In 2023, the Disneyland theme park in Anaheim, California welcomed more than 17 million visitors in total. This shows an increase of 2.2 percent compared to the previous year. The number of visitors to the park peaked in 2019.

Diverse learning theories have been constructed to understand learners' internal states through various tangible predictors. We focus on self-regulatory actions that are subconscious and habitual actions triggered by behavior agents' 'awareness' of their attention loss. We hypothesize that self-regulatory behaviors (i.e., attention regulation behaviors) also occur in e-reading as 'regulators' as found in other behavior models (Ekman, P., & Friesen, W. V., 1969). In this work, we try to define the types and frequencies of attention regulation behaviors in e-reading. We collected various cues that reflect learners' moment-to-moment and page-to-page cognitive states to understand the learners' attention in e-reading.

The text 'How to make the most of your day at Disneyland Resort Paris' has been implemented on a screen-based e-reader, which we developed in a pdf-reader format. An informative, entertaining text was adopted to capture learners' attentional shifts during knowledge acquisition. The text has 2685 words, distributed over ten pages, with one subtopic on each page. A built-in webcam on Mac Pro and a mouse have been used for the data collection, aiming for real-world implementation only with essential computational devices. A height-adjustable laptop stand has been used to compensate for participants' eye levels.

Thirty learners in higher education have been invited for a screen-based e-reading task (M=16.2, SD=5.2 minutes). A pre-test questionnaire with ten multiple-choice questions was given before the reading to check their prior knowledge level about the topic. There was no specific time limit to finish the questionnaire. We collected cues that reflect learners' moment-to-moment and page-to-page cognitive states to understand the learners' attention in e-reading. Learners were asked to report their distractions on two levels during the reading: 1) In-text distraction (e.g., still reading the text with low attentiveness) or 2) out-of-text distraction (e.g., thinking of something else while not reading the text anymore). We implemented two noticeably-designed buttons on the right-hand side of the screen interface to minimize possible distraction from the reporting task. After triggering a new page, we implemented blur stimuli on the text in the random range of 20 seconds. It ensures that the blur stimuli occur at least once on each page. Participants were asked to click the de-blur button on the text area of the screen to proceed with the reading. The button has been implemented in the whole text area, so participants can minimize the effort to find and click the button. Reaction time for de-blur has been measured, too, to grasp the arousal of learners during the reading. We asked participants to answer pre-test and post-test questionnaires about the reading material. Participants were given ten multiple-choice questions before the session, while the same set of questions was given after the reading session (i.e., formative questions) with added subtopic summarization questions (i.e., summative questions). It can provide insights into the quantitative and qualitative knowledge gained through the session and different learning outcomes based on individual differences. A video dataset of 931,440 frames has been annotated with the attention regulator behaviors using an annotation tool that plays the long sequence clip by clip, which contains 30 frames. Two annotators (doctoral students) have done two stages of labeling. In the first stage, the annotators were trained on the labeling criteria and annotated the attention regulator behaviors separately based on their judgments. The labels were summarized and cross-checked in the second round to address the inconsistent cases, resulting in five attention regulation behaviors and one neutral state. See WEDAR_readme.csv for detailed descriptions of features.

The dataset has been uploaded 1) raw data, which has formed as we collected, and 2) preprocessed, that we extracted useful features for further learning analytics based on real-time and post-hoc data.

Reference

Ekman, P., & Friesen, W. V. (1969). The repertoire of nonverbal behavior: Categories, origins, usage, and coding. semiotica, 1(1), 49-98.

Browse The Walt Disney Company (DIS) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

Supported market data schemas: MBP-1, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, TBBO, Trades, Statistics, Definition Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

The Magic Kingdom theme park at Walt Disney World in Florida, United States, reported over 17.7 million visitors in 2023. Despite welcoming more guests in 2023 than it did in 2022, the amusement park was not able to reach pre-pandemic levels of attendance that year. Theme parks - additional information The most visited theme park worldwide, Walt Disney World Magic Kingdom, located in Florida, reports increasing visitor numbers each year. However, this decreased slightly in 2016, during which attendance at the park was around 20.4 million. Disney's theme parks are not only ranked high in the United States. Disneyland Park in France received 9.93 million visitors in 2022 - almost twice that of its closest European competitor, De Efteling which counted 5.43 million attendees. SeaWorld In recent years, the controversial use of killer whales in shows and performances at SeaWorld parks has been the topic of public debate. In February 2010, a captive killer whale located at the SeaWorld park in Florida killed its trainer during a show. That year, the park reported a decline in visitor numbers. Declining visitor numbers at the SeaWorld theme park in California were also reported during the same year.