Integrating Technology Roadmaps into the Construction of Learning Indicators

Abstract

In the era of rapid technological advancement and the ascent of the United Nations’ Sustainable Development Goals (SDGs), addressing the persistent gap between education and employment is crucial to ensure “decent work for all” and enhance human well-being. This study initiates its inquiry from the construction of learning indicators, aiming to facilitate the early exposure of learners to relevant industrial technologies and the acquisition of future-oriented competencies. Firstly, through a review of the literature and an analysis of the current situation, the concept of technology mapping in the industrial sector is employed for technology forecasting. This involves the development of a technology roadmap and the identification of key technologies. Subsequently, the Delphi method is utilized to invite expert scholars to assess the suitability and importance of learning indicators. Data processing is carried out using descriptive statistics, qualitative recommendations, and the Kolmogorov–Smirnov single-sample analysis. Using a smart home system practice curriculum as an example, this study’s final development includes 9 main constructs and 56 sub-constructs, serving as the foundation for curriculum and instructional material development. Upon receiving relevant instruction, students can swiftly integrate into related industries.

1. Introduction

One of the current dilemmas facing the world is the gap between learning and application. Students acquire knowledge in educational settings that may not directly apply to industrial technology, requiring them to simultaneously learn new technologies or relevant knowledge while seeking employment [1]. This situation causes difficulties for industries and adds pressure on the individuals involved. Therefore, the inclusion of the “Decent Work and Economic Growth” target in SDG Goal 8 [2] is a subject worthy of scholarly investigation.

The gap between learning and application may stem from various factors such as human factors, textbook issues, or institutional problems [3,4]. In the era of rapid technological advancement, access to information is diverse and convenient. The inclusion of the “Quality Education” target in SDG Goal 4 [2], means that high-quality education can foster sustainable development by continually updating knowledge and skills, understanding the conveniences brought about by emerging technologies, and effectively leveraging them (SDG 4.3 and 4.7). Additionally, the teaching content may also be a contributing factor. In a rapidly changing environment, the lifecycle of technology is not necessarily prolonged, leading to outdated teaching materials that fail to keep pace with technological advancements, leaving students learning outdated skills. Moreover, educational systems driven by national policies may influence students’ learning outcomes. A well-designed system enables students to quickly integrate into the industry, while suboptimal strategies may give rise to further complications.

The disconnect between learning and application may lead to a range of issues affecting individuals, organizations, or society as a whole. From an individual perspective, the gap between the acquisition of skills and their practical application results in unresolved problems, leading to decreased work efficiency and quality, and potentially causing accidents or disasters. From a resource standpoint, while the goal is to maximize efficiency under economic considerations, the investment in time and cost often significantly exceeds the expected benefits, resulting in resource wastage. At the operational level, encountering frequent obstacles and stagnation leads to the failure to achieve anticipated outcomes or implementation. This not only fosters disappointment and frustration, affecting the willingness to learn, but also impedes innovation, resulting in missed opportunities.

A technology roadmap is the result of industry efforts to implement technology forecasting for specific technologies, predicting future trends in a particular field. There are various ways to represent this, all with the common objective of constructing a path from the present to the future for products or technologies [5,6,7]. Therefore, it is necessary to conduct research on relevant fields and consider factors that may influence them. Consensus on and the establishment of future prospects in the field are achieved through expert consultations, focus groups, expert meetings, and similar methods, serving as a reference for scholars or companies.

Textbooks serve as auxiliary tools for curriculum instruction, enabling educators to guide learners from basic to advanced levels and supplementing timely and relevant content knowledge. By utilizing well-designed textbooks, learners can use current technologies while mastering skills in the learning domain, and even gain insights into possible future trends. For learners, the complementary use of textbooks not only deepens their understanding but also reflects the editor’s ingenuity, establishing a systematic knowledge structure with logical coherence. This fosters a learning attitude that involves self-reflection, the rapid acquisition of new knowledge, and self-reorganization, leading to continuous self-improvement and simultaneously aligning with the SDGs’ objective of sustainable development.

Based on the announcement of the Ministry of Education’s Department of K-12 Education Administration [8], “smart home system practices” are one of the required subjects in the field of electrical engineering within curriculum outlines for technical high schools. Therefore, this study selected this subject for an in-depth exploration to identify important learning indicators, serving as the basis for future textbook and instructional development.

