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A zoo cannot show that a game changed visitor behavior by counting plays or measuring dwell time. A defensible evaluation starts with one observable action, records who had an opportunity to play, measures that action (or a tightly matched learning outcome), and compares results with a suitable baseline or comparison group. Add a delayed follow-up if the claim is that the change lasts.
Start with the change you want to detect
“Raise awareness” is a campaign aim, not a measurable outcome. Write a sentence that specifies the action, the opportunity to perform it and the time window. For example: “After playing, visitors who buy a drink will put the container in the correct recycling bin during the next 30 minutes,” or “Visitors will be less likely to tap the exhibit glass while watching the animals.”
The same discipline applies to learning. If the game teaches species identification, food-web relationships or a conservation action, write a small set of factual questions that directly reflect what the game presents. Do not use enjoyment, confidence or a general “impact” score as a substitute for the intended result.
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- Behavior: an action an observer can see, such as touching glass, following a sign, using a bin correctly or keeping a specified distance.
- Knowledge: a correct answer to a game-specific factual question.
- Attitude or intention: a response on a clearly defined scale, such as concern about biodiversity loss or interest in species conservation.
- Engagement: noticing, approaching, playing, watching someone else play and time spent interacting.
A game may improve one construct without changing another. In a touchscreen evaluation, game-linked knowledge improved, while the measured conservation opinions did not. Report those outcomes separately rather than combining them into one claim.
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Use a three-layer measurement model
A practical evaluation combines reach, a direct outcome and a comparison over time or across groups.
| Layer | What to record | What it can—and cannot—show |
|---|---|---|
| Reach and use | Whether visitors noticed the game, approached it, played it or watched; duration and access conditions | Who encountered the intervention and how it was used. It does not establish learning or behavior change. |
| Direct outcome | A predefined observed action, game-specific knowledge question or validated attitude measure | Whether the targeted construct changed. The measure must match the claim. |
| Comparison and timing | Pre/post scores, a contemporaneous group without access, within-participant measurements or a later follow-up | How plausibly the change can be attributed to the game and whether it persists. |
Whitehouse and colleagues’ study of interactive games at two UK zoo-based primate research centres gives the central warning: “Although these methods are useful indicators of the audience’s interest, they alone do not allow us to make any assumptions about visitor learning or visitor attitudes.” Read the 2014 PLOS ONE evaluation for the study methods and results.
Build the evaluation step by step
1. Define an observation codebook
For a conduct outcome, specify exactly what counts, what does not count, when observation starts and ends, and how an observer handles an ambiguous case. Include the opportunity needed for the behavior: a visitor cannot be scored for correct recycling if no bin is available, and cannot be scored for touching glass if the animal is not visible.
Use the same definitions before and after installation. Record contextual variables that could change behavior independently of the game, including age group, exhibit, crowding, time of day, weather where relevant, and whether the game was working and accessible.
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2. Track exposure separately from outcomes
Create exposure categories such as “passed,” “approached,” “played,” and “watched another person play.” In the touchscreen study, approaching meant pausing within arm’s reach while oriented toward the screen; interaction included playing or watching. Researchers used a stopwatch to record dwell time. A simple digital stopwatch is sufficient as a fieldwork aid; no particular model is required.
Record duration only when it answers a decision question, such as whether a shorter version is being ignored or whether access is constrained during peak periods. More minutes do not automatically mean more learning. Exposure data should be reported alongside a knowledge or behavior result.
3. Select a comparison design
Choose the strongest feasible design and state its limits. The following designs answer different questions:
| Design | How it works | Main strength | Main threat to interpretation |
|---|---|---|---|
| Post-use only | Measure visitors after they encounter the game | Low burden and easy to deploy | No baseline; differences may predate the game. |
| Pre/post | Measure the same or comparable visitors before and after exposure | Shows direction and size of change | Repeated testing, self-selection and outside events can affect scores. |
| Between-participant comparison | Compare visitors with game access to a comparable group without it | Provides a contemporaneous counterfactual | Groups may differ in age, interests, visit purpose or exhibit access. |
| Within-participant comparison | Measure the same participants under two conditions or at two times | Controls for many stable individual differences | Order, memory and carry-over effects can inflate differences. |
| Delayed follow-up | Recontact visitors after a defined interval | Tests retention rather than immediate reaction | Attrition and small samples can make estimates uncertain. |
Record which design was used, how participants were assigned and how many were lost at each stage. A 2024 meta-analysis of 56 zoo-led intervention studies found an overall standardized effect of d+ = 0.40 (95% CI 0.28–0.51), described as small to medium, with substantial heterogeneity. Effects were larger in within-participant than between-participant designs. That pattern supports transparent reporting; it does not make one design automatically causal or turn the pooled estimate into an effect size for a particular game. See the systematic review and meta-analysis.
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4. Sample the site fairly
Schedule observations across normal and busy periods, and rotate locations or observation windows when practical. A game beside a narrow path may be encountered differently from one in an open gallery. The Whitehouse evaluation used two UK sites whose layouts and device access were not comparable; visitor flow and peak volume could limit the share of visitors able to play. Its findings therefore describe those settings, not a universal play rate.
In that study, 1,084 people participated. At the Edinburgh site, 24% of 82 observed visitors played the games; among participating visitors, 47.0% of those aged 16 or younger interacted with the touchscreen compared with 35.2% of older visitors. Average game-play time was 2.31 minutes. These are site- and study-specific observations, not targets a different zoo should expect.
