Recommendation system based on rule-space model of two-phase blue-red tree and optimized learning path with multimedia learning and cognitive assessment evaluation

Chen, Yung-Hui; Tseng, Chun-Hsiung; Huang, Ching-Lien; Deng, Lawrence Y.; Lee, Wei-Chun

doi:10.1007/s11042-016-3717-3

Cited by 9 publications

(6 citation statements)

References 36 publications

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“…The key technical challenges involved in adaptive learning include the following: (1) build a large question bank that covers a wide range of knowledge points that could measure students’ learning abilities as many as possible; (2) determine the topic selection and test termination strategy; (3) construct a measurement model to estimate learners' ability level and knowledge state; (4) determine the recommendation algorithms, such as content‐based recommendation (Chen et al., 2017), knowledge‐based recommendation (Wan & Niu, 2018), collaborative filtering (Liu, 2019), colony optimization (Kurilovas et al., 2014), and reinforcement learning (Tan et al., 2019), that recommend the optimal learning methods for students to realize their continuous progress.…”

Section: From Teaching For Assessment To Adaptive Learningmentioning

confidence: 99%

Changing Educational Assessments in the Post‐COVID‐19 Era: From Assessment of Learning (AoL) to Assessment as Learning (AaL)

Yang

Xin

2022

Educational Measurement

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The upgrade educational information technology triggered by COVID-19 has shaped a new educational order and new educational forms. As a result, traditional educational measurement is now facing a systematic transformation, that is, from the Assessment of Learning (AoL) to Assessment for Learning (AfL), and finally to Assessment as Learning (AaL). By showing the initiative and the flexibility of large-scale online learning during the COVID-19 pandemic, this paper examines the evolution from AoL to AaL from four aspects: participants, test form, multivariate data for process-based measurement, and measurement models for multivariate data. We propose multidisciplinary corporations in the field, which integrate education, psychology, and information technology into the theories and methods of educational measurement. Further, we emphasize that the validity, ethics, and fairness of the measurement should also be considered the critical issues. Researchers and practitioners of educational measurement must persist in pursuing the substantive significance of measurement and provide unique experience and guidance for the theoretical and practical development of educational assessment in this great revolution.

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Section: From Teaching For Assessment To Adaptive Learningmentioning

confidence: 99%

Changing Educational Assessments in the Post‐COVID‐19 Era: From Assessment of Learning (AoL) to Assessment as Learning (AaL)

Yang

Xin

2022

Educational Measurement

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“…To solve the problem of forming a learning path, various mathematical tools are used: Petri nets [16], graph theory [17], artificial intelligence technologies [4,5,18,19], decision trees [20] and others. However, the application of these approaches does not make it possible to obtain a predicted value of the number of points in the final testing.…”

Section: Related Work Analysismentioning

confidence: 99%

Mathematical Model for Adaptive Technology in E-learning Systems

Barchenko¹,

Tolbatov²,

Lavryk³

et al. 2022

IJMECS

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The emergence of a large number of e-learning platforms and courses does not solve the problem of improving the quality of education. This is primarily due to insufficient implementation or lack of mechanisms for adaptation to the individual parameters of the student. The level of adaptation in modern e-learning systems to the individual characteristics of the student makes the organization of human-computer interaction relevant. As the solution of the problem, a mathematical model of the organization of human-computer interaction was proposed in this work. It is based on the principle of two-level adaptation that determines the choice of the most comfortable module for studying at the first level. The formation of an individual learning path is performed at the second level. The problem of choosing an e-module is solved using a fuzzy logic. The problem of forming a learning path is reduced to the problem of linear programming. The input data are the characteristics of the quality of student activity in the education system. Based on the proposed model the computer technology to support student activities in modular e-learning systems is developed. This technology allows increasing the level of student's cognitive comfort and optimizing the learning time. The most important benefit of the proposed approach is to increase the average score and increase student satisfaction with learning.

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“…Therefore, we use the RSM proposed by Tatsuoka (1983) to deduce the hierarchical relationship of the order of each learning object/chapter subject in the same test subject, as a reason for learning diagnosis, to investigate and improve learning performance, and to infer the structure tree of all reasonable learning performances. Thus, the analysis steps and process of the RSM are as follows (Y. H. Chen, Tseng, et al, 2017):…”

Section: Rsm Analysis Stepsmentioning

confidence: 99%

“…In order to adequately improve the learning performance of the network principles' course chapters and the passing rate of MTA certification, we invoke a learning concept map based on the FAHP and RSM analysis, combined with related definitions of relation weight (RW) and confidence level (CL) (Y. H. Chen, Tseng, et al, 2017) to infer the optimized learning path algorithm, and then apply it to the prototype system with learning performance analysis based on the online learning and testing system. Therefore, relevant definitions include:…”

Section: Inference Of the Optimized Learning Pathmentioning

confidence: 99%

Cognitive Learning Assessment Based on FAHP and RSM: A Case Study of Introduction to Network course

Lin

Chang

Chen

2021

Journal of Educational Computing Research

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With the progress and innovation of digital technology, people's knowledge acquisition, information exchange, and communication modes have changed significantly. The universality of emerging technology media enables instructional designers to use digital media to provide different teaching materials and teaching methods to meet the needs of individual learners according to their differences. Accordingly, this study takes the Introduction to Network course as an example, proposes a Fuzzy Analytic Hierarchy Process combined with Rule-Space Model to guide and analyze students' learning status, and imports Microsoft Technology Association international certification as empirical analysis. The study revealed that, the experts believe that “understanding protocols and services” is the most important part of the basic knowledge of the Internet, followed by “understanding network infrastructure” and “understanding network hardware.” In the section on learning performance, the average progress rates of two class were 69.44% and 62.20%, respectively, the students' scores were significantly improved. In the section on obtaining Microsoft Technology Association certification, the passing rates were 93.44% and 93.10%, which were significant improvements in certification passing rate. In the future, this study can be applied to other fields to improve the relative learning effect and make it broader and more diversified.

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Recommendation system based on rule-space model of two-phase blue-red tree and optimized learning path with multimedia learning and cognitive assessment evaluation

Cited by 9 publications

References 36 publications

Changing Educational Assessments in the Post‐COVID‐19 Era: From Assessment of Learning (AoL) to Assessment as Learning (AaL)

Changing Educational Assessments in the Post‐COVID‐19 Era: From Assessment of Learning (AoL) to Assessment as Learning (AaL)

Mathematical Model for Adaptive Technology in E-learning Systems

Cognitive Learning Assessment Based on FAHP and RSM: A Case Study of Introduction to Network course

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