In an era marked by explosive technological advancements, humanoid robot technology has emerged as a cutting-edge frontier, integrating knowledge from mechanical engineering, electronic information technology, computer science, and other disciplines. This field showcases highly intelligent and remarkably human-like characteristics, driving innovation across various sectors. Digital Electronics Technology, a foundational core course for electronic information-related majors, provides the underlying logical framework for numerous high-tech applications. A recent study conducted by researchers from Yan’an University Xi’an Innovation College explores the integration of humanoid robot technology into the Digital Electronics Technology curriculum, highlighting its potential to revolutionize teaching practices and cultivate versatile talent. This reform aims to bridge the gap between abstract theoretical knowledge and tangible real-world applications, fostering students’ practical skills and innovation capabilities in alignment with industry demands for multidisciplinary expertise.
1. Research Background and Significance
The rapid development of humanoid robot technology represents a significant leap in robotics, combining elements such as sophisticated mechanical structures, sensor systems, and intelligent software. These humanoid robots are designed to mimic human movements and interactions, requiring a deep understanding of digital electronics for their core functionalities. The Digital Electronics Technology course, which covers fundamental concepts like logic gates, sequential circuits, and microcontrollers, serves as a critical building block for engineering education. However, traditional teaching methods often fail to connect these concepts to contemporary applications, leading to a disconnect between classroom learning and industrial needs. By incorporating humanoid robot technology into the curriculum, educators can transform abstract digital electronics principles into engaging, hands-on experiences. This approach not only enhances student interest and motivation but also prepares them for careers in developing, maintaining, and advancing humanoid robot systems. The initiative aligns with the educational goals of institutions like Yan’an University Xi’an Innovation College, which focuses on cultivating application-oriented talent capable of contributing to technological evolution and economic growth.
2. Domestic and International Research Status
Globally, universities and research institutions have been pioneers in interdisciplinary education, with many integrating humanoid robot projects into electronic engineering courses. For instance, institutions in countries like Japan, the United States, and Germany have adopted practice-oriented teaching models that involve students in the entire development process of humanoid robots, from design to implementation. These programs emphasize real-world problem-solving and often utilize advanced simulation tools and hardware platforms to provide immersive learning experiences. However, challenges remain in systematically integrating course knowledge, as many initiatives focus on specific projects or competitions without fully embedding them into standard curricula. In contrast, domestic educational reforms in China have increasingly emphasized the fusion of前沿 technologies with foundational courses. Numerous universities have launched similar teaching reforms, but many are still concentrated around robotics competitions or extracurricular activities, lacking deep penetration into regular classroom instruction. Gaps persist in innovative teaching methodologies and tailored assessment systems, indicating a need for more comprehensive approaches that seamlessly blend humanoid robot technology with digital electronics education to achieve sustainable educational outcomes.
3. The Connection Between Humanoid Robot Technology and Digital Electronics Technology
The hardware system of humanoid robots, often referred to as their physical body, includes精密 mechanical skeletons, diverse sensors such as visual, auditory, and tactile systems, and efficient actuators like motors and servos. Digital electronics technology plays a vital role in enabling the precise驱动, coordination, and operation of these components. For example, microcontrollers generate pulse signals based on pre-set motion algorithms to control actuators, ensuring smooth and natural limb movements in humanoid robots. From a software perspective, humanoid robots rely on operating systems, motion control algorithms, and intelligent decision-making programs, all of which depend on digital signal processing, logical operations, and data storage facilitated by digital electronics. In visual sensors, vast amounts of image data are sampled, quantified, and encoded through digital circuits into digital signals for analysis, enabling humanoid robots to perceive and understand their environment accurately. This intrinsic link underscores how digital electronics form the backbone of humanoid robot functionality, from low-level circuit design to high-level intelligent behaviors.
4. Current Issues in Digital Electronics Course Teaching
Traditional Digital Electronics Technology courses often emphasize theoretical knowledge, with experimental sessions limited to basic verification-level exercises like circuit搭建. This approach results in a significant disconnect between classroom content and practical applications, as students struggle to relate abstract concepts to real-world scenarios such as humanoid robot development. Additionally, teaching methods tend to be monotonous, relying heavily on instructor-led lectures supplemented by板书, PowerPoint presentations, and辅助 videos. Even with some reforms incorporating online and offline blended models, the focus remains on theoretical adjustments, leaving students in a passive learning state. In the context of engaging fields like humanoid robots, which demand hands-on practice and creativity,单一 teaching approaches fail to ignite student enthusiasm or encourage exploration of digital electronics’ potential. Furthermore, assessment systems are often inadequate, dominated by closed-book final exams that test theoretical knowledge through concepts, circuit analysis, and simple calculations, with little emphasis on practical projects involving humanoid robots. This leads to a tendency among students to memorize content rather than develop application skills and innovative thinking, ultimately hindering their ability to meet industry demands after graduation.
5. Teaching Reform Goals and Principles
The primary goal of this teaching reform is to overhaul the traditional教学模式 of the Digital Electronics Technology course, ensuring students master the digital electronics knowledge and skills essential for humanoid robot technology. Through project-based practice, the reform aims to enhance students’ hands-on abilities and cultivate their competence in solving complex engineering problems related to humanoid robots, such as optimizing motion control circuits and improving sensor data processing efficiency. Simultaneously, the initiative focuses on fostering innovative thinking and teamwork, equipping students with the comprehensive qualities needed to adapt to the evolving challenges of humanoid robot technology. The reform adheres to key principles, including the紧密 integration of theory and practice. This ensures that course instruction and humanoid robot projects progress in tandem, allowing students to appreciate the importance of theoretical guidance in practical applications and the necessity of practice for deepening theoretical understanding. This creates a良性循环 of learning by doing and doing by learning, ultimately promoting a more dynamic and effective educational experience.
