Reconstructing University Music Curricula through Knowledge Graphs: Integrating Disciplinary Learning and Comprehensive Ideological and Political Education
University music programs face a familiar curriculum problem: how to connect specialist musical training with broader educational responsibilities without weakening either. In China’s comprehensive ideological and political education agenda, the problem is not only what content to include but how courses, musical practices, educational purposes, and assessment relate to one another. This article sets out a knowledge-graph-supported framework for curriculum reconstruction and follows its use in a practice-based study at X University. The study covers a twelve-week teaching cycle with four connected courses and two instructional conditions of sixty students each. A curriculum graph holds 412 entities and 786 relationships, separating disciplinary connections, pedagogical intentions, and assessment arrangements. The reconstruction adds coordinated sequencing, shared inquiry tasks, evidence-based interpretation, and differentiated assessment. Coverage and outcomes are reported side by side: complete objective–activity–assessment pathways rise from thirteen to twenty-one of twenty-four objectives, and the between-condition difference in mean change is 8.8 points for contextual reasoning, 5.0 for musical analysis, 7.4 for feedback-informed revision, and 0.8 for performance on a 100-point scale. These values are descriptive; they are not evidence of intervention effectiveness. The analysis also identifies three requirements for a defensible empirical study: a comparison with an equally supported non-graph approach, independent assessment of student work, and an explicit account of implementation costs. The article argues that knowledge graphs should be judged by the educational decisions they make possible, not by their size or the polish of their visualizations. Their value, if any, lies in making curriculum relationships traceable while preserving musical judgment, interpretive plurality, and student agency.
[1] Ministry of Education of the People’s Republic of China, 2020, Guidelines for Ideological and Political Education across the Curriculum in Higher Education, [2020]3.
[2] Ministry of Education of the People’s Republic of China and nine other departments, 2022, Work Plan for Comprehensively Advancing “Da Sizheng Ke”, [2022]3.
[3] Gaunt H, Duffy C, Coric A, et al., 2021, Musicians as “Makers in Society”: A Conceptual Foundation for Contemporary Professional Higher Music Education. Frontiers in Psychology, 2021(12): 713648. https://doi.org/10.3389/fpsyg.2021.713648
[4] Gaunt H, 2008, One-to-one Tuition in a Conservatoire: The Perceptions of Instrumental and Vocal Teachers. Psychology of Music, 36(2): 215–245. https://doi.org/10.1177/0305735607080827
[5] Gaunt H, 2010, One-to-one Tuition in a Conservatoire: The Perceptions of Instrumental and Vocal Students. Psychology of Music, 38(2): 178–208. https://doi.org/10.1177/0305735609339467
[6] Carey GM, Bridgstock R, Taylor P, et al., 2013, Characterising One-to-one Conservatoire Teaching: Some Implications of a Quantitative Analysis. Music Education Research, 15(3): 357–368. https://doi.org/10.1080/14613808.2013.824954
[7] Hogan A, Blomqvist E, Cochez M, et al., 2021, Knowledge Graphs. ACM Computing Surveys. 54(4): Article 71, 1–37. https://doi.org/10.1145/3447772
[8] Ji S, Pan S, Cambria E, et al., 2022, A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. IEEE Transactions on Neural Networks and Learning Systems, 33(2): 494–514. https://doi.org/10.1109/TNNLS.2021.3070843
[9] Chen P, Lu Y, Zheng VW, et al., 2018, KnowEdu: A System to Construct Knowledge Graph for Education. IEEE Access, 2018(6): 31553–31563. https://doi.org/10.1109/ACCESS.2018.2839607
[10] Ain QU, Chatti MA, Bakar KGC, et al., 2023, Automatic Construction of Educational Knowledge Graphs: A Word Embedding-based Approach. Information. 14(10): 526. https://doi.org/10.3390/info14100526
[11] Biggs J, 1996, Enhancing Teaching through Constructive Alignment. Higher Education. 1996(32): 347–364. https://doi.org/10.1007/BF00138871
[12] Shulman LS, 1986, Those Who Understand: Knowledge Growth in Teaching. Educational Researcher, 15(2): 4–14. https://doi.org/10.3102/0013189X015002004
[13] McPhail G, 2018, Curriculum Integration in the Senior Secondary School: A Case Study in a National Assessment Context. Journal of Curriculum Studies, 50(1): 56–76. https://doi.org/10.1080/00220272.2017.1386234
[14] Hess J, 2015, Decolonizing Music Education: Moving Beyond Tokenism. International Journal of Music Education, 33(3): 336–347. https://doi.org/10.1177/0255761415581283
[15] Biesta G, 2009, Good Education in an Age of Measurement: On the Need to Reconnect with the Question of Purpose in Education. Educational Assessment, Evaluation and Accountability, 2009(21): 33–46. https://doi.org/10.1007/s11092-008-9064-9
[16] Jaakkola E, 2020, Designing Conceptual Articles: Four Approaches. AMS Review, 2020(10): 18–26. https://doi.org/10.1007/s13162-020-00161-0
[17] Boud D, Falchikov N, 2006, Aligning Assessment with Long-Term Learning. Assessment & Evaluation in Higher Education, 31(4): 399–413. https://doi.org/10.1080/02602930600679050
[18] Nicol DJ, Macfarlane-Dick D, 2006, Formative Assessment and Self-Regulated Learning: A Model and Seven Principles of Good Feedback Practice. Studies in Higher Education. 31(2): 199–218. https://doi.org/10.1080/03075070600572090
[19] The Design-Based Research Collective, 2003, Design-based Research: An Emerging Paradigm for Educational Inquiry. Educational Researcher, 32(1): 5–8. https://doi.org/10.3102/0013189X032001005
[20] Sandoval W, 2014, Conjecture Mapping: An Approach to Systematic Educational Design Research. Journal of the Learning Sciences, 23(1): 18–36. https://doi.org/10.1080/10508406.2013.778204
