Students’ Perception Towards Do It Yourself (DIY) Workshop in Learning Internet of Things (IoT): A Case Study of CS110 Students in UiTM Sarawak Branch First Author\[1\]\*, Second Author2 (Double Blind Review: Please do not type or edit anything here until final-camera ready submissions) *1First affiliation, City and Country (Please do not type or edit anything here, until final camera-ready paper submission)* *2Second affiliation, City and Country (Please do not type or edit anything here, until final camera-ready paper submission)*
ARTICLE INFO ABSTRACT

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Published 1 March 2024

 The Internet of Things (IoT) has revolutionized the digital era by connecting everyday object to the Internet. The increasing adoption of the IoT in various sectors has led to the exploration of innovative teaching methods and tools in education. As a result, the Digital Electronics course offered in the Diploma in Computer Science (CS110) at UiTM now includes a new topic, Basic IoT. Before the topic was introduced, the students rarely worked directly with hardware components and knew little about IoT. This was prior to conventional teaching methods faling to provide students with comprehensive hands-on experience. Therefore, five (5) DIY workshop sessions were conducted to expose the students to IoT. This research aimed to determine the level of students' perceptions towards the DIY IoT workshop, evaluate the difficulty level for all modules throughout the DIY IoT workshop, and assess the effectiveness of DIY workshops in learning IoT. During the workshop, students were introduced to the fundamentals of the IoT, the ESP32 microcontroller and the installation of Arduino IDE software, the method of lighting LEDs using ESP32, the method of connecting ESP32 to a Wi-Fi network, and the method of reading data from sensors and sending data to Google Sheets. Online questionnaires were disseminated at the end of the workshop, and a short interview was conducted to gain the students’ perceptions of the DIY IoT workshop. Data analysis was conducted in three primary phases; descriptive statistics, mean scores, and t-tests using the Statistical Package for the Social Sciences (SPSS). The result of this study shows that students had positive perceptions towards the DIY workshop in learning IoT. It also offers invaluable insights into the role of experiential learning in IoT education and provides actionable recommendations for optimizing the workshop.

Keywords:

IoT

DIY Workshop

Computer Science

Digital Electronic

Arduino

Experiential Learing

DOI:

