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Please send to interested colleagues and students.
*** Call for Papers ***
Special Issue on Advances in Intelligent Systems for Online Education
Future Generation Computer Systems (Elsevier)
Impact Factor: 6.125
Link:
https://www.journals.elsevier.com/future-generation-computer-systems/call-for-papers/advances-in-intelligent-systems-for-online-education
*** Important dates ***
- Submission system open: September 15, 2020
- Manuscript submission due: January 15, 2021
- First round decision made: March 15, 2021
- Revised manuscript due: May 15, 2021
- Final decision made: June 15, 2021
- Final paper due: July 15, 2021
*** Aims and Scope *** The education sector is relying more and more on
online learning. Educational and training institutions are being motivated
to endorse online learning strategies thanks to its technical, economic,
and operational feasibility. This has become even more important after the
lockdown caused by the breakout of COVID-19, when even universities revised
their educational strategy, moving to online teaching. Learners and
teachers are benefiting from the flexibility, accessibility, and costs of
learning and teaching online. Nonetheless, moving education online is
bringing unprecedented challenges. For instance, learners may feel
isolation online, massive content alternatives often overload learners and
teachers who look for educational resources, and institutions are being
challenged to ensure academic integrity in online exams. The increasing
amount of learning-related data and high performance computing are enabling
intelligent systems that can support stakeholders while facing current
challenges. Bringing this intelligence to online education leads to a very
wide range of advantages, e.g., avoiding manual error-prone tasks or
providing learners with personalized guidance.
As artificial intelligence research and development is getting more mature
and the corresponding outputs are being deployed at scale in real-world
contexts, the crucial role of using automated systems in online education,
as an additional support for stakeholders during decision making processes,
becomes more evident nowadays. Current research has greatly expanded our
understanding on such artificial intelligence, but there has been less work
on how it applies to online education. Data, methods, tools, and
applications in this area are still limited, though they promise to
proliferate in next years. Further, more research and many questions remain
to be answered to bridge technological, social, pedagogical, and ethical
perspectives in these intelligent systems.
This Special Issue aims to present high-quality, high-impact, original
research results reporting the current state of the art of online education
systems empowered with artificial intelligence. We are interested in
submissions covering different levels of the experimental pipeline,
including but not limited to data collection, computational models, and
applicative systems. We also invite prospective authors to share experience
with dealing with online education in these months of COVID-19 emergency,
technological changes that happened at the institution, and impact of the
devised intelligent systems in their ecosystems.
*** Topics *** We are interested in contributions targeting automated
intelligent support in online education applications, focused but not
limited to the following areas. We seek to receive papers that clearly
state and contextualize how the proposed intelligent system or tool is
integrated in the real-world scenario and concretely supports stakeholders
during decision-making. If in doubt about suitability, please contact the
Guest Editors.
- *Data Set Collection*
- New tools and systems for capturing educational data (e.g.,
eye-tracking, motion, physiological, etc.).
- Proposals of procedures and tools to store, share and preserve
learning and teaching traces.
- Annotation standards and schemas for data that can be leveraged for
machine learning.
- Collecting and sharing data sets useful for applying machine
learning in online education contexts.
- *Model, Tool, and System Design*
- Semantic-based retrieval of instructional materials to identify
appropriate contents.
- Tools for adaptive question-answering and dialogue or automatically
generating test questions.
- Personalized support tools and systems for communities of learners
(e.g., recommendation).
- Content analysis for exam scoring and/or assessment.
- Behavioral and physiological analysis of learners while interacting
in online education platforms.
- Student engagement assessment via machine-learning techniques
(e.g., sentiment analysis).
- Systems that detect and/or adapt the platform to sentiment or
emotional states of learners.
- Techniques to provide automated proctoring support during online
examinations.
- Tools able to predict the dropout risk of learners along the
educational path.
- *Evaluation Protocol Design and Conduction*
- Evaluation techniques relying on computational analyses in online
education contexts.
