Social Sciences – Page 32 – UROP Spring Symposium 2021

Social Sciences

Improving Student Mastery through Question Interleaving

Intelligent tutoring systems often recommend questions based on the estimation of students’ current ability estimates, the randomness, or the expectations from the instructors. To help students improve their masteries in a concept, we are going to propose a question recommendation model by utilizing question interleaving. Previous researches in math classes have shown that interleaving questions enhance student learning. Hence, assuming interleaving will benefit students’ learning, we examine how to effectively reordering the concepts of the questions within a session. Analyzing mainly on two online skill-builder datasets, we demonstrate that there exists a statistically significant difference in what we call sub-abilities from which interleaving can be optimized. We come up with a simple method that only depends on knowing a question concept id and a binary outcome for correctness. We are writing a Python library for simulation to compare how ideal results match with the proposed recommendation algorithms. The result of our findings aims to generate a personalized question recommendation for the students without gathering extensive data from them while maintaining the flexibility to include other models. The ultimate goal of our research is to provide students from different backgrounds with an efficient way to improve learning results.

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Reimagining Current Messaging Systems of Social Networks

While social networks have enabled improved communication globally and the widespread Human-Computer Interaction (HCI), it has also exasperated unsolicited communication and harassing messages which consistently target vulnerable, marginalized groups. Consentful Messaging offers Twitter users the ability to filter potential message senders before the risk of receiving unsolicited messages through a system built on Twitter’s API, Python, and JavaScript. The field deployment of Consentful Messaging will reveal how social media users choose to receive messages and to what extent they wish to customize potential message senders. Consentful Messaging is made of four possible customizable functions: the user can set a threshold of number of followers required for a potential message sender, the Consentful Messaging user can verify whether they follow the potential message sender, the Consentful Messaging user can determine whether the potential message sender is followed by at least one account that the Consentful Messaging user follows, and verify whether the Consentful Messaging user has ever replied to a message from the potential message sender. The result is that Consentful Messaging Twitter extension will be deployed in March of 2021. This field study will show how and to what extent Twitter users choose to protect themselves from unsolicited messages with the help of technology. Consentful Messaging will offer not only a customizable layer of protection to marginalized social media users by providing a board for healthy interactions among users, but also information as to how Twitter users interact with and modify personalized computer settings.

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Reimagining current messaging systems on the social internet

While social networks have enabled improved communication globally, it has also exacerbated unsolicited communication and harassing messages which consistently target vulnerable, marginalized groups. Consentful Messaging offers Twitter users the ability to filter potential message senders before the risk of receiving unsolicited messages through a system built on Twitter’s API, Django, MySQL, Python, and JavaScript. The field deployment of Consentful Messaging will reveal how social media users choose to exercise agency over receiving messages and to what extent they wish to customize potential message senders. Consentful Messaging provides the following customizable functions that a Twitter user can use to carve out the network that can initiate interactions: the user can set a threshold of number of followers required for a potential message sender, the system only allows notifications or messages from accounts that the user follows, the user can determine whether the potential message sender is followed by at least one account that the user follows, and verify whether the user has ever replied to a message/tweet from the potential message sender. In short, Consentful Messaging aims to offer a customizable layer of protection to social media users, especially marginalized groups, by providing a board for healthy interactions among users. We plan to deploy the system and conduct a field study sometime in the spring. This field study will help us understand the effectiveness of the approach, and show how and to what extent Twitter users choose to protect themselves from unsolicited messages with the help of technology.

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Consentful Messaging: Giving People Agency over Online Interactions using Network Data

Our project works on developing a Chrome extension that allows Twitter users to have more control over their inbox messages and analyzes other accounts to generate potential warnings. This extension tackles the growing issue of online harassment and unsolicited messages on social media by letting Twitter users apply network-based rules on the messages and notifications. We use coding languages such as HTML, Javascript, CSS, Python, and web framework Django to create the frontend of our extension/website as well as the backend where the server runs. Team members can choose to work on the frontend, backend, or both. We will evaluate the extension by conducting a field deployment study on Twitter. We will recruit active Twitter users and ask them to use the extension for at least two weeks. Once the participants are finished using the system, they will be invited to complete a post-study survey and participate in interviews. There aren’t exactly any results or conclusions at this stage of developing the extension. We are currently still working on different parts of the project and individually working on appropriate functions/code. We plan to provide a fully functional and helpful extension that is able to reduce the issue of online harassment (on the user’s side).

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Tech and Innovation in K-12 Education

Across the globe, 617 million of 1 billion students are not achieving the minimum proficiency levels in reading and math. Our research is focused on exploring technology that can help counteract this learning deficiency. To develop a comprehensive solution to this learning crisis, our research team has conducted an extensive review of scientific research related to integrating technology into education. Our solution contains a wide variety of technologies, of which are designed to improve several aspects of education, including: motivation, personalization, comprehension, feedback and assessments. Our intention is that these technologies will improve the educational experience and learning outcomes of current and future students.

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Documentary Film Team

Despite media being virtually everywhere, there are issues that are under covered. This project aims to create a network of filmmakers that can work together to cover important problems ignored by mainstream media and to reach out to students that hadn’t before imagined that they could go to college and inform them of their opportunities. To gain knowledge to share with the rest of the network editing techniques have been explored through countless video tutorials, databases, and skill sharing sites. After the exploration phase these techniques were put to the test by creating a sample piece. Finally the best methods were combined and detailed in step by step tutorials on how to create the previously described samples. As the repertoire of tutorials and knowledge expanded it has been noticed that there are more opportunities to assist other filmmakers with their works. It has also been noticed that as the repertoire grew other filmmakers tended to listen to your suggestions and criticism on their projects more often. This project is still ongoing and more conclusions can be drawn at a later time as soon as more data is available.

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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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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

In an effort to improve driver safety and autonomous vehicle testing, video recordings of drivers allow for data to be analyzed. These videos are first examined by human coders, but a more efficient, automated algorithm would prevent the need for human coders entirely. However, in order to build the algorithm, human coders need to analyze videos of drivers and label various actions, such as if the driver is turning or tilting their head, or hand movements, such as texting, and if their hand is obscured. Once these labels are implemented, they are tested against each other for accuracy, so that the final algorithm is unbiased enough to be implemented into vehicle safety.

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