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Musical Research in the Contemporary Urban Environment

Code: 40829
Credits: 10
2026/2027
Degree programme Type Course
Musicology, Musical Education and Interpretation of Early Music OP 1

Contact lecturer

Name :
Jaume Ayats Abeya
Email :
jaume.ayats@uab.cat

Teaching staff

Diego Alonso Tomás
Carles Badal Pérez Alarcón

Group languages

You can consult this information at the end of the document.

Prerequisites

None

Objectives

By the end of the course, students should:

  • Have a general understanding of the potential applications of technologies related to data visualization and analysis.
  • Possess basic vocabulary in the field of digital humanities and data management.
  • Be able to search, read, and summarize research findings on music from other academic disciplines.
  • Have an overview of the role of music in different areas of scientific research.
  • Be familiar with the main lines of debate in contemporary research on musical practices in urban spaces.
  • Understand the theoretical and methodological approaches of the so-called "New Musicology" and its developments in recent decades.
  • Be able to apply different musicological analysis perspectives focused on issues of gender, identity, and social class.

Learning outcomes

  1. Distinguish the distinctive characteristics of the various musical cultures of the contemporary urban environment
  2. Relate contemporary music systems with their contexts of production and reception
  3. Compare methodological procedures developed in the last three decades in the study of complex musical activity of contemporary societies, and especially in urban environments.
  4. Apply research methodologies prior to every type of music research project in the contemporary urban environment.
  5. Adapt the results of contextual analysis of the study of contemporary urban environment where different social realities involved
  6. Mastering historiographical analysis tools adapted to the study of urban music
  7. Apply critical capacity in musicological research projects and interpretive projects.
  8. Propose innovative projects proposed in musicological research and interpretive projects.
  9. Develop the capacity to assess sex and gender inequalities in order to design solutions to them.
  10. Recognise the contributions of gender studies to the topics being researched.
  11. Discuss contemporary socio-musical contexts from the perspective of gender studies.

Contents

The module is organized into three thematic blocks:


Block 1: Musicology and Digital Humanities (professor: Carles Badal)


  • History of digital humanities: where we are and where we come from


  • Basic concepts in digital humanities and data environments


  • Data formats and analysis: file types and data management


Block 2: New Musicology (professor: Diego Alonso)


  • \"New Musicology\" and its recent developments: identity, gender and social class as analytical categories in current musicological research


Block 3: Panorama of current research in music (teacher: Jaume Ayats)

· Current music in confrontation with historical documents

· Oral music and the trace of documents

· Music that is not considered "music"


Learning activities and methodology

Title Hours ECTS Learning outcomes
Work on mandatory readings 30 1.2 1, 2, 3, 4, 5, 6, 7, 8
Writing and editing critical papers on course content 60 2.4 1, 2, 3, 4, 5, 6, 7, 8
Seminars with in-class participation (in-person or virtual) 40 1.6 1, 2, 3, 4, 5, 6, 7, 8
Case studies 30 1.2 1, 2, 3, 4, 5, 6, 7, 8

This module follows a hybrid format, combining theoretical lectures delivered by the instructor and in-class collaborative work on practical case studies. These sessions will deepen the understanding of theoretical aspects and key concepts from the syllabus.

This seminar-style approach and learning methodology actively engage students. Course content will be acquired primarily through:

  • Reading and discussing selected texts.

  • Analyzing and debating proposed audiovisual materials.

Active participation requires personal commitment to prepare assigned readings and viewings beforehand to contribute meaningfully to in-class discussions.

As a postgraduate courseindependent work plays a significant role in the methodology. Tasks will be completed both individually and in collaborative groups. Students will also participate in peer assessment of materials generated during seminars.

The module has a dedicated Moodle classroom, where the activity schedule and teaching materials will be published.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Assessment 1.2 (papers, presentations, and/or exams) 30% 25 1 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Assessment 3.1 (papers, presentations, and/or exams) 20% 20 0.8 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Assessment 2.1 (papers, presentations, and/or exams) 20% 20 0.8 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Assessment 1.1 (papers, presentations, and/or exams) 30% 25 1 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11

Each instructor may assess students through one or more assessment activities (paper, presentation, or exam), which will be specified at the beginning of the course. The overall grade for each block (Participation + Assessments) will contribute to the final grade in the same proportion as the percentage of teaching sessions devoted to that block.

  • Musicology and Digital Humanities (30% + 30%)
  • Music Research in the Natural and Social Sciences (20%)
  • New Musicology: Gender Identities and Social Class (20%)

At the time of each assessment activity, the instructor will inform students (via Moodle) of the assessment procedure and the date for reviewing grades.

