Education and ICT (e-learning)

Responsive Teaching and Learning Processes and Outcomes in Online Education

This research area investigates the various teaching and learning processes that take place in online environments as well as their effects on learner outcomes. Research issues such as how to tailor and fine-tune online teaching to learners’ needs, how learners culturally appropriate knowledge, and the effects of instruction on learners’ performance. Interaction and communication in formal and informal learning scenarios would be the core mechanisms for analysis throughout all kinds of ICT technologies. The results of the teaching and learning processes will search for adaptable decisions and actions that make these processes reliable. The three main areas of research are (but not limited): 1) instructional design of online tasks, materials and tools, 2) e-assessment methods and the provision of effective feedback 3) learning support and efficient student patterns and profiles.

 

Keywords

Thesis Proposals

Researchers

Research group

Keywords
Characteristics and nature of feedback and its impact on students' learning
 
This research line explores the following topics, with a focus on online learning environments or technology-enhanced learning:
 
  • Online learning environment and inner feedback
  • Artificial intelligence (IA) and feedback
  • Feedback personalization
  • Feedback and self-regulated learning
  • Assessment and evaluative judgment
  • Assessment and feedback practices in schools
     

Dr Rosa Mayordomo
mmayordomo@uoc.edu

Dr Teresa Guasch
tguaschp@uoc.edu               

Dr Anna Espasa
aespasa@uoc.edu

Feed2Learn

feedback for learning, assessment for learning; technology enhanced-learning
Feedback Strategies to Improve Learning
 
 
This proposal focuses on studying feedback strategies and practices to strengthen self-regulated learning and the development of evaluative judgement, particularly within the framework of competency-based assessment, in both schools and higher education institutions. Approaches such as peer assessment, multimodal feedback and learning analytics are analysed along with their application in hybrid, digital and in-person environments. Attention is paid to how pedagogical and technological conditions affect the quality of feedback. This proposal is relevant in the context of secondary and higher education, especially with regard to the study of online teaching processes, teacher training and the development of metacognitive skills.
 
(Coordination)
mfernandezferrer@uoc.edu 
 
llluchm@uoc.edu
 
GREDU feedback, autoregulació, avaluació formativa, competències, analítiques d’aprenentatge
Online Peer Assessment in Mathematics Education
 
 
This research focuses on adapting and applying peer assessment processes to online or blended mathematics learning environments. It will explore the design of subject-specific rubrics, the quality of peer feedback, and its impact on students' self-regulation and learning. Additional aspects such as reliability, student perceptions and teacher training needs for implementing technology-supported peer assessment will also be analysed
 
Dr Marc Guinjoan Francisco
mguinjoanf@uoc.edu
 
tsancho@uoc.edu
LAIKA peer assessment, feedback, rubrics
Technology-enhanced second language teaching and learning
 
There are increasingly more technologies that support computer-assisted language learning. While these are necessary developments, there is a need for technological options to go hand-in-hand with pedagogical and psycholinguistic considerations. This line of research investigates second language teaching and learning in blended and virtual environments and the effectiveness of different pedagogical interventions on L2 learning.
 
 
Research topics include, but are not limited to:
 
 
  • Focus on form and L2 learning (e.g., corrective feedback).
  • Technology-based Task-Based Language Teaching (TBLT).
  • Telecollaboration and interaction.
  • Learning design, including OER and MOOCs.
  • Individual differences in second language learning.
  • Artificial intelligence (AI) and language learning (e.g., voice-based chatbots).
  • AI and self-regulated learning.
  • Teacher training focused on the use of AI for instructional design.
  • Teachers' and learners' beliefs about language teaching and learning
 

 

Dr Laia Canals
ecanalsf@uoc.edu

Dr Gisela Grañena
ggranena@uoc.edu

llopn@uoc.edu 
 
arossoh@uoc.edu 
 
pfernandezmi@uoc.edu 
 

TechSLA Lab

technology-mediated second language learning and teaching; instructed language acquisition; individual learner differences; artificial intelligence; feedback
 
 
Second language learning and online communication
 
PhD Research proposals are welcome in any of the following topics:
 
  • eTandem language learning:  eTandem language learning takes place when two learners who are L1 speakers of each other’s TL help each collaborate. Dyads, peer-feedback and new technologies/contexts such as virtual reality are venues of exploration for this type of learning
  • Teaching speaking interaction online: teacher and peer-feedback, task design, blended formats.
  • Alignment phenomena in L2 dialogue.  Alignment phenomena in L2 dialogue has been posited to facilitate L2 acquisition, and be mediated by task or L1/L2.
  • Learner engagement in online environments
  • Affective factor. Emotions such as anxiety or enjoyment are strongly present in online communication and can enhance or hinder L2 learning.
  • Gamification
 

Dr Christine Appel
mappel@uoc.edu

realTIC-UOC
online communicatio; tandem language-learning; language learning design
 
Analysing and improving students’ success: Expectations, experience, and satisfaction with online learning at the UOC
 
