Type-2 fuzzy set construction and application for adaptive student assessment system

Wang, Mei-Hui; Wang, Chi-Shiang; Lee, Chang-Shing; Lin, Su-Wei; Hung, Pi‐Hsia

doi:10.1109/fuzz-ieee.2014.6891894

Cited by 11 publications

(12 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the adopted IRT model perfectly fits the analyzed data, the distribution of students' abilities will not affect the results of the item parameter estimation and vice versa [20]. The four levels for student's performance defined in the IRT are below basic, basic, proficient, and advanced [19]. According to the 3PL model of dichotomous scoring, one item has three parameters, namely, a, b, and c, to represent this item's discrimination, difficulty, and guessing, respectively [20].…”

Section: A Item Characteristic Curve Test Characteristic Curve Andmentioning

confidence: 99%

PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

Lee

Wang

et al. 2018

IEEE Trans. Fuzzy Syst.

Self Cite

View full text Add to dashboard Cite

Fuzzy relationships exist between students' learning performance with various abilities and a test item. However, the challenges in implementing adaptive assessment agents are obtaining sufficient items, efficient and accurate computerized estimation, and a substantial feedback agent. Additionally, the agent must immediately estimate students' ability item by item, which places a considerable burden on the server, especially for a group test. Hence, the implementation of adaptive assessment agent is more difficult in practice. This paper proposes an agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for students' learning performance evaluation and educational applications, and the proposed agent is according to the response data from a conventional test and an item response theory (IRT)-based three-parameter logistic (3PL) model. First, we apply a Gauss-Seidel (GS)-based parameter estimation mechanism to estimate the items' parameters according to the response data, and then to compare its results with those of an IRTbased Bayesian parameter estimation mechanism. In addition, we propose a static-IRT test assembly mechanism to assemble a form for the conventional test. The presented FML-based dynamic assessment mechanism infers the probability of making a correct response to the item for a student with various abilities. Moreover, this paper also proposes a novel PSO-based FML (PFML) learning mechanism for optimizing the parameters between items and students. Finally, we adopt a K-fold cross validation mechanism to evaluate the performance of the proposed agent. Experimental results show that the novel PFML learning mechanism for the parameter estimation and learning optimization performs favorably. We believe the proposed PFML will be a reference for education research and pedagogy and an important co-learning mechanism for future human-machine educational applications. Index Terms-Dynamic assessment, Fuzzy Markup Language (FML), Genetic FML (GFML), item response theory (IRT), particle swarm optimization (PSO)The authors would like to thank the financial support sponsored by 1) Ministry

show abstract

Section: A Item Characteristic Curve Test Characteristic Curve Andmentioning

confidence: 99%

PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

Lee

Wang

et al. 2018

IEEE Trans. Fuzzy Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…An online based task and employee management tool. Trello [8] provides various features in order to use it collaboratively. Various features such as notifications panel, calendar panel, comment window, file manager etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and Implementation of a Computer Aided Intelligent Examination System

Alghamdi

Alanezi

Khan

2020

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

Developing a computer based system for examinations are the substitute for the current examination system based on paper. In recent days, the e-learning has become more popular because of its adaptability, integrity and user friendliness. In terms of the paper based examinations, major challenge is the proctoring techniques used. In this paper, a novel method to avoid the presence of a proctor throughout the examination is proposed by an intelligent based examination system. This method is proposed to improve the e-learning using intelligent question bank and examination system. The system is designed with different complexity levels among the questions and also it acts as a tool to assessing the understanding of student from the teaching materials. This system can be timesaving and more efficient with an adequate level of security. The proposed methodology can be classified in to two main phases such as the design of question bank along with its database, design of the Artificial Intelligence (AI) based system for examination and its evaluation in order to improve the e-learning. Future works in this system can be the addition of theory-based questions and the integration of biometric based systems for enhancing the level of security.

show abstract

“…Although there is a large variety of countries where the selected studies take place, there are two countries that stand out: the United States of America, with 5 papers [29][30][31][32][33], China with 3 papers [34][35][36], and Pakistan with 2 papers [37,38].…”

Section: Q4: Where Do the Studies Take Place?mentioning

confidence: 99%

AI-Driven Assessment of Students: Current Uses and Research Trends

Prieto

Gamazo

Cruz-Benito

et al. 2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

During the last decade, the use of AIs is being incorporated into the educational field whether to support the analysis of human behavior in teachinglearning contexts, as didactic resource combined with other technologies or as a tool for the assessment of the students.This proposal presents a Systematic Literature Review and mapping study on the use of AIs for the assessment of students that aims to provide a general overview of the state of the art and identify the current areas of research by answering 6 research questions related with the evolution of the field, and the geographic and thematic distribution of the studies.As a result of the selection process this study identified 20 papers focused on the research topic in the repositories SCOPUS and Web of Science from an initial amount of 129.The analysis of the papers allowed the identification of three main thematic categories: assessment of student behaviors, assessment of student sentiments and assessment of student achievement as well as several gaps in the literature and future research lines addressed in the discussion.

show abstract

Type-2 fuzzy set construction and application for adaptive student assessment system

Cited by 11 publications

References 19 publications

PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

Design and Implementation of a Computer Aided Intelligent Examination System

AI-Driven Assessment of Students: Current Uses and Research Trends

Contact Info

Product

Resources

About