{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T03:22:49Z","timestamp":1790738569924,"version":"4.1.0"},"reference-count":31,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T00:00:00Z","timestamp":1770076800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Evaluation of student performance in music education is recognized as a persistent challenge. The current methods of assessment, such as peer feedback, instructor observations, and rubric-based grading, are subjective and fail to deliver prompt and personalized feedback. Previous approaches have largely relied on static evaluation schemes like standardized grading rubrics and subjective instructor judgments like qualitative assessments without real-time feedback, but they failed to accommodate individual learning differences and dynamic adjustment of instructional strategies based on a student\u2019s evolving abilities. To address these limitations, this study demonstrates a reinforcement learning-based adaptive evaluation framework designed for personalized music education. To optimize teaching interventions and customize learning experiences, the framework incorporates a task-selecting evaluation agent, a dynamic student model, and a continuous feedback mechanism. A Deep Q-Network (DQN) agent processes performance metrics like technical proficiency, expressiveness, sight-reading ability, and interpretative skills in real-time to suggest appropriate tasks and provide personalized feedback. A simulated dataset of students was used to train and test the model with different hyperparameters. These parameters are optimized through grid search and validation techniques. The results demonstrate that the proposed framework significantly outperforms baseline models, which include Q-learning, Proximal Policy Optimization (PPO), Soft Actor-Critic (SAC), Trust Region Policy Optimization (TRPO), Deep Deterministic Policy Gradient (DDPG), in terms of cumulative rewards, learning efficiency, and evaluation accuracy. Furthermore, the proposed framework exhibits superior adaptability by continuously updating student models and task recommendations based on ongoing performance data. This work offers a practical and scalable solution for personalized music education, contributing a step towards artificial intelligence (AI)-driven adaptive teaching systems in skill-based learning environments.<\/jats:p>","DOI":"10.7717\/peerj-cs.3464","type":"journal-article","created":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T08:07:37Z","timestamp":1770106057000},"page":"e3464","source":"Crossref","is-referenced-by-count":3,"title":["A reinforcement learning-based adaptive evaluation framework for personalized music education"],"prefix":"10.7717","volume":"12","author":[{"given":"Jing","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4443","published-online":{"date-parts":[[2026,2,3]]},"reference":[{"issue":"8","key":"10.7717\/peerj-cs.3464\/ref-1","doi-asserted-by":"publisher","first-page":"1154","DOI":"10.1007\/s42979-024-03491-z","article-title":"Generative AI and gamification for personalized learning: literature review and future challenges","volume":"5","author":"Abbes","year":"2024","journal-title":"SN Computer Science"},{"key":"10.7717\/peerj-cs.3464\/ref-2","doi-asserted-by":"publisher","first-page":"1361857","DOI":"10.3389\/fpsyg.2024.1361857","article-title":"The psychophysiology of music-based interventions and the experience of pain","volume":"15","author":"Arnold","year":"2024","journal-title":"Frontiers in Psychology"},{"key":"10.7717\/peerj-cs.3464\/ref-3","doi-asserted-by":"crossref","first-page":"51","DOI":"10.4018\/979-8-3693-8432-9.ch003","article-title":"Harnessing artificial intelligence in music creation: exploring genre musical features and their reflection in the pedagogical process","volume-title":"Enhancing Music Education With Innovative Tools and Techniques","author":"Babu","year":"2025"},{"key":"10.7717\/peerj-cs.3464\/ref-4","doi-asserted-by":"crossref","first-page":"63","DOI":"10.4324\/9781003419495-7","article-title":"Music education and the natural learning model","volume-title":"Teaching Music","author":"Barrett","year":"2023"},{"issue":"1","key":"10.7717\/peerj-cs.3464\/ref-5","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/S10758-022-09623-9","article-title":"Implementation and evaluation of an adaptive learning environment designed according to learner characteristics: a study on primary school social studies teaching","volume":"29","author":"Burak","year":"2024","journal-title":"Technology Knowledge and