Step by step guide for the implementation and assessment of SPOOC

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A Self-Paced Open Online Course (SPOOC) is an online educational offering where learners have significant control over the pace and timing of their learning journey. Participants can typically start the course at their convenience and progress through the modules and learning activities according to their own schedule, usually within a generous overall course access period rather than fixed cohort-based timelines. SPOOCs are “open” in terms of enrollment (often free or low-cost, though sometimes restricted to specific groups like in a PhD program as in Lopez, 2021) and provide access to all or most learning materials upfront. This approach is particularly well-suited for professionals and adult learners with busy or unpredictable schedules who require flexibility to integrate AMR/AMS education into their lives.

Table of contents

  1. Planning a SPOOC
  2. Defining roles in a SPOOC
  3. Assessing a SPOOC
  4. Suggested SPOOC prototype
  5. Reference
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Planning a SPOOC

The following steps should be taken into consideration when planning a SPOOC on AMR/AMS:

  1. Define Clear AMR/AMS Learning Objectives and Target Audience: Articulate what participants should know or be able to do after completing the SPOOC. While open, SPOOCs often target learners with a specific interest or need in particular AMR/AMS domains.
  2. Robust Instructional Design and Modular Structure: Develop well-structured, self-contained learning modules that learners can navigate independently. The design must be exceptionally clear, intuitive, and provide all necessary resources within the course, as direct instructor interaction is typically minimal. (Rizzuto, 2017, emphasizes clear structure and navigation for self-paced courses; Dhaliwal et al., 2018, used a modular design for their self-paced training).
  3. Develop Diverse and Self-Explanatory Content: Create or curate a variety of learning materials that support autonomous learning, such as recorded video lectures, downloadable readings (AMR guidelines, research summaries), interactive e-learning modules, case studies relevant to AMR/AMS, practical examples, and frequent self-assessment quizzes with immediate, detailed feedback. (Dhaliwal et al., 2018, included videos, readings, and interactive activities; Rizzuto, 2017, recommends varied content and application activities).
  4. Platform Selection and Configuration: Host the SPOOC on a Learning Management System (LMS) or other online platform that robustly supports self-paced progression, content delivery, and automated assessments. Ensure reliable 24/7 access.
  5. Establish Flexible Deadlines (if any): While primarily self-paced, there might be an overall course completion deadline for administrative purposes or if linked to a specific program or certification. Individual module or assignment deadlines are typically flexible or non-existent. (Southard et al., 2015, describe flexible deadlines within the semester).
  6. Provide Clear Guidance and Learner Support Mechanisms: Offer comprehensive orientation materials on how to navigate the course, access resources, and complete activities. Establish clear, albeit often asynchronous, channels for learners to seek technical support or clarification on content (e.g., a detailed FAQ section, an email helpdesk, an optional, lightly moderated Q&A forum).
  7. Incorporate Self-Reflection and Application Activities: Include activities that encourage learners to reflect on the AMR/AMS content and consider its application to their own professional context or practice. (Rizzuto, 2017, emphasizes transformative learning through self-reflection in self-paced courses).
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Defining roles in a SPOOC

Facilitator’s role (Primarily Course Designer/Administrator and Occasional Support): The main effort is concentrated in the upfront, high-quality instructional design and development of clear, comprehensive, and self-contained learning materials and activities that anticipate learner needs. The facilitator also ensures the technological platform is reliable and user-friendly. Ongoing facilitation is typically minimal, focusing on asynchronous support (e.g., monitoring a Q&A forum, responding to emailed queries within a defined timeframe, or grading major assignments if not automated).

Participant’s role (Learner): A high degree of self-motivation, self-discipline, autonomy, and effective time management skills are essential for success in a SPOOC. Learners are responsible for independently navigating the course materials, engaging with the content at their chosen pace, completing learning activities and assessments according to their own schedule (within any overall course timeframe), and proactively seeking support through provided channels if they encounter difficulties.

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Assessing a SPOOC

Methods

  • Automated Self-Assessment Quizzes: Frequent, short quizzes embedded within or at the end of modules, providing immediate automated feedback to help learners gauge their understanding and reinforce AMR/AMS concepts.
  • Graded Online Quizzes and Exams: These can be open-book (reflecting real-world information access) and timed, assessing comprehension and application of AMR/AMS knowledge. (Southard et al., 2015, included exams).
  • Submission of Assignments or Projects: Depending on the SPOOC’s depth, learners might submit case study analyses, reflective essays, or small projects related to AMR/AMS for assessment (which could be automated, peer-reviewed, or instructor-graded if resources allow).
  • Portfolio Development: Learners may compile a portfolio of completed activities or reflections as evidence of learning.
  • Learner Self-Reflection Activities: Submission of structured self-reflections on learning and its potential application. (Rizzuto, 2017, used self-reflections and teaching improvement plans).
  • Course Completion Metrics: Tracking module and overall course completion rates. (Dhaliwal et al., 2018, tracked module completion).
  • Post-Course Satisfaction Surveys: Gathering feedback on the SPOOC’s design, content quality, platform usability, flexibility, and overall perceived learning value.

