Since the inception of the SuperMap National GIS Competition for Higher Education Students (hereinafter referred to as the “GIS Competition”), many outstanding supervising instructors have emerged. Under their guidance, student teams have excelled—leading the way and winning top honors.

Starting today, we are launching the "Revelations from Excellent Supervising Instructors" series, aiming to share valuable professional experience and unique insights for all instructors currently participating in, or planning to participate in, the GIS Competition.

Our first guest is Associate Professor Ma Xuemei from the School of Geography and Environment, Liaocheng University—an instructor repeatedly honored as an Excellent Supervising Instructor in the GIS Competition. She has led her student teams to achieve remarkable results year after year. Today, she shares her experience on topic selection, project guidance, and the key elements that define an excellent competition work.

Ⅰ. On Topic Selection Guidance

Q: What characteristics should a good topic possess?

A:

1.Clear demand and practical value. A good topic should address a real-world problem.

2.Technological and algorithmic innovation, which forms the core of student development.

3.Feasibility and clear requirement analysis. A topic cannot remain a mere concept; it must have feasible implementation conditions, such as reliable data sources and the capacity to develop a usable system within a limited timeframe.

Q: How do you help students identify and finalize topics that are both innovative and feasible?

A:

1.I first guide students to focus on real-world issues and explore pain points that GIS technology can solve. We collect industry cases, policy trends, and cutting-edge research papers to ensure the topic has social value. Through brainstorming, we filter and refine several preliminary topics.

2.For these initial topics, we assess feasibility from the perspectives of data availability and technical capability. I help students evaluate the reliability, accuracy, and acquisition costs of the required data, as well as the accessibility of the necessary technologies. If data or technology is too difficult to obtain, I encourage them to find alternatives or pivot to a new topic.

3.We integrate emerging technologies to enhance innovation in core functions. During topic selection, I encourage students to review literature and reports on GIS advancements such as deep learning, big data processing, and cloud computing.

4.Before formal development, we hold brainstorming sessions and intentionally "challenge" team members to think critically about their topic's strengths and weaknesses. This helps avoid blind optimism. In our lab, a topic must convince the supervising teacher before it can proceed—this ensures every proposal is persuasive and realistic. Debates often arise between students or between students and instructors, which I consider a healthy and productive start.

Ⅱ. On the Guidance Process

Q: What guidance do you provide before students start project creation?

A:

1.First, I ensure students clarify project goals and conduct requirement analysis. That is to make sure that the topic truly solves a practical problem rather than merely combining technologies. We also identify target users (e.g., government departments, enterprises, or the general public), as this determines the system's functional priorities. Finally, we define usage scenarios—whether the system is for PC, mobile, or Web, and whether real-time data interaction is required.

2.Once the topic is confirmed, I review and refine the students' technical plan multiple times, selecting suitable models to ensure feasibility.

3.To ensure efficient progress, I pay close attention to project planning and task allocation led by the team leader. This avoids a slow start followed by a rushed and incomplete finish.

Q: What challenges arise during the development process, and how do you help students overcome them?

A:
The main focus is core technology progress. Students often deviate from their initial design, so I remind them to assess whether core functions need adjustment. For instance, in one project, the 3D function diverged from the original plan—I helped students revise their design to make it more practical.

I also act as a supervisor and mediator. Conflicts easily occur in team collaborations, and sometimes project delays stem from a single team member. In such cases, I check whether the issue is emotional or technical. My background in psychology helps me handle these situations effectively.

Finally, I emphasize encouragement and motivation. Near the end of the summer, when students feel exhausted and demoralized, I pay close attention to their morale. Sometimes, I can sense an issue the moment I walk into the lab. At such times, I act more like a mother figure—occasionally bringing snacks to ease tension and uplift spirits.

Q: How do you guide students to deepen and complete their projects?

A:

I guide students to conduct thorough research, identifying the pain points and needs of their chosen topic, and to build a clear project structure. We outline core and sub-functions, plan data, technology, and interface design, and assign tasks based on individual strengths. Students work in modules and later integrate them into a unified prototype. Finally, I encourage them to stay up-to-date with industry trends and continuously optimize their projects, making them more complete and competitive.

Ⅲ. On the Key Elements of an Excellent Work

Q: What are the defining elements of an excellent work?

A:

An excellent work should begin with an in-depth analysis of a real social problem and propose innovative, practical, and technically solid solutions. It should make use of new SuperMap platforms, explore new application scenarios, and solve real problems effectively. A top work should be user-friendly, stable, and well-structured, featuring advanced architecture, precise data processing, complete functions, comprehensive documentation, and aesthetic design.

