Measuring Students’ Intention to Use E-Learning During Covid-19 Pandemic: A Case Study in Technical College of Management – Baghdad

Ibrahim, Mohammed Fadhil; Aljader, H. K. S.; Fadhil, Nawar Abbood

doi:10.22266/ijies2021.1031.43

Cited by 3 publications

(2 citation statements)

References 49 publications

(50 reference statements)

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“…To ensure that all targeted students have experience dealing with the E-Learning platforms, the data collection process was conducted after 2021, guaranteeing students' experience using E-Learning platforms. In the latter half of 2020, an entire shift in e-learning was implemented in both countries [46] and [47]. Ensuring the accuracy and reliability of the gathered data is a crucial factor when collecting data.…”

Section: A Data Collectionmentioning

confidence: 99%

Extended Model of Expectation Confirmation Model to Examine Users’ Continuous Intention Toward the Utilization of E-Learning Platforms

Obeid,

Ibrahim,

Fadhil

2024

IEEE Access

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The utilization of E-learning platforms has attracted considerable attention recently. Universities are increasingly adopting diverse E-learning platforms that offer a range of features to enhance student satisfaction and promote their sustained utilization of E-learning platforms. The task of consistently engaging and encouraging students to use E-learning platforms remains a persistent challenge. Many students tend to discontinue their participation in E-Learning platform courses, showing reluctance towards sustained engagement with the platform. Therefore, this research analyses the essential factors impacting students' inclination to sustain their utilization of the E-Learning platform. The present study uses the "Expectation Confirmation Model" (ECM) with four factors: "interactivity", "social influences", "computer self-efficacy", and "perceived enjoyment". A survey was administered to college students via online Google Forms, resulting in 362 respondents. The data analysis is conducted using the Smart-PLS 4 Programme. Based on its findings, the study presented a "conceptual framework" for the sustained utilization of Elearning platforms. Results show that perceived enjoyment, satisfaction, interactivity, computer selfefficacy, and social influences impact continuing intention. This research indicates that satisfaction has the most substantial consequence on students' intention to persist in utilizing E-Learning platforms. The model prediction power (R2) is 70 %, which can explain the users' continuous intention.

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Section: A Data Collectionmentioning

confidence: 99%

Extended Model of Expectation Confirmation Model to Examine Users’ Continuous Intention Toward the Utilization of E-Learning Platforms

Obeid,

Ibrahim,

Fadhil

2024

IEEE Access

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“…The moderator of the model is Task Technology Fit. Though accuracy and self-efficacy were less significant, students loved e-learning [23]. The other study's results showed that (Perceived Ease of Use) plays a clear role in accepting e-learning and positively affects the acceptance rate (Perceived Usefulness), confirming that an information system can easily meet students' needs and convenience will be helpful for the student [24].…”

Section: Introductionmentioning

confidence: 97%

Measuring the Effect of E-Learning Information Quality on Studentâ€™s Satisfaction Using the Technology Acceptance Model

Aljader

2023

JOIV : Int. J. Inform. Visualization

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This study analyses a blended e-learning system's information resources. Their quality is assessed based on learners' perceptions using a modified version of the Technology Acceptance Model (TAM). To enable flexible learning and enhance understanding during the COVID-19 epidemic, most Iraqi universities have lately embraced Google Classroom and Moodle in addition to face-to-face (F2F) courses. Based on TAM, individual differences and perspectives were investigated concerning correlations between student satisfaction and technology adoption. There were 270 undergraduate students in the research sample who were enrolled in academic courses at Middle Technical University's (MTU) /Technical College of Management (TCM). A survey was used for data collection. The research was done after developing the model's essential and external variables and selecting their components. Partial least squares structural equation modelling (PLS-SEM) examined path-connected dependent and independent components. The study's results showed how "E-Learning Information Quality" (EIQ) positively impacted students' adoption of e-learning. That is demonstrated by the internal variables' positive correlation, which includes perceived usefulness (PU) and perceived ease of use (PEOU), which can be seen in H1 and H2 by the values of (β = 0.204, β = 0.715), and which both positively influence attitudes toward use (ATU), which can be seen in H5 were value (β = 0.643), and behavioral intention (BIU), which can be seen in H4 was value (β = 0.300). Therefore, e-Learning information sources must have value and meaning for students. However, more research is required to evaluate the system's quality. Furthermore, the acceptability of e-learning may change as pedagogies change

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A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps

et al. 2022

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Over the past three decades, the Technology Acceptance model (TAM) has garnered considerable attention in higher education. COVID-19 boosted the development of TAM as multiple studies were rapidly undertaken during the pandemic. This, however, created a gap in our current understanding of the directions and trends of TAM advancement. The purpose of this study is to obtain insight into the advancement of TAM throughout the pandemic. It would assist researchers in comprehending the advancement and direction of TAM studies in higher education, such as gaining an understanding of the prevalent external variables for TAM, the statistical analysis employed, research methodologies, the technologies studied, and the geographic location of the research conducted. Finally, research gaps and future directions for TAM studies are presented. A systematic review utilizing PRISMA was conducted on 104 sampled publications. It was found that self-efficacy, subjective norms, experience, and enjoyment were the external variables most frequently used in TAM, while internal motivation received minimal attention. The existing studies have focused mainly on student samples, so further investigation is needed into lecturers, higher education personnel, and mixed groups. Further study is also required on qualitative and mixed methods, with the partial least square structural equation model currently dominating statistical analysis. Future technologies such as 5G, AI, cloud computing, augmented reality, virtual reality, and BYOD represent new TAM-related research gaps. The majority of studies have been undertaken in Asian countries, such as China and those in southeast Asia. This new systematic literature review provides insight into the trend of TAM advancement in the sustainability of higher education during the pandemic, the identified research gaps, and recommendations for future research directions. These findings also serve as a reference for future research by enhancing the foundation established by previous reviews and research on TAM, thereby facilitating the model’s ongoing expansion.

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Measuring Students’ Intention to Use E-Learning During Covid-19 Pandemic: A Case Study in Technical College of Management – Baghdad

Cited by 3 publications

References 49 publications

Extended Model of Expectation Confirmation Model to Examine Users’ Continuous Intention Toward the Utilization of E-Learning Platforms

Extended Model of Expectation Confirmation Model to Examine Users’ Continuous Intention Toward the Utilization of E-Learning Platforms

Measuring the Effect of E-Learning Information Quality on Studentâ€™s Satisfaction Using the Technology Acceptance Model

A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps

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