This version of the course guide is provisional until the period for editing the new course guides ends.

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Research, Training and Digital Technologies

Code: 45005 ECTS Credits: 6
2025/2026
Degree Type Year
Research in Education OP 1

Contact

Name:
Oscar Mas Torello
Email:
oscar.mas@uab.cat

Teachers

Cristina Mercader Juan

Teaching groups languages

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


Prerequisites

No requeriments. 


Objectives and Contextualisation

This module aims to introduce students to research in the field of education/training and educational technology:

  • Reflect on the concepts of educational technology and digital technologies in service of learning and knowledge, as well as their educational impact.
  • Provide an overview of different research approaches related to educational technology.
  • Analyse and design research projects that address issues related to digital technologies in various educational contexts.

Learning Outcomes

  1. CA17 (Competence) Formulate a research problem related to digital training and technologies and formulate its questions and goals.
  2. CA18 (Competence) Adopt criteria of methodological quality in research on digital training and technologies.
  3. CA19 (Competence) Make proposals for improvement and/or innovation projects grounded on research-based evidence on digital training and technologies.
  4. KA16 (Knowledge) Describe the methodological paradigms, approaches and designs in research on digital training and technologies.
  5. KA17 (Knowledge) Identify different lines of research in digital training and technologies.
  6. KA18 (Knowledge) Identify problems and respond to educational needs in relation to digital training and technologies using innovative approaches.
  7. KA19 (Knowledge) Recognise the ethical principles of research when conducing studies on digital training and technologies.
  8. SA11 (Skill) Produce a comprehensive review of the scientific literature in relation to digital training and technologies.

Content

1. Information and Communication Technologies as Learning and Knowledge Technologies: Different Meanings According to the Vision of Educational Technology. From Technological Vision to Critique. Implications for Research.

2. Lines of Research in Digital Technologies Related to Education:

3. Organizational Implications of Educational Technology.

4. Face-to-Face, Blended, and Distance Learning.

5. Methodological Strategies and Digital Technologies.

6. Pedagogical Competencies and Digital Teaching Competence.

7. Policies and Practices in the Integration of Digital Technologies in Education. Digital Resources as Interactive, Hypertextual, and Multimedia. Generative Artificial Intelligence in Educational Contexts.

8. Creating Digital Materials for Research Dissemination: Collaboration, Participation, Research Ethics, and Data Ethics.


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Debates on readings-exhibitions / Workshops-classroom exercises / Presentation of works 20 0.8
Master classes 16 0.64
Type: Supervised      
activities in different formats and modalities 12 0.48
Memory 12 0.48
Tutoring 12 0.48
Type: Autonomous      
It refers to all activities related to personal study, readings, case analysis, realization of exercises, search for information, preparation of portfolios ... 64.5 2.58

 The training activity will be developed according to the following dynamics:

1.Article discussion and master classes / expositions by the teaching staff

2. Reading of articles and documentary sources

3. Analysis and collective discussion of articles and documentary sources

4. Classroom practices: problem solving and/or cases and/or exercises-activities-infographics and review of research (reviews, comparisons, etc.)  

5. Presentation / oral presentation of works

6. Tutorials

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

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Short classroom activities (individual/peers/small group). Attendance and participation 15% 2.25 0.09 CA19, KA16, KA17, KA18, KA19
WORK 1: Critical reviews of articles and presentations with graphic support. Attendance, discussion, and active participation. (Individual) 35% 5.25 0.21 KA16, KA17, KA18, KA19, SA11
WORK 2: Individual in-person test/critical reviews of articles and presentation with graphic support to be determined (individual). 50% 6 0.24 CA17, CA18, CA19, KA16, KA17, KA18, KA19, SA11

CONTINUOUS ASSESSMENT


The module will be assessed through the following activities:

• Assignment 1: Individual critical reviews of articles and a presentation with graphic support to be determined. Due approximately in the second week of April.
• Assignment 2: Individual in-person exam/critical reviews of articles and a presentation with graphic support to be determined. Due/completed during the month of May.
• Classroom activities/exercises.

The final grade will be the weighted average of the planned activities. To apply this criterion, the following must be achieved:

  • Obtain at least a 5 in the two required assignments,
  • Complete at least 80% of the classroom activities/exercises with sufficient quality and commitment.
  • Proof of 80% attendance.

