BMF CP45: The complex impacts of performance expectancy and effort expectancy on Moroccan nursing students’ ICT using intention
AISDL Team
August 11, 2023
1. Project description
1.1. Main objectives
The current study is conducted to examine whether effort expectancy moderates the relationship between performance expectancy and intention to use information and communication technologies (ICT) among Moroccan nursing students.
1.2. Materials
The mindsponge theory will be used for conceptual development, and Bayesian Mindsponge Framework (BMF) analytics will be used for statistical analysis on a dataset of 702 Moroccan nursing students [1-4]. The bayesvl R package, aided by the Markov chain Monte Carlo (MCMC) algorithm, will be employed for statistical analyses [5-8]. For more information on BMF analytics, portal users can refer to the following book [9]. Data and code snippets of this initial analysis were deposited at: https://osf.io/73pwj/.
1.3. Main findings
The analysis shows that performance expectancy is positively associated with nursing students’ intention to use information and communication technologies during the clinical internship to learn. Effort expectancy is also found to positively moderate the relationship between performance expectancy and intention to use ICT.
Figure 1. Estimated coefficients
2. Collaboration procedure
Portal users should follow these steps for registering to participate in this research project:
- Create an account on the website (preferably using an institution’s email).
- Comment your name, affiliation, and your desired role in the project below this post.
- Patiently wait for the formal agreement on the project from the AISDL mentor.
If you have further inquiries, please contact us at aisdl_team@mindsponge.info
If you have been invited to join the project by an AISDL member, you are still encouraged to follow the above formal steps.
All the resources for conducting and writing the research manuscript will be distributed upon project participation.
AISDL mentor for this project: Minh-Hoang Nguyen
AISDL members who have joined this project: Quan-Hoang Vuong.
The research project strictly adheres to scientific integrity standards, including authorship rights and obligations [10], without incurring an economic burden at participants’ expenses [11].
References
[1] Nguyen MH, La VP, Le TT, Vuong QH. (2022). Introduction to Bayesian Mindsponge Framework analytics: An innovative method for social and psychological research. MethodsX, 9, 101808.
[2] Vuong QH. (2023). Mindsponge Theory. De Gruyter.
[3] Vuong QH, Napier NK. (2015). Acculturation and global mindsponge: An emerging market perspective. International Journal of Intercultural Relations, 49, 354-367.
[4] Bahri H, et al. (2021). Dataset of Moroccan nursing students’ intention to use and accept information and communication technologies and social media platforms for learning. Data in Brief, 37, 107230.
[5] Van Huu N, Hoang VQ, Ngoc TM. (2005). Central Limit Theorem for Functional of Jump Markov Processes. Vietnam Journal of Mathematics, 33(4), 443-461.
[6] Thao HT, Vuong QH. (2015). A Merton model of credit risk with jumps. Journal Statistics Applications & Probability Letters, 2(2), 97-103.
[7] Van Huu N, Hoang VQ. (2007). On the martingale representation theorem and on approximate hedging a contingent claim in the minimum deviation square criterion. In R Jeltsch, TT Li, IH Sloan (Eds). Some Topics in Industrial and Applied Mathematics (pp. 134-151). Singapore: World Scientific.
[8] La VP, Vuong QH. (2019). bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with ‘Stan’. The Comprehensive R Archive Network.
[9] Vuong QH, Nguyen MH, La VP. (2022). The mindsponge and BMF analytics for innovative thinking in social sciences and humanities. De Gruyter.
[10] Vuong QH. (2018). The (ir)rational consideration of the cost of science in transition economies. Nature Human Behaviour, 2, 5.
[11] Vuong QH. (2020). Reform retractions to make them more transparent. Nature, 582, 149.