Tools

LMS quiz and assignment submission functionalities with options for automated grading and feedback. Online survey tools for course evaluations. E-portfolio platforms if applicable. Learning analytics can be employed to monitor general engagement patterns and identify potential areas where learners struggle, informing future course revisions. (Yan et al., 2021, discuss the role of learning analytics in self-paced online learning).

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Suggested SPOOC prototype

Target Audience: Food Producers, Prescribers (specifically Veterinarians), Dispensers (veterinary nurses/technicians).

Learning Objectives:

  • Equip participants with foundational knowledge on responsible antimicrobial use specific to [Target Animal Sector, e.g., dairy cattle, poultry, small companion animals].
  • Enable participants to identify common infectious diseases in that sector and understand evidence-based, stewardship-focused approaches to their prevention and treatment.
  • Provide practical guidance on implementing biosecurity measures and alternatives to antimicrobials to reduce AMR risks in their specific context.
  • Ensure understanding of relevant veterinary medicines regulations and record-keeping for AMU.

Curriculum/Activities:

  • A series of 5-7 self-paced online modules accessible via an LMS or dedicated web platform

    • Module Examples:

    • Understanding AMR in [Target Animal Sector]: Key Pathogens and Resistance Issues.
    • Principles of Prudent Antimicrobial Prescribing and Dispensing for Veterinarians/Staff.
    • Biosecurity on the [Type of Farm/Clinic]: Practical Implementation Guide.
    • Common Diseases in [Target Animal]: Diagnostic Approaches and Stewardship-Conscious Treatment Protocols (including when NOT to use antibiotics).
    • Alternatives to Antimicrobials: Vaccination, Nutrition, Management.
    • AMU Record-Keeping and Regulatory Compliance.
  • Each module includes: concise video lectures (e.g., from veterinary AMR experts), downloadable factsheets and sector-specific guidelines, interactive decision-making scenarios (e.g., “Choose the best course of action for this sick animal based on AMS principles”), and self-assessment quizzes with detailed feedback. (Dhaliwal et al., 2018, used varied materials in their self-paced modules).
  • An optional, lightly moderated Q&A forum where learners can post questions if they encounter difficulties with the material.

Evaluation of the Prototype’s Effectiveness:

  • Tracking of module and overall course completion rates via LMS analytics.
  • Analysis of aggregate performance on end-of-module self-assessment quizzes to identify concepts that may require clarification in future course revisions.
  • Post-course surveys to assess participant satisfaction with the self-paced format, the clarity and relevance of the AMR/AMS content for their specific animal sector, and self-reported confidence in applying prudent use principles.
  • Optional submission of a brief “My Farm/Clinic AMS Action Plan” where participants outline one or two changes they plan to implement based on the course learnings.
  • Longer-term (if feasible): Follow-up surveys to assess self-reported changes in AMU practices or adoption of new biosecurity measures.

References

  • Dhaliwal, N., Simpson, F., & Kim-Sing, A. (2018). Self-paced online learning modules for pharmacy practice educators: Development and preliminary evaluation. Currents in Pharmacy Teaching and Learning, 10(7), 964–974. https://doi.org/10.1016/j.cptl.2018.04.017
  • Lopez, D. (2021). Designing Training Activities for a New PhD Program in Engineering Education. 2021 IEEE Frontiers in Education Conference (FIE), 1–5. https://doi.org/10.1109/FIE49875.2021.9637153
  • Rizzuto, M. (2017). Design Recommendations for Self-Paced Online Faculty Development Courses. TechTrends, 61(1), 77–86. https://doi.org/10.1007/s11528-016-0130-8
  • Southard, S., Meddaugh, J., & France-Harris, A. (2015). Can SPOC (self-paced online course) live long and prosper? A comparison study of a new species of online course delivery. Online Journal of Distance Learning Administration, 18(2), 8.
  • Yan, H., Lin, F., & Kinshuk. (2021). Including Learning Analytics in the Loop of Self-Paced Online Course Learning Design. International Journal of Artificial Intelligence in Education, 31(4), 878–895. https://doi.org/10.1007/s40593-020-00225-z