Attitudes of EFL Learners to the Implementation of the Area9 Lyceum Online Platform Based on the UTAUT Model

Abstract

The advancement of technology has led to the creation of numerous platforms that could potentially be used for remote education. For example, the recent development of the English Diploma Programme at a top university in the Kingdom of Saudi Arabia (KSA) deploys a new platform known as Area9 Lyceum (Area9). Because the English Diploma Programme is a recent development, and especially given its use of a new platform, this proposed research will investigate learners’ attitudes to and acceptance of using the platform. Furthermore, it will look at how other universities could benefit from this experience to develop their own English as a Foreign Language (EFL) programmes along technological lines, specifically by deploying a survey tool based on the unified theory of acceptance and use of technology (UTAUT). The results reflect the positive attitude of the participants. Recommendations can be drawn from this study to help persuade stakeholders in higher education to adopt such platforms in the teaching of EFL or English as a Second Language (ESL).

1. Introduction

One of the most recent developments in language teaching is the use of adapted learning, which is identified as a personalised approach to teaching and learning. In personalised learning, learners are at the centre of the teaching and learning process, as clarified in most of the literature [1]. This happens when learners are given a high degree of responsibility for their own learning. Adapted learning also helps to shape learning provision. Furthermore, Prain [2] noted that personalised learning can help to improve students’ engagement and attainment. Additionally, the use of interactive technology in the instructional process can be helpful. Throughout the literature, it may be observed that many interactive learning environments provide on-demand assistance. The aim of deploying these environments is to positively enhance learning [3].

In the current paper, a personalised adapted environment in the form of an interactive platform is examined based on the unified theory of acceptance and use of technology (UTAUT). This specific theoretical framework is used to gain a better understanding of the participants’ levels and types of acceptance regarding this adapted online platform. In the specific research context, the use of ALP generative artificial intelligence (AI) is rather limited and only made available in large institutions. Consequently, there is very little examination of the use of such technology in the literature. The most common study of educational technology, especially in relation to EFL education, concerns the use of learning management systems (for example, [4,5]) and social media (for example, [6,7]).

1.1. Research Gap

In order to fill the gap identified in the research, a platform was included in this study that has not previously been implemented on degree programmes in Saudi universities. Specifically, it was used to deliver English diploma courses at one Saudi university.

1.2. Research Questions

On this basis, the current study will attempt to answer the following research questions:

• Why do EFL learners use an interactive platform for learning on an English diploma course?
• How do EFL learners perceive the implementation of an interactive platform to be useful to them for learning English on a diploma course?

2. Literature Review

2.1. Use of Adapted and Interactive Platforms in Teaching and Learning

In English language learning, the use of adapted learning has increased [8] and is being used to offer individualised learning. In a study conducted by Wang and Liao [9], adapted learning was utilised to teach an English as a second language (ESL) course via an e-learning system. The above study used a technique called data mining (an artificial neural network) to explore the learning performance of various students. The system was set to consider grammar, vocabulary, and reading. In an experimental approach, the results showed more development in the performance of the experimental group as compared to the control group who used the regular e-learning approach.

In another study, conducted by Sfenrianto et al. [10], the researchers proposed an adapted learning system at a knowledge level in an e-learning environment. The proposed system personalised materials based on the proficiency of the participating English language learners. Accordingly, a pre-test was conducted to determine the learners’ level, through which the learners were categorised as having high, intermediate, or low English language ability. The system then provided materials based on the learners’ needs, with 90 learners with different levels of English language proficiency participating in the study. The results indicated that the proficiency of all the participants was enhanced, thereby demonstrating the system’s effectiveness.

The option of using adapted learning in an e-learning environment was explained early in 2003. The suggested model was designed to keep relevant adapted metadata separate from the description of the course itself, thereby helping to enhance course maintenance [11]. Looking into the inclusion of adapted online platforms in an EFL context, more specifically in contexts like the one under study, research was conducted in Oman in 2022 to investigate the implementation of an online learning platform. Thus, the perceptions of a group of Omani students were explored at the English Language Centre of the University of Sciences and Applied Technology, Salalah campus. In particular, the students’ perceptions of using new online learning platforms were studied, namely, the platforms Moodle and Microsoft Teams. From the survey results, it was ascertained that the participants had positive perceptions of using the selected platforms, thereby recommending their use in EFL classes [12].

