Explaining Students’ Continuance Intention to Use Mobile Web 2.0 Learning and Their Perceived Learning: An Integrated Approach

Dalvi-Esfahani, Mohammad; Leong, Lam Wai; Ibrahim, Othman; Nilashi, Mehrbakhsh

doi:10.1177/0735633118805211

Cited by 51 publications

(54 citation statements)

References 140 publications

(247 reference statements)

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“…The empirical results have also supported the significant relationships between performance expectancy and students' continuous intention and attitude towards Moodle. These results are in parallel with prior studies in the same context (e.g., Al-Emran et al, 2020;S.-C. Chen et al, 2013;Y.-M. Cheng, 2014b;Dalvi-Esfahani et al, 2018;Joo et al, 2016;Sabah, 2016Sabah, , 2019. These results imply that students seem to be more motivated to continue using Moodle and more likely to have a higher positive attitude towards the system if they perceive it as more effective, productive, and a useful technology in their learning.…”

Section: Discussionsupporting

confidence: 86%

“…In this study, SN includes the influences of instructors, colleagues, and people who are important to students. Previous studies pointed out that subjective norms have a significant effect on continuous intention (e.g., Al-Emran et al, 2020;Dalvi-Esfahani et al, 2018;Huang, 2019;Sabah, 2019). Accordingly, the following hypothesis is suggested: H18: Subjective norms significantly influence continuous intention to use Moodle…”

Section: Subjective Norms (Sn)mentioning

confidence: 96%

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

Rabaa'i

ALmaati

Zhu

2021

IJIKM

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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.

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Section: Discussionsupporting

confidence: 86%

Section: Subjective Norms (Sn)mentioning

confidence: 96%

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

Rabaa'i

ALmaati

Zhu

2021

IJIKM

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“…Accordingly, information quality on social media can be considered as the expectations resulting from evaluating any user-generated content (students or universities), such as sufficiency and consistency [40]. The term information quality often is used in conjunction with implementation and measurement items ease of understanding and personalization [41]. As mentioned by [42,43], the message is of critical importance in terms of the impact of information quality [44], while [45] implies it is a measure of excellence in communicating knowledge.…”

Section: Information Qualitymentioning

confidence: 99%

“…The impact of quality information and the sources' reliability needs to be clarified [47]. Additionally, in this field, the literature review makes clear that there exists a lack of knowledge [41].…”

Section: Information Qualitymentioning

confidence: 99%

The Influence of Information System Success and Technology Acceptance Model on Social Media Factors in Education

et al. 2021

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The current study explores the students’ behavioral intention to use social media and actual social media use in higher education, specifically the perception of their academic performance and satisfaction. The study is theoretically based on the technology acceptance model (TAM) with evaluation information system success models (ISSM). Theoretically, five independent constructs were identified as contributory to behavioral intention to use social media, and actual social media use towards the students’ satisfaction and performance impact was analyzed. A questionnaire survey based on the technology acceptance model (TAM) and information system success model (ISSM) was utilized as the key method for collecting data and disseminated to 1200 students from four public universities of Malaysia chosen through a random sampling technique. For data analysis, the SPSS and structural equation modeling (SEM-Amos) were used. Outcomes obtained from the students’ behavioral intention to use and actual social media usage indicates a positive and constructive influence on satisfaction and academic performance in higher education. In addition, both male and female students were satisfied with perceived usefulness (β = 0.095, t-value = 3.325, p < 0.001 and β = −0.045, t-value = −2.079, p < 0.001, respectively), perceived ease of use (β = 0.108, t-value = 3.29, p < 0.001 and β = 0.307, t-value = 12.365, p < 0.001, respectively), perceived technology fit (β = 0.14, t-value = 4.769, p < 0.001 and β = 0.277, t-value = 12.358, p < 0.001, respectively), information quality (β = 0.108, t-value = 3.825, p < 0.001 and β = 0.109, t-value = 5.087, p < 0.001, respectively), and system quality (β = 0.232, t-value = 7.573, p < 0.001 and β = 0.176, t-value = 7.429, p < 0.001, respectively). Therefore, we encourage students to use social media for educational purposes and encourage more interactions with peers at higher education institutions. The study’s empirical findings present strong support for the integrative association between the TAM and the ISSM in using online learning platforms to improve students’ academic achievements and satisfaction. This could help decision makers in universities, higher education institutions, and colleges to plan, evaluate, and implement online learning platforms in their institutions.

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“…Addressing self-regulatory skills is a natural conduit for improving academic performance (Mrazek et al, 2018). Given the relationships between smartphone usage, SRL, and achievement, modifications to how the smartphone is used are also appropriate (Dalvi-Esfahani et al, 2020). In addition, given the ubiquity of the smartphone, it is prudent to utilize it in any SRL intervention (e.g, as a support for cue-based interventions; van Merriënboer & de Bruin, 2019).…”

Section: Changing Behaviormentioning

confidence: 99%

The smartphone in self-regulated learning and student success: clarifying relationships and testing an intervention

Hartley

Bendixen

Gianoutsos

et al. 2020

Int J Educ Technol High Educ

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This two-part observational and intervention study addressed the role of the smartphone in self-regulated learning (SRL) and student success as measured by achievement. Smartphone usage among students has been identified as contributing to lower academic achievement in a variety of settings. What is unclear is how smartphone usage contributes to lower outcomes. This study surveyed participants’ self-regulated learning skills and smartphone usage at the beginning and end of the term for first semester undergraduates. A regression analysis demonstrated that when controlling for prior achievement, general SRL measures had a positive impact on first semester achievement. Smartphone related SRL did not have a direct impact on achievement. The second part of the study evaluated the efficacy of a brief intervention to ameliorate factors contributing to lower achievement. Students were presented with either SRL strategies, awareness and attention strategies or career planning guidance (control). A regression analysis of the brief intervention resulted in modest gains in SRL but did not influence achievement.

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Explaining Students’ Continuance Intention to Use Mobile Web 2.0 Learning and Their Perceived Learning: An Integrated Approach

Cited by 51 publications

References 140 publications

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

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

The Influence of Information System Success and Technology Acceptance Model on Social Media Factors in Education

The smartphone in self-regulated learning and student success: clarifying relationships and testing an intervention

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