Learning"},{"issue":"1","key":"10.7717\/peerj-cs.3464\/ref-6","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s44196-024-00623-4","article-title":"The application of big data and fuzzy decision support systems in the innovation of personalized music teaching in universities","volume":"17","author":"Chen","year":"2024","journal-title":"International Journal of Computational Intelligence Systems"},{"key":"10.7717\/peerj-cs.3464\/ref-7","first-page":"153","article-title":"Creativity and digital music education in the AI era","author":"Coppi","year":"2024"},{"key":"10.7717\/peerj-cs.3464\/ref-8","doi-asserted-by":"publisher","first-page":"1195","DOI":"10.1145\/3357236.3395525","article-title":"A survey on interactive reinforcement learning: design principles and open challenges","author":"Cruz","year":"2020"},{"issue":"4","key":"10.7717\/peerj-cs.3464\/ref-9","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1080\/10447318.2022.2049141","article-title":"Accessible digital musical instruments in special educational needs schools\u2013design considerations based on 16 qualitative interviews with music teachers","volume":"39","author":"F\u00f6rster","year":"2023","journal-title":"International Journal of Human\u2013Computer Interaction"},{"key":"10.7717\/peerj-cs.3464\/ref-10","first-page":"309","article-title":"Advancements in smart learning techniques: a comprehensive review of trends and analytical insights","author":"Kaur","year":"2024"},{"issue":"3","key":"10.7717\/peerj-cs.3464\/ref-11","doi-asserted-by":"publisher","first-page":"2193","DOI":"10.1007\/S10462-022-10224-2","article-title":"A survey on deep reinforcement learning for audio-based applications","volume":"56","author":"Latif","year":"2023","journal-title":"Artificial Intelligence Review"},{"issue":"4","key":"10.7717\/peerj-cs.3464\/ref-12","doi-asserted-by":"publisher","first-page":"1279","DOI":"10.1080\/10494820.2022.2118787","article-title":"Modern mobile learning technologies in online piano education: online educational course design and impact on learning","volume":"32","author":"Liu","year":"2024","journal-title":"Interactive Learning Environments"},{"issue":"1","key":"10.7717\/peerj-cs.3464\/ref-13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1057\/s41599-025-04616-2","article-title":"Empowering music education with technology: a bibliometric perspective","volume":"12","author":"Ma","year":"2025","journal-title":"Humanities and Social Sciences Communications"},{"issue":"1","key":"10.7717\/peerj-cs.3464\/ref-14","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/S10639-021-10568-2","article-title":"Engaging students in creative music making with musical instrument application in an online flipped classroom","volume":"27","author":"Ng","year":"2022","journal-title":"Education and Information Technologies (Dordr)"},{"issue":"8","key":"10.7717\/peerj-cs.3464\/ref-15","doi-asserted-by":"publisher","first-page":"8336616","DOI":"10.1155\/2022\/8336616","article-title":"The generation of piano music using deep learning aided by robotic technology","volume":"2022","author":"Pan","year":"2022","journal-title":"Computational Intelligence and Neuroscience"},{"issue":"1","key":"10.7717\/peerj-cs.3464\/ref-16","doi-asserted-by":"publisher","first-page":"1704","DOI":"10.1038\/s41598-023-28426-1","article-title":"Studying the effect of self-selected background music on reading task with eye movements","volume":"13","author":"Que","year":"2023","journal-title":"Scientific Reports"},{"key":"10.7717\/peerj-cs.3464\/ref-17","doi-asserted-by":"publisher","first-page":"1331806","DOI":"10.3389\/fpsyg.2024.1331806","article-title":"Music performance as knowledge acquisition: a review and preliminary conceptual framework","volume":"15","author":"Reybrouck","year":"2024","journal-title":"Frontiers in Psychology"},{"key":"10.7717\/peerj-cs.3464\/ref-18","doi-asserted-by":"publisher","first-page":"55169","DOI":"10.1109\/access.2025.3554222","article-title":"End-to-end deployment of the educational AI hub for personalized learning and engagement: a case study on environmental science education","volume":"13","author":"Sajja","year":"2025","journal-title":"IEEE Access"},{"issue":"4","key":"10.7717\/peerj-cs.3464\/ref-19","doi-asserted-by":"publisher","first-page":"2583","DOI":"10.1007\/S00521-021-05846-6","article-title":"Exploring online intelligent teaching method with machine learning and SVM algorithm","volume":"34","author":"Shuo","year":"2022","journal-title":"Neural Computing and Applications"},{"issue":"3","key":"10.7717\/peerj-cs.3464\/ref-20","doi-asserted-by":"publisher","first-page":"1512","DOI":"10.3390\/EN16031512","article-title":"A systematic study on reinforcement learning