Students’ Continuance Intention to Use Moodle: An Expectation-Confirmation Model Approach

Abstract

Aim/Purpose: This study aims at investigating the factors that influence students’ continuous intention to use Moodle, as an exemplar of learning management systems (LMSs), in the post-adoption phase. Background: Higher education institutions (HEIs) have invested heavily in learning management systems (LMSs), such as Moodle and BlackBoard, as these systems enhance students’ learning and improve their interactions with the educational systems. While most studies on LMSs have focused on the pre-adoption or acceptance phases of this technology, the determinant factors that influence students’ continuance intention to use LMSs have received less attention in the information systems (IS) literature. Methodology: The theoretical model for this study was primarily drawn from the expectation-confirmation model (ECM). A total of 387 Kuwaiti students, from a private American University in the State of Kuwait, participated in this study. Partial least squares (PLS) was employed to analyze the data. Contribution: This study contributes to the existing scientific knowledge in different ways. First, this study extends the expectation confirmation model (ECM) by integrating factors that are important to students’ continuous intention to use LMSs, including system interactivity, effort expectancy, attitude, computer anxiety, self-efficacy, subjective norms, and facilitating conditions. Second, this study adds on a Kuwaiti literature context by focusing on the continuous intention to use LMSs, which is, to the best of our knowledge, the first study that extends and empirically assesses the applicability of the ECM in the LMSs context in a developing country – Kuwait. Third, this study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM, and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Finally, this study aims to assist HEIs, faculty members, and systems’ developers in understanding the main factors that influence students’ continuance use intention of LMSs. Findings: While subjective norms were not significant, the results mainly showed that students’ continuous intention to use Moodle is significantly influenced by performance expectancy, effort expectancy, attitude, satisfaction, self-efficacy and facilitating conditions. The study’s results also confirmed that satisfaction and attitude are two conceptually and empirically different constructs, conflicting with the views that these constructs can be taken as interchangeable factors in the ECM. Recommendations for Practitioners: This study offers several useful practical implications. First, given the significant influence of system interactivity on performance expectancy and satisfaction, faculty members should modify their teaching approach by enabling communication and interaction among instructors, students, and peers using the LMS. Second, given the significant influence of performance expectancy, satisfaction, and attitude on continuous intention to use the LMS, HEIs should conduct training programs for students on the effective use of the LMS. This would increase students’ awareness regarding the usefulness of the LMS, enhance their attitude towards the LMS, and improve their satisfaction with the system. Third, given the significant role of effort expectancy in influencing performance expectancy, attitude, and students’ continuous intention to use Moodle, developers and system programmers should design the LMS with easy to use, high quality, and customizable user interface. This, in turn, will not only motivate students’ performance expectancy, but will also influence their attitude and continuous intention to use the system. Recommendation for Researchers: This study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Hence, it is recommended that researchers include these two constructs in their research models when investigating continuous intention to use a technology. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other LMSs, such as Blackboard. Future Research: This study focused on how different factors affected students’ continuous intention to use Moodle but did not consider all determinants of successful system, such as system quality, information quality, and instructional as well as course content quality. Thus, future research should devote attention to the effects of these quality characteristics of LMS.

Antecedents of continuance intention in online learning systems among vocational college students: The moderating effect of gender

“…Having anxiety makes it more difficult to confirm, as the relationship is negative. Previous research has supported this relationship (Lee et al, 2009;Rabaa'i et al, 2021;Barroso et al, 2022). The anxiety generated by students in the online learning process will inhibit the positive expectations of the system.…”

“…The subsequent formation of satisfaction is caused by the confirmation of expectations and the perception of usefulness ( Rahi et al, 2022 ). Finally, a high degree of technical satisfaction will form a continuous intention ( Rabaa'i et al, 2021 ; Anjum et al, 2022 ; Huang et al, 2022 ).…”

Students’ continuance intention to use MOOCs: empirical evidence from India

“…The levels of motivation among people are determined by their self-efficacy beliefs, which are reflected in the amount of effort they put in and how long they will persevere in the face of an obstacle. If the belief in their capability is stronger, then the efforts are greater and are more persistent (Bandura, 1988(Bandura, , 1989Rabaa'i et al, 2021). Computer self-efficacy can be defined as the ability of a person to perform tasks using a computer (Shahbaz et al, 2020).…”

A Model Predicting Student Engagement and Intention with Mobile Learning Management Systems

“…Other studies have confirmed the model's effectiveness in predicting users' intentions to adopt different information systems (Han & Shin, 2016;Hwang et al, 2016;Jin, 2014). Some other studies have shown that when students perceive m-learning to be useful and easy-to-use, they are more likely to be engaged in the learning process (Al-Adwan et al, 2021;Al-Emran et al, 2021;Rabaa'i et al, 2021). Therefore, this study is based on the following hypotheses:…”

“…ERP usability, which is related to interactivity, was proved to influence the intentions to continue using ERP systems (Scholtz et al, 2016). Moreover, system interactivity significantly influences students' satisfaction with Moodle (Rabaa'i et al, 2021).…”