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Evaluating the impact of prompting styles on LLM accuracy for AIME math questions

Ganesa et al. | Jul 26, 2026

Evaluating the impact of prompting styles on LLM accuracy for AIME math questions

Large language models are increasingly used to solve math problems, but their ability to handle multi-step reasoning remains uncertain. In this study, students tested whether different prompting styles could improve LLM accuracy on challenging AIME math questions and found that detailed step-by-step solutions did not significantly outperform simpler prompts. These results suggest that improving LLM mathematical reasoning may require deeper model-level advances rather than changes in prompting style alone.

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Implication of education levels on gender wage gap across states in the United States and Puerto Rico

Dash et al. | Apr 16, 2025

Implication of education levels on gender wage gap across states in the United States and Puerto Rico

Here the authors examined the relationship between education levels and the gender wage gap (GWG) in the US and Puerto Rico from 2010 to 2022, hypothesizing that higher education would correlate with a lower GWG. Their analysis of income data revealed an inverse correlation, where higher education levels were associated with reduced gender wage disparities, suggesting that policies aimed at closing the gender gap in higher education could promote socioeconomic equality.

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Early detection of student burnout using data science: a study of behavioral and psychological indicators

Baber et al. | Jul 13, 2026

Early detection of student burnout using data science: a study of behavioral and psychological indicators

This study examined behavioral and psychological predictors of burnout among high school and university students in Pakistan using survey data and machine-learning models. Shorter sleep and greater mental fatigue—especially fatigue—were associated with higher burnout risk, while a Random Forest model successfully identified students at risk of burnout.

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Comparison of three large language models as middle school math tutoring assistants

Ramanathan et al. | May 02, 2024

Comparison of three large language models as middle school math tutoring assistants
Image credit: Thirdman

Middle school math forms the basis for advanced mathematical courses leading up to the university level. Large language models (LLMs) have the potential to power next-generation educational technologies, acting as digital tutors to students. The main objective of this study was to determine whether LLMs like ChatGPT, Bard, and Llama 2 can serve as reliable middle school math tutoring assistants on three tutoring tasks: hint generation, comprehensive solution, and exercise creation.

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The impact of COVID-19 quarantine on physical activities in Basra, Iraq: A cross-sectional study

Al Saeedi et al. | Aug 30, 2022

The impact of COVID-19 quarantine on physical activities in Basra, Iraq: A cross-sectional study

As the COVID-19 pandemic continues, the authors noticed a change in the physical activity of many people, as well as a change in the type of physical activity they practice. Here, the authors used a cross-sectional survey of 150 participants from the province of Basra in Iraq. They found an overall decrease in the number of days of physical activity for participants along with an increasing proportion of at-home exercises compared to other activities that are performed inside sports clubs during the pandemic.

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Giving Teens a Voice: Sources of Stress for High School Students

Corson et al. | Sep 09, 2019

Giving Teens a Voice: Sources of Stress for High School Students

The authors investigate the negative effects stress has on teen mental and physical health. Through a survey, they give Virginia teens a voice in revising the Health and Physical Education curriculum to include a standards of learning (SOL). Notably they identify factors contributing to stress levels including homework level, amount of free and sleep time, parental pressure and family encouragement.

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Exploring Political Discourse Among High School Journalists with Web Scraping and AI Technology

Gong et al. | Jun 10, 2025

Exploring Political Discourse Among High School Journalists with Web Scraping and AI Technology

Here the authors provided greater coverage of adolescent stances by investigating the political perspectives and trends of high school journalists, utilizing web scraping methods and artificial intelligence (ChatGPT-4o) to analyze over 153,000 articles. They found that high school publications exhibit lower levels of political polarization compared to mainstream media and that journalists' views, while tending to lean moderately liberal, showed no significant correlation with local voting patterns.

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A comparative study of dynamic scoring formulas for capture-the-flag competitions

Ho et al. | Aug 30, 2024

A comparative study of dynamic scoring formulas for capture-the-flag competitions

The use of gamification in cybersecurity education, particularly through capture-the-flag competitions, involves scoring challenges based on their difficulty and the number of teams that solve them. The study investigated how changing the scoring formulas affects competition outcomes, predicting that different formulas would alter score distributions.

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