Category Archives: Education

May 30, 2023 · 8:25 am

Metaverse education: A cost-benefit analysis

This is an excerpt from one of my latest articles.

Suggested Citation: Camilleri, M.A. (2023). Metaverse applications in education: A systematic review and a cost-benefit analysis, Interactive Technology and Smart Education, Forthcoming, https://doi.org/10.1108/ITSE-01-2023-0017

A critical review of the literature suggests that there are both pros and cons of using the Metaverse applications in education. Table 3 provides a summary of possible costs and benefits of delivering education through the Metaverse’s virtual environments. The following section features a more detailed discussion on these elements.

Table 1. A cost-benefit analysis on Metaverse education

Costs	Benefits
Infrastructure, resources and capabilities	Immersive multi-sensory experiences in 3D environments
The degree of freedom in a virtual world	Equitable and accessible space for all users
Privacy and security of users’ personal data	Interactions with virtual representations of people and physical objects
Identity theft and hijacking of user accounts	Interoperability
Borderless environment raises ethical and regulatory concerns
Users’ addictions and mental health issues

(Camilleri, 2023)

Costs

Infrastructure, resources and capabilities

The use of the Metaverse technology will probably necessitate a thorough investment in hardware to operate in the universities’ virtual spaces. It requires intricate devices, including appropriate high-performance infrastructures to achieve accurate retina display and pixel density for realistic virtual immersions. These systems rely on fast internet connections with good bandwidths as well as computers with adequate processing capabilities, that are equipped with good graphic cards (Bansal et al., 2022; Chang et al., 2022; Girard and Robertson, 2020; Jiawen et al., 2022; Makransky and Mayer 2022). For the time being, VR, MR and AR hardware may be considered as bulky, heavy, expensive and cost-prohibitive, in some contexts.

The degree of freedom in a virtual world

The Metaverse may offer higher degrees of freedom than what is available through the worldwide web and web2.0 technologies (Hackl et al., 2022). Its administrators cannot be in a position to anticipate the behaviors of all persons using their technologies. Therefore, Metaverse users including students as well as their educators, can possibly be exposed to positive as well as to negative influences, as other individuals can disguise themselves, by using anonymous avatars, to roam in the vast virtual environments.

Privacy and security of users’ personal data

The users’ interactions with the Metaverse as well as their personal or sensitive information, can be tracked by platform operators hosting this Internet service, as they continuously record, process and store their virtual activities in real-time. Like its preceding worldwide web and Web 2.0 technologies, the Metaverse can possibly raise the users’ concerns about the security of their data and of their intellectual properties (Chen, 2022; Ryu et al., 2022l; Skalidis et al., 2022). They may be wary about data breaches, scams, et cetera (Njoku et al., 2023; Tan et al., 2022).

Public blockchains and other platforms can already trace the users’ sensitive data, so they are not anonymous to them. Individuals may decide to use one or more avatars to explore the Metaverse’s worlds. They may risk exposing their personal information, particularly when they are porting from one Metaverse to another and/or when they share transactional details via non-fungible token (NFTs) (Hwang, 2023). Some Metaverse systems do not require their users to share personal information when they create their avatar. However, they could capture relevant information from sensors that detect their users’ brain activity, monitor their facial features, eye motion and vocal qualities, along with other ambient data pertaining to the users’ homes or offices.

They may have legitimate reasons to capture such information, in order to protect them against objectionable content and/or unlawful conduct of other users. In many cases, the users’ personal data may be collected for advertising and/or for communication purposes. Currently, different jurisdictions have not regulated their citizens’ behaviors within the Metaverse contexts. Works are still in progress, in this regard.

Identity theft and hijacking of user accounts

There may be malicious persons or groups who may try use certain technologies, to obtain the personal information and digital assets from Metaverse users. Recently, a deepfake artificial intelligence software has developed short audible content, that mimicked and impersonated a human voice. Other bots may easily copy the human beings’ verbal, vocal and visual data including their personality traits. They could duplicate the avatars’ identities, to commit fraudulent activities including unauthorized transactions and purchases, or other crimes with their disguised identities. For example, Roblox users reported that they experienced avatar scams in the past. In many cases, criminals could try to avail themselves of the digital identities of vulnerable users, including children and senior citizens, among others, to access their funds or cryptocurrencies (as they may be linked to the Metaverse profiles). As a result, Metaverse users may become victims of identity theft. In the near future, evolving security protocols and digital ledger technologies like the blockchain will be increasing the transparency and cybersecurity of digital assets (Ryu et al., 2022). However, users still have to remain vigilant about their digital footprint, to continue protecting their personal information.

As the use of the virtual environment is expected to increase in the coming years, particularly with the emergence of the Metaverse, it is imperative that new ways are developed to protect all users including students. Individuals ought to be informed about the risks to their privacy. Various validation procedures including authentication, such as face scans, retina scans, and speech recognition may be integrated in such systems to prevent identity theft and hijacking of Metaverse accounts.

Borderless environment raises ethical and regulatory concerns

For the time being, a number of policy makers as well as academics are raising their questions on the content that can be presented in the Metaverse’s virtual worlds, as well as to how they can control the conduct and behaviors of the Metaverse users. Arguably, it may prove difficult for the regulators of different jurisdictions to enforce their legislation in the Metaverse’s borderless environment (Njoku et al., 2023). For example, European citizens are well acquainted with the European Union’s (EU) General Data Protection Regulation (GDPR, 2016). Other countries have their own legal frameworks and/or principles that are intended to safeguard the rights of data subjects as well as those of content creators. For example, the United States governments has been slower that the EU to introduce its privacy by design policies. Recently, the South Korean Government announced a set of laudable, non-binding ethical guidelines for the provision and consumption of metaverse services. However, currently, there aren’t a set of formal rules that can apply to all Metaverse users.

Users’ addictions and mental health issues

Although many AR and VR technologies have already been tried and tested in the past few years, the Metaverse is still getting started. At the moment, it is difficult to determine what are the effects of the Metaverse on the users’ health and well-being (Chen, 2022). Many commentators anticipate that an unnecessary exposure to Metaverse’s immersive technologies may result in negative side-effects for the psychological and physical health of human beings (Han et al., 2022). They are suggesting that individuals may easily become addicted to a virtual environment, where the limits of reality are their own imagination. They are lured to it “for all the things they can do” and will be willing to stay “for all the things they can be” (these are excerpts from Ready Player One, a movie blockbuster).

Past research confirms that spending excessive time on internet, social media or playing video games can increase the chances of mental health problems like attention deficit disorders (Dullur et al., 2021), as well as anxiety, stress or depression (Lee et al., 2021), among others. Individuals play video games to achieve their goals, to advance to the next level. Their gameplay releases dopamine (Pallavicini and Pepe, 2020). Similarly, their dopamine levels can increase when they are followed through social media, or when they receive likes, comments or other forms of online engagements (Capriotti et al., 2021; Camilleri and Kozak, 2022; Troise and Camilleri, 2021). Individuals can easily develop an addiction to this immersive technology, as they seek stimulating and temporary pleasurable experiences in its virtual spaces. As a result, they may become dependent to it (Burhan and Moradzadeh, 2020).

However, the individuals’ interpersonal communications via social media networks are not as authentic or satisfying as real-life relationships, as they are not interacting in-person with other human beings. In the case of the Metaverse, their engagement experiences may appear to be real. Yet again, in the Metaverse, its users are located in a virtual environment, they not physically present near other individuals. Human beings need to build an honest and trustworthy relationship with one another. The users of the Metaverse can create avatars that could easily conceal their identity within the virtual world.

Benefits

Immersive multi-sensory experiences in 3D environments

The Metaverse could provide a smooth interaction between the real world and the virtual spaces. Its users can engage in activities that are very similar to what they do in reality. However, it could also provide opportunities for them to experience things that could be impossible for them to do in the real world. Sensory technologies enable users to use their five senses of sight, touch, hearing, taste and smell, to immerse themselves in a virtual 3D environment.

Many students are experienced gamers and are lured by their 3D graphics. They learn when they are actively involved (Siyaev and Jo, 2021a). Therefore, the learning applications should be as meaningful, socially interactive and as engaging as possible (Camilleri and Camilleri, 2019). The Metaverse’s VR tools can be entertaining and could provide captivating and enjoyable experiences to their users (Bühler et al., 2022; Hwang, 2023; Suh and Ahn, 2022). In the past years, a number of educators and students have been using 3D learning applications (e.g. like Second Life) to visit virtual spaces that resemble video games (Hadjistassou, 2016).

Arguably, there is scope for educators and content developers to create digital domains like virtual schools, colleges and campuses, where students and teachers can socialize and engage in two-way communications. Students could visit the premises of their educational institutions in online tours, from virtually anywhere. A number of universities are replicating their physical campus with virtual ones (Díaz et al., 2020). The design of the virtual campuses may result in improved student services, shared interactive content that could improve their learning outcomes, and could even reach wider audiences. Previous research confirms that it is more interesting and appealing for students to learn academic topics through the virtual world (Lu et al., 2022).

Equitable and accessible space for all users

Like other virtual technologies, the Metaverse could be accessed from remote locations. Educational institutions can use its infrastructure to deliver courses (free of charge or against tuition fees, as of now). Metaverse education may enable students from different locations to use its open-source software to pursue courses from anywhere, anytime. Hence, its democratized architecture could reduce geographic disparities among students, and increases their chances of continuing education through higher educational institutions in different parts of the world.

In the future, students including individuals with different abilities, may use the Metaverse’s multisensory environment to immerse themselves in engaging lectures (Hutson, 2022; Lee et al., 2022a).

Interactions with virtual representations of people and physical objects

Currently, individual users can utilize the AR and VR applications to communicate with others and to exert their influence on the objects within the virtual world. They can organize virtual meetings with geographically distant users, attend conferences, et cetera (Camilleri and Camilleri, 2022b; Yu, 2022). Various commentators indicate that the Metaverse can be used to learn academic subjects in real-time sessions in a VR setting (Saritas and Topraklikoglu, 2022; Singh et al., 2022). It could be utilized to interact with peers and course instructors. The students and their lecturers will probably use an avatar that will represent their identity in the virtual world. Many researchers noted that avatars facilitate interactive communications and are a good way to personalize the students’ learning experiences (Barry et al., 2015; Díaz, 2020; Garrido-Iñigo and Rodríguez-Moreno, 2015; Melendez Araya and Hidalgo Avila, 2018; Park, and Kim, 2022).

Interoperability

Many commentators speculate that unlike other VR applications, the Metaverse could probably enable its users to retain their identities as well as the ownership of their digital assets through different virtual worlds and platforms (Hwang, 2023; Xu et al., 2022). This implies that Metaverse users can communicate and interact with other individuals in a seamless manner through different devices or servers, across different platforms. They may be in a position to use the Metaverse to share data and content in different virtual worlds via Web 3.0 (Seddon et al., 2023).

Conclusion

This research theorizes about the pros and cons of using Metaverse’s immersive applications for educational purposes. It clearly indicates that many academics are already experimenting with VR’s immersive technology. While some of them anticipate that the Metaverse is poised to transform education as they envisage that it could be integrated with school curricula and in their educational programs. Others are more skeptical about the hype around this captivating technology. Time will tell whether the Metaverse project comes to fruition.

For the time being, education stakeholders are invited to untap the potential of AR and VR technologies to continue improving the students’ learning journeys. Of course, further research is required to better understand how policy makers as well as practitioners including the developers of the Metaverse, can address the number of challenges and issues identified in this contribution.

