Development of Mobile Learning Digital Engineering for Electrical Engineering Education Students
Alifio Yoga Pradana
(1), Danar Amirul Kaffi
(2), Hafiz Muqorobbin
(3), Muhammad Fauzan
(4), Athaya Rashif Hanang Syah
(5)(1)(2)(3)(4)
Universitas Negeri Semarang
(5)
Universitas Diponegoro
Email: [email protected]
ABSTRACT
This study aims to develop a mobile learning device for digital engineering students in Electrical Engineering Education, testing its effectiveness and practicality. The research method used is Research and Development. The stages of this research process include:
(1) preliminary stage, in the form of literature study, preliminary research on the use of smartphones, analyzing the syllabus, determining the substance of the material and learning objects; (2) development stage, making a
Map of learning programs integrated into digital engineering mobile learning; (3) validation stage, conducted by media and material experts. After obtaining validation with decent criteria, it can be tested. Testing was carried out at the Electrical Engineering Department of Semarang State University, involving ten small group trial students and 31 field test students—data collection methods in the form of test questions and questionnaires. Media validation test results amounted to 83.25% (feasible), while material validation amounted to 95.5% (feasible). The results of the small group trial obtained an average score of pre-test 70.0 and post-test 89.0 with a gain of 0.63 (medium). The field test results obtained an average score of 67.9 pre-test and 85.2 post- test with a gain of 0.54 (medium). The practicality test results obtained 82.8% and were included in the practical criteria. Thus, it can be concluded that digital engineering mobile learning development is feasible, effective, and practical for use as a learning medium for digital engineering courses.
Keywords: Development, Mobile learning, Electrical engineering
INTRODUCTION
The utilization of Information and Communication Technology (ICT) has now experienced relatively rapid development. The ease of accessing the internet is an essential aspect supporting the role of ICT.
In Indonesia, although not all areas can be reached by the Internet, the government and the private sector work together to develop the Internet so that people can enjoy easy access. The impact of technological innovation also varies based on a country's income level. Research shows that technological innovation tends to support all pillars of sustainable development only in developed countries. In contrast, in middle-income countries such as Indonesia, the impact is more limited to the economic and environmental dimensions (Omri, 2020). However, financial development often associated with technological innovation can negatively affect the environment, such as by increasing CO2 emissions. These effects vary by financial indicator, estimation technique, country, and period, suggesting the need for a balanced strategy to ensure environmentally friendly technological development ( Gök, 2020).
The Internet, which is an acronym for interconnection networking , is a computer network on a worldwide scale. The Internet makes communication borderless. Along with technological advances, mobile phones are no longer only used to send and receive Short Message Service (SMS) or calls. Cell phones can also be used to access the internet with services that support data transmission, such as GPRS, EDGE, 3G, 4G, or Wi-Fi (Huang et al., 2021). Internet use in Indonesia is regulated by the Law of the Republic of Indonesia Number 11 of 2008 on Electronic Information and Transactions, better known as the ITE Law.
Technological developments also support the improvement of network reliability, such as the application of silicon photonic-electronic neural networks to compensate for fiber nonlinearity, which has been proven to improve the reliability of the network in addition to improving efficiency and reliability, investment in technology research and development can also have a positive impact on the environment. Research shows that increased R&D investment in BRICS countries reduces carbon emissions by 0.8122%. However, other factors such as economic activity, industrialization, and renewable energy consumption also have a significant effect (Wang & Zhang, 2020).
Cell phones also increased in number with many types and models until the development of smartphones, commonly known as smartphones. A smartphone is a mobile phone with high-level capabilities, sometimes with computer-like functions. The development of material technology, such as halide perovskites, faces challenges in the electrical doping process due to intrinsic defects and easy ion migration. However, controlling the electronic properties of these materials is essential for energy and optoelectronic applications, including advanced technology-based mobile learning devices (Euvrard et al., 2021).
In other words, smartphones are mini-computers that have more capabilities than phones. In addition to hardware and software advances, the development of energy technologies such as ambient radio-frequency energy harvesting opens up opportunities for new electronic devices, including mobile-based educational applications, by utilizing advanced semiconductor materials such as graphene and gallium nitride (Zhang et al., 2020).
Mobile phones can be used in education as a learning media through mobile devices, also called mobile learning. Mobile learning refers to the use of mobile or wireless devices with the aim of learning that can be done anywhere. In some universities, as seen in Spain, the
application of mobile devices in education reaches almost 73%.
