Intelligent Mentoring Bots in Learning Management Systems

Neumann, Alexander Tobias; Lange, Peter de; Klamma, Ralf; Pengel, Norbert; Arndt, Tamar

doi:10.1007/978-3-030-66906-5_1

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…The addition of AI mentors is even more notable as the availability and participation in online instruction continue to increase. The use of chatbots makes participation in the online formats more attractive to students and enhances their sense of self-satisfaction [ 49 ], while also providing an excellent way to profile how students are progressing with mastering the material online [ 50 ].…”

Section: Reviewmentioning

confidence: 99%

Artificial Intelligence and Healthcare Simulation: The Shifting Landscape of Medical Education

Hamilton

2024

Cureus

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The impact of artificial intelligence (AI) will be felt not only in the arena of patient care and deliverable therapies but will also be uniquely disruptive in medical education and healthcare simulation (HCS), in particular. As HCS is intertwined with computer technology, it offers opportunities for rapid scalability with AI and, therefore, will be the most practical place to test new AI applications. This will ensure the acquisition of AI literacy for graduates from the country's various healthcare professional schools. Artificial intelligence has proven to be a useful adjunct in developing interprofessional education and team and leadership skills assessments. Outcome-driven medical simulation has been extensively used to train students in imagecentric disciplines such as radiology, ultrasound, echocardiography, and pathology. Allowing students and trainees in healthcare to first apply diagnostic decision support systems (DDSS) under simulated conditions leads to improved diagnostic accuracy, enhanced communication with patients, safer triage decisions, and improved outcomes from rapid response teams. However, the issue of bias, hallucinations, and the uncertainty of emergent properties may undermine the faith of healthcare professionals as they see AI systems deployed in the clinical setting and participating in diagnostic judgments. Also, the demands of ensuring AI literacy in our healthcare professional curricula will place burdens on simulation assets and faculty to adapt to a rapidly changing technological landscape. Nevertheless, the introduction of AI will place increased emphasis on virtual reality platforms, thereby improving the availability of self-directed learning and making it available 24/7, along with uniquely personalized evaluations and customized coaching. Yet, caution must be exercised concerning AI, especially as society's earlier, delayed, and muted responses to the inherent dangers of social media raise serious questions about whether the American government and its citizenry can anticipate the security and privacy guardrails that need to be in place to protect our healthcare practitioners, medical students, and patients.

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Section: Reviewmentioning

confidence: 99%

Artificial Intelligence and Healthcare Simulation: The Shifting Landscape of Medical Education

Hamilton

2024

Cureus

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“…To create the chatbots, we use the Social Bot Framework (SBF) ( Neumann et al, 2019 ; Neumann et al, 2020 ), a Web-based collaborative modeling tool. Aiming to support collaborative bot development for users both with and without a technical background, the SBF offers a visualized model of the bot and allows for easy drag and drop interactions with elements like user intents and bot messages.…”

Section: Technical Basis and Architecturementioning

confidence: 99%

Chatbots as a Tool to Scale Mentoring Processes: Individually Supporting Self-Study in Higher Education

Neumann¹,

Arndt²,

Köbis³

et al. 2021

Front. Artif. Intell.

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Like most curricula in the humanities and social sciences, the curriculum of pre-service teacher training in educational sciences often includes time-consuming reading and writing tasks, which require high quality support and feedback in a timely manner. A well-known way to provide this support to students is one-to-one mentoring. However, limited time and resources in the German university context require to effectively scale the benefits of individual feedback. The use of scalable technologies to support learning processes seems to be promising, but its development usually requires a deep technical understanding. With an interdisciplinary approach, this contribution investigates how personal mentoring can be made available to as many students as possible, taking into account the didactic, organizational and technical frameworks at universities. We describe the development and implementation process of two chatbots that both aim to support students of educational sciences in their self-study of the seminar topics and literature. The chatbots were used by over 700 students during the course of 1 year and our evaluations show promising results that bear the potential to improve the availability of digital mentoring support for all students.

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