10.24191/jcrinn.v9i1
# 1.0 introduction The Internet of Things (IoT) has emerged as a transformative technology in today's digital age. It has the potential to revolutionize the way humans live and work by connecting everyday objects to the Internet and enabling these objects to communicate and exchange data. IoT is progressively becoming an important aspect of human life IoT devices, which can vary from home items to industrial equipment, are mini-computer processors that employ machine learning to act on sensor data. Everything from healthcare and transportation to agriculture and manufacturing stands to benefit significantly from the IoT. Mouha (2021) described sensors, connectivity, data processing, and the user interface as the four components that make up a full IoT system. As such, students especially Computer Scinece students need to acquire a solid understanding of IoT concepts and technologies. The Digital Electronics course offered in CS110 recently added Basic IoT as a new topic. Before Basic IoT was introduced, CS110 students had generally dealt with software tools but rarely worked with hardware components and were unfamiliar with the IoT. In addition, the traditional instructional approaches may not fully equip Computer Science students with practical, experiential learning opportunities. Traditional methods of teaching IoT often involve theoretical lectures, laboratory exercises, and simulations. Although these methods are essential for teaching theoretical knowledge, they may be insufficient in equipping students with practical experiences that closely resemble real-world IoT implementation. To comprehend the concept of IoT, students must recognize the hardware components that will be used in IoT systems, including the function of each component. Incorporating IoT into the curriculum may result in a significant pedagogical shift that connects software-centric learning with hands-on hardware experiences. The Do-It-Yourself (DIY) IoT workshop offers students the opportunity to actively engage in building IoT devices, experimenting with sensors and actuators, and developing their own IoT solutions. The study by Kuznetsov and Paulos (2010) mentioned that DIY projects can enhance students' creativity, problem-solving, and critical thinking skills while promoting sustainable development. The primary goal of this workshop was to teach students how to build a basic IoT system by introducing them to the necessary hardware components. Through these hands-on activities, students were expected to gain a deeper understanding of IoT hardware through exploration of its capabilities, and witnessing firsthand how these components contribute to the broader IoT landscape. ![A hand holding a piece of paper with wires Description automatically generated](65c30b9847dca_media/media/image1.jpg) ![A person sitting at a desk with a computer Description automatically generated](65c30b9847dca_media/media/image2.jpeg) Fig. 1. Demonstration of an IoT project during the DIY IoT workshop using a soil moisture sensor, an ESP32, and an Adafruit IO Dashboard. This research paper, we aimed to explore the level of students' perceptions of DIY workshops in learning IoT, focusing on students' experiences in higher learning institutions (HLIs). To address the challenges of this transformation, this study aimed to evaluate the difficulty level of all modules throughout the DIY IoT workshop. The difficulty of these modules would reveal students' learning curves in learning IoT through hands-on activities. Another central objective of this research was to assess the effectiveness of the DIY workshop in facilitating IoT education, especially in tailoring instructional methods to meet students’ needs and expectations. A total of three objectives were formulated to achieve the aims of this paper: i) to evaluate the level of difficulty for all modules throughout the DIY IoT workshop, ii) to assess the effectiveness of the DIY workshop in learning IoT, and iii) to determine the level of students’ perceptions towards the DIY IoT workshop. # 2.0 Literature Review ## 2.1 Internet of Things (IoT) The Internet of Things, or IoT, refers to a network of physical objects that are embedded with sensors, software, and other technologies, allowing them to communicate with other devices and systems over the Internet or other communication networks (Gillis, 2021). Mouha (2021) adds that IoT involves the connection of sensors and actuators embedded in physical objects through wired and wireless networks, often using the same Internet Protocol (IP) that connects the Internet. In recent years, IoT has garnered considerable attention due to its capacity to profoundly transform multiple industries. According to Alam et al. (2020), IoT is a revolutionary approach that has transformed various aspects of our daily lives, including smart cities, smart homes, pollution control, energy saving, smart transportation, and smart industries. In addition a systematic literature review by Granell et al. (2019) identified the advantages of integrating IoT technologies across various sectors and industries. The research shows that the Internet of Things (IoT) can improve efficiency, sustainability, and production. Kumar et al. (2019) viewed IoT as an emerging paradigm that allows smart devices to communicate with the internet, thereby offering inventive resolutions to a multitude of challenges and concerns. As the IoT continues to evolve, experts and developers are working together to make the technology bigger and better, fixing many problems with the systems that are already in place. ## 2.2 IoT in Education Alzahrani and Alshahrani (2020) highlight the benefits and challenges of integrating IoT into education. They found that IoT can enhance students' critical thinking, problem-solving, and collaboration skills. In a literature review by Chen and Wu (2019), the authors emphasized the importance of user-centered design in developing accessible, usable, and effective IoT applications for educational purposes. Bajracharya et al. (2021) explained that there are two (2) categories where IoT is incorporated into educational activities, either by adopting IoT to help with teaching and learning, or by including IoT courses into the existing curriculum. IoT was also introduced into the curriculum of computer science in high school (Abichandani et al., 2022) and the first year of college (Izumi et al., 2022), where the students were reported to be able to grasp the concept of IoT and sensors. Accordingly, the incorporation of IoT into the curriculum of computer science studies is not new. Ahmed et al. (2022) reported the inclusion of the IoT module into the computer science curriculum, and the students expressed increased interest in exploring IoT in the future. ## 2.3 IoT DIY Workshop Kuznetsov and Paulos (2010) discussed the potential roles of user-centered technology, specifically DIY projects, in empowering learners while promoting sustainable development. The study found that DIY projects can enhance students' creativity, problem-solving, and critical thinking skills while promoting sustainable development. Many approaches have been employed to teach IoT concepts to students. Ronoh et al. (2021) presented a survey of IoT learning methods, including problem-based learning, flipped laboratories, flipped classrooms, cooperative learning, and collaborative learning. The same authors found that Arduino and Raspberry Pi are the most common hardware platforms used for teaching IoT. Budihartono et al. (2022) conducted a series of workshops consisting of presentations, demonstrations, and training to improve the students’ learning of IoT technologies. Results from a questionnaire conducted after the workshop showed almost all students were able to understand the IoT topics discussed during the workshop. A study by Wang and Wang (2019) discussed the use of widely available educational IoT kits for beginners or non-major students. The study found that IoT kits can enhance students' understanding of IoT concepts and provide hands-on experiences. The authors emphasized the need for innovative teaching methods to integrate IoT into the curriculum effectively. A study by Bajracharya et al. (2021) also discussed the benefits and challenges of choosing an education kit for learning IoT, then concluded that there are many opportunities for using educational kits for teaching and learning IoT. The use of educational kits will speed up the process of learning IoT concepts. # 3.0 Methodology This study employed a quantitative survey to assessstudents' perceptions towards DIY workshops in learning IoT. The target respondents were Computer Science diploma students enrolled in the ITT270 Digital Electronics course at UiTM Sarawak branch, Samarahan Campus 2 who registered for during the semester of March–August 2023. A structured questionnaire was utilized as the primary data collection instrument. This questionnaire was developed based on a review of existing literature. It comprised closed-ended questions featuring a 5-Likert scale response formatthat enable students to provide feedback regarding their perceptions of the conducted DIY workshop. Additionally, in-depth information about the workshop was gathered through interviews with the students. At the final session of the DIY workshop, students were provided with a link to complete an online questionnaire. A total of 19 out of 21 students enrolled in ITT270 courses responded to the survey, resulting in a response rate of 90.47 per cent. In this study, Statistical Package for the Social Sciences (SPSS) was employed for comprehensive data analysis. The analysis was conducted in three primary phases. In the first phase, descriptive statistics were performed to offer a comprehensive summary of the demographic profile. In the second phase, mean scores were calculated to determine the level of difficulty and students’ perception towards the DIY IoT workshop. In the last phase, t-tests were employed to assess the effectiveness of the DIY workshop in learning IoT. # 4.0 Result and Discussion ## 4.1 Demographic Profile Table 1 lists the demographic profile of respondents according to their genders, semesters of studies, ages, and races. Most of the respondents (68.4%) were male students and the other (31.6%) were female students. About 94.7 per centof the respondents were from semester four and with only a respondent from semester three of studies. The study involved the highest number of respondents from Malay students (31.6 %), followed by Iban students (26.3 %). The lowest participation was observed among Bajau, Banjar, and Melanau students, with each race accounting for 5.3 per cent of the total respondents. Table 1: Demographics of Respondents | | | | | | --------------------- | --------------- | ------------- | ------------------ | | **Demographic** | **Label** | **Frequency** | **Percentage (%)** | | **Gender** | Male | 13 | 68.4 | | ** ** | Female | 6 | 31.6 | | **Semester of study** | 3 | 1 | 5.3 | | ** ** | 4 | 18 | 94.7 | | **Age** | 19 | 1 | 5.3 | | ** ** | 20 | 18 | 94.7 | | **Race** | Bajau | 1 | 5.3 | | ** ** | Banjar | 1 | 5.3 | | ** ** | Bidayuh | 3 | 15.8 | | ** ** | Iban | 5 | 26.3 | | ** ** | Kadazan - Dusun | 2 | 10.5 | | ** ** | Malay | 6 | 31.6 | | ** ** | Melanau | 1 | 5.3 | ** ** ## 4.2 Levels of difficulty for all modules throughout the DIY IoT workshop All respondents were required to answer questions about the difficulty level of the modules that were used throughout the workshop so that the level could be determined. Each item of the questions was constructed on 5 point Likert-scale. Scale 1 was referred to as very difficult while scale 5 was for very easy. To determine the levels of difficulty, the difficulty level scores were averaged and categorized into five levels of difficulty, i) very high, ii) high, iii) moderate, iv) low, and v) very low (Moidunny, 2009) as shown in Table 2. Table 2: Level of Difficulties | | | | -------------- | ----------------------------- | | **Mean Score** | **Mean interpretation table** | | 1.00 – 1.80 | Very High | | 1.81 – 2.60 | High | | 2.61 – 3.20 | Moderate | | 3.21 – 4.20 | Low | | 4.21 – 5.00 | Very Low | Source: Moidunny (2009) The mean score in Table 3 concluded that the difficulty level of all modules in the DIY IoT except Module 5 was easy for students to understand and follow since the mean scores were between 3.21 to 4.20. Module 5 was categorized as moderately difficult since the mean score was 3.1930, which was deemed neither easy nor difficult to understand by the students. Table 3: Mean Score for Level of Difficulties

