Social Sciences – Page 31 – UROP Spring Symposium 2021

Social Sciences

Methods of Exploring the Effect of Verb Causativity on Reaction Time

Our research focuses on methods of studying how causativity of verbs affect our processing of them and therefore our reaction time, and how these reaction time effects can be isolated from other sentence processing effects like general lexical prediction. In a previous study conducted by Dr. Levinson, it was found that there is an added level of complexity in transitive variants of causative verbs as compared to transitive variants of non-causative, or activity, verbs. This was concluded by measuring reaction times in self-paced reading tasks of sentences with verbs of transitive and intransitive, as well as causative and non-causative variants. For example, a causative transitive verb appears in the sentence “The sun melted the ice”, whereas an example of a causative intransitive verb appears in the sentence “The ice melted”, which differs from an activity verb, such as “ate”. The complexity of causative verbs vs. non-causative verbs is something that has long been debated, and helps to better understand linguistic processing. Our research mainly focused on using different methods of studying this causativity phenomenon other than self-paced reading tasks, as well as determining the best methods for disentangling verb representations from lexical confounds.

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Impact of School Policy Change on School Enrollment: Evidence from Mozambique

Enrollment in primary and secondary education in Sub Saharan Africa has lagged behind much of the rest of the world. Amongst numerous potential reasons, the fees to attend school is often considered a prohibitive barrier in accessing public education. In 2018, the government of Mozambique introduced legislation abolishing the fees for school enrollment in grades corresponding to the school-ages of 6 to 12. Previously on average, the fee for primary school is 21,410 meticas ($354 USD) per child per year for grades 1 to 5 and Mt 60,013 ($992 USD) per child per year for grades 6 and 7. This study explores the efficacy of this policy change and its external validity with respect to education in Sub-Saharan Africa.

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Data is asset – Evaluating the market value of databases

The world is encountering a remarkable transformation to the digital economy. Uber, Alibaba, Airbnb…More and more large companies are having no real capital. What is the truly valuable things today for a company? It is data. Data affects a company’s valuation, from the simple question of revenue earned to different metrics that show a company’s ability. Valuation is, however, a tricky work to do today: most data are not transparent to the public, and factors are complex behind. The project aims to determine the exact factors behind company valuation, and how stock prices react to data changes.

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Effective ways of communicating research on language learning by children and adults

Media use has been a beneficial tool for education in schools, especially over the past year, and can expand the knowledge that can be known by any individual person. While it advances education in the school systems, it may also have some negative effects regarding how children adapt to language acquisition, especially those who are not native to English in the U.S. In this study, we observed 23 children from Spanish-speaking homes. We asked about both the children’s and their parents Spanish and English media use through a questionnaire asking them to report their time spent on certain categories of media. In addition, two animated videos aiming to teach English possessive nouns and verbs were shown to the students. They were tested on English vocabulary, through the Peabody Picture Vocabulary Test, Spanish vocabulary through the Spanish version, TVIP, and on English and Spanish grammar through morphosyntax tests. The results of this project reinforce that educational content is beneficial for children’s language development. However, the results also show that parent’s media use negatively impacted childrens English morphosyntax scores, as well as their English and Spanish vocabulary knowledge. For future research, it would be beneficial to understand which aspects of educational media benefit bilingual children’s ability to develop their non-native language. Additionally, it would be interesting to see the impacts of interactive educational media compared to passive animated media.

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Effective ways of communicating research on language learning by children and adults

Language can be taught in a variety of ways, but is there a specific way that helps young children benefit the most? The present study of English language learners was conducted in order to see if children’s acquisition of possessive and past tense in English could be facilitated by watching “passive” but targeted child-centric animations, and if a child’s first language plays a role in their second language acquisition. For this study, native Spanish- and Mandarin-speaking children were tested on their English vocabulary and grammar before and after being shown immersive language-learning animations where both implicit and explicit teaching methods were used. Although this study is still in progress we found that both the Spanish and Mandarin-speaking children were able to learn English vocabulary and grammar from the animations. One question that we now have is whether children who received the same exposure to the target learning material but in an interactive game would be better able to learn and whether their learning would be affected by the amount of media exposure children get in their day to day lives.

