Important notice
The course guide is provisional.
The PDF version of the course guide may take a few days to become available in the DDD.

Research, Training and Digital Technologies
Code: 45005Credits: 6
| Degree programme | Type | Course |
|---|---|---|
| Research in Education | OP | 1 |
Contact lecturer
- Name :
- Oscar Mas Torello
- Email :
- oscar.mas@uab.cat
Teaching staff
- Cristina Mercader Juan
Group languages
You can consult this information at the end of the document.
Prerequisites
No requeriments.
Objectives
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
- CA17 (Formulate a research problem related to digital training and technologies and formulate its questions and goals.) Formulate a research problem related to digital training and technologies and formulate its questions and goals.
- CA18 (Adopt criteria of methodological quality in research on digital training and technologies.) Adopt criteria of methodological quality in research on digital training and technologies.
- CA19 (Make proposals for improvement and/or innovation projects grounded on research-based evidence on digital training and technologies.) Make proposals for improvement and/or innovation projects grounded on research-based evidence on digital training and technologies.
- KA16 (Describe the methodological paradigms, approaches and designs in research on digital training and technologies.) Describe the methodological paradigms, approaches and designs in research on digital training and technologies.
- KA17 (Identify different lines of research in digital training and technologies.) Identify different lines of research in digital training and technologies.
- KA18 (Identify problems and respond to educational needs in relation to digital training and technologies using innovative approaches.) Identify problems and respond to educational needs in relation to digital training and technologies using innovative approaches.
- KA19 (Recognise the ethical principles of research when conducing studies on digital training and technologies.) Recognise the ethical principles of research when conducing studies on digital training and technologies.
- SA11 (Produce a comprehensive review of the scientific literature in relation to digital training and technologies.) Produce a comprehensive review of the scientific literature in relation to digital training and technologies.
Contents
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.
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Debates on readings-exhibitions / Workshops-classroom exercises / Presentation of works | 20 | 0.8 | |
| It refers to all activities related to personal study, readings, case analysis, realization of exercises, search for information, preparation of portfolios ... | 78 | 3.12 | |
| Master classes | 16 | 0.64 | |
| Tutoring | 12 | 0.48 | |
| Memories (1 and 2), activities in different formats and modalities | 24 | 0.96 |
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
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| WORK 2 (individual): in person test / critical reviews of a set of articles, complemented with graphic supports to be determined and a presentation to the class group. | 50% | 0 | 0 | CA17, CA18, CA19, KA16, KA17, KA18, KA19, SA11 |
| Short classroom activities (individual/peers/small group). Attendance and participation | 15% | 0 | 0 | CA19, KA16, KA17, KA18, KA19 |
| WORK 1(individual): critical review of a set of articles and co assessment of a classmate’s set of critical reviews, complemented with graphic supports to be determined and a presentation to the class group. | 35% | 0 | 0 | KA16, KA17, KA18, KA19, SA11 |
CONTINUOUS ASSESSMENT
The module will be assessed through the following activities:
• Assignment 1 (individual): critical review of a set of articles and co‑assessment of a classmate’s set of critical reviews, complemented with graphic supports to be determined and a presentation to the class group. Due approximately in the second week of April.
•Assignment 2 (individual): in‑person test / critical reviews of a set of articles, complemented with graphic supports to be determined and a presentation to the class group. Due/completed during the month of May.
• Class activities / exercises (individual/peers/small group) carried out in the classroom, attendance, and participation.
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.\"
To be eligible to participate in the resit assessment, students must have been previously evaluated in a set of activities whose weight corresponds to at least two-thirds of the total grade for the course.
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.
Copying or plagiarism in any type of assessment activity constitute a serious offence and will be penalised with a grade of 0 for the course, with no possibility of resitting, whether it is an individual or group assignment (in the latter case, all group members will receive a 0). If, during an in‑class exam or individual assignment, the instructor considers that a student is attempting to cheat, or if the student is found with any document or device not authorised by the teaching staff, the activity will be graded with a 0, with no option for resit, and the student will therefore fail the course. An assignment, activity, or exam will be considered “copied” when it reproduces all or a significant part of another student’s work. An assignment or activity will be considered “plagiarised” when a portion of an author’s text is presented as one’s own without citing the sources, regardless of whether the original sources are in print or digital format.
For this course, the use of Artificial Intelligence (AI) technologies is permitted in a restricted manner and only for assignments in which the teaching staff explicitly indicates so. The student must clearly identify which parts have been generated using such technology, specify the tools employed, and include a critical reflection on how these tools have influenced both the process and the final outcome of the activity. Unauthorized use or lack of transparency regarding the use of AI in any activity will be considered a breach of academic integrity and may result in failure of the assignment or more severe sanctions in cases of greater seriousness.
.
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 review of a set of articles and self-co‑assessment of a classmate’s set of critical reviews, complemented with graphic supports to be determined and multimedia presentation
• Assignment 2 (individual): in‑person test / critical reviews of a set of articles, complemented with graphic supports to be determined and multimedia presentation.
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 Research, 59 (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
Departament d'Educació (2025). Competència digital docent en IA. https://educacio.gencat.cat/ca/departament/publicacions/monografies/mon-digital/competencia-digital-docent-intelligencia-artificial/index.html
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.
Mercader, C. & Castro, D. (2026). After the Storm: an Instrument to Measure the Impact of Digital Technologies in Schools. Technology, Knowledge and Learning, 31(1), 501–518. https://doi.org/10.1007/s10758-025-09869-z
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...
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 | Spanish | second semester | afternoon |