2.1. Transitions: From xMOOCs, cMOOCs, to Wrapped MOOCs
Scholars argue that one of the reasons for the high dropout rate in MOOCs is a lack of interaction, a key factor influencing learning engagement [
3,
17,
18]. Consequently, the concept of MOOCs has been further classified into xMOOCs and cMOOCs [
19].
Extended MOOCs, commonly known as xMOOCs, typically embrace a more traditional approach to online education [
14]. They emphasize structured content delivery using methods like video lectures, self-assessment quizzes, and other carefully curated learning resources [
20].
In contrast, cMOOCs focus on collaborative interactions among participants rather than a centralized teaching approach. cMOOCs encourage learners to build and share knowledge through online networks, fostering a more decentralized and participatory learning experience [
21,
22]. The shift from xMOOCs to cMOOCs signifies educators’ awareness that the mere provision of instructional videos is insufficient and that education requires more learner-centric interactions.
In the cMOOCs model, the challenge of insufficient engagement persists. In response, a more collaborative and interactive approach has emerged: the integration of MOOCs with a traditional face-to-face course, commonly known as wrapped MOOCs [
23]. In the wrapped-MOOC model, online content and resources from MOOCs are seamlessly blended with in-person instruction [
24]. This approach allows students to both access worldwide instructional videos and participate in teacher-student and student-student interactions [
25]. As emphasized by Jaffer, Govender and Brown [
26], the most valuable aspect of wrapped MOOCs is the face-to-face interactions.
From the above, it can be seen that interactions are important factors influencing the sustained use of MOOCs, and they are also something that MOOC platforms are actively working to strengthen [
10]. However, it is worth noting that what exactly is provided by these interactions has not been clearly defined.
2.2. MOOCs and Technology Acceptance
MOOCs, with their distinct advantages, have experienced swift growth in the education field. Measuring technology acceptance is essential for predicting the success of a new technology, as the potential of even the most cutting-edge and feature-rich technology may remain untapped if it does not achieve broad acceptance among users [
16,
27,
28]. Moreover, considering MOOCs’ challenges in maintaining learner retention, the intention of users to accept these platforms is especially critical.
A wide array of theoretical frameworks exists to unravel the complexities of technology acceptance. These include well-known models like the Technology Acceptance Model (TAM), which underscores factors like perceived ease of use and perceived usefulness [
29]. The Unified Theory of Acceptance and Use of Technology (UTAUT and UTAUT2) delves into aspects such as performance expectancy, effort expectancy, social influence, and facilitating conditions, offering a comprehensive understanding of user engagement with technology [
30,
31]. Additionally, the Innovation Diffusion Theory by Rogers [
32] provides a thorough exploration of the mechanisms through which new technologies and ideas permeate cultures, examining the dynamics of adoption over time and across different social groups. Each of these models contributes significantly to our understanding of the complex interplay of factors that drive users towards or away from adopting new technologies, highlighting the multifaceted nature of technological acceptance and integration.
Among the numerous studies exploring the relationship among contributing factors to technology acceptance, some have reported unexpected findings. For example, Wu and Chen [
14] attempted to integrate the TAM model with the Task Technology Fit (TTF) model. They hypothesized that if MOOCs are perceived as easy to use or can bring about social influence, learners would have a better attitude toward MOOCs. However, the results showed that these two hypotheses were not supported. Al-Rahmi, Yahaya, Alamri, Alyoussef, Al-Rahmi and Kamin [
13] integrated the TAM model with the Innovation Diffusion Theory (IDT). They hypothesized that if MOOCs were perceived as highly compatible, they would be perceived as useful, and if MOOCs had trialability, they would be perceived as easier to use. These two hypotheses were also not supported, neither.
The unexpected findings and the unsupported hypotheses indicate a need for further research in the field of technology acceptance, especially concerning the integration of different theoretical models and their applicability in varied contexts like MOOCs.
