Exploring factors influencing academic literacy – A data-driven perspective

Background: Data science and machine learning have shown their usefulness in business and are gaining prevalence in the educational sector. In illustrating the potential of educational data mining (EDM) and learning analytics (LA), this article illustrates how such methods can be applied to the South African higher education institution (HEI) environment to enhance the teaching and learning of academic literacy modules. Objectives: The objective of this study is to determine if data science and machine learning methods can be effectively applied to the context of academic literacy teaching and learning and provide stakeholders with valuable decision support. Method: The method applied in this study is a variation of the knowledge discovery and data mining process specifically adapted for discovery in the educational environment. Results: This study illustrates that utilising educational data can support the educational environment by measuring pedagogical support, examining the learning process, supporting strategic decision-making, and predicting student performance. Conclusion: Educators can improve module offerings and students’ academic acculturation by applying EDM and LA to data collected from academic literacy modules. Contribution: This manuscript contributes to the field of EDM and LA by illustrating that methods from these research fields can be applied to the South African educational context and produce valuable insights using local data, providing practical proof of its feasibility and usefulness. This is aligned with the scope of this journal as it pertains to innovations in information management and competitive intelligence

The Effects of Previous Misestimation of Task Duration on Estimating Future Task Duration

It is a common time management problem that people underestimate the duration of tasks, which has been termed the "planning fallacy." To overcome this, it has been suggested that people should be informed about how long they previously worked on the same task. This study, however, tests whether previous misestimation also affects the duration estimation of a novel task, even if the feedback is only self-generated. To test this, two groups of participants performed two unrelated, laboratory-based tasks in succession. Learning was manipulated by permitting only the experimental group to retrospectively estimate the duration of the first task before predicting the duration of the second task. Results showed that the experimental group underestimated the duration of the second task less than the control group, which indicates a general kind of learning from previous misestimation. The findings imply that people could be trained to carefully observe how much they misestimate task duration in order to stimulate learning. The findings are discussed in relation to the anchoring account of task duration misestimation and the memory-bias account of the planning fallacy. © 2014 Springer Science+Business Media New York

Associations of linoleic acid with markers of glucose metabolism and liver function in South African adults

Background: The relation between dietary and circulating linoleic acid (18:2 n-6, LA), glucose metabolism and liver function is not yet clear. Associations of dietary and circulating LA with glucose metabolism and liver function markers were investigated. Methods: Cross-sectional analyses in 633 black South Africans (aged > 30 years, 62% female, 51% urban) without type 2 diabetes at baseline of the Prospective Urban Rural Epidemiology study. A cultural-sensitive 145-item food-frequency questionnaire was used to collect dietary data, including LA (percentage of energy; en%). Blood samples were collected to measure circulating LA (% total fatty acids (FA); plasma phospholipids), plasma glucose, glycosylated hemoglobin (HbA1c), serum gamma-glutamyl transferase (GGT), alanine (ALT) and aspartate aminotransferase (AST). Associations per 1 standard deviation (SD) and in tertiles were analyzed using multivariable regression. Results: Mean (±SD) dietary and circulating LA was 6.8 (±3.1) en% and 16.0 (±3.5) % total FA, respectively. Dietary and circulating LA were not associated with plasma glucose or HbA1c (β per 1 SD: - 0.005 to 0.010, P > 0.20). Higher dietary LA was generally associated with lower serum liver enzymes levels. One SD higher circulating LA was associated with 22% lower serum GGT (β (95% confidence interval): - 0.25 (- 0.31, - 0.18), P </p