The Multimodal Study of Blended Learning Using Mixed Sources: Dataset and Challenges of the SpeakUp Case

Social media applications have been proposed as a tool to complement students’ formal learning experiences, often to increase interactivity and participation. However, evidence regarding the benefits and challenges of such applications is still conflicting. In our latest study to explore this conundrum, we have gathered a multimodal dataset that showcases the teaching and learning processes co-occurring simultaneously on a physical space (face-to-face university lectures) and a digital one (SpeakUp, a social media app). The raw data, provided by different sources and informants, were transformed and analyzed using mixed (quantitative and qualitative) techniques. In this contribution, we describe the multiple pieces that composed our dataset, and the steps we took in the multimodal analyses to explore the learning experience occurring in both the physical and digital spaces. This dataset and analysis pipeline illustrates not only challenges and limitations specific to our study, but also more general ones. Several such challenges and limitations, commonplace in blended learning settings analyzed using mixed (multimodal) methods, are synthesized at the end of our paper.


Editor(s):
Prieto, Luis P.
Martínez-Maldonado, Roberto
Spikol, Daniel
Hernández-Leo, Davinia
Rodriguez Triana, Maria Jesus
Ochoa, Xavier
Published in:
Joint Proceedings of the Sixth Multimodal Learning Analytics (MMLA) Workshop and the Second Cross-LAK Workshop co-located with 7th International Learning Analytics and Knowledge Conference, 1828, 68-73
Presented at:
6th Multimodal Learning Analytics (MMLA) Workshop, Vancouver, Canada, March 14, 2017
Year:
2017
Publisher:
CEUR
Keywords:
Laboratories:




 Record created 2017-07-02, last modified 2018-09-13

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