交互密度作为展品类型的行为特征：来自双场馆科学体验中心的最小日志研究
Interaction Density as a Behavioural Signature of Exhibit Type: A Minimal-Log Study from a Two-Venue Science Experience Centre
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中文总结 AI 辅助
研究如何从触摸式展品默认记录的少量字段获取参观者与展品互动信息，通过分析得出交互密度这一行为特征区分游戏和测验，发现其能预测展品类型，但数据有复杂性，还表明最小化交互日志可支持行为研究。
中文摘要 AI 辅助
理解参观者如何与互动展品互动通常需要劳动密集型的人工观察或侵入性的多模态传感（如眼动追踪、摄像头、可穿戴设备），而很少有科学中心能够大规模部署。我们探讨能否从大多数触摸式展品默认记录的少量字段（会话开始时间、结束时间和按压次数）中获取更多信息。通过分析印度班加罗尔一个科学体验中心两个场馆的八个展品的2816个参观者会话，我们得出交互密度（每秒按压次数）作为一种简单的行为特征，并用它来区分快节奏游戏和较慢的、经过深思熟虑的测验。密度能够清晰地区分（曼-惠特尼r = 0.556），并以交叉验证的AUC = 0.778自行预测展品类型。但数据使情况变得复杂：游戏不仅更激烈，参观者在上面停留的时间也更长（r = 0.172），这与强度和持续时间之间直观的权衡相反，这可追溯到难度不断增加从而产生开放式重新参与循环而非固定终点展品。密度也不是现有指标的通用替代品：仅原始按压次数就能解释停留时间的更多方差（R^2 = 0.527），而密度仅为（R^2 = 0.081），不过两者结合比单独使用任何一个都有所改进（R^2 = 0.667）。展品级异常、跨场馆复制检查和会话长度审查人工制品进一步对这些结果进行了压力测试而非简单确认。我们提出的更广泛的观点是方法论上的：最小化、保护隐私的交互日志——而非额外的传感器——已经可以支持任何有触摸式展品的科学中心进行严谨、可证伪的行为研究。
英文摘要
Understanding how visitors engage with interactive exhibits usually calls for either labour-intensive manual observation or invasive multimodal sensing -- eye-tracking, cameras, wearables -- that few science centres can deploy at scale. We ask how much can be learned instead from the handful of fields that most touch-enabled exhibits already log by default: a session's start time, end time, and press count. Analysing 2,816 visitor sessions across eight exhibits at two venues of a science experience centre in Bengaluru, India, we derive interaction density -- presses per second -- as a simple behavioural signature, and use it to distinguish fast-paced games from slower, deliberate quizzes. Density does so cleanly (Mann-Whitney r=0.556) and predicts exhibit type on its own with a cross-validated AUC=0.778. But the data complicates the obvious story: games are not just more intense, visitors also dwell on them longer (r=0.172), reversing the intuitive trade-off between intensity and duration -- traced to exhibits whose escalating difficulty creates open-ended re-engagement loops rather than fixed endpoints. Density is not a universal replacement for existing metrics either: raw press count alone explains far more variance in dwell time (R^2=0.527) than density does (R^2=0.081), though combining both improves on either alone (R^2=0.667). Exhibit-level anomalies, a cross-venue replication check, and a session-length censoring artefact further stress-test rather than simply confirm these results. The broader case we make is methodological: minimal, privacy-preserving interaction logs -- not additional sensors -- can already support rigorous, falsifiable behavioural research at any science centre with touch-enabled exhibits.