In another study, conducted by Alakrash et al. [13], the possible use of an online platform in EFL classes was investigated, specifically in the Arab world. Alakrash therefore studied EFL students’ use of digital platforms for learning purposes, as well as their attitudes and digital literacy. In addition, the above study examined the correlation between students’ digital literacy, attitudes toward, and use of digital platforms for learning purposes. A quantitative approach was adopted, surveying 80 EFL learners. The resulting data showed that the students had strongly positive attitudes, moderate levels of digital literacy, and moderate levels of digital platform usage for learning purposes.

It is evident from these studies that the use of online platforms is helpful for offering better learning opportunities in EFL. However, few researchers have examined such implementation to date, especially in the Arab world. This is precisely because of the limited uptake of these platforms in the Arab EFL context. Consequently, in order to promote the technology, it is essential to gather students’ opinions following their experience of implementing such a personalised tool.

2.2. Unified Theory of Acceptance and Use of Technology (UTAUT)

According to Momani [14], UTAUT is one of the most intensive and well-developed models used for testing the acceptance of technology adoption. Momani further notes that this model is robust and trusted for use with different types of technology. Furthermore, the model is not overly complicated, as it includes a limited number of constructs and moderating variables, thereby facilitating an examination of the acceptance of technology integration.

Based on the above description, this study applies UTAUT [15] to create a model built on four variables, which reflect the behavioural intention to use technology [16]. Each variable measures different perspectives of the acceptance of technology use. Šumak et al. [17] define these variables as follows: performance expectancy (PE) is “the degree to which an individual believes that using the system will help him or her achieve gains in job performance”; effort expectancy (EE) is “the degree of ease associated with the use of a system”; social influence (SI) is “the degree to which an individual perceives that important people believe they should use the new system”; and facilitating conditions (FC) are “the degree to which an individual believes that an organisational and technical infrastructure exists to support the use of a system”. Use of this theoretical framework is common among studies that investigate participants’ perceptions of using different kinds of technology for teaching and learning. In a systematic review investigating studies on the impact of technology use around the world from the perspective of UTAUT, the resulting data effectively predicted technology adoption in higher education settings [18].

Nevertheless, UTAUT is a model that has not been tested extensively on EFL courses, although one recent study in Saudi Arabia examined the continuity of English teachers’ use of online education in elementary schools in the Kingdom [19]. Through a multiple regression analysis of the four factors mentioned above, the results revealed that performance expectancy, social influence, and facilitating conditions can predict teachers’ use of online learning.

3. Methodology

In this section, descriptions of the selected platform and Diploma Programme are presented, with the study design explained.

3.1. The Area9 Platform

According to its website, the Area9 platform deploys adapted learning [20] and is represented as:

• An online delivery method that automatically adjusts to the needs of each learner.
• A tool that recreates at scale the optimal teaching approach of a one-on-one personal tutor.
• The use of proven data analytics and intelligent technologies to adjust in real-time and deliver an optimal experience.

Furthermore, the website indicates the following benefits of applying an adapted learning approach:

• Compared to traditional training:

  ◦

  It cuts training time in half.

  ◦

  It leads to higher proficiency.

  ◦

  No one is left behind.

  ◦

  It eliminates boredom and frustration.

  ◦

  It improves business outcomes.

  ◦

  It reveals and addresses unconscious incompetence.

  ◦

  It promotes retention and reinforcement.

In addition, the website presents the following content, as illustrated in Figure 1.

Area 9 facilitates learning by eliciting learners’ responses to questions related to the registered course. This interactive platform identifies learners’ weaknesses in the subject and directs them toward relevant resources based on their responses to the interaction. Following this diagnostic assessment, the system will build personalized learning material for each student. In other words, learners interact with the system to build up their personalized resources.

As a complement to the platform, the department provides weekly online lectures using slides generated by the system tailored to common students’ needs identified in the primary diagnostic assessment. Importantly, the students are required to independently use the platform as part of their course. The platform has been successfully integrated into all Diploma courses, from Level One to graduation, covering a wide range of subjects from language skills to theoretical linguistics.

3.2. Study Design

For the current research, a case study design involving a quantitative approach was implemented, using a survey adapted from Venkatesh et al. [15] based on UTAUT. However, some changes were made to the original survey items to suit the research context. For example, in Item 1 of the questionnaire on the topic of performance expectancy, the word ‘job’ was changed to ‘course’, as follows: ‘I would find the system useful on my course’. Meanwhile, a four-point Likert scale was adopted to ensure clearly defined answers from the participants.

