Meta-SEE:Intelligent and Interactive Learning Framework for Software Engineering Education Based on Metaverse and Metacognition

With the rapid evolution of technology and the increasing complexity of software systems,there is a growing demand for effective educational approaches that empower learners to acquire and apply software engineering skills in practical contexts.This paper presents an intelligent and interactive learning(Meta-SEE)framework for software engineering education that combines the immersive capabilities of the metaverse with the cognitive processes of metacognition,to create an interactive and engaging learning environment.In the Meta-SEE framework,learners are immersed in a virtual world where they can collaboratively engage with concepts and practices of software engineering.Through the integration of metacognitive strategies,learners are empowered to monitor,regulate,and adapt their learning processes.By incorporating metacognition within the metaverse,learners gain a deeper understanding of their own thinking processes and become self-directed learners.In addition,MetaSEE has the potential to revolutionize software engineering education by offering a dynamic,immersive,and personalized learning experience.It allows learners to engage in realistic software development scenarios,explore complex systems,and collaborate with peers and instructors in virtual spaces.

A New Model of Software Engineering Education and Exploration of Professional Curriculum Teaching

This paper focuses on the problems,opportunities,and challenges faced by software engineering education in the new era.We have studied the core ideas of the new model and reform,the specific measures implemented,and the challenges and solutions faced.The new model and reform must focus on cultivating practical abilities,introducing interdisciplinary knowledge,and strengthening innovation awareness and entrepreneurial spirit.The process of reform and innovation is carried out from the aspects of teaching methods,teaching means,and course performance evaluation in the teaching practice of software engineering courses.We adopt a method of“question guiding,simple and easy to understand,flexible and diverse,and emphasizing practical results”,optimizing the curriculum design,providing diverse learning opportunities,and establishing a platform for the industry-university-research cooperation.Our teaching philosophy is to adhere to the viewpoint of innovative teaching ideas,optimizing teaching methods and teaching means,and comprehensively improving the teaching quality and level of software engineering education.

QualiTeam: A Support Tool When Learning Software Quality and Testing Concepts

QualiTeam is a web application to support the teaching-learning process on Software Quality Assurance, Quality Control and Testing introductory concepts. It has two main objectives: to facilitate the understanding of concepts learned in theory and to facilitate the monitoring of SW projects that students develop. The system gives the teacher control and the students a guide on the activities that must be carried out throughout a software project development. QualiTeam is a tool conceived to help in the challenge of providing students with concrete examples with which they can practice and clarify the topics taught in the classroom. With it, students can apply concepts that, in the initial training of a software engineer, are generally taught only at a theoretical level such as: review process, change requests, trouble reports, document version control and testing documentation management. QualiTeam is free and available online. It has been in operation for 5 years, through which improvements have been made until achieving a quite stable version.

Towards Large-scale AI Solutions for Postgraduate Study:An Exploration of Teaching Scheme

With the development of deep learning algorithms,deep learning-related courses play an important role in the curriculum of software engineering education.Most of the existing courses in deep learning focus on its foundation,while the skills of integrating deep learning algorithms into large-scale industrial software are not well trained.In this paper,we explore a teaching scheme,developing the foundation for postgraduate students to create large-scale AI solutions for the marketplace.This is achieved through the optimized teaching contents,assignment,and a group project.We evaluate the efficacy of this scheme for 2 classes in the School of Software,Northwestern Polytechnical University.Feedback from these students,as well as the project’s outcomes,validate that the skills of students in creating scalable and complex deep learning solutions are significantly improved.

Modelling User Needs:Students as Enterprise Analysts

We illustrate a case study,where students designed enterprise architectures,that were not only welcome but successfully implemented.The success key was threefold.First the analysis framework,that integrates all the aspects of the systems that are relevant to users,namely user interface,rules,and information.Second,the analysis approach,that guides,trough confirmatory sessions,to elicit real requirements from users.Third,the model-to-model transformation,that assures consistency from the highest aggregate abstraction down to an executable model.

软件工程研究生工程化教育模式探讨(英文)

This paper introduces the pattern of software engineering postgraduate education in School of Software Engineering of South China University of Technology(SSE_SCUT).SSE_SCUT aims to foster the software talented with capability of achieving large scale or complex systems.In its education pattern,emphasizes engineering practices are emphasized.And this education notion is implemented in the postgraduate curriculum.