An Open Framework for Constructivist Learning 

Hai Zhuge
Knowledge Grid Research Group, Key Lab of Intelligent Information Processing,
Institute of Computing Technology, Chinese Academy of Sciences,100080, Beijing, China
Yanyan Li
Knowledge Grid Research Group, Key Lab of Intelligent Information Processing,
Institute of Computing Technology, Chinese Academy of Sciences,100080, Beijing, China


Constructivist learning is a learner-centered learning approach. Based on the Web and agent technologies, this paper proposes an open framework to effectively support constructivist learning. The framework allows the learners to freely interact with intelligent agent and other learners, enables convenient exploration of the learning resources at the learners' own paces, and provides adaptive curriculum. 


Agent, Constructivist learning, Knowledge Grid, Ontology, Topic Map.


With the advancement of computer and Web technologies, e-learning is an emerging mode of education. However, most of the learning implementations concentrate on providing multitude of static web pages without considering the learner characteristics and not supporting active learning processes.

The literature in education suggests that learners who are actively engaged in the learning process will be more likely to achieve success [1]. Constructivist learning is an effective learning approach enabling a more active and explorative learning process.


The overall architecture is depicted in Figure1. Teachers and students can communicate with the system through the Web server. Core modules are as follows:

Figure. 1. Architecture of the constructivist learning.


The interaction functionality not only motivates the learners to learn actively, but also enables collaborative learning. Two types of interaction are supported as follows:


An ontology is a formal, explicit specification of a shared conceptualization [2]. Topic Map is a standard used to represent and organize knowledge in a way that can be optimized for navigation [3]. Based on ontology and Topic Map, we propose a Knowledge Grid model to manage the learning resources, as shown in Figure2.

Figure2. Knowledge Grid  model for managing learning resources.

We design  two types of ontologies: Domain Ontology and Pedagogical Ontology. The former contains a hierarchy of domain concepts, relationships between the concepts and properties of concepts. The latter contains pedagogical concepts, pedagogical structure, and pedagogical rules. Other knowledge items are organized as follows:

The manually inputted learning materials are indexed, classified and stored in the Knowledge Grid. Besides, resources from the Internet can be increasingly integrated to the Knowledge Grid by following the process: parses the documents, extracts keywords as index concepts, clusters based on similarity computation and ontology.


Adaptive curriculum is generated  in terms of the semantic context, including the ontology, relationships between topics, pedagogical rules, and learner profile. Currently we mainly realize the inquiry-oriented mode and in the future problem-oriented mode should also be supported. Taken the query proposed by a learner as the learning goal,  a curriculum is generated and delivered to guide learning towards his goal by following a four-step process: locates the topic matching the learning goal, performs a backward navigation algorithm to retrieve the prerequisites to the matching topic, checks and selects the knowledge items that are not sufficiently known by the learner, and presents a sequence of knowledge items with flexible navigation structure in the form of hypertext.

Additionally, three operations are provided for learners to conveniently explore the learning resources at their own paces, including skip, horizontal-expansion and vertical-expansion. Teaching agent will accordingly dynamically adjust the curriculum in response to the learnersí operations. The skip operation is to delete the specific subsection from the curriculum. The horizontal-expansion operation is to search for more referenced materials about the same topic, with the purpose to present a detailed explanation or give an example, etc. In contrast to the horizontal-expansion operation, the vertical-expansion operation is to search for more related topics (e.g. abstract topics) to enrich learner's knowledge. The learnerís activities are also traced to evaluate a learnerís performance by taking into account three factors: quiz score, review times on the same topic, and lingering period on the topic. The learnerís performance indicates how well the topic is learned, which is stored in the learner profile for later reference.


This paper proposes an open framework to support constructivist learning with the following functionalities. Firstly, it facilitates the learning progress by providing flexible interaction facilities. Secondly, it delivers adaptive learning curriculum for various learners. Thirdly, it allows learners to freely explore the learning resources at their own paces.


The research work was supported by the National Science Foundation of China (NSFC).


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