The full article and the list of references are available through Researchgate, Academia and SSRN.

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Tagged as augmented reality, Education, educational technology, immersive technology, Metaverse, Metaverse education, virtual reality

June 25, 2022 · 5:00 pm

Learning from anywhere, anytime: The use of mobile technologies for educational purposes

This contribution is a excerpt from my latest article that was published by Springer’s Technology, Knowledge and Learning (Journal). The content has been adapted for this blog post.

_{Suggested citation: Camilleri, M.A. & Camilleri, A.C. (2022). Learning from anywhere, anytime: Utilitarian motivations and facilitating conditions to use mobile learning applications. Technology, Knowledge and Learning, https://doi.org/10.1007/s10758-022-09608-8}

University students are 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).

One may argue that the m-learning paradigm is associated with the constructivist approaches (Chang et al., 2018), including those related with discovery-based learning (Camilleri & Camilleri, 2019c). Relevant theoretical underpinnings suggest that the use of mobile apps can improve the delivery of quality, student-centered education (Camilleri & Camilleri, 2021; Camilleri, 2021b; Chang et al., 2018; Crompton & Burke, 2018; Furió et al., 2015; Lameu, 2020; Nikolopoulou et al., 2021; Sung et al., 2016; Swanson, 2020). This research raises awareness on m-learning technologies that enable students to search for solutions for themselves through the Internet and via learning management systems. It also indicated that mobile apps like Microsoft Teams or Zoom, among others, allow them to engage in synchronous conversations with course instructors and with their peers, in real time.

This study explored the users’ perceptions about m-learning technologies. It validated key constructs from TAM Briz-Ponce et al., 2017; Cheung & Vogel, 2013; Granić & Marangunić, 2019; Ngai et al., 2007; Scherer et al., 2019; Thong Hong & Tam, 2002) and UTAUT (Gunasinghe et al., 2019; Yang et al., 2019), as shown in Table 1.

The descriptive statistics clearly indicated that the research participants felt that m-learning technologies were useful for them to continue their course programs. The principal component analysis confirmed that the students’ engagement with their educational apps was primarily determined by their ease of use. This is one of the main factors that influenced their intentions to engage with m-learning apps.

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.

The stepwise regression analyses shed light on the positive and significant relationships of this study’s research model. Again, these results have proved that the respondents were utilizing m-learning apps because their university (and course instructors) supported them with adequate and sufficient resources (i.e. facilitating conditions). The findings indicated that they were assisted (by their institution’s helpdesk) during their transition to emergency remote learning. In fact, the study confirmed that there was a positive and significant relationship between facilitating conditions and the students’ engagement with m-learning technologies.

On the other hand, this empirical research did not yield a statistically significant relationship between the students’ social influences and their intentions to use the mobile technologies. This is in stark contrast with the findings from past contributions, where other researchers noted that students were pressurized by course instructors to use education technologies (Camilleri & Camilleri, 2020; Teo & Zheng, 2014). The researchers presume that in this case, the majority of university students indicated that they were not coerced by educators or by their peers, to use m-learning apps. This finding implies that students became accustomed or habituated with the use of mobile technologies to continue their course programs.

This research builds on previous technology adoption models Davis et al., 1989; Venkatesh et al., 2003; 2012) to better understand the students’ dispositions to engage with m-learning apps. It integrated constructs from TAM with others that were drawn from UTAUT/UTAUT2. To the best of the researchers’ knowledge, currently, there are no studies that integrated facilitating conditions and social influences (from UTAUT/UTAUT2) with TAM’s perceived ease of use, perceived usefulness and attitudes. This contribution addresses this knowledge gap in academia. In sum, it raises awareness on the importance of providing appropriate facilitating conditions to students (and educators). This way, they will be in a better position to use educational technologies to improve their learning outcomes.

Practical implications

This research indicated that students held positive attitudes and perceptions on the use of m-learning technologies in higher educational settings. Their applications allow them to access course material (through Moodle or other virtual learning environments) and to avail themselves from video conferencing facilities from everywhere, and at any time. The respondents themselves considered the mobile technologies as useful tools that helped them improve their learning journeys, even during times when COVID-19’s preventative measures were eased. Hence, there is scope for university educators and policy makers to create and adopt m-learning approaches in addition to traditional teaching methodologies, to deliver quality education (Camilleri, 2021).

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).

This study has clearly shown that the provision of technical support, as well as the utilization of user-friendly, m-learning apps, among other factors, would probably improve the students’ willingness to engage with these remote technologies. Thus, course instructors are encouraged to create attractive and functional online environments in formats that are suitable for the screens of mobile devices (like tablets and smartphones). There can be instances where university instructors may require technical training and professional development to learn how to prepare and share customized m-learning resources for their students.

Educators should design appealing content that includes a good selection of images and videos to entice their students’ curiosity and to stimulate their critical thinking. Their educational resources should be as clear and focused as possible, with links to reliable academic sources. Moreover, these apps could be developed in such a way to increase the users’ engagement with each other and with their instructors, in real time.

Finally, educational institutions ought to regularly evaluate their students’ attitudes and perceptions toward their m-learning experiences, via quantitative and qualitative research, in order to identify any areas of improvement.

Research limitations and future research directions

To date, there have been limited studies that explored the institutions’ facilitating conditions and utilitarian motivations to use m-learning technologies in higher education, albeit a few exceptions. A through review of the relevant research revealed that researchers on education technology have often relied on different research designs and methodologies to capture and analyze their primary data. In this case, this study integrated measures that were drawn from TAM and UTAUT. The hypotheses were tested through stepwise regression analyses. The number of respondents that participated in this study was adequate and sufficient for the statistical purposes of this research.

Future research could investigate other factors that are affecting the students’ engagement with m-learning technologies. For example, researchers can explore the students’ intrinsic and extrinsic motivations to use educational apps. These factors can also have a significant effect on their intentions to continue their learning journeys. Qualitative research could shed more light on the students’ in-depth opinions, beliefs and personal experiences on the usefulness and the ease of use of learning via mobile apps, including serious games and simulations. Inductive studies may evaluate the effectiveness as well as the motivational appeal of gameplay. They can possibly clarify how, where and when mobile apps can be utilized as teaching resources in different disciplines. They can also identify the strengths and weaknesses of integrating them in the curricula of specific subjects.

Prospective researchers can focus on the design, structure and content of m-learning apps that are intended to facilitate the students’ learning experiences. Furthermore, longitudinal studies may provide a better understanding of the students’ motivations to engage with such educational technologies. They can measure their progress and development, in the long term. The students’ perceptions, attitudes and intentions to use m-learning technologies can change over time, particularly as they become experienced users.

A prepublication of the full article is available here: https://www.researchgate.net/publication/360541461_Learning_from_anywhere_anytime_Utilitarian_motivations_and_facilitating_conditions_to_use_mobile_learning_applications

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Tagged as academic research, Education, education measuring scales, education technology, elearning, measures, mlearning, mobile learning, online learning, quantitative research, Quantitative Study, research, TAM, technology, technology acceptance model, Technology adoption constructs, unified theory of acceptance and use of technology, UTAUT

May 26, 2022 · 10:27 am

The pros and cons of remote learning

_{This is an excerpt from one of my latest articles that was accepted for publication by the 6th International Conference on E-Education, E-Business & E-Technology (ICEBT2022).}

Suggested Citation: Camilleri, M.A. & Camilleri, A.C. (2022). A cost-benefit analysis on remote learning: A systematic review and implications for the future. 6th International Conference on e-Education, e-Business and e-Technology (Beijing, China: 26th June 2022). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4104629

After the outbreak of COVID-19 pandemic, educational institutions were expected to adapt to an unexpected crisis situation. In many cases, they had to follow their policy makers’ preventative measures to mitigate the contagion of the pandemic [1, 2]. As a result, they introduced contingency plans, and disseminated information on the virus, among students and employees. In many cases, educators were coerced to shift from the provision of traditional, face-to-face teaching and blended learning approaches, to a fully virtual remote course delivery [3, 4]. This transition resulted in a number of challenges to students and instructors [5]. Educators were pressurized to utilize digital technologies including learning management systems (LMS) as well as video conferencing programs [6]. Very often, they relied on their institutions’ Moodle or virtual learning environment (VLE) software to share digital resources including videos, power point presentations and links to online notes [7]. During the pandemic educators also acquainted themselves with video-conferencing platforms [8].

Subsequently, when COVID-19 restrictions were eased, a number of educational institutions reopened their doors to students and employees [9]. They introduced social distancing policies and hygienic procedures in their premises [4, 10]. At the time of writing, a number of academic members of staff, in various contexts, are still utilizing learning technologies including LMS and video conferencing programs [6]. Currently, student-centered educators are adopting hybrid/blended learning approaches, as they deliver face-to-face lectures in addition to online learning methodologies. Very often, they do so to support students who are not in a position to attend their lectures on campus.

A synthesis of the literature on the costs and benefits of remote learning

The costs

Many researchers noted that Covid-19 disrupted the provision of education. In the main, they reported that there were various challenges for the successful implementation of remote learning [17, 23-25]. For example, one of the contributions implied that the prolonged use of virtual platforms might negatively impact the efficacy of synchronous learning [27].

Various studies indicated that the research participants were not always pleased with the quality of education that was provided by their educators, during the pandemic [28]. Academic commentators indicated that faculty members were not experts in the delivery of remote/online instruction. They implied that instructors could require periodic developmental training to improve the service quality of their courses [4, 10].

While a few researchers noted that students appreciated the availability of recorded lectures [29], others reported that educators were not always recording their lectures and/or did not share learning resources with them [21]. This issue could have affected the students’ learning outcomes [30, 31]. In fact, some students were worried about their academic progress during COVID-19 [32]. In many cases, they encountered a number of difficulties during remote course delivery. For instance, online group work involved additional planning as well as institutional support [33]. Previous literature suggests that students necessitate counseling, tutoring and mentoring as well as ongoing assurances to succeed [34, 35].

In many cases, the researchers discovered that course participants required adequate training and support to complete their assessments [23, 24, 36]. A few of them also hinted that was a digital divide among students could have been evidenced among those who experienced connectivity and equipment problems, among other issues [5, 37]. Other authors argued about the individuals’ challenges to focus on their screens for long periods of time [6]. Notwithstanding, educators and students may develop bad postures and other physical problems due to staying hunched in front of a screen. Therefore, students ought to be given regular breaks from the screen to refresh their minds and their bodies.

The benefits

Generally, a number of contributions shed light on the benefits of using remote learning technologies, including learning management systems [1, 21, 29, 32] and interactive conferencing programs (1, 6, 17, 33]. Such educational technologies can help in creating rich social interactions [38-40] as well as positive learning environments – that foster learning and retention [41, 42]. Previous research indicated that digital learning resources can enhance the students’ knowledge and skills [43]. Remote instruction approaches can also provide supportive environments to students [39] and could even increase their chances of learning [30, 31]. Virtual lectures may be recorded or archived for future reference [29]. Hence, students or educators could access their learning materials at their convenience [44-46].

Several researchers underlined the importance of maintaining ongoing, two-way communications with students, and of providing them with appropriate facilitating conditions, to continue improving their learning journeys [6, 47-48]. Video conferencing technologies allow educators to follow up on their students’ progress. They facilitate online interactions, in real time, and enable them to obtain immediate feedback from their students [1, 49]. Notwithstanding, there are fewer chances of students’ absenteeism and on missing out on their lessons, as they can join online meetings from home or from other locations of their choice.

