# Student Data Dashboard > > - **Type:** Skill - **Install:** `agentstack add skill-jjuice22-classroom-ready-ai-skills-student-data-dashboard` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [JJuice22](https://agentstack.voostack.com/s/jjuice22) - **Installs:** 0 - **Category:** [Data & Analytics](https://agentstack.voostack.com/c/data-and-analytics) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [JJuice22](https://github.com/JJuice22) - **Source:** https://github.com/JJuice22/classroom-ready-ai-skills/tree/main/skills/student-data-dashboard ## Install ```sh agentstack add skill-jjuice22-classroom-ready-ai-skills-student-data-dashboard ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Student Data Dashboard ## Purpose Transform raw student assessment data into clear, actionable insights that drive instructional decisions — without requiring the educator to be a data analyst. Every output should answer the only question that ultimately matters: **What does this tell me about what students need next?** **Data philosophy**: Data is a means, not an end. Assessment data is a proxy for student understanding — useful when it informs instruction, harmful when it becomes the primary lens through which students are seen. --- ## What You Need From the User Gather before generating. Ask for anything missing: - **The data** (required): Pasted table, uploaded file, or verbal description - **Assessment tool name**: DIBELS 8th Ed, iReady, NWEA MAP, STAR, state test (SBAC, PARCC, MCAS, etc.), benchmark screener, progress monitoring probe - **Grade level(s)** and subject area - **Time point**: Beginning-of-year / Mid-year / End-of-year / Progress monitoring - **Purpose of this analysis**: Class-level instruction planning / Individual student IEP data / Team meeting presentation / Parent communication / Identifying intervention students? --- ## Data Interpretation Workflow ### Step 1 — Intake and Audit Before interpreting, check data integrity: - Are there missing data points? Flag them explicitly. - Are column headers clear? If not, ask for clarification. - Are all students/rows de-identified? If names are present, apply anonymization before proceeding (or prompt user to do so). - What is the assessment's unit of measure? (percentile, scaled score, lexile, grade equivalent, raw score, benchmark category) ### Step 2 — Score Translation Translate raw scores into educator-meaningful language: | Measure Type | Translation Approach | |---|---| | Percentile rank | "This score is higher than X% of students nationally at this time of year" | | Benchmark category | Use the tool's category language (Well Below / Below / At / Above) + what it means for instruction | | Scaled score / RIT | Compare to normative growth expectation for this time of year | | Grade equivalent | Use with caution — note limitations (GE of 5.2 does not mean student reads like a 5th grader) | | Lexile | Connect to text complexity ranges for grade level | **Common assessment reference norms** — See `references/assessment-norms.md` for benchmark cut scores, national norms, and growth targets for DIBELS, NWEA MAP, iReady, and STAR. ### Step 3 — Class-Level Summary For class or group data, generate: #### Distribution Summary ``` CLASS DATA SUMMARY — [Assessment] | [Grade] | [Date] Total students assessed: [N] Performance Distribution: Well Below Benchmark: [N] ([%]) ← Priority for Tier 2/3 intervention Below Benchmark: [N] ([%]) ← Monitor; some may need Tier 2 At Benchmark: [N] ([%]) ← Core instruction meeting needs Above Benchmark: [N] ([%]) ← Consider enrichment/extension Class median: [score] | National 50th percentile: [score] Class average: [score] ``` #### Instructional Grouping Suggestion Based on the distribution, suggest flexible instructional grouping: - Which students need intensive (Tier 3) support? - Which students need supplemental (Tier 2) support? - Which students are ready for enrichment? - What skill areas are most common across struggling students? #### Class-Level Instructional Implications What does this data collectively suggest about the core instructional program? - If >20% of students are below benchmark: consider core program review - If a specific subgroup shows consistent gap: name it and suggest targeted response - If high variance: differentiation and flexible grouping are the priority ### Step 4 — Individual