scholarly journals Repurposing Case-Based Learning to a Conversational Agent for Healthcare Cybersecurity

2021 ◽  
Author(s):  
Matthew Pears ◽  
James Henderson ◽  
Stathis Th. Konstantinidis
Keyword(s):  
Educational Technology ◽  
Natural Language ◽  
Best Practice ◽  
Critical Appraisal ◽  
Heuristic Evaluation ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Delivery Methods ◽  
Case Based Learning ◽  
Case Based

A crucial factor for successful cybersecurity education is how information is communicated to learners. Case-based learning of common cybersecurity issues has been shown to improve human behaviour for prevention. However, some delivery methods prevent realistic critical appraisal and reflection of awareness. Conversational agents can scaffold healthcare workers’ understanding and promote deterrence strategies. The challenges of repurposing material to create a case-based agent were explored, and the ASPIRE process was modified. Heuristic evaluation from 10 experts in innovative educational technology resulted in the desired outcomes of usability, however Natural Language Understanding improvements were needed. Discussion of best practice when repurposing into conversational agents suggested modification of the ASPIRE process is feasible for future use.

A Procedure to Create a Pedagogic Conversational Agent in Secondary Physics and Chemistry Education

2013 ◽  
Vol 9 (4) ◽  
pp. 94-112 ◽  
Author(s):  
Diana Pérez-Marín ◽  
Antonio Boza
Keyword(s):  
Natural Language ◽  
Chemistry Education ◽  
Teaching Method ◽  
Computer Applications ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Innovative Teaching ◽  
Language Support ◽  
Teachers And Students ◽  
Innovative Teaching Method

Pedagogic Conversational Agents are computer applications that can interact with students in natural language. They have been used with satisfactory results on the instruction of several domains. The authors believe that they could also be useful for the instruction of Secondary Physics and Chemistry Education. Therefore, in this paper, the authors present a procedure to create an agent for that domain. First, teachers have to introduce the exercises with their correct answers. Secondly, students will be presented the exercises, and if the students know the answer, and if it is correct, more difficult exercises will be presented. Otherwise, step-by-step natural language support will be provided to guide the student towards the solution. It is the authors’ hypothesis that this innovative teaching method will be satisfactory and useful for teachers and students, and that by following the procedure more computer programmers can be encouraged to develop agents for other domains to be used by teachers and students at class.

scholarly journals Modelling a Conversational Agent with Complex Emotional Intelligence

2020 ◽  
Vol 34 (10) ◽  
pp. 13710-13711
Author(s):  
Billal Belainine ◽  
Fatiha Sadat ◽  
Hakim Lounis
Keyword(s):  
Emotional Intelligence ◽  
Natural Language ◽  
Natural Language Understanding ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Language Understanding ◽  
Leading Role ◽  
Complex Emotions

Chatbots or conversational agents have enjoyed great popularity in recent years. They surprisingly perform sensitive tasks in modern societies. However, despite the fact that they offer help, support, and fellowship, there is a task that is not yet mastered: dealing with complex emotions and simulating human sensations. This research aims to design an architecture for an emotional conversation agent for long-text conversations (multi-turns). This agent is intended to work in areas where the analysis of users feelings plays a leading role. This work refers to natural language understanding and response generation.

scholarly journals Conversational agents in healthcare: a systematic review

2018 ◽  
Vol 25 (9) ◽  
pp. 1248-1258 ◽  
Author(s):  
Liliana Laranjo ◽  
Adam G Dunn ◽  
Huong Ly Tong ◽  
Ahmet Baki Kocaballi ◽  
Jessica Chen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Natural Language ◽  
Depression Symptoms ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Cross Sectional ◽  
Evaluation Measures ◽  
Health Related ◽  
Quasi Experimental ◽  
Language Input

Abstract Objective Our objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes. Methods We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen’s kappa measured inter-coder agreement. Results The database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies. Conclusions The use of conversational agents with unconstrained natural language input capabilities for health-related purposes is an emerging field of research, where the few published studies were mainly quasi-experimental, and rarely evaluated efficacy or safety. Future studies would benefit from more robust experimental designs and standardized reporting. Protocol Registration The protocol for this systematic review is registered at PROSPERO with the number CRD42017065917.

scholarly journals Conversational Agent Research Toolkit: An alternative for creating and managing chatbots for experimental research

2019 ◽  
Author(s):  
Theo Araujo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Experimental Research ◽  
Experimental Studies ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Communication Environment

Conversational agents in the form of chatbots available in messaging platforms are gaining increasing relevance in our communication environment. Based on natural language processing and generation techniques, they are built to automatically interact with users in several contexts. We present here a tool, the Conversational Agent Research Toolkit (CART), aimed at enabling researchers to create conversational agents for experimental studies. CART integrates existing APIs frequently used in practice and provides functionality that allows researchers to create and manage multiple versions of a chatbot to be used as stimuli in experimental studies. This paper provides an overview of the tool and provides a step-by-step tutorial of to design an experiment with a chatbot.