Conclusions

This review implies that online technologies have opened a window of opportunity for educators. Indeed, learning management systems as well as conferencing programs are useful tools for educators to continue delivering education in a post covid-19 context. However, it is imperative that educational institutions invest in online learning infrastructures, resources and facilitating conditions, for the benefit of their students and faculty employees. They should determine whether their instructors are (or are not) delivering high levels of service quality through the utilization of remote learning technologies to continue delivering student-centered education.

This paper can be downloaded from: https://www.researchgate.net/publication/360474225_A_cost-benefit_analysis_on_the_use_of_remote_learning_technologies_A_systematic_review_and_a_synthesis_of_the_literature

References (these are all the references that were featured in the full paper)

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September 23, 2021 · 4:53 pm

The students’ perceptions of remote learning through video conferencing!

_{This is an excerpt from a recent article that was published by Springer’s Technology, Knowledge and Learning Journal.}

_{Source: Camilleri, M.A. & Camilleri, A.C. (2021). The Acceptance of Learning Management Systems and Video Conferencing Technologies: Lessons Learned from COVID-19. Technology, Knowledge & Learning.}

The unexpected Coronavirus (COVID-19) pandemic has disrupted the provision of education in various contexts around the globe. Education service providers, including higher education institutions (HEIs) were required to follow their respective governments’ preventative social distancing measures and to increase their hygienic practices, to mitigate the spread of the pandemic. They articulated contingency plans, disseminated information about the virus, trained their employees to work remotely, and organised virtual sessions with students or course participants.

These latest developments have resulted in both challenges and opportunities to students and educators. Course instructors were expected to develop a new modus operandi to deliver their education services, in real time. During the first wave of COVID-19, HEIs were suddenly expected to shift from traditional and blended learning approaches to a fully virtual course delivery.

The shift to online, synchronous classes did not come naturally. COVID-19 has resulted in different problems for course instructors and their students. In many cases, educators were compelled to utilise online learning technologies to continue delivering their courses. In the main, educators have embraced the dynamics of remote learning technologies to continue delivering educational services to students, amid the peaks and troughs of COVID-19 cases.

Subsequently, policy makers have eased their restrictions when they noticed that there were lower contagion rates in their communities. After a few months of lockdown (or partial lock down) conditions, there were a number of HEIs that were allowed to open their doors. They instructed their visitors to wear masks, and to keep socially distant from each other. Most HEIs screened individuals for symptoms as they checked their temperatures and introduced strict hygienic practices like sanitisation facilities in different parts of their campuses.

However, after a year and a half, since the outbreak of COVID-19, some academic members of staff were still relying on the use of remote learning technologies to deliver education services, as they utilised learning management systems (LMS) and video conferencing software to teach their courses. During the pandemic, they became acquainted with online technologies that facilitated asynchronous as well as synchronous learning.

Whilst their asynchronous approaches included text and/or recorded video that were made available through LMS (like Moodle), in many cases, they also utilised video conferencing platforms including Microsoft Teams, Google Meet, Zoom, D2L, Webex, Adobe Connect, Skype for Business, Big Blue Button and EduMeet, among others, to interact with students in real time.

In this light, our research investigated the facilitating conditions that can foster the students’ acceptance and usage of remote learning technologies including LMS and video conferencing programs. We examined the participants’ motivations to use them to continue pursuing their educational programs from home, during COVID-19. Specifically, our study investigated students’ perceptions about the usefulness of remote learning, their interactive capabilities, their attitudes toward their utilisation, the facilitating conditions as well as their intentions to continue using them.

Our targeted respondents were registered students who followed full-time and part-time courses at the University of Malta in Malta. We used a structural equation modeling partial least squares (SEM-PLS) analytical approach to examine the responses of 501 students who voluntarily participated in our research.

The findings clearly indicated that the higher education students perceived the usefulness of remote learning technologies during COVID-19 and valued their interactive attributes. They confirmed that the respondents held positive perceptions toward their universities’ facilitating conditions (like ongoing support, as well as training and development opportunities).

The empirical results reported that the HEI’s facilitating conditions had a significant effect on the students’ interactive engagement with online learning resources and on their attitudes towards these technologies.

The confirmatory composite analysis reported that there were positive and highly significant effects that predicted the students’ intentions to continue using remote learning technologies. Evidently, educators have provided them with the necessary resources, knowledge and technical support to avail themselves of remote learning technologies.

The respondents indicated that they accessed their course instructors’ online resources and regularly interacted with them through live conferencing facilities. The findings from SEM-PLS confirmed that the perceived usefulness and perceived interactivity with online technologies had a positive effect on their attitudes toward remote learning.

In sum, this contribution has differentiated itself from other studies as it investigated the students’ perceptions and attitudes on the use of asynchronous as well as synchronous learning technologies in higher education. It implies that the integration of these technologies ought to be accelerated in the foreseeable future as they may become the norm, in a post COVID-19 era. Therefore, HEIs ought to continue investing in online learning infrastructures, resources and facilitating conditions, for the benefit of their students and faculty employees.

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August 15, 2021 · 11:24 am

The acceptance of learning management systems and video conferencing technologies

The following texts are excerpts from one of my latest articles.

_{Suggested Citation: Camilleri, M.A. & Camilleri, A.C. (2021). The Acceptance of Learning Management Systems and Video Conferencing Technologies: Lessons Learned from COVID-19, Technology, Knowledge and Learning, https://doi.org/10.1007/s10758-021-09561-y}

Introduction

An unexpected Coronavirus (COVID-19) pandemic has disrupted the provision of educational services in various contexts around the globe (Rahiem, 2020; Johnson, Veletsianos & Seaman, 2020; Bolumole, 2020). During the first wave of COVID-19, several educational institutions were suddenly expected to interrupt their face-to-face educational services. They had to adapt to an unprecedented situation. This latest development has resulted in both challenges and opportunities to students and educators (Howley, 2020; Araújo, de Lima, Cidade, Nobre, & Neto, 2020). Education service providers, including higher education institutions (HEIs) were required to follow their respective governments’ preventative social distancing measures and to increase their hygienic practices, to mitigate the spread of the pandemic. Several HEIs articulated contingency plans, disseminated information about the virus, trained their employees to work remotely, and organized virtual sessions with students or course participants.

Course instructors were expected to develop a new modus operandi to deliver their higher education services, in real time (Johnson et al., 2020). During the pandemic, many HEIs migrated from traditional and blended teaching approaches to fully virtual and remote course delivery. However, their shift to online, synchronous classes did not come naturally. COVID-19 has resulted in different problems to course instructors and to their students. In many cases, during the pandemic, educators were compelled to utilize online learning technologies to continue delivering their courses (Fitter, Raghunath, Cha, Sánchez, Takayama & Matarić, 2020). In the main, educators have embraced the dynamics of remote learning technologies to continue delivering educational services to students, amid peaks and troughs of COVID-19 cases.

Subsequently, policy makers have eased their restrictions when they noticed that there were lower contagion rates in their communities. After a few months of lockdown (or partial lock down) conditions, there were a number of HEIs that were allowed to open their doors. They instructed their visitors to wear masks, and to keep socially distant from each other. Most HEIs screened individuals for symptoms as they checked their temperatures and introduced strict hygienic practices like sanitization facilities in different parts of their campuses.

However, after a year and a half, since the outbreak of COVID-19, some academic members of staff were still relying on the use of remote learning technologies like learning management systems (like Moode) and video conferencing software to teach their courses (Cesco, Zara, De Toni, Lugli, Betta, Evans & Orzes, 2021). During the pandemic, they became acquainted with online technologies that facilitated asynchronous learning through text and/or recorded video (Sablić, Mirosavljević & Škugor, 2020). Moreover, many of them, organized interactive sessions with their students in real time. Very often, they utilized video conferencing platforms including Microsoft Teams, Google Meet, Zoom, D2L, Webex, Adobe Connect, Skype for Business, Big Blue Button and EduMeet, among others. COVID-19 has triggered them to use these remote technologies to engage in two-way communications with their students.

Although in the past year, there were a number of researchers who have published discursive articles about the impacts of COVID-19 on higher education, for the time being, there are just a few empirical studies on the subject (Bergdahl & Nouri, 2020; Aguilera-Hermida, 2020; Gonzalez, de la Rubia, Hincz, Comas-Lopez, Subirats, Fort & Sacha, 2020). This contribution addresses this gap in academia. Specifically, it investigates the facilitating conditions that can foster the students’ acceptance and usage of remote learning technologies. It examines the participants’ utilitarian motivations to utilize asynchronous learning resources to access course material, and sheds light on their willingness to engage with instructors and/or peers through synchronous, video conferencing software, to continue pursuing their educational programs from home, during an unexpected pandemic situation.

This study builds on previous theoretical underpinnings on technology adoption (Cheng & Yuen, 2018; Al-Rahmi, Alias, Othman, Marin & Tur, 2018; Merhi, 2015; Schoonenboom, 2014; Lin, Zimmer & Lee, 2013; Chen, Chen & Kazman, 2007; Ngai, Poon & Chan, 2007; Davis, 1989). At the same time, it explores the students’ perceptions about the interactivity (McMillan & Jang-Sun Hwang, 2002) of LMS as well as video conferencing software, and sheds light on their HEI’s facilitating conditions (Hoi, 2020; Dečman, 2015; Venkatesh, Thong & Xu, 2012; Venkatesh, Morris, Davis & Davis, 2003). The rationale of this study is to better understand the research participants’ intentions to use remote technologies, to improve their learning journey. To the best of our knowledge, there are no other contributions that have integrated the same measures that have been used in this research. Therefore, this study differentiates itself from the previous literature, and puts forward a research model that is empirically tested.

The development of remote learning

According to the social constructivist theory, individuals necessitate social interactions (Fridin, 2014; Lambropoulos, Faulkner & Culwin, 2012; Ainsworth, 2006; Tam, 2000). They develop their abilities by interacting with others. Therefore, online learning environments ought to be designed to support and challenge the students’ reflective and critical skills, by including interactive learning and collaborative approaches (Rienties & Toetenel, 2016; Dabbagh & Kitsantas, 2012; Wang, 2009; Wang, Woo, & Zhao, 2009). Social constructivism and discovery-based learning techniques emphasize the importance of having students who are actively involved in their learning process. This is in stark contrast with previous educational viewpoints where the responsibility rested with the instructor to teach, and where the learner played a passive, receptive role (Lambropoulos et al., 2012).

Today’s students are increasingly using online technologies to learn, both in and out of their higher educational institutions (Al-Maroof, Al-Qaysi, & Salloum, 2021). They are using interactive media to acquire formal and informal skills (Dabbagh & Kitsantas, 2012), particularly when they take part in constructivist activities with their peers and course instructors (Fridin, 2014). This argumentation is consistent with the collaborative learning theory (Lambropoulos et al., 2012; Khalifa & Kwok, 1999). Students can use digital technologies to access recorded podcasts (Merhi, 2015; Lin et al., 2013), watch videos (Hung, 2016) and interact together through live streaming technologies in real time (Payne, Keith, Schuetzler & Giboney, 2017). Hence, online education has fostered collaborative learning approaches (Wang, 2009). Computer mediated education enables students to search for solutions, to share online information with their peers, to evaluate each other’s ideas, and to monitor one another’s work (Lambić, 2016; Sung et al., 2015; Soflano, et al., 2015).

