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Subject:
From:
Elvira Popescu <[log in to unmask]>
Reply To:
Elvira Popescu <[log in to unmask]>
Date:
Mon, 28 Jun 2021 18:09:08 +0300
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Intelligence Support for Mentoring Processes in Higher Education (and beyond)
Research Topic in Frontiers in Artificial Intelligence (AI for Human
Learning and Behavior Change)

https://www.frontiersin.org/research-topics/14009/intelligence-support-for-mentoring-processes-in-higher-education-and-beyond

Submission deadline: 30 September 2021


Mentoring is the activity of a senior person (the mentor) supporting a
less experienced person (the mentee) in learning. It is based on a
trustful, protected and private atmosphere between the mentor and the
mentee. The goal is to develop a professional identity and to reflect the
current situation. At universities, mentors are senior academics or
skilled employees while mentees are mostly students with different
competences. Outside universities, mentors and mentees are professionals.
Intelligent tutoring systems have a long tradition, focusing on cognitive
aspects of learning in a selected domain. They were successfully applied
especially in such areas, where the domain knowledge can be well
formalised with the help of experts. Nevertheless, in the learning process
also motivations, emotions and meta-cognitive competences play a crucial
role. These can be nowadays quite well recognised and monitored through
big educational data and a wide spectrum of available sensors. This
enables the support also for the mentoring process, which is more
spontaneous, holistic and depends on the needs and interests of the
mentee. Psychological and emotional support are at the heart of the
mentoring relationship, underpinned by empathy and trust. Various roles
and success factors for mentoring have been identified.

We want to look at these aspects and investigate how they were
technologically supported, in order to specify the requirements for
intelligent mentoring systems. This should help us to answer the following
questions: How can we design educational concepts that enable a scalable
individual mentoring in the development of competences? How can we design
intelligent mentoring systems to cover typical challenges and to scale up
mentoring support in universities and outside? How can we design an
infrastructure to exchange data between universities in a private and
secure way to scale up on the inter-university level? How can we integrate
heterogeneous data sources (learning management systems, sensors, social
networking sites) to facilitate learning analytics supporting mentoring
processes?

Topics include but are not limited to:

 Pedagogical models of mentoring
 Peer mentoring & crowdsourcing mentoring
 Workplace & career mentoring
 Meta-cognitive competences of mentoring
 Chatbots in Mentoring
 Mixed Reality Mentoring
 Wearables and Sensors for mentoring
 Self-regulated mentoring, nudging & behaviour change
 Mentoring analytics
 Mentoring support in learning management systems
 Mobile mentoring support
 Design and research methodologies for mentoring support
 Measuring and Analysing mentoring support
 Visualization techniques for mentoring support
 Motivation and gamification of mentoring support
 Deep learning, machine learning and data mining in mentoring support
 Recommender technologies for mentoring support (mentor-mentee matching)
 Semantic technologies for mentoring support (ontologies, domain &
mentoring models)
 Distributed mentoring environments (cloud & p2p platforms)
 Mentoring for specific domains & subjects (math, engineering, social
sciences, pedagogy)
 Affective computing for mentoring
 Requirements of intelligent mentoring systems

If you decide to submit a manuscript within our collection, your
contribution will be peer-reviewed and judged on originality, interest,
clarity, relevance, correctness, language, and presentation (inter alia)
by our editorial board members. Immediately upon publication, your paper
will be free to read for everyone, increasing visibility, and citations.

We encourage authors to submit Abstracts ahead of the full manuscript
submission.

Topic Editors:
 Ralf Klamma (RWTH Aachen University, Germany)
 Milos Kravcik (German Research Center for Artificial Intelligence -
DFKI, Germany)
 Elvira Popescu (University of Craiova, Romania)
 Viktoria Pammer-Schindler (Graz University of Technology, Austria)

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