Eye tracking has taken hold in second language acquisition (SLA) and bilingualism as a valuable technique for researching cognitive processes, yet a comprehensive picture of reporting practices is still lacking. Our systematic review addressed this gap. We synthesized 145 empirical eye-tracking studies, coding for 58 reporting features and…

Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…

This study investigates the cognitive and emotional processes involved in augmented reality (AR)-based learning. The study looks at learning outcomes, emotional responses, meditation, and attention using a comprehensive approach that includes self-assessment, electroencephalogram data gathering, and postexperiment questionnaires. In total, 12…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…

Probes are follow-ups to survey questions used to gain insights on respondents' understanding of and responses to these questions. They are usually administered as open-ended questions, primarily in the context of questionnaire pretesting. Due to the decreased cost of data collection for open-ended questions in web surveys, researchers have argued…

Thinking about knowledge and knowing ("i.e.", epistemic cognition) is an important part of student learning and has implications for how they apply their knowledge in future courses, careers, and other aspects of their lives. Three classes of models have emerged from research on epistemic cognition: developmental models, dimensional…

A common theme in the literature on learning technologies is the way in which they can facilitate engagement both within and outside of the classroom. However, a lack of a scholarly consensus on what constitutes engagement renders problematic the issue of how one makes meaningful sense of the data presented in studies. This paper presents an…

The application of big data in education sparks debates on its effects. Researchers explore its impact on learning outcomes, with divergent views on neural networks' potential and negative consequences. This study assesses big data's influence on basic literacy skills in music education for 5th graders. Using clustering and k-density analyses,…

Response process validity evidence provides a window into a respondent's cognitive processing. The purpose of this study is to describe a new data collection tool called a whole-class think aloud (WCTA). This work is performed as part of test development for a series of problem-solving measures to be used in elementary and middle grades. Data from…

Recent research underscores the importance of inquiry learning for effective science education. Inquiry learning involves self-regulated learning (SRL), for example when students conduct investigations. Teachers face challenges in orchestrating and tracking student learning in such instruction; making it hard to adequately support students. Using…

Using multimodal data fusion techniques, we built and tested prediction models to track middle-school student distress states during educational gameplay. We collected and analyzed 1,145 data instances, sampled from a total of 31 middle-school students' audio- and video-recorded gameplay sessions. We conducted data wrangling with student gameplay…

The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…

Keystroke logging is used to automatically record writers' unfolding typing process and to get insight into moments when they struggle composing text. However, it is not clear which and how features from the keystroke log map to higher-level cognitive processes, such as planning and revision. This study aims to investigate the sensitivity of…

We present an empirical study on the use of keystroke analytics to capture and understand how writers manage their time and make inferences on how they allocate their cognitive resources during essay writing. The results suggest three distinct longitudinal patterns of writing process that describe how writers approach an essay task in a writing…

The collection and selection of the data used in learning analytics applications deserve more attention. Optimally, selection of data should be guided by pedagogical purposes instead of data availability. Using design science research methodology, we designed an artifact to collect time-series data on students' self-regulated learning and…