scholarly journals MP24: Contagion: An innovative approach to learning the Orange Book and Choosing Wisely Canada guidelines around antimicrobial treatment

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S50-S51
Author(s):  
M. Khalid ◽  
S. Shah ◽  
S. Bala ◽  
M. Luterman
Keyword(s):  
Active Learning ◽  
Video Game ◽  
Large Scale ◽  
Medical Training ◽  
Clinical Symptoms ◽  
Clinical Skills ◽  
Real Life ◽  
Role Playing ◽  
Choosing Wisely ◽  
Orange Book

Innovation Concept: The Orange Book (OB) identifies drugs approved on the basis of safety and effectiveness by the FDA and serves as the gold standard reference for correct pharmacological therapies. It ties in closely with Choosing Wisely Canada (CWC) modelling good stewardship in antimicrobial prescriptions. The book focuses on passive didactic learning instead of active learning, which was shown to have a greater influence on prescribing behaviour. Educational video games, a form of active learning, have been shown to improve clinical skills in medical training. Contagion is a role-playing video game providing an active way of teaching antimicrobial components of the OB and CWC guidelines. Method: Phase I of Contagion was qualitatively tested on students and physicians at McMaster University for teaching effectiveness, applicability to real-life scenarios, and enjoyability. Post-game play 12 participants scored different aspects of the game on a Likert scale. Curriculum, Tool, or Material: The player is a rural physician treating infections in various communities. Each round, the player is given a crate of antibiotics. As communities are infected, the player is provided with clinical symptoms the patients present with. The player must identify the pathology and then correctly treat the communities. The player can treat empirically or order tests to identify the infectious organism. The player strategically navigates which communities to treat as there are limited actions per turn and the player must prevent communities from dying or infecting neighboring regions. Communities tend to build antibiotic resistance over time making first-line treatments unviable, thus careful strategizing and stewardship is essential. Active learning will occur when players are tasked with finding the correct answer to different presentations. After each turn, players will learn about the infecting organism, its phenotypes, and common infectious symptoms. This is considered passive learning. Conclusion: Contagion was well-received by physicians and medical students as an active learning tool to teach the OB and CWC guidelines. On preliminary user testing Contagion scored 5 in effectiveness in teaching treatments and 4.6 in teaching stewardship. An objective of this project is to perform large scale testing across schools to demonstrate the effectiveness of the learning components of the game. We hope to eventually create a tool that can be incorporated in continuing medical education for physicians.

“This is like an RPG where you pick up friends along the way”

2021 ◽  
pp. 122-151
Author(s):  
Sylvia Sierra
Keyword(s):  
Video Games ◽  
Identity Construction ◽  
Video Game ◽  
Real Life ◽  
Role Playing ◽  
Face To Face ◽  
Oregon Trail ◽  
Role Playing Games ◽  
Constructed Dialogue ◽  
The Oregon Trail

This chapter examines how Millennial friends in their late twenties appropriate texts from video games they have played to serve particular social interactive functions in their everyday face-to-face conversations. Speakers use references to the video games Papers, Please, The Oregon Trail, Minecraft, and Role Playing Games (RPGS) to shift the epistemic territories of conversations when they encounter interactional dilemmas. These epistemic shifts simultaneously rekey formerly problematic talk (on topics like rent, money, and injuries) to lighter, humorous talk, reframing these issues as being part of a lived video game experience. Overlapping game frames are laminated upon real-life frames and are strengthened by embedded frames containing constructed dialogue. This chapter contributes to understanding how epistemic shifts relying on intertextual ties can shift frames during interactional dilemmas in everyday conversation, which is ultimately conducive to group identity construction.

scholarly journals Pharmacy Students’ Perception and Evaluation of Objective Structured Clinical Examination: Near East University Experience

2019 ◽  
Author(s):  
Bilgen Basgut ◽  
Abdikarim Mohamed Abdi
Keyword(s):  
Formative Assessment ◽  
Clinical Examination ◽  
Clinical Skills ◽  
Student Assessment ◽  
Real Life ◽  
Opportunity To Learn ◽  
Role Playing ◽  
Pharmacy Students ◽  
Objective Structured Clinical Examination ◽  
Cross Sectional Survey

