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In this article is presented the result of qualitative investigation in which a case study method and eye tracking technology were used. The participant has analyzed the algorithm shown in the flowchart. The path of saccades and fixations were recorded and the researchers followed the process of solving linear equations. The results confirmed the h...
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People who act in emergencies must make decisions based on their perceptions of the environment. Thus, emergency equipment, such as a fire extinguisher, must be identified clearly and quickly (intuitive use). Thereby, this paper presents the visual perception study of a Brazilian extinguisher using Eye Tracking. This case study involves twelve part...
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... It has been hypothesized that individuals who are able to solve a problem successfully tend to focus their visual attention on the most salient information needed to solve the problem [12]. This hypothesis was confirmed in the study [13]. Eye tracking scaffolding in the form of introducing an immediate feedback mechanism has also been shown to have a significant impact on promoting students' sense of self-efficacy when learning C programming [11]. ...
Prediction of visual attention is a new and challenging subject, and to the best of our knowledge, there are not many pieces of research devoted to the anticipation of students’ cognition when solving tests. The aim of this paper is to propose, implement, and evaluate a machine learning method that is capable of predicting saliency maps of students who participate in a learning task in the form of quizzes based on quiz questionnaire images. Our proposal utilizes several deep encoder–decoder symmetric schemas which are trained on a large set of saliency maps generated with eye tracking technology. Eye tracking data were acquired from students, who solved various tasks in the sciences and natural sciences (computer science, mathematics, physics, and biology). The proposed deep convolutional encoder–decoder network is capable of producing accurate predictions of students’ visual attention when solving quizzes. Our evaluation showed that predictions are moderately positively correlated with actual data with a coefficient of 0.547 ± 0.109. It achieved better results in terms of correlation with real saliency maps than state-of-the-art methods. Visual analyses of the saliency maps obtained also correspond with our experience and expectations in this field. Both source codes and data from our research can be downloaded in order to reproduce our results.
... To study and detect different levels of performance, eye tracking is a suitable technology. Eye tracking allows to assess peoples' reading behavior and objectively indicates their underlying cognitive processes [Meng Lung et al. 2013;Stolińska and Andrzejewska 2017]. Therefore, this paper contributes an eye tracking study that examines student's visual attention and mental schema when solving programming problems. ...
This eye tracking study examines participants' visual attention when solving algorithmic problems in the form of programming problems. The stimuli consisted of a problem statement, example output, and a set of multiple-choice questions regarding variables, data types, and operations needed to solve the programming problems. We recorded eye movements of students and performed an Area of Interest (Aol) sequence analysis to identify reading strategies in terms of participants' performance and visual effort. Using classical eye tracking metrics and a visual Aol sequence analysis we identified two main groups of participants---effective and ineffective problem solvers. This indicates that diversity of participants' mental schemas leads to a difference in their performance. Therefore, identifying how participants' reading behavior varies at a finer level of granularity warrants further investigation.
The ability to solve problems using algorithms plays an increasingly important role in modern society, whereas programming, alongside with broadly understood digital skills, are considered to be one of the key competences of the future. The result of this trend is the modification in the Polish education system of the IT subjects’ core curriculum, under which teaching programming is planned at every stage of education. While teaching the skills of programming is important, it is not an easy task to achieve and hence it poses many methodological challenges. Researchers in this field are increasingly turning to new experimental methods, such as eye tracking techniques that allow to gain an insight into cognitive mechanisms and thus can provide objective information about the process of learning programming. The article discusses the results of authors’ own study, in which the state of declarative and procedural knowledge of students related to the forms of algorithm presentation was diagnosed. The questionnaires along with the tasks included in them, which the students solved in a traditional way and with the means of eye tracking techniques, were used in the study to track the process of solving comparable tasks presented on a computer monitor. The indicator of operational knowledge was the effectiveness of problem solving. The research was conducted on a group of 48 third-grade junior secondary school students.The obtained results (low level of correct answers) indicate that the situation in the area of learning the algorithmic skills of students requires improvement. The measurement data obtained using eye tracking allowed for an in-depth analysis and interpretation of visual activity of students. Therefore, it seems that eye tracking can be considered as a complementary research technique, enriching the state of knowledge on cognitive mechanisms that are triggered in the process of solving algorithmic problems.
