keyword
MENU ▼
Read by QxMD icon Read
search

Problem-based learning

keyword
https://www.readbyqxmd.com/read/28079727/how-supervisor-experience-influences-trust-supervision-and-trainee-learning-a-qualitative-study
#1
Leslie Sheu, Jennifer R Kogan, Karen E Hauer
PURPOSE: Appropriate trust and supervision facilitate trainees' growth toward unsupervised practice. The authors investigated how supervisor experience influences trust, supervision, and subsequently trainee learning. METHOD: In a two-phase qualitative inductive content analysis, phase one entailed reviewing 44 internal medicine resident and attending supervisor interviews from two institutions (July 2013 to September 2014) for themes on how supervisor experience influences trust and supervision...
January 10, 2017: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/28078685/peer-assessment-of-professional-behaviours-in-problem-based-learning-groups
#2
Chris Roberts, Christine Jorm, Stacey Gentilcore, Jim Crossley
CONTEXT: Peer assessment of professional behaviour within problem-based learning (PBL) groups can support learning and provide opportunities to identify and remediate problem behaviours. OBJECTIVES: We investigated whether a peer assessment of learning behaviours in PBL is sufficiently valid to support decision making about student professional behaviours. METHODS: Data were available for two cohorts of students, in which each student was rated by all of their PBL group peers using a modified version of a previously validated scale...
January 12, 2017: Medical Education
https://www.readbyqxmd.com/read/28073525/delineation-of-the-role-of-nutrient-variability-and-dreissenids-mollusca-bivalvia-on-phytoplankton-dynamics-in-the-bay-of-quinte-ontario-canada
#3
Yuko Shimoda, Sue B Watson, Michelle E Palmer, Marten A Koops, Shan Mugalingam, Andrew Morley, George B Arhonditsis
The Bay of Quinte, a Z-shaped embayment at the northeastern end of Lake Ontario, has a long history of eutrophication problems primarily manifested as spatially extensive algal blooms and predominance of toxic cyanobacteria. The purpose of this study was to identify the structural changes of the phytoplankton community induced by two environmental alterations: point-source phosphorus (P) loading reduction in the late 1970s and establishment of dreissenid mussels in the mid-1990s. A combination of statistical techniques was used to draw inference about compositional shifts of the phytoplankton assemblage, the consistency of the seasonal succession patterns along with the mechanisms underlying the algal biovolume variability in the Bay of Quinte over the past three decades...
May 2016: Harmful Algae
https://www.readbyqxmd.com/read/28066963/phenotiki-an-open-software-and-hardware-platform-for-affordable-and-easy-image-based-phenotyping-of-rosette-shaped-plants
#4
Massimo Minervini, Mario Valerio Giuffrida, Pierdomenico Perata, Sotirios A Tsaftaris
Phenotyping is important to understand plant biology but current solutions are either costly, not versatile or difficult to deploy. To solve this problem, we present Phenotiki, an affordable system for plant phenotyping which, relying on off-the-shelf parts, provides an easy to install and maintain platform, offering an out-of-box experience for a well established phenotyping need: imaging rosette-shaped plants. The accompanying software (with available source code) processes data originating from our device seamlessly and automatically...
January 9, 2017: Plant Journal: for Cell and Molecular Biology
https://www.readbyqxmd.com/read/28066703/how-common-are-wm-deficits-in-children-with-difficulties-in-reading-and-mathematics
#5
Susan E Gathercole, Francesca Woolgar, Rogier A Kievit, Duncan Astle, Tom Manly, Joni Holmes
The extent to which deficits in working memory (WM) are characteristic of children with reading and mathematics difficulties was investigated in a large sample aged 5-15 years reported to have problems in attention, learning and memory. WM performance was highly correlated with reading and mathematics scores. Although deficits in individual tests of short-term memory (STM) and WM occurred in less than half of the children with detected learning difficulties, three-quarters of the children with low reading and mathematics scores obtained one or more WM scores in the deficit range...
December 2016: Journal of Applied Research in Memory and Cognition
https://www.readbyqxmd.com/read/28062244/identification-of-time-varying-neural-dynamics-from-spike-train-data-using-multiwavelet-basis-functions
#6
Song Xu, Yang Li, Qi Guo, Xiao-Feng Yang, Rosa H M Chan
BACKGROUND: Tracking the changes of neural dynamics based on neuronal spiking activities is a critical step to understand the neurobiological basis of learning from behaving animals. These dynamical neurobiological processes associated with learning are also time-varying, which makes the modeling problem challenging. NEW METHOD: We developed a novel multiwavelet-based time-varying generalized Laguerre-Volterra (TVGLV) modeling framework to study the time-varying neural dynamical systems using natural spike train data...
