Fig 3 - uploaded by Fajar Purnama
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Mouse Tracking Chrome extension. The mouse tracking extension is visible on the extension bar. The user can open the configuration window by clicking the icon and config. the events (clicks, moves, scrolls) to record.
Source publication
Mouse tracking serves as an alternative to eye tracking in measuring the learning process in education because of its affordability. Moreover, mouse tracking does not require extra hardware, as in the case of eye tracking, because it is a feature in personal computers by default. Therefore, it is possible to implement mouse tracking in a massive op...
Contexts in source publication
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... authors' laboratory server, which can be accessed on https://md.hicc.cs.kumamoto-u.ac.jp. The authors planned to publish the Moodle plugin on Moodle's website in the future. To implement the application on the client, the mouse tracking code is incorporated into the browser's code. This can be achieved by direct insertion or plugin installation. Fig. 3 shows a mouse tracking browser extension installed on Google's Chrome Browser. The authors plan to publish the extension in Chrome stores and other online stores. Implementation on a server is more efficient because the mouse tracking code is only installed on the server, whereas implementation on the client requires installation on ...
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... high level of activities only occurs momentarily and not constantly. Network and server administrators observed that mouse activities potentially generate a large amount of data. However, there was concern that this high level of activity is constant. The presented results clearly demonstrate that high-level mouse activity is mostly temporary. Fig. 13. Screenshot of mouse tracking data of students from National University of Mongolia who attempted a quiz session on a Moodle server at Kumamoto ...
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... authors were able to obtain mouse tracking data from 44 students in the School of Engineering and Applied Science, National University of Mongolia, for an online quiz session on the server in the Human Interface Cyber Communication Laboratory, Kumamoto University. Fig. 13 shows a screenshot of the mouse tracking data in form of a table. The table size is approximately 145 MB, containing 393585 rows and 22 columns. Are the rumors that mouse tracking produces a notoriously large amount of data true? The answer to this question is "yes." A half Copyright transferred from Fajar Purnama to Springer ...
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... which we need USD 2750. This is Author's pre-print which is the submitted version or before the peer review process. The final publication is available at https://link.springer.com/article/10.1007/s10639-020-10141-3. year Moodle log data with a similar number of students was only approximately 300 kB, while the mouse tracking data represented in Fig. 13 was 145 MB after 3 hours and 30 ...
Citations
... The authors of this paper want to track mouse movements in order to diagnose "technology acceptance items for students when interacting with a web-based tutoring system during a web development course" (Tzafilkou & Protogeros, 2020), this means the author is finding a correlation with technology and online tutoring [11]. Despite that their ultimate goal is different from us, we are both trying to track user mouse movements to analyze their behavior. ...
... The authors of this paper are tracking mouse movements, but on overseas quizzes [13]. Their mouse tracking system was "implemented on the Moodle learning management system and tested on an online quiz session accessed abroad" (Purnama et al., 2020). They were also able to record their data in real-time. ...
Online schooling has become more and more popular during recent years due to COVID-19 [1][15]. It allows teaching to continue without in-person contacts. A prominent issue with online schooling is teachers are unable to oversee students’ behavior during class as they would in-person. It has been known that many students tend to lose attention. This can make online schooling less effective, causing it to yield worse results than in-person schooling [2]. In order to tackle this issue,this paper outlines a tool that has been developed to monitor children’s mouse and keyboard movements during online classes and analyze the data with artificial intelligence to ensure students are focused in class [3]. For example, if the students are typing and clicking their mouse frequently, then there is a higher possibility the student is not focused because frequent keyboard and mouse movements might indicate they are chatting with friends or playing games; on the other hand, if they are attentive in class, there would be less keyboard and mouse movements, as they should be taking notes.
... • Mouse tracking web browser plugin and client side programming script [31,32]. ...
... The implementation of mouse tracking is based on DOM events, specifically mouse, touch, and user interface (UI) events which are actions that occurs as a result of the user's mouse actions or as result of state change of the user interface or elements of a DOM tree [37]. Our previous work [31] uses jQuery to access the DOM API and Purnama and Usagawa J Big Data (2020) 7:27 receives information that are related to mouse, touch, and UI events. They can be stored into default dynamic variables or in an ArrayBuffer for enhanced performance. ...
... Finally the information is either stored locally or sent to a server using hyper text transfer protocol (HTTP) post method. Traditionally, the information is transmitted all at once at the end of the session, but in our study [31], we found that it is better to transmit them in real-time without delay. The difference between offline, regular online, and real-time online mouse tracking is shown in Fig. 2. ...
