Implementing remote collaboration in a virtual patient platform – enabling students and physicians to learn collaborative clinical reasoning (Preprint)

2020 ◽  
Author(s):  
Jan Kiesewetter ◽  
Inga Hege ◽  
Michael Sailer ◽  
Elisabeth Bauer ◽  
Claudia Schulz ◽  
...  
Keyword(s):  
Clinical Reasoning ◽  
Application Programming Interface ◽  
Virtual Patient ◽  
Virtual Patients ◽  
Remote Collaboration ◽  
Student Collaboration ◽  
Collaborative Tool ◽  
Study Results ◽  
Application Programming ◽  
Set Up

BACKGROUND Learning with virtual patients is highly popular for fostering clinical reasoning in medical education. However, little learning with virtual patients is done collaboratively, despite the potential learning benefits of collaborative vs. individual learning. OBJECTIVE In this article, we describe the rationale behind the implementation of student collaboration in the CASUS virtual patient platform. METHODS The SimpleWebRTC library of andYet was used to implement the collaborative tool. It provided a basis for the conferencing platform and could be adapted to include features such as video communication and screensharing. An additional text chat was created based on the message protocol of the SimpleWebRTC library. We implemented a user interface for educators to set up and configure the collaboration. Educators can configure video, audio, and text-based chat communication, which are known to promote effective learning. RESULTS We tested the tool in a sample of 137 students working on virtual patients. The study results indicate that students successfully diagnosed 53% (SD = 26%) of the patients when working alone and 71% (SD= 20%) when collaborating using the tool (p < .05, eta2=.12). A usability questionnaire for the study sample shows a usability score of 82.16 (SD = 1.31), a B+ grade. CONCLUSIONS The approach provides a technical framework for collaboration that can be used with the CASUS virtual patient system. Additionally, the application programming interface is generic, so that the setup can also be used with other learning management systems. The collaborative tool helps students diagnose virtual patients and results in a good overall usability of CASUS. Using learning analytics, we are able to track students’ progress in content knowledge and collaborative knowledge and guide them through a virtual patient curriculum designed to teach both. More broadly, the collaborative tool provides an array of new possibilities for researchers and educators alike to design courses, collaborative homework assignments, and research questions for collaborative learning.

User identification across online social networks in practice: Pitfalls and solutions

2016 ◽  
Vol 44 (3) ◽  
pp. 377-391 ◽  
Author(s):  
Azadeh Esfandyari ◽  
Matteo Zignani ◽  
Sabrina Gaito ◽  
Gian Paolo Rossi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Full Range ◽  
Application Programming Interface ◽  
User Identification ◽  
Application Programming ◽  
Test Sets ◽  
Set Up ◽  
Different Levels ◽  
Programming Interface

To take advantage of the full range of services that online social networks (OSNs) offer, people commonly open several accounts on diverse OSNs where they leave lots of different types of profile information. The integration of these pieces of information from various sources can be achieved by identifying individuals across social networks. In this article, we address the problem of user identification by treating it as a classification task. Relying on common public attributes available through the official application programming interface (API) of social networks, we propose different methods for building negative instances that go beyond usual random selection so as to investigate the effectiveness of each method in training the classifier. Two test sets with different levels of discrimination are set up to evaluate the robustness of our different classifiers. The effectiveness of the approach is measured in real conditions by matching profiles gathered from Google+, Facebook and Twitter.

scholarly journals How to Build Your Own ASP-based System?!

