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Supporting teachers in adaptive educational systems through predictive models: A proof of concept
Abstract:

Adaptive educational systems (AESs) guide students through the course materials in order to improve the effectiveness of the learning process. However, AES cannot replace the teacher. Instead, teachers can also benefit from the use of adaptive educational systems enabling them to detect situations in which students experience problems (when working with the AES). To this end the teacher needs to monitor, understand and evaluate the students’ activity within the AES. In fact, these systems can be enhanced if tools for supporting teachers in this task are provided. In this paper, we present the experiences with predictive models that have been undertaken to assist the teacher in PDinamet, a web-based adaptive educational system for teaching Physics in secondary education. Although the obtained models are still very simple, our findings suggest the feasibility of predictive modeling in the area of supporting teachers in adaptive educational systems

Keywords: Adaptive educational systems Machine learning Predictive models Descriptive models
Author(s): .
Source: Expert Systems with Applications 39 (2012) 621–625
Subject: مدیریت آموزشی
Category: مقاله مجله
Release Date: 2012
No of Pages: 5
Price(Tomans): 0
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