Tracking Students’ Analytical Reasoning Using Visual Scan Paths

Khedher, Asma Ben; Jraidi, Imène; Frasson, Claude

doi:10.1109/icalt.2017.151

Cited by 4 publications

(5 citation statements)

References 5 publications

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“…Likewise, the application of string-edit methods facilitates discrimination and prediction of effective versus non-effective learning patterns [5]. In this area, not all the string-edit methods that apply clustering techniques appear to show greater discrimination between the distances [8,10,11]. Additionally, if this method is accompanied by visualization techniques, it will facilitate user interpretation of the results [9].…”

Section: Discussionmentioning

confidence: 99%

“…Learning Management Systems are currently one of the most frequent areas of application for eye-tracking technology. Relevant versus non-relevant information can be obtained from those environments [10]. As mentioned in Section 1.1, different Machine Learning techniques such as clustering are used to analyze those records.…”

Section: Areas Of Application Of Eye-tracking Technologymentioning

confidence: 99%

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Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques

et al. 2020

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The use of learning environments that apply Advanced Learning Technologies (ALTs) and Self-Regulated Learning (SRL) is increasingly frequent. In this study, eye-tracking technology was used to analyze scan-path differences in a History of Art learning task. The study involved 36 participants (students versus university teachers with and without previous knowledge). The scan-paths were registered during the viewing of video based on SRL. Subsequently, the participants were asked to solve a crossword puzzle, and relevant vs. non-relevant Areas of Interest (AOI) were defined. Conventional statistical techniques (ANCOVA) and data mining techniques (string-edit methods and k-means clustering) were applied. The former only detected differences for the crossword puzzle. However, the latter, with the Uniform Distance model, detected the participants with the most effective scan-path. The use of this technique successfully predicted 64.9% of the variance in learning results. The contribution of this study is to analyze the teaching–learning process with resources that allow a personalized response to each learner, understanding education as a right throughout life from a sustainable perspective.

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Section: Discussionmentioning

confidence: 99%

Section: Areas Of Application Of Eye-tracking Technologymentioning

confidence: 99%

Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques

et al. 2020

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“…An experimental study was conducted to analyze learners' visual behaviour and brain activity as they interact with a computer-based learning environment called Amnesia: a medical simulation system that assesses analytical skills of novice medicine students through clinical problem-solving [70]. Fifteen participants (8 males, 7 females) aged 20-27 years (M = 21.8 ± 2.73) were recruited.…”

Section: Experimental Design and Methodologymentioning

confidence: 99%

“…Amnesia is a realistic computer-based environment developed for undergraduate medical students to assess their analytical reasoning process as they explore a series of observations and make clinical decisions through patient case solving. All the curricula underlying the software material were designed by a medical professional and approved by a doctor [70].…”

Section: Amnesiamentioning

confidence: 99%

Understanding Clinical Reasoning through Visual Scanpath and Brain Activity Analysis

et al. 2022

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This paper presents an experimental study that analyzes learners’ visual behaviour and brain activity in clinical reasoning. An acquisition protocol was defined to record eye tracking and EEG data from 15 participants as they interact with a computer-based learning environment called Amnesia, a medical simulation system that assesses the analytical skills of novice medicine students while they solve patient cases. We use gaze data to assess learners’ visual focus and present our methodology to track learners’ reasoning process through scanpath pattern analysis. We also describe our methodology for examining learners’ cognitive states using mental engagement and workload neural indexes. Finally, we discuss the relationship between gaze path information and EEG and how our analyses can lead to new forms of clinical diagnostic reasoning assessment.

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“…In a previous work, we applied this algorithm to our experimental data [51], [52]. We ran bivariate correlations to assess the relationships between the alignment score and students' results in the medical cases.…”

Section: *(-1) + 4*(-2)mentioning

confidence: 99%

Local Sequence Alignment for Scan Path Similarity Assessment

Khedher¹,

Jraidi²,

Frasson³

2018

IJIET

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Abstract-It has long been shown that there is a close relationship between eye movement, human cognition and brain activity. The present work seeks to explore this relationship by investigating the students' saccadic eye movement sequences in a problem solving task. We aim to assess students' reasoning process in a clinical problem solving task using students' visual trajectories. We use students' scan path, followed while resolving medical cases, and a local sequence alignment algorithm, to evaluate their analytical reasoning during medical case resolution. An experimental protocol was conducted with 15 participants. Eye movements were recorded while they were interacting with our learning environment. The proposed approach, based on gaze data, can be reliably applied to eye movement sequence comparison. Our findings have implications for improving novice clinicians' reasoning abilities in particular and ultimately enhancing learning outcomes.Index Terms-Cognitive tasks, eye movements, local sequence alignment, medical reasoning, scan path similarity.

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Tracking Students’ Analytical Reasoning Using Visual Scan Paths

Cited by 4 publications

References 5 publications

Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques

Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques

Understanding Clinical Reasoning through Visual Scanpath and Brain Activity Analysis

Local Sequence Alignment for Scan Path Similarity Assessment

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