Prior to the development of instructional materials, the construction of learning indicators should be completed. This study conducted an expert survey using the Delphi method [9], ultimately obtaining 9 main constructs and 56 sub-constructs. Initially, a technology roadmap was drawn for the field, and reference was made to the domestic curriculum outline. An initial survey questionnaire was developed based on this process, utilizing the Likert five-point scale to collect expert opinions on the importance of items. Additionally, qualitative recommendations provided by expert scholars were gathered for adjustment purposes. Furthermore, a Kolmogorov–Smirnov single-sample analysis was employed to verify whether there was consensus among the expert scholars regarding the content of the sub-constructs.

Different from traditional models of learning indicator construction, this study incorporates the concept of a technology roadmap, enhancing the comprehensiveness of learning indicators. By directly aligning educational materials with the knowledge and skills required by the industry, it mitigates the occurrence of a gap between learning and application. Moreover, it facilitates the acquisition of emerging technologies, enabling rapid adaptation when engaging with related industries in the future. This approach proves advantageous for both industry and academia.

The present study begins with an overview of the research topic, background, methodology, and findings, as outlined in this section. The following succinctly describes the key points and themes of each section: Section 2 presents a literature review and analysis on the topics of the gap between learning and application, smart homes, technology roadmaps, and the development of key indicators. Section 3 outlines the research methodology, including the expert panel, research process, and the creation of the technology roadmap. Section 4 performs data analysis, utilizing descriptive statistics, K-S tests, and qualitative suggestions to explore and analyze the data. Section 5 presents the results and discussions, providing an explanation and exploration of the research data. Section 6 concludes with discussions on the findings and directions for future work.

2. Literature Review

This section aims to explore issues pertaining to the education–job mismatch, smart homes, technology roadmaps, and methodologies for constructing indicators. Through the research of experts and scholars, beneficial content for this study will be identified, leading to a more enriched outcome.

2.1. Education–Job Mismatch

When the content learned cannot be applied in practical industries, resulting in a disparity between supply and demand, it is termed the education–job mismatch. According to the literature analysis, the exploration of this issue initially began in European countries and has since expanded to other regions, making it a global concern. Neglecting the severity of this issue may lead to further educational challenges and an inability to meet industry demands, thereby causing a disruption in the supply–demand balance.

The global unemployment rate among graduates is showing an increasing trend, with Malaysia also facing related issues [10]. Researchers investigated 402 graduates who had not secured suitable employment and found that besides issues such as attitudes, communication, and salary expectations not meeting the needs of both parties, skills were also a key influencing factor. Due to job seekers not possessing the necessary skills required in their respective fields, they are facing unemployment crises. Therefore, the failure to adequately prepare for future industries they are about to enter will inevitably lead to the continued expansion and exacerbation of this situation, resulting in a mismatch between supply and demand.

The number of graduates has been increasing annually, yet the employment rate remains low or even stagnant, a situation observed in China [11]. One of the key factors contributing to this phenomenon is the mismatch between the disciplinary knowledge and core competencies of graduates and the demands of industries. With the advancement of technology and the widespread application of emerging technologies, it is imperative for the economy to achieve sustainable growth and for education to continuously improve. Therefore, closer communication between academia and industry is necessary to facilitate the matching of talent supply and demand. The authors also propose collaborative approaches wherein industry demands are taken into account in educational planning and curriculum design, thereby promoting the greater integration of information and technology and addressing the warning signs of rising unemployment rates.

To assess the state of supply and demand in the labor market of European countries, researchers have utilized the issue of the supply–demand imbalance as a developmental model for further exploration and analysis [12]. Within policy formulation, it is essential to establish connections between scenarios of sustainable development and the education system. This entails deeper coordination and collaboration in aspects such as curriculum design and skills training to facilitate the generation of clear objectives, enabling learning to align more closely with current industries. This reduces the perpetuation of this situation, leading to a balance between supply and demand.

To investigate the alignment between the competencies of graduates and employer demands, this study conducted an integrated analysis following the PRISMA protocol for literature reviews and analyses. A total of 69 relevant studies from 2009 to 2019 were collected [13]. The research findings indicate that this issue has been addressed and discussed in most countries. However, there still exists a gap between the competencies cultivated through education and industry demands, leading to a failure in achieving alignment between learning and application. Consequently, there is a need to establish effective communication channels between academia and industry and jointly devise strategies to address this issue.

Hence, this issue has garnered global attention, necessitating concerted efforts to devise relevant strategies to address the situation. By alleviating industry concerns, such measures assist individuals in adapting promptly to the rapid changes in this era.

