A data set for the investigation of the effects of audio-reinforcement on recollection rates of e-learning users

This is a data set for the investigation of the effects of audio-reinforcement on recollection rates of e-learning users. It contains two kinds of data as (i) audio files and (ii) activity log files. Note that the raw data set contains privacy sensitive information, which is concealed in this release. <strong>Audio files</strong> The audio stimuli are recorded from a Japanese mother-tongue speaker. In total, the speaker uttered 504 words and 118 numbers. In each recording session, we displayed a sequence of images, which is either a word or a number on the screen of a notebook PC to the speaker [1]. Together with the sequence of images, a single audio clip is recorded for each image (i.e. text). Note that both the sequence of images and the audio recording are executed through programs implemented in Python. After the recording sessions were finished, the audio clips are post-processed such that the silence segments are cropped and padded. <strong>Activity log files</strong> The activity log files are recorded from the e-learning software Anki [2]. They contain two basic kinds of information as (i) temporal and (ii) identifier. The temporal variables are registered in UNIX time at millisecond resolution and include \(t_p\), \(t_f\), and \(t_e\). Here, \(t_p\) denotes the time of prompt, i.e. the instant when the Q-face of a card appears. In addition, \(t_f\) represents the time of flip, i.e. the instant when the learner presses the ''Show Answer'' button and discloses the A-face of the card. Finally, \(t_e\) stands for the time of evaluation, i.e. the instant when the learner assesses the difficulty of a card by choosing one of ''Again'', ''Good'' or ''Easy''. On the other hand, the identifier variables are integer codes used to determine the deck or card that is being studied (i.e.displayed) at a given time instant (e.g. deck ID, card ID). Note that each log file is associated with a single user. Namely, the software recorded one log file into the account of each user. In addition, each line of the activity log file corresponds to a single action of the user which is considered as a reaction to the software. The structure of each line of data is as follows: [unix time], function name, data in detail (i.e. flags, queue). The data set is used as an input for building the estimator model in our article [3]. <strong>Reference:</strong> [1] P. Supitayakul, Displaying visual stimuli and recording audio, https://github.com/Parisa-S/Displaying-visual-stimuli-and-recording-audio. [2] D. Elmes, “Anki - friendly, intelligent flashcards.” https://ankiweb.net/about, 2021. [3] P. Supitayakul, Z. Yücel, A. Monden, P. Leelaprute, Investigation of the effects of audio-reinforcement on recollection rates of e-learning users (in preparation).本数据集用于探究音频强化对电子学习（e-learning）用户回忆率的影响。数据集包含两类数据：(i) 音频文件与(ii) 活动日志文件。请注意，原始数据集包含隐私敏感信息，本次发布版本已对其进行脱敏处理。 <strong>音频文件</strong> 本次录制的音频刺激素材来自一名日语母语受试者。该受试者共朗读了504个单词与118个数字。在每次录制会话中，我们通过笔记本电脑屏幕向受试者展示图像序列，图像内容为单词或数字[1]。配合图像序列，为每张图像（即对应文本）录制单条音频片段。需注意，图像序列展示与音频录制均通过Python编写的程序完成。录制会话结束后，对音频片段进行后处理，裁剪并补全静音片段。 <strong>活动日志文件</strong> 活动日志文件来自电子学习软件Anki[2]，包含两类基础信息：(i) 时间变量与(ii) 标识符变量。时间变量采用毫秒级精度的UNIX时间戳记录，包含(t_p)、(t_f)与(t_e)。其中，(t_p)代表提示时间，即卡片问题面（Q-face）出现的时刻；(t_f)代表翻卡时间，即学习者点击“显示答案”按钮并展示卡片答案面（A-face）的时刻；(t_e)代表评估时间，即学习者通过选择“困难（Again）”“良好（Good）”或“容易（Easy）”来评估卡片难度的时刻。标识符变量为整数编码，用于确定当前正在学习（即展示）的卡组或卡片（例如卡组ID、卡片ID）。需注意，每个日志文件对应单个用户，即软件会为每位用户的账户生成一份专属日志文件。此外，活动日志文件的每一行对应学习者针对软件的单次操作行为。每行数据的结构如下：[UNIX时间戳]、函数名称、详细数据（即标记、队列）。本数据集用作本文[3]中估计器模型构建的输入数据。 <strong>参考文献：</strong> [1] P. Supitayakul, 《视觉刺激展示与音频录制》, https://github.com/Parisa-S/Displaying-visual-stimuli-and-recording-audio. [2] D. Elmes, "Anki——友好智能的闪卡工具", https://ankiweb.net/about, 2021. [3] P. Supitayakul, Z. Yücel, A. Monden, P. Leelaprute, 《音频强化对电子学习用户回忆率的影响探究》（待发表）.