Big Data Application in Hospitality and Tourism Industry
The Big Data Application in Tourism and Hospitality course is a crucial component in cultivating modern tourism professionals. However, teaching this course presents numerous challenges. Wintour has meticulously developed a comprehensive curriculum and teaching resources with the aim of nurturing tourism and hospitality professionals who possess both expertise in the field and a strong data mindset.The course content imparts the concepts and thinking methodologies of big data as fundamental knowledge. It emphasizes the teaching of big data awareness, thinking, literacy, and methodologies, supplemented by relevant theoretical frameworks, lightweight coding exercises, and user-friendly practical training. The course syllabus supports 32 to 48 teaching hours and includes 11 practical training tasks that encompass typical industry tasks such as data collection, processing, analysis, visualization, and reporting. Each task is closely aligned with industry needs, ensuring students can apply their acquired knowledge in real-world scenarios.
Wintour's intelligent learning platform provides instructors responsible for teaching this course with a complete teaching plan and a repository of teaching resources. This repository includes textbooks, PowerPoint presentations, question banks, training software, practical training tasks, and manuals. It not only empowers instructors to innovate course content but also offers systematic support for the transformation of teaching methods.
Features
- Integration of Theory and Practice: Balances theoretical depth with practical breadth, utilizing methodologies, lightweight coding exercises, and industry case studies to help students translate knowledge into applicable skills.
- Real-World Data-Driven, Deeply Connected to the Industry: Provides abundant real industry data and 11 practical training tasks covering data collection, processing, analysis, visualization, and reporting, allowing students to experience the entire data application process in real-world scenarios and cultivate problem-solving abilities.
- Mastering the Entire Data Lifecycle from the Source: Breaks through traditional teaching models, enabling students to start from raw data collection and participate in data preprocessing, processing, visualization, and other stages, deeply understanding the data value chain and fostering practical operational skills.
- Scenario-Based Simulation Teaching: Innovatively introduces a scenario-based simulation sandbox to simulate real business scenarios, stimulating students' interest in learning and enhancing their ability to solve practical problems.
- Comprehensive Teaching Support: Wintour's Smart learning platform provides teachers with a complete teaching plan, a rich library of teaching resources, and convenient teaching tools to enhance teaching effectiveness.
Technology And Tools
- Wintour Smart Learning Platform
- Wintour Scenario Simulation Sandbox
- Wintour Tourism (Hotel) Big Data Application Platform
Innovations
- Blended Learning (based on Wintour Smart Learning Platform)
- Project-Based Learning
- Serious Game Learning (based on Wintour Scenario Simulation Sandbox)
Recommends
Tourism and Hospitality Big Data Applications -ISBN 9787302619338 (Tsinghua University Press)
- Originality: The first textbook designed for hotel management majors, incorporating real-world data for big data course instruction.
- Zero Barriers: No coding experience required, suitable for both teachers and students without technical backgrounds.
- Accessibility: Written with non-science majors in mind, featuring in-depth yet easy-to-understand explanations, rich visuals, and plain language.
- Practicality: Covers big data knowledge, technical principles, practical applications, scenarios, and methodologies, offering comprehensive and practical guidance.
- Applicability: Especially suitable for higher vocational colleges and technical secondary schools offering hotel management programs, also beneficial for industry professionals seeking self-improvement.