However, sociodemographic factors, including faculty status, type of institution, and educational technology research, influence the development of good teaching practices in mobile learning (Romero- Rodríguez et al., 2020). In the context of technology development, specific and cost-effective system design approaches, such as in applying pulsed electric field technology in the food industry, are vital to ensuring the sustainability and efficiency of the applied technology (Arshad et al., 2020).
Mobile learning influences learning processes and products, provides new opportunities to influence learning outcomes, and collects data that can improve understanding and modeling of learning processes, which is essential in educational technology development (Bernacki et al., 2020). Mobile learning is widely used because it can be accessed anytime and anywhere, especially by students with mobile devices such as smartphones, phablets, or tablets. Research shows that the most effective mobile learning approaches involve augmented reality, are focused on higher education, and are smartphone-based.
Taiwan, the United States, China, and the United Kingdom are the most influential countries in contributing to this research (Göksu, 2021). In higher education institutions, mobile learning applications cover many aspects, such as learning management, vodcasts and podcasts, and smartphone-based learning. Game-based, collaborative, and language-learning applications support more innovative and effective learning (Goundar & Kumar, 2021). Often, these mobile devices are only used to interact on social media, play games, take selfies, and so on. Mobile devices can also be used as learning tools for various tasks, such as collecting homework, reflecting on hands-on learning experiences, and sharing ideas with fellow students or lecturers, thus increasing learning engagement and effectiveness (Sophonhiranrak, 2021). The use of mobile devices in student learning is still rare. Therefore, using mobile devices in lectures is expected to support learning because many students already have them but have not maximized their functionality.
This principle aligns with views in other fields, such as nursing, where continuing professional development (CPD) is considered essential for professionalism and lifelong learning. Accessibility and relevance of learning, including through digital media, are crucial to improving the quality of education and work outcomes (Mlambo et al., 2021). While financial development is often perceived as less supportive of economic growth, the diffusion of information and communication technologies (ICTs) can drive such growth. The positive impact is even more substantial in middle- and low-income countries, making it relevant for the Indonesian context in developing mobile learning media (B. Chen et al., 2020). However, it is crucial to consider the long-term impact of technology on cognitive health. However, it is vital to consider the negative impact of technology use on cognitive development, especially at a young age. Impaired brain development can lead to neurodevelopmental disorders with cortical malformations closely associated with neuropsychiatric disorders (Hines, 2021). Research shows that non-coding RNAs (ncRNAs) play an essential role in the developing brain and neurodevelopmental disorders, which can be affected by exposure to external factors such as technology, chemicals, or infections (Arzua et al., 2021). The development of wearable electronics and photonics, integrating artificial intelligence (AI) and the Internet of Things (IoT), opens up opportunities for intelligent applications such as bright clothing, smart homes, and smart cities.
These technologies can be adapted to support mobile-based learning devices, making them increasingly relevant in digital education environments (Shi et al., 2020).
Digital engineering is one of the courses that students must take in
the Electrical Engineering Education study program. The learning activities carried out in digital engineering courses in the Electrical Engineering Education study program have been. However, there are still some obstacles, namely the large percentage of students who repeat the Digital Engineering course. In addition, the level of self-efficacy in completing complex tasks and self-regulation abilities in Electrical Engineering students can vary depending on their level of education and previous experience in programming (Kittur, 2020).
Based on a survey of the Academic System, a list of participants in digital engineering courses in the last three academic years was obtained. In the academic year 2012/2013, as many as 25 students were expelled out of 101 students (25%). In the 2013/2014 academic year, 60 students repeated out of 149 students (40%). In the 2014/2015 academic year, 32 students were repeated out of 124 students (26%).
Many factors cause a large percentage of students to repeat digital engineering courses. One aspect that significantly affects achieving competence is how lecturers learn. Learning. There is a tendency for the learning process to remain lecturer-centered, where lecturers tell more stories or lectures can make students not actively involved in learning.
Lecturers who do not / rarely use learning media also cause the learning process to be passive.
The paradigm of lecturer-centered learning must begin to be replaced with a student-centered learning orientation. Lecturers can implement student-centered learning as facilitators who provide learning media, including mobile learning. The existence of mobile learning is expected to make it easier for lecturers to visualize digital engineering material. Along with the development of technology, various studies on the prediction of electrical energy consumption in the manufacturing industry also provide insight into how technology can be used to optimize the use of resources, which is relevant to the development of efficient and environmentally friendly technology- based mobile learning devices (Walther & Weigold, 2021). The application of visualization is packaged in the form of text, video, multimedia, and animation.