January 4, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28061800/does-a-pbl-based-medical-curriculum-predispose-training-in-specific-career-paths-a-systematic-review-of-the-literature
#7
Jordan Tsigarides, Laura R Wingfield, Myutan Kulendran
BACKGROUND: North American medical schools have used problem-based learning (PBL) structured medical education for more than 60 years. However, it has only recently been introduced in other medical schools outside of North America. Since its inception, there has been the debate on whether the PBL learning process predisposes students to select certain career paths. OBJECTIVES: To review available evidence to determine the predisposition of specific career paths when undertaking a PBL-based medical curriculum...
January 7, 2017: BMC Research Notes
https://www.readbyqxmd.com/read/28061777/whatsapp-messenger-as-a-tool-to-supplement-medical-education-for-medical-students-on-clinical-attachment
#8
Lewis Raiman, Richard Antbring, Asad Mahmood
BACKGROUND: Instant messaging applications have the potential to improve and facilitate communication between hospital doctors and students, hence generating and improving learning opportunities. This study aims to demonstrate the feasibility and acceptability of instant messaging communication to supplement medical education for medical students whilst on clinical attachment. METHODS: A total of 6 WhatsApp Messenger (WhatsApp Inc.) groups were created for medical students on clinical attachment...
January 6, 2017: BMC Medical Education
https://www.readbyqxmd.com/read/28060838/attitudes-and-readiness-of-students-of-healthcare-professions-towards-interprofessional-learning
#9
Mari Kannan Maharajan, Kingston Rajiah, Suan Phaik Khoo, Dinesh Kumar Chellappan, Ranjit De Alwis, Hui Cing Chui, Lui Lee Tan, Yee Ning Tan, Shin Yee Lau
OBJECTIVES: To evaluate the attitudes and readiness of students of healthcare professions towards interprofessional learning. METHODOLOGY: A cross-sectional study design was used. Two different scales were used to measure the readiness for and perception of interprofessional learning; these were the 'Readiness for Interprofessional Learning Scale' and the 'Interdisciplinary Education Perception Scale'. A convenience sampling method was employed. The sample was drawn from undergraduate students enrolled in years 1 to 5 of medical, dental, pharmacy and health sciences programme...
2017: PloS One
https://www.readbyqxmd.com/read/28060807/svm-and-svm-ensembles-in-breast-cancer-prediction
#10
Min-Wei Huang, Chih-Wen Chen, Wei-Chao Lin, Shih-Wen Ke, Chih-Fong Tsai
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions...
2017: PloS One
https://www.readbyqxmd.com/read/28060712/self-taught-low-rank-coding-for-visual-learning
#11
Sheng Li, Kang Li, Yun Fu
The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data...
January 2, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28059391/sparse-identification-for-nonlinear-optical-communication-systems-sino-method
#12
Mariia Sorokina, Stylianos Sygletos, Sergei Turitsyn
We introduce low complexity machine learning method method (based on lasso regression, which promotes sparsity, to identify the interaction between symbols in different time slots and to select the minimum number relevant perturbation terms that are employed) for nonlinearity mitigation. The immense intricacy of the problem calls for the development of "smart" methodology, simplifying the analysis without losing the key features that are important for recovery of transmitted data. The proposed sparse identification method for optical systems (SINO) allows to determine the minimal (optimal) number of degrees of freedom required for adaptive mitigation of detrimental nonlinear effects...
December 26, 2016: Optics Express
https://www.readbyqxmd.com/read/28056098/a-model-for-good-governance-of-healthcare-technology-management-in-the-public-sector-learning-from-evidence-informed-policy-development-and-implementation-in-benin
#13
P Th Houngbo, H L S Coleman, M Zweekhorst, Tj De Cock Buning, D Medenou, J F G Bunders
Good governance (GG) is an important concept that has evolved as a set of normative principles for low- and middle-income countries (LMICs) to strengthen the functional capacity of their public bodies, and as a conditional prerequisite to receive donor funding. Although much is written on good governance, very little is known on how to implement it. This paper documents the process of developing a strategy to implement a GG model for Health Technology Management (HTM) in the public health sector, based on lessons learned from twenty years of experience in policy development and implementation in Benin...
