Applying Eye Tracking to Identify Students' Use of Learning Strategies in Understanding Program Code

2019 ◽  
Author(s):  
Gary Cheng ◽  
Leonard K. M. Poon ◽  
Wilfred W. F. Lau ◽  
Rachel C. Zhou
Keyword(s):  
Eye Tracking ◽  
Learning Strategies ◽  
Program Code

scholarly journals How are learning strategies reflected in the eyes? Combining results from self-reports and eye-tracking

2017 ◽  
Vol 88 (1) ◽  
pp. 118-137 ◽  
Author(s):  
Leen Catrysse ◽  
David Gijbels ◽  
Vincent Donche ◽  
Sven De Maeyer ◽  
Marije Lesterhuis ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Learning Strategies ◽  
Self Reports

Image Analysis

2013 ◽  
pp. 1-14
Author(s):  
Detlev Droege
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Eye Tracking ◽  
Real Time ◽  
Basic Knowledge ◽  
Eye Tracker ◽  
Tracking Systems ◽  
Program Code ◽  
Time Performance

This chapter focuses on the image processing part of eye tracking systems. Basic knowledge of image processing is assumed. After an overview of the possible input images and some remarks on preprocessing of the images, we will focus on the detection relevant features such as pupils and glints. The last part of this chapter focuses on estimating positions of these features. It is not possible to present a comprehensive solution for an eye tracker in this chapter; however, we will indicate possible yet simplified methods in the different steps of processing and demonstrate how images can be processed to obtain real-time performance. The program code is given in Matlab (Octave) language for clarity.

scholarly journals Impacts of Color Coding on Programming Learning in Multimedia Learning: Moving Toward a Multimodal Methodology

2021 ◽  
Vol 12 ◽  
Author(s):  
Yang Liu ◽  
Weifeng Ma ◽  
Xiang Guo ◽  
Xuefen Lin ◽  
Chennan Wu ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Pupil Diameter ◽  
Learning Performance ◽  
Physiological Measures ◽  
Color Coding ◽  
Eeg Signals ◽  
Program Code ◽  
Video Lectures ◽  
Band Power ◽  
Practical Implications

In the present study, we tested the effectiveness of color coding on the programming learning of students who were learning from video lectures. Effectiveness was measured using multimodal physiological measures, combining eye tracking and electroencephalography (EEG). Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions (color-coded vs. grayscale). The participants’ eye tracking and EEG signals were recorded while watching the assigned video, and their learning performance was subsequently assessed. The results showed that the color-coded design was more beneficial than the grayscale design, as indicated by smaller pupil diameter, shorter fixation duration, higher EEG theta and alpha band power, lower EEG cognitive load, and better learning performance. The present findings have practical implications for designing slide-based programming learning video lectures; slides should highlight the format of the program code using color coding.

scholarly journals Eye Tracking and Learning Predictability

2020 ◽  
Vol 2 (4) ◽  
pp. 18
Author(s):  
Tiffanye McCoy-Thomas
Keyword(s):  
Early Intervention ◽  
Eye Tracking ◽  
Learning Strategies ◽  
Research Method ◽  
Empirical Studies ◽  
Learning Behaviors

Eye-tracking is a unique research method in education to help understand learners’ attention, reading struggles, learning strategies, and learning behaviors within the context of multimedia. This study overviews the empirical studies in this field, examines the role of eye-tracking in learning predictability, and discusses the ways that eye-tracking can be used for early intervention.

Image Analysis

2012 ◽  
pp. 296-309
Author(s):  
Detlev Droege
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Eye Tracking ◽  
Real Time ◽  
Basic Knowledge ◽  
Eye Tracker ◽  
Tracking Systems ◽  
Program Code ◽  
Time Performance

This chapter focuses on the image processing part of eye tracking systems. Basic knowledge of image processing is assumed. After an overview of the possible input images and some remarks on preprocessing of the images, we will focus on the detection relevant features such as pupils and glints. The last part of this chapter focuses on estimating positions of these features. It is not possible to present a comprehensive solution for an eye tracker in this chapter; however, we will indicate possible yet simplified methods in the different steps of processing and demonstrate how images can be processed to obtain real-time performance. The program code is given in Matlab (Octave) language for clarity.

