Essential Data Elements

1. Employment Data on Individual Teachers

Many of these data elements and those identified in 2. below are the most essential to state efforts to track the supply, demand, and basic adequacy of their teacher workforce and to identify attrition and retention patterns. The salary data facilitate the comparison of educational costs between schools and districts across the state. Unless otherwise indicated, all of these data are assumed to be longitudinal – i.e., to be collected on an ongoing basis over time:

• Current year's teaching status, including school and specific course assignments
• Previous years' teaching status, including school and specific course assignments for each individual year
• Status as mentor or master teacher (if not already included in licensure categories)
• Percentage FTE assigned to teaching and non-teaching responsibilities
• Compensation – including base salary and additions
• Current and historical employment
  

  Note

  1

  This facilitates the identification of entry, re-entry, and attrition patterns that may provide important information for developing various kinds of incentives. It would require a state’s ability to track licensed teachers not only through the teacher employment database but also through a comprehensive employment and retirement database. Few, if any, states currently have that capacity.
  outside of teaching¹ (including salary)

2. Teacher Licensure and Certification Data on Individual Teachers

Maintaining these data is essential for tracking the state-issued credentials of teachers – a

Note
2
The Teacher Quality and Teacher Licensure unit of this project contains a detailed discussion of the role of teacher licensure and certification.
baseline indicator ² of teacher adequacy – and comparing the baseline quality of teachers between schools and districts.
• Licensure examination
  

  Note

  3

  Several relatively recent research studies indicate that teachers who have had to take licensure examinations repeatedly before passing them may be less effective than teachers who pass the examinations more readily. See Presley, J. B., White, B. R., & Gong, Y. (2005). Examining the Distribution and Impact of Teacher Quality in Illinois. Carbondale, IL: Illinois Education Research Center.; and Boyd, D., Lankford, R. H., Loeb, S., Rockoff, J., & Wyckoff, J. (2007). The Narrowing Gap in New York City Teacher Qualifications and its Implications for Student Achievement in High-poverty Schools. Albany, NY: Teacher Policy Research.

  This list of data elements is slightly expanded from the recommendations of Voorhees and Barnes. If state licensure agencies do not collect these data on teachers transferring in from other states, however, it is likely to be inaccessible.

  history and results³, including attempts and scores for all general and specialty area licensure examinations
• Date of initial licensure
• Licensure renewals, additions, and advancements and dates these were received
• Subject certification(s) and/or endorsements and dates received and renewed
• National Board for Professional Teaching Standards certification and dates received and renewed (if applicable)
• 

  Note

  4

  This list of data elements is slightly expanded from the recommendations of Voorhees and Barnes. If state licensure agencies do not collect these data on teachers transferring in from other states, however, it is likely to be inaccessible.
  Out-of-state transfer information⁴: Years teaching out-of-state; undergraduate and graduate institution(s) and degree(s) received; subject major(s) and minor(s); preparation program attended and completion date; prior licenses, certifications, and endorsements (including dates received and renewed)

3. Professional Development Data on Individual Teachers

Maintaining these data facilitates understanding of the continuing education activities of a state's teacher workforce. The data may provide an indication, in particular, of whether or not a state's science teachers are maintaining currency in their ever-changing fields – and whether there appears to be a disparity between districts in the currency of their teachers' knowledge. Teachers' participation in continuing education also may be linked to retention and attrition patterns, a link the collection of the data identified here and in 1. above makes it possible to probe:

• Participation in mentoring and induction programs
• Participation in continuing education and professional development
• Advanced degrees received, including coursework

4. Teacher Preparation Data

Maintaining these data – which most logically would be collected by each teacher preparation program – increases understanding of the current quality of a state’s teacher workforce and the potential for improving it. The data enable states, districts, or individual teacher preparation institutions and K-12 schools to probe the possible relationship between differences in teachers’ educational backgrounds and disparities in the performance of their pupils. Aggregated by preparation program, these data also facilitate understanding of program outcomes (e.g., their success in preparing minority teachers), assessment of program effectiveness, and comparison of baseline program quality:

• Data on individual
  

  Note

  5

  Not all, candidates enrolled in preparation or certification programs will complete the programs, obtain licensure, and enter the classroom, but it is valuable to collect data on all of them.
  teacher candidates⁵
  • Demographic information – age, gender, race/ethnicity
  • Institution and specific program attended for teacher certification (e.g., 2-year program in the college of education, special program in the college of natural sciences, post-baccalaureate certificate program, district residency program, etc.)
  • Undergraduate major(s), and minor(s)
  • Field of graduate study if license pursued via a graduate degree program
  • GPA in major (or in field(s) of certification) and overall
  • Date of graduation from teacher preparation program
• Aggregated data on individual teacher preparation programs, whether traditional or alternative
  • Number of students who enter the program each year
  • Number and percentage of entering students, by demographic, who continue in and complete the program each year
  • Pass rate and distribution of student scores on licensure examinations
  • 

    Note

    6

    This is not a data element called for in Voorhees and Barnes, but it is used by some university-based preparation programs to assess the academic talent of their students and may be an indicator of a problem if the GPA of teacher candidates is significantly lower than that of other students in the same major. See, for example, the data collected by the UTeach program at the University of Texas at Austin.
    GPA of teacher program graduates in their science and mathematics major in comparison to GPA of other students at the institution in the same major ⁶

5. Non-Teacher Data

Linking these data to data on individual teachers, particularly their teaching assignments, makes it possible to attempt to assess teachers' effectiveness on the basis of their students' academic performance. It also opens the possibility of looking for correlations between teachers' preparation history or other factors in their background and their students' performance:

• School characteristics, including student SES profiles and class size, ideally specifiable for each individual class taught
• Student performance data for each individual student,
• Identification of individual students' classrooms or teachers