Student Profile For individual or small group data: ``` STUDENT PROFILE — [Pseudonym] | [Grade] | [Date] Assessment: [Name] Score: [X] | Benchmark Category: [Category] Compared to grade-level benchmark: [X points above/below] Compared to last assessment: [+/- X] ([growth / concern / stable]) SKILL AREA BREAKDOWN: [Subtest 1]: [Score] — [At/Below/Above] expected range [Subtest 2]: [Score] — [At/Below/Above] expected range [etc.] INSTRUCTIONAL PRIORITY: Primary need: [skill area] Recommended focus: [specific skill target] Suggested next step: [brief instructional recommendation] ``` ### Step 5 — Progress Monitoring Trend Analysis For repeated-measure data (progress monitoring over time): - Calculate growth rate (score per week or per month) - Compare to expected growth rate for the intervention goal - Generate a brief trend statement: - **Adequate Progress**: "Student's growth rate ([X] points/week) meets the target of [Y] points/week. Continue current intervention." - **Insufficient Progress**: "Student's growth rate ([X] points/week) falls below the target of [Y] points/week. Consider adjusting intervention intensity, duration, or approach." - **Plateau**: "Student's scores have been stable for [X] weeks without growth. This warrants a team review and possible program change." If the user has chart/graph data or wants visualization, generate an ASCII trend chart or export-ready data table: ``` PROGRESS MONITORING TREND — Student A Week 1: ████████░░░░░░░░░░░░ 42 WCPM Week 3: █████████░░░░░░░░░░░ 48 WCPM Week 5: ██████████░░░░░░░░░░ 51 WCPM Week 7: ███████████░░░░░░░░░ 56 WCPM Goal: ████████████████████ 80 WCPM (by [date]) Current growth rate: +3.5 WCPM/week | Needed: +4.9 WCPM/week ``` ### Step 6 — Communication Outputs #### For Parent/Guardian Communication Plain-language summary (no jargon). See `references/parent-data-language.md` for tested parent-friendly framing. Template: > "[Student pseudonym]'s recent reading assessment tells us [plain-language > summary of performance]. Compared to what we expect at this point in the > year, [student] is [at / working toward / exceeding] the goal. Here is > what we are doing to support [him/her/them], and here is what you can do > at home." #### For Team/IEP Meeting Brief data summary table + one paragraph of interpretive narrative. Format the narrative around three questions: What does the data show? What does it mean? What are we going to do about it? #### For Administrative / Board Presentation Anonymized class or grade-level aggregate only. Highlight trends, growth rates, and action plans. Avoid individual student data in any non-IEP administrative presentation. --- ## Assessment Literacy Notes Include these clarifications when the context suggests the user may benefit: **On percentile ranks**: A percentile rank of 40 does not mean a student got 40% correct. It means the student performed higher than 40% of the normative sample. Percentile ranks do not move on an equal-interval scale — a 10-point gain at the 50th percentile is different from a 10-point gain at the 5th percentile. **On grade equivalents**: A 3rd grader with a grade equivalent of 5.2 does not read like a 5th grader. GE scores mean the student scored as well as the average 5th grader, month 2, would score on a *3rd grade test*. GE scores should not be used to place students in grade-level texts. **On growth scores**: Growth without context is misleading. A student who grew 8 points may be making excellent progress or inadequate progress depending on the expected growth for that starting point and time of year. Always compare growth to a benchmark growth target. --- ## Reference Files - `references/assessment-norms.md` — Benchmark cut scores, national norms, and growth targets for DIBELS 8th Ed, NWEA MAP, iReady, STAR, and common state assessments - `references/parent-data-language.md` — Tested plain-language templates for communicating assessment data to families ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [JJuice22](https://github.com/JJuice22) - **Source:** [JJuice22/classroom-ready-ai-skills](https://github.com/JJuice22/classroom-ready-ai-skills) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-jjuice22-classroom-ready-ai-skills-student-data-dashboard - Seller: https://agentstack.voostack.com/s/jjuice22 - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.