Adaptive instructional planning using ontologies

Karampiperis, Pythagoras; Sampson, Demetrios G.

doi:10.1109/icalt.2004.1357388

Cited by 45 publications

(22 citation statements)

References 6 publications

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“…Later approaches in CG (such as [4], [5], [9], [10]) all have in common that the pedagogical knowledge used in these systems is rather rudimentary [2]. As a consequence, these systems cannot generate with respect to different learning goals.…”

Section: Related Workmentioning

confidence: 99%

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The Design and Application of an Automatic Course Generation System for Large-Scale Education

Tan

Ullrich

Wang

et al. 2010

2010 10th IEEE International Conference on Advanced Learning Technologies

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Abstract-In China, the number of online learners who attend formal education has quadrupled in the last 5 years to 8.2 millions until the end of 2008. How can online teachers build and update web-courses for such a large numbers of online students -courses that ideally respect the different requirements of the students? In this paper we describe an automatic course generation System (ACGS) developed at the Shanghai Jiao Tong University (SJTU). In this ACGS, teachers can build web-based courses according to their own instructional plan and publish the web-based courses without requiring technological support. Teachers can also update the web-courses whenever the instructional objective changes. The web-course learning environment generated from this system takes into account pedagogical scenarios. The ease of use of our system is illustrated by its quickly increasing number of users. About 50 teachers in the SJTU School of Continuing Education (SOCE-SJTU) have developed 45 web-courses in only two months. These 45 web-courses have been provided to about 5800 online learners in the last 2009 autumn semester alone.

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Section: Related Workmentioning

confidence: 99%

“…Following [9], we consider an instructional plan as connecting two different spaces. The first one is the knowledge space, which includes the concepts and the relationship among them -actually a network of concepts, stored in the Knowledge repository (KR).…”

Section: The General Framework Of the Automatic Course Generatiomentioning

confidence: 99%

The Design and Application of an Automatic Course Generation System for Large-Scale Education

Tan

Ullrich

Wang

et al. 2010

2010 10th IEEE International Conference on Advanced Learning Technologies

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“…All of them use various inputs provided during the learning process and aim to tune the activities and actions of the learner to get the best learning experience as possible (Butz, Olivier et al, 2003). A wide and consistent set of rules of dependencies among users, methods and learning objects is needed to describe these eight types of adaptation, and moreover their possible combinations (Karampiperis and Sampson, 2004). Boticario (2005) examine the external adaptation of a UoL, making modifications to both the internal elements of the UoL and the playing layer through which the UoL is delivered (player).…”

Section: Types Of Adaptationmentioning

confidence: 99%

How to represent adaptation in e-learning with IMS learning design

Burgos

Tattersall

Koper

2007

Interactive Learning Environments

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“…As such there is no explicit pedagogic guidance offered to the author, but it could be argued that IMS LD has in built pedagogical biases. The authoring process supported in ASK-LDT consists of several steps [2]. The first allows the definition of the pedagogical elements and is followed by the definition of the environment.…”

Section: State Of the Artmentioning

confidence: 99%

“…Over the last few years a number of adaptive eLearning tools for authoring have begun to appear as witnessed by the success of the A3H Workshop [1]. A number of these tools have been little more than technical editors to allow for the generation of adaptive content [2]. Others have focused on designing complete adaptive courses, e.g.…”

Section: Introductionmentioning

confidence: 99%

Supporting Users in Creating Pedagogically Sound Personalised Learning Objects

Brady

Conlan

Wade

et al.

Lecture Notes in Computer Science

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Abstract. Successful eLearning is predicated on the application of pedagogies appropriate to online education that respond to the capabilities and needs of the learners. Typically, designing and assembling personalized Learning Objects that respond to the pedagogical needs of a variety of different learners is an expensive and time-consuming process requiring both domain and educational expertise. Educators have the domain expertise and formal or informal pedagogical knowledge to create quality Learning Objects. However, they lack the tools and often the specific knowledge of online pedagogical approaches that make it time efficient for them to do so. This paper describes the motivation behind, the workflow supported by and the evaluation of the LO Generator, a tool that offers personalized support and scaffolding for users, who are not necessarily content creation or pedagogical experts, in assembling pedagogically sound personalized Learning Objects.

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Adaptive instructional planning using ontologies

Cited by 45 publications

References 6 publications

The Design and Application of an Automatic Course Generation System for Large-Scale Education

The Design and Application of an Automatic Course Generation System for Large-Scale Education

How to represent adaptation in e-learning with IMS learning design

Supporting Users in Creating Pedagogically Sound Personalised Learning Objects

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