Data-driven decision making in graduate students’ research topic selection: Cognitive processes and challenging factors
Aslib Journal of Information Management
ISSN: 2050-3806
Article publication date: 27 August 2019
Issue publication date: 18 September 2019
Abstract
Purpose
With the advent of the intelligent environment, as novice researchers, graduate students face digital challenges in their research topic selection (RTS). The purpose of this paper is to explore their cognitive processes during data-driven decision making (DDDM) in RTS, thus developing technical and instructional strategies to facilitate their research tasks.
Design/methodology/approach
This study developes a theoretical model that considers data-driven RTS as a second-order factor comprising both rational and experiential modes. Additionally, data literacy and visual data presentation were proposed as an antecedent and a consequence of data-driven RTS, respectively. The proposed model was examined by employing structural equation modeling based on a sample of 931 graduate students.
Findings
The results indicate that data-driven RTS is a second-order factor that positively affects the level of support of visual data presentation and that data literacy has a positive impact on DDDM in RTS. Furthermore, data literacy indirectly affects the level of support of visual data presentation.
Practical implications
These findings provide support for developers of knowledge discovery systems, data scientists, universities and libraries on the optimization of data visualization and data literacy instruction that conform to students’ cognitive styles to inform RTS.
Originality/value
This paper reveals the cognitive mechanisms underlying the effects of data literacy and data-driven RTS under rational and experiential modes on the level of support of the tabular or graphical presentations. It provides insights into the match between the visualization formats and cognitive modes.
Keywords
Acknowledgements
The authors would like to acknowledge reviewers, editors, and all participants for their contribution to the improvement of this study. This study is supported by grants from the National Natural Science Foundation of China under the agreement 71774121 and 91546124.
Citation
Li, Q., Wang, P., Sun, Y., Zhang, Y. and Chen, C. (2019), "Data-driven decision making in graduate students’ research topic selection: Cognitive processes and challenging factors", Aslib Journal of Information Management, Vol. 71 No. 5, pp. 657-676. https://doi.org/10.1108/AJIM-01-2019-0019
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited