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Record W2548672494

The Effect of School Improvement Planning on Student Achievement

2015· article· en· W2548672494 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePlanning and changing · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityAcademic achievementStudent achievementIntervention (counseling)Plan (archaeology)White paperPsychologyEffective schoolsStandardized testProcess (computing)Quality managementQuality (philosophy)Mathematics educationPolitical scienceEngineeringOperations managementComputer scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

Under the No Child Left Behind (NCLB) Act of 2001, schools identified as not making adequate progress are to submit a school improvement plan (SIP). SIPs were designed to close achievement gaps and raise levels of student achievement (White, 2009). Although not required for all schools, Fernandez (2009) found that by 2000, most schools were writing formal plans for improvement. States have recognized the importance of school accountability and are using student achievement and the process of school improvement planning as a method of distinguishing effective and ineffective schools (Phelps & Addonizio, 2006). Given the use of SIPs for decision making, it is critical to examine whether SIP quality is related to student achievement.A review of the literature on characteristics of effective SIPs indicates the importance of targeted areas for improvement, integration of specific intervention strategies, frequent monitoring of student data, and identification of persons responsible for implementation of each strategy (Fernandez, 2009; Reeves, 2004; White, 2009). Other areas necessary for systemic improvement, yet often missing from SIPs, include leadership strategies, data analysis techniques, decision making practices, and an evaluation of a school's readiness to change along with the process for improvement (Beach & Lindahl, 2004; Hall & Hord, 2011; Reeves, 2004; White, 2009). Without the integration of these steps and a frequent formal evaluation of the improvement process, sustained improvement is unlikely (Webb, 2007; White & Smith, 2010).School improvement efforts have been documented since the 1970s, and it is surprising that a clear agreement on exactly how to carry out the improvement efforts has yet to emerge (White & Smith, 2010). Despite recommendations on the content for SIPs, evidence suggests that plans often fall short. To date, there still is no required format for an SIP. Mclnerney and Leach ( 1992) and Webb (2007) have found, within the process of planning there is the chance that schools will set goals that are inappropriate or fail to meet specific subgroup needs. Additionally, if administrators only create a SIP because it is required (rather than because it is a valued process in a school), they are unlikely to build in effective strategies for achieving goals, or mechanisms for frequent monitoring of goal progress.Evidence of Effectiveness of SIPsGiven that SIPs are required in some cases, and that they have been used in decision making about schools, it is important to ask whether differences in quality correlate with student achievement. Only three of the studies have provided evidence on the effectiveness of school improvement planning. One study that examined the role of SIPs and student achievement was by Curry (2007). The study involved a content analysis of SIPs for 67 middle and high schools. The results showed significant negative correlations for student achievement with the number of math strategies found in plans and the number of writing operational action steps. These findings are consistent with Reeves' (2004) and White's (2009) recommendation to limit the number of goals and strategies.Two additional studies were more closely related to the current study. Reeves' (2011) planning, implementation, and monitoring (PIM) study and Fernandez's (2009) study on effectiveness of school improvement plans provide a framework for the current study. Both studies used similar rubrics to examine specific characteristics of SIPs in an effort to quantify the plans' effectiveness. The PIM study (Reeves, 2011) included 2,000 schools in the United States and Canada using achievement data for more than 1.5 million students. The participants in this study represented a very diverse group including both urban and rural districts spanning levels from elementary to high school. The study included double-blind reviews of SIPs in an attempt to see what components of a plan focusing on leadership practices, could be associated with increases in student achievement. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.112
GPT teacher head0.439
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it