Background: Pharmacy educators have always been desirous of the best methods for formative and summative evaluation of trainees. The Objective Structured Clinical Examination (OSCE) is an approach for student assessment in which aspects of clinical competence are evaluated in a comprehensive, consistent, and structured manner. Though recently become popular in pharmacy schools globally, its use in North Cyprus and Turkey pharmacy schools appears limited. Objectives: To assess pharmacy students’ evaluation and overall perception of OSCE. Methods: A cross-sectional survey was conducted on pharmacy students, who participated in the final OSCE examination in 2015-2016.The study sample consisted of fifth-year Pharmacy students who took the OSCE assessment during their studies. A24-item self-administered structured questionnaire was employed to obtain relevant data on OSCE evaluation in terms of content reliability and structure of the examination. Students’ responses were based on a 4-point Likert scales ranging from disagree to no comment. The data were analyzed using SPSS, version 22. Results: Of 81 eligible students, 74 completed self- administered questionnaire representing 91.35% response rate. A total of 68(90.7%) students agreed that wide knowledge area and clinical skills were covered in the exam. Over 80% of the students saw that OSCE besides it provided them with an opportunity to learn real life scenario, it was well administered and run in the faculty and better organized compared to a previous pilot OSCE (68%). Around 77% of the students saw that 7 minutes time allocated per station was adequate, while a close percentage also agreed that standardized patients were competent in their role playing. Majority of students though they identify that OSCEs highlighted areas of weakness in their skills and knowledge but still disagree with incorporating OSCEs marks into final marks and thus prefer it as an formative assessment. Conclusions: Students highly perceived the exam feeling that it is more resembles actual practice providing them with self-confidence, and more clearly their defects and what they need to improve regarding both skills and knowledge. They saw OSCEs as being a beneficial formative assessment that should not be included as marks into finals.

The Hitman Study

2010 ◽  
Vol 15 (2) ◽  
pp. 99-108 ◽  
Author(s):  
Christopher J. Ferguson ◽  
Stephanie M. Rueda
Keyword(s):  
Experimental Study ◽  
Young Adults ◽  
Aggressive Behavior ◽  
Video Game ◽  
Real Life ◽  
Mood Management ◽  
Video Game Play ◽  
Video Game Playing ◽  
Violent Video Game ◽  
The Social

This article explores commonly discussed theories of violent video game effects: the social learning, mood management, and catharsis hypotheses. An experimental study was carried out to examine violent video game effects. In this study, 103 young adults were given a frustration task and then randomized to play no game, a nonviolent game, a violent game with good versus evil theme (i.e., playing as a good character taking on evil), or a violent game in which they played as a “bad guy.” Results indicated that randomized video game play had no effect on aggressive behavior; real-life violent video game-playing history, however, was predictive of decreased hostile feelings and decreased depression following the frustration task. Results do not support a link between violent video games and aggressive behavior, but do suggest that violent games reduce depression and hostile feelings in players through mood management.

PENERAPAN FINITE STATE MACHINE UNTUK PENGENDALIAN ANIMASI PADA VIDEO GAME RPG NUSANTARA LEGACY

2018 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Mustofa Mustofa ◽  
Sidiq Sidiq ◽  
Eva Rahmawati
Keyword(s):  
Life Cycle ◽  
Video Game ◽  
Finite State Machine ◽  
Role Playing ◽  
State Machine ◽  
Game Development ◽  
Development Life Cycle ◽  
Finite State ◽  
Role Playing Game

Perkembangan dunia yang dinamis mendorong percepatan perkembangan teknologi dan informasi. Dengan dorongan tersebut komputer yang dulunya dibuat hanya untuk membantu pekerjaan manusia sekarang berkembang menjadi sarana hiburan, permainan, komunikasi dan lain sebagainya. Dalam sektor hiburan salah satu industri yang sedang menjadi pusat perhatian adalah industri video game. Begitu banyaknya produk video game asing yang masuk ke dalam negeri ini memberikan tantangan kepada bangsa ini. Tentunya video game asing yang masuk ke negara ini membawa banyak unsur kebudayaan negara lain. Ini semakin membuat kebudayaan nusantara semakin tergeserkan dengan serangan kebudayaan asing melalui berbagai media. Maka dari itu peneliti mencoba untuk menerapkan Finite State Machine dalam merancang sebuah video game RPG (Role-Playing game) yang memperkenalkan kebudayaan. Dalam perancangan video game ini peneliti menggunakan metode GDLC(Game Development Life Cycle) agar penelitian ini berjalan secara sistematis. Dalam suatu perancangan video game tedapat banyak elemen, pada penelitian ini penulis lebih fokus pada pengendalian animasi karakter yang dimainkan pada video game ini. Dari perancangan yang dilakukan, disimpulkan bahwa Finite State Machine dapat digunakan untuk pengendalian animasi yang baik pada video game RPG. Diharapkan video game ini dapat menjadi salah satu media untuk mengenalkan kebudayaan nusantara

