Towards Collaborative and Intelligent Learning Environments Based on Eye Tracking Data and Learning Analytics: A Survey

Wang, Yuehua; Lu, Shulan; Harter, Derek

doi:10.1109/access.2021.3117780

Cited by 8 publications

(2 citation statements)

References 62 publications

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“…However, recently in the field of LA, there has been an increasing focus on the third development mentioned by Sweller et al (2019): objective measurement, particularly using eye tracking technology. For instance, the study by Wang et al (2021) explored the measurement of cognitive load in collaborative and intelligent learning environments based on eye tracking data. Nonetheless, these studies primarily concentrate on the cognitive aspects of learners, rather than specifically investigating the cognitive load of teachers.…”

Section: Measurement Of Teachers' Cognitive Loadmentioning

confidence: 99%

The effects of visualisation literacy and data storytelling dashboards on teachers’ cognitive load

Liu,

Pozdniakov,

Martinez-Maldonado

2024

AJET

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Learning analytics (LA) dashboards are becoming increasingly available in various learning settings. However, teachers may face challenges in understanding and interpreting the data visualisations presented on those dashboards. In response to this, some LA researchers are incorporating visual cueing techniques, like data storytelling (DS), into LA dashboard design to reduce the data visualisation skills – often referred to as visualisation literacy (VL) – and cognitive effort required by teachers to effectively use dashboards. However, despite the potential of DS principles in simplifying data visualisations, there is limited evidence supporting their effectiveness in actually reducing teachers’ cognitive load. The study presented in this paper addresses this gap by investigating the potential impact of LA dashboards, with and without DS elements, on teachers with varying VL levels. Through a quasi-experimental study involving 23 teachers, we analysed changes in pupil dilation – a proxy for cognitive load – as they examined LA dashboards featuring student data captured while participating in synchronous, online collaborative learning tasks. Our findings suggest DS can reduce cognitive load, particularly for teachers with lower VL. These results provide insight into the effects of DS and VL on teachers’ cognitive load, thereby informing the design of LA dashboards. Implications for practice or policy:• Developers of LA dashboards need to pay more attention to incorporating visual and narrative elements that are easily comprehensible and target-oriented, based on users’ visualisation literacy levels.• Educational providers and LA designers can recommend dashboards with DS elements to teachers with low VL to enhance their work efficiency.

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Section: Measurement Of Teachers' Cognitive Loadmentioning

confidence: 99%

The effects of visualisation literacy and data storytelling dashboards on teachers’ cognitive load

Liu,

Pozdniakov,

Martinez-Maldonado

2024

AJET

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“…MMLA has emerged as a transformative approach in educational research that utilizes various data sources to gain a comprehensive understanding of student learning experiences. The literature emphasizes the importance of integrating different modalities, such as academic records, online interactions, and sensor-based data, to capture a holistic view of students' cognitive and affective states [17]. Frameworks like SNAPP (Social Networks Adapting Pedagogical Practice) demonstrate the benefits of MMLA in understanding student engagement in online learning environments [18].…”

Section: Multi-modal Learning Analytics (Mmla)mentioning

confidence: 99%

Multi-Modal LA in Personalized Education Using Deep Reinforcement Learning Based Approach

Sharif,

Uckelmann

2024

IEEE Access

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The demand for personalized learning experiences and effective analytics in education has significantly increased. The integration of technology in education has brought about significant changes in teaching and learning practices. In the era of digital technology, the integration of education technology in the classroom has led to a change in teaching methods and learning strategies. In this paper, we introduce the KNIGHT (AI in Education at Hochschule für Technik (HFT) Stuttgart) framework, which is a holistic solution designed to tackle the complex issue of personalized education in a digital era. The paper explores the application of multimodal data integration, the novel application of deep reinforcement learning to education analytics, and the ethical consideration of privacy-preserving personalized feedback. The proposed framework's efficacy is substantiated through a case study, demonstrating its potential to revolutionize personalized education. This paper provides a comprehensive overview of the current discourse, providing valuable insights for educators, policymakers, and researchers into the multifaceted landscape of modern education, contributing to ongoing discussions and advancements in educational technology.

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Using eye tracking to support professional learning in vision-intensive professions: a case of aviation pilots

Hämäläinen,

De Wever,

Sipiläinen

et al. 2024

Educ Inf Technol

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In an authentic flight simulator, the instructor is traditionally located behind the learner and is thus unable to observe the pilot’s visual attention (i.e. gaze behaviour). The focus of this article is visual attention in relation to pilots’ professional learning in an Airbus A320 Full Flight Simulator. For this purpose, we measured and analysed pilots’ visual scanning behaviour during flight simulation-based training. Eye-tracking data were collected from the participants (N = 15 pilots in training) to objectively and non-intrusively study their visual attention behaviour. First, we derived and compared the visual scanning patterns. The descriptive statistics revealed the pilots’ visual scanning paths and whether they followed the expected flight protocol. Second, we developed a procedure to automate the analysis. Specifically, a Hidden Markov model (HMM) was used to automatically capture the actual phases of pilots’ visual scanning. The advantage of this technique is that it is not bound to manual assessment based on graphs or descriptive data. In addition, different scanning patterns can be revealed in authentic learning situations where gaze behaviour is not known in advance. Our results illustrate that HMM can provide a complementary approach to descriptive statistics. Implications for future research are discussed, including how artificial intelligence in education could benefit from the HMM approach.

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Towards Collaborative and Intelligent Learning Environments Based on Eye Tracking Data and Learning Analytics: A Survey

Cited by 8 publications

References 62 publications

The effects of visualisation literacy and data storytelling dashboards on teachers’ cognitive load

The effects of visualisation literacy and data storytelling dashboards on teachers’ cognitive load

Multi-Modal LA in Personalized Education Using Deep Reinforcement Learning Based Approach

Using eye tracking to support professional learning in vision-intensive professions: a case of aviation pilots

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