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Analyze most-taught books and texts via Open Syllabus analytics
---
name: open-syllabus-api
description: "Analyze most-taught books and texts via Open Syllabus analytics"
metadata:
openclaw:
emoji: "📖"
category: "domains"
subcategory: "education"
keywords: ["Open Syllabus", "syllabi analytics", "teaching data", "textbook rankings", "curriculum analysis", "higher education"]
source: "https://opensyllabus.org/"
---
# Open Syllabus API
## Overview
Open Syllabus analyzes 20M+ college course syllabi from 7,000+ institutions in 140+ countries, tracking which books, articles, and media are most frequently assigned in higher education. The Explorer provides teaching frequency rankings and co-assignment patterns. Useful for curriculum research, textbook selection, and understanding disciplinary norms. Free for basic search; institutional subscription for full API access.
## Explorer Interface
### Web Search
```bash
# The primary interface is the web explorer:
# https://explorer.opensyllabus.org/
# Search by title, author, or field
# Filter by country, institution, discipline, year range
```
### API Access
```bash
# API requires institutional subscription
# Base URL: https://api.opensyllabus.org/v1/
# Search titles
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/titles?query=republic+plato&limit=20"
# Get title details
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/titles/12345"
# Co-assignment analysis
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/titles/12345/co-assigned?limit=20"
# Rankings by field
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/rankings?field=Economics&limit=50"
```
### Query Parameters
| Parameter | Description | Example |
|-----------|-------------|---------|
| `query` | Search text | `query=machine+learning` |
| `field` | Academic discipline | `field=Computer Science` |
| `country` | Country filter | `country=US` |
| `institution` | Institution filter | `institution=Harvard` |
| `year_from` | Start year | `year_from=2020` |
| `year_to` | End year | `year_to=2026` |
| `limit` | Results per page | `limit=50` |
## Key Metrics
| Metric | Description |
|--------|-------------|
| **Teaching Score** | 0-100 normalized frequency of syllabi appearances |
| **Count** | Raw number of syllabi featuring the title |
| **Rank** | Position in overall or field-specific ranking |
| **Co-assignment** | Titles frequently taught alongside this one |
## Python Usage
```python
import requests
BASE_URL = "https://api.opensyllabus.org/v1"
def search_titles(query: str, field: str = None,
country: str = None,
limit: int = 20, token: str = "") -> list:
"""Search Open Syllabus for assigned titles."""
headers = {"Authorization": f"Bearer {token}"} if token else {}
params = {"query": query, "limit": limit}
if field:
params["field"] = field
if country:
params["country"] = country
resp = requests.get(
f"{BASE_URL}/titles",
headers=headers,
params=params,
)
resp.raise_for_status()
data = resp.json()
results = []
for item in data.get("results", []):
results.append({
"title": item.get("title"),
"authors": item.get("authors"),
"teaching_score": item.get("teaching_score"),
"count": item.get("appearance_count"),
"rank": item.get("rank"),
"top_fields": item.get("top_fields", []),
})
return results
def get_co_assigned(title_id: int, limit: int = 20,
token: str = "") -> list:
"""Get titles frequently co-assigned with a given title."""
headers = {"Authorization": f"Bearer {token}"} if token else {}
resp = requests.get(
f"{BASE_URL}/titles/{title_id}/co-assigned",
headers=headers,
params={"limit": limit},
)
resp.raise_for_status()
return resp.json().get("results", [])
def get_field_rankings(field: str, limit: int = 50,
token: str = "") -> list:
"""Get most-taught titles in a field."""
headers = {"Authorization": f"Bearer {token}"} if token else {}
resp = requests.get(
f"{BASE_URL}/rankings",
headers=headers,
params={"field": field, "limit": limit},
)
resp.raise_for_status()
return resp.json().get("results", [])
# Example: find most-taught economics texts
# results = search_titles("microeconomics", field="Economics")
# for r in results:
# print(f"#{r['rank']} {r['title']} — {r['authors']}")
# print(f" Teaching Score: {r['teaching_score']} "
# f"({r['count']} syllabi)")
```
## Top Assigned Works (Examples)
| Rank | Title | Author | Field |
|------|-------|--------|-------|
| 1 | *The Elements of Style* | Strunk & White | Writing |
| 2 | *The Republic* | Plato | Philosophy |
| 3 | *A Manual for Writers* | Turabian | Writing |
| ~10 | *Thinking, Fast and Slow* | Kahneman | Psychology |
| ~50 | *Introduction to Algorithms* | CLRS | CS |
## Use Cases
1. **Curriculum design**: Find canonical texts in a discipline
2. **Textbook market research**: Identify widely adopted materials
3. **Teaching trends**: Track changes in assigned readings over time
4. **Interdisciplinary mapping**: Discover texts bridging fields
5. **Academic publishing**: Understand teaching impact vs. citation impact
## References
- [Open Syllabus](https://opensyllabus.org/)
- [Open Syllabus Explorer](https://explorer.opensyllabus.org/)
- Sinykin, D. & McLaughlin, T. (2021). "Mapping the Disciplinary Canon with Open Syllabus." *Cultural Analytics*.