When two computer-supported learning strategies are better than one: An eye-tracking study

2018 ◽  
Vol 125 ◽  
pp. 376-388 ◽  
Author(s):  
Héctor R. Ponce ◽  
Richard E. Mayer ◽  
María Soledad Loyola ◽  
Mario J. López ◽  
Ester E. Méndez
Keyword(s):  
Eye Tracking ◽  
Learning Strategies ◽  
Better Than

An Eye-Tracking Study on Audiovisual Speech Perception Strategies Adopted by Normal-Hearing and Deaf Adults Under Different Language Familiarities

2020 ◽  
Vol 63 (7) ◽  
pp. 2245-2254 ◽  
Author(s):  
Jianrong Wang ◽  
Yumeng Zhu ◽  
Yu Chen ◽  
Abdilbar Mamat ◽  
Mei Yu ◽  
...  
Keyword(s):  
Speech Perception ◽  
Eye Tracking ◽  
Normal Hearing ◽  
Audiovisual Speech ◽  
Audiovisual Speech Perception ◽  
Allocation Pattern ◽  
Deaf Adults ◽  
Bilingual Speaker ◽  
Primary Hypothesis ◽  
Standard Chinese

Purpose The primary purpose of this study was to explore the audiovisual speech perception strategies.80.23.47 adopted by normal-hearing and deaf people in processing familiar and unfamiliar languages. Our primary hypothesis was that they would adopt different perception strategies due to different sensory experiences at an early age, limitations of the physical device, and the developmental gap of language, and others. Method Thirty normal-hearing adults and 33 prelingually deaf adults participated in the study. They were asked to perform judgment and listening tasks while watching videos of a Uygur–Mandarin bilingual speaker in a familiar language (Standard Chinese) or an unfamiliar language (Modern Uygur) while their eye movements were recorded by eye-tracking technology. Results Task had a slight influence on the distribution of selective attention, whereas subject and language had significant influences. To be specific, the normal-hearing and the d10eaf participants mainly gazed at the speaker's eyes and mouth, respectively, in the experiment; moreover, while the normal-hearing participants had to stare longer at the speaker's mouth when they confronted with the unfamiliar language Modern Uygur, the deaf participant did not change their attention allocation pattern when perceiving the two languages. Conclusions Normal-hearing and deaf adults adopt different audiovisual speech perception strategies: Normal-hearing adults mainly look at the eyes, and deaf adults mainly look at the mouth. Additionally, language and task can also modulate the speech perception strategy.

The Role of Test Anticipation in the Link Between Performance-Approach Goals and Academic Achievement

2016 ◽  
Vol 75 (3) ◽  
pp. 123-132 ◽  
Author(s):  
Marie Crouzevialle ◽  
Fabrizio Butera
Keyword(s):  
Learning Strategies ◽  
Test Performance ◽  
Longitudinal Design ◽  
Study Strategies ◽  
High Achievers ◽  
Course Content ◽  
And Mathematics ◽  
Set Up ◽  
Approach Goals ◽  
Goal Endorsement

Abstract. Performance-approach goals (i.e., the desire to outperform others) have been found to be positive predictors of test performance, but research has also revealed that they predict surface learning strategies. The present research investigates whether the high academic performance of students who strongly adopt performance-approach goals stems from test anticipation and preparation, which most educational settings render possible since examinations are often scheduled in advance. We set up a longitudinal design for an experiment conducted in high-school classrooms within the context of two science, technology, engineering, and mathematics (STEM) disciplines, namely, physics and chemistry. First, we measured performance-approach goals. Then we asked students to take a test that had either been announced a week in advance (enabling strategic preparation) or not. The expected interaction between performance-approach goal endorsement and test anticipation was moderated by the students’ initial level: The interaction appeared only among low achievers for whom the pursuit of performance-approach goals predicted greater performance – but only when the test had been scheduled. Conversely, high achievers appeared to have adopted a regular and steady process of course content learning whatever their normative goal endorsement. This suggests that normative strivings differentially influence the study strategies of low and high achievers.

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