Data-Based Student Learning Objectives for Teacher Evaluation
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| Title: | Data-Based Student Learning Objectives for Teacher Evaluation |
|---|---|
| Language: | English |
| Authors: | Lin, Shuqiong, Luo, Wen, Tong, Fuhui (ORCID |
| Source: | Cogent Education. 2020 7(1). |
| Availability: | Cogent OA. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2020 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Early Childhood Education Preschool Education |
| Descriptors: | Student Educational Objectives, Teacher Evaluation, Data Use, Academic Achievement, Growth Models, Predictive Validity, Reliability, Scores, Preschool Teachers, Grouping (Instructional Purposes), School Districts, School District Size, Urban Schools, Bilingual Education, English (Second Language), Hispanic American Students, Preschool Children |
| Geographic Terms: | Texas |
| Assessment and Survey Identifiers: | Bracken Basic Concept Scale |
| DOI: | 10.1080/2331186X.2020.1713427 |
| ISSN: | 2331-186X |
| Abstract: | Student learning objectives (SLOs) have become an increasingly popular tool for teacher evaluations as an alternative to Value-added Models (VAMs). However, the use of SLOs faces two major challenges. First, the target setting is mostly subjective and arbitrary. Second, there is little evidence on the reliability and validity of the tool. In this paper, we proposed three data-based SLO target-setting models: split, banded, and class-wide models. The data-based approach ensures that the targets set for students are challenging yet realistic and achievable. Using data of 176 pre-kindergarten teachers and two cohorts of students from a large school district in Texas, we investigated the reliability and predictive validity of teachers' SLO scores. Results indicated that teachers' SLO scores had moderate to high consistency across different subtests, and moderate stability over time. Teachers' SLO scores were also demonstrated to be useful in predicting future students' achievement, which supported the predictive validity of the tool. |
| Abstractor: | As Provided |
| Entry Date: | 2021 |
| Accession Number: | EJ1282644 |
| Database: | ERIC |
| Abstract: | Student learning objectives (SLOs) have become an increasingly popular tool for teacher evaluations as an alternative to Value-added Models (VAMs). However, the use of SLOs faces two major challenges. First, the target setting is mostly subjective and arbitrary. Second, there is little evidence on the reliability and validity of the tool. In this paper, we proposed three data-based SLO target-setting models: split, banded, and class-wide models. The data-based approach ensures that the targets set for students are challenging yet realistic and achievable. Using data of 176 pre-kindergarten teachers and two cohorts of students from a large school district in Texas, we investigated the reliability and predictive validity of teachers' SLO scores. Results indicated that teachers' SLO scores had moderate to high consistency across different subtests, and moderate stability over time. Teachers' SLO scores were also demonstrated to be useful in predicting future students' achievement, which supported the predictive validity of the tool. |
|---|---|
| ISSN: | 2331-186X |
| DOI: | 10.1080/2331186X.2020.1713427 |
