From the algorithmic and emergent mindset to the heuristic mindset of reviewing literature

• Published in: Quality & quantity Vol. 55; no. 4; pp. 1419 - 1455
• Main Authors: Kofi Frimpong, Adasa Nkrumah, Li, Ping, Amoah, Millicent, Hossin, Md Altab
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-08-2021; Springer; Springer Nature B.V
• Subjects: Algorithms; Analysis; Citation management software; Clustering; Data analysis; Graduate students; Heuristic; Information management; Keywords; Literature reviews; Methodology of the Social Sciences; Ontology; Scientometrics; Social network analysis; Social networks; Social Sciences; Students; Tactics; Translation; Trends; Visualization; Word processing; Literature review; Postgraduate students; Discourse analysis; Challenges of literature review; Qualitative data analysis; Educational research
• ISSN: 0033-5177; 1573-7845
• DOI: 10.1007/s11135-020-01065-8

Studies on literature review (LR) methodology appear scant. Researchers have outlined common challenges associated with the LR process. Traditionally, conducting a LR entails paraphrasing existing studies. Researchers have failed to address the emergent nature of literature and how to deal with this challenge effectively. We analyzed the challenges of conducting a LR of published articles. Also, we collected data from postgraduate students in China. Using the five-level Qualitative Data Analysis and the learning heuristics of the translation process, we matched the units of analytical tasks of the LR at the strategy level to their selected and constructed components at the tactics level. A post-test analysis shows that this model explains 72% of the variance in the new strategy .