6. Teaching Reform Strategies Based on Humanoid Robot Technology
To achieve the reform objectives, a multi-faceted approach has been implemented, focusing on content optimization, methodological innovation, and assessment improvement. These strategies are designed to make the Digital Electronics Technology course more relevant, engaging, and effective in preparing students for advancements in humanoid robot technology.
- Optimizing Teaching Content: The curriculum has been enriched by introducing real-world cases involving humanoid robots. For instance, at the start of the course, videos of humanoid robots in action, such as dance performances or rescue simulations, are shown to capture student interest and spark curiosity about the underlying digital electronics. When teaching combinatorial logic circuits, examples like hand gesture control in humanoid robots are used to illustrate how logic gates can design circuits for finger movements. In sequential logic sections, robot walking gait control serves as a practical example to explain the role of counters and registers in generating periodic control signals. Additionally, course knowledge points have been reorganized around the workflow of humanoid robots—from perception to decision-making and execution—integrating topics like sensor interface circuits, digital signal processing, and microcontroller programming into a cohesive learning chain. This helps students build a comprehensive understanding of how digital electronics components collaborate to enable intelligent operations in humanoid robots.
- Innovating Teaching Methods: Several interactive methodologies have been adopted to enhance learning. Project-driven teaching involves designing a series of projects centered on humanoid robot functional modules, such as facial expression control systems or autonomous obstacle avoidance platforms. Students work in groups to tackle these projects, covering all stages from需求 analysis and scheme design to circuit搭建 and debugging. Virtual simulation teaching utilizes software like Proteus, Multisim, and MATLAB to create realistic virtual environments where students can design and test digital electronic circuits for humanoid robots without hardware constraints. For example, simulating visual tracking systems allows students to adjust circuit parameters and observe effects on performance, thereby improving design skills while reducing costs and enhancing safety. Group cooperative learning organizes students into teams of 4-6 based on diverse abilities and characteristics, with clear roles such as hardware setup, software programming, documentation, and testing. In projects like a humanoid robot music performance, students collaborate to complete tasks, fostering teamwork and communication while sharing knowledge and achieving collective goals.
- Improving Assessment Methods: The evaluation system has been diversified to include multiple indicators: theoretical knowledge (30-40%), practical ability (30-40%), project outcomes (10-20%), and teamwork (10-20%). Theoretical assessments incorporate questions set in humanoid robot contexts to encourage application, while practical skills are evaluated through lab operations and project defenses. Project results are graded based on innovation, functionality, and stability, and teamwork is assessed for分工合理性, communication effectiveness, and collaborative problem-solving. Process-oriented evaluation is strengthened by tracking classroom participation (10-20%), project progress (30-40%), and lab reports (30-40%), which record实验目的, steps, issues, and solutions. This comprehensive approach ensures a balanced assessment of student engagement, initiative, and overall development throughout the learning process.
7. Practical Case Analysis of Teaching Reform
A practical implementation of the reform was conducted in electronic information majors, involving two classes: an experimental group that adopted the new strategies and a control group that followed traditional teaching methods. In the experimental group, the reform included introductory lectures on humanoid robots, project-based group activities supported by virtual simulations, regular progress reports, and a final project exhibition with defenses, all under a多元化考核 system. The control group, however, adhered to textbook chapter sequences, teacher-centered lectures, and simple experiments, with traditional exams as the primary assessment. After one semester, results showed that the experimental group outperformed the control group by nearly 10 points in average final exam scores. Moreover, the experimental group demonstrated stronger innovation capabilities, such as designing more intelligent gesture recognition systems for humanoid robots. Interest surveys revealed that over 80% of students in the experimental group expressed high engagement with the course, compared to only about 25% in the control group, indicating that the reform significantly boosted learning outcomes and motivation. However, challenges emerged, including limited access to humanoid robot hardware, which restricted hands-on time and increased workloads, and difficulties for some students with weaker foundations in adapting to interdisciplinary knowledge. To address these, measures such as seeking industry partnerships to expand equipment resources and implementing blended online-offline teaching with pre-class materials and post-class support were introduced to accommodate diverse student needs.
8. Conclusion and Outlook
The integration of humanoid robot technology into the Digital Electronics Technology course has proven effective in revitalizing teaching content, methods, and assessments. By making knowledge more vivid through case studies and holistic integration, and by激发 student enthusiasm with innovative approaches, the reform has strengthened both theoretical foundations and practical applications in humanoid robots. Students have shown improved performance and readiness for future careers, laying a solid groundwork for their professional development. Looking ahead, as humanoid robot technology advances toward greater intelligence and flexibility, further interdisciplinary integration with fields like biology and psychology will be essential to refine robot design. International collaborations can bring in advanced teaching理念 and techniques, while the development of more open and challenging projects will continue to nurture talent capable of leading the humanoid robot era. This ongoing effort promises to sustain educational innovation and contribute to the growth of high-quality, innovative professionals in the field of humanoid robots.