Q: What common mistakes do students make when creating their projects?

A:

Students often overlook the following four key areas—oversights that can cost them awards:

1.Data Governance: The Leap from "Adoptism" to "Precision Verification"
Verify the authority of data sources by cross-referencing official sources such as the Ministry of Natural Resources standard maps or the National Geographic Information Public Service Platform, especially for sensitive data like national borders or maritime boundaries.

2.Technical Details: The Devil is in the Code Comments

• Algorithm Robustness Testing: Most students only test ideal cases. Adopt the "Five-Step Stress Testing Method" used by Wuhan University teams: Null Value Injection → Data Overflow → Concurrency Impact → Exception Interruption → Recovery Verification.
• User Interaction Design: Avoid overloading interfaces with excessive information—consider users’ cognitive limits.

3.Time Management: Fragmented Development Cycles

A typical SuperMap project requires 200–300 development hours, but students often waste time redoing basic modules. Adopt the "Four-Phase Control Method":

Foundation Building (30%) → Function Implementation (40%) → Aesthetic Optimization (20%) → Backup & Recovery (10%).

4.Team Collaboration: The Hidden Cost of 1+1<2

Technical members often stray into UI design, slowing progress. Follow the "Three-Dimensional Division of Labor":

• Data Processing Group (GIS majors): Spatial database construction and model tuning
• Development Group (CS majors): API integration and performance optimization
• Narrative Group (Design/Humanities majors): "Problem–Analysis–Solution" storytelling

These "small" details are what truly separate qualified works from award-winning ones. I recommend that every team create a "Defect Pre-check List" and strive for excellence through self-improvement.

Ⅳ. Suggestions for Supervising Instructors

Q: What are your reflections and suggestions for fellow instructors?

A:

In guiding professional competitions, teachers should understand that while the love of teaching is a natural professional trait, students must be the main drivers of the entire process—from topic selection and data collection to system design and implementation. This experience fosters ownership and a sense of achievement, which is the true value of such competitions. Therefore, instructors should avoid assigning their own research topics to students. Having students work on a teacher's project is like asking them to raise someone else's child—it's difficult to fully spark their passion.

Teachers should act as coaches, neither taking over the work nor leaving students entirely alone. The purpose of competitions is to cultivate students' comprehensive abilities, so all efforts should focus on student growth and development. Of course, genuine care and encouragement remain the hallmarks of an excellent supervising instructor.

Since I began teaching, I've always been passionate about mentoring students in professional competitions. During the 2024 SuperMap Development Competition, I deeply felt the vibrant momentum of our field. When visiting the SuperMap History Exhibition at headquarters, I was moved to realize I've accompanied SuperMap for 19 years of its journey. While students change every year, SuperMap's contribution to nurturing countless outstanding professionals remains timeless. Here, I raise a glass to SuperMap and our shared dream. Looking ahead to 2025, may we gather again and continue writing glorious new chapters together.

Ⅴ. Suggestions for Participating Students

Q: What advice do you have for students participating in this year's GIS Competition?

A:

1.Topic Planning: Base on Social Needs, Seek Innovative Breakthroughs

• Three Elements of Topic Selection: Balance uniqueness, social significance, and feasibility. Start from national strategic directions (e.g., smart cities, ecological protection) or social concerns (e.g., aging population services, pandemic monitoring) to ensure real-world value.
• Cultivate Innovative Thinking: Go beyond traditional GIS frameworks and explore AI-assisted design or multi-dimensional data fusion (e.g., time-series + spatial analysis).

2.Technical Practice: Strengthen Core Skills, Refine Details

• Solid Foundations: Master key SuperMap software operations—especially spatial database construction, map symbolization standards, and coordinate system consistency.
• Programming Skills: Each development team member should master at least one programming language to implement custom spatial analysis algorithms rather than relying solely on built-in tools.

3.Team Collaboration: Clarify Roles, Promote Synergy

• Adopt a composite team structure: "Technical Backbone + Design Talent + Documentation Expert."
• Use project management tools like Gantt charts and hold weekly progress reviews.

4.Project Presentation: Build Logical Narratives and Visual Appeal

• Storytelling Design: A map is not just a data container—it should tell a story. Use a "Problem Discovery → Data Analysis → Solution" framework.
• Visual Aesthetics: Apply color psychology, control information density, and avoid overloaded map designs.