Here are five ed-tech considerations for a successful Student Learning Objectives program.
Student Learning Objectives (SLOs) have gained tremendous momentum in K-12 education over the last 15 years and hold great promise for improving student learning.
An SLO is an academic goal for a student or a group of students that is focused on the most important course content. SLOs are set at the beginning of a course, after a teacher has reviewed historical student data and administered a baseline assessment. This specific, measureable objective for student academic growth is tracked through formative assessment throughout the year, as the educator engages in aligned professional development and implements strategies designed to improve student learning. At the end of the instructional interval, the student is assessed through summative assessment.
In several states—including Florida, Maryland, New Jersey, New York, and Ohio—Student Learning Objectives are now being used in educator evaluations as well. The number of students who meet or exceed the stated objective is used to calculate an effectiveness rating for the educator. This rating is then used as one of several measures for educator performance evaluation. Evaluation results are used to make decisions regarding pay, placement, tenure, employment, and professional development.
Most states and districts place a great deal of emphasis on the development of Student Learning Objectives. However, little emphasis typically is given to building the ed-tech infrastructure to support the implementation of these learning objectives, or to managing crucial tasks that must be accomplished for thousands or tens of thousands of SLOs to be implemented with fidelity.
Here are five ed-tech recommendations to prepare for a full-scale SLO implementation:
1. Develop a solution for tracking assessments and data.
In its most constrained format, with one baseline assessment and one summative assessment for each course, most K-12 districts will require a data system that can handle at least 500 unique assessments. Districts that require multiple measures or that allow for a wider range of assessments have an exponentially larger management challenge.
Further, each course has multiple teachers who each may select a slightly different content focus for their SLO, resulting in thousands of assessment configurations that must be managed, analyzed, and reported upon. Student results for each assessment and item groupings must also be maintained. A data system that can house this information in a relational database and provide an intuitive user interface is essential for this volume of information management.
2. Devise a method for managing data associations at scale.
As stated above, each Student Learning Objective is associated with a baseline measured by at least one pre-assessment, and a student growth target measured by at least one post-assessment. A growth algorithm connects these two assessments and identifies the percent change or static change required to meet the SLO.
To ensure an SLO has practical use, content of the pre- and post-assessments should be aligned, and educators should easily be able to view assessments and their attributes side by side. To facilitate this work, a district needs an ed-tech solution that allows for selection of compatible pre- and post-assessments, matching of items from pre- to post-assessment based on content and rigor, and simple use and customization of growth algorithms.
3. Facilitate workflow processes to streamline management.
As Student Learning Objectives are implemented, pre- and post-assessments will be administered in varied ways. District data systems should allow for plain paper scanning, selected response scanning, and integrated online testing, so records are maintained and scores are available automatically for analysis.
For assessments not scored within the district’s data platform (such as standardized test scores), the system should have the capacity to load results in multiple formats, including XML, API, or a common flat file layout. Otherwise, external results will have to be processed manually, which is time consuming and can compromise data integrity.
Results should be housed in a relational database that provides an administrative interface with access to individual student data points as well as SLO metadata. SLO metadata are the attributes associated with the given Student Learning Objective, such as the growth algorithm, students included in the SLO population, baseline scores, and derived target scores.
Finally, the ed-tech system should have the capability to roll up student results into a final SLO score for each educator and integrate this score into multi-measure evaluations, producing a final evaluation rating for educators.
4. Create an audit trail.
When Student Learning Objectives are used for evaluation purposes, all administrative actions with SLO attributes should be logged to ensure data integrity and establish an audit trail. When educators design and submit SLOs to their evaluator for approval, and again when they meet at mid-interval, there should be a clear audit trail showing that rosters have been validated, and assessments, algorithms, and targets have been officially approved. Changes made to any SLO attributes should be clearly logged in the database with a username and timestamp.
An SLO system utilized in educator evaluation must be legally defensible; accurate recordkeeping and provisions for ensuring data integrity are important elements of risk avoidance. A district’s data infrastructure should facilitate this level of accuracy and auditability.
5. Refine capabilities for advanced reporting.
Because Student Learning Objectives can be used for evaluation purposes, the system must provide options for creating SLO-level compliance reports for teachers, principals, district administrators or the state. Compliance reports allow for spot-checking of SLOs across schools and districts to ensure SLOs are being approved in a timely fashion, are aligned to targeted content, and are rigorous for all student populations.
Implementing ed-tech tools
As more states turn to Student Learning Objectives to measure student growth and use the results to calculate effectiveness ratings for educators, there is a rapidly growing need for ed-tech tools that can help educators streamline the SLO process. One tool districts are using to create, manage, and monitor SLOs is the SLO Module from Performance Matters. With this tool, educators can build or select the SLO assessment, choose the growth algorithm, set the target score for each student or group, and then access pre- and post-assessment results under each SLO. With the tool’s automatic calculations, they can see whether or not each student met the SLO, as well as the overall percentage of students achieving the SLO by class or by course. These data then can be used to group educators into the appropriate ratings category on the SLO portion of their annual performance reviews.
Improving student achievement and focusing educator growth
Student Learning Objectives hold great promise for improving student achievement and focusing educator growth. They provide an opportunity for educators to participate in their own evaluations and for student growth to be incorporated into educator evaluations in non-tested grades and subjects. Developing a coherent infrastructure to manage, administer, and report SLOs will be essential to ongoing success as SLOs are brought to scale and integrated into assessment frameworks.
By developing solutions for tracking assessments and data, devising a method for managing data associations at scale, facilitating workflow processes that streamline management, creating an audit trail, and developing capabilities for advanced reporting, districts and states will be prepared with the infrastructure necessary to implement a successful SLO program.
Kimberly Fleming, Ph.D., is the author of a new white paper titled, “Technology Considerations for a Successful Student Learning Objectives Program.” She is president and founder of Core Education LLC, a consulting firm focused on educator effectiveness.
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