Course participants can use remote technologies, including their personal computers, smart phones and tablets to access their instructors’ asynchronous, online resources including course notes, power point presentations, videos clips, case studies, et cetera (Butler, Camilleri, Creed & Zutshi, 2021; Hung, 2016; Ifenthaler & Schweinbenz, 2013). Moreover, in this day and age, they are utilizing video conferencing technologies to attend virtual meetings, and to engage in one-to-one conversations, or in group discussions and debates with their course instructor and with other students. These virtual programs enable students to engage in synchronous communications with course instructors, to ask questions, and receive feedback, in real time.

A critical review of the relevant literature reported that university students were already using asynchronous technologies, in different contexts, before the outbreak of COVID-19 (Butler et al., 2021; Sánchez-Prieto et al., 2017; Hung, 2016; Liu et al., 2010; Sánchez & Hueros, 2010). Many authors held that online technologies were improving the students’ experiences (Crompton & Burke, 2018; Kurucay & Inan, 2017; Sánchez-Prieto et al., 2016). Before the outbreak of COVID-19, many practitioners blended traditional learning methodologies with digital and mobile applications to improve learning outcomes (Al-Maroof et al., 2021; Boelens et al., 2018; Furió et al., 2015). Course instructors can design and develop online learning environments to support their students with asynchronous resources (Wang et al., 2009). They may allow them to engage in collaborative learning activities through virtual environments (Rienties & Toetenel, 2016; Dabbagh & Kitsantas, 2012). These contemporary approaches are synonymous with the social constructivist theory (Fridin, 2014; Lambropoulos et al., 2012) and with discovery-based learning (Ifenthaler, 2012; Lambropoulos et al., 2012).

Theoretical implications
This contribution investigated the students’ perceived usefulness, perceived interactivity, attitudes toward use, facilitating conditions and behavioral intentions to utilize remote technologies. It posited that higher education students perceived the usefulness of remote learning technologies including LMS and video conferencing programs during COVID-19. The findings clearly indicated that they valued their interactive attributes. These factors have led them to embrace these programs during their learning journey. This study also confirmed that the universities’ facilitating conditions had a significant effect on their perceptions about the interactivity of these online learning resources and on their attitudes towards these technologies, as reported in Figure 1. This finding is consistent with previous research that reported that facilitating conditions is positively related to the students’ intentions to continue using digital and mobile learning resources (Gangwar et al., 2015; Teo, 2009).

This image has an empty alt attribute; its file name is the-use-of-learning-management-systems-and-conferencing-technologies.png — Figure 1

This study has differentiated itself from previous contributions as it integrated facilitating conditions (Hoi, 2020; Dečman, 2015; Venkatesh et al. 2003; 2012) and perceived interactivity (Chattaraman et al., 2019; Chen et al., 2007; McMillan & Jang-Sun Hwang, 2002) with perceived usefulness (of technology) and attitudes (toward the use of technology) to better understand the students’ intentions to utilize remote learning technologies to improve their learning journey (Cheng & Yuen, 2018; Al-Rahmi et al., 2018; Merhi, 2015; Schoonenboom, 2014; Lin et al., 2013; Ngai et al., 2007; Davis, 1989) during an unexpected pandemic situation.
A bibliographic analysis revealed that there are a number of theoretical papers that have been published in the last eighteen months on this hot topic (Cesco et al., 2021; Fitter et al., 2020; Howley, 2020; Rahiem, 2020). Yet, to date, there are just a few rigorous studies, that examined the utilization of synchronous video conferencing technologies, in addition to conventional, asynchronous content, like LMS, in the context of higher education (Aguilera-Hermida, 2020; Gonzalez et al., 2020).
The findings from this research shed light on the utilitarian factors that were influencing the students’ engagement with interactive learning resources. According to the descriptive statistics, the students felt that remote technologies were useful to achieve their learning outcomes. They indicated that they were provided with appropriate facilitating conditions that enabled them to migrate to a fully virtual learning environment from face-to-face or blended learning approaches. During the pandemic’s lockdown or partial lockdown conditions, and even when the preventative measures were eased, many students were still using remote learning technologies to access online educational resources. They also kept using video conferencing technologies to attend to virtual classes, and to engage with their course instructor(s) and with their peers, in real time.
The confirmatory composite analysis reported that there were positive and highly significant effects that predicted the students’ intentions to use remote learning technologies. Evidently, educators have provided them with the necessary resources, knowledge and technical support to avail themselves of remote learning technologies. The respondents indicated that they accessed their course instructors’ online resources and regularly interacted with them through live conferencing facilities. The findings from SEM-PLS confirmed that the perceived usefulness and perceived interactivity with online technologies had a positive effect on their attitudes toward remote learning. This research implies that the students were confident with the utilization of interactive technologies to continue their educational programs. In fact, this research model proved that they were likely to use synchronous and asynchronous learning technologies in the foreseeable future, in a post COVID-19 context.
Implications of study for educators and policy makers
The COVID-19 pandemic and its preventative measures urged HEIs and other educational institutions to embrace video conferencing technologies to continue delivering student-centered education. This research suggests that educators ought to monitor their students’ engagement during their virtual sessions. It revealed that the students’ perceived interactivity as well as their higher education institutions’ facilitating conditions were having an effect on their perceptions about the usefulness of remote learning, on their attitudes as well as on their intentions to use them. These digital technologies were supporting the research participants in their learning journeys, whether they were at home or on campus. The students themselves perceived the usefulness of asynchronous LMS as well as of synchronous communications, including video conferencing software like Zoom or Microsoft Teams, among others.
These virtual technologies were already utilized in various contexts, before the outbreak of COVID-19. However, they turned out to be important learning resources in the realms of education. Course instructors are expected to support their students, by developing attractive digital learning resources (e.g. interactive presentations, online articles and recorded video clips) in appropriate formats that can be accessed with ease, through different media, including mobile technologies (Sablić et al., 2020). In this day and age, they can also use video conferencing technologies to interact with course participants in real time. When engaging with online resources, instructors should consider their students’ facilitating conditions, particularly if they are including high-res images, interactive media, including podcasts, videos, etc., in their LMSs. Their asynchronous content should be as clear and focused as possible, with links to relevant sources, including notes, case studies, quizzes, rubrics and formative assessments, among others.
COVID-19 has taught us that the individuals’ engagement with LMS and video conferencing software necessitate high‐quality wireless networks. There may be situations where students as well as their instructors may require online technical support, whether they are working from home of from university premises. Educational institutions including HEIs ought to regularly evaluate their students’ experiences with remote teaching in order to identify any issues that are affecting their academic performance (Camilleri, 2021b). HEI leaders are not always in a position to evaluate the quality and standards of their instructors’ online learning methods and to determine with absolute certainty whether their students have achieved their learning outcomes. During remote course delivery, students may not always have access to appropriate interactive technologies, learning materials or to adequate productive environments (Bao, 2020). There can be instances where course instructors and students could require facilitating conditions like technical support or training and development to enhance their competences and capabilities with the use of remote technologies.
A prepublication copy of this contribution can be downloaded through: https://www.researchgate.net/publication/353859136_The_Acceptance_of_Learning_Management_Systems_and_Video_Conferencing_Technologies_Lessons_Learned_from_COVID-19

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April 3, 2020 · 11:43 am

The Performance Management in Higher Education

This is an excerpt from my latest academic article, entitled; “Using the balanced scorecard as a performance management tool in higher education” that will be published in Sage’s “Management in Education” (Journal).

The higher education institutions (HEIs) are competing in a global marketplace, particularly those which are operating in the contexts of neoliberal policymaking (Fadeeva and Mochizuki, 2010; Deem et al., 2008; Olssen and Peters, 2005; Bleiklie, 2001). Several universities are characterized by their de-centralized leadership as they operate with budget constraints (Smeenk, Teelken, Eisinga and Doorewaard, 2008; Bleiklie, 2001). Notwithstanding, their stakeholders expect their increased accountability and quality assurance, in terms of their efficiency, economy and effectiveness (Witte and López-Torres, 2017; Smeek et al., 2008). Hence, HEIs set norms, standards, benchmarks, and quality controls to measure their performance; as they are increasingly market-led and customer-driven (Jauhiainen, Jauhiainen, Laiho and Lehto, 2015; Billing, 2004; Etzkowitz, et al., 2000). Specifically, the universities’ performance is having a positive effect on the economic development of societies; through the provision of inclusive, democratized access to quality education and high impact research (Arnesen & Lundahl, 2006). Moreover, the educational institutions are also expected to forge strong relationships with marketplace stakeholders, including business and industry (Waring, 2013).

As a result, many universities have adapted, or are trying to adapt to the changing environment as they re-structure their organization and put more emphasis on improving their organizational performance. These developments have inevitably led to the emergence of bureaucratic procedures and processes (Jauhiainen et al., 2015). HEIs have even started using the corporate language as they formulate plans, set objectives, and use performance management criteria to control their resources (Smeenk et al., 2008; Ball, 2003). For instance, the Finnish universities have introduced new steering mechanisms, including the performance systems in budgeting, organizational reforms, management methods and salary systems (Camilleri, 2018; Jauhiainen et al., 2015). Previously, Welch (2007) noted that HEIs were adopting new modes of governance, organizational forms, management styles, and values that were prevalent in the private business sector. The logic behind these new managerial reforms was to improve the HEIs’ value for money principles (Waring, 2013; Deem, 1998). Therefore, the financing of HEIs is a crucial element in an imperfectly competitive, quasi-market model (Marginson, 2013; Olssen and Peters, 2005; Enders, 2004; Dill, 1997).

Academic commentators frequently suggest that the managerial strategies, structures, and values that belong to the ‘private sector’ are leading to significant improvements in the HEIs’ performance (Waring, 2013; Teelken, 2012; Deem and Brehony, 2005; Deem, 1998). On the other hand, critics argue that the ‘managerial’ universities are focusing on human resource management (HRM) practices that affect the quality of their employees’ job performance (Smeenk et al., 2008). Very often, HEIs are employing bureaucratic procedures involving time-consuming activities that could otherwise have been invested in research activities and / or to enhance teaching programs. The HEIs’ management agenda is actually imposed on the academics’ norms of conduct and on their professional behaviors. Therefore, the universities’ leadership can affect the employees’ autonomies as they are expected to comply with their employers’ requirements (Deem and Brehony, 2005). Smeenk et al. (2008) posited that this contentious issue may lead to perennial conflicts between the employees’ values and their university leaders’ managerial values; resulting in lower organizational commitment and reduced productivities.

The HEIs’ managerial model has led to a shift in the balance of power from the academics to their leaders as the universities have developed quality assurance systems to monitor and control their academic employees’ performance (Camilleri, 2018; Cardoso, Tavares and Sin, 2015). This trend towards managerialism can be perceived as a lack of trust in the academic community. However, the rationale behind managerialism is to foster a performative culture among members of staff, as universities need to respond to increased competitive pressures for resources, competences and capabilities (Decramer et al., 2013; Marginson, 2006; 2001; Enders, 2004). These issues have changed the HEIs’ academic cultures and norms in an unprecedented way (Chou and Chan, 2016; Marginson, 2013).

HEIs have resorted to the utilization of measures and key performance indicators to improve their global visibility. Their intention is to raise their institutions’ profile by using metrics that measure productivity. Many universities have developed their own performance measures or followed frameworks that monitor the productivity of academic members of staff (Taylor and Baines, 2012). Very often, their objective is to audit their academic employees’ work. However, their work cannot always be quantified and measured in objective performance evaluations. For instance, Waring (2013) argued that academic employees are expected to comply with their employers’ performance appraisals (PAs) and their form-filling exercises. The rationale behind the use of PAs is to measure the employees’ productivity in the form of quantifiable performance criteria. Hence, the PA is deemed as a vital element for the evaluation of the employees’ performance (Kivistö et al., 2017; Dilts et al., 1994). The PA can be used as part of a holistic performance management approach that measures the academics’ teaching, research and outreach. This performance management tool can possibly determine the employees’ retention, promotion, tenure as well as salary increments (Subbaye, 2018; Ramsden, 1991).