2.2. From Smart City to Smart Home

In the pursuit of a more convenient lifestyle, integrating technology into daily life to achieve objectives has become increasingly prevalent. With relevant technologies gradually maturing, the smart home has emerged as a trend with widely applied examples. A smart home is a system that can be installed at various locations within a residence, incorporating multiple sensors deployed around household appliances. Moreover, through internet transmission, data are collected and processed, enabling information feedback or command execution, thus enhancing the convenience of human life.

The inclusion of the “Affordable and Clean Energy” target in SDG Goal 7 [2] describes how the family, as the foundational unit of society, can benefit from the implementation of smart home systems, which can be applied to tasks such as lighting monitoring, appliance monitoring, environmental safety monitoring, audio–visual control, among others [14,15]. Through sensors and internet communication, users can quickly access information about the current environment and device status, thereby enhancing the convenience of daily life. Furthermore, through data analysis and statistics, more efficient power management can be achieved, resulting in energy saving benefits.

Safety monitoring is a crucial component of smart homes, where sensors are strategically placed around potential hazard areas such as gas, fire, water, high temperatures, and humidity to ensure that the environment remains within safe parameters and to prevent disasters [16,17]. Additionally, the application of image surveillance and identity recognition systems can facilitate the preliminary identification of individuals, reducing the threat posed by suspicious individuals or unknown dangers [18,19].

With the advent of an aging population, it becomes imperative to monitor the health status of elderly friends and relatives regularly. The application of sensors for health monitoring is a future trend. Simultaneously aligning with the inclusion of the “Good Health and Well-Being” target in SDG Goal 3 [2], data obtained from such monitoring can be transmitted to healthcare facilities to monitor their physical and mental health status. In case of necessity, immediate contact or rescue can be provided, thereby reducing manpower expenditure and ensuring the precise control of recent or current information [20,21], thereby achieving health risk management (SDG 3.4 and 3.d).

To optimize efficiency, the assistance of intelligent devices is necessary to achieve this goal. In this regard, data analysis of electrical appliances is crucial for grasping relevant information at different time periods, aggregating and analyzing it to obtain corresponding parameter adjustments that are more suitable, thus promoting energy conservation, environmental protection, and alignment with current sustainable development goals [22,23]. By gaining a deeper understanding of current industry technologies, more individuals can access modern energy services and understand the correct concepts, thereby accelerating the goal of improving energy efficiency (SDG 7.1 and 7.3).

2.3. Technology Roadmap

The rapid advancement of technology is characterized by ever-changing developments, leading to a gradual shortening of the active cycle of any given technology. This phenomenon is accompanied by the emergence of newer technologies that are not only more convenient but also faster. Therefore, it is imperative to understand key technologies and incorporate them into potential future domains and developmental directions to avoid missing opportunities and to become forward-thinking competitors. According to the literature, Motorola [24] was among the pioneers in mapping out relevant technologies, effectively integrating various domains. Furthermore, this company also crafted technology roadmaps for its products, predicting future market trends and positioning itself at the forefront of technological development and human needs. In the process of map-making, it is essential to consider trends across three time periods: past, present, and future, facilitating deductive reasoning.

To maintain competitiveness, ABC Inc. (Portland, Oregon) [25] has developed a technology roadmap and formulated strategic plans to address the challenges of the era and the market. In addition to devising short-term and long-term plans, this company has also identified gaps in products, technologies, and resources to facilitate its development. Industry experts have conducted QFD (Quality Function Deployment) strategic analyses considering market, societal, and economic factors to delineate the company’s development trajectory for the next 20 years, thereby establishing goals for each phase.

The ESTO (European Science and Technology Observatory) [26] has conducted research and developed technology roadmaps exploring the application of smart technologies across various domains of everyday life. This investigation involves analyzing themes from technological, societal, and policy perspectives. Within this study, key technologies have been identified, demonstrating both future-oriented and forward-thinking characteristics. These findings serve as references for future research and can also be used to verify and assess whether the development of such technologies progresses as anticipated.

The application of technology roadmaps within specific domains serves to propel the development trajectory of those domains. Furthermore, it facilitates policy planning and forecasts future technological advancements, thereby preventing researchers from blindly pursuing avenues of inquiry. Consequently, the selection of a particular key technology and the periodic exploration and mapping of its trajectory become essential. This process establishes development directions and validates current technological trends. Regular updates are performed to ensure one stays at the forefront of the evolving landscape.

