With the creation of the first drug court in Miami-Dade County, Florida in 1989, problem-solving courts emerged as an innovative effort to close the revolving door of recidivism. Designed to target the social and psychological problems underlying certain types of criminal behavior, the problem-solving model boasts a community-based, therapeutic approach. As a result of the anecdotal successes of early drug courts, states expanded the problem-solving court model by developing specialized courts or court dockets to address a number of social problems. Although the number and types of problem-solving courts has been expanding, the formal research and statistical information regarding the operations and models of these programs has not grown at the same rate. Multiple organizations have started mapping the variety of problem-solving courts in the county; however, a national catalogue of problem-solving court infrastructure is lacking. As evidence of this, different counts of problem-solving courts have been offered by different groups, and a likely part of the discrepancy lies in disagreements about how to define and identify a problem-solving court. What is known about problem-solving courts is therefore limited to evaluation or outcome analyses of specific court programs. In 2010, the Bureau of Justice Statistics awarded the National Center for State Courts a grant to develop accurate and reliable national statistics regarding problem-solving court operations, staffing, and participant characteristics. The NCSC, with assistance from the National Drug Court Institute (NDCI), produced the resulting Census of Problem-Solving Courts which captures information on over 3,000 problem-solving courts that were operational in 2012.

In 2020, nearly 92 percent of Poles stated that their doctor helped them solve their problem during an online video consultation.

PIAAC12 - Literacy/Numeracy and Adaptive Problem Solving mean score and levels. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Literacy/Numeracy and Adaptive Problem Solving mean score and levels...

This statistic demonstrates the share of service professionals worldwide who say their organization's agents can easily solve issues with information from back-end systems in 2018, by type. During the survey, 70 percent of service decision makers said that their organization's agents can solve problems more easily with information from back-end systems.

Factor loadings of Diversity of assessment problem format.

This dataset contains the supplementary materials to our publication "Collaborative Problem Solving in Mixed Reality: A Study on Visual Graph Analysis", where we report on a study we conducted. Please refer to publication for more details, also the abstract can be found at the end of this description. The dataset contains: The collection of graphs with layout used in the study The final, randomized experiment files used in the study The source code of the study prototype The collected, anonymized data in tabular form The code for the statistical analysis The Supplemental Materials PDF Paper abstract: Problem solving is a composite cognitive process, invoking a number of systems and subsystems, such as perception and memory. Individuals may form collectives to solve a given problem together, in collaboration, especially when complexity is thought to be high. To determine if and when collaborative problem solving is desired, we must quantify collaboration first. For this, we investigate the practical virtue of collaborative problem solving. Using visual graph analysis, we perform a study with 72 participants in two countries and three languages. We compare ad hoc pairs to individuals and nominal pairs, solving two different tasks on graphs in visuospatial mixed reality. The average collaborating pair does not outdo its nominal counterpart, but it does have a significant trade-off against the individual: an ad hoc pair uses 1.46 more time to achieve 4.6 higher accuracy. We also use the concept of task instance complexity to quantify differences in complexity. As task instance complexity increases, these differences largely scale, though with two notable exceptions. With this study we show the importance of using nominal groups as benchmark in collaborative virtual environments research. We conclude that a mixed reality environment does not automatically imply superior collaboration.

In 2024, problem-solving emerged as the most sought-after soft skill among IT professionals worldwide, with 21 percent of respondents indicating they were actively developing this ability. Effective communication followed at 14 percent, while relationship building ranked third at 11 percent of IT professionals focusing on its development. Interestingly, analytical thinking, often associated with technical roles, was being pursued by only five percent of professionals. Skills such as active listening, teamwork, and public presentation each accounted for around two percent of learning focus, suggesting a diverse range of interpersonal abilities being cultivated in the IT sector.

PIAAC01 - Literacy/Numeracy and Adaptive Problem Solving Skills mean score. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Literacy/Numeracy and Adaptive Problem Solving Skills mean score...

PIAAC10 - Literacy/Numeracy and Adaptive Problem Solving mean score and levels. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Literacy/Numeracy and Adaptive Problem Solving mean score and levels...

As of March 2024, OpenAI o1 was the large language model (LLM) tool that had the best benchmark score in solving math problems, with a score of 94.8 percent. Close behind, in second place, was OpenAI o1-mini, followed by GPT-4o.

This brief research report presents an experiment investigating how people interpret quantities displayed in pictorial charts. Pictorial charts are a popular form of data visualization in media. They represent different quantities with differently scaled pictures. In the present study, 63 university students answered a 12-item questionnaire containing three different pictorial charts. The study aimed to evaluate how individuals perceive the quantities in the pictorial charts intuitively. Therefore, the students’ answers were not rated as correct or incorrect. Instead, it was analyzed which functional relationship between scale factor and estimated quantity best described people’s interpretation of pictorial charts. The experiment showed that, on average, a model assuming a quadratic relationship fitted best. This result deviates from research that found an overgeneralization of linearity when students compare the areas of two mathematically similar shapes. It may be that the routines for the interpretation of pictures differ considerably depending on whether a person must calculate a quantity arithmetically or is prompted to estimate the quantity based on visual perception.

Factor loadings of Perceived usefulness of assessment.

Problem-solving in a technology-rich environment (PS-TRE), distribution of PS-TRE non-respondents and proficiency levels by sex, age group, population aged 16 to 65, Canada, provinces and territories

According to a February and March 2023 survey, most people in Czechia found AI problem-solving capabilities suitable for the IT sector. This share amounted to 69 percent. Telecommunications and administration sectors followed with 65 and 53 percent of the respondents, respectively.

In 2021, 38 percent of respondents indicate prototyping a new idea or product with no-code tools. No-code helps both technical and non-technical users automate processes. Instead of using traditional computer programming, graphical user interfaces are used to perform tasks.

During a survey among chief executive officers (CEOs) in the United States concluded in October 2023, respondents were asked to select the five problems they wanted marketing to help them solve. Over half (or 52 percent) of the interviewees mentioned creating new customers, retaining existing ones, and driving revenue growth. Driving sales and growing market shares and staying ahead, differentiating, and growing faster than their competition followed, mentioned by 45 and 44 percent of respondents, respectively.

During a global 2023 survey, 28 percent of responding professionals from among brands, agencies, publishers, technology and data platforms said they expected third-party cookie replacement solutions to solve targeting and retargeting problems. Second most popular use case that the respondents envisaged was data onboarding.

This data set contains the data used for statistical analyses during puzzle box problem-solving experiments in the titled “Learning and innovation in urban yellow mongoose (Cynictis penicillata).” A description of the variables is included under the "General_Information" sheet in the document.

MATH is a new dataset of 12,500 challenging competition mathematics problems. Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations and explanations.

According to a 2023 survey on artificial intelligence (AI) safety, 46 percent out of all respondents of the survey in Australia thought that AI solves more problems than it creates. Out of this respondent group, 28 percent indicated that AI was for the betterment of the society. Another 18 percent thought that AI was beneficial if used correctly.