“Student Career Portal” — Choose your study path based on facts!
This project was carried out as part of the TechLabs “Digital Shaper Program” in Dortmund (winter term 2020).
In a nutshell:
High school and university students have no access to objective data related to popular and in demand career paths to help them choose and design their study programs at the university. The data from students of different age groups and study programs were collected and analyzed. The data was processed within python to observe the objective trends related to study choices and future plans of students.
Introduction:
The idea was to develop an open-source student career guidance portal where every student can have access to the current trends in higher education and popular career paths based on the preferences of other students.
High school and university students have no access to objective data related to popular and in-demand career paths to help them design their study path at the university. Furthermore, a lot of students don’t have an idea about the job market and in-demand skills while making their study choices. The career portals like LinkedIn or Xing are mostly focused on job professionals. Furthermore, one can not readily find any objective data or facts. A career portal focused solely on students can be very useful to address this gap of guidance available for students.
An initial database can be developed by using an online survey form to collect the data. Several questions related to the study choices, favorite subjects, and future plans could be asked from the students in the survey form. Based on the data, an open-source website portal can be developed where every student can register after providing the information related to his or her study plans. The collected data can be analyzed and split into multiple categories such as gender, study discipline, or education level to observe the trends. Every member of the portal will be asked to continuously update their data and career choices after a specific amount of time. This will lead to automatic updates of the data and as well as a depiction of the latest trends.
Methodology:
We designed a google form to collect the data from students in schools and universities. As our team comprised of Data Science students only, the plan to develop a website was dropped. However, we wrote a detailed python code to clean, group, and analyze the collected data.
Following methods/tools were used in our python code:
- Pandas Dataframe
- Matplotlib. to plot and visualize data
- Numpy Arrays
- Conditional Statements
- Loops
- Functions
Results:
The developed python code generates different correlations between study programs, future plans, and popular career paths among male and female students based on the collected data. Furthermore, we also analyzed the correlation between the current study program and favorite subjects in the high school for bachelor and master students.
The developed python algorithm can serve as a foundation to further develop a career portal website in the future. As many students struggle to decide about their study paths due to lack of awareness related to the latest trends and future demand of job markets, this open-source student career portal will provide students with the facts based on numbers to help them design their study paths and make career choices.
Repository:
- https://github.com/AjithSi/StudentCareerPortal (GitHub)
- https://forms.gle/feMugzvcXNjbLvM67 (Google Forms)
Team members:
- Abdelrehman Taha
Track: Data Science
E-Mail: abelrehman94ayman@gmail.com
LinkedIn: https://www.linkedin.com/in/abdelrahman-a-taha/
Responsibility in the Project: Python Programmer - Ajith Sivakumar
Track: Data Science
E-Mail: ajith.sivakumar@uni-muenster.de
LinkedIn: https://www.linkedin.com/in/ajith-sivakumar-224043192/
Responsibility in the Project: Python Programmer - Muhammad Tayyab
Track: Data Science
E-Mail: muhammad.tayyab@tu-dortmund.de
LinkedIn: https://www.linkedin.com/in/muhammad-tayyab-b7675297
Responsibility in the Project: Python Programmer
Team mentors:
- Tobias Küper, Data Science Mentor
- Lara Stahl, Project Assistent
- Saqib Bhatti, Project Assistant
