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ML 2027: International Conference on Mobile Learning

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Submission Date:
2026-10-09 Due in 3 days
Notification Date:
2026-11-13
Conference Date:
2027-03-13
Location:
Porto, Portugal
Years:
Organizer:
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Conference Partner Index (CP-I)

55.4 / 100
Ranked #831 of 5,693 conferences · Top 15%
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
86
Community attention (10%)
25
Public record completeness (15%)
55

Inputs used: Editions on record: 23 · Researchers following it here: 3 · Researchers who opened this page in the past 24 months: 4

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
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Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-10-05

Call For Papers

ML 2027 (International Conference on Mobile Learning) is an academic conference held in Porto, Portugal on 2027-03-13. The paper submission deadline is 2026-10-09. Acceptance notifications are sent on 2026-11-13.

Mobile learning is concerned with a society on the move. In particular, with the study of “…how the mobility of learners augmented by personal and public technology can contribute to the process of gaining new knowledge, skills and experience” (Sharples et al. 2007). A growing understanding of the learning and instructional affordances of mobile technologies (alongside technological developments), have enabled the design and investigation of mobile learning experiences across contexts and dimensions of mobile learning. For instance, the literature in the field is rich in studies which investigate how learners move physical locations, utilising several devices/technologies, interacting with various social networks (perhaps across formal and informal learning settings), as they pursuit a learning path or event. There is much appreciation of learning principles, such as contextual, situated, augmented and collaborative among others, particularly suited to mobile learning. There is a well of studies reporting on how these principles can be best applied in the field. There are also always new technologies being implemented in the context of mobile learning for example, ‘smarter’ phones, e-readers, tablet and augmented reality applications. However, the evaluation of mobile learning is an area that has lagged behind. The mobile nature of mobile learners and the application of traditional evaluation strategies and tools, have often limited the scope of investigation to what can be observed by researchers or captured by external recording devices (such as video or sound). Thus, a challenge remains to understand what happens while learners are on the move. The advent of cloud computing and learning analytics offer potential for exploring innovative mobile learning experiences and alternative evaluation strategies which may in turn, shade light into what learning happens in the move. The Mobile Learning 2027 International Conference seeks to provide a forum for the presentation and discussion of mobile learning research which illustrate developments in the field. We invite researchers, practitioners, developers and all those working in the mobile learning arena to submit work under the following topics: – Learning analytics and mobile learning – Cloud computing and mobile learning – Pedagogical approaches, models and theories for mLearning – mLearning in and across formal and informal settings – Strategies and challenges for integrating mLearning in broader educational scenarios – User Studies in mLearning – Learner mobility and transitions afforded by mlearning – Socio-cultural context and implications of mLearning – Mobile social media and user generated content – Enabling mLearning technologies, applications and uses – Evaluation and assessment of mLearning – Research methods, ethics and implementation of mLearning – Innovative mLearning approaches – Tools, technologies and platforms for mLearning – mlearning: where to next and how?
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