Genetics and Bioinformatics Course Feedback

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Questions and Answers

What kind of outcomes would you like to achieve through a CSL project? (Select up to 3)

  • Enhance communication and teaching skills
  • Learn about ethical data practices (correct)
  • Improve community health or awareness (correct)
  • Build a portfolio of real-world projects (correct)
  • Create lasting community impact (correct)
  • Gain technical skills (e.g., coding, data analysis) (correct)

Which topics or concepts were most engaging for you? (Select all that apply)

  • Topic Microbiomics (correct)
  • Topic Metabolomics (correct)
  • Topic Genomics (correct)
  • Topic Transcriptomics (correct)

Which of the following CSL activities would you be most interested in participating in? (Select up to 3):

  • Open-Source Data Projects for Public Health Awareness (correct)
  • Data Literacy Workshops for Health Organizations (correct)
  • Collaborative Data Analysis for Environmental Health Projects (correct)
  • Patient-Centric Data Analysis for Local Clinics (correct)
  • Crowdsourced Health Data Projects with Privacy Preservation (correct)
  • Predictive Models for Food Insecurity and Nutritional Needs (correct)
  • Educational Programs for High School Students on Bioinformatics and Machine Learning (correct)
  • Community Health Prediction Models (correct)
  • Public Data Science Consultations (correct)

What type of project structure do you prefer?

<p>Ongoing projects with flexible participation (A), Short-term projects (1-3 months) (B), Long-term projects (4-12 months) (C)</p> Signup and view all the answers

Do you prefer to work:

<p>In larger groups (6+ people) (A), In small teams (2-5 people) (B), Individually (C)</p> Signup and view all the answers

How actively did you participate in course activities (e.g., discussions, assignments)?

<p>Sometimes, (A), Not at all, (B), Always (C), Rarely, (D), Often, (E)</p> Signup and view all the answers

How well did the structure of the course support your understanding of genetics and bioinformatics?

<p>Slightly well (A), Extremely well (B), Very well (C), Not well at all (D), Moderately well (E)</p> Signup and view all the answers

How would you like to see more content focused on data platform-specific low-level analytics?

<p>Not sure (A), No, the current focus is sufficient (B), Yes, I would like to see more on low-level analytics (C)</p> Signup and view all the answers

How effectively did you overcome these challenges?

<p>Well, (A), Somewhat, (B), Not at all, (C), Very effectively (D), Slightly (E)</p> Signup and view all the answers

How would you rate your overall understanding of the subject after completing this course?

<p>Average, (A), Good, (B), Poor, (C), Very poor, (D), Excellent (E)</p> Signup and view all the answers

What was the biggest challenge for you in this course?

<p>Comments or other (please specify) (A), Staying motivated (B), Managing time and workload (C), Understanding content (D), Participating in group work (E)</p> Signup and view all the answers

Would you like the option to cover more advanced modules on specific topics?

<p>Other (please specify): (A), Yes, covered directly in class sessions (B), Yes, as optional homework assignments for deeper learning (C), No, I find the current level sufficient (D)</p> Signup and view all the answers

How relevant is what you learned in this course to your future goals?

<p>Slightly relevant, (A), Not relevant, (B), Very relevant, (C), Moderately relevant, (D), Extremely relevant (E)</p> Signup and view all the answers

How would you rate the clarity and relevance of the materials provided in the Analytics Block?

<p>Good (A), Poor (B), Very poor (C), Excellent (D), Fair (E)</p> Signup and view all the answers

What was the most memorable part of this course? (Select one)

<p>A specific lecture or topic (A), Other (please specify) (B), A group project or discussion (C), A practical assignment or research project (D)</p> Signup and view all the answers

What skills do you hope to develop through a CSL project? (Select all that apply):

<p>Coding and data visualization (A), Reproducibility (B), Teaching and mentorship skills (C), Bioinformatics principles (D), Communication and consulting skills (E), Machine learning and predictive modeling (F), Ethical data usage and privacy practices (G)</p> Signup and view all the answers

Would you like to see PBL integrated more extensively into future modules?

<p>Yes, I found it engaging and potentially beneficial (A), No, I prefer traditional instruction methods (B), I'm undecided and would need more experience with PBL to decide (C), Other (please specify): (D)</p> Signup and view all the answers

How do you feel about the current course structure with two distinct blocks (Genetics Block and Non-Genetics (Analytics-Oriented) Block)?

