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Enhancing Online Practical Assignments through Chatbot-Based Individualization and Scalability

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dc.contributor.authorShahriar, Asif
dc.date.accessioned2024-08-21T11:08:31Z
dc.date.available2024-08-21T11:08:31Z
dc.date.issued2024
dc.description.abstractThis research investigates the scalability and individualisation challenges of online practical assignments in online learning modules. Utilising a MOOC prototype in a blended learning framework, the study employs the Action Design Research (ADR) method to enhance online learning. Key interventions include chatbots for task provision and feedback, aiming to offer personalised and scalable solutions. The study will evaluate these interventions' impact on learning outcomes and develop a comprehensive conceptual framework. Findings will provide insights into effective technological solutions, contributing significantly to the field of Human-Computer Interaction (HCI) and online education.en
dc.identifier.doi10.18420/muc2024-mci-dc-377
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44251
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2024 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.rightshttp://purl.org/eprint/accessRights/RestrictedAccess
dc.rights.urihttp://purl.org/eprint/accessRights/RestrictedAccess
dc.subjectScalability
dc.subjectPersonalized Learning
dc.subjectOnline Learning
dc.subjectChatbots
dc.subjectEducational Technology
dc.subjectAction Design Research (ADR)
dc.titleEnhancing Online Practical Assignments through Chatbot-Based Individualization and Scalabilityen
dc.typeText/Conference Paper
gi.conference.date1.-4. September 2024
gi.conference.locationKarlsruhe
gi.conference.sessiontitleMCI: Doctoral Consortium

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