2.4. Developing Key Indicators by Using Delphi Method

To explore the competency indicators required for energy and technology education among students in Taiwanese vocational senior high schools [27], this study employed the Behavioral Event Interview (BEI) and Delphi method to gather opinions from experts and scholars. The consistency of expert opinions was ensured through the K-S test. This study identified 24 knowledge-based indicators, 12 affective-based indicators, and 24 skill-based indicators, which serve as the basis for curriculum development and instructional material design.

Teppanyaki, a renowned and popular cuisine in Taiwan, serves as a significant reference for training curriculums in culinary education [28]. Through the Delphi method, opinions were gathered from lecturers in university hospitality departments, experienced chefs, and restaurant owners. These opinions were categorized into four dimensions: knowledge, affect, skills, and traits. The K-S test was then employed to establish expert consensus. In total, 16 main constructs and 74 sub-constructs were identified, serving as training objectives and certification criteria for relevant institutions.

With the development of the green energy industry, wind turbines are widely installed along the coastlines of Taiwan [29]. The competency indicators for welding technicians serve as the primary basis for training. Initially, this study employed a literature analysis method to collect and explore relevant research findings, subsequently developing competency indicators. An expert panel was then established using the Delphi method, with the K-S test and K-W test employed to achieve expert consensus. This process confirmed 3 main constructs, 10 sub-constructs, and 75 behavioral indicators, facilitating talent recruitment and educational training.

In response to hygiene and food safety concerns, the necessity of disposable products persists, albeit with ongoing exploration into their environmental impact [30]. Specifically, the lids of containers are made from food-grade polypropylene. To address sustainability concerns and reduce manufacturing costs and energy consumption, this study conducted literature reviews and expert interviews to identify key indicators and factors. Subsequently, employing the Delphi method, qualitative and quantitative surveys were conducted with experts and scholars. The K-S test was then used to ensure expert consensus, resulting in the identification of ten key factors aimed at enhancing competitiveness and achieving sustainability goals.

Through the Delphi method, experts and scholars were invited to participate in surveys and interviews, yielding reliable results regarding the critical factors in the field. Complemented by K-S test technology, this approach further confirms the consensus among experts’ opinions. This method proves effective for investigating key indicators and technologies, providing a robust research methodology.

3. Research Methods

Upon establishing the research topic as “smart home system practices”, we referenced current curriculum outlines and learning objectives as the foundation. We conducted a literature review and discussion, and crafted a technological map development blueprint in this domain. Furthermore, upon reviewing the 17 SDGs, relevant aspects of this study were integrated into the indicator construction and analysis. Concurrently, an expert investigation team utilizing the Delphi method was established. A questionnaire was drafted for surveying, and upon data collection, compilation and editing ensued. Subsequent adjustments were made progressively, followed by analysis using research methods such as descriptive statistics and a Kolmogorov–Smirnov single-sample analysis to achieve consensus among expert scholars.

3.1. Technology Roadmap for Technological Forecasting

This study presents a simplified roadmap for the development of smart homes, as shown in Figure 1. The timeline is divided into three periods: past, present, and future, exploring trends and characteristics of each period. Future development directions are collected and analyzed through a literature review, presenting attributes and development goals corresponding to each period.

3.2. The Delphi Method

In this study, the Delphi method references the model process proposed by Murry and Hammons in 1995 as the foundation [31]. By adhering to the current framework of learning objectives and integrating a literature review and expert consultation at the front end, a technology roadmap was developed. Subsequently, questionnaire design and surveys were conducted, followed by iterative data collection and reference. Ultimately, consensus among experts was achieved, as shown in Figure 2.

3.3. Experts and Scholars

This study employed the Delphi technique for expert surveys, forming an expert survey panel consisting of 13 members. Among them, there were four scholars from universities specializing in electrical engineering and engineering technology education, all engaged in research and teaching in related fields. Additionally, there were four technical managers from relevant industries, responsible for operational management in areas such as information technology, hydroelectric technology, and smart home applications. Furthermore, there were five electrical engineering teachers from technical high schools, all serving as frontline curriculum implementers while being actively involved in teaching. These members were selected to ensure objectivity across various domains and to maximize the feasibility of indicator construction, execution, and representativeness.

3.4. Data Processing

A Likert scale was utilized to assess the importance of each item, where “Very Important” was rated as 5 points, “Important” as 4 points, “Neutral” as 3 points, “Unimportant” as 2 points, and “Very Unimportant” as 1 point, to gather opinions from expert scholars. Descriptive statistics were employed for data compilation, including mode, mean, and standard deviation, to determine the importance of each item. Furthermore, this facilitated the assessment of the concentration and dispersion of opinions among members of the expert panel.