<p>Neutral (A), Dissatisfied (B), Very satisfied (C), Very dissatisfied (D), Satisfied (E)</p> Signup and view all the answers

If you could choose an alternative structure, would you prefer:

<p>Changing to a structure organized by data types (e.g., each type with its own introduction, generation platforms, low-level analysis, and high-level analysis) (A), Keeping the current structure (Genetics and Analytics blocks) (B), Other (please specify): (C)</p> Signup and view all the answers

Do you have prior experience with any of the following?

<p>Coding (e.g., Python, R) (A), Community service or nonprofit work (B), Machine learning frameworks (e.g., TensorFlow, scikit-learn) (C), Data visualization tools (e.g., Tableau, Power BI) (D), Public speaking or teaching (E), Bioinformatics software (e.g., BLAST, Bioconductor) (F)</p> Signup and view all the answers

Which aspects of the course were most helpful?

<p>Other (please specify) (A), In-class assignments (group projects) (B), Feedback from the instructors (including during or outside class) (C), Lectures (D)</p> Signup and view all the answers

A growth mindset isn't just about effort. Perhaps the most common misconception is simply equating the growth mindset with effort. Certainly, effort is key for students' achievement, but it's not the only thing. Students need to try new ______ and seek input from others when they're stuck. They need this repertoire of approaches-not just sheer effort—to learn and improve.

<p>strategies</p> Signup and view all the answers

Would you like your efforts and performance on DataCamp assignments to be scored and count toward your final exam score?

<p>No, I prefer that DataCamp efforts do not count toward the final score. (A), I'm undecided. (B), Yes, I think DataCamp efforts should count toward the final score. (C)</p> Signup and view all the answers

How much personal growth did you experience in this course?

<p>Slight, (A), Significant, (B), Transformational (C), None, (D), Moderate, (E)</p> Signup and view all the answers

What personal strengths did you develop during this course? (Select all that apply)

<p>Resilience (A), Collaboration (B), Time management (C), Creativity (D), Problem-solving (E)</p> Signup and view all the answers

Where would you prefer to have content on data platform-specific low-level analytics?

<p>Other (please specify): (A), No preference (B), In the Analytics Block (to keep analytics-focused content together) (C), In the Genetics Block (due to natural alignment with data types) (D)</p> Signup and view all the answers

What future topics or skills would you like to explore next? (Select all that apply)

<p>Other (please specify) (A), Advanced topics in this subject (B), Interdisciplinary applications (C), Practical skills (e.g., coding, writing) (D)</p> Signup and view all the answers

How effective were the teaching methods in supporting your learning?

<p>Very effective, (A), Not effective, (B), Moderately effective, (C), Slightly effective, (D), Extremely effective (E)</p> Signup and view all the answers

How would you rate the effectiveness of each tutor in explaining the course content?

<p>Very poor (A), Excellent (B), Poor (C), Good (D), Fair (E)</p> Signup and view all the answers

What kind of knowledge is essential for success in this course?

<p>Bioinformatics (A), Biomedicine (B), Informatics (C), Genetics (D), Data science or statistics or machine learning (E)</p> Signup and view all the answers

Did you take this course as part of a specific program?

<p>Bachelor (A), Freelance (B), Erasmus (C), Master (D)</p> Signup and view all the answers

What type of community engagement appeals to you the most? (Select all that apply):

<p>Research and data analysis (A), Developing technical tools (e.g., dashboards, models) (B), Hands-on collaboration with organizations (C), Public presentations or consultations (D), Teaching or mentoring others (E)</p> Signup and view all the answers

To what extent did this course improve your skills in each of the following areas?

<p>Some improvement (A), No improvement (B), Significant improvement (C)</p> Signup and view all the answers

Flashcards

Prior knowledge

Student's existing knowledge about genetics, bioinformatics, data science, etc., before taking the course.

Course Structure

The organization of the course into distinct modules or blocks, such as Genetics and Analytics.

Data types

Different forms of data used in bioinformatics, including genomics, transcriptomics, and others.

Low-level analytics

Data processing and quality control for specific data platforms.

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High-level analytics

Integrative analyses like pathway analysis or machine learning.

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DataCamp

Online platform for learning programming and analytics skills, integrated with the course.

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PBL

Project-Based Learning, an approach to learning by taking on projects.

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Genetics Block

Part of the course focused on genetics.

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Analytical Block

Part of the course focusing on data analysis (bioinformatics).

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RNA-Seq

Method to study gene expression by analyzing RNA molecules.

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Microarray

Method to measure gene expression via DNA arrays.