Reaction-based Enumeration, Active Learning, and Free Energy Calculations to Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin Dependent Kinase 2 Inhibitors

2019 ◽  
Author(s):  
Kyle Konze ◽  
Pieter Bos ◽  
Markus Dahlgren ◽  
Karl Leswing ◽  
Ivan Tubert-Brohman ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Active Learning ◽  
Large Scale ◽  
Chemical Space ◽  
Population Based ◽  
Free Energy Calculations ◽  
Computational Technique ◽  
Cyclin Dependent Kinase ◽  
Energy Calculations

We report a new computational technique, PathFinder, that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. Coupling PathFinder with active learning and cloud-based free energy calculations allows for large-scale potency predictions of compounds on a timescale that impacts drug discovery. The process is further accelerated by using a combination of population-based statistics and active learning techniques. Using this approach, we rapidly optimized R-groups and core hops for inhibitors of cyclin-dependent kinase 2. We explored greater than 300 thousand ideas and identified 35 ligands with diverse commercially available R-groups and a predicted IC<sub>50</sub> < 100 nM, and four unique cores with a predicted IC<sub>50</sub> < 100 nM. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

Reaction-based Enumeration, Active Learning, and Free Energy Calculations to Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin Dependent Kinase 2 Inhibitors

2019 ◽  
Author(s):  
Kyle Konze ◽  
Pieter Bos ◽  
Markus Dahlgren ◽  
Karl Leswing ◽  
Ivan Tubert-Brohman ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Active Learning ◽  
Large Scale ◽  
Chemical Space ◽  
Population Based ◽  
Free Energy Calculations ◽  
Computational Technique ◽  
Cyclin Dependent Kinase ◽  
Energy Calculations

We report a new computational technique, PathFinder, that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. Coupling PathFinder with active learning and cloud-based free energy calculations allows for large-scale potency predictions of compounds on a timescale that impacts drug discovery. The process is further accelerated by using a combination of population-based statistics and active learning techniques. Using this approach, we rapidly optimized R-groups and core hops for inhibitors of cyclin-dependent kinase 2. We explored greater than 300 thousand ideas and identified 35 ligands with diverse commercially available R-groups and a predicted IC<sub>50</sub> < 100 nM, and four unique cores with a predicted IC<sub>50</sub> < 100 nM. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

Gambling-like video game practices: A cross-sectional study of links with problem gambling and disordered gaming

2019 ◽  
Author(s):  
David Zendle
Keyword(s):  
Video Games ◽  
Problem Gambling ◽  
Video Game ◽  
Large Scale ◽  
Significant Degree ◽  
Cross Sectional Study ◽  
Video Gaming ◽  
Cross Sectional ◽  
Streaming Services ◽  
Clinically Significant

A variety of practices have recently emerged which are related to both video games and gambling. Most prominent of these are loot boxes. However, a broad range of other activities have recently emerged which are also related to both gambling and video games: esports betting, real-money video gaming, token wagering, social casino play, and watching videos of both loot box opening and gambling on game streaming services like Twitch.Whilst a nascent body of research has established the robust existence of a relationship between loot box spending and both problem gambling and disordered gaming, little research exists which examines whether similar links may exist for the diverse practices outlined above. Furthermore, no research has thus far attempted to estimate the prevalence of these activities.A large-scale survey of a representative sample of UK adults (n=1081) was therefore conducted in order to investigate these issues. Engagement in all measured forms of gambling-like video game practices were significantly associated with both problem gambling and disordered gaming. An aggregate measure of engagement was associated with both these outcomes to a clinically significant degree (r=0.23 and r=0.43). Engagement in gambling-like video game practices appeared widespread, with a 95% confidence interval estimating that 16.3% – 20.9% of the population engaged in these activities at least once in the last year. Engagement in these practices was highly inter-correlated: Individuals who engaged in one practice were likely to engage in several more.Overall, these results suggest that the potential effects of the blurring of lines between video games and gambling should not primarily be understood to be due to the presence of loot boxes in video games. They suggest the existence of a convergent ecosystem of gambling-like video game practices, whose causal relationships with problem gambling and disordered gaming are currently unclear but must urgently be investigated.

