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

本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溯性调查问题(关于过去发生的事件的问题)来收集关于受访者最近自传事件的信息。然而，即使是最近发生的事件也会给受访者带来负担，而且往往会因为回忆错误而导致数据质量参差不齐。该项目将对一种名为记忆书签(MB)的新方法进行试验性评估，以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。这些信息稍后会作为记忆提示或书签反馈给受访者。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。这种方法不仅应该改善对提示事件的记忆，还可以帮助受访者记住与提示事件在时间上相邻并在语义上相关的其他事件--就像实际的书签允许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当前对自传体记忆的思考，特别是关于人们主要表现他们生活中的事件的形式(语言、视觉和空间)。该项目将使用数据科学的技术来分析非结构化数据，从而有助于正在进行的将数据科学技术纳入调查方法的努力。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方法将通过析因实验进行评估，在该实验中，受访者被要求重建他们在过去48小时内经历的完整事件序列。MB受访者在指定的时间在他们的智能手机上被“ping”，并被要求通过他们的智能手机提供关于当时正在进行的活动的信息。然后，这些信息作为记忆线索呈现给受访者，帮助他们重建他们在之前48小时内的所有活动，而不仅仅是被ping的事件。受访者的回忆将在通过将ping次数与书签格式交叉而创建的实验条件以及书签条件和无书签控制条件之间进行比较。这项研究将解决以下问题：与不提供线索时相比，MB方法是否会导致更准确和完整的回忆？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，特别是在书签数量增加的情况下？

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?