JUCS - Journal of Universal Computer Science 29(3): 265-297, doi: 10.3897/jucs.84558
CIMLA: A Modular and Modifiable Data Preparation, Organization, and Fusion Infrastructure to Partially Support the Development of Context-aware MMLA Solutions
expand article infoShashi Kant Shankar‡, Adolfo Ruiz-Calleja§, Luis P. Prieto‡, María Jesús Rodríguez-Triana‡, Pankaj Chejara‡, Sandesh Tripathi|
‡ Tallinn University, Tallinn, Estonia§ Universidad de Valladolid, Valladolid, Spain| Birla Institute of Applied Sciences, Bhimtal, India

Corresponding author: Shashi Kant Shankar ( shashi2y22@gmail.com )

© Shashi Kant Shankar, Adolfo Ruiz-Calleja, Luis P. Prieto, María Jesús Rodríguez-Triana, Pankaj Chejara, Sandesh Tripathi.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.
Citation: Shankar SK, Ruiz-Calleja A, Prieto LP, Rodríguez-Triana MJ, Chejara P, Tripathi S (2023) CIMLA: A Modular and Modifiable Data Preparation, Organization, and Fusion Infrastructure to Partially Support the Development of Context-aware MMLA Solutions. JUCS - Journal of Universal Computer Science 29(3): 265-297. https://doi.org/10.3897/jucs.84558
Open Access
Abstract
Multimodal Learning Analytics (MMLA) solutions aim to provide a more holistic picture of a learning situation by processing multimodal educational data. Considering contextual information of a learning situation is known to help in providing more relevant outputs to educational stakeholders. However, most of the MMLA solutions are still in prototyping phase and dealing with different dimensions of an authentic MMLA situation that involve multiple cross-disciplinary stakeholders like teachers, researchers, and developers. One of the reasons behind still being in prototyping phase of the development lifecycle is related to the challenges that software developers face at different levels in developing context-aware MMLA solutions. In this paper, we identify the requirements and propose a data infrastructure called CIMLA. It includes different data processing components following a standard data processing pipeline and considers contextual information following a data structure. It has been evaluated in three authentic MMLA scenarios involving different cross-disciplinary stakeholders following the Software Architecture Analysis Method. Its fitness was analyzed in each of the three scenarios and developers were interviewed to assess whether it meets functional and non-functional requirements. Results showed that CIMLA supports modularity in developing context-aware MMLA solutions and each of its modules can be reused with required modifications in the development of other solutions. In the future, the current involvement of a developer in customizing the configuration file to consider contextual information can be investigated.
Keywords
ad-hoc development, reusability, Separation of Concerns, SAAM