The Impact of AI in Physics Education: A Comprehensive Review from GCSE to University Levels

With the rapid evolution of Artificial Intelligence (AI), its potential implications for higher education have become a focal point of interest. This study delves into the capabilities of AI in Physics Education and offers actionable AI policy recommendations. Using a Large Language Model (LLM), we assessed its ability to answer 1337 Physics exam questions spanning GCSE, A-Level, and Introductory University curricula. We employed various AI prompting techniques: Zero Shot, In Context Learning, and Confirmatory Checking, which merges Chain of Thought reasoning with Reflection. The AI's proficiency varied across academic levels: it scored an average of 83.4% on GCSE, 63.8% on A-Level, and 37.4% on university-level questions, with an overall average of 59.9% using the most effective prompting technique. In a separate test, the LLM's accuracy on 5000 mathematical operations was found to decrease as the number of digits increased. Furthermore, when evaluated as a marking tool, the LLM's concordance with human markers averaged at 50.8%, with notable inaccuracies in marking straightforward questions, like multiple-choice. Given these results, our recommendations underscore caution: while current LLMs can consistently perform well on Physics questions at earlier educational stages, their efficacy diminishes with advanced content and complex calculations. LLM outputs often showcase novel methods not in the syllabus, excessive verbosity, and miscalculations in basic arithmetic. This suggests that at university, there's no substantial threat from LLMs for non-invigilated Physics questions. However, given the LLMs' considerable proficiency in writing Physics essays and coding abilities, non-invigilated examinations of these skills in Physics are highly vulnerable to automated completion by LLMs. This vulnerability also extends to Physics questions pitched at lower academic levels.Comment: 22 pages, 10 Figures, 2 Table

The impact of AI in physics education: a comprehensive review from GCSE to university levels

With the rapid evolution of artificial intelligence (AI), its potential implications for higher education have become a focal point of interest. This study delves into the capabilities of AI in physics education and offers actionable AI policy recommendations. Using openAI’s flagship gpt-3.5-turbo large language model (LLM), we assessed its ability to answer 1337 physics exam questions spanning general certificate of secondary education (GCSE), A-Level, and introductory university curricula. We employed various AI prompting techniques: Zero Shot, in context learning, and confirmatory checking, which merges chain of thought reasoning with reflection. The proficiency of gpt-3.5-turbo varied across academic levels: it scored an average of 83.4% on GCSE, 63.8% on A-Level, and 37.4% on university-level questions, with an overall average of 59.9% using the most effective prompting technique. In a separate test, the LLM’s accuracy on 5000 mathematical operations was found to be 45.2%. When evaluated as a marking tool, the LLM’s concordance with human markers averaged at 50.8%, with notable inaccuracies in marking straightforward questions, like multiple-choice. Given these results, our recommendations underscore caution: while current LLMs can consistently perform well on physics questions at earlier educational stages, their efficacy diminishes with advanced content and complex calculations. LLM outputs often showcase novel methods not in the syllabus, excessive verbosity, and miscalculations in basic arithmetic. This suggests that at university, there’s no substantial threat from LLMs for non-invigilated physics questions. However, given the LLMs’ considerable proficiency in writing physics essays and coding abilities, non-invigilated examinations of these skills in physics are highly vulnerable to automated completion by LLMs. This vulnerability also extends to pysics questions pitched at lower academic levels. It is thus recommended that educators be transparent about LLM capabilities with their students, while emphasizing caution against overreliance on their output due to its tendency to sound plausible but be incorrect

Strongholds of Ostrea edulis populations in estuaries in Essex, SE England and their association with traditional oyster aquaculture: evidence to support a MPA designation

The flat oyster Ostrea edulis has declined significantly in European waters since the 1850s as a result of anthropogenic activity. Ostrea edulis was designated a UK Biodiversity Action Plan Species and Habitat in 1995, and as a Feature of Conservation Importance (FOCI) within the UK Marine & Coastal Access Act 2009. To promote the recovery of oyster beds, a greater understanding of its abundance and distribution is required. Distribution of O. edulis across the proposed Blackwater, Crouch, Roach and Colne MCZ in Essex was determined between 2008 and 2012. Ostrea edulis were present in four estuary zones; with highest sample abundance in the Blackwater and Ray Sand zones. Size structure of populations varied, with the Ray Sand and Colne zones showing a significant lack of individuals with shell height <39 mm. Ostrea edulis occurred in highest number on shell substratum, followed by silty sediments. There were no significant associations between O. edulis abundance or size structure with water column Chl a, suspended solids, oxygen, nitrate or ammonium concentrations, temperature or pH. Highest abundance and most equitable population shell-size distribution for O. edulis were located within, or adjacent to, actively managed aquaculture zones. This suggests that traditional seabed management contributed to the maintenance or recovery of the species of conservation concern. Demonstration that the Essex estuaries were a stronghold for Ostrea edulis in the southern North sea area led to the designation of the Blackwater, Crouch, Roach and Colne estuaries Marine Conservation Zone in 2013