Abstract Pageview is the most popular webpage analytic metric in all sectors including blogs, business, e-commerce, education, entertainment, research, social media, and technology. To perform deeper analysis, additional methods are required such as mouse tracking, which can help researchers understand online user behavior on a single webpage. However, the geometrical data generated by mouse tracking are extremely large, and qualify as big data. A single swipe on a webpage from left to right can generate a megabyte (MB) of data. Fortunately, the geometrical data of each x and y point of the mouse trail are not always needed. Sometimes, analysts only need the heat map of a certain area or perhaps just a summary of the number of activities that occurred on a webpage. Therefore, recording all geometrical data is sometimes unnecessary. This work introduces preprocessing during real-time and online mouse tracking sessions. The preprocessing that is introduced converts the geometrical data from each x and y point to a region-of-interest concentration, in other words only heat map areas that the analyzer is interested in. Ultimately, the approach used here is able to greatly reduce the storage and transmission cost of real-time online mouse tracking.
... • Mouse tracking web browser plugin and client side programming script [31] [32]. Some commercial and open source software programs are as follows: ...
... The implementation of mouse tracking is based on DOM events, specifically mouse, touch, and user interface (UI) events which are actions that occurs as a result of the user's mouse actions or as result of state change of the user interface or elements of a DOM tree [37]. Our previous work [31] uses jQuery to access the DOM API and receives information that are related to mouse, touch, and UI events. They can be stored into default dynamic variables or in an ArrayBuffer for enhanced performance. ...
... Finally the information is either stored locally or sent to a server using hyper text transfer protocol (HTTP) post method. Traditionally, the information is transmitted all at once at the end of the session, but in our study [31], we found that it is better to transmit them in real-time without delay. The difference between offline, regular online, and real-time online mouse tracking is shown in Figure 2. [31]. ...
Pageview is the most popular webpage analytic metric in all sectors including blogs, business, e-commerce, education, entertainment, research, social media, and technology. To perform deeper analysis, additional methods are required such as mouse tracking, which can help researchers understand online user behavior on a single webpage. However, the geometrical data generated by mouse tracking are extremely large, and qualify as big data. A single swipe on a webpage from left to right can generate a megabyte (MB) of data. Fortunately, the geometrical data of each x and y point of the mouse trail are not always needed. Sometimes, analysts only need the heat map of a certain area or perhaps just a summary of the number of activities that occurred on a webpage. Therefore, recording all geometrical data is sometimes unnecessary. This work introduces preprocessing during real-time and online mouse tracking sessions. The preprocessing that is introduced converts the geometrical data from each x and y point to a region-of-interest concentration, in other words only heat map areas that the analyzer is interested in. Ultimately, the approach used here is able to greatly reduce the storage and transmission cost of real-time online mouse tracking.
There is a growing concern to find an effective teaching and learning methodology during a social distancing situation as well as to address the drawbacks in the current educational system of Sri Lanka for students in Key Stage 1. Gamification has proved to make a positive impact on the concentration level, motivation and educational capabilities of students. Although previous research has been successful in introducing various gamified tools, very few are available in the local language. In this study, a gamified learning tool named “Punchi Nanasala” was introduced targeting grade 1 and 2 students which focussed on the subjects; Mathematics, Sinhala language, and Environmental studies. The tool was developed in three prototypes using a User-Centered-Design approach. The experimental and control groups Were given a pretest to measure their current knowledge capacity and a post-test to evaluate their knowledge capacity after the gamified treatment was given. The positive results obtained from the multiple evaluation techniques; Emotion detection, mouse click monitoring, performance analysis, interviews, and surveys suggested that the tool was successful as a learning approach.
Academic cheating is a significantly common occurrence at the university level in developing countries particularly, in Afghanistan. In online education practices, it could be a difficult task for a better process of secret reconstruction and identifying/ detecting the potential cheaters. Due to a huge number of students and the rapid increase of online education and penetration of the internet (the diversity of electronic devices used by learners in online activities), a big gap exists across creating an honest culture and teacher practices in the classroom. As such, raising the way of early prediction of potential cheaters through the mouse-tracking technique should be an urgent priority. In this paper, the authors examine the developed mouse tracking application along with the developed Moodle plugin in a blended course mid-term (20%) examination for the purpose of detecting and identifying the potential cheaters. The proposed model correctly predicted 94% of students committing illicit actions during the online mid-term examination, which can be possible to early intervene and prevent illegal actions. The study outcome can be used to analyze the learners’ mouse tracking behaviors that lead to a better process of secret reconstruction and transparent space.