To obtain individual recommendations from members of the expert panel and obtain the most direct feedback, open-ended fields were set up for expert scholars to fill in. Careful recording and analysis were conducted, and when necessary, the implications were confirmed via email or letter to ensure the quality and specificity of the responses.

To analyze whether there is consensus among expert scholars regarding each item, a Kolmogorov–Smirnov single-sample analysis was used to assess the adequacy, examining whether consensus was reached among experts in various fields.

4. Data Analysis

For the smart home system practices, after three rounds of Delphi expert questionnaire surveys and subsequent iterative analysis, adjustments were made to the items based on feedback from the open-ended fields. Consequently, the “9 main construct dimensions” and “56 sub-construct dimensions” were finalized to align with the recommendations of the expert scholars.

4.1. Analysis of Main Construct Dimensions

In the main construct dimensions, there was little variation in the opinions of the expert scholars, and the mode, mean, and standard deviation showed a trend of convergence with each round, indicating increasing consensus, as shown in

Table 1. Analysis of main construct dimensions.

Main Construct Dimensions	Mode	Mean	Standard Deviation
A. Smart Home System Introduction	5	4.77	0.439
B. Control Systems and Simulation Instruments	5	4.77	0.439
C. Programming	5	4.85	0.376
D. Application Unit of Output Components	5	4.77	0.439
E. Application Unit of Input Components	5	4.85	0.376
F. Security Monitoring System	5	4.92	0.277
G. Home Care System	5	4.77	0.439
H. Smart Home Appliance System	5	4.92	0.277
I. Remote Monitoring and Cloud Systems	5	4.92	0.277
Mean		4.84	0.371

. The mean value of the main construct dimensions reached a high of 4.84, with the standard deviation converging to 0.371.

4.2. Analysis of Sub-Construct Dimensions and Consistency Testing of Expert Opinions

In the sub-construct dimensions, the opinions provided by the expert scholars were consistently aligned, with a converging trend observed across each round. The mode for each item was either 4 or 5, indicating high agreement. Regarding the mean values, the overall average was 4.70, and for the standard deviations, each item was below 1, with an overall average of 0.427. Taken together, it can be confirmed that the expert opinions tended towards consensus.

Furthermore, to further validate the consistency of the opinions of the expert scholars, a Kolmogorov–Smirnov single-sample analysis was conducted for adequacy testing, as shown in

Table 2. Analysis of sub-construct dimensions and K-S test.

