Identifying and Monitoring Students' Learning Needs With Technology
Abstract
This article presents initial findings from an evaluation research study of the implementation of a Web-based decision support tool, the Quality School Portfolio (QSP), developed at the National Center for Research on Evaluation, Standards, and Student Testing (CRESST) at the University of California, Los Angeles (UCLA). The study focused on users' experiences with the training for and implementation of QSP. Data were collected by telephone interviews. The results show that QSP provided educators with enhanced access to more extensive and broadly founded student data and with the ability to analyze student data to identify at-risk students. Additionally, QSP was found to promote collaboration and shared planning among educators. It is concluded that technology tools, which can facilitate the analysis and reporting of educational data, have opened up the prospect of timely identification of at-risk students and interventions to meet their educational needs. Tools like this also support sound assessment practices, providing opportunities for frequent assessment and other evidence of competency beyond standardized testing.
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Real-time progress tracking of students facilitates the prompt identification of educational issues, allowing for customized guidance and interventions.
“the findings align with previous research, which indicates that real-time progress tracking of students facilitates the prompt identification of educational issues, allowing for customized guidance and interventions (Chen et al., 2005;Minović & Milovanović, 2013).”
From Data-Driven Decision-Making through Real-time Student Progress Monitoring: Academic Administrators Perspectives (2025) · cites this paper as Chen et al., 2005
Some studies found that the existence of professional learning communities and a culture of collaboration facilitate DDDM.
“Some studies also found that the existence of professional learning communities and a culture of collaboration facilitate DDDM (e.g., Chen, Heritage, and Lee, 2005; Holcomb, 2001; Love, 2004; Symonds, 2003).”
From Making Sense of Data-Driven Decision Making in Education: Evidence from Recent RAND Research (2006) · cites this paper as Chen, Heritage, and Lee, 2005
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- Authors
- Chen, E., Heritage, M., & Lee, J.
- Venue
- Journal of Education for Students Placed at Risk (JESPAR)
- Publisher
- Informa UK Limited
- Published
- 2005-07
- Volume
- 10
- Issue
- 3
- Pages
- 309-332
- ISSN
- 1082-4669 (ISSN-L)
- 1532-7671
- OpenAlex
- W2051774141
- Cited by
- 93
- References
- 37
- Citations by year
- 2026: 1 · 2024: 4 · 2023: 2 · 2021: 4 · 2020: 4 · 2019: 3 · 2018: 4 · 2017: 5 · 2016: 3 · 2015: 5 · 2014: 9 · 2013: 9 · 2012: 5
- FWCI
- 14.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Education for Students Placed at Risk (JESPAR) (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Information Systems › Educational Management and Quality
- Keywords
- web-based decision support tool, at-risk students, student learning needs, educational data analysis, teacher collaboration, shared planning, educational technology implementation, frequent assessment, competency-based assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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