5. Measure the intended outcome directly
For behavior, observers should record opportunities and actions using the codebook rather than relying only on visitor recollection. For knowledge, ask a few questions tied closely to the game and keep wording appropriate for the age groups being assessed. For attitudes, use a multi-item scale that matches the construct instead of a single broad question.
Collins and colleagues demonstrated the feasibility of direct behavior measurement in a controlled educational intervention at three animal exhibits. Children in treatment groups showed statistically significant reductions in negative behavior at each exhibit, while animal behavior generally did not show a corresponding change. The result illustrates why “visitor behavior” and “animal response” must be separate endpoints. The study is available in Zoological education: Can it change behaviour?
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6. Pilot the questionnaire and scales
Pilot every question with the youngest visitors expected to answer it. Check whether children interpret “conservation,” “biodiversity” and probability words as intended, and keep factual items distinct from opinion items.
A 2024 study across nine zoos examined adjusted instruments for connection to nature, interest in species conservation, environmental concern and attitudes toward biodiversity loss. It reported 674 pretest and 619 posttest questionnaires, including a six-item species-conservation-interest construct and a five-item biodiversity-loss-attitude scale. These instruments can inform a zoo’s questionnaire selection, but they still require local piloting and should not be presented as a direct behavior measure. See Environmental education in zoos: analysis of different scales to measure the impact of educational programs.
7. Plan a delayed follow-up for lasting claims
An exit survey can estimate immediate response. It cannot establish that a visitor remembers the lesson months later or acts differently at home. Define the follow-up interval before collecting baseline data, use the same core outcome where possible, and report how many people respond.
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How to analyze and report the results
Report reach without calling it impact
Give the number observed, the number who could access the game, the number who played and the number who completed each outcome measure. Present play rate and dwell-time distributions by site or session when layouts differ. Explain missing observations, equipment outages and periods when crowding blocked access.
Report each outcome in its own unit
For a behavior, report the proportion of opportunities in which the target action occurred, with the comparison or baseline alongside it. For knowledge, report the percentage correct for each question or a clearly defined score. For an attitude scale, report the scale direction and item count so readers know what a higher score means. Do not describe a statistically significant knowledge result as a conservation-attitude result when the attitude items did not change.
State what the design can support
A quasi-experimental pre/post result can show an association with installation and exposure; it cannot rule out every alternative explanation. A comparison group improves attribution only when the groups are genuinely comparable and access is documented. A delayed survey supports a retention statement only for respondents who completed it. Include uncertainty and sample loss rather than presenting a single percentage as definitive.
A worked measurement plan
Suppose a zoo game teaches visitors to protect a wetland. A concise plan could look like this:
- Outcome: “When visitors leave the exhibit, they will place a recyclable drink container in the correct bin during the next 30 minutes.” Define the bin, the eligible container and the observation window.
- Exposure: Log passers-by, approaches, players and watchers; record whether the screen was available and the approximate interaction duration.
- Behavior sample: Observe the same exit area during matched time blocks before installation and after installation, recording crowding and bin availability.
- Knowledge check: Ask two or three questions that use facts and actions explicitly taught by the game.
- Comparison: If possible, use a nearby comparable exhibit without the game or alternate game availability by preplanned sessions. Document assignment and access rather than allowing visitors to choose a condition unknowingly.
- Follow-up: Invite a consented subset to answer the same core knowledge and action-intention items after a defined interval. Label intention as intention, not observed conduct.
- Decision rule: Specify in advance what size and direction of behavior change would justify keeping, revising or removing the game, while considering reach and operational cost.
This plan produces separate answers: who used the game, whether the targeted action changed during the visit, whether knowledge changed, and whether any measured learning persisted.
Common mistakes and fixes
- Mistake: treating dwell time as learning. Fix: pair exposure timing with a direct knowledge or behavior measure.
- Mistake: asking only “Did you enjoy it?” Fix: ask game-specific factual questions and, when relevant, observe the target action.
- Mistake: using one broad attitude question for every goal. Fix: choose a construct-matched, age-appropriate scale and pilot it.
- Mistake: comparing different sites without recording context. Fix: document layout, device access, visitor flow, crowding, time and age composition.
- Mistake: claiming lasting behavior from an exit survey. Fix: add a delayed measurement and report attrition and its limited scope.
- Mistake: treating a pooled meta-analysis as a guarantee for one game. Fix: describe the intervention type, design and uncertainty of the local evaluation.
- Mistake: confusing visitor and animal outcomes. Fix: code them as distinct measures with separate hypotheses.
Context that should not be misclassified
Evidence from related education programs can inform measurement without becoming evidence for a visitor game. Counsell and colleagues’ 2020 in-school repeat-engagement program involved 445 students across seven schools and reported a 60.5% aggregate increase in conservation understanding and a 24% increase in knowledge of pro-conservation behaviors. Those figures describe a school program, not a zoo visitor-game effect, so they should not be used as the game’s expected impact.
The standard for a credible conclusion
A strong conclusion names the population, setting, exposure, outcome and time horizon: for example, “Among visitors who could access and play the touchscreen at this exhibit, game-specific knowledge was higher immediately afterward than in the comparison condition.” It does not silently expand that statement into “the game changed conservation behavior.” If the data show only engagement, call it engagement; if they show a short-term knowledge difference, call it that; if direct behavior and delayed retention were not measured, say so.
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