Some research results on the use of mobile learning show a positive impact on improving student competence. The study results mentioned that groups using high-frequency mobile devices have increased feedback and math achievement scores compared to low- frequency mobile device groups and traditional groups. In addition, the research mentioned that perseverance in online classes is more challenging than in conventional classes. In addition, participation in online classes can reduce fear, and the quality and quantity of interaction will increase.
Mobile learning development can be an alternative media for learning digital techniques for Electrical Engineering Education students. The development of digital engineering mobile learning must follow the essential competencies in the syllabus of digital engineering courses. Therefore, this research aims to develop digital engineering mobile learning tools for Electrical Engineering Education students and test their effectiveness.
METHODS
The research method used is Research and Development. The concrete steps in the research procedure developed are (1) the preliminary stage, (2) the development stage, and (3) the validation stage. Media experts and material experts conducted the validity test.
The research was conducted at the Electrical Engineering Department of Semarang State University, involving ten small group trial students and 31 field trial students. A questionnaire sheet evaluated the technical, media, and educational quality. In contrast, the instrument in the form of a test was used to determine the extent of the achievement of student learning outcomes before and after using the developed digital engineering mobile learning.
RESULTS AND DISCUSSION
Form Development Digital Engineering Mobile Learning Device for Electrical Engineering Education Students
This digital engineering mobile learning tool for Electrical Engineering Education students is developed using the Edmodo Learning Management System (LMS) application. The development of Edmodo-based mobile learning tools is also integrated with several learning objects, including text objects, graphic/image objects, animations, audio, video, and interactive links. The mobile learning application can also be customized for special groups like refugees. The application has 15 characteristics, including interrelated psychological, educational, and cultural features of refugees, which can increase the relevance and effectiveness of learning for this group (Drolia et al., 2022). Technology maintenance and adaptation challenges are also significant concerns in educational technology development. As developers of smart contracts in the Ethereum ecosystem face the need for method adaptation and innovation to address future challenges, this is an essential lesson for developing digital learning tools (J. Chen et al., 2020). Flexible approaches to tool development, as seen with UWE and OOHDM in web development in dynamic environments, are also relevant to ensure that mobile learning systems can be adapted to the needs of different sizes of learning groups and knowledge levels of users (Ríos &
Pedreira-Souto, 2020). The integration of several learning objects is selected and adjusted to the essential competencies and subject matter of digital engineering learning. Two-dimensional semiconductor materials with tunable bandgaps can support the development of more efficient electronic and optoelectronic technologies, thus enabling innovations for digital-based educational applications (Chaves et al., 2020).
The developed digital engineering mobile learning covers seven essential competencies that have been adjusted to the digital engineering course syllabus. The seven essential competencies are: (1) number system, (2) primary gate, (3) Boolean and De Morgan theorems, (4) combinational circuits, (5) digital arithmetic, (6) flip-flops, and (7) counters and registers. Each basic competency consists of several sessions. In addition to software development, optimizing thermoelectric systems through weighted mobility analysis can improve the energy efficiency of electronic devices. This can be done by analyzing the electronic structure and scattering mechanism in semiconductor materials, which is relevant to support the sustainability of mobile learning devices based on the latest technology (Snyder et al., 2020).
Each digital engineering mobile learning development session is divided into introduction, core, and closing activities. Like the complex inter-neuron interactions facilitated by multifunctional recognition molecules to support brain development, digital learning tools also require strategies that pay attention to the complexity of student needs
and material specificity to achieve optimal results (Sanes & Zipursky, 2020). Each session is presented separately in the Edmodo application so that students can download the sequence of learning activities according to the digital engineering course syllabus. The application of precision control in advanced electrical drives can be adapted to support the development of mobile learning devices, which enable more efficient control of interaction and learning and energy savings on digital devices used in education (Doncker et al., 2020).
