In 2022, the revenue generated from accounting services hit an all-time high of 119.48 billion USD (“Accounting Services in the US - Market Size”, 2022). On top of this, research has shown that 45% of all accounting professionals would like to automate something about their workflow (Thomas, 2020). Indeed, a lot of bookkeeping accountancy has been phased out by simple automation. However, larger accounting tasks like business mergers still require a team of accountants despite being a largely iterative process. This project chronicles one such attempt at automating accounting events or transactions that are performed by businesses both large and small. With the help of accounting students Madeline Stolper and Heddie Liu we were able to build a fully-functioning website to automate accounting transactions. For this project, we used industry-standard software frameworks React and Express to build the site with dynamic accounting applications. These applications were built with reusable components, making the development of future applications very simple. We also leveraged cutting-edge technological solutions from Amazon Web Services to make the website available on the Internet with rapid response times. Lastly, we incorporated an agile approach to project management and communication, in order to create functionality in the most efficient and organized manner possible. On a large scale, something like this has never been attempted and TurboIFRS/GAAP represents a revolutionary leap in accounting automation.

In 2022, the revenue generated from accounting services hit an all-time high of 119.48 billion USD (“Accounting Services in the US - Market Size”, 2022). On top of this, research has shown that 45% of all accounting professionals would like to automate something about their workflow (Thomas, 2020). Indeed, a lot of bookkeeping accountancy has been phased out by simple automation. However, larger accounting tasks like business mergers still require a team of accountants despite being a largely iterative process. This project chronicles one such attempt at automating accounting events or transactions that are performed by businesses both large and small. With the help of accounting students Madeline Stolper and Heddie Liu we were able to build a fully-functioning website to automate accounting transactions. For this project, we used industry-standard software frameworks React and Express to build the site with dynamic accounting applications. These applications were built with reusable components, making the development of future applications very simple. We also leveraged cutting-edge technological solutions from Amazon Web Services to make the website available on the Internet with rapid response times. Lastly, we incorporated an agile approach to project management and communication, in order to create functionality in the most efficient and organized manner possible. On a large scale, something like this has never been attempted and TurboIFRS/GAAP represents a revolutionary leap in accounting automation.

While people are scrolling through their various social media apps, they encounter messaging that does not necessarily promote good mental health. Rather, images, posts, and videos often make a mockery of those with mental health problems, leaving the viewers to believe that mental health problems often lead to dangerousness, criminality, and unpredictability. It then is essential that social media messaging about mental health, and its stigmas are analyzed and solutions to promote better mental health messages on these platforms are implemented because they affect everyone. Anti-stigma campaigns may be useful in bringing awareness to mental health and its stigmas, so two anti-stigma campaigns, Stamp Out Stigma and StigmaFree, were analyzed in this study. To understand the types of messages people are receiving about mental health and its stigmas from anti-stigma organizations on social media platforms, three research questions were developed. A thematic analysis was conducted that included 205 posts from 2021 that came from the campaigns' Facebook and Twitter accounts. Several themes emerged for each research question as well as multiple limitations for this study. Ultimately, social media messaging about mental health and its stigmas must continue to be researched.

Machine learning is a rapidly growing field, with no doubt in part due to its countless applications to other fields, including pedagogy and the creation of computer-aided tutoring systems. To extend the functionality of FACT, an automated teaching assistant, we want to predict, using metadata produced by student activity, whether a student is capable of fixing their own mistakes. Logs were collected from previous FACT trials with middle school math teachers and students. The data was converted to time series sequences for deep learning, and ordinary features were extracted for statistical machine learning. Ultimately, deep learning models attained an accuracy of 60%, while tree-based methods attained an accuracy of 65%, showing that some correlation, although small, exists between how a student fixes their mistakes and whether their correction is correct.