TECH8 intelligent and adaptive e-learning system: Integration into Technology and Science classrooms in lower secondary schools

Dolenc, Kosta; Aberšek, Boris

doi:10.1016/j.compedu.2014.12.010

Cited by 64 publications

(34 citation statements)

References 20 publications

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“…In this way, the eSchoolbag meets both teachers' requirements and students' learning needs. Numerous studies have revealed the fact that students' learning performance could be improved by using the eSchoolbag [4] [5]. However, there is insufficient research on how students' learning performance affects their perceptions of the eSchoolbag.…”

Section: Introductionmentioning

confidence: 99%

Students’ Technology Acceptance, Motivation and Self-Efficacy towards the eSchoolbag: An Exploratory Study

Zheng¹,

Li²,

Zheng³

2017

IJI

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Section: Introductionmentioning

confidence: 99%

Students’ Technology Acceptance, Motivation and Self-Efficacy towards the eSchoolbag: An Exploratory Study

Zheng¹,

Li²,

Zheng³

2017

IJI

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“…Authors used the Bayesian network for pulley setup. In the work (Dolenc and Aberšek, 2015) authors demonstrate the design and evaluation of intelligent tutoring system based on cognitive characteristics of the learner. This model is based on a system for collecting metadata and variables that are vital for the teaching process.…”

Section: Intelligent and Adaptive Learning Systemsmentioning

confidence: 99%

An Intelligent Learning Support System

Gavriushenko

Khriyenko

Tuhkala

2017

Proceedings of the 9th International Conference on Computer Supported Education

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Abstract:Fast-growing technologies are shaping many aspects of societies. Educational systems, in general, are still rather traditional: learner applies for school or university, chooses the subject, takes the courses, and finally graduates. The problem is that labor markets are constantly changing and the needed professional skills might not match with the curriculum of the educational program. It might be that it is not even possible to learn a combination of desired skills within one educational organization. For example, there are only a few universities that can provide high-quality teaching in several different areas. Therefore, learners may have to study specific modules and units somewhere else, for example, in massive open online courses. A person, who is learning some particular content from outside of the university, could have some knowledge gaps which should be recognized. We argue that it is possible to respond to these challenges with adaptive, intelligent, and personalized learning systems that utilize data analytics, machine learning, and Semantic Web technologies.In this paper, we propose a model for an Intelligent Learning Support System that guides learner during the whole lifecycle using semantic annotation methodology. Semantic annotation of learning materials is done not only on the course level but also at the content level to perform semantic reasoning about the possible learning gaps. Based on this reasoning, the system can recommend extensive learning material.

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“…ITSs have been used both in class and for homework in mathematics, physics, computer programming, and other subjects (A. T. Corbett et al, 2002;Oliveira Neto & Nascimento, 2012;Rai & Beck, 2012;Sklavakis & Refanidis, 2013;. Also, ITSs was incorporated in e-learning systems to provide personalized courses of action based on student's profile (Dolenc & Aberšek, 2015;Schiaffino, Garcia, & Amandi, 2008). To benefit ITSs' one-on-one tutoring paradigm, many systems have been developed to teach students how to draw a diagram.…”

Section: Intelligent Tutoring Systems (Itss)mentioning

confidence: 99%