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I've learned about the origins of The Common Career Technical Core and how it came about in 2012. Also I have a clear understanding of programs of studies and how it supports high quality skill acquisition and student learning. It's important to collaborate with other teachers and program advisory to identify skills gaps and to determine which of the standards are relevant giving the current state of the workforce within the industry so that it can be determine what scope and sequence is needed when teaching these concepts and skills. 

Ways to share data with CTE Stakeholders-

Specific tools and implementation strategies:

Visual Data Dashboards
Tools:
·         Tableau: Professional-grade visualization with deep customization

·         Power BI: Microsoft's solution, excellent for integration with Excel data

·         Google Data Studio: Free option with good Google Sheets integration

·         Quicksight: AWS-based solution for cloud-first approaches

Implementation Tips:

·         Create different views for various stakeholder groups

·         Include drill-down capabilities for detailed analysis

·         Set up… >>>

CTE programs utilize disaggregated data by breaking down student demographics like race, ethnicity, gender, socioeconomic status, and disability status to identify disparities in participation, achievement, and post-graduation outcomes within their programs, allowing them to pinpoint specific areas where certain student groups are underrepresented or experiencing lower success rates, thus highlighting equity gaps that need to be addressed; this enables targeted interventions and program adjustments to promote equitable access and outcomes for all students. 

Key points about how CTE programs use disaggregated data for equity:

Identifying disparities:
By analyzing data broken down by demographic factors, CTE programs can see if certain… >>>

Important sources of aggragate data are as follows:

Types of CTE Program Aggregate Data Analysis
Key Data Categories Available in SRCDS CTE Programs:
• Enrollment Data

Total student participation numbers
Demographics (gender, ethnicity, special populations)
Program-specific enrollment trends
Year-over-year comparison statistics

• Academic Performance Metrics

Course completion rates
Grade point averages
Technical skill attainment
Industry certification pass rates

• Program Completion Data

Graduation rates
Program retention statistics
Time to completion metrics
Certificate/degree completion rates

• Career Readiness Indicators

Work-based learning participation
Industry credential attainment
Dual credit completion
Career technical student organization participation

• Post-Program Outcomes

Employment rates
Post-secondary enrollment
Industry… >>>

Disaggregated data plays a crucial role in evaluating and improving high-quality CTE programs of study. By breaking down data into subcategories such as race, gender, socioeconomic status, and special populations, educators and administrators can identify trends, equity gaps, and areas needing targeted support. Here are some key benefits and applications of disaggregated data in CTE:

  1. Identifying Equity Gaps - Pinpoints groups of students who may be underrepresented in certain programs (e.g., girls in STEM or low-income students in work-based learning opportunities).
    Application: Implement recruitment and retention strategies that target these underrepresented groups.
  2. Tracking Student Performance- Helps monitor the success rates of
  3. >>>

It is important to make sure you add the appropriate weight to all the objectives on your assessments.

To keep Career and Technical Education (CTE) data secure and private, you should: follow established data privacy regulations, use strong passwords and encryption, limit data collection to what's necessary, educate students and staff on data privacy practices, regularly review and update security protocols, and only share data with authorized individuals with a legitimate need to access it; ensuring that all sensitive student information, like grades, attendance, and personal details, are protected from unauthorized access. 

Key practices to implement:

Compliance with regulations:
Understand and comply with relevant data privacy laws like FERPA (Family Educational Rights and Privacy Act) in the US,… >>>

To inform a CTE program of study, common sources of labor market data include: state workforce agencies, the Bureau of Labor Statistics (BLS) ONET database, state department of education data, local employer surveys, industry publications, and regional economic development organizations*; all providing information on current and projected job openings, skills required for specific occupations, salary ranges, and emerging trends within the local labor market. 

Key details about these sources:

State Workforce Agencies:
These agencies typically provide detailed labor market information at the state and regional level, including data on job openings, unemployment rates, and occupational projections. 

ONET Database (BLS):*
This… >>>

Peter Drucker’s quote, “You cannot improve what you do not measure,” underscores the importance of aggregate data in high-quality CTE programs. Data provides a foundation for understanding the strengths and areas for improvement within our programs. It helps us move beyond assumptions and focus on measurable outcomes to drive meaningful change.

Aggregate data offers several key benefits:

  • Informed Decision-Making: Data reveals which programs are thriving and which may need targeted improvements. For example, low certification pass rates might indicate a need for enhanced test preparation resources.
  • Equity and Access: Monitoring demographic trends helps ensure that all student populations have access
  • >>>

Qualitative data that could be collected on a CTE program includes student and employer interviews, focus group discussions, observations of classroom interactions, student reflections, and feedback on work-based learning experiences, which can be used to understand student perceptions, identify areas of improvement in curriculum, teaching methods, and program alignment with industry needs, ultimately leading to better student outcomes and program adjustments based on real-time feedback.  
 
Specific examples of qualitative data to collect: Student perspectives:  

  • Perceptions of the program's relevance to their career goals  
  • Satisfaction with the quality of instruction and learning materials  
  • Challenges faced during
  • >>>

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