Seshat — a web‐based educational resource for teaching the most common algorithms of lexical analysis

Arnaiz‐González, Álvar; Díez-Pastor, José-Francisco; Ramos‐Pérez, Ismael; García‐Osorio, César

doi:10.1002/cae.22036

Cited by 18 publications

(14 citation statements)

References 24 publications

(27 reference statements)

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“…In particular, we were interested in feedback on the visualizations provided by the tool, the outputs generated by the tool, and its user interface and ease of use. Similar questionnaires have been used by many other researchers, like Singh et al [24] and Arnaiz‐González et al [3]. The survey was designed to assess student satisfaction with the ComVis simulator and its use in the teaching and learning process.…”

Section: Discussionmentioning

confidence: 99%

Teaching concepts related to finite automata using ComVis

Jovanović¹,

Miljković²,

Stamenković³

et al. 2020

Comp Applic In Engineering

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This paper describes educational software for visualization and finite automata simulation. The system was developed in Java programming language, and its main purpose is learning process improvement. Using this software, finite automata can be defined in a graphical editor in the form of a state diagram, or by defining the transition function using the transition table. Upon defining an automaton, it is possible to run a visual simulation of the automaton operation for an arbitrary input string, whereby a textual description of the automaton simulation is also obtained. Furthermore, the system allows for conversion of regular expressions to deterministic finite automata and nondeterministic finite automata. The simulation of Thompson's construction algorithm is implemented, so that transformation of a regular expression to the corresponding NFA can be monitored in a step‐by‐step process. The quantitative analysis and evaluation of the effectiveness of the simulator are based on a survey of undergraduate students at two universities. The majority of students found the tool a useful means for better understanding and mastering of finite automata concepts.

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Section: Discussionmentioning

confidence: 99%

Teaching concepts related to finite automata using ComVis

Jovanović¹,

Miljković²,

Stamenković³

et al. 2020

Comp Applic In Engineering

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“…Nielsen and Hoban applied web mining, association rule mining, and decision tree techniques to recommender systems to recommend suitable resources to users [17]. Arnaiz-González et al studied the personalized resource recommendation service in the basic education resource network and proposed a personalized resource recommendation service model [18]. Aiming at the contradiction between the current ubiquitous mass instructional resources and the personalized needs of users, Barry proposed to introduce personalized recommendation technology into the network instructional resource system [19].…”

Section: Related Workmentioning

confidence: 99%

A Recommendation Model for College English Digital Teaching Resources Using Collaborative Filtering and Few-Shot Learning Technology

2022

Computational Intelligence and Neuroscience

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This study designs and implements a digital English instructional resource management recommendation system based on collaborative filtering technology based on CF research and the construction of digital English instructional resources. This study designs the system with B/S structure combined with hierarchical design architecture, plans the overall design goal, architecture design, compilation structure, and key technologies, and designs and implements the system’s core modules on the basis of fully analysing the functional and nonfunctional requirements of personalized educational resource recommendation system. Furthermore, the traditional CF has been improved to address scalability, data sparseness, and user cold start in the recommendation process. The evaluation results show that this algorithm has a recall rate of 96.37% and a system resource recommendation accuracy rate of 95.31%, both of which are higher than the traditional method’s 6.37%. This algorithm can overcome the drawbacks of traditional algorithms, improve recommendation accuracy, and efficiently provide high-quality English teaching resources. Educators and students will be more likely to find high-quality digital English instructional resources if they use the instructional resource system proposed in this study.

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“…e system adopts decision trees, fuzzy matching and reasoning, and ant colony clustering as supporting technologies for personalized services [13]. Kim proposed a standard instructional resource library model in view of the low degree of resource abstraction and poor correlation between resources in most current instructional resource libraries.…”

Section: Related Workmentioning

confidence: 99%

A Music Teaching Resource Management Model Based on Fuzzy Clustering Algorithm

2022

Mobile Information Systems

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This study develops and implements a music instructional resource platform based on fuzzy clustering algorithm knowledge in order to make the management of music teaching quality more scientific and standardised. This study presents the construction scheme of a music instructional resource management system in a higher education institution through requirements analysis, function design, system development and implementation, and system testing of the software system. In this study, a system is developed that uses computational intelligence to calculate the content and topics contained in resources based on semantic similarity, generate category labels, and cluster educational resources in order to integrate educational resources and implement effective management. It not only meets the needs of users who want to access the platform system via mobile terminals but also increases the platform system’s utilisation rate. Experiments show that this system’s stability can reach 95.37%. The retrieval accuracy is 96.24%, which is 8.94% better than the traditional method. It has the ability to effectively provide high-quality music teaching resources. Using the instructional resource system proposed in this study will improve teaching effectiveness, reduce learners’ learning burden, and increase learning efficiency.

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Seshat — a web‐based educational resource for teaching the most common algorithms of lexical analysis

Cited by 18 publications

References 24 publications

Teaching concepts related to finite automata using ComVis

Teaching concepts related to finite automata using ComVis

A Recommendation Model for College English Digital Teaching Resources Using Collaborative Filtering and Few-Shot Learning Technology

A Music Teaching Resource Management Model Based on Fuzzy Clustering Algorithm

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