Just as optimizing the performance of energy systems by exploiting sulfur hole defects in MoS2 nanosheets, the development of efficient learning devices also requires optimizing materials and technologies to develop efficient learning devices. The primary competency 1 number system is divided into sessions 1, 2, and 3. Session 1 contains core activities in the form of 1.1 Quantity Representation, 1.2 Binary Representation, 1.3 Binary to Decimal Conversion, and 1.4 Decimal to Binary Conversion. The time allocation presented in learning session 1 is around 100 minutes, with details of 5 minutes for introduction, 90 minutes for material and quiz, and 5 minutes for closing. The primary learning materials in sessions 1, 2, and 3 integrate text learning objects, graphics/images, and interactive links, each packaged in a PowerPoint file with a .ppsx extension. The Note feature uploads the session file to the Edmodo application. The session learning subject matter that the lecturer account has uploaded to the Edmodo application can appear in the Edmodo application of the student account, as shown in Figure.
Figure1. Session 1 Mobile Learning Digital Engineering on Edmodo Student Accounts
After students have finished downloading and studying the material in session 1, they can then take a quiz on session 1 test questions on their Edmodo account. After studying session one and doing the quiz, students can start learning session two about the 1.5 Octal Number System. Next, after finishing studying session two and taking the session two quizzes, students can continue learning session 3 with core activity 1.6 Hexadecimal Number System. After studying session 3, students can work on session three quizzes. After completing studying sessions 1, 2, and 3, students can work on assignments as basic competency tasks 1. Tasks that can be downloaded on the student's
Edmodo account are in the form of description questions in the file format with the extension of .docx, as presented in Figure 2.
Figure2. Basic Competency Task Assignment Upload 1
Sessions 4 to 7 are basic gate competency materials developed in .swf files. The time allocation presented in learning sessions 4 to 7 is around 100 minutes each, with learning objects in text, graphics/images, animation, audio, and interactive links.
In addition to being developed in the.swf file format, sessions 4 to 7 were converted into video format to be uploaded to the YouTube application. The YouTube application only allows uploading files with specific extensions. Extension .avi is one of the file extensions that is allowed on YouTube. Therefore, it is necessary to convert files from .swf to .avi, so the Sothink SWF to Video Converter 2.4 software is used. The purpose of uploading the video is to make it easier for students to use the facility to watch videos stored offline on YouTube, considering that no offline video viewing menu is available on Edmodo. After completing the study of sessions 4 to 7, students can work on assignments in the form of basic competency two tasks uploaded to the Edmodo account.
The following learning activity is session nine on Boolean Theorem and De Morgan. The learning time allocation for session 9 is approximately 100 minutes, with learning objects in the form of text, graphics/images, audio, video, and interactive links integrated into a .ppt file from PowerPoint, which is then recorded with the help of Camtasia Studio 7 software to form a video in the .mp4 file format. The video results are then uploaded to Edmodo. After completing the study of the next session 9, students can do quizzes and assignments.
Competencies Basic competencies Combinational circuits are developed in sessions 10 and 11 with learning objects in text, graphics/images, and interactive links in .pptsx files integrated with the Edmodo application. After completing the study of sessions 10 and 11, students can work on the quiz sessions 10 and 11. In addition, students can also work on the assignment of four basic competency tasks on the Edmodo account.
The primary competency of digital arithmetic is developed in sessions 12 and 13. The time allocation presented in sessions 12 and 13 is around 100 minutes, with learning objects in text, graphics/images, and interactive links. After completing the study of sessions 12 and 13, students can do the quiz sessions 12 and 13. In addition, students can also work on assignments in the form of basic competency five tasks uploaded to the Edmodo account.
Session 14 contains the essential competencies of flip-flops with a learning time allocation of 100 minutes. After completing the learning session 14, there is a quiz and assignment. The learning object of session 14 is text, graphic/image, audio, video, and interactive link in a .ppsx file.
After the PowerPointShow file is finished, it is integrated with Screen Recorder software from http://screencast-o-matic.com/ to produce a video learning session 14 in .mp4 file format, then uploaded to the Edmodo application and YouTube channel.
Session 15 contains the essential competencies of counters and registers with a time allocation of around 100 minutes. The learning objects of session 15 are text, graphics/images, and interactive links in a .pdf file integrated with the Edmodo application. After completing the study of session 15, students can take the session 15 quiz. In addition, students can also work on assignments in the form of basic competency seven assignments on the Edmodo account.
Validity Test Results of Mobile Learning Digital Engineering for Electrical Engineering Education Students
The validity test from media experts aims to determine the criteria for ease of access, readability and display quality, documentation quality, flexibility, and the quality of tests and assessments. Based on the results of the validity test from media experts, a validity percentage of 83.25% was obtained or in very feasible criteria.
