STEP UP – Baseline Survey Design

Baseline Survey Design for Project “STEP UP”

A structured, multi‑respondent survey framework to establish the project’s baseline conditions.

Capturing leadership, teaching, infrastructure, GESI, and career guidance indicators across Cambodia’s upper secondary system.

Illustration: Baseline Data Ecosystem

Show how data from principals, teachers, students, and officials flows into a unified baseline dataset that feeds the PMEF.

Graphic placeholder: Multi‑layer diagram with respondent groups feeding into a central “Baseline Database”, then arrows to “PMEF” and “OpenEMIS”.

1. Target respondents

Who the survey covers

The survey is administered through tailored modules for each respondent group to capture comprehensive, multi‑level data.

Primary respondents

  • School Principals/Directors: School management capacity, leadership, resource availability, STEM policies, and infrastructure status.
  • Upper Secondary STEM Teachers: (Physics, Chemistry, Biology, Mathematics, ICT, Earth Sciences) teaching practices, pedagogy, confidence, EdTech use, CPD access, and resource perceptions.
  • Upper Secondary Students (Grades 10–12): STEM interest and attitudes, perceived teaching quality, access to resources, career aspirations, and participation in STEM activities.

Secondary respondents

  • School Career Guidance Counselors: Current career guidance practices, especially for STEM, and linkages with tertiary education and industry.
  • POE/DOE Officials: Data management capacity (pre‑OpenEMIS), monitoring roles, and support for STEM and EdTech initiatives.
  • NIE Lecturers: PRESET curriculum baseline, STEM pedagogy, and technology integration in pre‑service training.
Baseline Survey Respondents Graphic
Graphic: Respondent Map

Concentric circles with students, teachers, and principals at the core, and counselors, POE/DOE, and NIE lecturers in outer rings, all pointing toward “Baseline Survey”.

2. Sampling strategy

Ensuring representativeness

A stratified random sampling approach is used to ensure the sample reflects Cambodia’s diverse school contexts.

Stratification

  • School type: USSs, GTHSs, SRS, NGS.
  • Geographic location: Urban, peri‑urban, rural.
  • Province: Representation across regions.

Selection process

  • A statistically significant number of schools is randomly selected within each stratum.
  • Within each selected school:
    • Principal and Career Guidance Counselor surveyed (census).
    • Random sample of 2–4 STEM teachers (depending on school size).
    • One or two classes per grade (10, 11, 12) randomly selected for student surveys.
  • Relevant POE/DOE officials and NIE lecturers purposively selected based on roles.
Graphic: Sampling Funnel
Sampling Funnel

Funnel diagram: “All Schools” → “Strata (Type, Location, Province)” → “Sampled Schools” → “Sampled Respondents”.

3. Key survey questions by theme

Indicators and respondent focus

Theme A: School leadership, management, and STEM focus

Target: School Principals

  • A1. School planning: STEM objectives in school improvement plan (Yes/No + details).
  • A2. Resource allocation: % of non‑salary budget for STEM resources.
  • A3. Teacher support: Rating of support for STEM CPD (1–5).
  • A4. Community engagement: Number of STEM‑related outreach/parent activities.

Theme B: STEM teaching and learning environment

Target: STEM Teachers, Students

For teachers:

  • B1. Teaching practices: Frequency of methods (lecture, group work, experiments, PBL, ICT) – 5‑point scale.
  • B2. Teacher confidence: Confidence in STEM content, lab safety, digital tools, competency‑based assessment – 1–5 scale.
  • B3. Lab safety: Existence of clear lab safety guidelines (Yes/No).

For students:

  • B4. Student interest: Interest in STEM careers – 1–5 scale.
  • B5. Learning experience: Perception that teachers encourage questions and experimentation – 1–5 scale.
  • B6. Practical application: Frequency of hands‑on experiments/practical activities – 5‑point frequency scale.

Theme C: Teacher professional development (CPD)

Target: STEM Teachers, School Principals

  • C1. Recent training: Days of STEM/EdTech CPD in last 12 months.
  • C2. Training relevance: Relevance of most recent CPD to daily teaching – 1–5 scale.
  • C3. PLCs: Existence of active STEM PLCs (Yes/No).

Theme D: Infrastructure, resources, and EdTech

Target: School Principals, STEM Teachers

  • D1. Laboratory availability: Physics, Chemistry, Biology labs – Not available / Available but not functional / Available and functional.
  • D2. Safety equipment: Condition of fire extinguishers, first aid kits, goggles, fume hoods – Good / Needs repair / Not available.
  • D3. ICT availability: Number of functional student computers.
  • D4. Internet connectivity: Quality and reliability – 1–5 scale.
  • D5. Data management: System used – paper, Excel, digital system, don’t know.

Theme E: Gender equality and social inclusion (GESI)

Target: All respondents (adapted per group)

  • E1. Enrollment data: Grade 12 students by gender (principals).
  • E2. Inclusive environment: Perception that school encourages girls in STEM – 1–5 scale.
  • E3. Teacher training: Training on gender‑responsive pedagogy/inclusive practices (teachers) – Yes/No.
  • E4. Accessibility: Infrastructure for students with physical disabilities – Yes/No.
  • E5. Demographics: Gender, ethnicity (including indigenous peoples), disability status – categorical.

Theme F: Career guidance and industry linkages

Target: Career Counselors, Students, Principals

  • F1. Program availability: Existence of structured career guidance program – Yes/No.
  • F2. STEM career information: Number of STEM career information events in last year.
  • F3. Student awareness: Awareness of STEM jobs and careers – 1–5 scale.
  • F4. Partnerships: Partnerships with private sector or tertiary institutions related to STEM – Yes/No.
Graphic: Theme Overview Grid

3×2 grid with icons for each theme: leadership, classroom, CPD, infrastructure, GESI, careers, each labeled with its main focus.

4. Measurement methods

How data will be captured
  • Likert scales (5‑point): Perceptions, attitudes, confidence, agreement (e.g., Strongly Disagree to Strongly Agree).
  • Binary (Yes/No): Existence or availability of programs, resources, or policies.
  • Numerical values: Counts, percentages, frequencies (e.g., students, budget %, training days).
  • Categorical / multiple choice: Demographics and system types (e.g., data management systems).
  • Checklists: Infrastructure and resource audits (e.g., lab equipment, safety features).
  • Data disaggregation: All data structured for disaggregation by gender, school type, location, and beneficiary group (e.g., indigenous peoples).
Graphic: Measurement Toolkit

Icons for scales, checkboxes, numbers, and category tags, with a filter icon labeled “Disaggregation” to show slicing by gender, location, and group.