The survey (Appendix A) was distributed electronically via Google Forms to facilitate data collection. The questionnaire was also translated into Arabic to ensure the learners’ understanding, and a translation expert was designated to check the translation. The validity of the content was determined to check the suitability of the tool to answer the research questions, whereupon two experts in the field were asked to give their opinions.

Reliability refers to the degree of consistency or stability in the results of a study if it is conducted with the same respondents on repeated occasions. Reliability is therefore a very important aspect of selecting a questionnaire instrument. In order to evaluate the reliability of the questionnaire administered in this current study, the Cronbach’s alpha values were calculated for each dimension. Cronbach’s alpha (α), developed by educational psychologist Lee Cronbach in 1951, is the most common estimate of reliability. Based on the intercorrelations of the observed indicator variables, Cronbach’s alpha produces values of between 0 and 1, with an acceptable range of 0.7–1.

The above table demonstrates that the research data passed the reliability test, because the Cronbach’s alpha value for the questionnaire was 0.864 (greater than 0.7), and all the Cronbach’s alpha values exceeded the acceptable minimum.

Regarding the research participants, comprehensive sampling was carried out, as the survey was distributed to all male and female Level 4 learners in the English Diploma Programme. This sample was selected because the learners had already used the platform for three terms. Therefore, they would have had sufficient experience of it to be able to give their opinions. Moreover, they had one more term remaining before they graduated.

The English Diploma Programme is described on the Saudi Electronic University website as an English Language Diploma on the Internet, accessible to male and female students all over the Kingdom as of Fall 2021. The aim of this Programme is “to prepare learners interested in English studies to become highly competent in English language practice” [21]. Its overarching purpose is to equip learners “with the various skills and knowledge required in the job market to have a successful career…” (ibid.). Twenty different English language courses are available within the Diploma Programme, consisting of “translation, interpreting, and research and presentation skills” (ibid.). The course designers are highlighted as “experienced faculty members whose research and scientific interests lie at the intersection of those academic fields” (ibid.). Each learner is expected to meet a number of milestones over the course of the Programme.

From an ethical perspective, every effort was made to hide the participants’ identities in the study in consideration of the need for participant anonymity and confidentiality. Moreover, participation was purely voluntary and did not affect the participants’ grades. Prior to their participation, the respondents were asked to sign informed consent forms. Finally, all participants were informed of their right to withdraw from the study at any time.

The researcher contacted the head of the English department from the College of Science and Theoretical Studies at the Saudi Electronic University where the platform was being implemented. This was to verify that the study could be conducted. Approval was granted orally. However, the researcher subsequently needed to apply to the Deanship of Scientific Research at the Saudi Electronic University for formal approval to conduct the study by gaining ethical approval from the researcher’s institution.

3.3. Results

This subsection presents a statistical analysis of the questionnaire responses. The research sample comprised 59 participants of different ages and at different university levels. The aim of this study was to explore the attitudes of EFL learners to the implementation of the Area9 platform based on the UTAUT Model. Thus, the statistical data analysis is reported as follows: the main characteristics of the sample are first presented to describe the participants’ personal information (i.e., age, gender, reason for undertaking the English Diploma course, and any training in the use of the Area9 platform for the English Diploma). This is followed by an analysis of reliability, and finally, the results of the hypothesis testing are set out.

Thus, the main characteristics of the sample are presented below, with tables that include the participants’ personal information (i.e., age, gender, reason for undertaking the English Diploma, and any training in the use of the Area9 platform for the English Diploma).

As illustrated in

Table 1. Table of frequency for age.

	Frequency	Percentage
20–25 years	13	22.0
25–30 years	14	23.7
30–35 years	15	25.4
35 years or over	17	28.8
Total	59	100.0

and

Table 2. Table of frequency for gender.

	Frequency	Percentage
Male	12	20.3
Female	47	79.7
Total	59	100.0

, the English Diploma is a mixed-gender programme attended by students of different ages. Therefore, the educational content generated should be suitable for use across these differences.

Table 3. Table of frequency for the reasons for undertaking the Diploma.

