Design of adaptive hypermedia learning systems: A cognitive style approach

Mampadi, Freddy; Chen, Sherry Y.; Ghinea, Gheorghita; Chen, Ming-Puu

doi:10.1016/j.compedu.2010.11.018

Cited by 125 publications

(76 citation statements)

References 41 publications

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“…Kişiselleştirilenbu ortamın, öğrenen performansını pozitif yönde etkilediği (Chen ve Duh, 2008;Mampadi, Chen, Ghinea ve Chen, 2011;Yang, Hwang ve Yang, 2013), öğrenme sürecini kolaylaştırdığı Papanikolaou, Grigoriadou, Magoulas ve Kornilakis, 2003;Popescu, 2010;Tseng, Chu, Hwang ve Tsai, 2008) ve öğrenen memnuniyetini arttırdığı (Mampadi vd., 2011;Papanikolaou vd., 2003;Popescu, 2010;Yang vd., 2013)yönünde alanyazında birçok çalışma mevcuttur.…”

Section: Introductionunclassified

Content Analysis of Studies Conducted on Adaptive Educational Hypermedia Environments in Turkey

Güyer

Çebi

2015

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Section: Introductionunclassified

Content Analysis of Studies Conducted on Adaptive Educational Hypermedia Environments in Turkey

Güyer

Çebi

2015

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“…To measure the correctness of an answer, there is a 'set of rules' to be created. A multiple-choice test may be considered a 'set of rules', and the score produced could be operationally defined as knowledge [16,19,20]. To measure knowledge on a particular topic, the test items must represent the topic.…”

Section: The Concept Of Knowledgementioning

confidence: 99%

An Adaptive User Interface for an E-learning System by Accommodating Learning Style and Initial Knowledge

Hariyanto¹,

Köhler²

2017

Proceedings of the International Conference on Technology and Vocational Teachers (ICTVT 2017)

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Abstract-There is a conception among researchers that every student has his or her own learning style preferences. One student cannot be treated as same as the other students. A specific strategy is required to provide a learning environment that is suitable for different students' preferences. In the context of technology-enhanced learning, it is urgently necessary to design an adaptive e-learning system based on multiple learning criteria. This paper presents the design of a user interface for an e-learning system that can adapt to multiple learning styles and initial knowledge levels. To evaluate the design concept, an application has been developed and then tested based upon a functional test approach. As a result, it was found that the elearning system could react as intended, presenting the learning material and navigation components based on both the learning styles and initial knowledge of the students.

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“…Previous research generally indicates that positive results occur when individual differences and orientations of learning are taken into consideration when designing adaptive learning systems, but there is some evidence that adaptive learning may have negative aspects as well (e.g., Magoulas et al, 2003;Peredo et al, 2011;Tseng et al, 2008). Moreover, the majority of research focuses on pedagogical activities, such as adaptive presentations or navigational frameworks that are tailored to specific aspects of the teaching content (Hsiao, Sosnovsky, & Brusilovsky, 2010;Mampadi et al, 2011). These studies have failed to investigate the notion of scaffolding on the promotion of students' cognition and motivation when acquiring conceptual knowledge.…”

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confidence: 99%

“…However, in the context of computer-supported learning environments in which the teacher is outside of the learning process or is not immediately available, learners' engagement in and motivation to complete a task requiring mental effort decreases over time (Sins, Van Joolingen, Savelsbergh, & Van Hout-Wolters, 2008;Whipp & Chiarelli, 2004;Zhu, 2006). Therefore, a major interest for researchers and educators is examining how this type of learning environment can provide both dynamic and adaptive support for learners.In recent years, research examining the development of adaptive educational systems has offered advanced forms of learning environments that attempt to meet the needs of different students (Akbulut & Cardak, 2012;Diziol, Walker, Rummel, & Koedinger, 2010;Magoulas, Papanikolaou, & Grigoriadou, 2003;Mampadi, Chen, Ghinea, & Chen, 2011;Peredo, Canales, Menchaca, & Peredo, 2011;Tseng, Chu, Hwang, & Tsai, 2008). In practical terms, adaptive systems build a model that is tailored to the learner's characteristics, knowledge, goals, learning style and preferences (e.g., Brusilovsky, 2001;Papanikolaou, Grigoriadou, Kornilakis, & Magoula, 2003;Rasmussen & Davidson-Shivers, 1998;Specht & Oppermann, 1998).…”

