Systematic Literature Review to Explore Research Trends and Future Directions of Multimodal Learning Analytics

2021 ◽  
Vol 27 (2) ◽  
pp. 501-529
Author(s):  
Yoonhee Ham ◽  
Young Hoan Cho ◽  
Hansol Lee ◽  
Hyeeun Kim
2021 ◽  
Author(s):  
Haifa Alwahaby ◽  
Mutlu Cukurova ◽  
Zacharoula Papamitsiou ◽  
Michail Giannakos

There is a growing interest in the research and use of multimodal data in learning analytics. This paper presents a systematic literature review of multimodal learning analytics (MMLA) research to assess i) the available evidence of impact on learning outcomes in real-world contexts and ii) explore the extent to which ethical considerations are addressed. A few recent literature reviews argue for the promising value of multimodal data in learning analytics research. However, our understanding of the challenges associated with MMLA research from real-world teaching and learning environments is limited. To address this gap, this paper provides an overview of the evidence of impact and ethical considerations stemming from an analysis of the relevant MMLA research published in the last decade. The search of the literature resulted in 663 papers, of which 100 were included in the final synthesis. The results show that the evidence of real-world impact on learning outcomes is weak, and ethical aspects of MMLA work are rarely addressed. We discuss our results through the lenses of two theoretical frameworks for evidence of impact types and ethical dimensions of MMLA. We conclude that for MMLA to stay relevant and become part of mainstream education, future research should directly address the gaps identified in this review.


2017 ◽  
Vol 41 (3) ◽  
pp. 222-233 ◽  
Author(s):  
David J. Bumgarner ◽  
Elizabeth J. Polinsky ◽  
Katharine G. Herman ◽  
Joanne M. Fordiani ◽  
Carmen P. Lewis ◽  
...  

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ryosuke Kawamura ◽  
Shizuka Shirai ◽  
Noriko Takemura ◽  
Mehrasa Alizadeh ◽  
Mutlu Cukurova ◽  
...  

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