AI-enabled Qualitative Research: Saudi Education

Evidano is an AI-powered qualitative data analysis platform that helps teams turn classroom observations, interviews, and artifacts into reproducible themes and stakeholder-ready visualizations.

A 2026 PLOS One study of 47 private-school science teachers in Al-Qassim and Al-Ahsa found near-universal AI adoption for personalization (97.9%), high use for interactive activities (89.4%), and strong inter-rater reliability (Cohen’s κ = 0.86), which a structured seven-step workflow can reproduce.

• The PLOS One study (published 21 July 2026) collected observations 25 Aug–30 Oct 2025 and interviewed 47 teachers, producing six analytic themes suitable for thematic synthesis.
• Report and defend reliability metrics: the classroom observers achieved Cohen’s κ = 0.86 and interview coding agreement was 95%.
• Follow a seven-step Evidano-backed workflow (ingest, transcribe, prep codebook, double-code, synthesize, visualize, audit) to produce reproducible themes and exportable audit logs.
• Ensure ethics: the original study followed KFU-REC Decision No. KFU-REC-2025JUN-EA000985 and used consent and pseudonyms, and AI processing should be covered in consent.

The quick summary: a 2026 qualitative study published in PLOS One examined 47 private-school science teachers in Al-Qassim and Al-Ahsa, using classroom observations (25 Aug–30 Oct 2025) and semi-structured interviews to study how AI tools support culturally responsive science curricula.

• Source: PLOS One (Published 21 July 2026).
• Key reliability numbers: classroom observers Cohen’s κ = 0.86; interview coding agreement = 95%.
• Primary dataset: n = 47 teachers; observation sessions of 45 minutes across Grades 6–9.

The researchers used a purposive sample of 47 teachers, paired classroom observations and semi-structured interviews, and applied an inductive thematic analysis informed by grounded theory principles.

Observers used a validated checklist, two observers achieved κ = 0.86 and reconciled discrepancies in calibration meetings, and interview transcripts were double-coded with 95% agreement.

The analytic output was six themes: AI-supported personalization, analysis of cultural texts, AI-designed interactive activities, AI in curriculum development, interactive/collaborative learning, and intelligent assessment of cultural values.

• Transparency: authors state this is an inductive thematic approach (not full grounded theory, no theoretical sampling or saturation claims).
• Limitations flagged: perception-based outcomes; no standardized student achievement measures.
• Practical measures reported: session lengths (45 min), observation period (two+ months), and expert-validated instruments.

This seven-step workflow reproduces the PLOS study analysis with AI support and maps each analytic step to traceable outputs.

• 1) Ingest: upload audio, observation checklists, and interview files to Evidano; apply the custom dictionary for local Arabic terms.
• 2) Transcribe & translate: run AI transcription with PII redaction; verify low-confidence segments manually.
• 3) Prep codebook: import the observation checklist as initial codes and run AI to surface candidate subcodes from transcripts.
• 4) Double-code: assign two coders, use Evidano’s disagreement dashboard, calculate κ and percent agreement, reconcile in calibration meeting.
• 5) Thematic synthesis: use Evidano to produce theme frequencies, cross-segment comparisons (by school/experience), and co-occurrence networks.
• 6) Visualize & export: create thematic hierarchies, quote lists linked to sources, and slide exports for stakeholders.
• 7) Audit & archive: lock final codebook, archive raw files with metadata, and export an audit log for ethics/compliance.

The study followed institutional ethics (KFU-REC Decision No. KFU-REC-2025JUN-EA000985) and used consent and pseudonyms.

When using AI tools, ensure consent covers AI processing and maintain human review for culturally sensitive outputs.

AI-enabled qualitative research, when paired with clear coder protocols and human validation, can cut weeks from synthesis while strengthening reproducibility.

• Ready to apply this workflow? Start a pilot: ingest one teacher interview + two observation sessions into Evidano, run the seven-step sequence above, and produce a stakeholder brief in under 7 days.
• Request a demo or pilot on Evidano or Try Evidano for free, our team can show how to map your instruments, preserve audit trails, and generate the exact thematic and cross-segment outputs you need for publication or policy.