	Frequency	Percentage
To help you get a promotion at work	2	3.4
To help you apply for jobs	12	20.3
To help you in your education	11	18.6
To improve your English abilities	34	57.6
Total	59	100.0

and

Table 4. Any previous training in the use of the Area9 platform for the English Diploma.

	Frequency	Percentage
No	15	25.4
Yes	44	74.6
Total	59	100.0

present the participants’ responses relating to research question 1. In their responses to the question ‘Why are you taking this English Diploma?’, as illustrated in Table 3, the participants mostly indicated that they were undertaking the Diploma to improve their English language ability. Therefore, AI should generate material that is suitable to meet this need.

In Table 4, it may be noted that most of the participants were trained prior to starting the online course, this being an important factor in the success of technology implementation.

Table 5. The means and median standard deviations for the dimensions of the questionnaire.

No.	Items	Mean	Std. Deviation	Median	%	Ranking	Response
2	Effort expectancy	3.17	0.62	3.00	79.3%	1	Agree
1	Performance expectancy	2.90	0.62	3.00	72.6%	2	Agree
4	Facilitating conditions	2.85	0.42	3.00	71.3%	3	Agree
3	Social influence	2.80	0.58	3.00	69.9%	4	Agree
	Total	2.93	0.45	3.00	73.3%		Agree

and

Table 6. The means and median standard deviations for the questionnaire items.

No.	Items	Mean	Std. Deviation	Median	%	Ranking	Response
4	If I use the system, I will increase my chances of achieving high grades	3.14	0.80	3.00	78.4%	1	Agree
1	The system is useful on my course	2.92	0.77	3.00	72.9%	2	Agree
3	Using the system increases my productivity	2.81	0.75	3.00	70.3%	3	Agree
2	Using the system enables me to accomplish tasks more quickly	2.75	0.84	3.00	68.6%	4	Agree
	Performance expectancy	2.90	0.62	3.00	72.6%		Agree
8	Learning to operate the system is easy for me	3.24	0.73	3.00	80.9%	1	Agree
6	It is easy for me to become skilful in using the system	3.22	0.72	3.00	80.5%	2	Agree
7	I find the system easy to use	3.15	0.71	3.00	78.8%	3	Agree
5	My interaction with the system is clear and easy to understand	3.08	0.73	3.00	77.1%	4	Agree
	Effort expectancy	3.17	0.62	3.00	79.3%		Agree
12	In general, the University has supported use of the system	3.14	0.75	3.00	78.4%	1	Agree
11	The teacher has been helpful with using the system	2.85	0.83	3.00	71.2%	2	Agree
10	People who are important to me think that I should use the system	2.63	0.83	3.00	65.7%	3	Agree
9	People who influence my behaviour think that I should use the system	2.58	0.79	3.00	64.4%	4	Agree
	Social influence	2.80	0.58	3.00	69.9%		Agree
13	I have the necessary resources to use the system	3.27	0.64	3.00	81.8%	1	Agree
14	I have the necessary knowledge to use the system	3.22	0.65	3.00	80.5%	2	Agree
16	A specific person (or group) is available for assistance with system difficulties	2.68	0.99	3.00	66.9%	3	Agree
15	The system is incompatible with other systems that I use.	2.24	0.92	2.00	55.9%	4	Agree
	Facilitating conditions	2.85	0.42	3.00	71.3%		Agree
	Total	2.93	0.45	3.00	73.3%		Agree

present the participants’ responses relating to research question 2:

It is clear from the data in the above Table 5 and Figure 2 that most of the EFL learners accepted the use of an interactive platform for learning in an English Diploma course (73.3%). The highest level of agreement was for effort expectancy (79.3%), the second highest was for performance expectancy (72.6%), and the third highest was for facilitating conditions (71.3%). Meanwhile, the lowest level of agreement was indicated for social influence (69.9%).

In relation to specific survey items, the following results were also obtained:

It is clear from the data in the above table that the students were in agreement over the interactivity and benefits of implementing the new Programme, with a percentage ranging between 55.9% and 81.8%. The statement ‘I have the necessary resources to use the system’ received the highest agreement response (81.8%), closely followed by ‘Learning to operate the system is easy for me’ (80.9%), ‘It is easy for me to become skilful in using the system’ (80.5%), and ‘I have the necessary knowledge to use the system’ (80.5%). High agreement was also found in response to the statements, ‘In general, the University has supported use of the system’ (78.4%), ‘If I use the system, I will increase my chances of achieving high grades’ (78.4%), and ‘The system is useful on my course’ (72.9%). Meanwhile, a lower level of agreement was found in response to the statements: ‘Using the system enables me to accomplish tasks more quickly’ (68.6%), ‘People who are important to me think that I should use the system’ (65.7%), ‘A specific person (or group) is available for assistance with system difficulties’ (66.9%), and ‘People who influence my behaviour think that I should use the system’ (64.4%). Finally, the lowest level of agreement was indicated in response to the statement, ‘The system is incompatible with other systems that I use’ (55.9%). In the next section, these results are discussed in relation to the theoretical underpinnings of the study and the existing literature.