2017: PloS One
https://www.readbyqxmd.com/read/28056090/accurate-de-novo-prediction-of-protein-contact-map-by-ultra-deep-learning-model
#14
Sheng Wang, Siqi Sun, Zhen Li, Renyu Zhang, Jinbo Xu
MOTIVATION: Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. METHOD: This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks...
January 5, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28055941/a-dynamic-neighborhood-learning-based-gravitational-search-algorithm
#15
Aizhu Zhang, Genyun Sun, Jinchang Ren, Xiaodong Li, Zhenjie Wang, Xiuping Jia
Balancing exploration and exploitation according to evolutionary states is crucial to meta-heuristic search (M-HS) algorithms. Owing to its simplicity in theory and effectiveness in global optimization, gravitational search algorithm (GSA) has attracted increasing attention in recent years. However, the tradeoff between exploration and exploitation in GSA is achieved mainly by adjusting the size of an archive, named Kbest, which stores those superior agents after fitness sorting in each iteration. Since the global property of Kbest remains unchanged in the whole evolutionary process, GSA emphasizes exploitation over exploration and suffers from rapid loss of diversity and premature convergence...
December 30, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28055940/deep-nonlinear-metric-learning-for-3-d-shape-retrieval
#16
Jin Xie, Guoxian Dai, Fan Zhu, Ling Shao, Yi Fang
Effective 3-D shape retrieval is an important problem in 3-D shape analysis. Recently, feature learning-based shape retrieval methods have been widely studied, where the distance metrics between 3-D shape descriptors are usually hand-crafted. In this paper, motivated by the fact that deep neural network has the good ability to model nonlinearity, we propose to learn an effective nonlinear distance metric between 3-D shape descriptors for retrieval. First, the locality-constrained linear coding method is employed to encode each vertex on the shape and the encoding coefficient histogram is formed as the global 3-D shape descriptor to represent the shape...
December 28, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28055920/robust-dlpp-with-nongreedy-%C3%A2-%C3%A2-norm-minimization-and-maximization
#17
Qianqian Wang, Quanxue Gao, Deyan Xie, Xinbo Gao, Yong Wang
Recently, discriminant locality preserving projection based on L1-norm (DLPP-L1) was developed for robust subspace learning and image classification. It obtains projection vectors by greedy strategy, i.e., all projection vectors are optimized individually through maximizing the objective function. Thus, the obtained solution does not necessarily best optimize the corresponding trace ratio optimization algorithm, which is the essential objective function for general dimensionality reduction. It results in insufficient recognition accuracy...
December 29, 2016: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28055847/show-and-tell-lessons-learned-from-the-2015-mscoco-image-captioning-challenge
#18
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, we present a generative model based on a deep recurrent architecture that combines recent advances in computer vision and machine translation and that can be used to generate natural sentences describing an image. The model is trained to maximize the likelihood of the target description sentence given the training image. Experiments on several datasets show the accuracy of the model and the fluency of the language it learns solely from image descriptions...
July 7, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28055027/interdisciplinary-onsite-team-based-simulation-training-in-the-neonatal-intensive-care-unit-a-pilot-report
#19
D J W Reed, R L Hermelin, C S Kennedy, J Sharma
OBJECTIVE: Simulation training improves individual clinician confidence, performance and self-efficacy in resuscitation and procedural training experiences. The reality of resuscitation experiences in the neonatal intensive care unit (NICU) is that they are team-accomplished events. However, limited data exist on team-based simulation training (TBST) in the NICU. We report the experience of TBST over a 4-year period. STUDY DESIGN: This is a retrospective report of 65 TBST events in a 71-bed Level IV NICU at a regional subspecialty children's hospital...
January 5, 2017: Journal of Perinatology: Official Journal of the California Perinatal Association
https://www.readbyqxmd.com/read/28052091/sense-of-accomplishment-is-modulated-by-a-proper-level-of-instruction-and-represented-in-the-brain-reward-system
#20
Tomoya Nakai, Hironori Nakatani, Chihiro Hosoda, Yulri Nonaka, Kazuo Okanoya
Problem-solving can be facilitated with instructions or hints, which provide information about given problems. The proper amount of instruction that should be provided for learners is controversial. Research shows that tasks with intermediate difficulty induce the largest sense of accomplishment (SA), leading to an intrinsic motivation for learning. To investigate the effect of instructions, we prepared three instruction levels (No hint, Indirect hint, and Direct hint) for the same insight-problem types. We hypothesized that indirect instructions impose intermediate difficulty for each individual, thereby inducing the greatest SA per person...
2017: PloS One
keyword
keyword
6325
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"