The ClassTrack Suite is the Observation & Coaching Layer of CrazyGoldFish’s AI reasoning stack. It captures classroom signals, applies rubric-based evaluation, and generates insights for teachers, principals, leaders, and parents.
Core Capabilities
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AI-Powered Classroom Observation
- Audio session ingestion with speech-to-text + speaker ID.
- Engagement analysis (talk-time balance, sentiment, pacing, questioning).
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Rubric-Based Evaluation
- Automatic scoring across dimensions: pedagogy, classroom management, student engagement.
- Supports custom rubrics for schools and boards.
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Teacher Growth Support
- Actionable feedback linked to micro-trainings.
- Peer observation journals and reflection tools for continuous growth.
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Parent Engagement Reports
- Weekly summaries with student engagement highlights and activity snapshots.
- Simple visual reports designed for accessibility.
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Leadership Dashboards
- Principals and admins see aggregated insights: observation volume, teacher growth, engagement trends.
- Export-ready for compliance and audits.
ClassTrack
Supported Inputs
- ✅ Classroom audio recordings
- ✅ Live or uploaded session logs
- ✅ Rubric configurations (default + custom)
- ✅ Teacher/Student/Parent metadata
Stakeholder Value
- Teachers → Get structured feedback + growth resources.
- Students → Indirectly benefit from improved pedagogy and engagement.
- Principals → Monitor teacher effectiveness across classrooms.
- Parents → Receive simple reports that build trust and visibility.
- School Leaders/Admins → Gain data-driven insights for governance and decision-making.
Ecosystem Integration
- Upstream: Lesson Plans + Worksheets feed into observed sessions.
- Core: ClassTrack analyses classroom interactions and generates feedback.
- Downstream:
- Feeds teacher insights into Teacher Action Plans.
- Informs AI Studio to adjust lesson plans and worksheets.
- Closes the loop with Evaluation Layer by refining assessment strategies.
Next Step
Next → Explore the Workflow to see how ClassTrack captures, processes, and delivers observation insights.FAQ
How does the Classroom Observation module (ClassTrack) compute talk-time balance, questioning, and pacing from live audio/video?
How does the Classroom Observation module (ClassTrack) compute talk-time balance, questioning, and pacing from live audio/video?
ClassTrack processes classroom audio/video with speech-to-text, speaker ID, and engagement analytics to quantify talk-time balance, questioning frequency, and pacing. These signals align to rubrics for coaching and can feed downstream improvements to materials, while keeping a human-in-the-loop step for teacher review before publishing.
What multimodal signals does classroom observation use (e.g., speech-to-text, speaker ID), and what exactly do we get back in the output?
What multimodal signals does classroom observation use (e.g., speech-to-text, speaker ID), and what exactly do we get back in the output?
Observation ingests audio/video alongside text artifacts and applies speech-to-text and speaker identification to extract engagement metrics. Outputs include rubric-aligned summaries, annotations, and engagement analytics (talk-time, questioning, pacing) that are export-ready for LMS/ERPs and CBSE/ICSE/GDPR aligned reporting.
How is human-in-the-loop applied to observation notes and rubric-based feedback before results are published?
How is human-in-the-loop applied to observation notes and rubric-based feedback before results are published?
Educators review suggested observations and rubric-aligned feedback, make edits, trigger rechecks, and approve outcomes with audit logs. This preserves agency while targeting up to 95% accuracy, ensuring observation insights are trustworthy and instruction-ready before they appear in dashboards or reports.
What are the integration paths for Classroom Observation—REST APIs vs. white-label embeddable UI—and what does a typical 24h integration involve?
What are the integration paths for Classroom Observation—REST APIs vs. white-label embeddable UI—and what does a typical 24h integration involve?
You can integrate via standard REST APIs for deep control or use a white-label embeddable UI for rapid rollout—both support 24h integration. Teams typically wire sandbox keys, map IDs and branding, and enable webhooks for automation; no AI team is required to launch or maintain the workflow.
How do observation insights close the loop—feeding back into rubrics, reteach strategies, and AI Studio lesson plans?
How do observation insights close the loop—feeding back into rubrics, reteach strategies, and AI Studio lesson plans?
Observation completes the Evaluate → Personalize → Generate → Observe loop by sending engagement signals back to refine rubrics and materials. Insights update reteach strategies and AI Studio–generated lesson plans/worksheets, helping teachers act on evidence quickly with CBSE/ICSE/GDPR aligned outputs.
Which leader dashboards and compliance controls ship with Classroom Observation for CBSE/ICSE/GDPR aligned reporting?
Which leader dashboards and compliance controls ship with Classroom Observation for CBSE/ICSE/GDPR aligned reporting?
Leaders get compliance-ready dashboards showing observation volume, growth, and trends, backed by audit logs and role-based access. Workflows are CBSE/ICSE/GDPR aligned out of the box, so institutions can monitor usage, support inspections, and maintain privacy-by-design governance.
How do you maintain up to 95% accuracy on observation analytics, and what calibration or review tools are included?
How do you maintain up to 95% accuracy on observation analytics, and what calibration or review tools are included?
Accuracy targets are supported by rubric/model-aligned scoring combined with multimodal signals like speech-to-text, speaker ID, and engagement analytics. Human-in-the-loop safeguards and calibration tools allow teachers to review, edit, and re-evaluate observations with auditability to sustain fairness and consistency.
How is classroom audio/video handled for privacy and governance, especially under CBSE/ICSE/GDPR aligned workflows?
How is classroom audio/video handled for privacy and governance, especially under CBSE/ICSE/GDPR aligned workflows?
Data flows follow privacy-by-design practices with secure handling and role-based access, and all outputs are CBSE/ICSE/GDPR aligned. Human-in-the-loop review plus audit trails provide transparent oversight so institutions can meet board and regional expectations during observation and reporting.
What export options exist for LMS/ERPs—reports, webhooks, and data fields—from the observation pipeline?
What export options exist for LMS/ERPs—reports, webhooks, and data fields—from the observation pipeline?
Observation results are export-ready, including rubric-aligned summaries, annotations, and engagement metrics that sync to LMS/ERPs. APIs and webhooks support automated publishing and downstream analytics, keeping datasets consistent with the rest of the evaluation stack.
Can we deploy Classroom Observation without an internal AI team, and how do we configure branding, roles, and access?
Can we deploy Classroom Observation without an internal AI team, and how do we configure branding, roles, and access?
Yes—no AI team is required. Use the embeddable, white-label UI to match brand colors and layouts or opt for APIs for deeper control; configure role-based access and review gates so teachers stay in charge while leaders retain compliant, audit-ready visibility.