4. Discussion

It is evident from the results that the participants had a positive experience of dealing with the English course created by the AI system. In response to the first research question, ‘Why do EFL learners use an interactive platform for learning on an English diploma course?’, the first part of the survey showed the participants’ reflections on the system, as they had primarily enrolled in the Programme to develop their English language skills. Meanwhile, they had been trained in using the system in other courses. The students’ motivation to improve their English language skills in such a manner may have been because AI enables a more adaptive kind of learning, which suits each student’s educational needs and level [22]. Furthermore, learners have greater autonomy because they can engage with such a course at a time and place that suits them [23].

For the second research question, ‘How do EFL learners perceive the implementation of an interactive platform to be useful to them for learning English on a diploma course?’ the different variables of the survey driven by UTAUT showed a high level of agreement among the participants. Regarding performance expectancy related to developing learners’ educational levels, the learners found the system helpful for English language practice. Similarly, a study conducted in India by Jaiswal and Arun [24] confirmed that AI adaptive learning can cause a positive shift in education. It changes conventional teaching methods to innovative education, thereby enhancing learners’ educational experience. Through in-depth interviews with four senior managers and four subject matter experts, all working with AI-related technologies, the participants confirmed that by developing AI-based applications on the basis of grounded theory, they found that personalised earning and adaptive assessments supported teachers and helped students. More specifically, in developing countries, AI may have the potential to enhance the learning experience.

The participants strongly agreed with the second variable related to effort expectancy and the ease of using the system. Artificial intelligence tools are known to facilitate the learning process through their ease of use. This was supported by Wang et al. [25], who mentioned that AI technologies are promoted in the educational sector due to this feature, as it was noted that AI increased learning performance in a school setting. In an exploration of teachers’ intentions and concerns about using AI, a total of 311 teachers participated in a survey that examined anxiety (AN), self-efficacy (SE), attitude towards AI (ATU), perceived ease of use (PEU), and perceived usefulness (PU); the results demonstrated that the ease of using an AI application motivated the participants to adopt the tool.

Regarding social influence, the participants indicated that people with authority at their institution had encouraged them to use the system, such as the teachers and administration. This is very important, because learners would thereby gain a sense of responsibility and build self-confidence as influential participants in the educational process. Teachers would consequently adopt the use of AI to provide further assistance in teaching; the teacher’s role is vital in designing, visualising, and orchestrating AI systems for teaching and learning. Moreover, AI would help to develop computational presentations built on meaningful data and inferred from pedagogy and learner models [26].

The facilitating conditions represent the necessary facilities to use an AI system easily, like the availability of technological tools and resources with IT support to help overcome technical issues. The participants strongly agreed with this variable. The provision of technological support is essential, especially if tests are taken electronically. Saudi Electronic University is a pioneering university that uses technology for blended and online courses, providing the necessary support for its beneficiaries in KSA. Hughes [27] indicates that this will ensure the learners’ readiness and their willingness or ability to make the best use of the system, which would help meet the course objectives.

5. Conclusions

The inclusion of technology in language teaching has been widely examined in the literature, either by looking at its impact or at perceptions of its beneficiaries. However, very few of these technologies are adaptive to the specific needs of language learners. With recent developments in the field of AI, this has become possible, offering learners educational programmes that target their specific weaknesses. It is likely to be highly impactful, especially in the Arab EFL context, where the concept of adaptive learning is novel.

Throughout the results, it was evident that EFL learners at the Saudi Electronic University had a positive experience of using the adaptive learning platform, Area9. This finding should influence stakeholders and policymakers at the Ministry of Education to develop AI for use in teaching foreign languages, leading to a more personalised learning experience. Thus, it is anticipated to enhance learning quality because the content introduced would be generated according to learners’ needs.