CiSA: An Inclusive Chatbot Service for International Students and Academics

Heo, Jeongyun; Lee, Ji-Yoon

doi:10.1007/978-3-030-30033-3_12

Cited by 16 publications

(10 citation statements)

References 25 publications

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“…The chatbots use NLP, which sometimes fails to respond to the user or understand what users say. This aspect is ignored in many studies of chatbots (Abdulquadri et al, 2021;Heo and Lee, 2019;Kaimakis et al, 2018). The chatbots have varied functions; however, if the chatbot does not understand the language the employees use and at the same time, if the employees do not understand the chatbot language and accent, then the adoption of chatbots would be slow.…”

Section: Theoretical Implicationsmentioning

confidence: 99%

Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots

Pillai¹,

Ghanghorkar²,

Algharabat

et al. 2023

ITP

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PurposeAI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.Design/methodology/approachThe proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.FindingsThis research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.Originality/valueThis is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.

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Section: Theoretical Implicationsmentioning

confidence: 99%

Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots

Pillai¹,

Ghanghorkar²,

Algharabat

et al. 2023

ITP

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show abstract

“…• curate and deliver personalized formative assessment (Gupta and Chen, 2022;Heo & Lee, 2019) through e.g., curating multiple choice format formative assessments generated via AI conversational agents (Pereira, 2016).…”

Section: Rq2: What Are the Main Ai Use Cases Relating To Assessments?mentioning

confidence: 99%

“…-Chatbot CiSA is designed to promote equity and social inclusivity for international students (Heo & Lee, 2019). -Build an AI ethics framework, that will make explicit ethic issues (such as privacy, explainability, fairness etc.…”

Section: Domainmentioning

confidence: 99%

Artificial Intelligence in Today’s Education Landscape: Understanding and Managing Ethical Issues for Educational Assessment

Lim

Gottipati

Cheong

2023

Preprint

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In a societal institution as fundamental as education, when teaching practitioners or researchers apply artificial intelligence in academic processes such as assessments, it is important to study the divide between what may be ethically permissible and not permissible. This study applied a systematic literature mapping methodology to scour extant research, so as to holistically structure the landscape into explicit topical research clusters. Through topic modelling and network analyses, research mapped ten key ethical principles to five research archetypical domains, and reviewed the contribution and intensity of these ethical principles in each thematic domain. The study extended this review, by mapping out ethics programs and activities that can be applied in practice, alongside their relevant underpinning theories. This study provides a comprehensive treatment of this subject matter to date. We hope the findings of this research can provide researchers and practitioners the insights into the application methods of AI in assessments, and in particular, in terms of their intertwined ethical challenges and how these challenges may be addressed, for follow up studies.

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“…From this category, we can identify four features: Information: It refers to information, such as educational offers, staff contact data, and study plans, needed by people interested in becoming a student of the institution. Examples of chatbots that provide this kind of information are: [ 23 ], [ 24 ], [ 25 ], [ 26 ], [ 27 ], [ 28 ], [ 29 ], Mekni et al. [ 30 ], [ 31 ], and Ranoliya et al.…”

Section: Related Workmentioning

confidence: 99%

“…This characteristic also exists in the Student/Teacher-Oriented category. Works like [ 23 ], [ 27 ], [ 29 ], Mekni et al. [ 30 ], Ranoliya et al.…”

Section: Related Workmentioning

confidence: 99%

A Model to Develop Chatbots for Assisting the Teaching and Learning Process

Mendoza

Sánchez-Adame

Urquiza-Yllescas

et al. 2022

Sensors

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Recently, in the commercial and entertainment sectors, we have seen increasing interest in incorporating chatbots into websites and apps, in order to assist customers and clients. In the academic area, chatbots are useful to provide some guidance and information about courses, admission processes and procedures, study programs, and scholarly services. However, these virtual assistants have limited mechanisms to suitably help the teaching and learning process, considering that these mechanisms should be advantageous for all the people involved. In this article, we design a model for developing a chatbot that serves as an extra-school tool to carry out academic and administrative tasks and facilitate communication between middle-school students and academic staff (e.g., teachers, social workers, psychologists, and pedagogues). Our approach is designed to help less tech-savvy people by offering them a familiar environment, using a conversational agent to ease and guide their interactions. The proposed model has been validated by implementing a multi-platform chatbot that provides both textual-based and voice-based communications and uses state-of-the-art technology. The chatbot has been tested with the help of students and teachers from a Mexican middle school, and the evaluation results show that our prototype obtained positive usability and user experience endorsements from such end-users.

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CiSA: An Inclusive Chatbot Service for International Students and Academics

Cited by 16 publications

References 25 publications

Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots

Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots

Artificial Intelligence in Today’s Education Landscape: Understanding and Managing Ethical Issues for Educational Assessment

A Model to Develop Chatbots for Assisting the Teaching and Learning Process

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