Exploring the Need for Data-Driven Decision Making in CTE

By Daggett, Bill | Techniques, September 2007 | Go to article overview

Exploring the Need for Data-Driven Decision Making in CTE


Daggett, Bill, Techniques


THE CARL D. PERKINS CAREER AND TECHNICAL Improvement Act of 2006, which went into effect on July 1, is more than a reauthoriration of the 1998 Perkins law. The expanded law emphasizes the integration of more rigorous and relevant academics with technical instruction. There also is a new focus on applied learning, higher expectations for students, and career and technical education (CTE) program accountability.

The emphasis on accountability is significant. CTE programs must now develop and enhance information systems to collect and analyze data on secondary and postsecondary academic and employment outcomes. Achievement gaps also must be identified and quantified at the secondary level. In addition, the law requires that CTE programs meet state performance levels, and technical skills must be assessed to all aspects of industry standards.

Now more aligned with the No Child Left Behind Act, the Perkins law moves CTE toward a systematic approach to measuring student learning, setting goals, monitoring progress and recognizing successes--an approach that is at the heart of what the International Center for Leadership in Education promotes and practices.

Data-Driven Decision Making

Some education initiatives are carefully constructed, viewed appropriately through the lens of a school's mission, driven by data, and accountable to multiple stake holders. Other initiatives, however, are not so meticulously conceived. Rather than allowing data to drive goal setting and decision making, some schools are still guided by good intentions, hunches and impressions. Often, these schools inadvertently lose sight of learners' needs as they struggle to ensure compliance with state regulations.

The Learning Criteria to Support Rigor, Relevance, and Relationships is a tool developed by the International Center that supports school improvement processes through a stepwise data collection and analysis process. In the hands of a thoughtful and broad-based school leadership team, the Learning Criteria helps a school clarify its mission, prioritize problems and interventions, and critically review school performance. CTE administrators and educators need to make sure that there are data indicators in the Learning Criteria areas that relate to CTE programs and activities.

An Overview of the Learning Criteria

The Learning Criteria framework is arranged in four data categories that educators can use to determine the success of their high schools in preparing students for current assessments as well as for future careers and life roles and responsibilities. A school should have data indicators in each of the categories listed. At least one indicator in each category should apply to a school's entire student population.

1. Core Academic Learning refers to achievement in the core subjects of English language arts, mathematics, science and other subjects identified by the school. Sample data indicators include:

* percentage of students meeting proficiency level on state tests (required);

* average scores on ACT/SAT/PSAT tests;

* achievement levels on standardized tests other than state exams;

* percentage of students requiring English/ mathematics remediation in college;

* follow-up surveys of graduates' academic achievements; and

* percentage of students graduating high school in four years.

The International Center believes that core academic learning and state testing are essential, but not adequate. It defines the problem, not the solution, and predominantly represents basic learning in the content areas.

2. Stretch Learning refers to the demonstration of rigorous and relevant learning beyond minimum requirements through participation and achievement in higher level or specialized courses. Sample data indicators include:

* percentage of students completing career majors or CTE programs;

* number of credits required to graduate;

* average number of credits earned at graduation;

* interdisciplinary work and projects, such as a senior exhibition;

* participation/test scores in International Baccalaureate courses;

* average number of college credits earned by graduation through dual enrollment;

* enrollment in advanced mathematics or science courses;

* enrollment in Advanced Placement (AP) courses, scores on AP exams, and the percentage of participants achieving a score of three or higher on a five-point scale;

* four or more credits in a career area;

* four or more credits in arts; and

* achievement of specialized certificates (e. …

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