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Documentary Film Team

Documentaries are a way of telling stories in a visual form. Through learning about the process that goes into creating documentaries one can develop communication, research, and film-making skills as well as connect with others interested in film. In order to expand our knowledge of the documentary process, we were given tasks to explore the pre-production, production, and post-production aspects by looking at old documentaries, filming, editing, and reviewing video footage. As a result of our project, we plan to create a short documentary of our own with the combined knowledge we gained. Learning the process of documentary making allows one to discover and share stories that haven’t been explored.

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Using Machine Learning to Better Understand Environmental Policy Innovation

Climate change and environmental protection are perhaps the most important issues of our generation, and government policies and laws are key ways to address them. In order to better understand which countries are leaders in passing environmental protection laws, how they pass them, and what types of laws they pass, it is necessary to comb through databases of hundreds of thousands of laws, something impossible for humans to do. Therefore, it is necessary to use text analysis to more efficiently analyze laws. This project seeks to find the best method of computer text analysis to most accurately label and analyze laws and policies. In order to find the best method we are comparing the accuracy rates of a supervised transfer-learning model trained on laws we manually labeled in Atlas.ti, other more traditional machine-learning models we are building, and models used by others in similar literature. If we are able to construct a model with a high accuracy rate, it will make the analysis of law and policies much more efficient, which can help in a variety of research contexts. In our context, it would help us most accurately analyze how environmental policies have been passed worldwide.

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Data Gathering Data Analysis Toward Better Air Quality Outcomes in SW Detroit

In support of the ongoing initiatives by community advocates to cut diesel emissions in Southwest Detroit, this research aims to gauge the effects on air quality that commercial vehicles have in residential areas when using their streets as routes. SW Detroit has some of the highest levels of PM and toxic pollutants measured in Detroit, with Detroit having the worst air quality conditions in Michigan. This study accesses the ambient air quality in residential areas that have a high frequency of commercial trucks traveling their streets. We want to know how each passing truck contributes to the air pollution on the street it is using.

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A Review of People’s Perceptions of COVID-19 and Adherence to Public Health Policy

From early 2020 to 2021, the unprecedented outbreak of novel coronavirus (COVID-19) in Wuhan has evolved into a pandemic. As coronavirus impacted people’s daily life, public transportation and recreational facilities worldwide, countries implemented various public health guidelines to help their cities recover from the virus attack. To understand international differences and similarities in people’s thoughts about the novel coronavirus and associated public health guidelines, I conducted a literature review to examine: 1) people’s perceptions of the coronavirus; 2) people’s adherence to public health policies (e.g., face masks, social distancing, and hand hygiene); and 3) potential reasons for the differences (e.g., cultural beliefs). I reviewed research articles related to the effectiveness of general public health guidelines in major countries in North America, Europe and Asia (e.g., the U.S, U.K., and China respectively) and the opinions of residents regarding the current rules they need to follow. My findings indicate that even though residents in eastern and western nations share basic knowledge about the coronavirus, people from western countries still have some misconceptions about the coronavirus. If people are more optimistic, they are more willing to adhere to public health policies. Based on these findings, future research can focus on the development of new tailored strategies to combat transmission of the coronavirus, such as raising people’s awareness.

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Developing fast and unbiased computer vision algorithms

Images and videos are a common way to easily store data for research. However, turning these into usable and analyze data is much more time consuming and costly. In order to help research teams save time and money, DEVIATE is developing a computer vision algorithm to label image and video data for them. An essential part of the development process is to consider and mitigate any possible bias. In order to reduce bias, DEVIATE is using human coders to label the training and testing data. In addition, the pool of data represents a diversity of skin tones as well as different light levels. It is especially important to reduce bias since this product will be used by other research groups. If the algorithm was biased, it would affect countless other research studies as well, so it is essential that DEVIATE is able to minimize any harm coming from its product. As this is still an ongoing project, it is expected that the final product will be an unbiased comprehensive computer vision algorithm that can help research teams label data stored in images and video.

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