Socioeconomic inequalities in childhood-to-adulthood BMI tracking in three British birth cohorts

Background: Body mass index (BMI) tracks from childhood to adulthood, but the extent to which this relationship varies across the distribution and according to socio-economic position (SEP) is unknown. We aimed to address this using data from three British cohort studies. Methods: We used data from: 1946 National Survey of Health and Development (NSHD, n=2,470); 1958 National Child Development Study (NCDS, n=7,747); 1970 British Cohort Study (BCS, n=5,323). BMI tracking between 11 and 42 years was estimated using quantile regression, with estimates reflecting correlation coefficients. SEP disparities in tracking were investigated using a derived SEP variable based on parental education reported in childhood. This SEP variable was then interacted with the 11-year BMI z-score. Results: In each cohort and sex, tracking was stronger at the upper end of the distribution of BMI at 42 years. For example, for men in the 1946 NSHD, the tracking estimate at the 10th quantile was 0.31 (0.20, 0.41), increasing to 0.71 (0.61, 0.82) at the 90th quantile. We observed no strong evidence of SEP inequalities in tracking in men in the 1946 and 1958 cohorts. In the 1970 cohort, however, we observed tentative evidence of stronger tracking in low SEP groups, particularly in women and at the higher end of the BMI distribution. For example, women in the 1970 cohort from low SEP backgrounds had tracking coefficients at the 50th, 70th, and 90th quantiles which were 0.05 (-0.04; 0.15), 0.19 (0.06; 0.31), and 0.22 (0.02; 0.43) units higher, respectively, than children from high SEP groups. Conclusion: Tracking was consistently stronger at the higher quantiles of the BMI distribution. We observed suggestive evidence for a pattern of greater BMI tracking in lower (compared to higher) SEP groups in the more recently born cohort, particularly in women and at the higher end of the BMI distribution

Surplus to the city: Austerity urbanism, displacement and ‘letting die’

From SAGE Publishing via Jisc Publications RouterHistory: epub 2021-06-18Publication status: PublishedFunder: University of Leeds and ESRCFunder: Feminist Review Trust; FundRef: https://doi.org/10.13039/100012055Urban scholars have traditionally associated displacement in cities of the global North with gentrification, generally understood as a class-based process of neighbourhood change. This article expands this scalar focus and adopts the larger scale of the local authority district (in this case the London borough) as its epistemological starting point to study the displacement of homeless people by the local state. Participatory action research was undertaken with housing campaigners in the East London borough of Newham to explore who is being displaced, their experiences of displacement and the impacts of displacement on their lives. Empirically, the article argues that displacement in this case is a product of national welfare state restructuring – or ‘austerity urbanism’ – implemented through a localised regime of ‘welfare chauvinism’ in which some groups are framed as economically unproductive and therefore undeserving of access to social housing. Displacement has the effect of reinforcing the surplus status of these groups by separating them from employment, education and care networks and eroding their physical and mental health. The article draws on research on the biopolitics of surplus populations in the global South to develop an original theorisation of the relationship between welfare state restructuring and displacement. This theorisation reveals that displacement is the spatial expression of a biopolitical shift away from the logic of ‘making live’ associated with the post-war welfare state towards a logic of ‘letting die’ more traditionally associated with postcolonial contexts

Utility of the new Movement Disorder Society clinical diagnostic criteria for Parkinson's disease applied retrospectively in a large cohort study of recent onset cases

Objective: To examine the utility of the new Movement Disorder Society (MDS) diagnostic criteria in a large cohort of Parkinson's disease (PD) patients. Methods: Recently diagnosed (&lt;3.5 years) PD cases fulfilling United Kingdom (UK) brain bank criteria in Tracking Parkinson's, a UK multicenter prospective natural history study were assessed by retrospective application of the MDS criteria. Results: In 2000 cases, 1835 (91.7%) met MDS criteria for PD, either clinically established (n = 1261, 63.1%) or clinically probable (n = 574, 28.7%), leaving 165 (8.3%) not fulfilling criteria. Clinically established cases were significantly more likely to have limb rest tremor (89.3%), a good l-dopa response (79.5%), and olfactory loss (71.1%), than clinically probable cases (60.6%, 44.4%, and 34.5% respectively), but differences between probable PD and ‘not PD’ cases were less evident. In cases not fulfilling criteria, the mean MDS UPDRS3 score (25.1, SD 13.2) was significantly higher than in probable PD (22.3, SD 12.7, p = 0.016) but not established PD (22.9, SD 12.0, p = 0.066). The l-dopa equivalent daily dose of 341 mg (SD 261) in non-PD cases was significantly higher than in probable PD (250 mg, SD 214, p &lt; 0.001) and established PD (308 mg, SD 199, p = 0.025). After 30 months' follow-up, 89.5% of clinically established cases at baseline remained as PD (established/probable), and 86.9% of those categorized as clinically probable at baseline remained as PD (established/probable). Cases not fulfilling PD criteria had more severe parkinsonism, in particular relating to postural instability, gait problems, and cognitive impairment. Conclusion: Over 90% of cases clinically diagnosed as early PD fulfilled the MDS criteria for PD. Those not fulfilling criteria may have an atypical parkinsonian disorder or secondary parkinsonism that is not correctly identified by the UK Brain Bank criteria, but possibly by the new criteria

