Logo

Audiovisual Programming

Code: 105006
Credits: 6
2026/2027
Degree programme Type Course
Audiovisual Communication OB 3

Contact lecturer

Name :
Carles Llorens Maluquer
Email :
carles.llorens@uab.cat

Teaching staff

María Victoria Mas
Patricia Mani Redondo

Group languages

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

Prerequisites

To undertake this course, it is necessary to have achieved the content and competencies of the Audiovisual Genres Theory course. In addition, a good reading comprehension of English is required.

Objectives

The course is integrated into the "Audiovisual Genres” area, which trains students in learning the narrative production routines of messages based on audiovisual genres and the analysis of scheduling strategies.

The specific objective of the course is for students to acquire theoretical and analytical knowledge about the models of audiovisual scheduling in the main broadcasting and ondemand channels, as well as the dynamics of their constant evolution. This will allow them to understand the programming strategies, the factors that condition them, and their impact on the current audiovisual industry.

Learning outcomes

  • CM10 (To programme the different modes of audiovisual programming based on the various audiovisual genres.) To programme the different modes of audiovisual programming based on the various audiovisual genres.
  • KM16 (To identify the criteria that audiovisual operators use to organise projects.) To identify the criteria that audiovisual operators use to organise projects.

Contents

The subject is articulated around the following topics:


TOPIC 1 – Introduction to audiovisual scheduling


      1.1. Definition and scope of audiovisual scheduling


      1.2. History of audiovisual scheduling


      1.3. Professional profile of the scheduler


      1.4. Audience research


TOPIC 2 – Linear programming


      2.1. Time slots and linear flow and continuity


      2.2. Models of linear television scheduling


      2.3. Models of linear radio scheduling


      2.4. Linear audience indexes


TOPIC 3 – Programming on demand


      3.1. The power of the platform (content and consumers)


      3.2. On-demand programming models


      3.3. Flow and continuity in on-demand programming (manual and algorithmic programming)


      3.4. On-demand audiences


TOPIC 4 – Scheduling genres and trends


      4.1. Scheduling genres and strategies


      4.2. Trends and diversity in scheduling


TOPIC 5 – Distribution and circulation of contents


      5.1. Exhibition windows


      5.2. Localization and circulation of content

Learning activities and methodology

Title Hours ECTS Learning outcomes
Tutorial 7.5 0.3
Realization of work 42.5 1.7
Project classes and seminars 36 1.44 CM10, KM16
Autonomous study 40 1.6
Theory classes 15 0.6 CM10, KM16

The methodology of this subject includes theoretical classes, analysis exercises and debates (seminars) and research activities on audiovisual content schedules and audiences (group project).

A detailed schedule outlining the content of each session will be presented on the first day of the course and will be available on the course’s Virtual Campus, where students will find all teaching materials deemed appropriate by the instructors and necessary information for eƯective course monitoring. Should the teaching modality change for reasons of force majeure according to the competent authorities, the teaching staƯ will inform students of any modifications to the course schedule and teaching methodologies.

The course content will be sensitive to issues related to gender perspective and the use of inclusive language.

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
Seminars 30% 3 0.12 CM10, KM16
Work in group 40% 3 0.12 CM10, KM16
Exam 30% 3 0.12 CM10, KM16

CONTINUOUS ASSESSMENT SYSTEM

The continuous assessment of the course is based on the following percentages:

A) Exam, 30% of the final grade

B) Seminars, 30% of the final grade

C) Group work (including oral presentation), 40% of the final grade

A (30%) + B (30%) + C (40%) = 100% FINAL GRADE OF THE COURSE

SINGLE-ASSESSMENT SYSTEM

The single assessment system of the course is based on the following percentages:

A) Exam, 40% of the final grade (the model and day of the exam will be different from that of continuous assessment)

B) Analysis exam, 40% of the final grade

C) Oral presentation, 20% of the final grade

A (40%) + B (40%) + C (20%) = 100% FINAL GRADE OF THE COURSE

REASSESSMENT (CONTINUOUS SYSTEM)

It is necessary to obtain a minimum grade of 5 in the three activities to pass the subject. Students will be entitled to the revaluation of the subject if they have presented a minimum of activities that equals two-thirds of the total grading. To have access to revaluation, the average grade should be 3,5 or higher. Seminars (30% of the final grade) are excluded from the revaluation process.

In the event that the student performs any irregularity that may lead to a significant variation of an evaluation act, this evaluation act will be graded with 0, regardless of the disciplinary process that could be instructed. In the event, that several irregularities occur in the evaluation acts of the same subject, the final grade for this subject will be 0.

REASSESMENT (SINGLE SYSTEM)

It is necessary to obtain a minimum grade of 5 in the three activities to pass the subject. Students will be entitled to the revaluationof the subject if they have presented a minimum of activities that equals two-thirds of the total grading. To have access to revaluation, the average grade should be 3,5 or higher. The critical reflection dissertesion (20% of the final grade) is excluded from the revaluation process.

In the event that the student performs any irregularity that may lead to a significant variation of an evaluation act, this evaluation act will be graded with 0, regardless of the disciplinary process that could be instructed. In the event, that several irregularities occur in the evaluation acts of the same subject, the final grade for this subject will be 0.


Not assessable

In this course, a student will be graded as not assessable if they do not attend or complete any of the scheduled assessment activities on the dates indicated in the course calendar, without a duly justified reason (such as illness with a medical certificate, the death of a close family member, a court summons, or other similar situations properly documented).