If the assessments cannot be conducted in person, their format will be adapted (while maintaining the same weighting) to the possibilities offered by the UAB's virtual learning tools. Assignments, activities, and class participation will take place through forums, wikis, and/or exercise discussions via Teams, etc. The instructor will ensure that students can access these resources or will provide alternative means within their possibilities.

Submission of one of the assignments or attendance at one of the written examinations will count as an "in-person" assessment activity for the course. Therefore, only students who have not completed any assessment activity during the course may be classified as "Not Assessed."

If a student does not achieve the minimum passing grade (5/10), they may take the resit assessment for all four assessment items by resubmitting the assignment, repeating the presentation, or retaking the examination on the date and at the time established by the Faculty.

For this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively for support tasks, such as bibliographic or information searches, text proofreading, translations, and other similar uses expressly authorized by the teaching staff. In any written assignment, students must clearly identify which parts were prepared with the assistance of AI and specify the tools used. A lack of transparency regarding the use of AI in an assessed activity will be considered a breach of academic integrity and may result in a partial or total penalty in the grade for that activity.

If a student commits any irregularity that may lead to a significant alteration of the grade for an assessment activity, that assessment activity will be graded 0, regardless of any disciplinary proceedings that may be initiated. If multiple irregularities occur in the assessment activities of the same course, the final grade for the course will be 0.

SINGLE ASSESSMENT:

  • For the single assessment, four pieces of evidence will be considered: two for the first block and one for each of the other two blocks, drawn from at least two different assessment formats (paper, presentation, or examination).
  • Each instructor will specify the characteristics of the assessment evidence corresponding to their block at the beginning of the course.
  • The weight of each of the four assessment items in the final grade will be 30%, 30%, 20%, and 20%, respectively.
  • The same resit assessment system as for continuous assessment will apply.

Bibliography

Beard, David and Gloag, Kenneth (ed.). Musicology: The Key Concepts. New York and London: Routledge, 2005.

Burdick, Anne; Drucker, Johanna; Lunenfeld, Peter; Presner, Todd ; Schnapp, Jeffrey. Digital_humanities. Cambridge, MA: MIT Press, 2012. (https://archive.org/details/DigitalHumanities_201701)

D'Angelo, Robin. Fragilidad blanca. Ediciones del Oriente y del Mediterráneo, 2021.

Manchado, Marisa (ed.). Música y mujeres: Género y poder. Ménades Editorial, 2019.

Marín, Miguel Angel. “Challenging the Listener: How to Change Trends in Classical Music Programming”. Resonancias, vol. 22, n° 42, 115-130, 2018. (https://investigacion.unirioja.es/documentos/5cf121312999525b985d0461)

Mikutta, C.A.; G. Maissen, A. Altorfer W. Strik i T. Koenig. “Professional musicians listen differently to music”. Neuroscience. 268, 102-111, 2014. (https://www.ibroneuroscience.org/article/S0306-4522(14)00213-9/abstract)

Müllensiefen, D.; B. Gingras, J. Musil i L. Stewart. “The Musicality of Non-Musicians: An Index for Assessing Musical Sophistication in the General Population.” PLoS ONE 9(2), 2014.  (https://doi.org/10.1371/journal.pone.0089642)

National Endowment for the Arts. Officeof Research and Analysis. Why we Engage: Attending, Creating, and Performing Art. Sept 2020. (https://www.arts.gov/sites/default/files/Why-We-Engage-0920_0.pdf)

Ramos, Pilar. Feminismo y música: Introducción crítica. Narcea Ediciones, 2003.

Sloboda, J. i O’Neill, S. “Emotions in everyday listening to music”. In: Music and emotion: Theory and researched, ed. per J. Sloboda i P.N Juslin. Oxford: Oxford University Press, 2001. 415-429.

Williamon, A.; J. Ginsborg, R. Perkins, i G. Waddell. Performing Music Research: Methods in Music Education, Psychology, and Performance Science. Oxford: Oxford University Press, 2021.

Software

LIBRE OFFICE
Free and open-source office software will be used, specifically the Base (relational database manager) and Calc (spreadsheet) applications.
https://es.libreoffice.org/descarga/libreoffice/

GEPHI
Free and open-source software for graph and network visualization.
https://gephi.org/

VOYANT
Free and open-source software for text analysis and visualization.
https://voyant-tools.org/

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TEm) Theory (master) 1 Catalan/Spanish first semester afternoon