Whilst the links between learner corpus research (LCR) and Second Language Acquisition (SLA) have long been debated, McEnery et al. (2019. “Corpus Linguistics, Learner Corpora, and SLA: Employing Technology to Analyze Language Use.†Annual Review of Applied Linguistics 39: 74–92. doi:10.1017/S0267190519000096) claim that learner corpus data are not yet sufficiently integrated in SLA research. This article aims to go one way towards bridging the LCR/SLA gap by illustrating the benefits of collecting and analyzing data sets that better document multiliteracy practices. We first contextualize our work within the field of LCR where calls for more multidimensional data sets have been made. We then present a new database called MulTINCo – Multilingual Traditional, Immersion, and Native Corpus – collected in the framework of a project on Content and Language Integrated Learning in French-speaking Belgium. As our data set contains rich metadata and blends corpus data with other data types, we illustrate its potential for SLA research. In Sections 3 and 4, we describe the data collected and the interface. In the last section of the paper, we wrap up with a discussion on the methodological assets of such multidimensional data sets for SLA studies, and present directions for future research.