Considerations for Developing a Generalized Gradebook for an Open-Source Intelligent Tutoring System Framework

被引：0

作者：

Sinatra, Anne M. ^{[1
]}

机构：

[1] US Army Combat Capabil Dev Command DEVCOM Soldier, Orlando, FL 32826 USA

来源：

ADAPTIVE INSTRUCTIONAL SYSTEMS, AIS 2023 | 2023年 / 14044卷

关键词：

Intelligent Tutoring Systems; Gradebook; Generalized Intelligent Framework for Tutoring; GIFT;

D O I：

10.1007/978-3-031-34735-1_12

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The current paper describes a use case of an open-source intelligent tutoring system (ITS) framework, the Generalized Intelligent Framework for Tutoring (GIFT). GIFT has been primarily used by researchers, and it is a highly flexible system that allows for tutoring to be created in the topic area of the author's choice. While there are tools to output data from GIFT, there is not a traditional standardized gradebook tool that can be easily used by a non-researcher. Due to the generalizable design of GIFT, and the unique characteristics of intelligent tutoring performance, this is an interesting design challenge. The current paper discusses the current state of data export in GIFT, describes the adaptive courseflow approach to tutoring in GIFT, and discusses potential approaches to visualizing adaptive tutoring data in a way that instructors can easily understand and gain the maximum knowledge from.

引用

页码：162 / 173

页数：12

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