Sharma Nirwan, Colucci-Gray Laura, Siddharthan Advaith, Comont Richard, van der Wal René
School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, UK.
School of Biological Sciences, University of Aberdeen, Aberdeen, UK.
PeerJ. 2019 Jan 28;6:e5965. doi: 10.7717/peerj.5965. eCollection 2019.
In recent years, the number and scale of environmental citizen science programmes that involve lay people in scientific research have increased rapidly. Many of these initiatives are concerned with the recording and identification of species, processes which are increasingly mediated through digital interfaces. Here, we address the growing need to understand the particular role of digital identification tools, both in generating scientific data and in supporting learning by lay people engaged in citizen science activities pertaining to biological recording communities. Starting from two well-known identification tools, namely identification keys and field guides, this study focuses on the decision-making and quality of learning processes underlying species identification tasks, by comparing three digital interfaces designed to identify bumblebee species. The three interfaces varied with respect to whether species were directly compared or filtered by matching on visual features; and whether the order of filters was directed by the interface or a user-driven open choice. A concurrent mixed-methods approach was adopted to compare how these different interfaces affected the ability of participants to make correct and quick species identifications, and to better understand how participants learned through using these interfaces. We found that the accuracy of identification and quality of learning were dependent upon the interface type, the difficulty of the specimen on the image being identified and the interaction between interface type and 'image difficulty'. Specifically, interfaces based on filtering outperformed those based on direct visual comparison across all metrics, and an open choice of filters led to higher accuracy than the interface that directed the filtering. Our results have direct implications for the design of online identification technologies for biological recording, irrespective of whether the goal is to collect higher quality citizen science data, or to support user learning and engagement in these communities of practice.
近年来，让普通民众参与科学研究的环境公民科学项目的数量和规模迅速增加。其中许多项目都涉及物种的记录和识别，这些过程越来越多地通过数字界面来实现。在此，我们探讨了日益增长的一种需求，即了解数字识别工具在生成科学数据以及支持参与与生物记录群体相关的公民科学活动的普通民众学习方面所发挥的特殊作用。本研究从两种知名的识别工具，即识别检索表和野外指南入手，通过比较三种旨在识别熊蜂物种的数字界面，聚焦于物种识别任务背后的决策过程和学习质量。这三种界面在物种是直接比较还是通过视觉特征匹配进行筛选，以及筛选顺序是由界面引导还是用户驱动的开放选择方面存在差异。我们采用了一种并发混合方法，来比较这些不同界面如何影响参与者进行正确和快速物种识别的能力，并更好地理解参与者如何通过使用这些界面进行学习。我们发现，识别的准确性和学习质量取决于界面类型、被识别图像上标本的难度以及界面类型与“图像难度”之间的相互作用。具体而言，基于筛选的界面在所有指标上都优于基于直接视觉比较的界面，并且开放选择筛选方式比引导筛选的界面具有更高的准确性。我们的研究结果对于生物记录在线识别技术的设计具有直接影响，无论目标是收集更高质量的公民科学数据，还是支持用户在这些实践社区中的学习和参与。
