California University Fields of Study Distribution

Analyzing Course Enrollment and Fields of Study at California University (2018)

By Eva Murray [source]

About this dataset

> This dataset offers an in-depth exploration into the variety of fields of study offered at California University during an undisclosed academic year. It delves into information such as course names, numbers, as well as their pertaining areas and general areas of study. The dataset also includes additional information like descriptions of each course and the professors associated with them. > > The data gives a numeric representation for the number of students who registered for these courses across the four main academic semesters: Fall, Winter, Spring and Summer. This allows for an accurate understanding of student interest and enrollment trends throughout different times in the academic year. > > Additionally, this dataset also provides clarity on whether a particular course was taught that year or not. This binary information signifies the viability and relevance of each course during that specific period. > > Ultimately, this dataset serves as a beneficial tool for studying patterns within various fields available at California University as well as student choices over time due to its comprehensive nature. Whether you are interested in exploring patterns within specific fields or merely curious about seasonal enrollment patterns – this rich data set can provide valuable insights. > > Please note that while certain fields are represented numerically such as 'year' which represents when data was collected or 'number' indicating unique identifiers related to programs or courses; others are presented in string format exhibiting textual details like names (course name), descriptions (brief outline about a particular course) among others. > > This extensive pool focuses on providing both quantitative measures (student registrations per semester) along with qualitative parameters (detailed program description). These combinations enable researchers to perform multifaceted analyses where correlations can be drawn from multiple perspectives thereby drawing more nuanced conclusions from their studies. > > Two important columns Profs1 & Profs2 reveal primary and secondary professors associated with certain programs allowing individuals to understand manpower distributions across diverse disciplines based on seasons & workloads. > Every included piece seemed pertinent providing useful insight towards courses' alignment under larger educational domains funneling down from general to more specific categories. > > Moreover, the dataset is perfect for anyone seeking to scrutinize broader educational dynamics revealing information about various disciplines offered within a university system. Its comprehensive nature ensures a detailed peek into the intricate workings of California University's academic programs through seasons and years making it an invaluable tool for data analysts, educational administrators, academic researchers and curious individuals alike

How to use the dataset

> This dataset offers comprehensive information about various fields of study at California University, including the number of courses in each field, associated professors, and the distribution of student registrations across different semesters within an academic year. > > Before delving into utilizing this extensive collection, let's understand what every column represents: > > - Year: The academic year when the data was collected. > - Field: The specific area of study being considered. > - Name: Name of the course under a particular field. > - Number: Course number associated with that course name. > - Area: A broader category under which that field falls. > - GenArea : An even larger umbrella term under which 'Area' lies. > - Description : Brief summary about what the course entails. > - Profs1 and Profs2 : The primary and secondary professors (if any) teaching a particular course. 'Profs2' may be null indicating no secondary professor for that class. > - Fall, Winter, Spring & Summer : These numerical columns depict how many students are registered for a given course in respective semesters/quarters (fall/winter/spring/summer). > -Taught - A Boolean value to show whether or not this class was offered during this academic year. > > So how can you use it? Here are some suggestions: > - Trend Analysis: You may check trends over years for certain fields or courses based upon several parameters; like student enrollments per semester or number of courses taught etc. > > - Comparative Analysis: Compare multiple fields to determine popularity among students by assessing enrollment numbers. > > - Correlation: Look if there's correlation between certain categories – like is there an increase in students during fall quarter across most courses? What could be attributing factors? > > - Resource Allocation: Analyze data from perspective of resource allocation - are there more professors assigned where enrollments are high? If not then unmet demand may indicate need for hiring more staff. > > All in all this dataset serves multitude of analytical uses. Whether the reason for your research is academically motivated, as part of administration / policy making, or purely out of curiosity to investigate patterns; it provides ample information that can guide a vast range of studies. Enjoy diving into the world of data analytics!

Research Ideas

> - Analyzing the popularity of different fields of study: The dataset provides information about the number of students registered for each course in different semesters. This data can be used to identify trends regarding which fields of study are becoming more or less popular among students, which can help the university plan and allocate resources better. > - Assessing teaching staff distribution across fields: With the information about primary and secondary professors teaching each course, it is possible to analyze how teaching staff is distributed across various fields and courses, as well as between semesters. This could provide insights into workload distribution and potential need for additional faculty recruitment in certain areas. > - Evaluating Course Demand & Schedule Planning: The dataset spans all seasons, making it possible to see when courses are taught most frequently and have highest student registrations. Universities could use this data for efficient course scheduling or even considering offering highly demanded summer/winter term courses more frequently during regular term schedules if there's a need or student interest. > > - Understanding correlations between broader field groupings (GenArea) and specific area concentrations (Area): It could provide insight into which broader academic spheres (like Humanities, Sciences etc.) see high engagement within certain concentration areas over others. > > - Student Behavior Analysis: Mapping trajectory of a specific field over years can give insights on student behavior - whether they prefer certain courses only during specific terms (like summers) due to factors like course load/difficulty etc., which again aids program planning efforts from a university standpoint

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > Data Source > >

License

> > > License: Dataset copyright by authors > - You are free to: > - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. > - Adapt - remix, transform, and build upon the material for any purpose, even commercially. > - You must: > - Give appropriate credit - Provide a link to the license, and indicate if changes were made. > - ShareAlike - You must distribute your contributions under the same license as the original. > - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Courses_Berkeley_2018-01-15.csv

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > If you use this dataset in your research, please credit Eva Murray.