- Interpretability and/or fairness of the models and the resulting
impact on real-world adoption.
- Error analysis devoted to understanding, measuring, and managing
uncertainty in model design.
- Strategies to evaluate effectiveness and impact of intelligent
systems on educational environments.
- Exploration of cognition, affect, motivation, and attitudes of
stakeholders, while deploying systems.
- *Ethics and Privacy Investigation*
- Analysis of issues and approaches to the lawful and ethical use of
intelligent systems.
- Tackling unintended bias and value judgements in intelligent
systems.
- Regulations and policies in data management ensuring privacy while
designing intelligent systems.
- Broad discussion on potential and pitfalls of intelligent systems
for educational contexts.
- Studies on how teachers can be made part of the loop as moderators
instead of being replaced.
*** Submission Instructions *** The system will be open for submissions to
our Special Issue *from September 15, 2020*. When submitting your
manuscript please select the article type "*VSI: Int Sys Edu*". Please
submit your manuscript *before January 15, 2021*. Please ensure you read
the Guide for Authors before writing your manuscript <
https://www.elsevier.com/journals/future-generation-computer-systems/0167-739x/guide-for-authors>.
The Guide for Authors and the link to submit your manuscript is available
on the Journal’s homepage. Each manuscript can have* no more than 14 pages*
(plus one page after revision) in double-column format, including all its
content (e.g., figures, references, appendix, and so on).
All submissions deemed suitable to be sent for peer review will be reviewed
by at least two independent reviewers on the basis of relevance for the
Special Issue, novelty/originality, significance, technical quality and
correctness, quality and clarity of presentation, quality of references and
reproducibility. The editors reserve the right to reject without review any
submissions deemed to be outside the scope of the Special Issue. Authors
are welcome to contact the Special Issue editors with questions about scope
before preparing a submission. Once your manuscript is accepted, it will go
into production, and will be published in the current regular issue and
pulled into the online Special Issue. Articles from this Special Issue will
appear in different regular issues of the journal, though they will be
clearly marked and branded as Special Issue articles.
Submissions must represent original material, that has not appeared
elsewhere for publication and that is not under review for another refereed
publication. If any portion of your submission has previously appeared in
or will appear in a conference/workshop proceeding, you should notify this
at the time of submission, make sure that the submission references the
conference publication, and supply a copy of the conference version(s).
Please also provide a brief description of the differences between the two
manuscript (at least 30% of new material must be provided). *** Guest
Editors *** *Geoffray Bonnin*
Université de Lorraine, Nancy, France
Email: bonnin@xxxxxxxx
*Danilo Dessì*
FIZ Karlsruhe Leibniz Institute for Information Infrastructure, Karlsruhe
Institute of Technology AIFB, Karlsruhe, Germany
Email: danilo.dessi@xxxxxxxxxxxxxxxx
*Gianni Fenu*
Department of Mathematics and Computer Science, University of Cagliari,
Cagliari, Italy
Email: fenu@xxxxxxxx
*Martin Hlosta*
Faculty of Science, Technology, Engineering & Mathematics, The Open
University, Milton Keynes, United Kingdom
Email: martin.hlosta@xxxxxxxxxx
*Mirko Marras* [Managing Guest Editor]
Department of Mathematics and Computer Science, University of Cagliari,
Cagliari, Italy
Email: mirko.marras@xxxxxxxx
*Harald Sack*
FIZ Karlsruhe Leibniz Institute for Information Infrastructure, Karlsruhe
Institute of Technology AIFB, Karlsruhe, Germany
Email: harald.sack@xxxxxxxxxxxxxxxx
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Mirko Marras, PhD
Department of Mathematics and Computer Science
University of Cagliari
Via Ospedale 72
09124 Cagliari - Italy
E-Mail: mirko.marras@xxxxxxxx
Phone: +39 070 675 8756
Skype: mmarras92
LinkedIn: https://it.linkedin.com/in/mmarras92
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