Failure Rates
The reported average failure rate in intro programming courses?
33%
A common reason for failure according to the study.
A lack of prior experience with abstract problem-solving.
One change that could improve student outcomes.
More formative assessments with feedback?
The result of failure rates in CS.
Reduced student retention in CS?
The failure rate has done this over 12 years.
Stayed the same.
What percentage of students fail programming courses globally?
33%
What role does pre-university preparation play in failure rates?
Students with weaker math and logic skills struggle more.
What is one strategy educators could use to improve motivation?
Gamification can increase student motivation.
How does failure affect students’ self-confidence in programming?
Reduced self-confidence and fear of programming.
Early reforms aimed at reducing failure rates found this.
Limited success.
In the study, which type of institution (e.g., university, community college) has higher failure rates?
Universities
Abstract nature of programming contributes to failure rates through this.
Overwhelm beginners.
One way to reduce the cognitive load for beginners.
Start with visual or block-based programming.
High failure rates affect the diversity of students in CS through this.
Detering underrepresented groups from pursuing CS.
This has changed about the demographics of students entering CS programs over time.
More women and non-traditional students are entering CS programs today.
New students in CS typically drop out after this.
After failing an intro course.
This teaching style impacts student performance in programming.
Lecture-heavy teaching styles contribute to disengagement and failure.
Flipped classrooms help reduce failure rates through this.
Improving understanding.
High failure rates in intro CS classes influence a student’s decision to do this.
Switch majors or leave CS entirely.
External trends have influenced programming education over the past 12 years through this.
Creating more diverse course offerings and pathways into CS.
Range of failure rates across different countries according to the study.
25% to 50%
Cultural factors like these play a role in failure rates.
Differing attitudes toward failure and academic pressure.
Changing grading policies impact student outcomes in this way for programming.
Helps struggling students with more flexible, mastery-based approaches.
Societal perceptions of programming in this way influence students’ willingness to persist after failure.
Societal perceptions of programming as “difficult”
One significant change in how CS education is delivered today versus 12 years ago.
Rise of coding bootcamps and/or online education platforms.