Predicting Academic Performance: A Systematic Literature Review

The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.Peer reviewe

Unequivocal identification of an underestimated opportunistic yeast species, Cyberlindnera fabianii, and its close relatives using a dual-function PCR and literature review of published cases

Although Cyberlindnera fabinaii is a rare opportunist yeast species, its ability to cause septicemia, produce biofilm, and rapid acquisition of resistance to fluconazole and voriconazole, reinforced the urge for its identification from its closely related species. Widely used biochemical assays mainly identify Cyberlindnera fabinaii as Cyberlindnera jadinii and Wickerhamomyces anomalus, resulting in underestimation of this yeast in clinical settings. Moreover, the urge for a reliable molecular means of identification remains unsolved for 28 years. In order to unequivocally differentiate Cy. fabianii, Cy. mississipiensis, Cy. jadinii, and W. anomalus, we designed a dual-function multiplex polymerase chain reaction (PCR) assay. Challenging our dual-function multiplex PCR assay with 30 most clinically important yeast species, proved its specificity. Although conventional PCR could differentiate four target species, the real-time PCR counterpart due to Tm overlap misidentified Cy. mississipiensis as Cy. jadinii. Alongside of presenting a comprehensive literature review of published cases of Cy. fabianii from 1990 to 2018, we collected various clinical isolates from Tehran, Shiraz, and Fasa (July 1, 2017, to December 31, 2017) to find a passive relative distribution of these closely-related species in Iran. Subjecting our Iranian collection of yeast isolates to matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS and LSU and ITS rDNA sequencng revealed six isolates of Cy. fabianii (central venous catheter n = 2 and vaginal swabs n = 4) and one isolate of Cy. jadinii (vaginal swabs). Due to the use of biochemical assays in global ARTEMIS study, we encourage reidentification of clinical isolates of Cy. jadinii and Cy. jadinii using MALDI-TOF or Sanger sequencing that might lead to correcting the distribution of this fungus