Longitudinal evaluation of pharmacy students' metacognition in interpretation of evidence-based medicine.

BACKGROUND AND PURPOSE: Metacognition is one's ability to "think about thinking" and to understand what knowledge and skills one has. Pharmacy professionals are required to have high metacognitive skills to ensure they are aware of what information they know and when to utilize resources. This longitudinal evaluation of pharmacy students' metacognitive ability was conducted via analysis of students' knowledge and confidence in evidence-based medicine (EBM) skills. EDUCATIONAL ACTIVITY AND SETTING: A survey was administered to the graduating classes of 2017 and 2018 four times, from the beginning of the second-year drug literature evaluation course (baseline) through graduation. The surveys included seven self-confidence questions for which a corresponding knowledge question was asked. Students' metacognition was evaluated on the basis of whether the level of confidence was a "match" or a "mismatch" to their corresponding level of knowledge of each question. The proportion of matches over time was determined. FINDINGS: Fifty-eight students (22%) completed all four surveys. The mean proportion of matches at baseline was 40% and increased over time until graduation when the proportion of matches was 74%. The proportion of matches at baseline for all seven questions were ranged from 33% to 57%. An improvement in meta-cognition was seen in 5 out 7 questions. SUMMARY: This evaluation provides evidence that as students learned material and revisited concepts, their confidence, knowledge, and potentially metacognition regarding EBM concepts increased. However, as 26% of items measured were not a match at graduation, interventions need to be designed and tested to improve student metacognition.

SAS-Pro: simultaneous residue assignment and structure superposition for protein structure alignment.

Protein structure alignment is the problem of determining an assignment between the amino-acid residues of two given proteins in a way that maximizes a measure of similarity between the two superimposed protein structures. By identifying geometric similarities, structure alignment algorithms provide critical insights into protein functional similarities. Existing structure alignment tools adopt a two-stage approach to structure alignment by decoupling and iterating between the assignment evaluation and structure superposition problems. We introduce a novel approach, SAS-Pro, which addresses the assignment evaluation and structure superposition simultaneously by formulating the alignment problem as a single bilevel optimization problem. The new formulation does not require the sequentiality constraints, thus generalizing the scope of the alignment methodology to include non-sequential protein alignments. We employ derivative-free optimization methodologies for searching for the global optimum of the highly nonlinear and non-differentiable RMSD function encountered in the proposed model. Alignments obtained with SAS-Pro have better RMSD values and larger lengths than those obtained from other alignment tools. For non-sequential alignment problems, SAS-Pro leads to alignments with high degree of similarity with known reference alignments. The source code of SAS-Pro is available for download at http://eudoxus.cheme.cmu.edu/saspro/SAS-Pro.html.