Standard 9 - Assessment of Candidate Competence - PowerPoint PPT Presentation

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Standard 9 - Assessment of Candidate Competence
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Standard 9 - Assessment of Candidate Competence

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  1. Standard 9 - Assessment of Candidate Competence • Candidates preparing to serve as professional school personnel know and demonstrate the professional knowledge and skills necessary to educate and support effectively all students in meeting the state-adopted academic standards. Assessments indicate that candidates meet the Commission-adopted competency requirements, as specified in the program standards.

  2. Types of Data Used in Biennial Reports, 2008-09

  3. Background • Staff reviewed 155 separate program reports representing more than 35 institutions • Biennial reports submitted in the fall of 2008-09 represented every kind of credential program approved by the CTC • The most frequently reported credential programs were the single and multiple subjects • This report describes the types of data reported for MS/SS and for education admin programs.

  4. Reporting the Data • Programs have the option of deciding how to organize, report and analyze data. • Some programs reported MS data separately from SS, whereas others reported data from the two programs together. • Similarly, some programs reported preliminary ed admin program data separately, whereas others reported the prelim. and professional ed admin data together.

  5. Understanding the Count • Staff made notes in the feedback form for every program in every institution that submitted reports. Some of those notes were pretty cryptic. The tables represent our best attempts at categorizing data in meaningful ways. • Data were organized to identify when, in the program, the assessment was performed (e.g., pre-student teaching, at the end of student teaching). • Every type of data from every report was counted as a single example.

  6. Understanding the Count • Multiple sets of one type of data were counted as one example (e.g., grades from four courses in the same program). • Data from one course, pre-student teaching observations, and student-teaching observations from the same program were counted as three examples of data. • Grades from one course reported in one program at an institution and grades from one course reported in a second program at that institution were counted as two examples.

  7. How to Use This Information • As we discuss the tables: • Remember that types of data transcend program type. A type of data used in a MS program (e.g., pre-student teaching observation) can model a type of data appropriate for a school nursing credential program. • Identify whether you currently use instruments similar to those on the tables. • Notice who does the assessment; faculty member, candidate, clinic supervisor, etc.

  8. How to use this information • If one of the instruments suggests something you might want to do, make note of it to share with your colleagues. • Similarly, if we identify problems with a particular type of data that’s similar to something you plan to report, please say something about that during the webcast. Be assured that you won’t be the only person with that kind of question.

  9. MS/SS Data Eight major categories of data • RICA and Candidate Knowledge represent tests or assignments designed to measure candidate content and pedagogical knowledge. • Grades were used as an indicator of candidate quality. • In virtually every example of these types of data, faculty were doing the assessments of candidate competence. • What problems do you see with using grades or candidates’ GPA to measure candidate competence or program quality? What problem could occur if an institution only used assessments from faculty?

  10. MS/SS Data • Candidate dispositions is a type of data that was reported by only six programs. • What does this type of data tell you about a program’s effectiveness? • Pre-student-teaching observations • These data were distinct from the other pre-student-teaching data because they used a standards-based rubric and were completed by faculty or district supervisor. • What makes these data more useful than previous types of data?

  11. MS/SS Data • The second most frequent type of data was student-teaching evaluations. • The majority of these evaluations were standards-based (TPE, CSTP, institution-developed) • The evaluations were completed by faculty or a district supervisor. • In some cases, these assessments were used to provide both formative and summative feedback to the candidate. • What qualities of these data make them particularly informative? How can they be used?

  12. MS/SS Data • Programs were required to report TPA data and nearly all did so. • Some programs reported the results of multiple test-taking attempts which could be analyzed to demonstrate remediation efforts. • Some programs utilized TPA standards (the TPEs) for assessing coursework and student teaching. What did this enable them to do? They were able to monitor candidate progress throughout the entire educator preparation program. They were able to measure program impact on candidate development.

  13. MS/SS Data • Program evaluation surveys were the most common type of instrument used. • Of these, the most common was the CSU exit survey and one year out survey. Some non-CSU institutions have adopted it or something similar. • The majority of individuals who provided this data were candidates (course evaluations) or program completers. • District-employed supervisors and employers provided some of the information.

  14. MS/SS Data, summary • Overall, candidates and program completers (former candidates) provided the majority of the information. Faculty provided the next greatest amount of information by evaluating coursework and half of the student teaching evaluations. District-employed supervisors had two means for providing feedback; student teaching evaluations and program evaluations

  15. MS/SS Data Summary • The most frequently used measures for MS/SS programs were evaluation surveys. • The second most frequently used were student teaching evaluations. • Assessments of candidate knowledge were the third most frequently used sources of data. • Questions or comments?

  16. Education Admin Data • The most common source of data was coursework and the most frequent rater was faculty. • Fieldwork was also a source of data but, unlike for teacher prep programs, there was little uniformity regarding the standards used. CPSELS was used and was MINDSCAPES.

  17. Education Admin Data • The second most frequent type of data was evaluation surveys. The surveys provided feedback on courses, programs, and practicum/fieldwork experiences. Unlike for teacher preparation programs, there are no institution-wide completer or employer survey efforts.

  18. Education Admin Data Summary • Ed Admin Programs have less institutional guidance for assessing candidate competencies or program effectiveness. • Types of data are more likely to reflect program-specific emphases and the needs of district partners or of individual candidates. In addition, the data are muddled because some programs integrated preliminary and professional ed admin program data. • Questions or comments?

  19. Using Individual-Level Data for Program Evaluation • Every type of data in the tables is individual-level data. Even evaluation survey data reflects the perspectives of one individual. • There are two main types of data we’ve discussed. Candidate competence and evaluation data. • Evaluation data, generally collected through surveys, is intended to be reported in the aggregate. • Also, evaluations generally reflect on something that’s in the past; reflect back on an experience or on the competencies of an individual trained by a program. • How might a program use candidate competency data for program evaluation?

  20. Using Individual-Level Data for Program Evaluation • If candidate assessment data measures competencies described in standards and can be summarized (quantitatively or qualitatively), it can be aggregated to the program level. • However, how do you know whether the competency level of the candidates is due to the program? • What if the candidates come into the program with those skills? What if your admission requirements screen for those skills? • One way to significantly reduce uncertainty about what results of candidate assessments mean is to measure candidate competencies multiple times.

  21. Using Individual-Level Data for Program Evaluation • How can you do that? • For example, assess candidates with a standards-based measure early in the program, to provide a baseline. • Prior to student teaching, measure those attributes again, using the same instrument or another instrument but against the same standards. • At the end of student-teaching, assess the candidates again. • Change between the scores gives an indication of program impact. This may not be true for any individual candidate, but across a group of candidates, it can be indicative of program quality. • In a minute, Cheryl will provide examples.

  22. Using Individual-Level Data for Program Evaluation • Gathering data from multiple stakeholders also ensures that your data realistically reflects your program. • As you plan your “system,” build in opportunities for multiple, informed stakeholders to provide feedback on candidate competencies and on program quality (evaluation). • If all data points in the same direction, you can make program modifications with confidence. If data points in different directions, you may need to reassess your instruments, or wait another year before modifying assessment and evaluation system. • Comments or questions?