Strategic Plan
2020-2024 CNMI State Longitudinal Data System Strategic Plan
The CNMI’s State Longitudinal Data System mission to support effective educator data use, the 2020-2024 CNMI SLDS Strategic Plan reflects the growing need for high quality data from a multitude of data systems to inform policies and practices that support students from early childhood through K-12 and beyond.
Our Vision
To develop one of the most distinguished data systems in the Pacific that will transform the way we use education data in the Marianas.
Our Mission
The CNMI State Longitudinal Data System brings together a wide range of data so teachers and childcare providers, parents, and policymakers in the CNMI may make data-informed decisions that support the educational progress of our children and analyze their long-term outcomes as they exit the K12 system and enter the workforce or higher education.
Priority Areas & Goals
Priority Area 1: Establish a highly effective Statewide Longitudinal Data System (SLDS)
As of September 2020, the CNMI SLDS hired a Project Director, Data Governance Coordinator and Admin Officer to carry out the tasks and outcomes to support, maintain, and enhance the CNMI SLDS.
2020
- Hired a Project Director, Data Governance Manager and Project Specialist (formerly Administrative Officer).
2022
- Hired a Technical Manager and Data Privacy Specialist to support to the growing technical needs of the program and data infrastructure.
Stakeholders will engage in the development and successful use of the SLDS to help mitigate risks, increase perceived and actual value to the users, and subsequently drive long-term sustainability.
2021
- Key Stakeholders were identified, selected for inclusion in the SLDS and their roles and responsibilities were articulated to ensure the prioritization of the CNMI SLDS’ need
2022
- A Stakeholder Engagement Plan was developed to inform the development, implementation and use of the SLDS products.
Using longitudinal education data from early childhood to high school graduation will help educators, policy-makers, researchers, and the public understand what works for student success. A commonwealth-wide longitudinal data system that will manage, analyze, disaggregate, and use individual student data helps to ensure the resulting data products are relevant to understandign the most pressing issues facing the state.
2020
- DBDriven, an information technology service provider, signed a 2.5-year contract with PSS to develop a P12 (early childhood to 12th grade) data warehouse that can be scaled up to a P20W (early childhood to college and workforce) data warehouse.
A data architecture is data strategy, or master plan, that outlines the policies, business requirements, and standards governing data flow and management within PSS. The data architecture includes the current state of data assets, data requirements for the desired future state, data inventory and system design to effectively and efficiently collect, store, and provide data to end users.
2020
- Conducted a data architecture self-assessment.
2021
- Identified SLDS end-users and their information needs, which included the timeliness of the data, accessibility of the data, and data content requirements.
2022
- Conducted a data-needs discovery and analysis (data crosswalk) for all P-12 programs and departments.
- Considered long-term goals and future needs for unique identifiers across multiple systems (included in the program’s sustainability plan).
A phased approach to developing the SLDS ensures IT processes are integrated into the system design and considered throughout the lifecycle of data assets and processes.
2021
- Developed a process to that ensures early childhood data is linked to K-12 data, and can be linked to other sectors such as postsecondary and workforce when the system matures into a P20W.
- Established a process for managing the multiple unique identifiers as they are integrated or created across systems.
2022
- Setup SLDS environment and mapped source data to SLDS.
A phased approach to developing the SLDS ensures IT processes are integrated into the system design and considered throughout the lifecycle of data assets and processes.
2020
- Conducted an annual review to ensure compliance with program policies and all applicable federal and local laws.
2021
- Conducted an annual review to ensure compliance with program policies and all applicable federal and local laws.
2022
- Conducted an annual review to ensure compliance with program policies and all applicable federal and local laws.
- Planned, designed, produced, and implemented data quality processes, including establishing a critical data issues process to identify, prioritize, and resolve barriers to data quality and use.
- Implemented a privacy plan to ensure data residing in the SLDS is protected according federal and local laws.
An early warning system uses research-based indicators to identify students at risk of failing to meet key educational milestones, and in this case, reading proficiently by grade 3. By identifying students early, educators can target interventions and supports to help students to achieve readiness and success.
2020
- Engaged stakeholders to identify and prioritize needs for early warning system.