---
name: open-syllabus-api
description: "Analyze most-taught books and texts via Open Syllabus analytics"
metadata:
openclaw:
emoji: "📖"
category: "domains"
subcategory: "education"
keywords: ["Open Syllabus", "syllabi analytics", "teaching data", "textbook rankings", "curriculum analysis", "higher education"]
source: "https://opensyllabus.org/"
---
# Open Syllabus API
## Overview
Open Syllabus analyzes 20M+ college course syllabi from 7,000+ institutions in 140+ countries, tracking which books, articles, and media are most frequently assigned in higher education. The Explorer provides teaching frequency rankings and co-assignment patterns. Useful for curriculum research, textbook selection, and understanding disciplinary norms. Free for basic search; institutional subscription for full API access.
## Explorer Interface
### Web Search
```bash
# The primary interface is the web explorer:
# https://explorer.opensyllabus.org/
# Search by title, author, or field
# Filter by country, institution, discipline, year range
```
### API Access
```bash
# API requires institutional subscription
# Base URL: https://api.opensyllabus.org/v1/
# Search titles
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/titles?query=republic+plato&limit=20"
# Get title details
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/titles/12345"
# Co-assignment analysis
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/titles/12345/co-assigned?limit=20"
# Rankings by field
curl -H "Authorization: Bearer $OS_TOKEN" \
"https://api.opensyllabus.org/v1/rankings?field=Economics&limit=50"
```
### Query Parameters
| Parameter | Description | Example |
|-----------|-------------|---------|
| `query` | Search text | `query=machine+learning` |
| `field` | Academic discipline | `field=Computer Science` |
| `country` | Country filter | `country=US` |
| `institution` | Institution filter | `institution=Harvard` |
| `year_from` | Start year | `year_from=2020` |
| `year_to` | End year | `year_to=2026` |
| `limit` | Results per page | `limit=50` |
## Key Metrics
| Metric | Description |
|--------|-------------|
| **Teaching Score** | 0-100 normalized frequency of syllabi appearances |
| **Count** | Raw number of syllabi featuring the title |
| **Rank** | Position in overall or field-specific ranking |
| **Co-assignment** | Titles frequently taught alongside this one |
## Python Usage
```python
import requests
BASE_URL = "https://api.opensyllabus.org/v1"
def search_titles(query: str, field: str = None,
country: str = None,
limit: int = 20, token: str = "") -> list:
"""Search Open Syllabus for assigned titles."""
headers = {"Authorization": f"Bearer {token}"} if token else {}
params = {"query": query, "limit": limit}
if field:
params["field"] = field
if country:
params["country"] = country
resp = requests.get(
f"{BASE_URL}/titles",
headers=headers,
params=params,
)
resp.raise_for_status()
data = resp.json()
results = []
for item in data.get("results", []):
results.append({
"title": item.get("title"),
"authors": item.get("authors"),
"teaching_score": item.get("teaching_score"),
"count": item.get("appearance_count"),
"rank": item.get("rank"),
"top_fields": item.get("top_fields", []),
})
return results
def get_co_assigned(title_id: int, limit: int = 20,
token: str = "") -> list:
"""Get titles frequently co-assigned with a given title."""
headers = {"Authorization": f"Bearer {token}"} if token else {}
resp = requests.get(
f"{BASE_URL}/titles/{title_id}/co-assigned",
headers=headers,
params={"limit": limit},
)
resp.raise_for_status()
return resp.json().get("results", [])
def get_field_rankings(field: str, limit: int = 50,
token: str = "") -> list:
"""Get most-taught titles in a field."""
headers = {"Authorization": f"Bearer {token}"} if token else {}
resp = requests.get(
f"{BASE_URL}/rankings",
headers=headers,
params={"field": field, "limit": limit},
)
resp.raise_for_status()
return resp.json().get("results", [])
# Example: find most-taught economics texts
# results = search_titles("microeconomics", field="Economics")
# for r in results:
# print(f"#{r['rank']} {r['title']} — {r['authors']}")
# print(f" Teaching Score: {r['teaching_score']} "
# f"({r['count']} syllabi)")
```
## Top Assigned Works (Examples)
| Rank | Title | Author | Field |
|------|-------|--------|-------|
| 1 | *The Elements of Style* | Strunk & White | Writing |
| 2 | *The Republic* | Plato | Philosophy |
| 3 | *A Manual for Writers* | Turabian | Writing |
| ~10 | *Thinking, Fast and Slow* | Kahneman | Psychology |
| ~50 | *Introduction to Algorithms* | CLRS | CS |
## Use Cases
1. **Curriculum design**: Find canonical texts in a discipline
2. **Textbook market research**: Identify widely adopted materials
3. **Teaching trends**: Track changes in assigned readings over time
4. **Interdisciplinary mapping**: Discover texts bridging fields
5. **Academic publishing**: Understand teaching impact vs. citation impact
## References
- [Open Syllabus](https://opensyllabus.org/)
- [Open Syllabus Explorer](https://explorer.opensyllabus.org/)
- Sinykin, D. & McLaughlin, T. (2021). "Mapping the Disciplinary Canon with Open Syllabus." *Cultural Analytics*.
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.