The Role of Learner Characteristics in the Adaptive Educational Hypermedia Systems: The Case of the MATHEMA

Papadimitriou, Alexandros; Gyftodimos, Georgios

doi:10.5815/ijmecs.2017.10.07

Cited by 6 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this research, OBCSS is based on AHAM (Adaptive Hypermedia Application Model) reference model which is one of the highly accepted models in the literature (Knutov et al, 2009;Papadimitriou, 2017). AHAM reference model is emerged as a base model in adaptive hypermedia design (De Bra et al, 1999).…”

Section: Aham Reference Modelmentioning

confidence: 99%

Utilizing a smart cognitive support system for K-8 education

Kaya

Altun

2018

Smart Learn. Environ.

View full text Add to dashboard Cite

This research is aimed to determine how cognitive apprenticeship framework could be utilized in designing and utilizing an ontology based cognitive support system (OBCSS). It is also aimed to evaluate the use of OBCSS in educational settings to determine how much mental effort is needed for students to use it and to determine whether use of OBCSS decreases disorientation and supports navigation as stated in literature. Scales are used to get perceived behavioral data from the participants. This data is used to investigate experiences of users who have gender and computer experience diversities. Personal information form, mental effort evaluation scale and perceived disorientation scale are used to collect data. Log data is collected from learners' interaction with system. Sample of this study are fifth and sixth grade students at three state schools and one private school in Central Turkey. At the first phase, data is collected from 83 students, and this data is used for Reliability and Validity of the disorientation scale. At second phase data is collected from 89 students, and this data is used for the analysis of the OBCSS. System is evaluated by collecting data from real time users. According to results of statistical analyses, mental efforts of learners did not differ across gender, daily average computer and internet use, and frequency of internet use for studying. Similarly, perceived disorientation and perceived ease of use did not differ across gender, daily average computer and internet use and frequency for using internet to study. According to log data, OBCSS can provide different personalized learning paths based on the current knowledge of learners.

show abstract

Section: Aham Reference Modelmentioning

confidence: 99%

Utilizing a smart cognitive support system for K-8 education

Kaya

Altun

2018

Smart Learn. Environ.

View full text Add to dashboard Cite

show abstract

“…CS considers both learner‐related features and curriculum‐related constraints, including learner's ability, learner's available time, learner's objectives, LOs prerequisites, LOs difficulty, and LOs required time . In general, adaptive techniques use a representation of the learner's characteristics (e.g., Papadimitriou and Gyftodimos’) to provide a better adaptation.…”

Section: Introductionmentioning

confidence: 99%

Swarm intelligence to solve the curriculum sequencing problem

Menaï

Alhunitah

Al-Salman

2018

Comp Applic In Engineering

View full text Add to dashboard Cite

The curriculum sequencing (CS) problem asks to find a personalized optimal path for a learner in an e‐learning environment. Solving this problem contributes to developing adaptive e‐learning systems which provide personalized learning paths compatible with the individual profiles of the learners. The solutions to large CS instances can be only approximated as this problem is NP‐hard. In this paper, we formulate the CS problem as a constraint satisfaction problem and investigate swarm intelligence methods to solve it, including a newly introduced method called SwarmRW and the widely used ant colony system (ACS). In addition, we introduce two variants of SwarmRW, called SwarmRW_rnd and SwarmRW_inc. The performance results obtained on real data show that SwarmRW_rnd achieved the best results in terms of maximizing the number of satisfied constraints. However, SwarmRW_inc demonstrated the best trade‐off between the solution quality and the running‐time to obtain it.

show abstract

Lifelong Education of Sports Media Professionals Based on System Theory

Wang

Zhang

2019

Advances in Artificial Systems for Medicine and Education II

View full text Add to dashboard Cite

The Role of Learner Characteristics in the Adaptive Educational Hypermedia Systems: The Case of the MATHEMA

Cited by 6 publications

References 31 publications

Utilizing a smart cognitive support system for K-8 education

Utilizing a smart cognitive support system for K-8 education

Swarm intelligence to solve the curriculum sequencing problem

Lifelong Education of Sports Media Professionals Based on System Theory

Contact Info

Product

Resources

About