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Direct linkJeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
Peer reviewed
Download full textKautz, Tim; Feeney, Kathleen; Chiang, Hanley; Lauffer, Sarah; Bartlett, Maria; Tilley, Charles – Regional Educational Laboratory Mid-Atlantic, 2021
The District of Columbia Public Schools (DCPS) has prioritized efforts to support students' social and emotional learning (SEL) competencies, such as perseverance and social awareness. To measure students' SEL competencies and the school experiences that promote SEL competencies (school climate), DCPS began administering annual surveys to…
Descriptors: Social Emotional Learning, Educational Environment, Student Surveys, Teacher Surveys
Lin, Shuqiong; Luo, Wen; Tong, Fuhui; Irby, Beverly J.; Alecio, Rafael Lara; Rodriguez, Linda; Chapa, Selena – Cogent Education, 2020
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…
Descriptors: Student Educational Objectives, Teacher Evaluation, Data Use, Academic Achievement
