Moderating effect of innovation consciousness and quality consciousness on intention-behaviour relationship in E-learning integration

Olugbara, Cecilia Temilola; Imenda, Sitwala Namwinji; Olugbara, Oludayo O.; Khuzwayo, H. B.

doi:10.1007/s10639-019-09960-w

Cited by 10 publications

(7 citation statements)

References 56 publications

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“…Although we expected a positive association between intention and use, this gap is not surprising. Some studies have identified a positive correlation between intention and use of e-learning (Olugbara et al, 2020 ), but a number of ICT-related studies have identified this gap either completely or at least partially (Almås & Krumsvik, 2008 ; Henderikx et al, 2017 ).…”

Section: Discussionmentioning

confidence: 99%

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Understanding intention and use of digital elements in higher education teaching

Müller

Leyer

2023

Educ Inf Technol

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Digital elements are being increasingly used in higher education teaching, but the intention and their actual use vary depending on the lecturers. We used the reasoned action approach to understand the beliefs and intentions behind the use of digital elements in this context. We conducted a quantitative survey in which university lecturers shared their intention concerning the use of digital learning elements and indicated their actual use. The results confirm the influence of attitude, perceived norms, and perceived behavioral control on the intention to use digital learning elements. However, we also identified an intention–behavior gap: Only one-time effort to become familiar with digital elements has a significant impact on actual usage. We conclude that, above all, teachers must first be given the opportunity to become familiar with digital learning elements to be able to use them effectively. Understanding why such an intention–behavior gap exists should be the aim of future studies.

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Section: Discussionmentioning

confidence: 99%

“…Few studies have addressed the relationship between intention and behavior. A study by Olugbara et al ( 2020 ) found that the intention to use e-learning has a positive effect on actual integration. An older study by Almås and Krumsvik ( 2008 ) found a decreasing intention–behavior gap based on interviews and observations.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Understanding intention and use of digital elements in higher education teaching

Müller

Leyer

2023

Educ Inf Technol

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“…The other factor is Personal Innovation in which innovative person has high willingness to accept new technology (Olugbara, Imenda, Olugbara, Khuzwayo, 2019), it was supported by Baleghi-zadeh, Fauzi, Ayub, Ehsan, (2019) that personal innovativeness influences beliefs, it can be considered as an external variable. Personal Innovativeness with technology will affect a person's readiness to check new technology informatics (Yousef,Falze, Rabee, 2014),it was added by (Taylor, Al-busaidi, 2013) more users' personal innovativeness (willingness) of students likely to access e-learning will make them easy to find out the usefulness of e-learning, the more willingness to operate technology will make the participants having positive attitude toward e-learning (Fauzi, Ayub, Zaini, Luan, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…As it has been mentioned that Personal innovativeness is willingness to know and explore new technology and the intention to use it (Baleghi-zadeh et al, 2019), it inclined to make use of new technology that affects intention in using it (Yousef, Alharbi;Falze, Rabi;Rabee, 2014). This willingness factor would make the students access and learn about e-learning or increasing their confidence (Olugbara et al, 2019), their confidence will supporting the users to achieve a good result that is the correlation between (Fauzi et al, 2017).…”

Section: "I Have Been Used To Access E-learning Because Nowadays Is T...mentioning

confidence: 99%

Preparing for New Learning: Public Vocational High School Students’ and Teachers’ E-Learning Readiness Singaraja in the Efl Instruction

2022

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This study aimed to find out 1) the e-learning readiness level of students and teachers in Public Vocational High School Singaraja and 2) factors affecting teachers’ and students’ e-learning readiness level of Public Vocational High School Singaraja. It designed using mixed method through survey instrument consists of 3 dimensions (e-learning readiness, e-learning acceptance, e-learning training) and interview guide. The instruments validated by the experts and gained 0.666 from 70 students’ sample and 0.231 from 7 teachers’ sample. The reliability was 0.988 0.666 of 35 items and 0.933 0.231 of 38 items. The survey filled by 410 students and 15 English teachers meanwhile the interview answered by 10 students and 5 English teachers. The questionnaires showed they still need few improvements meanwhile interview results shown their e-learning readiness affected by features, benefits, challenges, familiarity, experience and personal innovativeness. Those results showing that e-learning benefits improve their readiness meanwhile e-learning challenges could lower the users’ readiness. It is considered to improve their readiness by reducing e-learning challenges to create comfortable e-learning access.

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“…Moreover, research findings are inconsistent regarding the “intention-behavior” gap in relation to technology adoption [ 12 ]. Very little research has been conducted to examine medical students’ intention to learn medicine-related AI and their actual learning behavior.…”

Section: Introductionmentioning

confidence: 99%

Understanding Medical Students’ Perceptions of and Behavioral Intentions toward Learning Artificial Intelligence: A Survey Study

Jiang

Jong

et al. 2022

IJERPH

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Medical students learning to use artificial intelligence for medical practices is likely to enhance medical services. However, studies in this area have been lacking. The present study investigated medical students’ perceptions of and behavioral intentions toward learning artificial intelligence (AI) in clinical practice based on the theory of planned behavior (TPB). A sum of 274 Year-5 undergraduates and master’s and doctoral postgraduates participated in the online survey. Six constructs were measured, including (1) personal relevance (PR) of medical AI, (2) subjective norm (SN) related to learning medical AI, (3) perceived self-efficacy (PSE) of learning medical AI, (4) basic knowledge (BKn) of medical AI, (5) behavioral intention (BI) toward learning medical AI and (6) actual learning (AL) of medical AI. Confirmatory factor analysis and structural equation modelling were employed to analyze the data. The results showed that the proposed model had a good model fit and the theoretical hypotheses in relation to the TPB were mostly confirmed. Specifically, (a) BI had a significantly strong and positive impact on AL; (b) BI was significantly predicted by PR, SN and PSE, whilst BKn did not have a direct effect on BI; (c) PR was significantly and positively predicted by SN and PSE, but BKn failed to predict PR; (d) both SN and BKn had significant and positive impact on PSE, and BKn had a significantly positive effect on SN. Discussion was conducted regarding the proposed model, and new insights were provided for researchers and practitioners in medical education.

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Moderating effect of innovation consciousness and quality consciousness on intention-behaviour relationship in E-learning integration

Cited by 10 publications

References 56 publications

Understanding intention and use of digital elements in higher education teaching

Understanding intention and use of digital elements in higher education teaching

Preparing for New Learning: Public Vocational High School Students’ and Teachers’ E-Learning Readiness Singaraja in the Efl Instruction

Understanding Medical Students’ Perceptions of and Behavioral Intentions toward Learning Artificial Intelligence: A Survey Study

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