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Survey design and workflow analysis

Teacher Workflow & Data Use Survey

A survey and analysis process that helps schools understand where teachers spend time, where data use breaks down, and which support systems would actually help.

What this helps solve

A focused consulting engagement that turns scattered needs, tools, data, or workflows into a clearer system schools can test, refine, and use.

Schools planning AI, data, PLC, or instructional support work
Leaders who want teacher input before choosing tools or training
Teams trying to reduce workload without guessing at the pain points
Districts that need quantitative and open-response survey analysis

Engagement workflow

Start with the real problem, then build the support around it.

1

Design the survey

Build short, targeted questions around time burden, data use, workflow pain points, AI readiness, and support needs.

2

Clean the responses

Standardize response formats, protect privacy, preserve useful comments, and create analysis-ready tables.

3

Analyze patterns

Combine numeric summaries, rankings, segment comparisons, and qualitative themes to identify practical priorities.

4

Recommend action

Translate the findings into a small set of pilots, templates, supports, or professional learning next steps.

What the work should produce

The goal is not another static report. The goal is a usable decision process: clearer priorities, cleaner evidence, practical workflows, and next steps that match the capacity of the school or district.

Common outcomes

Clear teacher workload priorities
Segmented findings by grade band, subject, role, or school
Open-response themes connected to numeric patterns
Actionable recommendations for pilots, training, and workflow design

Source material

Built from the services, writing, and prototypes already in progress.

Teacher AI workflow survey

Local survey analysis identified assignments, planning, grading, differentiation, data, and communication as workflow burden areas.

PD survey cleaning pipeline

Existing survey-cleaning work includes anonymous IDs, analysis-friendly columns, numeric summaries, tidy outputs, and codebooks.

Workflow blog support

The local workflow blog drafts frame the core idea: tools only help when they fit the actual school-day workflow.

Best starting point

Most engagements should start small: one clear problem, one limited data or workflow scope, one set of users, and a short review cycle. That creates enough evidence to decide what should be refined, stopped, or expanded.

Possible deliverables

Custom survey instrument
Cleaned wide and tidy datasets
Numeric and open-response findings summary
Segmented priority tables
Leadership-ready recommendations

Next step

Build a small, evidence-based version first.

A focused first phase can clarify the problem, test the workflow, and show whether the support is useful before a larger rollout.