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Career and Technical Educators Using a Data Driven Improvement Model

Career and Technical Educators Using a Data Driven Improvement Model. Collection of data: NOCTI pretest scores Fall semester grades Fall semester attendance Fall semester LASSI results. Career and Technical Educators Using a Data Driven Improvement Model. NOCTI Pretest scores :

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Career and Technical Educators Using a Data Driven Improvement Model

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  1. Career and Technical Educators Using a Data Driven Improvement Model Collection of data: NOCTI pretest scores Fall semester grades Fall semester attendance Fall semester LASSI results

  2. Career and Technical Educators Using a Data Driven Improvement Model NOCTI Pretest scores: • 16 students scored above the national average in 7 areas, below the national average in one area. (5 areas without national average data) • In the area scoring below the national average, 10 students scored below the national average.

  3. Career and Technical Educators Using a Data Driven Improvement Model Fall semester grades: • In 5 courses, 83.8% of students who completed the courses (attended for the full semester) earned a grade of a C or higher. • (My personal goal had been 91%)

  4. Career and Technical Educators Using a Data Driven Improvement Model Fall semester attendance: • 137 students enrolled in 5 courses • 2 on campus courses, 3 online courses • (each course met for 8 weeks-an experiment) • 18 withdrew • 58 never attended (42%!!)

  5. Career and Technical Educators Using a Data Driven Improvement Model LASSI test includes 10 areas- Anxiety Attitude Concentration Information Motivation Self-testing Selecting idea Study aids Time management Test strategy

  6. Career and Technical Educators Using a Data Driven Improvement Model • The LASSI pretest was given on 9/6/11 • First time, 8 week course time frame • The two lowest scoring areas were motivation and attitude • Intervention/lecture given 9/12/11 • Post test given 10/13/11 • 68% showed improvement in or or more areas

  7. Career and Technical Educators Using a Data Driven Improvement Model Analyzing the data: • NOCTI scores-area scoring below the national average was child development-cognitive development • Another area scoring above the national average but second lowest in average of the group-diversity in the classroom

  8. Career and Technical Educators Using a Data Driven Improvement Model Final grades: More than the majority of students who completed the courses achieved a grade of a C or higher.

  9. Career and Technical Educators Using a Data Driven Improvement Model LASSI results: A high percentage of students lacked motivation and/or displayed a lack of attitude towards attending. When the same group retested one month later (after a discussion on time management, attitude, employment, passion for what they want to do) both areas-motivation and attitude dramatically increased.

  10. Career and Technical Educators Using a Data Driven Improvement Model Action plan: • Identify MN Core competencies that match with lower NOCTI scores and then which child development courses include those components. • Review instructional delivery, assignments, and course assessments-demonstrations, quiz, tests, etc. for these components/competencies areas.

  11. Career and Technical Educators Using a Data Driven Improvement Model

  12. Career and Technical Educators Using a Data Driven Improvement Model • Triangulate data to identify relationship of attendance, LASSI results, semester grade and NOCTI score. • Schedule department meeting to discuss changes, if needed, to delivery, emphasis of concept/competency, and assessment competencies. • Determine priorities for addressing LASSI results.

  13. Career and Technical Educators Using a Data Driven Improvement Model Action plan: • First week of instruction-does the student really belong in the class. Many (42%) may not have known what they were doing when they registered because they didn’t show up or withdrew at some point. • Plan discussion of time management, attitude, motivation, etc. in first week of the course.

  14. Career and Technical Educators Using a Data Driven Improvement Model • Emphasis on cultural diversity and cognitive processes in all child development courses. • Create additional audio, video, and project-based assignments to accommodate all learners. • Assess these two components in a variety of ways, at different points within each course, within the semester.

  15. Career and Technical Educators Using a Data Driven Improvement Model • Do not offer 8 week course time frame-too short, students don’t get started, get overwhelmed, withdraw, or fail. • Schedule 15 week hybrid courses with on campus meeting once/week, remainder online. (done)

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