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GWAS

Genome-wide association study – looks for DNA changes linked to diseases

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Microbiome

All microorganisms in a specific environment.

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Metabolomics

Study of metabolites in a biological system.

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Clarity and Relevance

How well course materials explain concepts and connect them to practical applications.

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Practical Application

Examples and exercises that show how theoretical knowledge can be used.

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Critical Thinking

Ability to analyze information, identify problems, and suggest possible solutions

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Community Service Learning

Applying learning to real world problems in the community.

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Growth Mindset

Belief that abilities and intelligence can be developed through effort and learning.

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Time Management

Effective use of time.

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Collaboration

Working together.

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Problem Solving

Finding solutions to questions.

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Resilience

Ability to recover from setbacks.

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Data Literacy workshops

Teaching people how to use data information.

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Study Notes

Course Feedback Survey

  • Course Name: Genetics and Bioinformatics
  • Survey Date: 2024-11-14
  • Purpose: Gather feedback to improve course structure, content, and delivery.

Section 1: General Information

  • Background Knowledge: Respondents were asked to select their prior knowledge level in genetics, bioinformatics, informatics, biomedicine, data science, and statistics.
  • Program Affiliation: Participants were asked if they were taking the course as part of a specific program (e.g., Bachelor, Master, Erasmus, Freelance).

Section 2: Course Structure and Organization

  • Course Structure: The current structure has two distinct blocks (Genetics and Analytics-Oriented).
  • Alternative Structure Preferences: Respondents could choose between keeping the current structure or an alternative organized by data types (e.g., type, introduction, generation, etc.).
  • Structure Support for Understanding: The survey asked how well the structure supported understanding of genetics and bioinformatics. Responses ranged from "Extremely well" to "Not well at all".
  • Overall Organization: The structure was evaluated and participants were asked their opinions on the design as a whole.

Section 3: Course Content

  • Low-Level Analytics: Participants were questioned about the desire for more data platform-specific low-level analytics content. This content focuses on processing, control, and quality for particular data platforms.
  • Content Placement Preference: The survey asked where respondents would prefer this low level content placement (Genetics Block, Analytics Block, or No preference).
  • Clarity and Relevance of Materials: Course content clarity and relevance were assessed for both the Genetics and Analytics Blocks. Participants could rate from "Excellent" to "Very poor".
  • Balance between Theoretical and Practical Applications: The questionnaire addressed whether the balance between theory and practical application was appropriate.
  • Most Memorable Course Elements: Participants were asked to identify the most memorable aspect of the course (e.g., lecture, group project, practical).

Section 4: Teaching and Support

  • Tutor Effectiveness: Respondents evaluated the effectiveness of the tutors in explaining the course content. Assessments were provided for the assigned tutors (e.g. Genetics, Bioinformatics, Microbiome, RNA, Metabolome).

  • Support Resources: Participants rated the helpfulness of support resources like practical descriptions, slides, etc. towards course content understanding.

  • Tutor and Resource Improvement Suggestions: Participants could submit specific suggestions or improvements based on the teaching style and support materials.

Section 5: Learning Outcomes and Skills Development

  • Skill Improvement Areas: The survey explored participant skills' development in genetics, bioinformatics, high-level analysis (e.g. GWAS, micro), low-level analysis (e.g. platform specific), and critical thinking improvement as a result of the course.

Section 6: Self-Reflection about the Course

  • Understanding of Subject: Respondents were asked to rate their overall understanding of the course subject.

  • Engaging Topics: Participants could identify their most engaging parts of the course (e.g., Genomics, Transcriptomics, Microbiomics, Metabolomics).

  • Personal Growth: The survey sought details about personal growth arising from the course (e.g. skills, strengths).

  • Developed Strengths: Participants could note the strengths they developed during this course.

Section 7: Future Opportunities

  • Community Service Learning (CSL): Respondents were questioned about the interest and value in integrating community service into the course.
  • Additional Education (X-omics for Health): A potential master's level program focused on different omics types (genomics, proteomics, etc.) was proposed, with a survey designed to gather interest in the program.

Section 8, 9, 10, and 11: Additional Information

  • Project Structure Preference: Survey respondents provided their preferences for project structure (e.g., short-term, long-term).
  • Preference and Constraints: The survey investigated work preferences (individual, team) as well as constraints or preferences for project details (e.g., remote work, location, timing).
  • Teaching Methods Effectiveness: Participants were asked to evaluate the effectiveness of the course's teaching methods.

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Genetics and Bioinformatics Course Experience 2024-2025 PDF

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