- School data teams were formed, which include:
- School Administrator
- Counselor
- Classroom Teachers
- Reading Supports (e.g., Literacy Coach, Tutors)
- English Language (EL) Teachers
- Special Educaiton Teachers
- Registrar
- School data teams were formed, which include:
- Developed reporting requirements including preliminary analysis to identify appropriate indicators.
- Early Warning indicators include:
- STAR Reading/Early Literacy: students score in “Urgent Intervention.”
- Attendance: 6 or more absences.
- Behavior: at least one office referral.
- English Langugage Arts Grade: Score of 1 or 2.
- Retention: Student held back at least one grade level.
- Mobility: Student attended more than one school year between K-2.
- Early Warning indicators include:
- Conducted a pilot launch of system for early adopters:
- Garapan Elementary School
- Kagman Elementary School
- Koblerville Elementary School
- San Vicente Elementary School
- Sinapalo Elementary School
2021
- Conducted an evaluation on overall student progress and system effectiveness for the EWS pilot
- Early adopters fully implemented the EWS for at least one grade level in K-2.
- Conducted a pilot launch of system for new schools:
- GTC Elementary School
- Oleai Elementary School
- Tinian Elementary School
- WSR Elementary School
2022
- Conducted an evaluation on overall student progress and system effectiveness for Year 1 of the EWS.
- All elementary schools fully implemented the EWS for grades K-2 during SY 2022-23.
Stakeholders will receive appropriate training to carry out the specific tasks to establish the desired outcomes and objectives. These trainings include the transition from the legacy software to the new Student Information System (SIS), and knowledge transfer for technical staff who will be responsible for supporting the SLDS.
2021
- SLDS technical assistance and support plan was developed with data steward input.
2022
- SIS training provided for system end-users. Note: All SIS training was hosted and facilitated by the Department of Accountability, Research & Evaluation.
The SLDS sustainability plan is designed to support the continuity of SLDS program offerings and opportunities through broad and deep stakeholder support, widespread use, and long-term commitments fo funds and staff, and it provides a return on investment.
2022
- Conducted an SLDS self-assessment to identify areas of strength and areas in need of improvement, as well as short- and long-term goals for: 1. Stakeholder support; 2. SLDS Use; 3. Financial Support; 4. Return on Investment
Priority Area 2: Shifting the use of data from compliance to accountability and strategic instructional usage.
The SLDS program will train stakeholders to increase the organization’s capacity to identify and intervene for students who were off track to reading proficiently by grade 3.
2021
- Evaluated the effectiveness, impact, and use of the Early Warning System for the pilot.
- Revised training and other supports for Early Warning System based on evaluation results of the pilot.
2022
- Evaluated the effectiveness, impact, and use of the Early Warning System for Year 1.
- Revised training and other supports for Early Warning System based on evaluation results of Year 1.
One element of quality teaching for improving student outcomes is effective data use; however, policies have not gone far enough to promote practices to ensure that educators know how to access, analyze, and use data appropriately.
2022
- Developed training pathway on data policy and process, access, analysis, and using data appropriately for the EWS.
Stakeholders across the CNMI hope to see the SLDS continue to grow to advance critical analytic initiatives, uncover valuable insights, and build a strong data culture in partner organizations.
2020
- The SLDS Project Director, Annette Pladevega-Sablan, was accepted to Harvard University’s Center for Education Policy & Research (CEPR) Strategic Data Project (SDP). Dr. Pladevega-Sablan is the first participant from the CNMI to be accepted inot the SDP Program (a two-year fellowship).
- Dr. Pladevega-Sablan received training in Data Governance and Management, Education Policy Leadership, Descriptive Analytics, Data Visualization and Communication, and Change Management.
- The CNMI Public School System was accepted as a Partner Institution in CEPR’s Strategic Data Project.
2021
- Through the SDP Program Dr. Pladevega-Sablan received training in Predictive Analytics, Experimental and Quasi-experimental Design, Calculating Cost Effectiveness, Dashboarding and Advanced Visualization, and Sustaining Change.
2022
- Dr. Pladevega-Sablan developed an EWS Playbook, a best practices guide focused on how to integrate best practices on data use drive instructional changes.