FAQ: Student Experience Index (SEI)

1. Why does the SEI not require a clinical psychologist in the team?

The SEI is a non-clinical, behavioural, and educational instrument. It is not designed to diagnose or treat mental health conditions. Instead, it focuses on everyday school experiences that institutions can act on.

The SEI does not attempt to:

• Diagnose mental health conditions
• Screen for psychological disorders
• Classify individuals on clinical criteria
• Replace therapeutic or diagnostic tools

Instead, it measures everyday school experience across seven domains:

• Cognitive Focus
• Emotional Energy
• Social Belonging
• Academic Engagement
• Behavioral Activation
• Support Perception
• Routine Consistency

These domains are grounded in educational psychology, learning science, behavioural activation, cognitive load theory, and motivation research. None of these require clinical licensure to measure.

Why a psychologist is not required:

1. SEI is not clinical; it is behavioural and educational.
2. It uses published constructs, not case-by-case clinical judgment.
3. It does not assess or label pathology.
4. Most educational and wellbeing scales worldwide are built and validated by researchers, not clinicians.
5. SEI focuses on actionable institutional indicators, not individual diagnoses.

In short, SEI's development and use sit squarely in the space of educational measurement and institutional improvement, not clinical psychology.

2. What are SEI scores relative to?

SEI scores are interpreted using a dual-frame approach that combines absolute meaning with local, contextual meaning.

2.1 Absolute Interpretation (Intrinsic Meaning)

Each domain score is normalized to the interval [0, 1]:

• 1.0 = consistently strong positive behaviour
• 0.0 = consistently low behaviour

For example, a score of 0.80 in Belonging means the student (or cohort) frequently endorses positive social integration behaviours.

2.2 Relative Interpretation (Local Norms)

Experiences like belonging, engagement, and routines vary a lot by institution. SEI therefore uses local normative distributions, such as:

• The school's own SEI distribution
• Class-wise comparisons
• Cohort-wise differences
• Monthly trends
• Percentile benchmarks

This keeps interpretation context-aware rather than relying on a single global standard that may not fit every school.

3. How is a “good” or “bad” SEI score defined?

Interpretation combines absolute thresholds with local norms to avoid over- or under-reacting to raw numbers.

3.1 Absolute Thresholds

Normalized score ranges can be read as:

• 0.70 to 1.00: Strong / Healthy
• 0.50 to 0.70: Moderate / Stable
• 0.30 to 0.50: Weak / Needs Monitoring
• 0.00 to 0.30: Critical / High Concern

Roughly speaking, > 0.70 means consistent positive behaviour; 0.50 to 0.70 indicates a mixed or average experience; 0.30 to 0.50 suggests consistent difficulty; and < 0.30 indicates persistent challenge across items.

3.2 Local, Data-Driven Norms

At the school level, SEI also looks at where scores sit within the local distribution:

• Bottom 25%: high-need group
• Middle 50%: typical range
• Top 25%: thriving group

This dual absolute-and-relative framing is standard in psychometric practice and gives schools a richer, more nuanced sense of where they stand.

4. Why exactly these seven domains and 28 items?

The seven SEI domains were selected because they represent modifiable drivers of student experience that schools can realistically influence through policy, pedagogy, and support structures.

Each domain has strong theoretical grounding:

• Focus – cognitive attention and executive function
• Energy – motivational and affective activation
• Belonging – social integration and connectedness
• Engagement – academic engagement and interest
• Activation – behavioural activation and initiative
• Support – mentorship and teacher–student relationship research
• Routines – executive functioning and habit formation

The 28-item structure (4 items per domain) balances breadth and practicality:

• High reliability
• Low fatigue (completion time under ~3 minutes)
• Suitable for monthly tracking
• Psychometric adequacy with multiple items per construct
• Broad behavioural coverage without overburdening students

5. How does SEI handle measurement error?

Like all behavioural instruments, SEI has some measurement error at the individual level. It is designed to minimise and manage this through its structure and use.

Key design choices include:

• Multiple items per domain
• Use of domain averages to reduce random noise
• Emphasis on aggregate-level, not diagnostic, interpretation
• Pattern detection across related domains rather than single-item flags
• Repeated monthly cycles to smooth out week-to-week variance
• Exclusion of clearly patterned or dummy responses

Together, these help produce stable, decision-useful insights at the institutional level, even though individual responses are noisy.

6. Is SEI meaningful even though it is not clinical?

Yes. Most core school outcomes, such as engagement, belonging, routines, and energy, are non-clinical but strongly predictive of:

• Attendance
• Participation
• Academic performance
• Persistence and retention
• Overall day-to-day student functioning

SEI belongs to the same broad family as widely used non-clinical educational assessment tools worldwide: it tracks experience and functioning, not disorders.

7. How can schools act on SEI data?

Each SEI administration can yield over a hundred data points per school when broken down by domain, class, cohort, and time. This supports:

• Identifying weak or lagging domains
• Tracking improvement monthly
• Comparing class or batch performance
• Detecting emerging problem areas early
• Designing targeted, domain-specific interventions
• Measuring the effect of those interventions over time

Concrete examples include:

• Low Belonging → group activities, mentorship programs, peer support systems.
• Low Routines → habit-building workshops, structured study plans, schedule support.
• Low Engagement → teacher development, more interactive pedagogy, classroom design changes.
• Low Support → improved teacher–student communication channels, advisory systems, and feedback loops.

In this way, SEI turns student self-report data into a practical roadmap for making the school environment more human-centred and effective.