Unravelling the Literature Review: Helping Graduate Students in Education Re-conceptualize the Research Process

Lee, Elizabeth A.; Laverty, Cory

doi:10.1007/978-3-319-14136-7_74

Cited by 1 publication

(3 citation statements)

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“…Previous works have explored how visual data presentation can support decisions by demonstrating the matching between a decision maker's cognitive style and the format of visual data presentation. Regarding RTS decisions, visual maps can help enhance graduate students' initial conceptualization of a research topic (Lee and Laverty, 2014). However, few studies have investigated the cognitive states of graduate students during RTS decision and the effects of these states on the level of support of visual data presentation in KDD systems.…”

Section: Visual Data Presentationmentioning

confidence: 99%

“…Data literacy is the prerequisite for data use and is closely associated with DDDM (Hoogland et al, 2016), but there have been few empirical studies on the positive influence of data literacy on DDDM, especially in fields outside education. A literature review was regarded as the most critical approach to RTS for graduate students (Tang and Gan, 2005) and researchers proposed that information literacy, the core of literature review, contributed to students' RTS (Lee and Laverty, 2014). However, the emergence and enhancement of data-driven RTS raises challenges for traditional information literacy education.…”

Section: Data Literacymentioning

confidence: 99%

“…This finding reinforces the need to develop data literacy strategies for graduate students. However, researchers pay more attention to developing information literacy strategies that can support traditional RTS (Lee and Laverty, 2014), thus leaving a gap in data literacy strategies in the context of graduate students' data-driven RTS. In terms of human cognition, based on cognitive-experiential self-theory (Epstein, 1994) and dual-process theories, both rational and experiential modes of information-processing affect decision making (Khatri et al, 2018) and DDDM.…”

Section: Introductionmentioning

confidence: 99%

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Data-driven decision making in graduate students’ research topic selection

Qiao¹,

Wang

Sun

et al. 2019

AJIM

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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.

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Section: Visual Data Presentationmentioning

confidence: 99%