaining in situ data as a complement to traditional sampling methods, particularly for collecting data on poorly understood animals.

In a rapidly changing environment, predicting changes in the growth and survival of local populations can inform conservation and management. Plastic responses vary as a result of genetic differentiation within and among species, so accurate rangewide predictions require characterization of genotype-specific reaction norms across the continuum of historic and future climate conditions comprising a species’ range. Natural hybrid zones can give rise to novel recombinant genotypes associated with high phenotypic variability, further increasing the variance of plastic responses within the ranges of the hybridizing species. Experiments that plant replicated genotypes across a range of environments can characterize genotype-specific reaction norms; identify genetic, geographic, and climatic factors affecting variation in climate responses; and make predictions of climate responses across complex genetic and geographic landscapes. The North American hybrid zone of Populus trichocarpa and P. balsamifera represents a natural system in which reaction norms are likely to vary with underlying genetic variation that has been shaped by climate, geography, and introgression. Here, we leverage a dataset containing 45 clonal genotypes of varying ancestry from this natural hybrid zone, planted across 17 replicated common garden experiments spanning a broad climatic range, including sites warmer than the natural species ranges. Growth and mortality were measured over two years, enabling us to model reaction norms for each genotype across these tested environments. Genomic variation associated with species ancestry and northern/southern regions significantly influenced growth across environments, with genotypic variation in reaction norms reflecting a trade-off between cold tolerance and growth. Using modeled reaction norms for each genotype, we predicted that genotypes with more P. trichocarpa ancestry may gain an advantage under warmer climates. Spatial shifts of the hybrid zone could facilitate the spread of beneficial alleles into novel climates. These results highlight that genotypic variation in responses to temperature will have landscape-level effects.

Die hier vorgestellte Aufgabe soll eine Einführung in grundlegende Berechnungen zu Elementarzellen und Kernspaltungsprozessen geben. Inspiration dazu stiftet die Architektur und Bedeutungsebene des Atomiums.

Social computing scholars have long known that people do not interact with knowledge in straightforward ways, especially in digital environments. While policies around knowledge are essential for targeting misinformation, they are value-laden; in choosing how to present information, we undermine non-traditional, often non-Western, ways of knowing. Epistemic injustice is the systemic exclusion of certain people and methods from the knowledge canon. Epistemic injustice chips away at one's testimony and vocabulary until they are stripped of their due right to know and understand. In this paper, we articulate how epistemic injustice in sociotechnical applications leads to material harm. Inspired by a hybrid collaborative autoethnography of 14 CSCW practitioners, we present three cases of epistemic injustice in sociotechnical applications: online transgender healthcare, identity sensemaking on r/bisexual, and Indigenous ways of knowing on r/AskHistorians. We further explore signature tensions across our autoethnographic materials and relate them to previous CSCW research areas and personal non-technological experiences. We argue that epistemic injustice can serve as a unifying and intersectional lens for CSCW research by surfacing dimensions of epistemic community and power. Finally, we present a call to action of three changes the CSCW community should make to move toward its own goals of research justice. We call for CSCW researchers to center individual experiences, bolster communities, and remediate issues of epistemic power as a means towards epistemic justice. In sum, we recount, synthesize, and propose solutions for the various forms of epistemic injustice that CSCW sites of study---including CSCW itself---propagate.

Forest restoration thinning may accelerate the development of structural complexity toward old-growth conditions faster than a natural forest, yet associated changes in forest carbon (C) are poorly understood. Old-growth forests are characterized by high levels of sequestered C in aboveground biomass and soil C pools, yet active management has well-recognized negative impacts on stored C. Effects of forest restoration thinning on forest C can be determined using longitudinal measurements and modeling based on stand conditions and tree growth. At Ellsworth Creek Preserve in Southwest Washington, forest restoration efforts in a second-growth temperate rainforest have been monitored using permanent plots since 2007. Here, we compare repeat measurements from 2020, modeled forest C, and measurements of O-horizon C pools from 2022 to determine C impacts of silvicultural treatments for old-growth restoration. We found good general agreement between empirical measurements and models of forest C using the Forest Vegetation Simulator (FVS). However, treatment alone was not a strong indicator for C conditions; rather, forest age and age–treatment interactions better predicted soil C responses to restoration treatments. These data may indicate that “light” forest restoration thinning can accelerate old-growth development with minimal effects on soil carbon—a win-win conservation strategy for old-growth forests and the climate.

Abstract Stream‐associated amphibians are sensitive bioindicators in headwater streams across the Pacific Northwest moist coniferous forests of North America. Much of this landscape is intensively managed for timber. Forest Practice (FP) rules determine harvest prescriptions on most private lands in Washington State and cover over 3.7 million hectares. Under these rules, non‐fish‐bearing headwater streams receive buffers on at least 50% of the stream length, including FP Sensitive Sites that receive 15–17 m radius no‐cut patch buffers. We evaluated how torrent (Rhyacotriton spp.) and giant (Dicamptodon spp.) salamander relative abundance is influenced by headwater stream network features that correspond to FP Sensitive Sites. In particular, we examined how salamander relative abundance in the two most common FP Sensitive Sites, tributary junctions (TJs) and perennial initiation points (PIPs), compared to densities in non‐Sensitive Site stream reaches, hereafter branches. We also evaluated salamander relative abundance and two hydrologic characteristics, dry channel and seeps. We analysed data collected in 2006 and 2007 from 17 amphibian‐occupied, non‐fish‐bearing basins in Western Washington with managed forest ages 30–80. We found no relationship between torrent salamander relative abundance and PIPs and TJs or between giant salamander relative abundance and TJs compared to branches. Consistent with expectations, giant salamander relative abundance was less in PIPs than in TJs and branches, and less in first‐order than second‐ and third‐order streams. Conversely, torrent salamander relative abundance lacked a clear relationship to stream order. Giant and torrent salamander relative abundance showed a negative relationship with the proportion of dry channels, but torrent salamanders were observed in short reaches of surface water located in predominantly dry channels. Importantly, reaches with seeps had 123% (CI: +103% to +146%) and 81% (CI: +49% to +121%) greater relative abundance of torrent and giant salamanders, respectively, than reaches without seeps. Practical implication: Current FP rules protect select side‐slope seeps as another category of Sensitive Sites but may too narrowly define the criteria of seeps to protect the full range of those being utilized by stream‐breeding salamanders. Studies focused on seeps and adjacent stream channel characteristics may better inform features important to stream‐breeding salamanders.

Abstract Hands-on exercises provide students with practical skills and abilities. However, for exercises to be effective, students may need timely feedback while they are engaged to prevent them from getting stuck or frustrated. The goal of this project is to use machine learning to help identify such students such that timely and contextually appropriate hints can be given. We are building a system that identifies students who are potentially in the most need of help, and suggests hints that the instructor could provide. The instructor can reject hints that they do not find appropriate. The hint system will be integrated into the EDURange cybersecurity education platform and will also be compatible with other platforms. We are collecting data that will be analyzed to determine the efficacy of the tool, and to develop new hints and strategies for helping students. This project plans to use our machine learning system to create, test, and deploy semi-automated hints in a timely manner.

We are implementing a pure IPv6 networking stack optimized to run on IoT endpoints connected to a network through an Ethernet interface. Our implementation supports only the minimal set of protocols required to enable efficient UDP-based communication. In particular, it does not include support for specialized operations such as multicasting, routing, load balancing, firewalling, network address translation, and tunneling. We are on track soon to release our network stack implementation.