The validity test from material experts aims to determine the criteria for learning planning, presentation of learning materials, and learning evaluation. The use of efficient optimization algorithms such as AEFA-C, which combines speed and position limits, can be applied to design learning systems that are more efficient in using resources and time and support the development of more optimal learning media (Anita et al., 2020). Based on the results of the validity test from material experts, a validity percentage of 95.5% was obtained or in perfect criteria.
The results of the Digital Engineering Mobile Learning Effectiveness Test for Electrical Engineering Education Students
The small group trial was conducted with ten students. The average initial ability of students was 70.0, and the average final ability was 89.0. The highest value of the pre-test results of the small group trial was 96.0, while the lowest value was 52.0. The highest score on the post- test results of the small group trial small group trial was 100.0, while the lowest score was 66.0. Increase in the average score (gain) of 0.63 or moderate criteria.
Table 1. Results of Pre-Test and Post-Test Scores of Small Group Trial Criteria n Max Min Mean Gain
Pre Test 10 96,0 52,0 70,0 0,63 The post
Test
10 100,0 66,0 89,0 medium criteria Source: Research Data Analysis
The field trial was conducted on 31 students. The average initial ability of students was 67.9, and the average final ability was 85.2. The highest score in the pre-test results of the field trial was 95.0, while the lowest score was 32.5. The highest score on the post-test results of the field trial was 100.0, while the lowest score was 47.5. The average score (gain) increase is 0.54 or in moderate criteria.
Table 3. Practicality Test Results
Interval Percentage (%) Criteria (%) n
80 - 100 Very Practical 22
60 - 79,9 Practical 9
40 - 59,9 Not Practical 0
20 - 39,9 Not Very Practical 0
Total 31
Practicality Test Percentage 82,8
Source: Research Data Analysis
The development of the Internet and mobile phone technology has become a new trend that enables mobile learning. The combination of communication technology and the internet enables the development of a mobile learning system, which utilizes mobile devices on the client side. Mobile learning is a type of e-learning that provides educational content and materials learning support through wireless communication devices. An education-based mobile learning application is a learning management system (LMS). LMS is a software application designed to help lecturers fulfill the pedagogical goal of delivering learning content to students.
Mobile learning digital techniques developed in this study utilize Android-based smartphones and the internet among students. Mobile learning refers to the use of mobile or wireless devices with the aim of learning that can be done anywhere. Mobile learning also involves learning in various contexts through social interaction, using personal electronic devices capable of capturing information and providing it in real-time, thus enabling a more dynamic and flexible learning experience (Danish & Hmelo‐Silver, 2020). The existence of mobile learning digital techniques is expected to allow students to access online learning anywhere and anytime.
The digital engineering mobile learning developed utilizes an LMS called Edmodo. Edmodo is a free LMS accessed through http://www.edmodo.com or downloaded on a Play Store smartphone.
The selection of Edmodo as an LMS is due to its ease of free download and the context of the system, which is a social network, so that it can be more familiar to use. Edmodo was developed following the trend of famous social media such as Facebook, where students and lecturers can communicate and connect in an online social environment specifically for safe and secure learning.
Learning interactions with students through Edmodo include providing teaching materials, assignments, quizzes, polls, and assessments. In developing digital learning tools, challenges similar to DevSecOps adoption may also occur, such as issues related to the tools used and the need to balance development speed with system security.
This shows the importance of a careful approach to ensuring the efficiency and security of learning media (Rajapakse et al., 2021). The features on Edmodo used in this digital engineering mobile learning research include the Note, Alert, Quiz, and Poll features. The Note feature on Edmodo is used to provide learning materials to students. The Alert feature on Edmodo reminds students of the deadline for certain activities. The Quiz feature can be used to evaluate learning activities.
The poll feature can be used to determine student responses to some issues.
This digital engineering mobile learning was developed in 16 learning sessions. Each digital engineering mobile learning development session is divided into 5- 5-minute introductory activities, 90-minute core activities, and 5-minute closing activities. Each session is uploaded separately in the Edmodo application using the Note feature so that students can download it according to the session sequence and the digital engineering course syllabus.
Evaluation of learning media is needed to determine its effectiveness. To determine the quality of learning media, one must look at the criteria (1) quality of content and objectives, (2) instructional
quality, and (3) technical quality. Before being tested on respondents, this digital engineering mobile learning has undergone the stages of media and material validation tests. The average percentage of media validity test results is 83.25% or in very feasible criteria, while the average percentage of material validity test results is 95.5% or in very feasible criteria. Based on the validity test results from media and material experts, it can be concluded that the digital engineering mobile learning developed in the validity criteria is very feasible.
