A meta-analysis of the effectiveness of intelligent tutoring systems on college students’ academic learning.

Under the circumstance of COVID-19, online education has become an inevitable choice and a mainstream form of education in various countries. Intelligent Tutoring Systems ( ITSs ) are a critical category of a carrier of online education which refers to using Artificial Intelligence Technology ( AIT ) to realize distance teaching and learning through integrating multiple resources, assist teachers to implement online classes and help students learn courses online, etc. The target of this study is to examine the determinants that explain college students’ adoption of ITSs based on TRA and TAM under the era of COVID-19 in China.. This study targets college students who have used ITSs over the previous year to learn courses. In total, 590 valid samples were collected. Partial least squares ( PLS ) approach is employed to inspect the determinants of college students’ acceptance of using ITSs. The results of the analysis indicate that perceived ease of use, perceived usefulness, subjective norm, college students’ attitude and political influence significantly affect college students’ behavioral intention towards using ITSs. In addition, perceived usefulness, perceived ease of use, and political influence also affect college students’ attitude toward using ITSs. And consisitent with previous research, perceived ease of use has a significant effects on perceived usefulness. This study enriches the TRA and TAM theories by incorporating a new variable political influence for researchers to consider in the future. In addition, it makes several suggestions for system developers to improve system functions regarding its ease of use and for content manufactures to pay attention to quality regarding usefulness. Recommendations are provided to colleges, universities and education authorities to rethink their roles in reforming online education through ITSs.

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A Meta-Analytic Estimation of a Common Effect Size from a Series of Experiments Related To an E-Learning System Effectiveness Evaluation

Intelligent Tutoring Systems in E-Learning Environments ◽

10.4018/978-1-61692-008-1.ch016 ◽

2011 ◽

pp. 327-341

Author(s):

Ani Grubišic

Keyword(s):

Student Performance ◽

Effect Size ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Meta Analysis ◽

Learning System ◽

Tutoring Systems ◽

Learning And Teaching ◽

E Learning ◽

Series Of Experiments

As the acquisition of knowledge is often an expensive and time-consuming process, it is important to know whether it actually improves the student performance. The e-learning is a revolutionary paradigm that has lately been significantly evolving and it is closely related to the intelligent tutoring systems. Methodology for evaluating the educational influence of learning and teaching process, questions whether and in what amount, students learn effectively. Our contribution to this compulsive field of research is a meta-analysis of a series of experiments based on the same two-group methodology that reveals a more precise effect size of one particular e-learning system - eXtended Tutor-Expert System, a representative of web-based authoring shells for building intelligent tutoring systems.

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