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Intelligent Techniques in E-Learning

This special issue belongs to the section “Computing and Artificial Intelligence“.

Special Issue Information

Dear Colleagues,

Intelligent techniques in e-learning are revolutionizing how education is delivered and experienced. These techniques leverage artificial intelligence (AI), machine learning (ML), and data analytics to create personalized, adaptive, and efficient learning environments. By harnessing the power of intelligent algorithms, e-learning platforms can analyze learners' behaviors, preferences, and performance to tailor content and assessments according to individual needs.

One of the key intelligent techniques used in e-learning is adaptive learning. This approach dynamically adjusts the learning path based on the learner's progress and comprehension levels. It ensures that students receive the right level of challenge, avoiding either overwhelming or underwhelming them. This method significantly enhances learning outcomes and keeps learners engaged by providing a customized experience.

Moreover, intelligent tutoring systems (ITSs) are another critical aspect of intelligent e-learning. These systems mimic human tutors by providing immediate feedback, answering questions, and guiding learners through complex concepts. ITS can identify areas where learners struggle and provide additional resources or explanations to help them grasp difficult topics.

Natural language processing (NLP) is also being integrated into e-learning through chatbots and virtual assistants. These tools can facilitate communication, answer queries, and provide real-time support, allowing students to learn independently while still receiving help when needed.

Intelligent assessment techniques, such as automated grading systems and predictive analytics, further enhance e-learning by streamlining the evaluation process. Predictive models can identify at-risk students early and suggest interventions to improve performance, ensuring a higher success rate.

In summary, intelligent techniques in e-learning are transforming education by offering personalized, efficient, and scalable solutions that cater to individual learning styles, making education more accessible and effective for all learners.

Dr. Hao-En Chueh
Dr. Duen-Huang Huang
Dr. Fuyuan Chiu
Prof. Dr. Jenny Pange
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • virtual assistants
  • adaptive learning
  • personalized learning
  • intelligent tutoring systems
  • intelligent assessment techniques

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Appl. Sci. - ISSN 2076-3417