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LadderBot: A requirements self-elicitation system

Rietz, Tim; Maedche, Alexander

Abstract (englisch):
Digital transformation impacts an ever-increasing amount of everyone’s business and private life. It is imperative to incorporate user requirements in the development process to design successful information systems (IS). Hence, requirements elicitation (RE) is increasingly performed by users that are novices at contributing requirements to IS development projects. [Objective] We need to develop RE systems that are capable of assisting a wide audience of users in communicating their needs and requirements. Prominent methods, such as elicitation interviews, are challenging to apply in such a context, as time and location constraints limit potential audiences. [Research Method] We present the prototypical self-elicitation system “LadderBot”. A conversational agent (CA) enables end-users to articulate needs and requirements on the grounds of the laddering method. The CA mimics a human (expert) interviewer’s capability to rephrase questions and provide assistance in the process. An experimental study is proposed to evaluate LadderBot against an established questionnaire-based laddering approach. [Contribution] This work-in-progress introduces the chatbot LadderBot as a tool to guide novice users during requirements self-elicitation using the laddering technique. ... mehr

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Preprint §
DOI: 10.5445/IR/1000096469
Veröffentlicht am 26.03.2020
DOI: 10.1109/RE.2019.00045
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2019
Sprache Englisch
Identifikator ISBN: 978-1-7281-3912-8
KITopen-ID: 1000096469
Erschienen in 27th IEEE International Requirements Engineering Conference (RE'19), Jeju Island, ROK, September 23-27, 2019
Veranstaltung 27th IEEE International Requirements Engineering Conference (RE 2019), Jeju, Südkorea, 23.09.2019 – 27.09.2019
Verlag IEEE Computer Society
Seiten 357-362
Vorab online veröffentlicht am 05.12.2019
Externe Relationen Forschungsdaten/Software
Schlagwörter User, Requirements Elicitation, Wide Audience, Conversational Agent, Self-Elicitation, Laddering
Nachgewiesen in Scopus
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