The Rogue Alpha and Beta Mission: Operations, Infrared Remote Sensing, LEO Data Processing, and Lessons Learned From Three Years on Orbit With Two Laser Communication-Equipped 3U CubeSats

The Aerospace Corporation\u27s Rogue-alpha, beta program was a rapid prototyping demonstration aimed at building and deploying an infrared remote sensing capability into low Earth orbit within 18 months. The two satellites and their data were then used for three years as an experimental testbed for future proliferated low Earth orbit (pLEO) constellations. Their launch took place on November 2, 2019, followed by boost and deployment of two identical spacecraft (Rogue-alpha and beta) by the Cygnus ISS cargo vessel into circular 460-km, 52° inclined orbits on January31, 2020. The primary sensors were 1.4-micron band, InGaAs short wavelength infrared (SWIR) cameras with640x512 pixels and a 28° field-of-view. The IR sensors were accompanied by 10-megapixel visible context cameras with a 37° field-of-view. Star sensors were also tested as nighttime imaging sensors. Three years of spacecraft and sensor operations were achieved, allowing a variety of experiments to be conducted. The first year focused on alignment and checkout of the laser communication systems, sensor calibration, and priority IR remote sensing objectives, including the study of Earth backgrounds, observation of natural gas flares, and detection of rocket launches. The second year of operations added study of environmental remote sensing targets, including severe storms, wildfires, and volcanic eruptions, while continuing to gather Earth backgrounds and rocket launch observations. The final year emphasized advanced data processing and exploitation techniques applied to collected data, using machine learning and artificial intelligence for tasks such as target tracking, frame co-registration, and stereo data exploitation. Mission operations continued in the final year, with an emphasis on collecting additional rocket launch data, and higher frame rate backgrounds data. This report summarizes the Rogue alpha, beta mission’s outcomes and presents processed IR data, including the detection and tracking of rocket launches with dynamic Earth backgrounds, embedded moving targets in background scenes, and the use of pointing-based registration to create fire line videos of severe wildfires and 3D scenes of pyrocumulonimbus clouds. Lessons learned from the experimental ConOps, data exploitation, and database curation are also summarized for application to future pLEO constellation missions

A randomized controlled trial of assisted intention monitoring for the rehabilitation of executive impairments following acquired brain injury

Background. Acquired brain injury (ABI) can impair executive function, impeding planning and attainment of intentions. Research shows promise for some goal-management rehabilitation interventions. However, evidence that alerts assist monitoring and completion of day-to-day intentions is limited. Objective. To examine the efficacy of brief goal-directed rehabilitation paired with periodic SMS text messages designed to enhance executive monitoring of intentions (assisted intention monitoring [AIM]). Methods. A randomized, double-blind, controlled trial was conducted. Following a baseline phase, 74 people with ABI and executive problems were randomized to receive AIM or control (information and games) for 3 weeks (phase 1) before crossing over to either AIM or no intervention (phase 2). The primary outcome was change in composite score of proportion of daily intentions achieved. A total of 59 people (71% male; 46% traumatic brain injury) completed all study phases. Results. Per protocol crossover analysis found a significant benefit of AIM for all intentions [F(1, 56) = 4.28; P = .04; f = 0.28; 3.7% mean difference; 95% CI = 0.1%-7.4%] and all intentions excluding a proxy prospective memory task [F(1, 55) = 4.79; P = .033; f = 0.28, medium effect size; 3% mean difference; 95% CI = 0.3%-5.6%] in the absence of significant changes on tests of executive functioning. Intention-to-treat analyses, comparing AIM against control at the end of phase 1 revealed no statistically significant differences in the attainment of intentions. Conclusion. Combining brief executive rehabilitation with alerts may be effective for some in improving achievement of daily intentions, but further evaluation of clinical effectiveness and mechanisms is required