2021 ◽  
pp. 1-63
Author(s):  
ROLAND KAMINSKI ◽  
JAVIER ROMERO ◽  
TORSTEN SCHAUB ◽  
PHILIPP WANKO
Keyword(s):  
Problem Solving ◽  
Application Programming Interface ◽  
Ease Of Use ◽  
Cross Sectional ◽  
Difference Constraints ◽  
Application Programming ◽  
Set Up ◽  
The One ◽  
High Degree ◽  
Abstract Syntax Trees

Abstract Answer Set Programming, or ASP for short, has become a popular and sophisticated approach to declarative problem solving. Its popularity is due to its attractive modeling-grounding-solving workflow that provides an easy approach to problem solving, even for laypersons outside computer science. However, in contrast to ASP’s ease of use, the high degree of sophistication of the underlying technology makes it even hard for ASP experts to put ideas into practice whenever this involves modifying ASP’s machinery. For addressing this issue, this tutorial aims at enabling users to build their own ASP-based systems. More precisely, we show how the ASP system clingo can be used for extending ASP and for implementing customized special-purpose systems. To this end, we propose two alternatives. We begin with a traditional AI technique and show how metaprogramming can be used for extending ASP. This is a rather light approach that relies on clingo’s reification feature to use ASP itself for expressing new functionalities. The second part of this tutorial uses traditional programming (in Python) for manipulating clingo via its application programming interface. This approach allows for changing and controlling the entire model-ground-solve workflow of ASP. Central to this is clingo’s new Application class that allows us to draw on clingo’s infrastructure by customizing processes similar to the one in clingo. For instance, we may apply manipulations to programs’ abstract syntax trees, control various forms of multi-shot solving, and set up theory propagators for foreign inferences. A cross-sectional structure, spanning meta as well as application programming, is clingo’s intermediate format, aspif, that specifies the interface among the underlying grounder and solver. We illustrate the aforementioned concepts and techniques throughout this tutorial by means of examples and several nontrivial case studies. In particular, we show how clingo can be extended by difference constraints and how guess-and-check programming can be implemented with both meta and application programming.

scholarly journals Debriefing of virtual patient encounters: Systematic collection of nursing students clinical reasoning activities

2015 ◽  
Author(s):  
Carina Georg ◽  
Elisabet Welin Henriksson ◽  
Maria Jirwe ◽  
Johanna Ulfvarson ◽  
Nabil Zary
Keyword(s):  
Nursing Education ◽  
Nursing Students ◽  
Clinical Reasoning ◽  
Clinical Judgment ◽  
Virtual Patient ◽  
Learning Activity ◽  
Virtual Patients ◽  
Feed Forward ◽  
Undergraduate Nursing ◽  
Starting Point

Background. Studies have shown that nursing students have challenges in translating and applying their theoretical knowledge in a clinical context. Virtual patients (VPs) have been proposed as an adequate learning and assessment activity to improve clinical reasoning. Although feedback and debriefing are essential aspects to foster learning in medical simulation, few studies have explored systematic and theory anchored ways of supporting feed forward and debriefing based on student activity collected in a systematic manner. Objective. The aim of this study was to develop a systematic approach for collecting the nursing students’ clinical reasoning artifacts as they encounter virtual patients. Method. The Outcome-Present-State-Test (OPT) model for clinical reasoning was used as the starting point since it is an internationally common model used by faculty to plan for and design learning activities in nursing education (Pesut & Herman, 1999). Two virtual patients were developed using the virtual patient nursing design model vpNDM (Georg &Zary, 2014). Nighty-five participants from undergraduate nursing education encountered the VPs and the intervention was composed of the exploration of methods for tracking and collecting the participants’ clinical reasoning artifacts. Results. An instrument to collect the students’ clinical reasoning was developed. Artifacts are collected during the whole virtual patient encounter. The aspects collected are related to clinical judgment, nursing action, outcome and present states, cue logic and the client in context. The empirical demonstrated that the instrument was able to collect and expose quantitative and qualitative aspects of the students’ clinical reasoning. Conclusions. A method to systematically collect aspects of clinical reasoning during a virtual patient driven learning activity would allow purposeful feed forward and provide the necessary information for constructive debriefing sessions.

scholarly journals Debriefing of virtual patient encounters: Systematic collection of nursing students clinical reasoning activities

2015 ◽  
Author(s):  
Carina Georg ◽  
Elisabet Welin Henriksson ◽  
Maria Jirwe ◽  
Johanna Ulfvarson ◽  
Nabil Zary
Keyword(s):  
Nursing Education ◽  
Nursing Students ◽  
Clinical Reasoning ◽  
Clinical Judgment ◽  
Virtual Patient ◽  
Learning Activity ◽  
Virtual Patients ◽  
Feed Forward ◽  
Undergraduate Nursing ◽  
Starting Point

