Special Issue On: Deep Learning in Adaptive Learning: Educational Behavior and Strategy
Submission Due Date8/15/2023
Guest EditorsDr. Kate Saenko, Department of Computer Science, Boston University, United States, (
ksaenko@bu.edu)
Dr. Jie Yuan, School of Information Engineering, Minzu University of China, China, (
yuan.jie@muc.edu.cn)
IntroductionArtificial Intelligence (AI) techniques have been applied in various teaching and/or learning platforms and will change teachers' teaching and students' learning behaviors. The AI-related techniques can track and analyze users' behavioral data and then provide personalized responses and feedback, such as individualized learning instructions. The customized educational content can enhance students’ learning experience and performance. In particular, deep learning AI techniques, Deep Neural Network (DNN), or Recurrent Neural Networks (RNN) can be used to analyze and assess students' weaknesses before providing customized learning materials. RNN can analyze students' exams and online discussion data to understand students’ learning needs. To give the students human-like interactions, AI-based Chatbots are widely adopted in the intelligent tutoring systems as well. The chatbot services can answer learners' questions instantly and give them personalized responses. As the services collect learners' data and interactions over time, they can provide a more meaningful learning guide.
ObjectiveMachine learning techniques can be used in educational data mining and predicting student's learning performance. These techniques can build predictive models and descriptive models to discover meaningful patterns and knowledge. For example, predictive models can predict students' scores, while descriptive models can discover new learning guides from big educational data. The use of these techniques allows Intelligent Tutoring Systems (ITS) to suggest individual studying strategies. The users of the systems may face some challenges, such as learning new digital skills to use AI pedagogically or trusting in AI systems' suggestions. Therefore, there are many key issues in using AI-based systems that are being addressed, such as performance effectiveness, learning pedagogies, user experience, learning environment, and interactive content. This special issue aims to bring together researchers, engineers, and practitioners from both academia and industry to report, review, and exchange the up-to-date progress of using artificial intelligence-related techniques in educational behaviors and settings, to explore future research directions, and to prompt better service provision in specific domains for a wider target audience from diverse fields.
Recommended Topics- Augmented Reality (AR), Virtual Reality (VR), and eXtended Reality (XR) for learning;
- Interactive learning systems;
- Open and flexible learning;
- Experimental Learning;
- Learning analytics;
- Mobile learning;
- Open educational resources;
- Student advising and assessment;
- AI: Chatbots, virtual assistants, or intelligent tutoring systems;
- Robotics in the classroom to enhance student motivation;
- Innovative pedagogical approaches
Submission ProcedureResearchers and practitioners are invited to submit papers for this special theme issue on Deep Learning in Adaptive Learning: Educational Behavior and Strategy on or before
August 15th, 2023. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at
http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.
This is a full open access journal. Authors of manuscripts that are accepted to publish in this special issue will be expected to pay the article processing charge.
Open Access Resources:All inquiries should be directed to the attention of:Dr. Kate SaenkoGuest Editorksaenko@bu.eduDr. Jie YuanGuest Editoryuan.jie@muc.edu.cnInternational Journal of Web-Based Learning and Teaching Technologies (IJWLTT)