learning-objectives-writing

Write measurable, SMART learning objectives using Bloom's Taxonomy cognitive levels aligned with desired outcomes and assessment strategies

509 stars

Best use case

learning-objectives-writing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Write measurable, SMART learning objectives using Bloom's Taxonomy cognitive levels aligned with desired outcomes and assessment strategies

Teams using learning-objectives-writing should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/learning-objectives-writing/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/social-sciences-humanities/education/skills/learning-objectives-writing/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/learning-objectives-writing/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How learning-objectives-writing Compares

Feature / Agentlearning-objectives-writingStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Write measurable, SMART learning objectives using Bloom's Taxonomy cognitive levels aligned with desired outcomes and assessment strategies

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Learning Objectives Writing

Write measurable, SMART learning objectives using Bloom's Taxonomy cognitive levels aligned with desired outcomes and assessment strategies.

## Overview

This skill enables the creation of clear, measurable learning objectives that guide instructional design and assessment. It encompasses application of Bloom's Taxonomy, SMART criteria, and alignment with assessment strategies to ensure effective learning outcome specification.

## Capabilities

### Bloom's Taxonomy Application
- Apply cognitive domain levels appropriately
- Use action verbs matched to cognitive levels
- Sequence objectives by complexity
- Address affective and psychomotor domains
- Align objectives with assessment methods

### SMART Criteria
- Write Specific objectives
- Ensure Measurability
- Verify Achievability
- Confirm Relevance
- Define Time-bound expectations

### Alignment Strategies
- Link objectives to organizational goals
- Connect to assessment methods
- Sequence within curriculum
- Map to competency frameworks
- Ensure instructional alignment

### Documentation
- Format objectives consistently
- Organize by module or unit
- Include conditions and criteria
- Document alignment rationale
- Create objective hierarchies

## Usage Guidelines

### Writing Process
1. Identify desired performance outcomes
2. Determine appropriate cognitive level
3. Select measurable action verbs
4. Specify conditions and criteria
5. Verify SMART criteria
6. Validate alignment

### Action Verb Selection
- Remember: list, define, recall, identify
- Understand: explain, summarize, interpret
- Apply: demonstrate, implement, use
- Analyze: compare, differentiate, examine
- Evaluate: critique, assess, judge
- Create: design, develop, construct

### Quality Criteria
- One behavior per objective
- Observable and measurable
- Learner-centered focus
- Appropriate level of challenge
- Clear conditions and standards

## Integration Points

### Related Processes
- ADDIE Model Implementation
- Backward Design
- Bloom's Taxonomy Application

### Collaborating Skills
- learning-needs-analysis
- assessment-item-development
- rubric-design-validation

## References

- Bloom's Revised Taxonomy (Anderson and Krathwohl)
- Mager's instructional objectives
- SMART goals framework
- Backward design principles

Related Skills

tech-writing-lint

509
from a5c-ai/babysitter

Automated technical writing style and quality enforcement. Lint documentation with Vale, check for inclusive language, enforce style guides, and analyze readability metrics.

tech-writing-linter

509
from a5c-ai/babysitter

Lint technical documentation for style, consistency, and readability

Reinforcement Learning Skill

509
from a5c-ai/babysitter

RL training for robot control using simulation with sim-to-real transfer

academic-writing-publication

509
from a5c-ai/babysitter

Prepare manuscripts following APA, ASA, or discipline-specific guidelines with proper reporting standards and peer review navigation

philosophical-writing-argumentation

509
from a5c-ai/babysitter

Compose clear, rigorous philosophical prose with well-structured arguments, anticipation of objections, and proper scholarly engagement with existing literature

grant-narrative-writing

509
from a5c-ai/babysitter

Compose compelling research narratives for NEH, ACLS, and foundation funding proposals with clear significance statements

multimedia-learning-design

509
from a5c-ai/babysitter

Apply Mayer's multimedia learning principles to design effective audio, video, graphics, and animations that reduce cognitive load

learning-transfer-design

509
from a5c-ai/babysitter

Design instructional strategies that promote knowledge and skill transfer to real-world application contexts

learning-needs-analysis

509
from a5c-ai/babysitter

Conduct comprehensive learner audience analysis, identify performance gaps, and determine instructional requirements using surveys, interviews, and data analysis

learning-analytics-interpretation

509
from a5c-ai/babysitter

Analyze learner data from LMS reports, assessments, and engagement metrics to identify patterns and inform instructional decisions

elearning-storyboarding

509
from a5c-ai/babysitter

Create detailed storyboards for interactive digital learning content specifying narration, visuals, interactions, and navigation

interpretive-writing

509
from a5c-ai/babysitter

Create accessible interpretive content for diverse audiences including labels, wall text, catalog essays, educational materials, and digital content