Main Construct Dimensions	Sub-Construct Dimensions	Mode	Mean	Standard Deviation	K-S Test Z Value
A. Smart Home System Introduction	A-1. Development History of the Smart Home System	4	4.31	0.480	1.555 *
	A-2. Basic Architecture of the Smart Home System	5	4.85	0.376	1.821 **
	A-3. Advantages and Limitations of he Smart Home System	5	4.69	0.480	1.555 *
	A-4. Applications of the Smart Home System in the Industry	5	4.85	0.376	1.821 **
	A-5. Future Trends of the Smart Home System	5	4.69	0.480	1.555 *
	A-6. Challenges of the Smart Home System	4	4.38	0.506	1.412 *
B. Control Systems and Simulation Instruments	B-1. Development History of Controllers	4	4.08	0.277	1.919 **
	B-2. Introduction to Commonly Used Controllers	5	4.69	0.630	1.646 **
	B-3. Advantages and Limitations of Controllers	5	4.62	0.650	1.497 *
	B-4. Software Download and Basic Configuration (including drivers)	5	4.85	0.376	1.821 **
	B-5. Introduction to Controller Interface Environment and Functions	5	4.92	0.277	1.919 **
C. Programming	C-1. Introduction to Common Commands	5	4.85	0.376	1.821 **
	C-2. Introduction to Basic Functions	5	4.85	0.376	1.821 **
	C-3. Construction and Testing of Various Loop Structures	5	4.77	0.439	1.694 **
	C-4. Common Logic Structures and Processes in Programming	5	4.92	0.277	1.919 **
	C-5. Application of Loops and Functions Combination	5	4.92	0.277	1.919 **
D. Application Unit of Output Components	D-1. Basic Driving Modes, Principles, and Types of Output Components	5	4.77	0.439	1.694 **
	D-2. Principles, Characteristics, and Practical Applications of LED	4	4.38	0.506	1.412 *
	D-3. Principles, Characteristics, and Practical Applications of Buzzer	4	4.38	0.506	1.412 *
	D-4. Principles, Characteristics, and Practical Applications of Motors	5	4.77	0.439	1.694 **
	D-5. Introduction to Characteristics and Practical Applications of Seven-Segment Displays and Matrix LEDs	4	4.31	0.480	1.555 *
	D-6. Principles, Characteristics, and Practical Applications of LCD Interfaces	5	4.62	0.506	1.412 *
E. Application Unit of Input Components	E-1. Basic Principles and Types of Input Components	5	4.69	0.480	1.555 *
	E-2. Principles, Characteristics, and Practical Applications of Digital and Analog Signal Conversion	5	4.92	0.277	1.919 **
	E-3. Practical Applications of Common Button Switches	5	4.62	0.506	1.412 *
	E-4. Practical Applications of Multi-position Switches	5	4.62	0.650	1.497 *
	E-5. Practical Applications of Matrix Keyboards	5	4.77	0.439	1.694 **
	E-6. Characteristics, and Practical Applications of Electronic Switches	5	4.85	0.376	1.821 **
F. Security Monitoring System	F-1. Principles and Practical Applications of Gas Sensors	5	4.69	0.480	1.555 *
	F-2. Principles and Practical Applications of Flame Sensors	5	4.69	0.480	1.555 *
	F-3. Principles and Practical Applications of Water Level Sensors	4	4.38	0.506	1.412 *
	F-4. Principles and Practical Applications of Temperature Sensors	5	4.85	0.376	1.821 **
	F-5. Principles and Practical Applications of Humidity Sensors	5	4.85	0.376	1.821 **
	F-6. Principles and Practical Applications of Anti-theft and Access Control Systems	5	4.62	0.650	1.497 *
	F-7. Principles and Practical Applications of Video Surveillance Systems	5	5.00	0
	F-8. Principles and Practical Applications of Identity Recognition Systems	5	4.85	0.376	1.821 **
	F-9. Commonly Used Systems and Devices in the Industry	4	4.38	0.506	1.412 *
	F-10. Principles and Practical Applications of Data Transmission and Information Retrieval Technologies	5	4.92	0.277	1.919 **
G. Home Care System	G-1. Principles and Practical Applications of Medical Reminder Care System	4	4.31	0.480	1.555 *
	G-2. Principles and Practical Applications of Emergency Rescue System	5	4.69	0.480	1.555 *
	G-3. Principles and Practical Applications of Smart Medication Box System	5	4.62	0.506	1.412 *
	G-4. Principles and Practical Applications of Physiological Data Monitoring System	5	4.69	0.630	1.646 **
	G-5. Principles and Practical Applications of Indoor and Outdoor Positioning System	4	4.31	0.480	1.555 *
	G-6. Principles and Practical Applications of Video Surveillance System	5	4.92	0.277	1.919 **
	G-7. Principles and Practical Applications of Data Transmission and Information Retrieval Technologies	5	4.85	0.376	1.821 **
H. Smart Home Appliance System	H-1. Introduction to Home Energy Management System	5	4.77	0.439	1.694 **
	H-2. Planning and Improvement of Energy-saving Control Systems	5	4.77	0.439	1.694 **
	H-3. Principles and Practical Applications of Smart Meter System	5	4.77	0.439	1.694 **
	H-4. Principles and Practical Applications of Networked Appliance System	5	4.62	0.506	1.412 *
	H-5. Principles and Practical Applications of Data Transmission and Information Retrieval Technologies	5	4.92	0.277	1.919 **
I. Remote Monitoring and Cloud Systems	I-1. Concept and Development of Internet of Things (IoT)	5	4.85	0.376	1.821 **
	I-2. Construction of Cloud Platform Systems	5	4.77	0.439	1.694 **
	I-3. Principles and Practical Applications of ZigBee	5	4.69	0.480	1.555 *
	I-4. Principles and Practical Applications of Bluetooth	5	4.77	0.439	1.694 **
	I-5. Principles and Practical Applications of Wi-Fi	5	4.92	0.277	1.919 **
	I-6. Principles and Practical Applications of Mobile Devices Integration	5	4.92	0.277	1.919 **
			4.70	0.427

* p < 0.05, ** p < 0.01.