Therefore, PAs ought to be clear and fair. Their administration should involve consistent, rational procedures that make use of appropriate standards. The management’s evaluation of the employees’ performance should be based on tangible evidence. In a similar vein, the employees need to be informed of what is expected from them (Dilts et al., 1994). They should also be knowledgeable about due processes for appeal arising from adverse evaluations, as well as on grievance procedures, if any (Author, 2018). In recent years; the value of the annual performance appraisals (PAs) has increasingly been challenged in favor of more regular ‘performance conversations’ (Aguinis, 2013; Herdlein, Kukemelk and Türk, 2008). Therefore, regular performance feedback or the frequent appraisal of employees still remain a crucial aspect of the performance management cycle. Pace (2015) reported that the PA was used to develop the employees’ skills, rather than for administrative decisions. In a similar vein, the University of Texas (2019) HR page suggests that the appraisers’ role is “to set expectations, gather data, and provide ongoing feedback to employees, to assist them in utilizing their skills, expertise and ideas in a way that produces results”. However, a thorough literature review suggests that there are diverging views among academia and practitioners on the role of the annual PA, the form it should take, and on its effectiveness in the realms of higher education (Herdlein et al., 2008; DeNisi and Pritchard, 2006).

The Performance Management Frameworks

The HEIs’ evaluative systems may include an analysis of the respective universities’ stated intentions, peer opinions, government norms and comparisons, primary procedures from ‘self-evaluation’ through external peer review. These metrics can be drawn from published indicators and ratings, among other frameworks (Billing, 2004). Their performance evaluations can be either internally or externally driven (Cappiello and Pedrini, 2017). The internally driven appraisal systems put more emphasis on self-evaluation and self-regulatory activities (Baxter, 2017; Bednall, Sanders and Runhaar, 2014; Dilts et al., 1994). Alternatively, the externally driven evaluative frameworks may involve appraisal interviews that assess the quality of the employees’ performance in relation to pre-established criteria (DeNisi and Pritchard, 2006; Cederblom, 1982).

Many countries, including the European Union (EU) states have passed relevant legislation, regulatory standards and guidelines for the HEIs’ quality assurance (Baxter, 2017), and for the performance evaluations of their members of staff (Kohoutek et al., 2018; Cardoso et al., 2015; Bleiklie, 2001). Of course, the academic employees’ performance is usually evaluated against their employers’ priorities, commitments, and aims; by using relevant international benchmarks and targets (Lo, 2009). The academics are usually appraised on their research impact, teaching activities and outreach (QS Ranking, 2019; THE, 2019). Their academic services, including their teaching resources, administrative support, and research output all serve as performance indicators that can contribute to the reputation and standing of the HEI that employs them (Geuna and Martin, 2003).

Notwithstanding, several universities have restructured their faculties and departments to enhance their research capabilities. Their intention is to improve their institutional performance in global rankings (Lo, 2014). Therefore, HEIs recruit academics who are prolific authors that publish high-impact research with numerous citations in peer reviewed journals (Wood and Salt, 2018; Author, 2018). They may prefer researchers with scientific or quantitative backgrounds, regardless of their teaching experience (Chou and Chan, 2016). These universities are prioritizing research and promoting their academics’ publications to the detriment of university teaching. Thus, the academics’ contributions in key international journals is the predominant criterion that is used to judge the quality of academia (Billing, 2004). For this reason, the vast majority of scholars are using the English language as a vehicle to publish their research in reputable, high impact journals (Chou and Chan, 2016). Hence, the quantity and quality of their research ought to be evaluated through a number of criteria (Lo, 2014; 2011; Dill and Soo, 2005).

University ranking sites, including (THE) and the QS Rankings, among others, use performance indicators to classify and measure the quality and status of HEIs. This would involve the gathering and analysis of survey data from academic stakeholders. THE and QS, among others clearly define the measures, their relative weight, and the processes by which the quantitative data is collected (Dill and Soo, 2005). The Academic Ranking of World Universities (ARWU) relies on publication-focused indicators as 60 percent of its weighting is assigned to the respective university’s research output. Therefore, these university ranking exercises are surely affecting the policies, cultures and behaviors of HEIs and of their academics (Wood and Salt, 2018; De Cramer et al., 2013; Lo, 2013). For instance, the performance indicators directly encourage the recruitment of international faculty and students. Other examples of quantitative metrics include the students’ enrolment ratios, graduate rates, student drop-out rates, the students’ continuation of studies at the next academic level, and the employability index of graduates, among others. Moreover, qualitative indicators can also provide insightful data on the students’ opinions and perceptions about their learning environment. The HEIs could evaluate the students’ satisfaction with teaching; satisfaction with research opportunities and training; perceptions of international and public engagement opportunities; ease of taking courses across boundaries, and may also determine whether there are administrative / bureaucratic barriers for them (Kivistö et al., 2017; Jauhiainen et al., 2015; Ramsden, 1991). Hence, HEIs ought to continuously re-examine their strategic priorities and initiatives. It is in their interest to regularly analyze their performance management frameworks through financial and non-financial indicators, in order to assess the productivity of their human resources. Therefore, they should regularly review educational programs and course curricula (Kohoutek et al., 2018; Brewer and Brewer, 2010). On a faculty level, the university leaders ought to keep a track record of changes in the size of departments; age and distribution of academic employees; diversity of students and staff, in terms of gender, race and ethnicity, et cetera. In addition, faculties could examine discipline-specific rankings; and determine the expenditures per academic member of staff, among other options (Author, 2018).

The balanced scorecard

The balanced scorecard (BSC) was first introduced by Kaplan and Norton (1992) in their highly cited article, entitled “The Balanced Scorecard: Measures that Drive Performance”. BSC is an integrated results-oriented, performance management tool, consisting of financial and non-financial measures that link the organizations’ mission, core values, and vision for the future with strategies, targets, and initiatives that are designed to bring continuous improvements (Taylor and Baines, 2012; Wu, Lin and Chang, 2011; Beard, 2009; Umashankar and Dutta, 2007; Cullen, Joyce, Hassall and Broadbent, 2003; Kaplan and Norton, 1992). Its four performance indicators play an important role in translating strategy into action; and can be utilized to evaluate the performance of HEIs. BSC provides a balanced performance management system as it comprises a set of performance indices that can assess different organizational perspectives (Taylor and Baines, 2012). For BSC, the financial perspective is a core performance measure. However, the other three perspectives namely: customer (or stakeholder), organizational capacity and internal process ought to be considered in the performance evaluations of HEIs, as reported in the following table:

The balanced scorecard approach in higher education

Cullen et al. (2003) suggested that the UK’s Higher Education Funding Council for England (HEFCE), the Scottish Funding Council (SHEFC), the Higher Education Funding Council for Wales (HEFCW), as well as the Department for Employment and Learning (DELNI) have incorporated the BSC’s targets in their Research Excellence Framework. Furthermore, other HEI targets, including: the students’ completion rates, the research impact of universities, collaborative partnerships with business and industry, among others, are key metrics that are increasingly being used in international benchmarking exercises, like the European Quality Improvement System (EQUIS), among others. Moreover, BSC can be used to measure the academic employees’ commitment towards their employer (Umashankar and Dutta, 2007; McKenzie, and Schweitzer, 2001). Notwithstanding, Wu, Lin and Chang (2011) contended that the BSC’s ‘‘organizational capacity’’ is related to the employee development, innovation and learning. Hence the measurement of the HEIs’ intangible assets, including their intellectual capital is affected by other perspectives, including the financial one (Taylor and Baines, 2012). This table summarizes some of the strengths and weaknesses of the balanced scorecard.

BSC is widely used to appraise the financial and non-financial performance of businesses and public service organizations including HEIs. Many HEI leaders are increasingly following business-like approaches as they are expected to operate in a quasi-market environment (Marginson, 2013). They need to scan their macro environment to be knowledgeable about the opportunities and threats from the political, economic, social and technological factors. Moreover, they have to regularly analyze their microenvironment by evaluating their strengths and weaknesses. Hence, several HEIs are increasingly appraising their employees as they assess their performance on a regular basis. They may even decide to take remedial actions when necessary. Therefore, BSC can also be employed by HEIs to improve their academic employees’ productivity levels (Marginson, 2013; 2000).

A pre-publication version of the full article is available through ResearchGate and Academia.edu.

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Filed under academia, Balanced Scorecard, Education, Education Leadership, Higher Education, Human Resources, human resources management, performance appraisals, performance management, University Ranking, webometrics

Tagged as Balanced Scorecard, educational leadership, Higher Education, higher education institutions, Human Resources, human resources management, management, performance management, Strategic Management, Universities

September 29, 2019 · 6:19 pm

The Students’ Engagement with Mobile Learning Technologies

These are excerpts from our latest academic article.

How to Cite: Camilleri, M.A. & Camilleri, A.C. (2019). The Students’ Readiness to Engage with Mobile Learning Apps. Interactive Technology and Smart Education. https://www.emerald.com/insight/content/doi/10.1108/ITSE-06-2019-0027/full/html

Hand-held mobile devices such as smart phones and tablets allow individuals, including students, to access and review online (educational) content from virtually anywhere. The mobile applications (apps) can provide instant access to the schools’ learning resources (Camilleri & Camilleri, 2019b; Sánchez & Isaías, 2017; Cheon, Lee, Crooks & Song, 2012). Therefore, they are increasingly being utilized in the context of primary education to improve the student experience. Relevant theoretical underpinnings reported that more primary level students are utilizing mobile learning technologies to engage with their instructors (Rodríguez, Riaza & Gómez, 2017; Sánchez & Isaías, 2018). Notwithstanding, it is much easier for the younger pupils to mobile apps to read eBooks, as hard-copy textbooks need to be carried in their bags. Arguably, the proliferation of portable technologies like tablets are lighter and less bulky than laptop computers. Hence, primary school students can easily use mobile technologies anywhere, beyond the traditional classroom environment (Rodríguez et al., 2017). Currently, there is a wide variety of educational apps that are readily available on a wide array of mobile devices (Chee, Yahaya, Ibrahim &Hasan, 2017; Domingo & Garganté, 2016). Such interactive technologies can improve the delivery of quality education as teachers provide direct feedback to their students, in real time. Some of the mobile apps can even engage primary school students in immersive learning experiences (Camilleri & Camilleri,2019c; Isaias, Reis, Coutinho & Lencastre, 2017).

On the other hand, other academic literature posited that some students may not want to engage in mobile learning. Very often, commentators implied that the mobile technologies have their own limitations (Cheon et al., 2012; Wang, Wu & Wang, 2009). A few practitioners contended that mobile devices had small screens with low resolutions. Alternatively, some argued about their slow connection speeds, or pointed out that they lacked standardization features (Sánchez & Isaías, 2017; Camilleri & Camilleri,2017).

