scholarly journals Development of an Instrument to Measure Conceptualizations and Competencies About Conversational Agents on the Example of Smart Speakers

2021 ◽  
Vol 3 ◽  
Author(s):  
Carolin Wienrich ◽  
Astrid Carolus
Keyword(s):  
Digital Literacy ◽  
Basic Assumption ◽  
Conversational Agent ◽  
Data Input ◽  
Conversational Agents ◽  
Validity And Reliability ◽  
Learning Abilities ◽  
Interindividual Differences ◽  
Five Factors ◽  
Explanatory Factor Analysis

The concept of digital literacy has been introduced as a new cultural technique, which is regarded as essential for successful participation in a (future) digitized world. Regarding the increasing importance of AI, literacy concepts need to be extended to account for AI-related specifics. The easy handling of the systems results in increased usage, contrasting limited conceptualizations (e.g., imagination of future importance) and competencies (e.g., knowledge about functional principles). In reference to voice-based conversational agents as a concrete application of AI, the present paper aims for the development of a measurement to assess the conceptualizations and competencies about conversational agents. In a first step, a theoretical framework of “AI literacy” is transferred to the context of conversational agent literacy. Second, the “conversational agent literacy scale” (short CALS) is developed, constituting the first attempt to measure interindividual differences in the “(il) literate” usage of conversational agents. 29 items were derived, of which 170 participants answered. An explanatory factor analysis identified five factors leading to five subscales to assess CAL: storage and transfer of the smart speaker’s data input; smart speaker’s functional principles; smart speaker’s intelligent functions, learning abilities; smart speaker’s reach and potential; smart speaker’s technological (surrounding) infrastructure. Preliminary insights into construct validity and reliability of CALS showed satisfying results. Third, using the newly developed instrument, a student sample’s CAL was assessed, revealing intermediated values. Remarkably, owning a smart speaker did not lead to higher CAL scores, confirming our basic assumption that usage of systems does not guarantee enlightened conceptualizations and competencies. In sum, the paper contributes to the first insights into the operationalization and understanding of CAL as a specific subdomain of AI-related competencies.

scholarly journals The development of Response Strategies Scale (RSS): Validity and reliability studyTepki Stratejileri Ölçeği’nin (TSÖ) geliştirilmesi: Geçerlik ve güvenirlik çalışması

2018 ◽  
Vol 15 (3) ◽  
Author(s):  
Esra Asıcı ◽  
Rengin Karaca
Keyword(s):  
Factor Analysis ◽  
High School Students ◽  
Interpersonal Relations ◽  
English Summary ◽  
Validity And Reliability ◽  
School Students ◽  
Response Strategies ◽  
Five Factors ◽  
Explanatory Factor Analysis ◽  
Confirmatory Factor

In this study it was aimed to develop a scale for determining response strategies to damaging acts of adolescents in interpersonal relations. In line with this aim, a-70-item trial form was constituted based on The Integrated Forgiveness Model suggested by Scobie and Scobie (1998). The study was conducted with 1255 high school students. The explanatory factor analysis revealed a construct with five factors which explains 51.29% variance of total score. These factors were named as “reinterpret self-concept”, “seek retribution” “seek revenge”, “pseudoforgiveness”, “forgiveness”. Item loads ranged from .47 to .82. The results of confirmatory factor analysis confirmed the construct with 28 items and 5 factors (S-BX2=1.66, RMSEA=.05, SRMR=.06, GFI=.90, AGFI=.87, NFI=.94, NNFI=.97, CFI=.98). Cronbach alpha coefficients varied between .65 and .90. In the study of criterion-related validity, it was determined that Response Strategies Scale was positively and significantly related with aggressive behaviors and problem solving subscales of conflict resolution behavior scale. Extended English summary is in the end of Full Text PDF (TURKISH) file.ÖzetBu çalışmada ergenlerin kişilerarası ilişkilerde yaşanan zarar verici eylemlerle başa çıkmada kullandıkları tepki stratejilerini belirlemek için bir ölçme aracının geliştirilmesi amaçlanmıştır. Bu amaçla, Scobie ve Scobie’nin (1998) Bütünleştirilmiş Affetme Modeline dayalı olarak 70 maddelik bir deneme form oluşturulmuştur. Çalışma 1255 lise öğrencisiyle yürütülmüştür. Analizlerde açıklayıcı ve doğrulayıcı faktör analizi, pearson momentler çarpımı korelasyonu, ve Cronbach alfa güvenirlik katsayısıyı teknikleri kullanılmıştır. Açıklayıcı faktör analizi sonuçları toplam varyansın %51.29’unu açıklayan beş faktörlü bir yapı ortaya çıkarmıştır. Bu faktörler “benlik kavramını yeniden yorumlama”, “cezalandırma arayışı”, “intikam arayışı”, “sahte affetme” ve “affetme” olarak adlandırılmıştır. Madde faktör yüklerinin .47 ile .82 arasında değiştiği belirlenmiştir. Doğrulayıcı faktor analizi sonuçları 28 madde ve beş faktörden oluşan yapıyı doğrulamıştır (S-BX2=1.66, RMSEA=.05, SRMR=.06, GFI=.90, AGFI=.87, NFI=.94, NNFI=.97, CFI=.98). Ölçeğin Cronbach alfa iç tutarlık katsayılarının .65 ile .90 arasında değiştiği saptanmıştır. Ölçüt bağıntılı geçerlik çalışmasında, Tepki Stratejileri Ölçeği ile çatışma çözme davranışlarını belirleme ölçeğinin saldırgan davranışlar ve problem çözme davranışları alt boyutları arasında ilişki olduğu belirlenmiştir.

