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Module Evaluation Results

Programming for Life Sciences — 2025/26

24 survey responses (44% rate)57 students assessed

2.3

Teaching Quality

out of 4.0

2.4

Overall Satisfaction

out of 4.0

3.2

Practical Skills

out of 4.0

3.4

AI Understanding

out of 4.0

Survey Results

Scale: 1 (Not at all) to 4 (To a large extent)

Overall Mean: 2.86/4.0

Strong on practical skills and AI guidance; teaching pace needs work

Grade Distribution

DNA Analysis Assignment (15% weighting) — 57 students

65.2%

Mean

65%

Median

47–82%

Range

Feedback Themes

Analysis of free-text comments (frequency of mentions)

What Students Valued

Google Colab Notebooks

"Very helpful in developing skills"

Course Website

"Elegant... I enjoy learning at my own pace"

Practical Application

"Learnt practical skills... deeply interpret plots"

Workshop Sessions

"Good place to ask questions and get feedback"

Primary Challenges Identified

Lecture Pacing

Lectures ran too fast for beginner-intermediate learners; not enough time to absorb content

Assessment Workload

70% DepMap project estimated at 40 hours but took 80+ hours for many students

Resource Integration

Multiple resources (DataCamp, notebooks, website) without clear unified structure

Workshop Support

Inconsistent support quality; some students felt redirected to AI rather than helped

The Bottom Line

The "Innovation Tax" was high — students struggled with pace and delivery. But the "Innovation Dividend" was real — they recognised the career value and developed practical skills they found deeply valuable.

82%

Python Test Average

67%

Final Assignment Median