Variations on Defining a Dialect Region

This paper explores various methods of defining a dialect region, using syntactic constructions characteristic of the American South. We consider three important characteristics of such a method: place, feature, and measure. ”Place” details how data points should be grouped, ”feature” details which data points should be used, and ”measure” details how the data should be analyzed. While we may not claim one method as superior to any other, this research can provide insight into how different techniques of characterizing geographic variation may affect the resulting dialect regions

Mapbook of Syntactic Variation in American English: Survey Results, 2015–2019

This work presents the results of a series of acceptability judgment surveys conducted by the Yale Grammatical Diversity Project (YGDP) between 2015 and 2019. It contains over 200 maps of some 194 sentences, covering a wide range of syntactic constructions, including dative presentatives, personal datives, extended benefactives, the have yet to construction, the done my homework construction, wicked, hella, the so don’t I construction, the alls construction, the come with construction, fixin’ to, the needs washed construction, non-polarity anymore (aka “positive anymore”), and many others. For each sentence, we also provide some basic demographic information, such as how the sentence judgments varied by age, race, gender, education, and urban/rural classifications. We describe the goals of these surveys, as well as how they were designed, administered, processed, and mapped, along with a brief introduction to the history of the YGDP. In addition to providing a detailed look at syntactic variation in U.S. English to an extent that has previously been unavailable, we hope that this work will be useful in linguistics classrooms at all levels, and will provide the springboard for further, more detailed studies of the individual constructions, geographic regions, and linguistic and social factors connected to syntactic variation in U.S. English

A Mixed-Method Approach to Investigating Difficulty in Data Science Education

The purpose of this study was to define a methodology to identify any disconnect between students and instructors in data science classrooms through analyzing qualitative data. A combined qualitative and quantitative approach was used for analysis of survey data from students, faculty/instructors, and teaching assistants across three institutions. Using a manual content analysis paired with a TF-IDF analysis, researchers were able to pull out frequently used terms within responses and encode them into categories and subcategories. Trends were identified from these categories and subcategories to examine general areas of disconnect within the data science classroom. Additionally, a quality analysis was run to determine the effectiveness of the phrasing of the questions posed during the survey. As a whole, the methods used throughout this research process provide direction for researchers in interpretation and analysis of the survey data in an efficient and time-sensitive manner. Furthermore, it allows researchers to analyze the quality of responses to give insight towards rephrasing of survey questions in future analyses. Although the research was applied to data science classrooms, this method has the potential to be applied into other fields and areas of study when performed with coordination between a field expert and a data scientist

A Mixed-Method Approach to Investigating Difficulty in Data Science Education

The purpose of this study was to define a methodology to identify any disconnect between students and instructors in data science classrooms through analyzing qualitative data. A combined qualitative and quantitative approach was used for analysis of survey data from students, faculty/instructors, and teaching assistants across three institutions. Using a manual content analysis paired with a TF-IDF analysis, researchers were able to pull out frequently used terms within responses and encode them into categories and subcategories. Trends were identified from these categories and subcategories to examine general areas of disconnect within the data science classroom. Additionally, a quality analysis was run to determine the effectiveness of the phrasing of the questions posed during the survey. As a whole, the methods used throughout this research process provide direction for researchers in interpretation and analysis of the survey data in an efficient and time-sensitive manner. Furthermore, it allows researchers to analyze the quality of responses to give insight towards rephrasing of survey questions in future analyses. Although the research was applied to data science classrooms, this method has the potential to be applied into other fields and areas of study when performed with coordination between a field expert and a data scientist