As a matter of fact, Android, Apple and Microsoft Windows have different operating systems. As a result, learning apps may have to be customized to be compatible with such systems. Moreover, individuals, including primary school students may hold different attitudes towards the use of mobile devices. There may be students who may be motivated to engage with mobile technologies (Sánchez & Isaias, 2018; Ciampa, 2014) as they use these devices to play games, watch videos, or to chat with their friends, online (Wang et al., 2009). In this case, the primary school students may use their mobile devices for hedonic reasons, rather than to engage in mobile learning activities. Such usage of the mobile technologies can possibly result in undesired educational outcomes. Nevertheless, those primary level students who already own or have instant access to a mobile device may easily become habitual users of this technology; as they use it for different purposes. However, there is still limited research in academia that explores these students’ readiness to engage in mobile learning at home, and at school.

Results

The findings in this study are consistent with the argument that digital natives are increasingly immersing themselves in digital technologies (Bourgonjon et al., 2010), including educational games (Camilleri & Camilleri,2019; Ge & Ifenthaler, 2018; Carvalho et al., 2015, Wouters et al., 2013). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them. Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational apps; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school. This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is a common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given.

Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.

References (the full bibliography of this paper)

Ajzen, I. (1991), “The theory of planned behavior”, Organization Behaviour and Human Decision Processes, Vol. 50, No. 2, pp. 179-211.

Bourgonjon, J., Valcke, M., Soetaert, R., and Schellens, T. (2010), “Students’ perceptions about the use of educational games in the classroom”, Computers & Education, Vol. 54, No. 4, pp. 1145-1156.

Burguillo, J.C. (2010), “Using game theory and competition-based learning to stimulate student motivation and performance”, Computers & Education, Vol. 55, No. 2, pp. 566-575.

Camilleri, M.A. and Camilleri, A. (2017a), “The Technology Acceptance of Mobile Applications in Education”, In Sánchez, I.A. & Isaias, P. (Eds) 13th International Conference on Mobile Learning (Budapest, 11th April). Proceedings, pp 41-48. International Association for Development of the Information Society.

Camilleri, M.A., and Camilleri, A.C. (2017b), “Digital learning resources and ubiquitous technologies in education”, Technology, Knowledge and Learning, Vol. 22, No. 1, pp. 65-82.

Camilleri, M. A., and Camilleri, A. (2019a), “Student Centred Learning Through Serious Games”, 13th Annual International Technology, Education and Development Conference. Valencia, Spain (March, 2019). International Academy of Technology, Education and Development (IATED).

Camilleri, A.C., and Camilleri, M.A. (2019b), “Mobile Learning via Educational Apps: An Interpretative Study”. In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019). International Economics Development and Research Center (IEDRC).

Camilleri, A.C., and Camilleri, M.A. (2019c), “The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games”, In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019). International Economics Development and Research Center (IEDRC).

Carvalho, M.B., Bellotti, F., Berta, R., De Gloria, A., Sedano, C.I., Hauge, H.B., Hu, J., and Rauterberg, M. (2015), “An activity theory-based model for serious games analysis and conceptual design”, Computers & Education, Vol. 87, pp.166-181.

Chang, C.T., Hajiyev, J., and Su, C.R. (2017), “Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for e-learning approach”, Computers & Education, Vol. 111, pp. 128-143.

Chee, K. N., Yahaya, N., Ibrahim, N. H., and Hasan, M. N. (2017). Review of mobile learning trends 2010-2015: A meta-analysis. Journal of Educational Technology & Society, 20(2), 113-126.

Chen, K. C. and Jang, S. J. (2010), “Motivation in online learning: Testing a model of self-determination theory”, Computers in Human Behavior, Vol. 26, No. 4, pp. 741-752.

Cheon, J., Lee, S., Crooks, S. M. and Song, J. (2012), “An investigation of mobile learning readiness in higher education based on the theory of planned behavior”, Computers & Education, Vol. 59, No. 3, pp. 1054-1064.

Ciampa, K. (2014), “Learning in a mobile age: an investigation of student motivation”, Journal of Computer Assisted Learning, Vol. 30, No. 1, pp. 82-96.

Connolly, T.M., Boyle, E.A., MacArthur, E. Hainey, T., and Boyle, J.M. (2012), “A systematic literature review of empirical evidence on computer games and serious games”, Computers & Education, Vol. 59, No. 2, pp. 661-686.

Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, No. 3, pp. 319-340.

Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. (1989), “User acceptance of computer technology: a comparison of two theoretical models”, Management Science, Vol. 35, No. 8, pp. 982-1003.

Dickey, M.D. (2011), “Murder on Grimm Isle: The impact of game narrative design in an educational game‐based learning environment”, British Journal of Education Technology, Vol. 42, No. 3, pp. 456-469.

Domingo, M. G. and Garganté, A. B. (2016). Exploring the use of educational technology in primary education: Teachers’ perception of mobile technology learning impacts and applications’ use in the classroom. Computers in Human Behavior, Vol. 56, pp. 21-28.

Dunne, Á., Lawlor, M. A., and Rowley, J. (2010), “Young people’s use of online social networking sites–a uses and gratifications perspective”, Journal of Research in International Marketing,. Vol. 4, No. 1, pp. 46-58.

Ge, X., and Ifenthaler, D. (2018), “Designing engaging educational games and assessing engagement in game-based learning”, In Gamification in Education: Breakthroughs in Research and Practice, IGI Global, Hershey, USA, pp. 1-19.

Harris, J. Mishra, P., and Koehler, M. (2009), “Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed”, Journal of Research on Technology in Education, Vol. 41, No. 4, pp. 393-416.

Huang, W.H., Huang, W.Y., and Tschopp, J. (2010), “Sustaining iterative game playing processes in DGBL: The relationship between motivational processing and outcome processing”, Computers & Education, Vol. 55, No. 2, pp. 789-97.

Hwang, G.J., and Wu, P.H. (2012), “Advancements and trends in digital game‐based learning research: a review of publications in selected journals from 2001 to 2010”, British. Journal of Education Technology, Vol. 43, No. 1, pp. E6-E10.

Isaias, P., Reis, F., Coutinho, C. and Lencastre, J. A. (2017), “Empathic technologies for distance/mobile learning: An empirical research based on the unified theory of acceptance and use of technology (UTAUT)”, Interactive Technology and Smart Education, Vol. 14, No. 2, pp. 159-180.

Lee, M. K., Cheung, C. M., and Chen, Z. (2005), “Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation”, Information & Management,. Vol. 42, No. 8, pp. 1095-1104.

Li, H., Liu, Y., Xu, X., Heikkilä, J., and Van Der Heijden, H. (2015), “Modeling hedonic is continuance through the uses and gratifications theory: An empirical study in online games”, Computers in Human Behavior, Vol. 48, pp. 261-272.

Park, S.Y. (2009), “An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning”, Education. Technology & Society, Vol. 12, No. 3, pp. 150-162.

Park, S. Y., Nam, M. W., and Cha, S. B. (2012), “University students’ behavioral intention to use mobile learning: Evaluating the technology acceptance model”, British Journal of Education Technology, Vol. 43, No. 4, pp. 592-605.

Rodríguez, A. I., Riaza, B. G., & Gómez, M. C. S. (2017), “Collaborative learning and mobile devices: An educational experience in Primary Education”, Computers in Human Behavior, Vol. 72, pp. 664-677.

Ryan, R. M., and Deci, E. L. (2000), “Intrinsic and extrinsic motivations: Classic definitions and new directions”, Contemporary Education Psychology, Vol. 25, No. 1, pp. 54-67.

Sánchez, I. A., & Isaías, P. (2017), “Proceedings of the International Association for Development of the Information Society (IADIS)”, International Conference on Mobile Learning (13th, Budapest, Hungary, April 10-12, 2017). International Association for Development of the Information Society.

Sánchez, I. A., & Isaias, P. (2018), “Proceedings of the International Association for Development of the Information Society (IADIS)”, International Conference on Mobile Learning (14th, Lisbon, Portugal, April 14-16, 2018). International Association for Development of the Information Society.

Teo, T., Beng Lee, C., Sing Chai, C., and Wong, S.L. (2009), “Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM)”, Computers & Education, Vol. 53, No. 3, pp. 1000-1009.

Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), “User acceptance of information technology: Toward a unified view”, MIS Quarterly, Vol. 27, No. 3, pp. 425-478.

Venkatesh, V., Thong, Y.T.L., and Xu, X. (2012), “Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology”, MIS Quarterly, Vol. 36, No.1, pp. 157-178.

Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009), “Investigating the determinants and age and gender differences in the acceptance of mobile learning”, British Journal of Educational technology, Vol. 40, No. 1, pp. 92-118.

Wouters, P., Van Nimwegen, C., Van Oostendorp, H., and Van Der Spek, E.D. (2013), “A meta-analysis of the cognitive and motivational effects of serious games”, Journal of Education Psychology, Vol. 105, No. 2, pp. 249-266.

Related Publications

Camilleri, M.A. & Camilleri, A.C. (2019). The Acceptance and Use of Mobile Learning Applications in Higher Education. In Pfennig, A. & Chen, K.C. (Eds.) 3^rd International Conference on Education and eLearning (ICEEL2019), Barcelona, Spain.

Camilleri, A.C. & Camilleri, M.A. (2019). The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games at Home and at School. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (March, 2019). International Academy of Technology, Education and Development (IATED).Download this paper

Camilleri, M.A. & Camilleri, A. (2017). The Students’ Perceptions of Digital Game-Based Learning. In Pivec, M. & Grundler, J. (Ed.) 11th European Conference on Games Based Learning (October). Proceedings, pp. 52-62, H JOANNEUM University of Applied Science, Graz, Austria, pp 56-62. http://toc.proceedings.com/36738webtoc.pdf Download this paper

Camilleri, M.A. & Camilleri, A. (2017). Measuring The Educators’ Behavioural Intention, Perceived Use And Ease Of Use Of Mobile Technologies. In Wood, G. (Ed) Re-connecting management research with the disciplines: Shaping the research agenda for the social sciences (University of Warwick, September). Proceedings, pp., British Academy of Management, UK. http://conference.bam.ac.uk/BAM2017/htdocs/conference_papers.php?track_name=%20Knowledge%20and%20Learning Download this paper

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Filed under Education, education technology, internet technologies, internet technologies and society, Marketing, Mobile, mobile learning

Tagged as academic article, blended learning, Education, education technology, Mark Camilleri, Mobile, mobile learning, research, technology acceptance

May 28, 2019 · 9:22 pm

The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games

An Excerpt from one of my latest papers, entitled; “The Students’ Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games”.

How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games. In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019).

This contribution has explored the primary school’s grade three students’ intrinsic and extrinsic motivations toward the use of educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the schools’ games ([7], [8], [15]). Moreover, the researchers have also included the measuring items that explored the students’ perceived enjoyment ([12], [13], [20]) as they investigated whether they experienced normative pressures to play the educational games ([14], [22], [23]). The findings from the Wilcoxon test reported that the students played the school games at home, more than they did at school. They indicated that the school’s games were easy to play.

This study reported that the students recognized that the school’s games were useful and relevant as they were learning from them. Moreover, they indicated that the school’s educational games held their attention since they found them enjoyable and fun. The vast majority of the children played the educational games, both at home and at school. The findings in this study are consistent with the argument that digital natives are increasingly immersing
themselves in digital technologies ([2]), including educational games ([1], [4], [10], [11], [28]). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them.

Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational games; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school.

This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given. In this case, the survey items in this study were designed and adapted for the primary school children who were in grade 3, in a
small European state. Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.

ACKNOWLEDGEMENTS
We thank the department of education, the school’s principal and her members of staff who have provided their invaluable support during the data gathering process.

