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Digital Resources for Anthropological Research

Code: 107232
Credits: 6
2026/2027
Degree programme Type Course
Social and Cultural Anthropology FB 1

Contact lecturer

Name :
Miranda Jessica Lubbers
Email :
mirandajessica.lubbers@uab.cat

Teaching staff

Marc Alcalà i Rams

Group languages

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

Prerequisites

No preconditions.

Objectives

In this hands-on course, you will learn how anthropological research is organized today, what role digital resources play in this workflow, and how to use them effectively during the research cycle. You will experiment with the tools that will facilitate the whole research process, from searching and managing the literature to conducting collaborative fieldwork, observing digital spaces, transcribing interviews (using tools that make it easier), organizing data, and communicating the results.


What you will learn to do:

  • Understand the process of anthropological research: how data are collected, managed, and analysed in anthropological research (both qualitative and quantitative), including real ethical decisions.
  • Use key tools in the field: academic search engines, reference managers, fieldwork tools, transcription software, spreadsheets, advanced functions in Word/Google Docs, and other specialised resources.
  • Design your own workflow: collect data, organise them, analyse them, and store them efficiently and responsibly.
  • Turn data into results: format your writing and visualisations, prepare presentations, and explore audiovisual formats.


Learning outcomes

  • CM05 (Use academic communication strategies appropriately in the transmission of information in the anthropological field.) Use academic communication strategies appropriately in the transmission of information in the anthropological field.
  • CM06 (Produce academic and professional documents in the field of anthropology using a variety of methods and techniques of analysis and representation.) Produce academic and professional documents in the field of anthropology using a variety of methods and techniques of analysis and representation.
  • KM06 (Recognise the use of applications related to quantitative and qualitative techniques for obtaining and processing data in anthropology.) Recognise the use of applications related to quantitative and qualitative techniques for obtaining and processing data in anthropology.
  • SM08 (Use applications related to the collection and organisation of data.) Use applications related to the collection and organisation of data.
  • SM09 (Recognise the basic ethical dimensions of research in anthropology.) Recognise the basic ethical dimensions of research in anthropology.

Contents

Topic 1. Introduction: How to conduct research in anthropology and manage information

Topic 2. Doing research responsibly: Ethics in anthropological practice

Topic 3. Navigating academic sources: Finding, selecting, and organizing scientific articles, books, and contextual data

Topic 4. From field to data: How to collect, analyze, and interpret information

Topic 5. Communicating what you have discovered: Writing, visualization, and presentation of results

Topic 6. Artificial intelligence in anthropology: Uses and risks

Topic 7. Expanding your toolkit: Other digital tools and research possibilities

Learning activities and methodology

Title Hours ECTS Learning outcomes
Laboratory practices 33 1.32
Submission of works 40 1.6
Readings and research 50 2
Theoretical sessions 17 0.68

This course combines theoretical sessions with hands-on practical laboratory work.


Theoretical classes. These sessions introduce the tools, how they work, and their purposes, supported by examples and discussion with participants. Classes typically begin with an introduction by the teaching staff, followed by discussion, questions, and shared reflections. Readings will be suggested throughout the course, depending on emerging interests in class. Summaries, materials, and relevant links will be made available on the Virtual Campus as the course progresses. In some sessions, short in-class activities (in pairs or small groups, as indicated by the lecturer) will be included to facilitate immediate application of concepts. These activities will be collected at the end of the class and will form part of the continuous assessment.


Laboratory sessions. During these two-hour sessions, students will carry out a software-based activity related to the topic of the class (individually, in pairs, or in small groups, as indicated by the instructor). They will have the support of the instructor and an instruction guide available on the Campus Virtual, enabling them to progress independently and at their own pace. The instructor will present the activity to the entire group and address any questions that may arise. The results of these activities must be submitted via the Virtual Campus either at the end of the session or, at the latest, within one week of the practical session. These activities may take various forms depending on the content covered (e.g., exercises, viewings, analyses) and may be submitted in Catalan, Spanish, or English. The final practical sessions will be dedicated to preparing a group project that incorporates various resources and tools covered during the course.


The dates of the theoretical and laboratory sessions are provided in the course calendar from the first day. The teaching staff will make every effort to adhere to the established schedule; however, students should be aware that minor changes may occur (e.g., due to illness or strikes). Any changes will be communicated via the Virtual Campus. It is the student’s responsibility to stay informed about any updates.