RELEVANSI PEMBELAJARAN IPA DAN PAI HUMANIS

Edupedia ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 13-21
Author(s):  
Subyanto ◽  
Kurniyatul Faizah
Keyword(s):  
Social Interaction ◽  
Real Life ◽  
Problem Based Learning ◽  
Role Playing ◽  
Natural Sciences ◽  
Discovery Learning ◽  
Islamic Education ◽  
Transfer Of Knowledge ◽  
The Real ◽  
Team Research

In Natural Sciences (IPA) there are three aspects of learning, they arenatural sciences as product, process, and strengthening attitudes. This natural sciences learning classification found relevance with Islamic education learning in the aspect of fiqh, theseare fiqh as a product and fiqh as a process. The types of humanistlearning arelearning other than as a product, because this learning is not just transfer of knowledge without rationality, so that the lesson is not able to take part in the real life of humanity. In the implementation, humanist learning can be carried out using several scientific approaches such as problem based learning, discovery learning, social interaction, role playing, team research, and other forms that are oriented to students involvementdirectly.

scholarly journals Neural methods for effective, efficient, and exposure-aware information retrieval

2021 ◽  
Vol 55 (1) ◽  
pp. 1-2
Author(s):  
Bhaskar Mitra
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Large Scale ◽  
Web Search ◽  
Real Life ◽  
Inverted Index ◽  
Information Need ◽  
Product Model ◽  
Performance Improvements ◽  
Deep Model

Neural networks with deep architectures have demonstrated significant performance improvements in computer vision, speech recognition, and natural language processing. The challenges in information retrieval (IR), however, are different from these other application areas. A common form of IR involves ranking of documents---or short passages---in response to keyword-based queries. Effective IR systems must deal with query-document vocabulary mismatch problem, by modeling relationships between different query and document terms and how they indicate relevance. Models should also consider lexical matches when the query contains rare terms---such as a person's name or a product model number---not seen during training, and to avoid retrieving semantically related but irrelevant results. In many real-life IR tasks, the retrieval involves extremely large collections---such as the document index of a commercial Web search engine---containing billions of documents. Efficient IR methods should take advantage of specialized IR data structures, such as inverted index, to efficiently retrieve from large collections. Given an information need, the IR system also mediates how much exposure an information artifact receives by deciding whether it should be displayed, and where it should be positioned, among other results. Exposure-aware IR systems may optimize for additional objectives, besides relevance, such as parity of exposure for retrieved items and content publishers. In this thesis, we present novel neural architectures and methods motivated by the specific needs and challenges of IR tasks. We ground our contributions with a detailed survey of the growing body of neural IR literature [Mitra and Craswell, 2018]. Our key contribution towards improving the effectiveness of deep ranking models is developing the Duet principle [Mitra et al., 2017] which emphasizes the importance of incorporating evidence based on both patterns of exact term matches and similarities between learned latent representations of query and document. To efficiently retrieve from large collections, we develop a framework to incorporate query term independence [Mitra et al., 2019] into any arbitrary deep model that enables large-scale precomputation and the use of inverted index for fast retrieval. In the context of stochastic ranking, we further develop optimization strategies for exposure-based objectives [Diaz et al., 2020]. Finally, this dissertation also summarizes our contributions towards benchmarking neural IR models in the presence of large training datasets [Craswell et al., 2019] and explores the application of neural methods to other IR tasks, such as query auto-completion.

scholarly journals Multi-GPU approach to global induction of classification trees for large-scale data mining

2021 ◽  
Author(s):  
Krzysztof Jurczuk ◽  
Marcin Czajkowski ◽  
Marek Kretowski
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Real Life ◽  
Population Based ◽  
Tree Structure ◽  
Global Approach ◽  
Data Parallel ◽  
Large Scale Data ◽  
The Impact ◽  
Scale Data

AbstractThis paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers. It searches for the tree structure and tests simultaneously and thus gives improvements in the prediction and size of resulting classifiers in many situations. However, it is the population-based and iterative approach that can be too computationally demanding to apply for big data mining directly. The paper demonstrates that this barrier can be overcome by smart distributed/parallel processing. Moreover, we ask the question whether the global approach can truly compete with the greedy systems for large-scale data. For this purpose, we propose a novel multi-GPU approach. It incorporates the knowledge of global DT induction and evolutionary algorithm parallelization together with efficient utilization of memory and computing GPU’s resources. The searches for the tree structure and tests are performed simultaneously on a CPU, while the fitness calculations are delegated to GPUs. Data-parallel decomposition strategy and CUDA framework are applied. Experimental validation is performed on both artificial and real-life datasets. In both cases, the obtained acceleration is very satisfactory. The solution is able to process even billions of instances in a few hours on a single workstation equipped with 4 GPUs. The impact of data characteristics (size and dimension) on convergence and speedup of the evolutionary search is also shown. When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.

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