14234 research outputs found
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Muenks, LaCosse, Green, Garcia, Canning, Zirkel, & Murphy (2020; Study 1)
No full textA CREP replication of Study 1 from Muenks et al (2020) "Does my professor think my ability can change? Students' perceptions of their STEM professors' mindset beliefs predict their psychology vulnerability, engagement, and performance in class
Investigating how users interact with guidance during visual data analysis
No full textWhile Artificial Intelligence (AI) has been talked about for the last couple of decades, only now AI algorithms have achieved good performance levels on some tasks. On other tasks, humans enjoy supremacy including their ability to learn from human experts, to learn from other users, and consider contextual information.
One common task analysts perform is creating dashboards of charts that succinctly convey information and insights to the recipient. To perform such a task, an analyst sifts through a large set of attributes in a dataset, analyzes attribute-relevance for the task, uses own judgment, applies creativity in both selection of attributes and in displaying information and insights in charts. The whole task is often complex.
In this user study, participants will explore a dataset of attributes (e.g., one derived from online customer behaviors) and design multiple charts (e.g., those indicating meaningful drivers of dollar ($) sales revenue for a company).
Participants will be assigned to one of five following study conditions, each condition receiving a different kind of guidance than the other. We want to study how users interact with guidance received from these different sources.
1. Condition 1 (Human Expert Analyst): guidance is presented as if it comes from a human expert analyst who is well regarded in industry for acumen in data analysis.
2. Condition 2 (AI Model): guidance is presented as if it comes from an AI model trained on large information for data analysis tasks.
3. Condition 3 (Group of Data Analysts): guidance is presented as if it comes from a group of analysts in your organization well versed in data analysis.
4. Condition 4 (Generic Guidance): guidance is presented but without an explicit mention of a source.
5. Condition 5 (No Guidance, Baseline): there is no guidance presented in the interface
The longitudinal effects of material security on belief in God in young Americans
No full textThe prevalence of religious beliefs and practices is puzzling from the evolutionary viewpoint, but previous research suggested that religious traditions provide cooperative benefits and improve well-being. Seemingly in contrast with this claim are worldwide secularization trends where people disaffiliate from religions and belief in god(s). Theoreticians suggested that diminished pressures on cooperation and well-being no longer motivate individuals to seek religious benefits and pay the participation costs. We investigate this causal claim using the National Study of Youth and Religion dataset, which tracks the development of religiosity among US Christians from adolescence to young adulthood (n = 3 370). Using a general lagged panel methodology, we found that material security in Wave 1 (early adolescence) predicts higher probability of decrease in belief in God in Wave 4 (young adulthood). This result provides support for the hypothesis that participation in religious traditions is associated with living in an insecure socio-ecology, where the systems may still confer benefits onto their members. We conclude with a call for further research using more nuanced measures and larger sample sizes that may provide further insights into the potentially adaptive nature of cultural systems
'Getting Active' & 'Staying Active' with Medito: Creation of a digital mindfulness-based intervention supporting physical activity engagement
No full textThis repository includes materials used in/resulting from the co-creation of packs 'Getting Active' and 'Staying Active' in the Medito mobile app. The process was a collaboration between a research team at the University of Bath, led by Dr Masha Remskar, and the Medito Foundation, who own the resulting materials and host the intervention in their mobile app, Medito
Comment on Stallinga, P. (2023), Residence Time vs. Adjustment Time of Carbon Dioxide in the Atmosphere
No full textThe goal of Stallinga (2023), to address confusion about CO2 "residence time" and "adjustment time," is laudable. Unfortunately, the author, himself, has confused them. Dr. Stallinga made two key errors, the second following from the first. His first and most important mistake was his claim that, "the adjustment time is never larger than the residence time." That is backward. It is easily shown that the adjustment time is much longer than the residence time, because some of the processes which reduce the residence time do not reduce the adjustment time. He also wrote that neither the residence time nor the adjustment time is "longer than about 5 years." That is correct only for the residence time. It is wrong by a full order of magnitude for the adjustment time. The adjustment time can be determined from measurements, and it is approximately fifty years
Public communication about science in 68 countries: Global evidence on how people encounter and engage with information about science
No full textThis 68-country survey (n = 71,922) examines science information diets and communication behavior, identifies cross-country differences, and tests how economic and sociopolitical conditions predict such differences. We find that social media are the most used sources of science information in most countries, except those with democratic-corporatist media systems where news media tend to be used more widely. People in collectivist societies are less outspoken about science in daily life, whereas lower education is associated with higher outspokenness. Limited access to digital media is correlated with participation in public protests on science matters. We discuss implications for future research, policy, and practice
Exploring current and future AI use cases in the gambling industry: A focus group approach
No full textInvestigation into the current and future applications of AI in the gaming industry, along with their associated ethical consideration