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
Delivery of practices 01-03 (6.67% each) 20% 2 0.08 CM05, CM06, KM06, SM08, SM09
Submission of the final work 20% 4 0.16 CM05, CM06, KM06, SM08, SM09
Active participation 20% 0 0 KM06, SM09
Delivery of practices 07-09 (6.67% each) 20% 2 0.08 CM05, CM06, KM06, SM08, SM09
Delivery of practices 04-06 (6.67% each) 20% 2 0.08 CM05, CM06, KM06, SM08, SM09

Assessment of the course is based on continuous evaluation through the following activities:


1. Participation (20%):

Active participation in lectures, discussions, classroom activities, and laboratory sessions. In each session (theoretical or practical), students will receive a score of 0 or 1 based on their participation. At the end of the course, the total number of points obtained will be divided by the total number of assessed sessions, and the resulting score will be converted to a 0–2 scale (equivalent to 20% of the final grade). This partial assessment activity is not recoverable at a later date or time.


2. Quality of laboratory assignments (9 assignments, each worth 6.67% of the final grade; in total 60%)

Nine laboratory assignments will be completed throughout the course. During these sessions, students will carry out exercises related to the topic of the class using different software programs, either individually, in pairs, or in small groups, as instructed by the lecturer.

The results of each assignment must be submitted in Catalan, Spanish, or English through the Virtual Campus on the same day of the laboratory or within one week of completing the activity (using the "Assignment Submission" option on the Virtual Campus). The submitted file must include the student's NIU number, surname(s), and first name, and must be uploaded as a PDF file (or in the format generated by the software used).

Late submissions will not be accepted. Students are advised not to submit their work shortly before the deadline. The teaching staff cannot be held responsible for technical issues affecting students' own devices or internet connections. However, if the Virtual Campus itself becomes unavailable during the submission period, the deadline will be extended by one day.

Grades will normally be posted on the Virtual Campus approximately one week after the submission deadline. Each assignment will be graded on a scale from 0 to 3 points. The laboratory assignment grade will be calculated as the average of the nine grades and subsequently converted to a 0–6 scale (equivalent to 60% of the final grade).


3. Quality of the final project (20%). The final laboratory sessions will be devoted to the preparation of a group project using several of the tools and methods covered during the course. Students will present their results in the form of a written text, poster, or video, following guidelines that will be made available on the Virtual Campus. The final work has to be submitted via the Campus Virtual within a week after the last laboratory session.The project grade accounts for 20% of the final grade.


Reexamination: At the time each assessment activity is assigned, the teaching staff will inform students, through the Virtual Campus, of the procedure and date for reviewing grades. At the end of the course, a resit opportunity will be offered for assignments that were not submitted for justified reasons (supported by appropriate documentation) and for assignments that were submitted but not passed. Valid grounds are work-related, family-related, or medical reasons. To be eligible for the resit, students must have been assessed in activities accounting for at least two-thirds of the final course grade. In practice, this means having participated in most of the assessed activities throughout the course. The resit will consist of redoing the relevant assignment(s), although the exercises and/or materials used will differ from the original ones. Final grades will be published through Sigma, and a grade review session will be scheduled.


Students experiencing long-term health problems or other unforeseen circumstances that regularly interfere with the completion of assignments should contact the lecturer and provide supporting documentation so that alternative arrangements can be considered.


General criteria:

In accordance with UAB assessment regulations, final grades will be awarded on a 0–10 scale with one decimal place. To pass the course, students must obtain a minimum average final grade of 5.0. Students who submit 30% or fewer of the assessment activities will receive the grade "Not Assessed" (No Evaluable).


In the event of any academic misconduct (copying, plagiarism, etc.) that may significantly affect the grade awarded for an assessment activity, that activity will be graded 0, regardless of any disciplinary procedures that may also be initiated. If multiple instances of misconduct occur within the same course, the final course grade will be 0. Copying is defined as work that reproduces all or part of another student's work. Plagiarism is defined as presenting all or part of another author's text as one's own without properly citing the source, whether in print or digital format.


The use of Artificial Intelligence (AI) technologies is not permitted in any assessed activity unless explicitly stated otherwise in the instructions for a specific assignment. Any work containing AI-generated content without explicit authorization will be considered a breach of academic integrity and will receive a grade of 0 for that assessment, without the possibility of resubmission or resit. More serious cases may result in additional disciplinary sanctions.

Bibliography

Recommended literature:


Paulus, Trena M, & Lester, Jessica N. (2021). Doing Qualitative Research in a Digital World. London: Sage.


Complementary literature (only for those interested in reading more):


Ardèvol, Elisenda, & Lanzeni, Débora (2014). Visualidades y Materialidades de lo Digital: Caminos la Antropología. Anthropologica, 33, 11-38. PDF: http://www.scielo.org.pe/pdf/anthro/v32n33/a02v32n33.pdf. Exemple: Ardèvol, Elisenda, Martorell Fernández, Sandra, & San Cornelio, Gemma (2021). El Mito en las Narrativas Visuales del Activismo Medioambiental en Instagram. Comunicar: Revista Científica Iberoamericana de Comunicación y Educación, 68(29), 5970. https://doi.org/10.3916/C68-2021-05 Exemple, pàgina web: La web "Algorithmic Forberg, https://spark.adobe.com/page/cRH1UENjuWLAS/


Burgess-Allen, Jilla, & Owen-Smith, Vicci (2010). Using Mind Mapping Techniques for Rapid Qualitative Data Analysis in Public Participation Processes. Health Expectations: An International Journal of Public Participation in Health Care and Health Policy, 13(4), 406415. https://doi.org/10.1111/j.1369-7625.2010.00594.x


Chilisa, Bagele (2020). Indigenous Research Methodologies. 2a edició. Sage. Disponible a la Biblioteca de Ciències Socials de la UAB.


