Intelligent tutoring systems and learning performance. Applying task-technology fit and IS success model

Date12 August 2019
Pages600-616
DOIhttps://doi.org/10.1108/OIR-11-2017-0340
Published date12 August 2019
AuthorAli Yuce,A. Mohammed Abubakar,Mustafa Ilkan
Subject MatterLibrary & information science
Intelligent tutoring systems and
learning performance
Applying task-technology fit
and IS success model
Ali Yuce
School of Computing and Technology,
Eastern Mediterranean University, Mersin, Turkey
A. Mohammed Abubakar
College of Business, Antalya Bilim University, Antalya, Turkey, and
Mustafa Ilkan
School of Computing and Technology,
Eastern Mediterranean University, Mersin, Turkey
Abstract
Purpose Intelligent tutoring systems (ITS) are a supplemental educational tool that offers great benefits to
students and teachers. The systems are designed to focus on an individuals characteristics, needs and
preferences in an effort to improve student outcomes. Despite the potential benefits of such systems, little
work has been done to investigate the impact of ITS on users. To provide a more nuanced understanding of
the effectiveness of ITS, the purpose of this paper is to explore the role of several ITS parameters (i.e.
knowledge, system, service quality and tasktechnology fit (TTF)) in motivating, satisfying and helping
students to improve their learning performance.
Design/methodology/approach Data were obtained from students who used ITS, and a structural
equation modeling was deployed to analyze the data.
Findings Data analysis revealed that the quality of knowledge, system and service directly impacted
satisfaction and improved TTF for ITS. It was found that TTF and student satisfaction with ITS did not
generate higher learning performance. However, student satisfaction with ITS did improve learning
motivation and resulted in superior learning performance. Data suggest this is due to students receiving
constant and constructive feedback while simultaneously collaborating with their peers and teachers.
Originality/value This study verifies that there was a need to assess the benefits of ITS. Based on the
studys findings, theoretical and practical implications are proposed.
Keywords Intelligent tutoring system, IS success model, Learning motivation, Learning performance,
Satisfaction, Tasktechnology fit
Paper type Research paper
Introduction
Intelligent tutoring systems
Artificial intelligence is not new. However, recent developments in the field make it an
increasingly indispensable resource, especially in learning environments. Artificial
intelligence can assist students through intelligent tutoring systems (ITS), the latest
generation of computerized educational systems, which attempt to mimic the capabilities
of human tutors. Freedman et al. (2000) describe ITS as computerized programs entwined
with some intelligence that is used for teaching and learning. Koedinger and Tanner (2013)
expanded on that definition, describing ITS as computerized programs devised to imitate
humantutoringbehaviorsandskills.Thisstudy defines ITS as any digital teaching
and learning platform that utilizes artificial intelligence to mimic and simulate human
tutoring skills.
According to Amaralet al. (2011) and Hrubik-Vulanovic(2013), ITS is a computer-assisted
learning tool and a highly progressive program (i.e. standalone and/or web-based) that is
Online Information Review
Vol. 43 No. 4, 2019
pp. 600-616
© Emerald PublishingLimited
1468-4527
DOI 10.1108/OIR-11-2017-0340
Received 28 November 2017
Revised 9 July 2018
17 January 2019
Accepted 3 February 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1468-4527.htm
600
OIR
43,4
available to support l earnersneeds and to improve learning outcomes beyond classroom
settings.ITS as a pedagogical supplement functionsto allow studentsactive engagementand
participation.This ultimately enhances knowledge and skill retention by motivating learners
and providing them with opportunities to practice (Robb, 2016).
ITS offers a number of benefits to its users. First, students can improve their
understanding of course objectives with an ind ividualized and adaptive learning
environment. Second, students can receive instant feedback as a result of interaction with
a programmed tutor. Third, ITS offers flexibility that allows learners to go beyond the
classroom to reinforce their comprehensive learning (Latham et al., 2010). Fourth, ITS
increases studentssatisfaction significantly when students have immense desire to learn in
an interactive environment (Dziuban et al., 2015). Fifth, ITS also provides self-regulated
learning materials for students through educational experience that entails an intersection
between cognitive presences, social presence and teaching presence(Torras and Bellot,
2016). More subtly, ITS is a tutoring service that aim to provide solutions to diminish the
effect of obstacles that cause dissatisfaction, disengagement, resentfulness and low learning
performance due to a lack of learning reinforcement and assistance that may be experienced
in traditional classroom environments.
In this highly digitalized world, integrating emerging technologies with education has
unlimited potential to make significant contributions to teaching and learning outcomes.
Although the existing literature emphasizes similar ideas, most studies both overlooked the
impact of ITS and failed to explore the factors influencing learning outcomes when ITS is
utilized. Furthermore, the current literature lacks a complete frame of reference on the
potential role of success models and tasktechnology fit (TTF) to create student
engagement with ITS. Prior studies on ITS (i.e. Aleven et al., 2015; Huang et al., 2016;
Malekzadeh et al., 2015; Steenbergen-Hu and Cooper, 2014) examine only one or two factors
to predict the effective of ITS over traditional learning.
This study builds existing findings with well-established models and factors to further
understanding on the functional mechanisms associated with ITS in improving learning
outcomes. This study aims to uncover the factors that are critical for ITS users regarding
learning satisfaction, motivation, productivity and performance. In doing so, this paper
strives to answer the following questions: does ITS influence studentsmotivation and
satisfaction by providing quality information along with a high-quality system and service?
Does ITS increase student satisfaction and performance by providing learning activities
based on TTF? Do student users of ITS desire to use the tutoring systems more as their
student satisfaction is increased?
Literature review
Information systems (IS) success model
Gorla et al. (2010) defined information system (IS) quality as a confirmatory for the end
usersinformation and service requirements and adhere to industry standards.This model
entails system quality, knowledge quality, service quality and usage intention/use, user
satisfaction, and individual/organizational benefits (Delone and McLean, 2003; Wang and
Liao, 2008). However, the fundamental pillars of IS used to determine an ISs success are:
system quality, knowledge quality and service quality. System quality is related to the
characteristics of the software program. Knowledge quality relates to how accurately
information is transmitted to the end user. Finally, service quality relates to the impact of
information and system on the end user (Delone and McLean, 2003).
Tasktechnology fit model
The TTF model is a conceptual model developed by Goodhue and Thompson (1995) that
explores the relationships between tasks, technology and performance. The TTF model
601
ITS and
learning
performance

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT