I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents

Chatbots have been around for years and have been used in many areas such as medicine or commerce. Our focus is on the development and current uses of chatbots in the field of education, where they can function as service assistants or as educational agents. In this research paper, we attempt to make a systematic review of the literature on educational chatbots that address various issues. From 485 sources, 80 studies on chatbots and their application in education were selected through a step‐by‐step procedure based on the guidelines of the PRISMA framework, using a set of predefined criteria. The results obtained demonstrate the existence of different types of educational chatbots currently in use that affect student learning or improve services in various areas. This paper also examines the type of technology used to unravel the learning outcome that can be obtained from each type of chatbots. Finally, our results identify instances where a chatbot can assist in learning under conditions similar to those of a human tutor, while exploring other possibilities and techniques for assessing the quality of chatbots. Our analysis details these findings and can provide a solid framework for research and development of chatbots for the educational field.

Rediscovering the use of chatbots in education: A systematic literature review

The rapid evolution in artificial intelligence (AI) has redefined the customer experience and created huge opportunities for companies to interact with customers using chatbots. This study explores the role of AI chatbots in influencing the online customer experience and customer satisfaction in e-retailing.,A research model based on the technology acceptance model and information system success model is proposed to describe the interrelationships among chatbot adoption, online customer experience and customer satisfaction. Personality is a moderator in the model. The authors used a quantitative approach to collect 425 useable online questionnaires and Statistical Product and Service Solutions (SPSS) and SmartPLS to analyze the measurement model and proposed hypotheses.,The usability of the chatbot had a positive influence on extrinsic values of customer experience, whereas the responsiveness of the chatbot had a positive impact on intrinsic values of customer experience. Furthermore, online customer experience had a positive relationship with customer satisfaction, and personality influenced the relationship between the usability of the chatbot and extrinsic values of customer experience.,This research extends understanding of the online customer experience with chatbots in e-retailing and provides empirical evidence by showing that extrinsic and intrinsic values of online customer experience are enhanced by chatbot adoption.

Usability and responsiveness of artificial intelligence chatbot on online customer experience in e-retailing

Chatbots are intelligent conversational computer systems designed to mimic human conversation to enable automated online guidance and support. The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers. Chatbots utilise methods and algorithms from two Artificial Intelligence domains: Natural Language Processing and Machine Learning. However, there are many challenges and limitations in their application. In this survey we review recent advances on chatbots, where Artificial Intelligence and Natural Language processing are used. We highlight the main challenges and limitations of current work and make recommendations for future research investigation. 

https://www.mdpi.com/2078-2489/13/1/41/pdf?version=1642401608

A Literature Survey of Recent Advances in Chatbots

“In A.I. we trust?” The effects of parasocial interaction and technopian versus luddite ideological views on chatbot-based customer relationship management in the emerging “feeling economy”

In bot we trust: A new methodology of chatbot performance measures

In the pursuit to clarify the concept of "BCI illiteracy", we investigated the possibilities of attaining basic binary (yes/no) communication via brain‑computer interface (BCI). We tested four BCI paradigms: steady‑state visual evoked potentials (SSVEP), tactile, visual, and auditory evoked potentials (P300). The proposed criterion for assessing for the possibility of communication are based on the number of correct choices obtained in a given BCI paradigm after a short calibration session, without prior training. In this study users answered 20 simple "yes/no" questions. Fourteen or more correct answers rejected the null hypothesis of random choices at P=0.05. All of the 30 healthy volunteers were able to attain above‑chance choices in at least one of the four paradigms. Additionally, we tested the system in clinical settings on a patient recovering from disorders of consciousness, achieving successful communication in 2 out of 3 paradigms. In light of these facts, after a review of the sparse literature, and in the interest of motivating further research, we propose a paraphrase of de Finetti's provocative statement: "BCI illiteracy does not exist".

/pdf/successful-bci-communication-via-high-frequency-ssvep-or-4n6i06avjt.pdf

Successful BCI communication via high‑frequency SSVEP or visual, audio or tactile P300 in 30 tested volunteers.

On the Possibility of Mathematical Unification for the Currently Applied Analysis of Actigraphic Recordings

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In bot we trust: A new methodology of chatbot performance measures

Successful BCI communication via high‑frequency SSVEP or visual, audio or tactile P300 in 30 tested volunteers.

On the Possibility of Mathematical Unification for the Currently Applied Analysis of Actigraphic Recordings