If these criteria are not met, the course will be considered "Not Assessable."
For failed assignments (grades 1 and 2) (more than 3.5), there will be the option to make up the assignments by submitting a new, improved assignment based on the instructor's instructions.
Due to their nature, exercises/activities completed in class cannot be made up.
Late submissions, corrections, improvements, resubmissions, make-ups, etc., will be marked with a maximum of 6.5. Make-up assignments must be submitted no later than two weeks after receiving the correction/feedback, and the final assignment must be submitted by June 20th.
All assignments (individual and group) will be considered for linguistic accuracy, writing, and formal presentation. Students must be able to express themselves fluently and accurately and demonstrate a high level of understanding of academic texts. An assignment may be returned (not graded) or failed if the instructor deems it does not meet these requirements. To pass this subject, students must demonstrate good general communicative competence, both orally and in writing, and a good command of the language(s) used.
Class attendance is mandatory. To obtain a positive final evaluation, students must have attended at least 80% of the classes.
Feedback and return of tests and assessment activities will be provided within a maximum of 20 business days.
The review process for exams/assignments will be carried out individually and in person.
Cheating and plagiarism are intellectual theft and, therefore, constitute a crime punishable by a zero for the entire block in which the work is located. In the case of cheating between two students, if it is not possible to determine who copied from whom, the penalty will be applied to both students. We would like to remind you that "cheating" is considered to be any work that reproduces all or a large part of the work of another classmate. "Plagiarism" is the act of presenting all or part of an author's text as one's own, that is, without citing the sources, whether published in print or digitally on the Internet (see UAB documentation on plagiarism at: http://wuster.uab.es/web_argumenta_obert/unit_20/sot_2_01.html).
For this subject, the use of Artificial Intelligence (AI) technologies is permitted exclusively for translation tasks and for spelling, syntax, and grammar correction of texts, and also for those tasks specifically indicated by the faculty. Students must clearly identify which parts and what work has been done with these applications and how it has influenced the process and the final result of the assigned activity, task, etc. Lack of transparency in the use of AI in activities, assignments, etc. will be considered academic dishonesty and will result in the failure of said activity with the resulting evaluative implications. In all cases, an "alternative" in-person retake will be carried out.

 

SINGLE ASSESSMENT


Students who opt for the single assessment have the same attendance requirements as their peers taking the continuous assessment. They must create a learning folder/portfolio (digital and/or paper format, to be determined by the faculty) with the following content

• Standard cover page of the master's degree
• Comprehensive index
• All activities proposed to the group in the classroom, Moodle, etc., including a summary of the final reflection completed as a group (or individually if this has not been completed).
• Assignment 1: Individual critical reviews of articles and multimedia presentation with graphic support to be determined.
• Assignment 2: Individual in-person exam/critical reviews of articles and multimedia presentation with graphic support to be determined.

The learning folder/portfolio with all the evidence will be delivered on the day established for students enrolled in continuous assessment: the individual in-person test and/or the submission of critical reviews of articles and a presentation with graphic support to be determined.

For the remaining elements (minimum criteria for being assessed or considered "not assessable," attendance, weighting of work in the final grade, language proficiency and comprehension of academic texts, use of AI, remediation/revision, consideration of plagiarism/copying, etc.), the same criteria will apply as for students participating in continuous assessment.

 

ASSESSMENT with FINAL SUMMARY EXAM This course does not consider this option.

 


Bibliography

Adell, J. (2018). Más allá del instrumentalismo en tecnología educativa. En J. Gimeno (Ed.). Cambiar los contenidos, cambiar la educación (pp.117-128). Morata.

Area, M. & Adell, J. (2021). Tecnologías Digitales y Cambio Educativo. Una Aproximación Crítica. REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 19 (4), 83-96. https://doi.org/10.15366/reice2021.19.4.005

Arroyo, A. (Coord) (2024). Inteligencia artificial y educación: construyendo puentes. Graó.

Azorín, C. & Muijs, D. (2017). Networks and collaboration in Spanish education policy. Educational Research59 (3), 273-296. https://doi.org/10.1080/00131881.2017.1341817

Bauman, Z. (2002). Modernidad liquida. Fondo de Cultura Económica de España.

Cabero, J.; Barrosa, J. & Llorente, C. (2019). La realidad aumentada en la enseñanza universitaria. REDU. Revista de docencia universitaria, 17 (1), 105-118. https://doi.org/10.4995/redu.2019.11256

Castañeda, L., Salinas, J. & Adell, J. (2020). Hacia una visión contemporánea de la Tecnología Educativa. Digital Education Review, 37, 240-268. https://doi.org/10.1344/der.2020.37.240-268

Fernández-Enguita, M. (2023). Competencia digital docente para la transformación educativa. OEI.  https://oei.int/oficinas/secretaria-general/publicaciones/competencia-digital-docente-para-la-transformacion-educativa/

Mas, O. & Pozos, K.V. (2012). Las competencias pedagógicas y digitales del docente universitario. Un elemento nuclear en la calidad docente institucional. Revista del Congrés Internacional de Docència Universitàriai Innovació, 1, 1-21. https://raco.cat/index.php/RevistaCIDUI/issue/view/28684

Mas, O. & Tejada, J. (2013). Funciones y competencias de la docencia universitaria. Síntesis.

OEI (2022). Informe Diagnóstico de necesidades formativas en la educación técnica profesional sobre competencias digitales en los países de Alianza Pacífico. OEI. https://oei.int/wp-content/uploads/2022/12/informe-etp-necesidades-formativas-interactivo-1.pdf

OECD (2013). Educational Research and Innovation. Leadership for 21st Century Learning. OECD publishing. http://dx.doi.org/10.1787/9789264205406-en

 


Software

Moodle

Google Drive

Mentimeter

Gennially 

Etc...


Groups and Languages

Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.

Name Group Language Semester Turn
(TEm) Theory (master) 1 Spanish second semester afternoon