A Design Method for an Intelligent Tutoring System with Algorithms Visualization
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 13925 LNAI, Page: 223-234
2023
- 1Citations
- 2Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
Nowadays, learning has become more efficient via active learning methods. Active learning methods bring excitement and engagement to students. The proposed method in this paper suggests the utilization of graphical and dynamic web-based tools for visualization, as it is one of the most common and straightforward approaches. The objective of this method is to design an intelligent system for learning algorithms that can display the developed algorithm visually. This method proposes a model for representing the knowledge of an algorithm, called AI-Algo model, and solving problems about algorithm visualizing. The application of this method involves the development of an intelligent learning system focused on algorithms in a data structures and algorithms course. Additionally, it can support the knowledge engineer in creating and updating the content of visualization.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85172423613&origin=inward; http://dx.doi.org/10.1007/978-3-031-36819-6_19; https://link.springer.com/10.1007/978-3-031-36819-6_19; https://dx.doi.org/10.1007/978-3-031-36819-6_19; https://link.springer.com/chapter/10.1007/978-3-031-36819-6_19
Springer Science and Business Media LLC
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