A Chatbot for Goal-Oriented Requirements Modeling

Arruda, Danilo; Marinho, Matheus; Souza, Eric; Wanderley, Fernando

doi:10.1007/978-3-030-24305-0_38

Cited by 13 publications

(8 citation statements)

References 25 publications

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“…According to Winkler and Söllner ( 2018 ), chatbots, have the potential to compensate for inadequate individual support from instructors for a variety of reasons, which include enabling the student to progress at their own pace, increasing the quality of the learning process and providing individual solution that can be applied proactively to increase learning outcomes. Chatbots that support students individually are spreading rapidly in the field of education (Arruda et al, 2019 ; Chen et al, 2020 ; Haller et al, 2005 ; Nghi et al, 2019 ). Moreover, Grudin and Jacques ( 2019 ) state that chatbots are one appropriate learning method for students to repeat their knowledge of previous topics and can be used to collect feedback about a course.…”

Section: Introductionmentioning

confidence: 99%

“…The authors state that the probability of efficacy is higher with the utilization of chatbots in increasing user motivation, supporting stress reduction, and guiding self-learning. In a study conducted with computer science students by Arruda et al ( 2019 ), the chatbot they developed with goal-oriented requirements modeling was perceived as useful by students and note that the participants planned to use it in the future. Nghi et al ( 2019 ) explain that in using a chatbot application designed to teach the subject of prepositions in English, students benefited from the experience, that this application made learning exciting and fun; and that most students perceived AI chatbot tools as an important part of their learning process.…”

Section: Introductionmentioning

confidence: 99%

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Chatbot application in a 5th grade science course

2021

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This study aims to investigate the effect of chatbots that work with artificial intelligence on the success of students and their opinions about chatbots in the ‘Matter and the changing state of matter’ unit in the 5th grade science course. In addition to text-based functions, the designed chatbot includes a video accessed on the web to support students visually and aurally. The chatbot was designed using the Dialogflow program and an instant messaging program made available to students through a group created on Telegram. The study, which used a quasi-experimental pretest-posttest design, included 41 participants ( n = 20 for the experimental, n = 21 for the control group) studying in the 5th grade of a state secondary school in the 2020-2021 academic year. Results suggest that although there was no significant difference between the experimental and control groups in terms of academic achievement, it was determined that the chatbot application positively affected the online learning experience of the experimental group students. Students’ opinions about the chatbot included that it was useful and fun, they would like to use it for other courses, it provided useful assistance in learning outside the classroom, and it allowed them to repeat the course again. The results showed that, especially during the Covid-19 pandemic, such applications could contribute positively to students’ learning.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Chatbot application in a 5th grade science course

2021

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“…The first search using allintitle:modelling chatbot yields 15 hits. Some of the papers provide implementation support for chatbots, e.g., [21] and identify factors for the user experience, e.g., [5], especially in the medical and education domains. The search on ''model quality'' chatbot yields 0 hits, on ''redesign chatbot'' 1 hit, but with a focus on socio-linguistics, and on ''refactoring chatbot'' again 0 hits.…”

Section: Conversational Process Modellingmentioning

confidence: 99%

Conversational Process Modelling: State of the Art, Applications, and Implications in Practice

Klievtsova,

Benzin,

Kampik

et al. 2023

Lecture Notes in Business Information Processing

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Chatbots such as ChatGPT have caused a tremendous hype lately. For BPM applications, it is often not clear how to apply chatbots to generate business value. Hence, this work aims at the systematic analysis of existing chatbots for their support of conversational process modelling as process-oriented capability. Application scenarios are identified along the process life cycle. Then a systematic literature review on conversational process modelling is performed. The resulting taxonomy serves as input for the identification of application scenarios for conversational process modelling, including paraphrasing and improvement of process descriptions. The application scenarios are evaluated for existing chatbots based on a real-world test set from the higher education domain. It contains process descriptions as well as corresponding process models, together with an assessment of the model quality. Based on the literature and application scenario analyses, recommendations for the usage (practical implications) and further development (research directions) of conversational process modelling are derived.

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“…Laiq & Dieste (2020) propose a chatbot-based interview simulator for training novice software analysts. Unlike other chatbotbased proposals for RE (Arruda et al, 2019;Rajender Kumar Surana et al, 2019), where the chatbots are used for extracting requirements directly from stakeholders, such a proposal is focused on answering natural language questions related to the identi cation and extraction of requirements abstractions such as actors, goals, and actions from user stories by using a prede ned knowledge base. While such a proposal is the closest to the QUARE model, software analysts may only use it for answering RE-related questions in the context of the education domain.…”

Section: Related Workmentioning

confidence: 99%

“…Requirements Elicitation (RE) is focused on identifying and characterizing the stakeholders and their requirements (Dick et al, 2017). While there are several techniques for RE, including workshops, dialogues, and sample scenarios, interviews remain the most used technique for RE (Arruda et al, 2019). Such activity becomes challenging as the scope of the software product grows due to the number of requirements documents to be addressed, generating errors and delays.…”

Section: Introductionmentioning

confidence: 99%

QUARE: Towards a Question-Answering Model for Requirements Elicitation

Calle

Zapata

2022

Preprint

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Requirements elicitation is a stakeholder-centered approach; therefore, natural language remains an effective way of documenting and validating requirements. As the scope of the software domain grows, software analysts process a higher number of requirements documents, generating delays and errors while characterizing the software domain. Natural language processing is key in such a process, allowing software analysts for speeding up the requirements elicitation process and mitigating the impact of the ambiguity and misinterpretations coming from natural-language-based requirements documents. However, natural-language-processing-based proposals for requirements elicitation are mainly focused on specific domains and still fail for understanding several requirements writing styles. In this paper, we present QUARE, a question-answering model for requirements elicitation. The QUARE model comprises a meta-ontology for requirements elicitation, easing the generation of requirements-elicitation-related questions and the initial structuration of any software domain. In addition, the QUARE model includes a named entity recognition and relation extraction system focused on requirements elicitation, allowing software analysts for processing several requirements writing styles. Although software analysts address a software domain at a time, they use the same kind of questions for identifying and characterizing requirements abstractions such as actors, concepts, and actions from a software domain. Such a process may be framed into the QUARE model workflow. We validate our proposal by using an experimental process including real-world requirements documents coming from several software domains and requirements writing styles. The QUARE model is a novel proposal aimed at supporting software analysts in the requirements elicitation process.CCS CONCEPTS • Information systems~Information retrieval~Retrieval tasks and goals~Question answering • Software and its engineering~Software creation and management~Designing software~Requirements analysis • Information systems~Information retrieval~Retrieval tasks and goals~Information extraction

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A Chatbot for Goal-Oriented Requirements Modeling

Cited by 13 publications

References 25 publications

Chatbot application in a 5th grade science course

Chatbot application in a 5th grade science course

Conversational Process Modelling: State of the Art, Applications, and Implications in Practice

QUARE: Towards a Question-Answering Model for Requirements Elicitation

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