Using Principal Component Scores to Enhance the Validity and Reliability of Big Five Personality Measures

2017 ◽  
Vol 38 (2) ◽  
pp. 83-93
Author(s):  
Jeffrey M. Cucina ◽  
Nicholas L. Vasilopoulos ◽  
Arwen H. DeCostanza
Keyword(s):  
Big Five ◽  
Discriminant Validity ◽  
Reliability And Validity ◽  
Principal Component ◽  
Big Five Personality ◽  
Validity And Reliability ◽  
Scoring Method ◽  
Five Factors ◽  
Big Five Factors ◽  
Component Scores

Abstract. Varimax rotated principal component scores (VRPCS) have previously been offered as a possible solution to the non-orthogonality of scores for the Big Five factors. However, few researchers have examined the reliability and validity of VRPCS. To address this gap, we use a lab study and a field study to investigate whether using VRPCS increase orthogonality, reliability, and criterion-related validity. Compared to the traditional unit-weighting scoring method, the use of VRPCS enhanced the reliability and discriminant validity of the Big Five factors, although there was little improvement in criterion-related validity. Results are discussed in terms of the benefit of using VRPCS instead of traditional unit-weighted sum scores.

Knowledge-Based System supported by Chatbot to assist the Risk Classification Process of Patients in Hospital Emergency care (Preprint)

2021 ◽  
Author(s):  
Marciane Mueller ◽  
Rejane Frozza ◽  
Liane Mählmann Kipper ◽  
Ana Carolina Kessler
Keyword(s):  
Medical Care ◽  
Knowledge Base ◽  
Language Processing ◽  
Emergency Care ◽  
Risk Classification ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Hospital Emergency ◽  
Knowledge Based System ◽  
Knowledge Based

BACKGROUND This article presents the modeling and development of a Knowledge Based System, supported by the use of a virtual conversational agent called Dóris. Using natural language processing resources, Dóris collects the clinical data of patients in care in the context of urgency and hospital emergency. OBJECTIVE The main objective is to validate the use of virtual conversational agents to properly and accurately collect the data necessary to perform the evaluation flowcharts used to classify the degree of urgency of patients and determine the priority for medical care. METHODS The agent's knowledge base was modeled using the rules provided for in the evaluation flowcharts comprised by the Manchester Triage System. It also allows the establishment of a simple, objective and complete communication, through dialogues to assess signs and symptoms that obey the criteria established by a standardized, validated and internationally recognized system. RESULTS Thus, in addition to verifying the applicability of Artificial Intelligence techniques in a complex domain of health care, a tool is presented that helps not only in the perspective of improving organizational processes, but also in improving human relationships, bringing professionals and patients closer. The system's knowledge base was modeled on the IBM Watson platform. CONCLUSIONS The results obtained from simulations carried out by the human specialist allowed us to verify that a knowledge-based system supported by a virtual conversational agent is feasible for the domain of risk classification and priority determination of medical care for patients in the context of emergency care and hospital emergency.

scholarly journals A Modular System Oriented to the Design of Versatile Knowledge Bases for Chatbots

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Giovanni Pilato ◽  
Agnese Augello ◽  
Salvatore Gaglio
Keyword(s):  
Corpus Callosum ◽  
Knowledge Representation ◽  
User Behavior ◽  
Knowledge Bases ◽  
Modular System ◽  
Conversational Agent ◽  
Proof Of Concept ◽  
Conversational Agents ◽  
Specific Domain ◽  
Representation Techniques

The paper illustrates a system that implements a framework, which is oriented to the development of a modular knowledge base for a conversational agent. This solution improves the flexibility of intelligent conversational agents in managing conversations. The modularity of the system grants a concurrent and synergic use of different knowledge representation techniques. According to this choice, it is possible to use the most adequate methodology for managing a conversation for a specific domain, taking into account particular features of the dialogue or the user behavior. We illustrate the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation methodologies and capable of managing different conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, that selects in real time the most adequate chatbot knowledge module to activate.

