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Mouse Tracking Plugin on Moodle. The figure shows examples of mouse tracking implemented as a block plugin (in blue) and theme plugin (in red).
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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... HTML, CSS, and JS. A more direct approach is to inject the mouse tracking code in the JS code. Another approach is to create a plugin for a certain content management system (CMS) or LMS. In this work, a Moodle mouse tracking plugin was developed, which can be in the form of an admin plugin, theme plugin, or a block plugin shown as shown in Fig. 2. A theme plugin usually applies to entire Moodle pages managed by the administrator while a block plugin applies to selected pages usually managed by managers and teachers. Copyright transferred from Fajar Purnama to Springer Science+Business Media, LLC, part of Springer Nature and stated in their website that Springer encourages ...
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... more convenient to immediately measure the average resource costs. Unlike the P2P experiments, the local experiment measures not only the mouse tracking but also all the other processes, which includes accessing the Moodle page and answering 10 questions. During this experiment, the CPU percentage Fig. 10, the RAM usage Fig. 11, and the data rate Fig. 12 were rarely zero, indicating that idle activity was uncommon. For the local experiment with five users, the CPU percentage usage was an average of 10%, the RAM usage was an average of 1.7 GB, and the data rate was an average of 51 kB. This indicates that there was a reserve capacity for more users. It should be noted that the initial ...
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... interesting result is shown in Fig. 12 for the data rate. During the quiz session at approximately 17:02:40-17:14:20 (11 minutes and 40 seconds, or 700 seconds), a table size of 6.1 MB with approximately 16287 rows (equivalent to 16287 events) and 17 columns were generated (note that the number of columns is less than the number of introduced variables in Table 1 because ...
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... a single mouse swipe produce hundreds of mouse coordinates ( Leiva and Huang, 2015)? The answer is "yes," is we examine the spikes in Fig. 12. The highest Copyright transferred from Fajar Purnama to Springer Science+Business Media, LLC, part of Springer Nature and stated in their website that Springer encourages pre-print sharing and even allowing authors to license it as creative commons. The accepted version can only be shared 12 months after publication, so if you want to ...
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.
