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DSC TSS Overview for Mentors

Overview 

  • What is the TSS? The Technical Skills Survey is a skill check to ensure students new to data science are prepared to enter the career track portion of the DSC course. It is taken in HackerRank.
  • Who takes the TSS? 
    • New Springboard students with some data science experience take the TSS to see if they can skip the foundations and enter the career track. 
    • New Springboard students without data science experience are placed into the  Foundations to Core (F2C) course and take the TSS after 8 units.
  • What does it look like? As of Nov 1, 2023, the TSS has 21  questions designed to test Python and statistics. Here is the detailed schema, along with reference materials.
  • How much time do students have? Students have a 6-hour window to finish, but the average completion time is 90 minutes. Students can use their notes during this time; however, HackerRank will prevent them from accessing outside websites or copying and pasting during the exam. 

Course Pacing & Goal Setting

  • Students are encouraged to take the TSS by the fourth or fifth week of the course, assuming they are putting in 20-25 hours per week.
    • Students who are behind this pace by more than 2 weeks are often pacing behind their completion date. 
  • Mentors are an integral part of student accountability. Be sure to let them know you want to see them getting their hours in so they can be successful in the course. 
    • If a student falls behind, please notify their student advisor by sending an email to mentors@springboard.com with the context of what is happening and how an advisor might help. 

Other Common Questions

  • How many times can my student take the TSS? Students can take it up to 3 times.
  • How do I see the results of the TSS? Students receive an email with a notification of pass/fail.  Mentors will receive the actual TSS results and the curriculum units a student should work on. 
  • How does a student pass the TSS? Springboard uses a rubric to determine how many points the student scored and whether or not the student displays competency to move forward into the career track portion of the course. 

Recommendations & Best Practices
for Mentors

  • Bring up the TSS early (even the first call!) and use this as the first student success milestone. Students have to build up their skills by getting their hours in - they will need to watch the course videos and practice.  
  • Emphasize the importance of Python and Statistics. There are no shortcuts, and the student really needs to be ready to put in practice to learn. 
  • Take some of the pressure off by explaining how learning scaffolds: 
    • The foundations part of the course helps prepare the student for the career track.
    • The career track prepares a student for a job as a data scientist.
  • Encourage your students to take the TSS even if they don’t feel ready. Most students do better than they think, especially the ones who have completed all the practice problems. Remember - students can retake the TSS if needed without a penalty.
  • Help your student practice visualizing the problem and know how to research. Talk about problem-solving strategies like breaking down the big problem into smaller tasks and encourage students to research this.
  • Feedback is an important part of the learning process!


^Summary of this article

Additional Mentor Resources

  • If a mentor has questions related to the TSS, the #course_dsc channel on Slack is an excellent place to connect with tenured mentors. 
  • If students miss two consecutive calls and are not responding to your emails, please report them via this form. Our student advisors will contact the students and keep you updated.
  • If you have any concerns about a student's progress, please email mentors@springboard.com.