REFERENCES
[1] Ge, X., and Ifenthaler, D. 2018. Designing engaging
educational games and assessing engagement in game-based
learning” In Gamification in Education: Breakthroughs in
Research and Practice, IGI Global, Hershey, USA, 1-19,

[2] Bourgonjon, J., Valcke, M., Soetaert, R., and Schellens, T.
2010, Students’ perceptions about the use of educational
games in the classroom. Comp. & Educ. 54, 4, 1145-1156.

[3] Hwang, G.J., and Wu, P.H. 2012. Advancements and trends
in digital game‐based learning research: a review of
publications in selected journals from 2001 to 2010. Brit. J.
of Educ. Tech. 43, 1, E6-E10.

[4] Carvalho, M.B., Bellotti, F., Berta, R., De Gloria, A.,
Sedano, C.I., Hauge, H.B., Hu, J., and Rauterberg, M. 2015.
An activity theory-based model for serious games analysis
and conceptual design. Comp. & Educ. 87, 166-181.

[5] Connolly, T.M., Boyle, E.A., MacArthur, E. Hainey, T., and
Boyle, J.M. 2012. A systematic literature review of empirical
evidence on computer games and serious games. Comp. &
Educ. 59, 2, 661-686.

[6] Burguillo, J.C. 2010. Using game theory and competitionbased
learning to stimulate student motivation and
performance. Comp. & Educ. 55, 2, 566-575.

[7] Dickey, M.D. 2011. Murder on Grimm Isle: The impact of
game narrative design in an educational game‐based learning
environment. Brit. J. of Educ. Tech, 42, 3, 456-469.

[8] Huang, W.H., Huang, W.Y., and Tschopp, J. 2010.
Sustaining iterative game playing processes in DGBL: The
relationship between motivational processing and outcome
processing. Comp. & Educ. 55, 2, 789-97.

[9] Harris, J. Mishra, P., and Koehler, M. 2009. Teachers’
technological pedagogical content knowledge and learning
activity types: Curriculum-based technology integration
reframed. J. of Res. on Tech. in Educ. 41, 4, 393-416.

[10] Wouters, P., Van Nimwegen, C., Van Oostendorp, H., and
Van Der Spek, E.D. 2013. A meta-analysis of the cognitive
and motivational effects of serious games. J. of Educ. Psych.
105, 2, 249-266.

[11] Camilleri, M.A., and Camilleri, A. 2017. The Students’
Perceptions of Digital Game-Based Learning, In Pivec, M.
and Grundler, J. 11th European Conference on Games Based
Learning Proceedings (London, UK, October 04-05, 2017),
University of Applied Sciences, Graz, Austria, 56-62.

[12] Davis, F.D. 1989. Perceived usefulness, perceived ease of
use, and user acceptance of information technology. MIS
Quart. 319-340.

[13] Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. 1989. User
acceptance of computer technology: a comparison of two
theoretical models. Mgt. Science, 35, 8, 982-1003.

[14] Ajzen, I. 1991. The theory of planned behavior. Org. Behav.
and Human Dec. Proc. 50, 2, 179-211.

[15] Lee, M. K., Cheung, C. M., and Chen, Z. 2005. Acceptance
of Internet-based learning medium: the role of extrinsic and
intrinsic motivation. Inf. & Mgt. 42, 8, 1095-1104.

[16] Chen, K. C. and Jang, S. J. 2010. Motivation in online
learning: Testing a model of self-determination theory.
Comp. in Human Behav. 26, 4, 741-752.

[17] Dunne, Á., Lawlor, M. A., and Rowley, J. 2010. Young
people’s use of online social networking sites–a uses and
gratifications perspective. Journal of Res. in Int. Mktg. 4, 1,
46-58.

[18] Li, H., Liu, Y., Xu, X., Heikkilä, J., and Van Der Heijden, H.
2015. Modeling hedonic is continuance through the uses and
gratifications theory: An empirical study in online games.
Comp. in Human Behav. 48, 261-272.

[19] Teo, T., Beng Lee, C., Sing Chai, C., and Wong, S.L. 2009.
Assessing the intention to use technology among pre-service
teachers in Singapore and Malaysia: A multigroup invariance
analysis of the Technology Acceptance Model (TAM).
Comp. & Educ. 53, 3, 1000-1009.

[20] Camilleri, M.A., and Camilleri, A.C. 2017. Digital learning
resources and ubiquitous technologies in education, Tech.,
Knowl. and Learng. 22, 1, 65-82.

[21] Park, S.Y. 2009. An analysis of the technology acceptance
model in understanding university students’ behavioral
intention to use e-learning, Educ. Tech. & Soc. 12, 3, 150-
162.

[22] Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D.
2003. User acceptance of information technology: Toward a
unified view. MIS Quart. 425-478.

[23] Venkatesh, V., Thong, Y.T.L., and Xu, X. 2012.Consumer
acceptance and use of information technology: extending the
unified theory of acceptance and use of technology. MIS
Quart. 157-178.

[24] Ryan, R. M., and Deci, E. L. 2000. Intrinsic and extrinsic
motivations: Classic definitions and new directions.
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[25] Cheon, J., Lee, S., Crooks, S. M. and Song, J. 2012. An
investigation of mobile learning readiness in higher
education based on the theory of planned behavior. Comp. &
Educ. 59, 3, 1054-1064.

[26] Chang, C.T., Hajiyev, J., and Su, C.R. 2017. Examining the
students’ behavioral intention to use e-learning in
Azerbaijan? The general extended technology acceptance
model for e-learning approach. Comp. & Educ. 111, 128-
143.

[27] Park, S. Y., Nam, M. W., and Cha, S. B. 2012. University
students’ behavioral intention to use mobile learning:
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Educ. Tech. 43, 4, 592-605.

[28] Camilleri, M.A. and Camilleri, A.C. 2017. The Technology
Acceptance of Mobile Applications in Education. In
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International Conference on Mobile Learning (London, UK,
10-11 April 2018). International Association for
Development of the Information Society Budapest, Hungary,
41-48.

Presentation is available at: https://www.slideshare.net/markanthonycamilleri/the-students-intrinsic-and-extrinsic-motivations-148006875

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Filed under digital games, Digital Learning Resources, digital media, Education, internet technologies, internet technologies and society

Tagged as digital game based learning, digital games, Education, Education Technologies, educational apps, ICETT, mobile apps, mobile learning, research, technology acceptance model

March 22, 2019 · 12:02 pm

The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games

This is an excerpt from one of my latest empirical papers.

How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games at Home and at School. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (10-13 March, 2019). International Academy of Technology, Education and Development (IATED). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339163

games This contribution has explored the primary school’s grade three students’ attitudes toward educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the schools’ games ([10], [12], [44]). Moreover, the researchers have also included the measuring items that explored the students’ perceived enjoyment ([19]) as they investigated whether they experienced normative pressures to play the educational games ([10], [14], [20]). The findings from the Wilcoxon test reported that the students played the school games at home, more than they did at school. They indicated that the school’s games were easy to play. This study reported that the students recognized that the school’s games were useful and relevant as they were learning from them. Moreover, they indicated that the school’s educational games held their attention since they found them enjoyable and fun.

The vast majority of the children played the educational games, both at home and at school. The findings in this study are consistent with the argument that digital natives are increasingly immersing themselves in digital technologies ([45]), including educational games ([1], [3]). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them. Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational games; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school.

This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given. In this case, the survey items in this study were designed and adapted for the primary school children who were in grade 3, in a small European state. Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.

REFERENCES (this is a full list of references that appeared in the bibliography section of the paper)

[1] J. Bourgonjon, M. Valcke, R. Soetaert, and T. Schellens, “Students’ perceptions about the use of educational games in the classroom,” Computers & Education, vol. 54, no. 4, pp. 1145-1156, 2010.

[2] S. Bennett, K. Maton, and L. Kervin, “The ‘digital natives’ debate: A critical review of the evidence,” British Journal of Educational Technology, vol. 39, no. 5, pp. 775-786, 2008.

[3] M. Prensky, “Digital natives, digital immigrants part 1,” On the horizon, vol. 9, no. 5, pp. 1-6, 2001.

[4] W. Nadeem, D. Andreini, J. Salo, and T. Laukkanen, “Engaging consumers online through websites and social media: A gender study of Italian Generation Y clothing consumers.” International Journal of Information Management, vol. 35, no. 4, pp. 432- 442, 2015.

[5] H.J. So, H. Choi, W.Y. Lim, and Y. Xiong, “Little experience with ICT: Are they really the Net Generation student-teachers?”, Computers & Education, vol. 59, no. 4, pp. 1234- 1245, 2012.

[6] J.M. Twenge, “The evidence for generation me and against generation we.” Emerging Adulthood 1, no. 1, pp. 11-16, 2013.

[7] D. Oblinger, and J. Oblinger, “Is it age or IT: First steps toward understanding the net generation,” Educating the Net Generation, 2(1-2), 20, 2015.

[8] N. Howe, and W. Strauss, “Millennials go to college: Strategies for a new generation on campus,” American Association of Collegiate Registrars and Admissions Officers (AACRAO), 2003.

[9] K. Gregor, T. Judd, B. Dalgarno, and J. Waycott, “Beyond natives and immigrants: exploring types of net generation students,” Journal of Computer Assisted Learning, vol. 26, no. 5, pp.332-343, 2010.

[10] T. Teo, “Modelling technology acceptance in education: A study of pre-service teachers,” Computers & Education 52, no. 2 (2009): 302-312, 2009.

[11] M. Fishbein, and I. Ajzen, “Belief, attitude, intention and behavior: An introduction to theory and research,” 1975.

[12] F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, pp. 319-340, 1989.

[13] F.D. Davis, R.P. Bagozzi, and P.R. Warshaw, “User acceptance of computer technology: a comparison of two theoretical models,” Management Science, vol. 35, no. 8, pp. 982- 1003, 1989.

[14] I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211, 1991.

[15] V. Venkatesh, M.G. Morris, G.B. Davis, and F.D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, pp. 425-478, 2003.

[16] V. Venkatesh, J.Y.L. Thong, and X. Xu, “Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology,” MIS Quarterly, pp. 157-178, 2012.

[17] S.Y. Park. “An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning,” Educational Technology & Society, vol. 12, no. 3, pp. 150-162, 2009.

[18] P. Legris, J. Ingham, and P. Collerette, “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, vol. 40, no. 3, pp. 191-204, 2003.

[19] H. Nysveen, P.E. Pedersen, and H. Thorbjørnsen, “Intentions to use mobile services: Antecedents and cross-service comparisons,” Journal of the Academy of Marketing Science, vol. 33, no. 3, pp. 330-346, 2005.

[20] L.M. Maruping, B. Hillol, V. Venkatesh, and S.A. Brown, “Going beyond intention Integrating behavioral expectation into the unified theory of acceptance and use of technology,” Journal of the Association for Information Science and Technology, vol. 68, no. 3, pp. 623-637, 2017.

[21] V. Venkatesh, and M.G. Morris, “Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior.” MIS Quarterly, pp. 115-139, 2000.

[22] M.A. Camilleri and A. Camilleri, “The Students’ Perceptions of Digital Game-Based Learning,” In M. Pivec and J. Grundler, 11th European Conference on Games Based Learning (October). Proceedings, University of Applied Sciences, Graz, Austria, pp 56- 62, 2017.

[23] T. Teo, and M. Zhou, “Explaining the intention to use technology among university students: a structural equation modeling approach,” Journal of Computing in Higher Education, vol. 26, no. 2, pp. 124-142, 2014.

[24] T. Doleck, P. Bazelais, and D.J. Lemay, “Examining the antecedents of social networking sites use among CEGEP students,” Education and Information Technologies, vol. 22, no. 5, pp. 2103-2123, 2017.