Variables

Mean Score

Level of Difficulty

Module 1(a): Installation and Setup of Arduino IDE for ESP32

4.0000

Low

Module 1(b): Programming ESP32 to print to serial monitor and blink an LED

3.8070

Low

Module 2: Reading data from sensors

3.5965

Low

Module 3: Connecting ESP32 to Wi-Fi network

3.7400

Low

Module 4: Sending data from sensor to cloud

3.5614

Low

Module 5: Developing a DIY-based IoT system

3.1930

Medium
## 4.3 Assessing the Effectiveness of the DIY Workshop in Learning IoT Table 4 tabulates the mean and analysis of the paired t-test for students’ knowledge level before and after they attended the DIY IoT workshop. The result revealed a difference in the mean of students’ knowledge level as a result of the DIY IoT workshop. Therefore, a further analysis conducted to assess whether there was a significant improvement in students’ knowledge level before and after they attended the DIY IoT workshop. The results analysis of the paired t-test were tabulated in Table 4. The study concluded a significant improvement in the knowledge levels of students from the DIY IoT workshop (p-value \< 0.05). This indicates that students have an improvement in their knowledge level after attending the DIY IoT workshop. Thus, the study concludes that the DIY workshop is effective in learning IoT. Table 4. Paired T–test Analysis
  N Mean Mean

t-test

(p-value)

