MS059 Evaluations

Summary

Instructor Contribution:

2020: Goodwin was praised for his patience, thorough explanations, and willingness to help students individually, contributing positively to their understanding of the material.
2021: Students appreciated his encouragement, detailed demos, and explanations, which helped in understanding Python and visualization concepts.
2022 & 2023: Feedback was mixed. Some students felt the instructor was knowledgeable and kind, but others noted issues with lecture organization and clarity, suggesting that hands-on coding sessions often involved simply following pre-written examples.

Class Activities and Discussions:

2020: Activities helped students understand coding processes, with inspiration drawn from peers' work.
2021: Coding exercises and hands-on guidance were helpful, though some students felt feedback on assignments could be more consistent.
2022: In-class coding activities were perceived as less effective, as they mainly involved copying instructor-provided code. The use of external platforms like Kaggle was appreciated by some but criticized by others for inefficiency.
2023: Lectures and project work were beneficial, though some students felt exercises involved too much direct code copying without deeper understanding.

Feedback:

2020: Feedback was quick and supportive, aiding student development.
2021 & 2022: Comments highlighted a lack of consistent feedback, with confusion over assignments and grade transparency.
2023: Feedback on projects was seen as helpful during one-on-one interactions, but general feedback was less frequent.

Office Hours:

Across all years, students rarely attended office hours, often relying on in-class assistance and electronic communication.

Most/Least Useful Aspects:

2020: Direct coding practice and one-on-one time were valued.
2021: Readings and projects were beneficial, though the lack of feedback and organization were concerns.
2022: Kaggle tutorials received mixed reviews; some found them useful while others criticized them alongside the perceived lack of impactful exercises.
2023: Classroom exercises felt repetitive for some students, emphasizing code copying over individual learning.

Workload and Time Commitment:

2020: Workload was seen as manageable, with 3-6 hours spent weekly.
2021: Workload was light, similar in 2022 and 2023, and predominantly manageable, with minimal time required outside class.

Intellectual Development:

2020 & 2021: Courses inspired interest in Python and visualization, fostering a new appreciation for coding.
2022 & 2023: Learning outcomes varied; some students left with basic Python skills and interest in coding, while others felt less challenged.

Overall Impressions:

2020: Students found the class supportive, encouraging exploration and learning.
2021: While enjoyable and kind-spirited, students felt the need for more structure and interaction.
2022: Critical feedback pointed to disorganized teaching and lack of engagement, affecting learning experiences negatively.
2023: The course was seen as easy, with Goodwin offering helpful one-on-one support, though engagement and hands-on learning were noted as areas for improvement.

Student Respondent Demographics:

2020: Respondents were mainly first-year and sophomore students from Pitzer and Pomona, taking the course as a requirement or elective.
2021-2023: Students from Scripps and other Claremont colleges, mostly sophomores and seniors, took the course as an elective or requirement.