based applications","volume":"16","author":"Sivamayil","year":"2023","journal-title":"Energies"},{"key":"10.7717\/peerj-cs.3464\/ref-21","first-page":"169","article-title":"Integrating artificial intelligence and digital tools to enhance learning and accessibility in music education","author":"Sofianos","year":"2025"},{"issue":"20","key":"10.7717\/peerj-cs.3464\/ref-22","doi-asserted-by":"publisher","first-page":"10591","DOI":"10.1007\/S00500-021-06709-X","article-title":"An intelligent deep learning-enabled recommendation algorithm for teaching music students","volume":"26","author":"Tang","year":"2022","journal-title":"Soft Computing"},{"key":"10.7717\/peerj-cs.3464\/ref-23","doi-asserted-by":"publisher","first-page":"205920432311514","DOI":"10.1177\/20592043231151416","article-title":"Practicing musical intention: the effects of external focus of attention on musicians\u2019 skill acquisition","volume":"6","author":"Williams","year":"2023","journal-title":"Music & Science"},{"issue":"3","key":"10.7717\/peerj-cs.3464\/ref-24","doi-asserted-by":"publisher","first-page":"2836","DOI":"10.1177\/14727978251322675","article-title":"The application of artificial intelligence in music education management: opportunities and challenges","volume":"25","author":"Wu","year":"2025","journal-title":"Journal of Computational Methods in Sciences and Engineering"},{"issue":"1","key":"10.7717\/peerj-cs.3464\/ref-25","doi-asserted-by":"publisher","first-page":"1535957","DOI":"10.1155\/2022\/1535957","article-title":"An improved teaching-learning-based optimization algorithm with reinforcement learning strategy for solving optimization problems","volume":"2022","author":"Wu","year":"2022","journal-title":"Computational Intelligence and Neuroscience"},{"issue":"4","key":"10.7717\/peerj-cs.3464\/ref-26","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1080\/10494820.2022.2115080","article-title":"The perspectives of teaching electroacoustic music in the digital environment in higher music education","volume":"32","author":"Yang","year":"2024","journal-title":"Interactive Learning Environments"},{"issue":"9","key":"10.7717\/peerj-cs.3464\/ref-27","doi-asserted-by":"publisher","first-page":"4773","DOI":"10.1007\/s00521-018-3849-7","article-title":"On the evaluation of generative models in music","volume":"32","author":"Yang","year":"2020","journal-title":"Neural Computing and Applications"},{"issue":"2","key":"10.7717\/peerj-cs.3464\/ref-28","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1177\/87551233231198242","article-title":"Challenges and potential of a diverse music teaching force: a review of the literature","volume":"43","author":"Yi","year":"2025","journal-title":"Update: Applications of Research in Music Education"},{"issue":"5","key":"10.7717\/peerj-cs.3464\/ref-29","doi-asserted-by":"publisher","first-page":"104764","DOI":"10.1016\/J.COMPEDU.2023.104764","article-title":"Promoting musical instrument learning in virtual reality environment: effects of embodiment and visual cues","volume":"198","author":"Yu","year":"2023","journal-title":"Computers & Education"},{"issue":"2","key":"10.7717\/peerj-cs.3464\/ref-30","doi-asserted-by":"publisher","first-page":"e0295419","DOI":"10.1371\/journal.pone.0295419","article-title":"Development strategy of early childhood music education industry: an IFS-AHP-SWOT analysis based on dynamic social network","volume":"19","author":"Yue","year":"2024","journal-title":"PLOS ONE"},{"key":"10.7717\/peerj-cs.3464\/ref-31","doi-asserted-by":"publisher","first-page":"1194","DOI":"10.1080\/10494820.2022.2115081","article-title":"Interactive systems for music composition: a new paradigm in music education","volume":"32","author":"Zhao","year":"2024","journal-title":"Interactive Learning Environments"}],"container-title":["PeerJ Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/peerj.com\/articles\/cs-3464.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/articles\/cs-3464.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/articles\/cs-3464.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/articles\/cs-3464.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T08:07:42Z","timestamp":1770106062000},"score":1,"resource":{"primary":{"URL":"https:\/\/peerj.com\/articles\/cs-3464"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,3]]},"references-count":31,"alternative-id":["10.7717\/peerj-cs.3464"],"URL":"https:\/\/doi.org\/10.7717\/peerj-cs.3464","archive":["CLOCKSS","LOCKSS","Portico"],"relation":{},"ISSN":["2376-5992"],"issn-type":[{"value":"2376-5992","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,3]]},"article-number":"e3464"}}