. It was hypothesized in this study that the expert opinions lacked consistency, and significance levels below 0.05 were denoted by a single asterisk (*), while those below 0.01 were denoted by double asterisks (**). The analysis revealed that 23 items were below 0.05 and 32 items were below 0.01 in terms of significance. Additionally, in the “F-7 Principles and Practical Applications of Video Surveillance Systems” category, the expert panel provided uniform ratings.

4.3. Qualitative Recommendations and Management of Inconsistent Opinions

This study underwent three rounds of expert questionnaire surveys, ultimately achieving expert consensus and developing 9 main constructs and 56 sub-constructs. Qualitative recommendations were received in both the first and second rounds, with suggestions provided for addressing inconsistent opinions, leading to additions or deletions as discussed and explained, as shown in

Table 3. Qualitative recommendations and construct adjustment.

Round Number	Original Number and Content	Qualitative Recommendations	Disposition
Round one	I. Entertainment System	Considering the curriculum’s emphasis on environmental safety, electrical systems and energy, and home care, and due to the limitations of practical curriculum hours, this main construct and its sub-constructs have been removed.	1. Removed 2. Numbering Revised
Round one	A-5. Future Trends of the Smart Home System	“A-5. Current Status of Major Manufacturers’ Development” was added to the indicator to familiarize students with mainstream manufacturers and related application units. Other sub-constructs remain unchanged.	1. Added 2. Numbering Revised
Round one		“D-6. Principles, Characteristics, and Practical Applications of LCD Interfaces” was added to the indicator to enrich the learning content and align it with the required skills of the subject; the output unit should include content related to LCDs. Other sub-constructs remain unchanged.	Added
Round one	E-2. Practical Applications of Common Button Switches	“E-2. Principles, Characteristics, and Practical Applications of Digital and Analog Signal Conversion” was added to the indicator to familiarize individuals with the principles and applications of sensing components; it is necessary to address both digital and analog signals. Other sub-constructs remain unchanged.	1. Added 2. Numbering Revised
Round one	F-4. Principles and Practical Applications of Anti-theft and Access Control Systems	“F-4. Principles and Practical Applications of Temperature Sensors” was added to the indicator. As common sensors, temperature measurement components should be included. Other sub-constructs remain unchanged.	1. Added 2. Numbering Revised
Round one	F-5. Principles and Practical Applications of Video Surveillance Systems	“F-5. Principles and Practical Applications of Humidity Sensors” added to the indicator. As common sensors, humidity measurement components should be included. Other sub-constructs remain unchanged.	1. Added 2. Numbering Revised
Round one	J-3. Principles and Practical Applications of Bluetooth	“I-3. Principles and Practical Applications of ZigBee” was added to the indicator and revised. As communication-related technologies, ZigBee should be included. Other sub-constructs remain unchanged.	1. Added 2. Numbering Revised
Round one		“I-6. Principles and Practical Applications of Mobile Devices Integration” was added to the indicator and revised. Mobile devices need to be able to connect and communicate with the system, which is also a future trend. Other sub-constructs remain unchanged.	1. Added 2. Numbering Revised
Round two	A-5. Current Status of Major Manufacturers’ Development	The content of this indicator can be incorporated into A-4. Therefore, this sub-construct is deleted. Other sub-constructs remain unchanged.	1. Removed 2. Numbering Revised

.

5. Results and Discussion

After three rounds of Delphi surveys, expert opinions have converged and reached consensus, serving as learning indicators for the “smart home system practices” curriculum. Measures such as the mode, mean, standard deviation, and K-S test Z-value are used to elucidate their importance and convergence degree. Additionally, discussions were conducted on the curriculum design, subject selection, and relevant content of the technology roadmap, as described below.

5.1. Importance and Convergence Degree of Main Constructs

From the content of the main constructs, it can be observed that the expert panel’s assessments of importance are quite consistent. In terms of the mode, all are 5; the mean values are all above 4; and the standard deviations are all below 1. Based on the above data, it can be concluded that the expert opinions are generally consistent, and they have relatively high ratings assigned for importance, as shown in Figure 3.

5.2. Importance and Convergence Degree of Sub-Constructs

From the content of the main constructs, it can be observed that the expert panel’s assessments of importance are quite consistent. In terms of the mode, all are 4 or 5; the mean values are all above 4; and the standard deviations are all below 1. Furthermore, in the K-S test Z-value examination, it is observed that all the sub-constructs have reached significance levels, with a total of 23 items having p-values less than 0.05 and 32 items having p-values less than 0.01. Additionally, one item was unanimously recognized by all the experts and given an evaluation of “very important”. Based on the above data, it can be concluded that the expert opinions are generally consistent, and they have assigned relatively high ratings for importance, as shown in Figure 4.