Background. Studies have shown that nursing students have challenges in translating and applying their theoretical knowledge in a clinical context. Virtual patients (VPs) have been proposed as an adequate learning and assessment activity to improve clinical reasoning. Although feedback and debriefing are essential aspects to foster learning in medical simulation, few studies have explored systematic and theory anchored ways of supporting feed forward and debriefing based on student activity collected in a systematic manner. Objective. The aim of this study was to develop a systematic approach for collecting the nursing students’ clinical reasoning artifacts as they encounter virtual patients. Method. The Outcome-Present-State-Test (OPT) model for clinical reasoning was used as the starting point since it is an internationally common model used by faculty to plan for and design learning activities in nursing education (Pesut & Herman, 1999). Two virtual patients were developed using the virtual patient nursing design model vpNDM (Georg &Zary, 2014). Nighty-five participants from undergraduate nursing education encountered the VPs and the intervention was composed of the exploration of methods for tracking and collecting the participants’ clinical reasoning artifacts. Results. An instrument to collect the students’ clinical reasoning was developed. Artifacts are collected during the whole virtual patient encounter. The aspects collected are related to clinical judgment, nursing action, outcome and present states, cue logic and the client in context. The empirical demonstrated that the instrument was able to collect and expose quantitative and qualitative aspects of the students’ clinical reasoning. Conclusions. A method to systematically collect aspects of clinical reasoning during a virtual patient driven learning activity would allow purposeful feed forward and provide the necessary information for constructive debriefing sessions.

scholarly journals Multiplexed Chat Application

2013 ◽  
pp. 209-213
Author(s):  
A. Vivekanand ◽  
B. Sivaiah ◽  
SK. Khaja Shareef
Keyword(s):  
Application Programming Interface ◽  
Transport Layer ◽  
Network Communication ◽  
System Call ◽  
Network Programming ◽  
Peer Communication ◽  
Transport Layer Protocol ◽  
Application Programming ◽  
Set Up ◽  
Programming Interface

Multiplexing in socket programming is the capability of handling input and output from different I/O channels. we can multiplex UDP and TCP sockets to build multiplexed chat application UDP is a connectionless transport layer protocol. Since TCP doesn't provide the feature of Multicasting UDP is a widely used protocol to implement it. UDP's stateless nature is useful for servers that answer small queries for large number of clients. Socket network programming is one of the most popular technologies used to build a chat application and establishing network communication between systems. Socket programming helps to implement the bottom level of network communication, using Application Programming Interface (API). In this paper we propose a method to make a chat room using socket based on User Datagram Protocol (UDP) which enables the feature of acknowledgments after every message sent and poll system call[1]. It is equivalent to a dedicated chat server having a Server and n number of Clients. After client and server set up to connect, you can achieve many machines to communicate through peer to peer communication, multicasting and File sending. During communication taking place there might be different system and network failures occurring, which we have discussed and proposed a convenient solution for that.

scholarly journals Creating Web APIs with Python and Flask

2018 ◽  
Author(s):  
Patrick Smyth
Keyword(s):  
Application Programming Interface ◽  
Application Programming ◽  
Set Up ◽  
Programming Interface

Learn how to set up a basic Application Programming Interface (API) to make your data more accessible to users. This lesson also discusses principles of API design and the benefits of APIs for digital projects.

scholarly journals Putting the ghost in the machine: exploring human-machine hybrid virtual patient systems for health professional education

2016 ◽  
Author(s):  
David Topps ◽  
Michelle L Cullen ◽  
Nishan Sharma ◽  
Rachel H Ellaway
Keyword(s):  
Health Professional ◽  
Language Processing ◽  
Professional Education ◽  
Virtual Patient ◽  
Interactive Methods ◽  
Research Approach ◽  
Virtual Patients ◽  
Text Input ◽  
Project Description ◽  
Study Results