How to Create a Pedagogic Conversational Agent for Teaching Computer Science

2019 ◽  
pp. 114-134
Author(s):  
José Miguel Ocaña ◽  
Elizabeth K. Morales-Urrutia ◽  
Diana Pérez-Marín ◽  
Silvia Tamayo-Moreno
Keyword(s):  
Natural Language ◽  
Computer Science ◽  
Primary Education ◽  
Computational Thinking ◽  
Computer Applications ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Teacher Team

Pedagogic conversational agents are computer applications that can interact with students in natural language. They have been used with satisfactory results on the instruction of several domains. The authors believe that they could also be useful for the instruction of computer science programming. Therefore, in this chapter, the MEDIE methodology is described to explain how to create an agent to teach programming to primary education children and develop their computational thinking. The main steps are to communicate with the teacher team, to validate the interface, and to validate the functionality, practical sessions, and evaluation. The first two steps are covered in this chapter.

scholarly journals Conversational Agent Research Toolkit : An alternative for creating and managing chatbots for experimental research1

2020 ◽  
Vol 2 (1) ◽  
pp. 35-51 ◽  
Author(s):  
Theo Araujo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Experimental Studies ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Communication Environment

Abstract Conversational agents in the form of chatbots available in messaging platforms are gaining increasing relevance in our communication environment. Based on natural language processing and generation techniques, they are built to automatically interact with users in several contexts. We present here a tool, the Conversational Agent Research Toolkit (CART), aimed at enabling researchers to create conversational agents for experimental studies. CART integrates existing APIs frequently used in practice and provides functionality that allows researchers to create and manage multiple versions of a chatbot to be used as stimuli in experimental studies. This paper provides an overview of the tool and provides a step-by-step tutorial of to design an experiment with a chatbot.

Improving Case-Based Learning and Transfer Through Emotionally Rich Cases

2012 ◽  
Author(s):  
Chase E. Thiel ◽  
Lauren N. Harkrider ◽  
Shane Connelly ◽  
Lynn D. Devenport ◽  
Juandre Peacock
Keyword(s):  
Case Based Learning ◽  
Case Based

Application and Evaluation of Case-Based Learning as a Part of Early Clinical Exposure for Undergraduate Medical Education Program

2020 ◽  
Vol 5 (08) ◽  
pp. 284-288
Author(s):  
Vandana Daulatabad ◽  
Prafull K. ◽  
Dr. Surekha S. Kadadi-Patil ◽  
Ramesh S. Patil
Keyword(s):  
Medical Education ◽  
Research Centre ◽  
Muscle Physiology ◽  
Case Scenario ◽  
Clinical Exposure ◽  
Clinical Scenarios ◽  
Case Based Learning ◽  
Nerve Muscle ◽  
Case Based ◽  
Early Clinical Exposure

Introduction: Medical Education is witnessing a significant transition and global shift towards competency based medical education (CBME) which includes early clinical exposure (ECE) program to help students apply and correlate principles of preclinical subjects with clinical scenarios, in various forms and in a variety of settings. One of the easy and feasible methods of ECE being Case Based Learning (CBL), our study aimed to design a case scenario and to evaluate impact of case base learning as a part of ECE module in first year undergraduate medical teaching program in nerve muscle physiology. Methods: The present study was conducted in 96 students at Ashwini Rural Medical College Hospital and Research Centre, Solapur after obtaining institutional ethics committee approval. 3 hrs session of CBL was conducted for a case scenario on myasthenia gravis in the nerve muscle physiology module. The students’ responses on pre-test, post-test and their insights regarding the CBL were taken through a pre validated questionnaire using 5-point Likert scale. Results: High impact of CBL was seen as significant improvement in student’s performance. Maximum students felt CBL to be easy method of learning and was highly appreciated through their feedback. Conclusion: CBL was found to have positive impact on understanding and perception of topic. CBL helped students to understand, evaluate, analyze, diagnose and interpret the case, paving them towards newer approach of self-directed and vertical integrated learning. CBL is easier, feasible an effective method among other early clinical exposure methods as it involves students in deeper and self-directed active learning, encouraging and promoting them to reach higher levels of cognitive domain of Bloom’s taxonomy. This method will be very useful in its practical implementation during online classes for ECE module in the threat of COVID 19 situation as well.

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