Some research results on the use of mobile learning show a positive impact in improving student competence. The study results mentioned that groups using high-frequency mobile devices have increased feedback and math achievement scores compared to low- frequency mobile device groups and traditional groups. The study results mentioned that perseverance in online classes is more challenging than in conventional classes, participation in online classes can reduce fear, and the quality and quantity of interaction can increase.
Although mobile technology has great potential to support academic learning, more research is needed, focusing on media comparisons, instructional features, and boundary conditions that affect the effectiveness of these technologies in higher education contexts (Mayer, 2020).
The effectiveness data of this digital engineering mobile learning development can be seen from the acquisition of student pre-test and post-test scores. The results of the small group trial obtained the average pre-test results of students in the small group trial of 70.0 and the average post-test results of 89.0. The average score (gain) increase was 0.63 or in moderate criteria. The field trial results obtained an average pre-test result of 67.9 and an average post-test result of 85.2.
The average score (gain) increase was 0.54 or in moderate criteria.
Based on the gain, it can be concluded that there is an increase in student learning outcomes before and after using mobile learning digital techniques with moderate criteria. As in nursing education, where mobile learning improves students' skills, knowledge, satisfaction, and confidence compared to conventional methods, the same technology can significantly positively impact digital engineering learning in higher education (B. Chen et al., 2020). In addition, mobile learning has also been shown to improve self-regulated learning (SRL), with more than three-quarters of studies concluding that m-learning not only improves SRL but also mutually reinforces various other learning factors (Criollo- C et al., 2021). These findings align with other research showing that mobile learning has a moderate positive effect on student achievement in mathematics, demonstrating the potential of this technology to gradually improve learning outcomes (Güler et al., 2021). In addition, mobile learning has also been shown to enhance self-regulated learning (SRL), with more than three-quarters of studies concluding that m- learning not only enhances SRL but also mutually reinforces it—various other learning factors (Palalas & Wark, 2020).
Data on the practicality of the development of mobile learning devices for digital engineering was obtained using an instrument in the form of a questionnaire. The criteria tested in the practicality test of the development of mobile learning devices for digital techniques include ease of access, presentation of learning materials, and learning evaluation. The average result of the practicality test was a percentage of 82.8%, which is included in the efficient criteria. Based on this percentage, it can be concluded that developing a digital engineering mobile learning device is included in the efficient criteria.
Based on research that Another researcher mentioned that to measure how many students responded to the survey using the Edmodo application, it was only done in two weeks mid-semester. In addition, another researcher mentioned in the learning steps using Edmodo that
he did where the uploaded lecture files were in PDFs, syllabus in Word form, and Edmodo usage guides in YouTube links. Next, several website links are given, and short answer questions are presented at the end of the learning quiz.
Some of the advantages of digital engineering and mobile learning include:
(1) it can be used for mobile learning of digital engineering courses during the lecture time of 1 semester, which contains the syllabus, program map, semester learning plan, lecture material, there is a quiz at the end of each learning session, and there is an assignment at the end of each basic competence;
(2) digital engineering mobile learning by utilizing the Edmodo application is easily accessible on smartphones with available connections to the internet, thus enabling students.
(3) the presentation of this digital engineering mobile learning material uses varied learning objects in the form of text, images, animations, audio, video, and interactive links packaged in a file pptx, .swf, .avi, .mp4, .pdf, and also available offline on the Youtube Channel;
(4) mobile learning evaluation in this Edmodo application is available with various questions (type quiz) to adjust to the essential competencies, question indicators, aspects assessed, number of items, and processing time.
CONCLUSION
Based on the research and discussion results, it can be concluded that the mobile learning device developed using the Edmodo application is integrated with learning objects and adapted to the subject matter of learning. Media and material experts declared the validity test of the developed mobile learning device very feasible. The developed digital engineering mobile learning device effectively improves the learning outcomes of Electrical Engineering Education students in digital engineering courses. The digital engineering mobile learning device developed has a practical value with a convenient category due to its ease of access, presentation of learning materials, flexibility, and learning evaluation. Nevertheless, the development of educational technology, such as mobile learning, still faces challenges that have not been fully resolved. This is in line with the view that development resilience in research is often less consistently theorized, with methods that are not fully integrated, so further efforts are needed to produce more generalizable evidence (Barrett et al., 2021)
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