Search

Problem-based learning (PBL) is a self-directed learning strategy where students work collaboratively in small groups to investigate open-ended relatable case scenarios. Students develop transferable skills that can be applied across disciplines, such as collaboration, problem-solving, and critical thinking. Despite extensive research on problem-based learning, a thorough examination of student engagement in relation to PBL is lacking (Savin-Baden, 2014; 2016). We studied student motivation through self-reflection exercises, surveys, and peer-evaluations in a third-year undergraduate anthropology course (N = 49) with students of differing levels of course material experience. We hypothesized that throughout the course student motivation would be highest in students with the most subject matter experience. The results show that student motivation was higher in students with more subject matter experience at the beginning of the course, however during the course their motivation decreased. By the end of the course the majority of students had high motivation toward PBL, however, we were surprised that forensic specialists with the most subject matter experience had low motivation at the end of the course. This research is important to demonstrate the challenges of implementing PBL in a traditional curriculum, and to provide suggestions for engaging diverse student populations in PBL.

Purpose: The purpose of this paper is to examine the relationship between student motivation and technology in the implementation of problem-based learning (PBL) in a technologically enhanced active learning classroom (ALC). Design/methodology/approach: PBL was implemented in an undergraduate course in human osteology (n=49) at a large Canadian University. Numerous activities using the ALC technology were conducted to engage students in self-directed active learning. Students wrote critical self-reflections at the beginning of the course and with each PBL report. They completed a survey at the end of the course using a Likert scale that included written comments on their motivation toward different uses of technology. Findings: Students generally had high motivation toward PBL at the end of the course. Their evaluation of the technology to support PBL was dependent on the activity. Students (88 percent) appreciated the use of an overhead camera to visualize anatomical elements, and short problem-solving exercises using the whiteboard but they negatively evaluated the real-time projection of PBL sessions through a discussion board (52 percent). Almost half of the class (43 percent) felt that technology was a hindrance to their learning process in PBL. Originality/value: This study demonstrates the complex relationship between student motivation toward active learning, the learning environment, and technology. Instructors and students influence the learning environment through their conceptions of effective teaching. According to this framework, technology should be implemented not only according to the teaching method, but consider teaching conceptions and the learning environment.

In this paper, we present international comparisons of potential output growth among several economies—Canada, the euro area, France, Germany, Italy, Japan, the Netherlands, the United Kingdom, and the United States—for the period 1991–2004, for which we construct consistent and homogenous capital stock series. The main estimates rely on a structural approach where output of the whole economy is described by a Cobb–Douglas function and Total Factor Productivity (TFP) is estimated allowing for possible breaks in the deterministic trend. The results confirm that over the considered period the potential gross domestic product growth has been faster in the United States than in other studied countries, reflecting a combination of higher labour contribution and faster TFP growth. Overall, this paper might help to shed some light on cross-country differences in economic performance over the recent period. [ABSTRACT FROM AUTHOR]

Focuses on Toronto, Ontario-based Nexus percussion ensemble's utilization of the concept of diversification in attracting listeners to their music. Importance of merging the diverse elements of music on the formation of the ensemble; Positive impact of a program containing a diversity of music on listeners; Success of eclectic programming.

Aims: Identification, a priori, of those at high risk of progression from pre-diabetes to diabetes may enable targeted delivery of interventional programmes while avoiding the burden of prevention and treatment in those at low risk. We studied whether the use of a machine-learning model can improve the prediction of incident diabetes utilizing patient data from electronic medical records., Methods: A machine-learning model predicting the progression from pre-diabetes to diabetes was developed using a gradient boosted trees model. The model was trained on data from The Health Improvement Network (THIN) database cohort, internally validated on THIN data not used for training, and externally validated on the Canadian AppleTree and the Israeli Maccabi Health Services (MHS) data sets. The model's predictive ability was compared with that of a logistic-regression model within each data set., Results: A cohort of 852 454 individuals with pre-diabetes (glucose ≥ 100 mg/dL and/or HbA1c ≥ 5.7) was used for model training including 4.9 million time points using 900 features. The full model was eventually implemented using 69 variables, generated from 11 basic signals. The machine-learning model demonstrated superiority over the logistic-regression model, which was maintained at all sensitivity levels - comparing AUC [95% CI] between the models; in the THIN data set (0.865 [0.860,0.869] vs 0.778 [0.773,0.784] P < .05), the AppleTree data set (0.907 [0.896, 0.919] vs 0.880 [0.867, 0.894] P < .05) and the MHS data set (0.925 [0.923, 0.927] vs 0.876 [0.872, 0.879] P < .05)., Conclusions: Machine-learning models preserve their performance across populations in diabetes prediction, and can be integrated into large clinical systems, leading to judicious selection of persons for interventional programmes., (© 2020 John Wiley & Sons, Ltd.)