Validity and Reliability of Internalized Stigma of Mental Illness (Cantonese)

2016 ◽  
Vol 27 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Daniel Kim-Wan Young ◽  
Petrus Y. N. Ng ◽  
Jia-Yan Pan ◽  
Daphne Cheng
Keyword(s):  
Mental Illness ◽  
Reliability And Validity ◽  
Internalized Stigma ◽  
Validity And Reliability ◽  
Chinese Consumers ◽  
Cross Sectional ◽  
People With Mental Illness ◽  
Five Factors ◽  
Stigma Of Mental Illness

Purpose: This study aims to translate and test the reliability and validity of the Internalized Stigma of Mental Illness-Cantonese (ISMI-C). Methods: The original English version of ISMI is translated into the ISMI-C by going through forward and backward translation procedure. A cross-sectional research design is adopted that involved 295 participants randomly drawn from a population of Chinese consumers participated in different kinds of community-based mental health services. Results: Results show that the Cronbach’s α coefficient of the ISMI-C is .93. With regard to validity test, the ISMI-C shows significant and negative correlation with measures on self-esteem and quality of life. Also, an explorative factor analysis yields five factors that are consistent with previous research results. Discussion: This study shows that the ISMI-C is a reliable and valid measure. ISMI-C can facilitate the development of interventions in reducing self-stigma for people with mental illness across Chinese societies.

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 Changes to the Psychiatric Chatbot Landscape: A Systematic Review of Conversational Agents in Serious Mental Illness: Changements du paysage psychiatrique des chatbots: une revue systématique des agents conversationnels dans la maladie mentale sérieuse

2020 ◽  
pp. 070674372096642
Author(s):  
Aditya Nrusimha Vaidyam ◽  
Danny Linggonegoro ◽  
John Torous
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Bipolar Disorder ◽  
Mental Illness ◽  
Serious Mental Illness ◽  
Therapeutic Efficacy ◽  
Digital Tools ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Diagnostic Quality

Objective: The need for digital tools in mental health is clear, with insufficient access to mental health services. Conversational agents, also known as chatbots or voice assistants, are digital tools capable of holding natural language conversations. Since our last review in 2018, many new conversational agents and research have emerged, and we aimed to reassess the conversational agent landscape in this updated systematic review. Methods: A systematic literature search was conducted in January 2020 using the PubMed, Embase, PsychINFO, and Cochrane databases. Studies included were those that involved a conversational agent assessing serious mental illness: major depressive disorder, schizophrenia spectrum disorders, bipolar disorder, or anxiety disorder. Results: Of the 247 references identified from selected databases, 7 studies met inclusion criteria. Overall, there were generally positive experiences with conversational agents in regard to diagnostic quality, therapeutic efficacy, or acceptability. There continues to be, however, a lack of standard measures that allow ease of comparison of studies in this space. There were several populations that lacked representation such as the pediatric population and those with schizophrenia or bipolar disorder. While comparing 2018 to 2020 research offers useful insight into changes and growth, the high degree of heterogeneity between all studies in this space makes direct comparison challenging. Conclusions: This review revealed few but generally positive outcomes regarding conversational agents’ diagnostic quality, therapeutic efficacy, and acceptability, which may augment mental health care. Despite this increase in research activity, there continues to be a lack of standard measures for evaluating conversational agents as well as several neglected populations. We recommend that the standardization of conversational agent studies should include patient adherence and engagement, therapeutic efficacy, and clinician perspectives.

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 Study of Predictors of Entrepreneurial Intentions: Development of Comprehensive Measures

2017 ◽  
Vol 18 (3) ◽  
pp. 629-651 ◽  
Author(s):  
A. Uday Bhaskar ◽  
Somayajullu Garimella
Keyword(s):  
Statistical Analysis ◽  
Business School ◽  
Online Survey ◽  
Entrepreneurial Intentions ◽  
Validity And Reliability ◽  
School Students ◽  
Entrepreneurial Behaviour ◽  
Extensive Search ◽  
Five Factors ◽  
Complete Set

The purpose of this study was to develop a comprehensive set of measures to predict entrepreneurial intentions drawn from measures used in existing studies. Since intentions can be valuable for explaining the act of creating the venture, it is vital to develop a set of comprehensive measures that can better predict the intentions and the entrepreneurial behaviour. An extensive search of literature for a complete set of measures that are capable of explaining entrepreneurial intentions and behaviour did not yield any result. The present study was, therefore, attempted to address this gap in the extant literature. The final scale developed in this study is, in essence, the drawing together of various items from disparate sources and it should provide a more comprehensive research tool. Data was collected from four leading Indian business school students through an online survey. One hundred and one responses completed responses were obtained through the online survey which was open for one week. The data was subjected to statistical analysis to check the psychometric properties of the instruments. The scales were tested for validity and reliability. A total of 13 factors (measures) emerged from the study totalling 54 items. Out of these, seven factors were for motivators (28 items), five factors were for barriers (20 items) and one factor was for intention (6 items). These measures can be used by researchers to determine entrepreneurial intentions and behaviour of students, women, working managers and other sections of the society.

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