mentioning

confidence: 99%

“…In recent years, research examining the development of adaptive educational systems has offered advanced forms of learning environments that attempt to meet the needs of different students (Akbulut & Cardak, 2012;Diziol, Walker, Rummel, & Koedinger, 2010;Magoulas, Papanikolaou, & Grigoriadou, 2003;Mampadi, Chen, Ghinea, & Chen, 2011;Peredo, Canales, Menchaca, & Peredo, 2011;Tseng, Chu, Hwang, & Tsai, 2008). In practical terms, adaptive systems build a model that is tailored to the learner's characteristics, knowledge, goals, learning style and preferences (e.g., Brusilovsky, 2001;Papanikolaou, Grigoriadou, Kornilakis, & Magoula, 2003;Rasmussen & Davidson-Shivers, 1998;Specht & Oppermann, 1998).…”

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An adaptive scaffolding e-learning system for middle school students’ physics learning

Chen

2014

AJET

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This study presents a framework that utilizes cognitive and motivational aspects of learning to design an adaptive scaffolding e-learning system. It addresses scaffolding processes and conditions for designing adaptive scaffolds. The features and effectiveness of this adaptive scaffolding e-learning system are discussed and evaluated. An experiment was conducted within the domain of velocity and acceleration. The results revealed that the adaptive scaffolding system appeals to students and promotes improved performances and motivational outcomes. Specifically, the results suggested that learners with lower levels of knowledge who possessed extrinsic motivation benefited the most from the adaptive scaffolds. The implications of the design guidelines for developing personalized, adaptive scaffolding e-learning systems are discussed, and future research directions are recommended. IntroductionRecently, researchers have called for the use of scaffolding to help students learn complex and abstract knowledge (Azevedo, Cromley, & Seibert, 2004;Ge, Chen, & Davis, 2005; Van den Boom, Paas, Van Merrienboer, & Van Gog, 2004). A major reason for this call is that the development of human cognition is composed of a current level and a potential level, and that in between these is the zone of proximal development (ZPD) (Vygotsky, 1978). After accurately diagnosing students' current skill levels, we use scaffolding to advance their competence and to gradually hand the responsibility for learning to the students (Beed, Hawkins, & Roller, 1991;Wood, Bruner, & Ross, 1976). While several studies have lent support to the beneficial effect of scaffolding on student learning, their results showed that scaffolding must be supportive of students' learning tasks and must be adaptable to students' current level of understanding and affective state so that it can work within the students' prerequisite ZPD's (Chang & Sun, 2009;Rosenshine & Meister, 1992). Adaptive scaffolding reflects evidence that one size does not fit all (Reigeluth, 1996), and implies scaffolding should not only focus on student features such as cognitive status, but psychological traits that affect their learning. While human tutors have been found to be beneficial to students' learning, there is little empirical evidence to address situations in which no human tutor is immediately available (Akbulut & Cardak, 2012). Moreover, the use of scaffolding adaptively to meet the needs of individuals with different levels of prior knowledge, real-world experience, and problem-solving competencies is still limited. Given this research gap, this study proposed an adaptive scaffolding e-learning system that mapped the right type of scaffolding to different learners to maximize the benefits of scaffolding, and conducted a summative evaluation to conclude the effectiveness and efficiency of such a system to students' learning and motivation. The findings of this study sought to contribute to the literature on learning with e-learning systems by demonstrating that externally regulat...

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Design of adaptive hypermedia learning systems: A cognitive style approach

Cited by 125 publications

References 41 publications

Content Analysis of Studies Conducted on Adaptive Educational Hypermedia Environments in Turkey

Content Analysis of Studies Conducted on Adaptive Educational Hypermedia Environments in Turkey

An Adaptive User Interface for an E-learning System by Accommodating Learning Style and Initial Knowledge

An adaptive scaffolding e-learning system for middle school students’ physics learning

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