Background: Virtual patient authoring tools provide a simple means of creating rich and complex online cases for health professional students to explore. However, the responses available to the learner are usually predefined, which limits the utility of virtual patients, both in terms of replayability and adaptability. Using artificial intelligence or natural language processing is expensive and hard to design. This project description lays out an alternative approach to making virtual patients more adaptable and interactive. Methods: Using OpenLabyrinth, an open-source educational research platform, we modified the interface and functionality to provide a human-computer hybrid interface, where a human facilitator can interact with learners from within the online case scenario. Using a design-based research approach, we have iteratively improved our case designs, workflows and scripts and interface designs. The next step is to robustly test this new functionality in action. This report describes the piloting and background as well as the rationale, objectives, software development implications, learning designs, and educational intervention designs for the planned study. Results: The costs and time required to modify the software were much lower than anticipated. Facilitators have been able to handle text input from multiple concurrent learners. Learners were not discouraged waiting for the facilitator to respond. Discussion: The implementation and use of this new technique seems very promising and there are a great many ways in which it might be used for training and assessment purposes. This report also explores the provisional implications arising from the study so far.

scholarly journals Putting the ghost in the machine: exploring human-machine hybrid virtual patient systems for health professional education

2016 ◽  
Author(s):  
David Topps ◽  
Michelle L Cullen ◽  
Nishan Sharma ◽  
Rachel H Ellaway
Keyword(s):  
Health Professional ◽  
Language Processing ◽  
Professional Education ◽  
Virtual Patient ◽  
Interactive Methods ◽  
Research Approach ◽  
Virtual Patients ◽  
Text Input ◽  
Project Description ◽  
Study Results

Background: Virtual patient authoring tools provide a simple means of creating rich and complex online cases for health professional students to explore. However, the responses available to the learner are usually predefined, which limits the utility of virtual patients, both in terms of replayability and adaptability. Using artificial intelligence or natural language processing is expensive and hard to design. This project description lays out an alternative approach to making virtual patients more adaptable and interactive. Methods: Using OpenLabyrinth, an open-source educational research platform, we modified the interface and functionality to provide a human-computer hybrid interface, where a human facilitator can interact with learners from within the online case scenario. Using a design-based research approach, we have iteratively improved our case designs, workflows and scripts and interface designs. The next step is to robustly test this new functionality in action. This report describes the piloting and background as well as the rationale, objectives, software development implications, learning designs, and educational intervention designs for the planned study. Results: The costs and time required to modify the software were much lower than anticipated. Facilitators have been able to handle text input from multiple concurrent learners. Learners were not discouraged waiting for the facilitator to respond. Discussion: The implementation and use of this new technique seems very promising and there are a great many ways in which it might be used for training and assessment purposes. This report also explores the provisional implications arising from the study so far.

scholarly journals Experiential Learning Theory in Serious Gaming to Foster Clinical Reasoning in Orthopedics: Adaptations in Response to COVID-19 era

2020 ◽  
pp. 1-3
Author(s):  
Ayat Eltayar
Keyword(s):  
Experiential Learning ◽  
Learning Theory ◽  
Clinical Reasoning ◽  
Clinical Training ◽  
Virtual Patient ◽  
Learning Cycle ◽  
Virtual Patients ◽  
Experiential Learning Theory ◽  
Serious Gaming ◽  
Face To Face

Clinical reasoning is an important aspect in learning medicine. Due to social distancing in COVID-19 pandemic, clinical training of residents in orthopedic department in Alexandria faculty of medicine (AFM) faced many restrictions. The experiential learning cycle of Kolb was adopted in serious gaming platform. “Mediactiv platform” was used to create a case to teach clinical reasoning for orthopedic residents. Our experience guarantees that Virtual patients and serious gaming platforms can be used to teach clinical reasoning, replacing face to face discussions. AFM is the first medical school in Egypt to use a virtual patient platform to teach clinical reasoning for graduates in orthopedics. Our experience was beneficial as mentioned by staff and trainers.

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