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.

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 Prof. Watson: A Pedagogic Conversational Agent to Teach Programming in Primary Education

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 84
Author(s):  
Yeves-Martínez ◽  
Pérez-Marín
Keyword(s):  
Primary Education ◽  
Research Interest ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Global Trend ◽  
Alternative Procedures

Teaching programming in Primary Education has recently attracted a great deal of research interest. One global trend is using multimedia languages such as Scratch. However, it was our belief that by using Pedagogic Conversational Agents that dialog with the students, they have to think how to solve given problems and to write the code to solve them. In particular, the MECOPROG methodology was applied to design the student-agent dialog in Prof. Watson. An experiment with 19 students (11–12 years old) was carried out proving the viability of the approach, which shed some light into alternative procedures to teach programming in Primary Education.

A Brief Discussion on Incentives and Barriers to Computational Thinking Education

2022 ◽  
pp. 253-269
Author(s):  
Hüseyin Özçınar
Keyword(s):  
Computer Science ◽  
Programming Language ◽  
Primary Education ◽  
Computer Programming ◽  
Computational Thinking ◽  
Thinking Skill ◽  
Logo Programming ◽  
Basic Concepts ◽  
The 1960S ◽  
Algorithmic Thinking

The idea that computational thinking or algorithmic thinking should be taught to everyone dates back to the 1960s. First in 1960s, Alan Perlis argued that computer programming should be taught to everyone because it can be used as a mental tool for understanding and solving every kind of problem. In 1980s, under the leadership of Seymour Papert, students at the level of primary education were attempted to be taught LOGO programming language with the aim of gaining procedural thinking skill. After the publication of Jeannette Wing's “computational thinking” in Communications of the ACM in 2006, the idea that the basic concepts of computer science should be learned by all was started to be debated widely again. In the present paper, the justifications for teaching computational thinking and applicability of teaching computational thinking within the context of existing conditions will be discussed.

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.

A Procedure to Engage Children in the Morphological and Syntax Analysis of Pedagogic Conversational Agent-Generated Sentences to Study Language

2015 ◽  
Vol 5 (2) ◽  
pp. 23-42
Author(s):  
Diana Pérez Marín
Keyword(s):  
Computer Applications ◽  
Computer Assisted ◽  
Conversational Agent ◽  
User Centered Design ◽  
Conversational Agents ◽  
Immediate Feedback ◽  
Syntax Analysis ◽  
Computer Teaching ◽  
Different Levels ◽  
Syntactical Analysis

Pedagogic Conversational Agents are computer applications that interact with the students in natural language. They usually focus the dialogue on a certain topic under study. In this paper, the authors propose the possibility of children studying morphology and syntax by using a Pedagogic Conversational Agent. The main benefit is that the agent is able to generate an infinite number of sentences and, it automatically generates the morphological and syntactical analysis from a given grammar. That way, students can practise with all the sentences they need, receive immediate feedback with automatic evaluation, at their own rhythm and, the level of difficulty can be adapted to their particular competence of analysis. Given the originality of this new computer assisted learning initiative, the authors have devised a procedure to engage the students in the dialogue with the agent to carry out the morphological and syntax analysis at five different levels of difficulty, and test the validity of the approach with a limited number of users according to the principles of User-Centered Design. The results gathered provide evidence of the goodness of the procedure and, they encourage us to keep working on this promising field of using pedagogic agents as computer teaching language assistants.

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.

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 Methodology to Design and Evaluate Agents

2018 ◽  
pp. 63-87
Author(s):  
Silvia Tamayo-Moreno ◽  
Diana Pérez-Marín
Keyword(s):  
Natural Language ◽  
Infinite Number ◽  
Computer Applications ◽  
Automatic Evaluation ◽  
Conversational Agents ◽  
Immediate Feedback ◽  
Level Of Difficulty ◽  
Syntactical Analysis

Pedagogic conversational agents are computer applications that interact with the students in natural language. They usually focus the dialogue on a certain topic under study. In this chapter, the authors propose the possibility of designing and evaluating agents according to a generic methodology. In particular, the methodology called MEDIE was applied to a study language agent. The main benefit of the study language agent called Lingu is that it is able to generate an infinite number of sentences, and it automatically generates the morphological and syntactical analysis from a given grammar. That way, students can practice with all the sentences they need, receive immediate feedback with automatic evaluation at their own rhythm, and the level of difficulty can be adapted to their particular competence of analysis. To be able to extend Lingu to different schools and needs, MEDIE has been applied as described 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.

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