An Empirical Investigation of Reasons Influencing Student Acceptance and Rejection of Mobile Learning Apps Usage

Abstract

Sustainable learning and education (SLE) is a relatively new ideology based on sustainability principles and developed in response to the United Nations’ recently proclaimed Sustainable Development Goals (SDGs). As a result, technologies should be adopted to equip educational institutions with the tools necessary to attain SLE. Recently, the coronavirus (COVID-19) pandemic has affected educational systems globally, leading them to embrace more innovative technological methods to meet academic demands while maintaining SLE principles. Mobile learning apps (MLA) refers to using the unique capabilities of mobile apps to engage and collaborate towards establishing robust online learning. However, the effectiveness of MLA depends on learners’ acceptance. Therefore, the purpose of this study is to investigate the factors that could affect MLA acceptance. In order to analyze the collected data from 415 Jordanian students among schools and universities, structural equation modeling (SEM) was used. The empirical findings confirm that perceived usefulness and perceived ease of use are significantly influenced by self-efficacy and perceived compatibility. Furthermore, perceived usefulness is significantly influenced by perceived convenience and perceived ease of use. Additionally, perceived enjoyment significantly influences the behavioral intention to use MLA. On the other hand, perceived compatibility has no significant influence on perceived enjoyment. Finally, perceived ease of use, perceived usefulness, and perceived compatibility have no significant effect on behavioral intention to use MLA. This study addresses a critical research gap in the distance learning acceptance literature by proposing an exhaustive model in the post-COVID-19 era that can help to improve students’ performance and outcomes in Jordanian schools and universities.

Factors influencing microgame adoption among secondary school mathematics teachers supported by structural equation modelling-based research

“…This was to predict and explain the users’ behavioral intentions and actual use of new technologies. These were in line with previous studies, where this model was recently modified to predict the BI and AU of new technology, such as TPB, UTAUT, and TTF ( Hanham et al, 2021 ; Jiang M. Y. et al, 2021 ; Al-bashayreh et al, 2022 ).…”

“…This was to predict and explain the users' behavioral intentions and actual use of new technologies. These were in line with previous studies, where this model was recently modified to predict the BI and AU of new technology, such as TPB, UTAUT, and TTF (Hanham et al, 2021;Al-bashayreh et al, 2022). By modifying the Technology Acceptance Model (Davis, 1989), the proposed model of this present report was developed, with the addition of some factors, namely self-efficacy, subjective norm, facilitating conditions, and TPACK.…”

Do oil prices and oil production capacity influence decision making and uncertainty in the financial market? Evidence from Saudi Arabia

“…Oil price movements and production capacity are followed by an immediate impact on the Saudi financial market volatility. Moreover, Saudi financial market is considered the largest and the most active and liquid market in both the Gulf Cooperation Council (GCC) and MENA regions http://dx.doi.org/10.21511/imfi.19 (3).2022.28 (Mensi et al, 2015). On the other hand, Saudi Arabia's financial market attracts foreign investor's access to the market that can be a way to diversify portfolio investments in financial market.…”

“…In reaction, the country's administration has been reducing its dependence on oil exploration. Moreover, Saudi Arabia continued dominance of world oil production, and poor economic diversification limits its impression as a diversified marhttp://dx.doi.org/10.21511/imfi.19 (3).2022.28 ket. The administration has continuously reduced government expenditures and distributed wealth to other industries (Syed et al, 2019).…”

“…Given the fluctuations in global oil prices, the increasing uncertainty among investors, and the instability of the relationship between them, multiple cases of price fluctuations may result, which may affect the financial markets. On the one hand, according to different sources, uncertainty can be divided into economic policy uncertainty, climate Investment Management and Financial Innovations, Volume 19, Issue 3, 2022 http://dx.doi.org/10.21511/imfi.19 (3).2022. 28 policy uncertainty, geopolitical risk uncertainty, and market uncertainty.…”