Doctoral Dissertation Research: Memory Bookmarking: An Approach to Improve Recall in Surveys

这个研究项目将推进时间使用测量的调查方法。社会科学家广泛使用回顾性调查问题（关于过去发生的事件的问题）来收集受访者最近的自传式事件的信息。然而，即使是回忆最近发生的事件对受访者来说也是一种负担，而且由于回忆错误，它经常导致数据质量不均匀。这个项目将实验评估一种叫做记忆书签（MB）的新方法来解决调查中的回忆错误。MB方法收集受访者在进行过程中的经验信息。这些信息随后作为记忆线索或书签反馈给被调查者。根据实验条件，受访者将被要求以短信、照片或地点的形式提供关于日常事件的书签。这种方法不仅可以提高对线索事件的记忆，还可以帮助受访者记住与线索事件在时间上相邻且语义上相关的其他事件——就像一个真正的书签可以让读者看到上一页和下一页上的内容一样。这个项目的结果将推动目前关于自传式记忆的思考，特别是关于人们主要代表他们生活事件的格式（口头、视觉和空间）。该项目将使用数据科学技术来分析非结构化数据，从而有助于将数据科学技术整合到调查方法中。作为博士论文研究改进奖，提供支持，使有前途的学生建立一个强大的，独立的研究生涯。MB方法将在一个析因实验中进行评估，在该实验中，受访者被要求重建他们在过去48小时内经历的事件的完整序列。MB的受访者会在指定的时间用智能手机“ping”，并被要求通过智能手机提供有关当时正在进行的活动的信息。然后将这些信息作为记忆线索呈现给被调查者，以帮助他们重建之前48小时内的所有活动，而不仅仅是被ping到的事件。被调查者的回忆将在通过将ping数与书签格式交叉创建的实验条件之间进行比较，并在书签条件和无书签控制条件之间进行比较。该研究将解决以下问题：MB方法是否比不提供线索时更准确、更完整？对于不同类型的事件，三种形式的记忆线索（口头、视觉和空间）的效果如何？受访者是否会在48小时内及时回复ping，特别是随着书签数量的增加？

This research project will advance survey methods for time-use measurement. Social scientists widely use retrospective survey questions (questions about events that occurred in the past) to gather information about respondents' recent autobiographical events. Recall of even recent events is burdensome for respondents, however, and it often leads to uneven data quality due to recall error. This project will experimentally evaluate a new approach called Memory Bookmarking (MB) to address recall error in surveys. The MB approach collects information about respondents' experiences while they are underway. This information is later fed back to respondents as memory cues or bookmarks. Depending on the experimental condition, respondents will be asked to provide bookmarks about everyday events, in the form of text messages, photographs, or locations. The approach should not only improve memory for the cued events but also help respondents remember other events that are temporally adjacent and semantically related to the cued event -- much like an actual bookmark allows readers to see what is on the previous and next pages. The results of this project will advance current thinking about autobiographical memory, especially about the formats (verbal, visual, and spatial) in which people primarily represent the events of their lives. The project will use techniques from data science to analyze unstructured data and thus contribute to ongoing efforts to integrate data science techniques into survey methodology. As a Doctoral Dissertation Research Improvement award, support is provided to enable a promising student to establish a strong, independent research career.The MB approach will be evaluated in a factorial experiment in which respondents are asked to reconstruct the full sequence of events they have experienced over the prior forty-eight hours. MB respondents are "pinged" on their smartphone at designated times and asked to provide information via their smartphones about the event that is in progress at that moment. This information is then presented to the respondents as memory cues to help them reconstruct all their activities, not just the pinged events, during the prior forty-eight hours. Respondents' recall will be compared between the experimental conditions created by crossing the number of pings with the bookmark formats, and between the bookmark conditions and a no-bookmark control condition. The research will address the following questions: Does the MB approach lead to more accurate and complete recall than when no cues are provided? How effective are the three formats of memory cues (verbal, visual, and spatial) for different types of events? Will respondents reply to pings in a timely manner during the forty-eight hours, especially as the number of bookmarks increases?