 
This research line focuses on studying undergraduate and postgraduate students’ experiences with online learning in a fully online higher education institution such as the UOC. Drawing on the team’s expertise in designing and assessing educational innovations, the research carried out by the PhD students will contribute to a better understanding of the learners’ expectations, how they manage and engage with the online learning at our university, how the intersection between their expectations and experience influences their satisfaction and, in the end, how it affects their determination to achieve their educational goals. Candidates should be fluent in Catalan or Spanish to be able to carry on the fieldwork and analyse their data, developing a qualitative, quantitative or mixed methods approach.
jmenesesn@uoc.edu
 
sfabreguesf@uoc.edu
 
aangulob@uoc.edu
 
jreyesrey@uoc.edu 
MISS (Julio Meneses, Ariadna Angulo i José Israel Reyes)
 
 
NUTRALiSS (Sergi Fàbregas)
 
students’ success; students’ experience; online learning
Learners' identity, agency and learning engagement in blended and online environments
 
This research proposal is focused on analysing students' learning engagement in relation to their identity and agency development as learners in online and blended environments. We conceive agency and identity as dynamic and socioculturally mediated dispositions through which students build their learning pathways across different environments.
 
We propose dialogical and reflective learning approaches, including student participation in learning co-design via digital technologies, as means of encouraging students' learning engagement, as well as their identity and agency development by gradually taking control and direction of their own learning.

Dr Iolanda García González
igarciago@uoc.edu

MISS
student identity and agency; learning engagement; learning design and codesign
 
Personalization of Learning
 
 
The proposed research line aims to advance the personalization of learning based on learners' individual characteristics, needs and contexts. It explores how technology – particularly artificial intelligence – can support adaptive, inclusive and effective educational experiences.
 
Key research directions include:
 
  • Synchronous, asynchronous and hybrid learning methodologies
  • Active and experiential learning approaches
  • Feedback and learner support mechanisms
  • Competency-based programme design
  • Competence and knowledge assessment methods
  • Artificial intelligence for educational innovation
  • Formal and informal learning pathways
  • Linking learning methodologies to skills development and employability
 
 
 
 
mmartinezarg@uoc.edu
 
afitob@uoc.edu
 
cpagesserra@uoc.edu
 
cplag@uoc.edu
 
eserradell@uoc.edu
 
rferreras@uoc.edu
 
mpujoljo@uoc.edu
 
Dr Jordi Sales-Zaguirre
jsales@uoc.edu
 
Dr David Roman Coy
droman@eada.edu
 
ajony@uoc.edu
 
 
learning personalisation, artificial intelligence; skills development
Integrating insights from educational neuroscience, socio-emotional learning and imaginative pedagogies as well as news technologies, such as machine learning, big data or affective chatbots, to support new ways of teaching and learning
 
This research will investigate the following large-scale research topics (which can be independent PhD topics):
 
1.   The inclusion of psico-pedagogic mechanisms in learning digital resources, basically based on educational regulation and metacognition,                 mediated by AI to improve the quality of teaching and learning process.
 
2.   The relationship of educational neuroscience with socio-emotional learning, especially emotional intelligence.
 
3.   The relationship of virtual or human teacher cognitive and affective feedback with neurotransmitters and students’ motivation and attention.
 
4.   The development of an intelligent and affective-aware CSCL environment that orchestrates students' interactions and engagement in an effective manner, taking into consideration different affective states.
 
5. The analysis and interpretation of the relationship between emotion awareness and educational neuroscience, identifying what neurotransmitters have a strong relationship with the emotions that students experience during their online learning processes (conversations, debates, wikis) in context.
 
martaarg@uoc.edu
 
Edul@b
educational neuroscience, socio-emocional learning, metacognition and AI
 
Use of GenAI in Pre-service Teacher Education for Primary and Secondary Teachers
 
 
This research line focuses on the educational potential and pedagogical implications of generative artificial intelligence (GenAI) within initial teacher training (ITT) programmes for primary and secondary education teachers.
 
 
It investigates how GenAI-based tools can be integrated into the teacher preparation curriculum to equip future educators with the necessary skills to use GenAI effectively, ethically and critically in their classrooms.
 
 
The research aims to contribute to a deeper understanding of how initial teacher education (ITE) can be reformed to integrate GenAI responsibly. The goal is to ensure that future primary and secondary teachers are not only users of this technology but also critical, ethical and pedagogically informed designers of AI-enhanced learning experiences.
 
(Coordinator)
lbecerril@uoc.edu
 
tbadia@uoc.edu
 
Investigadors independents 
 
SINTE (UAB)
 
Generative Artificial Intelligence (GenAI); Pre-service teachers; Primary and Secondary education; Initial teacher training (ITT)
Teacher Professional Development in the Digital Era
 
Development of competency frameworks, strategies and actions for teaching, especially hybrid and online, that help with professional teaching updating in emerging and future educational scenarios (teaching focus).
 
 
mguitert@uoc.edu
 
jduart@uoc.edu
 
ncabrera@uoc.edu
 
lguardia@uoc.edu
 
mmaina@uoc.edu
 
mromerocar@uoc.edu
 
tromeu@uoc.edu
 
asangra@uoc.edu
 
 
Edul@b
competency frameworks; teacher professional development; future educational scenarios