[25] B. Wu, and X. Chen, “Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model,” Computers in Human Behavior, vol. 67, pp. 221-232, 2017.

[26] C.T. Chang, J. Hajiyev, and C.R. Su, “Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for elearning approach,” Computers & Education, vol. 111, pp. 128-143, 2017.

[27] I. Arpaci, K. Kilicer, and S. Bardakci, “Effects of security and privacy concerns on educational use of cloud services,” Computers in Human Behavior, vol. 45, pp. 93-98,
2015.

[28] A.F. Agudo-Peregrina, Á. Hernández-García, and F.J. Pascual-Miguel, “Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning,” Computers in Human Behavior, vol. 34,
pp. 301-314, 2014.

[29] F. Paraskeva, H. Bouta, and A. Papagianni. “Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice,” Computers & Education, vol. 50, no. 3, pp. 1084-1091, 2008.

[30] D.R. Compeau, and C.A. Higgins, “Computer self-efficacy: Development of a measure and initial test,” MIS Quarterly, pp. 189-211, 1995.

[31] S.A. Nikou, and A.A. Economides, “The impact of paper-based, computer-based and mobile-based self-assessment on students’ science motivation and achievement,” Computers in Human Behavior, vol. 55, pp. 1241-1248, 2016.

[32] L.A. Annetta, J. Minogue, S.Y. Holmes, and M.T. Cheng, “Investigating the impact of video games on high school students’ engagement and learning about genetics,” Computers & Education, vol. 53, no. 1, pp. 74-85, 2009.

[33] E.W.T. Ngai, J. K. L. Poon, and Y.H.C. Chan, “Empirical examination of the adoption of WebCT using TAM,” Computers & Education, vol. 48, no. 2, pp. 250-267, 2007.

[34] T.Teo, and C. Beng Lee, “Explaining the intention to use technology among student teachers: An application of the Theory of Planned Behavior (TPB),” Campus-Wide Information Systems, vol. 27, no. 2, pp. 60-67, 2010.

[35] T. Teo, and C. Beng Lee, C. Sing Chai, and S.L. Wong, “Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM),” Computers & Education, vol. 53, no. 3, pp. 1000-1009, 2009.

[36] J.Y.L. Thong, W. Hong, and K.Y. Tam, “Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences?” International journal of human-computer studies, vol. 57, no. 3, pp. 215-242, 2002.

[37] M.A. Camilleri, and A.C. Camilleri, “Digital learning resources and ubiquitous technologies in education,” Technology, Knowledge and Learning, vol. 22, no. 1, pp. 65- 82, 2017.

[38] D.Y. Lee, and M.R. Lehto, “User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model.” Computers & Education, vol. 61, pp. 193-208, 2013.

[39] T. Teo, and P. Van Schalk, “Understanding technology acceptance in pre-service teachers: A structural-equation modeling approach,” The Asia-Pacific Education Researcher, vol. 18, no. 1, pp. 47-66, 2009.

[40] C. Smarkola, “Technology acceptance predictors among student teachers and experienced classroom teachers,” Journal of Educational Computing Research, vol. 37, no. 1, pp. 65-82, 2007.

[41] M.A. Camilleri, and A.C. Camilleri, “Measuring The Educators’ Behavioural Intention, Perceived Use And Ease Of Use Of Mobile Technologies,” In Wood, G. (Ed) Reconnecting management research with the disciplines: Shaping the research agenda for the social sciences (University of Warwick, September). British Academy of Management, UK, 2017.

[42] M. Turner, B. Kitchenham, P. Brereton, S. Charters, and D. Budgen, “Does the technology acceptance model predict actual use? A systematic literature review,” Information and Software Technology, vol. 52, no. 5, pp. 463-479, 2010.

[43] R.P. Bagozzi, and Y. Youjae, “On the evaluation of structural equation models,” Journal of the Academy of Marketing Science, vol. 16, no. 1, pp.74-94, 1988.

[44] M.A. Camilleri, and A.C. Camilleri, “The Technology Acceptance of Mobile Applications in Education,” In Sánchez, I.A. and Isaias, P. (Eds) 13th International Conference on Mobile Learning (Budapest, 11th April). pp41-48. International Association for Development of the Information Society, 2017.

[45] A. Colbert, N. Yee, and G. George, “The digital workforce and the workplace of the future,” Academy of Management Journal, vol. 59, no. 3, pp. 731-739, 2016.

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Filed under digital games, digital media, Education

Tagged as corporate communication, digital game based learning, digital games, educational apps, educational games, educational technology, mark anthony camilleri, Mark Camilleri, perceived enjoyment, technology, technology acceptance model, theory of planned behavior, University of Malta

February 26, 2018 · 1:25 pm

Tourism Futures: Targeting Customers in the Digital Age

This is an excerpt from: Camilleri’s latest book on Travel Marketing (2018)

How to Cite: Camilleri, M. A. (2018). Market Segmentation, Targeting and Positioning. In Travel Marketing, Tourism Economics and the Airline Product (Chapter 4, pp. 69-83). Springer, Cham, Switzerland.

The advances in technology have enabled many businesses to reach their potential customers by using digital and mobile applications.

Google, Facebook, Ebay and Amazon, among others are dominating digital marketing; and are pushing the entire field of advertising to new levels. The use of personal info, web-browsing, search history, geographic location, apps and eCommerce transactions have gone mainstream. For example, Google has begun using transaction records to prove that its ads are working, and are pushing people to make more online purchases. This allowed the technology giant to determine the effectiveness of its digital ad campaigns and to verify their conversion rates.

All individuals leave a “digital trail” of data as they move about in the virtual and physical worlds. This phenomenon is called, “data exhaust”. Initially, this term that was used to describe how Amazon.com has used predictive analytics as it suggested items to its customers. However, predictive analytics cannot determine when and why individuals may decide to change their habitual behaviours, as the possibility of “one off” events must never be discounted. Yet, a firm with sufficient scarce resources could be in a position to exploit big data and analytics to improve its businesses operations.

For instance, Deloitte Consulting have developed a mobile app that has enabled Delta Airlines’ executives to quickly query their operations. For instance, when users touch an airport on a map, the system brings up additional data at their disposal. Executives could also drill further down to obtain granular information on staffing requirements. and customer service levels, as they identify and predict problems in their airline operations.

Nevertheless, business intelligence and predictive analytics could possibly raise a number of concerns. Many customers may be wary of giving their data to the businesses and their stakeholders. Very often, the technological advances anticipate legislation, and its deployment. These contingent issues could advance economic and privacy concerns that regulators will find themselves hard-pressed to ignore. Some academics argue that the digital market and its manipulation may be pushing the limits of consumer protection law. Evidently, society has built up a set of rules that are aimed to protect personal information. Another contentious issue is figuring out the value of data and its worth in monetary terms. In the past, companies could have struggled to determine the value of their business; including patents, trade secrets and other intellectual property.

Targeted Segmentation through Mobile Devices

The mobile is an effective channel to reach out to many users. Portable devices, including smart phones and tablets are surely increasing the productivities and efficiencies of individuals as well as organisations. This has led to the growth of mobile applications (apps). As a result, the market for advertising on mobile is still escalating at a fast pace. Moreover, there are niche areas as new applications are being developed for many purposes on different mobile platforms.

Recent advances in mobile communication and geo-positioning technologies have presented marketers with a new way how to target consumers. Location-targeted mobile advertising involves the provision of ad messages to mobile data subscribers. This digital technology allows marketers to deliver native ads and coupons that are customised to individual consumers’ tastes, geographic location and the time of day. Given the ubiquity of mobile devices, location-targeted mobile advertising are increasingly offering tremendous marketing benefits.

In addition, many businesses are commonly utilising applications, including browser cookies that track consumers through their mobile devices, as they move out and about. Very often, when internet users leave the sites they visited, the products or services they viewed will be shown to them again in retargeted advertisements, across different websites. Several companies are using browsing session data combined with the consumers’ purchase history to deliver “suitable” items that consumers like. There are also tourism businesses who are personalising their offerings as they collect, classify and use large data volumes on the consumers’ behaviours. As more consumers carry smartphones with them, they may be easily targeted with compelling offers that instantaneously pop-up on their mobile screens.

Furthermore, consumers are continuously using social networks which are indicating their geo-location, as they use mobile apps. This same data can be used to identify where people tend to gather. This information is valuable to brands as they seek to improve their consumer engagement and marketing efforts. Therefore, businesses are using mobile devices and networks to capture important consumer data. For instance, smart phones and tablets interact with networks and convey information on their users’ digital behaviours and physical movements to network providers and ISPs. These devices have become interactive through the proliferation of technologies, including; near-field communication (NFC). Basically, embedded chips in the customers’ mobile phones are exchanging data with the retailers’ items possessing such NFC tags. The latest iPhone, Android and Microsoft smartphones have already incorporated NFC capabilities. The growth of such data-driven, digital technologies is surely adding value to the customer-centric marketing. The latest developments in analytics are enabling businesses to provide a deeper personalisation of content as they use socio-demographic and geo-data that new mobile technologies are capable of gathering.

For example, mobile service companies are partnering with local cinemas, in response to the location-targeted mobile advertising; as cinema-goers may inquire about movie information, and could book tickets, and select their seats through their mobile app. These consumers who are physically situated within a given geographic proximity of the participating cinemas may receive location-targeted mobile ads. The cinemas’ ads will inform prospects what movies they are playing and could explain how to purchase tickets through their smart phone. The consumers may also call the cinemas’ hotlines to get more information from a customer service representative. Besides location-targeted advertising, the mobile companies can also promote movie ticket sales via mobile ads that are targeted to individuals, according to their behaviour (not by location). Therefore, companies may direct their mobile-ad messages to those consumers who had previously responded to previous mobile ads (and to others who had already purchased movie tickets, in the past months). Moreover, the cinema companies can also promote movies via Facebook Messenger Ads if they logged in the companies’ websites, via their Facebook account. Mobile users may also receive instant message ads via pop-up windows whenever they log into the corporate site of their service provider.

It is envisaged that such data points will only increase in the foreseeable future, as the multi-billion dollar advertising monopolies are being built on big data and analytics that are helping businesses personalise immersive ads as they target individual customers. The use of credit card transactions is also complementing geo-targeting and Google Maps, with ads; as the physical purchases are increasingly demanding personalisation, fulfillment and convenience. There may be consumers and employees alike who out of their own volition, are willing to give up their data for value. Therefore, the businesses need to reassure them through concise disclosures on how they will use personal data. They should clarify the purpose of maintaining their consumer data, as they are expected to provide simple user controls to opt in and out of different levels of data sharing. This way, they could establish a trust-worthy relationship with customers and prospects.

Companies are already personalising their shopping experience based on the user situation and history. Tomorrow’s tourism businesses are expected to customise the user experiences of their mobile applications and web interfaces, according to the specific needs of each segment. Big data and analytics capabilities are increasingly allowing businesses to fully leverage their rich data from a range of new digital touchpoints and to turn them into high impact interactions. Those businesses that are able to reorient their marketing and product-development efforts around digital customer segments and behaviours will be in a position to tap into the hyper-growth that mobile, social media and the wearables markets are currently experiencing.

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Tagged as Big Data, digital, digital marketing, digital media, marketing, technology, Tourism, Tourism Futures, Travel, Travel Marketing

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The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games

This is an excerpt from one of my latest empirical papers.

Tourism Futures: Targeting Customers in the Digital Age

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