Design and Implementation of a Closed-Loop Management System for Multi-Source Learning Evidence in Creative Programming Education

DOI: https://doi.org/10.62517/jbdc.202601401

Author(s)

Yingjiang Wang

Affiliation(s)

College of Information Engineering, Suqian University, Suqian, Jiangsu, China

Abstract

Creative programming courses generally cover classroom teaching, development of programming artifacts, regular quizzes, teacher grading and learning process documentation. If this data is stored in separate course, artifact and examination modules, it will be difficult for teachers to track the progress of student learning systematically. Dispersal of the evidence also limits the scope of process-oriented evaluation. Therefore, this paper proposes a design and implementation of a closed-loop management system for multi-source learning evidence in creative programming education. The basic organisational unit of instructional activities in the system is a course unit. Link course resources, attendance check-ins, class assignments, programming artifacts, knowledge-point questions, examination answers and error records. The linked data supports different access and management rights for administrators, teachers, students and parents. The management interface uses Vue 3 and Ant Design Vue. The backend services are based on Spring Boot, MyBatis-Plus, MySQL, Redis, Shiro/JWT, and a separate WeChat mini-program service extends query access for parents. For objective questions, the system will automatically grade them and record any incorrect answers upon submission of the exam. For questions of Scratch programming, the external program validation interface will return a similarity score or test result; however, creative tasks and subjective questions will still be graded by the teacher. The system can coordinate the management of learning process records, artifact assessment and knowledge-point diagnosis for creative programming courses. Evaluation is limited to the function and data traceability of the deployed system, and no causal improvement in learning achievement has been established.

Keywords

Creative Programming Education; Process-Oriented Assessment; Learning Evidence; Scratch; Online Teaching Management System

References

[1] RESNICK M, MALONEY J, MONROY-HERNÁNDEZ A, et al. Scratch: Programming for all. Communications of the ACM, 2009, 52(11): 60-67. [2] GROVER S, PEA R. Computational thinking in K-12: A review of the state of the field. Educational Researcher, 2013, 42(1): 38-43. [3] SÁEZ-LÓPEZ J M, ROMÁN-GONZÁLEZ M, VÁZQUEZ-CANO E. Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education, 2016, 97: 129-141. [4] ZHU Y W, XIAO Y, KUANG Y X, et al. Design and implementation of learning situation analysis management system based on WeChat mini program. Journal of Technology Innovation and Engineering, 2026, 2(5). [5] SUN L, HU X. Design and implementation of an intelligent academic status management system for universities based on augmented reality and large language models. Journal of Technology Innovation and Engineering, 2026, 2(6). [6] FERGUSON R. Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 2012, 4(5/6): 304-317. [7] VIBERG O, HATAKKA M, BÄLTER O, et al. The current landscape of learning analytics in higher education. Computers in Human Behavior, 2018, 89: 98-110. [8] BLACK P, WILIAM D. Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 1998, 5(1): 7-74. [9] SHUTE V J. Focus on formative feedback. Review of Educational Research, 2008, 78(1): 153-189. [10] NICOL D J, MACFARLANE-DICK D. Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 2006, 31(2): 199-218. [11] MENG Q. Design and implementation analysis of enterprise employee personnel information management system. Journal of Technology Innovation and Engineering, 2026, 2(1). [12] PAUTASSO C, ZIMMERMANN O, LEYMANN F. RESTful web services vs. “big” web services: Making the right architectural decision//Proceedings of the 17th International Conference on World Wide Web. New York: Association for Computing Machinery, 2008: 805-814. [13] DRAGONI N, Giallorenzo S, LAFUENTE A L, et al. Microservices: Yesterday, today, and tomorrow//Present and Ulterior Software Engineering. Cham: Springer, 2017: 195-216. [14] PARDO A, SIEMENS G. Ethical and privacy principles for learning analytics. British Journal of Educational Technology, 2014, 45(3): 438-450. [15] DRACHSLER H, GRELLER W. Privacy and analytics: It’s a DELICATE issue//Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. New York: Association for Computing Machinery, 2016: 89-98.