The performance of any irregularity in an evaluation act (academic fraud, plagiarism or improper use of AI, unless this use is expressly authorized by the teaching guide), which may lead to a significant variation in the grade, assumes that this act will be graded with a 0. In the event that the teaching guide foresees that in order to pass the subject it is an essential requirement to have obtained a minimum grade in this evaluation act or that there are several irregularities in the evaluation acts of the same subject, the final grade of this subject is 0. Apart from this, a disciplinary process may be instructed to the student that incurs any of these irregularities.


Artificial Intelligence

For this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively for quantitative audience data analysis. Students must clearly identify any parts generated with these technologies, specify the tools used, and include a critical reflection on how AI has influenced the process and final outcome of the assignment. Failure to disclose the use of AI in this assessed activity will be considered a breach of academic integrity and may result in a partial or total penalty to the assignment grade, or more serious sanctions in severe cases.


Any student suspected of submitting assignments that have been generated by AI, written by others or copied; include unattributed AI-generated content, or fall outside the permitted scope, may be asked to provide the preliminary work or other materials that can demonstrate it is original work and the result of their own authorship. They may also be asked to separately explain or justify their work. Teachers may also use AI detection systems or carry out any verification tasks they deem appropriate. If, after review, the instructor detects irregularities, the assignment may be graded zero, and the student may be subject to further disciplinary action

Bibliography

Basic References

Arana, Edorta (2011). Estrategias de programación televisiva. Síntesis 

Bonet, Montse & Sellas, Toni (2019). Del flujo al stock: El programador radiofónico ante la gestión del catálogo digital. Profesional de la información, 28(1), e280109. https://doi.org//10.3145/epi.2019.ene.09 

Bruun, Hanne (2020). Re-scheduling television in the digital era. Routledge.

Contreras, José María & Palacio, Manuel (2001). La programación en televisión. Síntesis.

Eastman, Susan & Ferguson, Douglas (2013). Media programming: strategies and practices. Berlmont: Wadsworth/Cengage Learning.

Huertas Bailén, Amparo (2015). Yo soy audiencia: ciudadanía, público y mercado. Editorial UOC. 

Izquierdo-Castillo, Jessica & Latorre-Lázaro, Teresa (2022). Oferta de contenidos de las plataformas audiovisuales. Hacia una necesaria conceptualización de la programación streaming. Profesional de la información, 31(2). https://doi.org/10.3145/epi.2022.mar.18

Martí, Josep Maria (2016). 51 maneras de hacer buena radio. Editorial UOC.

Neira, Elena, Clares-Gavilán, Judith & Sánchez Navarro, Jordi (2024). Las claves del éxito en streaming: Una aproximación teórico-práctica a la medición del impacto de los contenidos bajo demanda en las plataformas SVOD. VISUAL REVIEW: Revista Internacional de Cultura Visual, 16(Extra 3), 9. https://doi.org/10.62161/revvisual.v16.5233

 

Complementary References

Balló, Jordi & Oliva, Mercè (2024). La imagen incesante: Anatomía de los formatos audiovisuales. Llibres Anagrama.

Frey, Mattias (2021). Netflix Recommends. Algortihms, Film Choice and the History of Taste. University of California Press.

Gallego Pérez, J. Ignacio. (2010). Podcasting: Nuevos modelos de distribución y negocio para los contenidos sonoros. Editorial UOC.

Herbera, Joan, Linares, Rafael & Neira, Elena (2015). Marketing cinematográfico: cómo promocionar una película en elentorno digital. Editorial UOC.

Herrero Subías, Mónica; Medina Laverón,Mercedes & Urgellés Molina, Alicia (2018). Los sistemas de recomendación online en el mercado audiovisual español: análisis comparativo entre Atresmdedia, Movistar+, y Netflix. UCJC Business and Society Review, 15(4), 54-89. https://journals.ucjc.edu/ubr/article/view/3943

Huertas Bailén, Amparo; Cogo, Denise; Peres-Neto, Luiz; Almeida, Gabriela M.; Navarro, Celina & Camargo, Julia (2023). Ideas para abordar la comunicación inclusiva en los estudios universitarios de comunicación. Universitat Autònoma de Barcelona. Institut de la Comunicació.

Kelly, John Paul (2019). Television by the numbers: The challenges of audience measurement in the age of BigData. Convergence-the International Journal of Research into New Media Technologies, 25(1), 113-132.DOI:10.1177/1354856517700854

Martí, Josep Maria (2000). De la idea a l'antena. Tècniques de programació radiofónica. Pòrtic.

Martínez-Costa, María del Pilar & Moreno Moreno, Elsa (coords.) (2004). Programación radiofónica: arte y técnica del diálogo entre la radio y su audiencia. Servicio de Publicaciones. Universidad de Navarra.

Masanet, María José (2016). Pervivencia de los estereotipos de género en los hábitos de consumo mediático delos adolescentes: Drama para las chicas y humor para los chicos. Cuadernos.info, 39, 39-53. http://dx.doi.org/10.7764/cdi.39.1027.

Navarro, Celina & Monclús, Belén (2021). The curation of European Netflix catalogues on social media: The key role of transnational and local cultural traits. Critical Studies in Television, 16(4), 347-374. https://doi.org/10.1177/17496020211044444

Software

This course does not need specific softwares for the development of the classes.

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
(TE) Theory 4 Catalan second semester morning-mixed
(SEM) Seminars 41 Catalan second semester morning-mixed
(SEM) Seminars 42 Catalan second semester morning-mixed
(SEM) Seminars 43 Catalan second semester morning-mixed