Reflections on gaze data in statistics education

Boels, Lonneke

doi:10.1111/test.12340

Cited by 3 publications

(3 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our process consists of two related applications. Gaze data can indeed be captured remotely using web-based technologies like WebGazer.js, enabling researchers to record gaze coordinates through web cameras, including those integrated into portable devices (Boels, 2023). WebGazer.js is a webcam-based eye-tracking library that shows promise for remote eye-tracking research (Papoutsaki et al, 2016;Steffan et al, 2024).…”

Section: Data Analysis Toolsmentioning

confidence: 99%

Evaluating computer science students reading comprehension of educational multimedia-enhanced text using scalable eye-tracking methodology

Turčáni,

Balogh,

Kohútek

2024

Smart Learn. Environ.

View full text Add to dashboard Cite

In this research, a mixed-method approach was employed to conduct large-scale eye-tracking measurements, traditionally associated with high costs and extensive time commitments. Utilizing consumer-grade webcams in conjunction with open-source software, data was collected from an expansive cohort of students, thereby demonstrating the scalability and cost-effectiveness of this innovative methodology. The primary objective of this research was to discern the disparities in reading behaviour when students were presented with standard text accompanied by illustrations, compared to the same text with highlighted key terms. The participants, comprised of first-year university students, completed a questionnaire and an introductory test to ascertain their knowledge level. Subsequently, they were segregated into two groups and participated in two reading sessions, during which their ocular movements were recorded. The amassed data underwent both qualitative analyses, facilitated by visualizations, and quantitative analysis, employing statistical measures on the data and test results. Notably, no significant difference was observed in the gaze patterns or test results between the experimental and control groups. However, a significant divergence in gaze patterns was identified between high-achieving students and those experiencing difficulties, as evidenced by the averaged composite heatmaps generated from the data. The findings underscore two pivotal points. Firstly, the feasibility of conducting large-scale eye-tracking experiments is demonstrated. Traditional studies in this field often employ small population samples due to the time and financial constraints associated with methods that utilize specialized eye-tracking hardware. In contrast, our methodology is scalable, relying on low-end hardware and enabling students to record data on their personal devices. Secondly, while eye-tracking may not provide substantial benefits for fine-tuning text already optimized for readability, it could serve as a valuable tool for identifying and assisting learners who are struggling. This mixed-method approach holds significant potential to revolutionize the conduct and interpretation of eye-tracking studies within educational settings.

show abstract

Section: Data Analysis Toolsmentioning

confidence: 99%

Evaluating computer science students reading comprehension of educational multimedia-enhanced text using scalable eye-tracking methodology

Turčáni,

Balogh,

Kohútek

2024

Smart Learn. Environ.

View full text Add to dashboard Cite

show abstract

“…The articles in this issue focus on new approaches to the teaching and learning of data practices related to messy, complex, or nontraditional data from the youngest learners [8,19] to secondary learners [14,17], undergraduate students [15,16], graduate students, teachers, and researchers [2,5,9,17]. There are two overarching themes in the articles in this special issue: new ways to consider data visualizations in the classroom [2,5,14,17,19] and new approaches or elements that need to be considered in the teaching and learning of data science practices [8,9,15,16].…”

Section: Theme Of This Special Issuementioning

confidence: 99%

“…Boels' [2] work provides insights into how advances in gaze data could support teachers, researchers, and students to better understand complex cognitive processes. Gaze data, also known as eye-tracking data, are still uncommon in statistics education despite their promise.…”

Section: New Approaches To Data Visualizationsmentioning

confidence: 99%

Introduction to rethinking learners' reasoning with nontraditional data

Noll¹,

Kazak

Zapata‐Cardona

et al. 2023

Teaching Statistics

View full text Add to dashboard Cite

Students’ local vs. global views of data distributions: a cross-grade-level analysis using eye-tracking

Schreiter,

Vogel

2024

Educ Stud Math

View full text Add to dashboard Cite

The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center, spread, and shape (so-called global view). However, the latter is challenging for students to acquire. This study, involving 68 students in grades 4, 6, and 8, had two main objectives. First, we aimed to examine the potential impact of grade level on how students perceive and compare distributions presented in dot plots. Despite variations in specific pre-knowledge, our findings showed no significant grade-related differences in students’ gaze behavior or their ability to process global features when comparing distributions. This finding suggests that there is no significant developmental trend across grade levels regarding students’ capacity to perceive distributions globally, a critical aim in statistics education. Our second objective was to extend the findings of our previous work regarding the identification of specific eye-tracking measures as indicators of students’ local vs. global views. In line with our hypotheses, differences in gaze behavior between students with a local and global view were determined regardless of their grade level. This robustness across different educational stages underscores the validity of specific eye-tracking measures as reliable indicators for students local vs. global view of data. Our research highlights the potential of eye-tracking for understanding students’ data interpretation approaches in statistics education.

show abstract

Reflections on gaze data in statistics education

Cited by 3 publications

References 41 publications

Evaluating computer science students reading comprehension of educational multimedia-enhanced text using scalable eye-tracking methodology

Evaluating computer science students reading comprehension of educational multimedia-enhanced text using scalable eye-tracking methodology

Introduction to rethinking learners' reasoning with nontraditional data

Students’ local vs. global views of data distributions: a cross-grade-level analysis using eye-tracking

Contact Info

Product

Resources

About