Facilitating Conditions Questionnaire
Dinah Lianes
The majority of higher education students have their own mobile devices. They can use them to access educational content, whenever and wherever they are, as long as they are connected to the Internet (Al-Emran et al., 2016; Chang et al., 2018; Sevillano-Garcia & Vzquez-Cano, 2015). Therefore, they can use mobile technologies, at their convenience, to access learning management systems, course notes, recorded videos, assessments, quizzes, games, et cetera. These devices also allow their users to connect to conferencing software like Zoom or Microsoft Teams to interact with others, including with their course instructor, in real time (Camilleri & Camilleri, 2022).
They also offer synchronous learning opportunities if users install video conferencing programs including Skype, Google Meet, Zoom and Microsoft Teams (Camilleri & Camilleri, 2021a; 2022). Course participants may use mobile apps to interact with other online users in collaborative learning settings, including with their course instructor (Maqtary, Mohsen & Bechkoum, 2019). This allows them to apply their theoretical knowledge in an authentic context (i.e. in situated and informal learning contexts), as they are expected to engage in online communications (Kwong, Wong & Yue, 2017). Therefore, conferencing programs can be used to organize virtual meetings with students in real time (Nikolopoulou et al., 2021).
Nevertheless, previous literature reported that not all students are willing to utilize their mobile phones or tablets for educational purposes (Casey et al., 2020; Zogheib & Daniela, 2021). A few commentators argued that smart phones have small screens with low resolutions, slow connection speeds, and lacked standardization options (Al-Furaih & Al-Awidi, 2020; Lowenthal, 2010). In fact, Android, Apple and Microsoft Windows have their own operating systems. As a result, m-learning applications have to be programmed or customized to be compatible with these systems (Camilleri & Camilleri, 2021).
Some commentators contended that individuals may possess different attitudes on the usage of the mobile technologies (Al-Emran et al., 2016). There are individuals who may hold different opinions and perspectives on the use mobile technologies (Ciampa, 2014). They may be willing to utilize these devices to keep in contact with their friends on social media, to listen to their preferred music, or to watch video clips and live streaming (Park et al., 2012). They may use their mobile devices for hedonic and entertainment purposes, rather than to participate in learning activities.
Alternatively, individuals may believe that certain technologies are difficult to understand and use (Scherer et al., 2019). They may feel uncomfortable with the use of technological innovations if they consider them as time consuming and/or complicated. In these cases, they will probably hold negative perceptions towards such technologies. Thong Hong and Tam (2002) reported that there may be a negative relationship between the use of complex technologies and their perceived usefulness.
Davis (1989) reported that his TAM constructs were reliable. He indicated that the Cronbach Alpha values were above 0.90. His analysis also confirmed that these constructs had appropriate convergent and discriminant validities. Other studies yielded similar validity and reliability values as many researchers explored the use and acceptance of different technologies in various contexts (Park et al., 2012; Teo & Zhou, 2014). Venkatesh et al. (2012) found that their UTAUT constructs had internal consistency values that exceeded 0.75 (these figures were higher than the recommended threshold of 0.7). They held that their convergent and discriminant validity results were consistent with previous research. The constructs that were adopted in the survey instrument are featured in Table 2.
A stepwise procedure was used to investigate whether there were significant correlations. The p-value had to be less than 0.05 benchmark. Therefore, the insignificant variables were excluded from this empirical investigation.
This contribution has presented a critical review of the relevant literature that was focused on the use of m-learning. It reported that the university students were using mobile technologies to improve their learning outcomes. In the past years, a number of academic authors contended that educational apps were supporting many students in different contexts Butler et al., 2021; Crompton & Burke, 2018; Hamidi & Chavoshi, 2018; Sung et al., 2016; Tosuntas et al., 2015). In the main, they maintained that ubiquitous technologies enable them to access learning management systems and to engage in synchronous conversations with other individuals (Camilleri & Camilleri, 2021).
