Multimodal Data Value Chain (M-DVC): A Conceptual Tool to Support the Development of Multimodal Learning Analytics Solutions

Title:

Multimodal Data Value Chain (M-DVC): A Conceptual Tool to Support the Development of Multimodal Learning Analytics Solutions [Baixar]

Autores/as:

Shankar, Shashi Kant and Rodríguez-Triana, María Jesús and Ruiz-Calleja, Adolfo and Prieto, Luis P. and Chejara, Pankaj and Martínez-Monés, Alejandra

Índice de termos:

Stakeholders;Big Data;Tools;Complexity theory;Software;Data mining;Data Value Chain;Multimodal Learning Analytics;Usefulness;Evaluation;Stakeholder communication;Conceptual tools

Resumo:

Multimodal Learning Analytics (MMLA) systems, understood as those that exploit multimodal evidence of learning to better model a learning situation, have not yet spread widely in educational practice. Their inherent technical complexity, and the lack of educational stakeholder involvement in their design, are among the hypothesized reasons for the slow uptake of this emergent field. To aid in the process of stakeholder communication and systematization leading to the specification of MMLA systems, this paper proposes a Multimodal Data Value Chain (M-DVC). This conceptual tool, derived from both the field of Big Data and the needs of MMLA scenarios, has been evaluated in terms of its usefulness for stakeholders, in three authentic case studies of MMLA systems currently under development. The results of our mixed-methods evaluation highlight the usefulness of the M-DVC to elicit unspoken assumptions or unclear data processing steps in the initial stages of development. The evaluation also revealed limitations of the M-DVC in terms of the technical terminology employed, and the need for more detailed contextual information to be included. These limitations also prompt potential improvements for the M-DVC, on the path towards clearer specification and communication within the multi-disciplinary teams needed to build educationally-meaningful MMLA solutions.

DOI:

10.1109/RITA.2020.2987887

Como citar:
Shankar, Shashi Kant and Rodríguez-Triana, María Jesús and Ruiz-Calleja, Adolfo and Prieto, Luis P. and Chejara, Pankaj and Martínez-Monés, Alejandra, "Multimodal Data Value Chain (M-DVC): A Conceptual Tool to Support the Development of Multimodal Learning Analytics Solutions" in IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, pp. 113-122, May. 2020. doi: 10.1109/RITA.2020.2987887