 Conclusion
    (Before) (After)
Knowledge 19 1.74 3.95

-9.340

(0.000)

 Significant Effective
## 4.4 Reliability Analysis The accuracy or reliability of data used in this study was analyzed by conducting a Reliability Test. The data is concluded as reliable if the value of Cronbach’s Alpha is more than 0.7 (Pallant, 2011). The Cronbach’s Alpha value for all variables is displayed in Table 5. The analysis shows that all the variables in this study were reliable as their Cronbach’s Alpha values were more than 0.7. Table 5: Reliability Analysis | | | | | -------------- | ------------------- | -------------------- | | **Variable  ** | **Number of Items** | **Cronbach’s Alpha** | | Challenge | 7 | 0.917 | | Interest | 7 | 0.913 | | Readiness | 8 | 0.818 | ## 4.5 Students’ Perception Towards DIY IoT Workshop The students’ perception towards the DIY IoT workshop was measured using three variables challenge, interest, and readiness. To measure perception, respondents were required to respond to questions on these three variables. Similar to the level of difficulty of the modules, the questions on students perceptions were constructed using a 5 point Likert-scale. Scale 1 was referred to as very difficult, while scale 5 was for very easy. To determine the levels of difficulty, the difficulty level scores were averaged and categorised into five levels of difficulty: i) very high, ii) high, iii) moderate, iv) low, and v) very low (Moidunny, 2009), as shown in Table 6. Table 6: Level of Perceptions | | | | -------------- | ----------------------------- | | **Mean Score** | **Mean interpretation table** | | 1.00 – 1.80 | Very Low | | 1.81 – 2.60 | Low | | 2.61 – 3.20 | Moderate | | 3.21 – 4.20 | High | | 4.21 – 5.00 | Very High | Source: Moidunny (2009) Table 7 displays the mean score for all the variables used to measure the perception of students towards the DIY IoT workshop. The variable challenge had a mean score of 3.2331. It indicates that the students moderately agreed that the condition caused some challenges for them while attending the DIY IoT workshop. In terms of interest and readiness, students highly agreed with their preferences and preparations when attending the DIY IoT workshop. The findings revealed that they were interested in joining the workshop and were well-prepared before attending the workshop. Table 7: Mean Score for Perception Level
Variable  

Mean Score

Level of Perception
Challenge 3.2331 Medium
Interest 3.7820 High
Readiness 3.9605 High
# 5.0 Conclusion The DIY IoT workshop was conducted to address the limited knowledge of IoT among Computer Science students, specifically those who were taking the Digital Electronics course offered in the Diploma in Computer Science (CS110) at UiTM. The workshop aimed to expose students to the components of IoT systems and develop a simple IoT system. The integration of the DIY workshop in learning IoT has shown promising results. This hands-on learning experience provided students with valuable insights into the fundamentals of IoT, allowing them to work directly with hardware components and gain practical skills. The effectiveness of the DIY workshops in learning IoT was further supported by the students' positive perceptions. Besides, by incorporating the DIY IoT workshops into the curriculum, the workshop equipped them with the skills and knowledge necessary to excel in the rapidly evolving digital landscape, resulting in them being better prepared for the IoT-driven future. Overall, the DIY IoT workshop was a valuable initiative in bridging the gap between theoretical knowledge and practical application, enabling students to gain hands-on experience and a better understanding of IoT concepts and components. Therefore, in keeping with the present technical advancements in the Fourth Industrial Revolution (IR4.0), IoT workshops should be continued in the future to highlight the talent and creativity of students in the development of products based on the IoT concept. # Acknowledgements/Funding The authors would like to acknowledge the support of Universiti Teknologi MARA (UiTM) Cawangan Sarawak, Kampus Samarahan 2 for providing financial support through Tabung Amanah Pembangunan Akademik (TAPA) for the DIY IoT workshop. # Conflict of Interest The authors declared that they have no conflicts of interest to disclose. # References Abichandani, P., Lobo, D., & Shekhar, P. (2022). 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