Ivey, Camille, & Crum, Janet (2018). Choosing the Right Citation Management Tool: EndNote, Mendeley, RefWorks, or Zotero. Journal of the Medical Library Association, 106(3), 399-403. https://doi.org/10.5195/jmla.2018.468


Jayasinghe, Namalie, Parvez Butt, Anam, & Zaaroura, Mayssam (2019). Integración del Género a la Planificación de las Investigaciones. Oxfam. https://oxfamilibrary.openrepository.com/bitstream/handle/105 46/620621/gd-integrating-gender-research-planning-210219-es.pdf?sequence=4


Marçal, Heura, Kelso, Fiona, & Nogués, Mercè (2011). Guia per a l’Ús No Sexista del Llenguatge a la Universitat Autònoma de Barcelona (2ª edició). Servei de Llengües i Observatori per a la Igualtat, Barcelona. https://www.uab.cat/doc/llenguatge Universitat Autònoma de Barcelona.


Martini, Natalia (2020). Using GPS and GIS to Enrich the Walk-along Method. Field Methods, 32(2), 180-192. https://doi.org/10.1177/1525822X20905257


McLellan, Eleanor, MacQueen, Kathleen M., & Neidig, Judith L. (2003). Beyond the Qualitative Interview: Data Preparation and Transcription. Field Methods, 15(1), 6386. https://doi.org/10.1177/1525822X02239573


Ose, Solveig O. (2016). Using Excel and Word to Structure Qualitative Data. Journal of Applied Social Science, 10(2), 147-162. https://doi.org/10.1177/1936724416664948


Pelckmans, Lotte (2009). Phoning Anthropologists: The Mobile Phone’s Reshaping of Anthropological Research. En: Mirjam de Bruijn, Francis Nyamnjoh, & Inge Brinkman (Eds), Mobile Phones: The New Talking Drums of Everyday Africa. LANGAA: RCPIG. Preprint de l'autora: https://www.researchgate.net/publication/287010384_Phoning_anthropologists _The_mobile_phone%27s_re-shaping_of_anthropological_research


Zuberi, Tukufu, & Bonilla-Silva, Eduardo (2008). White Logic, White Methods: Racism and Methodology. Plymouth, UK: Rowman and Littlefield. Disponible en línia a la Biblioteca de la UAB.


Web resources:


Pàgina web “Digital Anthropology Resources” Emery: https://meyersemery.com/digital-resources/da/ de Kate Meyers Canal de youtube "Breaking Methods seminars" (hosted by the Vitalities Lab, UNSW Sydney and the Australian Research Council Centre for Automated Decision-Making Society: https://www.youtube.com/channel/UCu1q-2O2HIHLTUEZswtXXbA/videos (pots activar els subtítols i en configuració, traduir automàticament a català)


L'ètica: American Association of Anthropology (adopted in 1971, amended in 1986). Principles of Professional Responsibility http://ethics.americananthro.org/category/statement/?_ga=2.219532826.2060411335.1 688333955973224217.1688333955&_gl=1*10nhhoq*_ga*OTczMjI0MjE3LjE2ODgzMzM5NTU.*_ga_ NHV0Y97DC9*MTY4ODMzMzk1NC4xLjEuMTY4ODMzMzk3OC4zNi4wLjA. Codi d'ètica de l'Associació d'Antropòlegs Socials del Regne Unit i la Mancomunitat de Nacions (ASA): https://www.theasa.org/downloads/ASA%20ethics%20guidelines%202011 .pdf Recurs educatiu sobre l'ètica, University): https://ethicstraining.mq.edu.au/ d'accés obert (Macquarie Pàgina web del Comité d'Ètica en la Recerca de la UAB (CERec, amb models de consentiment informat, etc.): https://www.uab.cat/etica-recerca/



Software

UAB students can download Microsoft Office 365 for free onto their laptops or computers if they wish: https://si-respostes.uab.cat/inici/programari/obtencio-de-programari.


The other programs and digital resources that will be used in the course will be established in the first class, as they are selected based on criteria of development, quality, usability, and open access/licensing availability of the software available for each task at that time. All software is installed in the computer lab or can be installed or accessed during class.

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 1 Spanish second semester morning-mixed
(PLAB) Practical laboratories 11 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 12 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 13 Catalan/Spanish second semester morning-mixed