The findings revealed that higher education students were using m-learning apps as they considered them as useful tools to enhance their knowledge. Evidently, their perceptions about the ease of use of m-learning technologies were significantly correlated with their perceived usefulness. In addition, it transpired that both constructs were also affecting their attitudes towards usage, that in turn preceded their intentions to use m-learning apps.
The results also revealed that the respondents were satisfied by the technical support they received during COVID-19. Apparently, their university provided appropriate facilitating conditions that allowed them to engage with to m-learning programs during the unexpected pandemic situation and even when the preventative restrictions were eased.
Arguably, m-learning would require high-quality wireless networks with reliable connections. Course instructors have to consider that their students are accessing their asynchronous resources as well as their synchronous apps (like Zoom or Microsoft Teams) on campus or in other contexts. Students using m-learning technologies should have appropriate facilitating conditions in place, including adequate Wi-Fi speeds (that enable access to high-res images, and/or interactive media, including videos, live streaming, etc.). Furthermore, higher education institutions ought to provide ongoing technical support to students and to their members of staff (Camilleri & Camilleri, 2021).
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Design: a cross-sectional, descriptive, national survey of nurses and midwives practising in Ireland was undertaken in 2002. The questionnaire used in the survey included the 'Understanding of Empowerment Scale'.
Measurements and findings: factor analysis using the Principal Axis Factoring method of extraction and an oblique (Direct Oblimin) rotation was carried out on the Understanding of Empowerment Scale. This suggested four factors or conditions important for the empowerment of midwives: control, support, recognition and skills.
Key conclusions: these findings relating to the conditions that facilitate empowerment in midwifery reflect the professional distinctiveness of midwifery and take into account the specific role and working environment of the midwife.
Implications for practice: the identification of the important conditions to facilitate empowerment in midwifery provides a framework with which to explore ways of building on strengths and addressing weaknesses within the current situation for midwives in Ireland and elsewhere. These suggestive findings offer an opportunity to further develop a tool to measure levels of these conditions necessary to facilitate empowerment in midwifery.
Digital library (DL) is an important information system which provides all-encompassing benefits to various stakeholders in scholarship and research through its provision of access to immediate and up-to-date information resources. The review of literature indicated low use of this system by engineering lecturers owing to system characteristics; and pay little or no attention to factors such as Performance Expectancy (PE) and Facilitating Conditions (FC) on the use of this system by engineering lecturers in universities. This study therefore investigated the influence of performance expectancy and facilitating conditions on the use of digital library by engineering lecturers in universities in South-west, Nigeria. Descriptive survey research design of correlational type was adopted. The study comprised 759 engineering lecturers in 10 universities in South-west Nigeria. Data analysis for the study involved frequency counts, percentages, mean and standard deviation were used for the analysis. Performance expectancy was found to be a critical factor in the use of digital library by engineering lecturers. The paper therefore, recommends the need for improvement of facilitating conditions such as provision of uninterrupted power supply, high Internet bandwidth and facilitation of periodic training in order to sustain the use of digital library by engineering lecturers in universities in South-west, Nigeria.
The practicality of smartphone technology in enhancing classroom instruction has made substantial developments in the field of EFL education (Taleb & Sohrabi, 2012). For example, presenting approaches toward more classroom engagement (Martin & Ertzberger, 2013), the provision of multiple platforms alongside a variety of instructional strategies (Yang, 2013), and the implementation of effective strategies for language improvement (Golshan & Tafazoli, 2014) are a number of improvements made by mobile technologies in EFL (English as a foreign language) context. Furthermore, by providing an authentic learning environment for language learners (Avci & Adiguzel, 2017), technological tools such as smartphones have simplified the process of language learning achievement (Cho et al., 2018). In other words, mobile phones can provide opportunities for language learners to practice outside the classroom (Alshammari, 2020) and foster their language learning process through the adoption of various learning strategies (Gao & Shen, 2021). Thus, MALL is considered a critical element in classrooms and other academic contexts (Vafa & Chico, 2013).
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