Extract Tacit Knowledge in the Learner Model of the Smart Tutoring System

Hibbi, Fatima-Zohra; Abdoun, Otman; Haimoudi, El Khatir

doi:10.3991/ijet.v15i04.11781

Cited by 7 publications

(5 citation statements)

References 2 publications

(2 reference statements)

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“…Explicit knowledge, which is easy to express and codify, is often contrasted with tacit knowledge. Tactical knowledge includes things like intuition, creativity, and ability that have been honed through repetition and experience (Hibbi et al, 2020). Many industries, such as knowledge management, requirements engineering, and sustainable agriculture, rely on tacit knowledge (Curry &;Kirwan, 2014;Wipawayangkool & Teng, 2016).…”

Section: Tacit Knowledgementioning

confidence: 99%

Implementation Tacit Knowledge, Internal Knowledge on Performance Management: (Systematic Literature Review)

Dharmanto,

Sawitri,

Faeni

et al. 2024

IJSR

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This paper is to find the results of the implementation of the variables used in this paper which have been used in the research findings, problems and phenomena in this paper as illustrations and solutions from the research findings in the literature. A thorough literature review was conducted as part of the research methodology for this paper. A selection of related scientific articles were collected, analyzed, and reviewed as part of the literature review. The scope of the study was determined based on scores using the PICO framework (population problem, intervention, comparison). The implementation of these three variables already exists, but it is not related to all the variables in one literature in one paper, this paper provides an answer that these variables already exist, and the problems presented above are answered even though they are not optimal and satisfactory in the paper this. The implementation of the three variables in qualitative results is proven and answers problems that are not yet satisfactory.

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Section: Tacit Knowledgementioning

confidence: 99%

Implementation Tacit Knowledge, Internal Knowledge on Performance Management: (Systematic Literature Review)

Dharmanto,

Sawitri,

Faeni

et al. 2024

IJSR

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“…The first one concerns the difficulties encountered by the learner module to extract implicit knowledge. For this, the authors have suggested a solution to convert tacit knowledge into explicit knowledge in the learner model of the intelligent tutoring system with the help of a competitive learning algorithm [12]. The second observation concerns the traces generated by the learners.…”

Section: Learner Modulementioning

confidence: 99%

Genetic Approach for Improved Prediction of Adaptive Learning Activities in Intelligent Tutoring System

Hibbi,

Abdoun,

Haimoudi

2023

IJACSA

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The intelligent tutoring system registers the reference data of the learners in a database. This data is stored for later use in the instructional module. Designing a student model is not an easy task. It is first necessary to identify the knowledge acquired by the learner, then identify the learner's level of understanding of the functionality and finally identify the pedagogical strategies used by the learner to solve a problem. These elements must be taken into account in the development of the learner model. Learner characteristics must be considered in several forms. To build an effective learner model, the system must take into consideration both static (Learner preferences) and dynamic (Compartmental action) student characteristics. The objective of the article is to work out the learner model of the intelligent tutoring system by suggesting a new learning path. This proposal is based on the constructivist approach and the activist style (based on experimentation). According to the KOLB model, the authors propose a list of pedagogical activities depending on the learners' profile. Based on the learners' actions, the system reduces the list of activities based on two criteria: the learner's preference and the presence of one or more activities based on the activist style using genetic algorithm as an evolutionary algorithm. The results obtained led us to improve the learning process through a new conception of the ITS learner model.

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“…It emphasizes the importance of interactional activities with mentors who have rich tacit knowledge and have imparted it to newcomers to further their growth and advancement (Jacqueline, 2010). Hibbi et al (2020) agreed that knowledge, especially tacit knowledge, is dynamic. It is born of human interactions; created, transferred, applied, and created again.…”

Section: Literature Reviewmentioning

confidence: 99%

Mentoring and Tacit Knowledge Transfer in Novice Teachers From Chinese Middle Schools: Mediating Effect of Job Crafting

Xu-bin

Hisrich

et al. 2022

Front. Educ.

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In this study, we explore how mentoring relates to tacit knowledge transfer among middle school novice teachers in China and how job crafting mediates this relationship. In total, 465 Chinese novice teachers participated in this study and completed a set of self-reports measuring the mentoring function, tacit knowledge transfer, and job crafting. An analysis of the reports indicated that: (1) Mentoring, job crafting, and tacit knowledge transfer were positively correlated; (2) Four sub-factors of the mentoring function and five sub-factors of job crafting were significantly related to tacit knowledge transfer; (3) job crafting played a mediating role between mentoring and tacit knowledge transfer; (4) the mediating path of task crafting and skill crafting (two sub-factors of job crafting) between mentoring and tacit knowledge transfer was significant, while the mediating effect of role crafting, cognitive crafting, and relationship crafting (the other three sub-factors of job crafting) was not significant.

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Extract Tacit Knowledge in the Learner Model of the Smart Tutoring System

Cited by 7 publications

References 2 publications

Implementation Tacit Knowledge, Internal Knowledge on Performance Management: (Systematic Literature Review)

Implementation Tacit Knowledge, Internal Knowledge on Performance Management: (Systematic Literature Review)

Genetic Approach for Improved Prediction of Adaptive Learning Activities in Intelligent Tutoring System

Mentoring and Tacit Knowledge Transfer in Novice Teachers From Chinese Middle Schools: Mediating Effect of Job Crafting

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