A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors

Hwang, Gwo‐Jen; Sung, Han-Yu; Chang, Shao‐Chen; Huang, Xing-Ci

doi:10.1016/j.caeai.2020.100003

Cited by 84 publications

(62 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In traditional education, all students are provided with the same material [6]. An identical teaching methodology and rate of progress are utilized during their course [7]. After graduation, the engineers encounter many problems during site maintenance as they do not have adequate information.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] An Educational Web‐Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance

et al. 2021

View full text Add to dashboard Cite

Nowadays, higher education worldwide is affected by the COVID-19 pandemic. It has affected students’ attendance in the universities and causes universities to close down in more than 190 countries. On the other hand, novice engineers studied only a few lectures related to highway engineering. Their lectures have included very little knowledge about asphalt pavement construction as highway engineering consists of many areas that are not studied in detail during their studying years subject to their traditional education. Due to all mentioned, a new drive to promote online learning paves the way to evaluate our future approach to curriculum development and delivery of educational materials for engineering courses. However, experts can offer solutions to these problems using their past experience. Hence, a system that allows experts to share their experience with other engineers after completing a project is needed. Nevertheless, the web-based expert system for maintaining flexible pavement problems in tropical regions (ESTAMPSYS) designed in this study is a novel concept. Prior to developing this system, the need for such a system was determined through literature review and validated through a questionnaire survey. Experts were interviewed, and a questionnaire survey was conducted to construct the knowledge base of the system. Knowledge was presented as rules and coded in software through PHP programming. Web pages that support the user interface were designed using a framework that consists of CSS, HTML, and J-Query. Furthermore, the system was tested by an array of users engaged in highway engineering, namely, experts, teaching experts, novice engineers, and students. The mean values of the overall system evaluation performed by 20 users using a five-point Likert scale were 4, 4.5, 3.75, 4.25, 5, 4, and 3.5. Expert and user satisfaction prove the effectiveness of the proposed system.

show abstract

Section: Introductionmentioning

confidence: 99%

[Retracted] An Educational Web‐Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Ratings are a strong indicator of the usability of the system also. Fuzzy learners use cognitive attributes to train the model (Hwang et al, 2020a ). The adaptivity and dynamicity of the designs are ensured by exploring learning the paths and patterns within the system.…”

Section: Discussionmentioning

confidence: 99%

“…To improve learners' learning capacities, the proposed sequence also reflected the learner's preferences Fraihat and Shambour ( 2015 ) Ontology Model Learner requirements, LO attributes Make use of intra and extra semantic links between LOs and the learner's needs. Used shortest path algorithm Hwang et al( 2020a ) Hybrid (Fuzzy Logic Based, Rule-Based) Learners' affective and cognitive factors Through Ontology Model serving the learner's learning behaviors, the expert system determines the learner's affective states, and the learner's cognitive status is registered. To suggest pre-classified LOs based on the above criteria, a set of fuzzy inference rules is used Ibrahim et al ( 2020 ) Hybrid (Ontology Model, Fuzzy Logic Based) Learning goals, Learner Interests The contents' relevant class is chosen based on the frequency concept and weight concept for a requested topic in the class identification module.…”

Section: Analysis Of Literature On Content Recommender Systemsmentioning

confidence: 99%

A systematic literature review on adaptive content recommenders in personalized learning environments from 2015 to 2020

Renumol

2021

J. Comput. Educ.

115

View full text Add to dashboard Cite

In personalized learning, each student gets a customized learning plan according to their pace of learning, instructional preferences, learning objects, etc. Hence the content recommender system in Personalized Learning Environment (PLE) should adapt to learner attributes and suggest appropriate learning resources to aid the learning process and improve the learning outcomes. This systematic literature review aims to analyze and summarize the studies on learning content recommenders in adaptive and personalized learning environments from 2015 to 2020. The publications were searched using proper keywords and filtered using the inclusion and exclusion criteria, which resulted in 52 publications. This paper summarizes the recent trends in research on different aspects of the recommender systems, such as learner attributes, recommendation methods, evaluation metrics, and the usability tests used by the researchers. It is observed that cognitive aspects of learners like learning style, preferences, knowledge level, etc., are used by most studies than non-cognitive aspects as social tags or trust. In most cases, recommendation engines are a hybrid of collaborative filtering, content-based filtering, ontological approaches, etc. All models were evaluated for the correctness of the prediction done, and a few studies have also done evaluations based on learner satisfaction or usability.

show abstract

“…Based on existing studies from 2014 until 2020, it was understood that defense practice is considered as highly conventional even after several revolutions in educational pedagogy (Hwang et al, 2020).…”

Section: Problem Statementmentioning

confidence: 99%

Implementing Flexible Systems in Doctoral Viva Defense Through Virtual Mechanism

Raju

2021

Glob J Flex Syst Manag

View full text Add to dashboard Cite

Year 2020 has cultivated new arena in education. Covid-19 has not only reformed the world but also revived the process of operations. One among them is academics. Never in history of education was a lecture delivered without the physical presence of lecturers, in an academic environment. Even in present wildest innovative decade, the idea of eliminating the academia was not an option. However, after the pandemic encounter, it happened. These are not mere changes, but it is a transformation. While this phenomenon is getting acceptable gradually by takers, the mammoth turnaround is happening in Ph.D. final viva voce defenses too. Practice of online defense is approved by leading Universities so as to avoid stagnation of researchers in final stage. Question is, will it be appropriate to accept final defenses in online stream? and has the institutions developed rubrics to assess the researches which are presented online? Finally, if this is the only choice then how best we can use the technology to generalize it as a system? This research was executed through Delphi technique method from academia, research aspirants and policy-makers. Partial least square is used to quantify the data after interpreting qualitative data. Thirteen homogeneous University's respondents were used as sample. Focus of this paper remains to substantiate the benefits of emerging technology and developing a scheme for virtual streaming, rather identifying reasons to avoid them.

show abstract

A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors

Cited by 84 publications

References 39 publications

[Retracted] An Educational Web‐Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance

[Retracted] An Educational Web‐Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance

A systematic literature review on adaptive content recommenders in personalized learning environments from 2015 to 2020

Implementing Flexible Systems in Doctoral Viva Defense Through Virtual Mechanism

Contact Info

Product

Resources

About