skills/43-wentorai-research-plugins/skills/domains/education/curriculum-design-guide/SKILL.md
Systematic approaches to curriculum design using backward design and alignment
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research curriculum-design-guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A structured skill for designing research-informed curricula using backward design, constructive alignment, and competency-based frameworks. Applicable to higher education course design, training program development, and educational research.
Understanding by Design (Wiggins & McTighe, 2005) reverses the traditional content-first approach:
Define what students should know, understand, and be able to do:
course: "Introduction to Research Methods"
big_ideas:
- "Research is a systematic process of inquiry"
- "Methodology must align with research questions"
essential_questions:
- "How do we know what we know?"
- "What makes evidence credible?"
- "When should we use qualitative vs. quantitative methods?"
learning_outcomes:
- "Formulate testable research questions (Apply)"
- "Select appropriate research designs for given questions (Evaluate)"
- "Critically appraise published research methodology (Analyze)"
- "Design and defend a research proposal (Create)"
Design assessments before planning instruction:
# Assessment blueprint generator
def create_assessment_blueprint(outcomes: list[str], bloom_levels: list[str],
weights: list[float]) -> dict:
"""
Generate an assessment blueprint mapping outcomes to
assessment types and weights.
"""
assessment_types = {
'Remember': 'quiz',
'Understand': 'reflection_paper',
'Apply': 'problem_set',
'Analyze': 'case_study',
'Evaluate': 'peer_review',
'Create': 'research_proposal'
}
blueprint = []
for outcome, level, weight in zip(outcomes, bloom_levels, weights):
blueprint.append({
'outcome': outcome,
'bloom_level': level,
'assessment_type': assessment_types.get(level, 'portfolio'),
'weight_pct': weight * 100
})
return {'blueprint': blueprint, 'total_weight': sum(weights) * 100}
outcomes = [
"Formulate research questions",
"Select research designs",
"Appraise methodology",
"Design research proposal"
]
levels = ['Apply', 'Evaluate', 'Analyze', 'Create']
weights = [0.15, 0.20, 0.25, 0.40]
print(create_assessment_blueprint(outcomes, levels, weights))
Sequence activities that build toward assessment readiness. Use the WHERETO framework:
Biggs' Constructive Alignment (1996) ensures coherence between intended learning outcomes (ILOs), teaching/learning activities (TLAs), and assessment tasks (ATs):
ILO: "Students will analyze case studies using SWOT framework"
|
+--> TLA: Workshop where students collaboratively analyze
| a real company case in small groups
|
+--> AT: Individual case analysis report (1500 words)
assessed with rubric mapping to ILO verbs
Misalignment is the most common curriculum design failure. Audit each ILO to verify it has at least one matching TLA and one matching AT.
For programs with multiple courses, create a curriculum map:
Competency | Course 1 | Course 2 | Course 3 | Course 4
------------------------|----------|----------|----------|--------
Research question design| I | D | M | A
Literature review | I | D | D | M
Data collection | - | I | D | M
Statistical analysis | - | I | D | A
Academic writing | I | D | D | A
Legend: I = Introduced, D = Developed, M = Mastered, A = Applied
Ensure every competency reaches at least "Mastered" level by program completion, and identify gaps where competencies are introduced but never developed further.
Validate curriculum designs through:
Document all revisions in a curriculum changelog to maintain institutional memory and support accreditation reporting.
development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
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