5.3. The Creation of Technology Roadmap

Regarding the concept of a technology roadmap, this study applied a simplified framework, dividing the timeline into past, present, and future, and categorizing the vertical axis based on corresponding trends and characteristics. Through a literature review and consultation with experts, a technology roadmap was developed for this study to facilitate subsequent indicator construction processes.

5.4. Update of Technology Roadmap

Given the rapid pace of technological advancements and the shortened cycle of new technology emergence, it is essential to constantly monitor developments in relevant fields to prevent learning content from becoming outdated. Therefore, the timing of technology roadmap updates is crucial. By staying abreast of current technologies, predicting future trends, and seizing key technological opportunities, one can avoid falling behind.

5.5. Learning Indicators to Curriculum Design

Prior to the curriculum design, it is imperative to first establish the learning indicators as a reference for constructing the curriculum content. In the process of curriculum design, considerations such as starting from the basics and progressing to more advanced topics, as well as building upon prior knowledge need to be taken into account. Additionally, the allocation of learning hours for each learning indicator is also a topic requiring further exploration.

5.6. Constraints on Curriculum

However, the integration of the technology roadmap concept into the construction of learning indicators may not be applicable to every subject. Curriculums that can adopt the approach outlined in this study should primarily be those related to technology-related industries. Only in this way can the maximum benefits of the technology roadmap be realized.

6. Conclusions

The purpose of this study is to integrate the concept of technology maps into the construction of learning indicators. Through technology maps, technical forecasting is conducted to draw a roadmap of the target domain. Subsequently, learning indicators are jointly formulated by expert scholars for reference in instructional content and teaching material design. In alignment with the spirit of SDG Goal 8, fostering diversification, emerging technologies, and innovative thinking facilitates enhanced the attainment of suitable employment for learners in relevant domains (SDG 8.2, 8.5 and 8.6). Furthermore, this study also proposes the value of this research and potential directions for future work.

In addition, to bridge the gap between learning and application, integrating the concept of a technology roadmap, and leveraging its capability to anticipate future trends, ensures that the educational content remains at the forefront. This approach addresses the longstanding issue of discrepancies between learning and application. Leveraging this technique not only accelerates alignment with industry but also conserves time, costs, and resources, thereby achieving sustainability objectives.

6.1. Contribution

Compared to traditional curriculum learning indicator construction, this study integrates the concept of a technology roadmap. A panel of experts, including indicator constructors, industry representatives, and educational practitioners, was convened to discuss and investigate, thereby developing more comprehensive learning indicators and enhancing communication between academia and industry. This approach ensures that the curriculum content more directly aligns with industry needs, reducing the occurrence of the gap between learning and application. This benefits not only students but also indirectly aids in talent cultivation for the industry, resulting in a mutually beneficial relationship.

The rapid evolution of technology necessitates concurrent adjustments to educational content to ensure its alignment with practical applications. Conventional approaches to curriculum development may overlook current industry trends or future-oriented characteristics, thereby hindering the applicability of learning outcomes in real-world contexts and perpetuating widespread issues. Researchers thus integrate elements of technology roadmaps to address this longstanding and global challenge.

As this study has constructed learning indicators and reached consensus among expert scholars, it serves as a suitable guideline or resource for curriculum developers. Through the framework of these indicators and the ingenuity of editors, the developed materials not only provide a foundational knowledge structure but also address current industry applications, enabling learners to grasp current technologies and anticipate future trends.

In theoretical terms, students who master a more precise knowledge context will find it easier and faster to adapt to their careers in the future or pursue further studies with a more solid conceptual foundation. In practical terms, students are able to enter the workforce directly, responding to various situations as they arise, thereby meeting industry and client demands, which further affirms their own practical competence.

6.2. Future Work

This study, using the smart home system practices curriculum as an example, has performed indicator construction after research. In the future, exploration should continue and applications should be extended to ensure that this approach can develop in other fields. This ensures the fulfillment of talent cultivation and supply on the educational side, while also enabling the industrial side to shorten unit items and time in education and training, reallocating costs to other areas.

Furthermore, to verify talent development and track current situations, future investigations and interviews can be conducted with relevant personnel to explore and analyze their changes. Gathering valuable insights will assess areas for optimization and improvement, from indicator construction and instructional material development to curriculum design and actual teaching, ensuring the feasibility and advantages of the process.