{
  "abstract": "This study examined the role of digital platforms and artificial intelligence in music theory instruction from the perspectives of both students and instructors. Using a convergent mixed-methods design, data were collected through questionnaires administered to 47 undergraduate students and 9 instructors. Quantitative responses were analyzed descriptively, while open-ended responses were examined through inductive thematic analysis. The findings indicated that students associated these tools with increased engagement, perceived support for understanding complex theoretical concepts, and individualized learning opportunities. Written responses further suggested that flexible access and visual representations were particularly valuable in facilitating comprehension. Instructors, however, emphasized the importance of clear content, accurate information, and an awareness of practical limitations in classroom implementation. Although both groups acknowledged the potential of these technologies, their reasons for valuing them differed. Overall, the findings suggest that digital and AI-based tools may be particularly valuable when they are meaningfully integrated into everyday teaching practice, rather than being used as stand-alone additions. Their perceived educational value appears to depend not only on technical sophistication but also on alignment with instructional goals. Teacher readiness also appeared to be an important consideration in the effective integration of these tools. As automation assumes an increasingly prominent role in education, adapting resources to diverse learning needs appears to be of growing importance.",
  "abstract_shown": true,
  "affiliations": [
    "Ankara Music and Fine Arts University, Ankara, Türkiye"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ali Kalkan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4cxe7y6y5cgm1.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0352494",
  "fulltext_url": null,
  "id": "4cxe7y6y5cgm1",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0352494",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3304|Music Education and Analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Learning/Human learning"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Music cognition/Music perception"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Perception/Sensory perception/Music perception"
    ],
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      "plos",
      "/Biology and life sciences/Neuroscience/Learning and memory/Learning/Human learning"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Sensory perception/Music perception"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Cognitive psychology/Learning/Human learning"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Cognitive psychology/Music cognition/Music perception"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Cognitive psychology/Perception/Sensory perception/Music perception"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Psychometrics"
    ],
    [
      "plos",
      "/Computer and information sciences/Artificial intelligence"
    ],
    [
      "plos",
      "/Computer and information sciences/Artificial intelligence/Machine learning"
    ],
    [
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      "/People and places/Population groupings/Professions/Instructors"
    ],
    [
      "plos",
      "/People and places/Population groupings/Professions/Teachers"
    ],
    [
      "plos",
      "/Research and analysis methods/Research design/Survey research/Questionnaires"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Cognitive psychology/Learning/Human learning"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Cognitive psychology/Music cognition/Music perception"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Cognitive psychology/Perception/Sensory perception/Music perception"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Psychometrics"
    ]
  ],
  "openalex": "W7225390225",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-06",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/4cxe7y6y5cgm1.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T12:20:24Z",
      "native_id": "10.1371/journal.pone.0352494",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0352494"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "The role of digital and AI-based tools in music theory education",
  "title_text": "The role of digital and AI-based tools in music theory education",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T12:20:48Z",
  "url": "https://research.draconitic.com/paper/4cxe7y6y5cgm1",
  "venue": "PLOS One",
  "versions": []
}