Adaptive Interface Methodology for Intelligent Tutoring Systems

Curilem, Millaray; Azevedo, Fernando Mendes de; Barbosa, Andréa R.

doi:10.1007/978-3-540-30139-4_70

Cited by 2 publications

(2 citation statements)

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“…If r is a strategy which appears in recommendation history, we get calculation of w r by using (5). The calculation rules of w r for a strategy are as follows:…”

Section: (A) If Stop Criterion Is Satisfied or Set Is Indivisible Mamentioning

confidence: 99%

“…The relevant and correct data should be mining and used as the information and knowledge to provide a certain service [3]. It becomes an important issue to study on the tutoring systems that how to serve the needs of tutees adaptively [4].In the programming learning systems, learners have different interests, backgrounds and various ways to get the knowledge to fulfill themselves [5]. It is important to solve the problem how to help learners adopting appropriate behaviors and thoughts during programming learning process.…”

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confidence: 99%

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A Personalized Learning Strategy Recommendation Approach for Programming Learning

Chen

et al. 2017

Database Systems for Advanced Applications

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Abstract. Nowadays, it has been a significant problem to recommend learning strategy for different learners in programming learning projects. This paper discusses a personalized learning strategy recommendation approach to aid programming learning. In this paper, an improved design method of model learner strategies and programming learning strategy recommendation approach are presented. A reward factor is adopted to help to construct a learning strategy recommendation mechanism adaptively. The programming learning strategy recommendation system (ZZULI-PLS) is proposed based on those models to help learners learning in programming according to the actual progresses of learners. Usability tests are conducted to validate the recommendation efficiency in ZZULI-PLS system. Keywords: Intelligent tutoring system · Learning strategy recommendation system · Learning strategy · Learning strategy model Background and MotivationsAlong with rapid development of computer technology and network education, online learning technology applies in many universities and training institution [1]. The various data is available on the web and has increased considerably [2]. The relevant and correct data should be mining and used as the information and knowledge to provide a certain service [3]. It becomes an important issue to study on the tutoring systems that how to serve the needs of tutees adaptively [4].In the programming learning systems, learners have different interests, backgrounds and various ways to get the knowledge to fulfill themselves [5]. It is important to solve the problem how to help learners adopting appropriate behaviors and thoughts during programming learning process. Though there are many definitions of learning strategies, the common idea of learning strategies is the behaviors and thoughts that a learner takes

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“…If r is a strategy which appears in recommendation history, we get calculation of w r by using (5). The calculation rules of w r for a strategy are as follows:…”

Section: (A) If Stop Criterion Is Satisfied or Set Is Indivisible Mamentioning

confidence: 99%

mentioning

confidence: 99%