A multi-expert approach for developing testing and diagnostic systems based on the concept-effect model

Panjaburee, Patcharin; Hwang, Gwo‐Jen; Triampo, Wannapong; Shih, Bo-Ying

doi:10.1016/j.compedu.2010.02.015

Cited by 54 publications

(27 citation statements)

References 43 publications

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“…To improve the learning achievement of students, it is important to diagnose the learning problem and provide learning suggestions for individual students. In the last decade, several studies have been conducted for diagnosing student learning problems and providing appropriate learning guidance for individual students [19]. Among the existing models, Concepteffect relationship (CER) has been proved to be an effective way of improving the learning performance of student [1].…”

Section: Discussionmentioning

confidence: 99%

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Improving the Learning Performance by Providing Intellectual Suggestions

Sarem

Bellafkih

Ramdani

2012

Lecture Notes in Electrical Engineering

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In developing a diagnosis system for detecting student's learning problems, providing intellectual suggestions is helpful and powerful tool to improve the learning performance. However, it is difficult and time consuming for teachers to give personalized suggestions to each student, particularly when there are many students in class. To cope with this problem, this study proposes concept-effect relationship model (CER) as a tool to identify the learning problem of students. Based on that, an intellectual learning guidance system has been proposed.

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Section: Discussionmentioning

confidence: 99%

“…Furthermore, let the questions-concepts matrix shown as follows: , where "qc ij " denotes the weighting or degree of relevance for each concept "C i "to each question "Q j " integrated from multiple experts [19] and 1 ≤ qc ij ≤ 1.…”

Section: Probability Approach For Calculating the Error Ratiomentioning

confidence: 99%

Improving the Learning Performance by Providing Intellectual Suggestions

Sarem

Bellafkih

Ramdani

2012

Lecture Notes in Electrical Engineering

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“…Then, the multiple rule types are used to further analyse the above mined rules, and a heuristic algorithm is used to automatically construct the concept map. Panjaburee, Hwang, Triampo, and Shih () proposed a set of weighting rules to define the weighting or degree of relevance for each concept to each test item. Abdullah, Herawan, Ahmad, Ghazali, and Deris () used indirect least association rules to analyse student examination datasets as a basis to improve their teaching and learning strategies.…”

Section: Related Workmentioning

confidence: 99%

Discovering the associations between test items in an examination

et al. 2018

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An examination is .an important approach to comprehensively evaluate students' abilities. An examination paper is composed of test items. Most studies assume that test items are independent, but there may, in fact, be associations among test items. How to select test items with low correlations into a test paper is our concern. Meanwhile, for diagnostic learning, students must perform highly relevant exercises to help them efficiently understand the concepts included in the test items. People usually find the associations among test items based on properties of individual test items. This paper proposes a test item association model to represent the correlations of test item pairs by mining the response data of examinees. Then, a hypothesis test and an empirical analysis were used to verify and analyse the relationship between the test item correlation and similarity. Next, the effects of test item parameters on the correlation are investigated by applying the model to the simulated response data which are produced by Item Response Theory (IRT) simulation data generation software. Finally, three applications of this test item association model are listed. After verification, the proposed model can be used for precise teaching.

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“…With the CER model, the adaptive learning systems are able to generate learning paths for individual students for improving their learning achievements (Hwang, 2003). This model has been shown to be effective in analyzing student learning problems and providing them with personalized suggestions by several researchers in various applications, including natural science, mathematics, physics and computer courses (Chu, Hwang & Huang, 2010; Hwang, 2007; Panjaburee, Hwang, Triampo & Shih, 2010; Tseng, Sue, Su, Weng & Tsai, 2007). Moreover, several studies have demonstrated the effectiveness of the learning diagnosis model via using the diagnosis results to determine personalized learning paths or learning content (Jong et al , 2004; Kwasnicka, Szul, Markowska‐Kaczmar & Myszkowski, 2008; Tseng et al , 2008).…”

Section: Introductionmentioning

confidence: 99%

A group decision approach to developing concept–effect models for diagnosing student learning problems in mathematics

Hwang

Panjaburee

Triampo

et al. 2012

Brit J Educational Tech

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Diagnosing student learning barriers has been recognized as the most fundamental and important issue for improving the learning achievements of students. In the past decade, several learning diagnosis approaches have been proposed based on the concept–effect relationship (CER) model. However, past studies have shown that the effectiveness of this model heavily depends on the concept relationship knowledge provided by the domain experts (eg, experienced teachers or educators for a specified subject); ie, the performance of the developed learning diagnosis systems could be significantly affected by subjective opinions, ignorance or insufficient knowledge if those concept relationships are derived from a single domain expert. To cope with this problem, this study proposes a group decision approach for developing the CER model with the cooperation of multiple domain experts. Based on the proposed approach, a testing and diagnostic system has been implemented; moreover, an experiment has been conducted to evaluate the effectiveness of this new approach. The experimental results show that this approach is able to develop quality CER models, and hence the low‐achievement students who received the generated learning suggestions had significantly better learning achievements than those who learned with the previous approach. Practitioner notes What is already known about this topic Diagnosing student learning barriers is a fundamental and important issue for improving the learning achievements of students. Several learning diagnosis approaches have been proposed based on the concept–effect relationship (CER) model. The effectiveness of the learning diagnosis model heavily depends on the concept relationship knowledge provided by the domain experts. What this paper adds A group decision approach for developing the CER model with the cooperation of multiple domain experts is proposed. A testing and diagnostic system was implemented based on the proposed approach. An experiment was conducted to investigating whether the students guided by the proposed approach had better learning achievements than those guided by the original CER model approach. Implications for practice and/or policy The experimental results show that the low‐achievement students who received the learning suggestions generated by the new approach had significantly better learning achievements than those who learned with the previous approach. Further studies of developing more effective tools or leading in other group decision strategies to help domain experts cooperatively determine the prerequisite relationships are needed.

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A multi-expert approach for developing testing and diagnostic systems based on the concept-effect model

Cited by 54 publications

References 43 publications

Improving the Learning Performance by Providing Intellectual Suggestions

Improving the Learning Performance by Providing Intellectual Suggestions

Discovering the associations between test items in an examination

A group decision approach to developing concept–effect models for diagnosing student learning problems in mathematics

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