2.3. Perceived Usefulness, Perceived Ease of Use, and Technology Acceptance Intention
In the field of technology acceptance, a well-established model is the TAM model by Davis, Bagozzi and Warshaw [
29]. The TAM model indicates that the main factors influencing an individual’s attitude and intention to accept a technology are perceived usefulness and perceived ease of use.
Perceived usefulness is defined as the degree to which an individual believes that using a particular system would enhance his or her job performance [
29]. According to previous studies, perceived usefulness has a positive effect on technology acceptance intention [
33,
34,
35,
36].
Perceived ease of use is defined as the degree to which an individual believes that using a particular system would be free of physical and mental effort [
29], which is similar to effort expectancy in the unified theory of acceptance and use of technology (UTAUT) framework [
31]. Results from the extant literature indicate that perceived ease of use was a statistically significant predictor of intention to use new technologies, such as the Internet and educational games [
35].
There is a correlation between PEoU and PU because Davis, Bagozzi and Warshaw [
29] indicates that PEoU should be a contributing element to PU. In other words, individuals are inclined to believe that a technology is useful if they perceive it as easy to use. Therefore, we established the first hypothesis (H1):
H1. The perceived ease of use (PEoU) of MOOCs positively influences the perceived usefulness (PU) of MOOCs.
2.4. Academic Support in MOOC Learning
Academic support, also named instructional support, refers to “instructional guidance to learning, which involves answering students’ questions, correcting their misunderstandings, providing clear instruction, relevant resources, and constructive feedback on their assignments and performance” [
37]. Academics are aware of the importance of academic support in online education and advocate to ensure its provision [
37]. In the xMOOCs model, sufficient academic support can hardly be guaranteed.
Firstly, to maintain user attention, instructional videos on MOOC platforms are often kept relatively short, typically ranging from 5 to 17 min [
38]. This feature, accordingly, limits the academic depth of MOOC learning resources.
Secondly, on MOOC platforms, teachers and students do not physically appear simultaneously, making real-time interaction impossible [
39]. Although some MOOC platforms may include interactive channels such as discussion forums and scheduled Q&A sessions, the opportunities for teachers to provide feedback are limited [
3]. Previous studies have also indicated that certain posts in MOOC discussion forums require an urgent response, but instructors find it challenging to attend to such situations [
9]. Therefore, some researchers have even attempted to establish help-seeking mechanisms in MOOCs [
10]. These efforts demonstrate that academic support on MOOC platforms is not always sufficient, particularly concerning learning Q&A and learning feedback.
Moreover, due to technological and financial constraints, MOOC platforms are not able to provide personalized learning materials to learners. Most MOOC platforms offer one-size-fits-all content to all learners, making it difficult to provide sufficient support for everyone [
2,
40]. Nowadays, researchers are attempting to address the lack of personalized learning by incorporating artificial intelligence (AI) and chatbots into MOOC platforms [
41,
42,
43,
44]. These efforts further demonstrate that simply presenting short videos on MOOC platforms is insufficient.
As the content on MOOC platforms may lack depth and flexibility, the academic support provided by teachers and peers becomes crucial. Students require more detailed explanations from teachers to help them better grasp knowledge [
45,
46], as well as feedback from both teachers and peers tailored to their learning [
47]. We can hypothesize that if the design of a MOOC platform allows teachers and peers to offer enhanced academic support to students, the MOOC platform is more likely to be accepted by students. This hypothesis is also applicable to learning English as a foreign language on MOOC platforms. Therefore, we hypothesized that academic support positively influences EFL learners’ behavioral intention towards MOOC platforms.
As stated in the
Section 1, in our pilot study, the survey items intended to measure behavioral intention did not pass reliability and validity tests, leading to their removal. Consequently, we did not formulate a hypothesis regarding the impact of academic support on the behavioral intention of MOOC platforms. Instead, we focused on its influence on perceived usefulness and perceived ease of use of MOOC platforms:
H2-a. Academic support (AS) positively influences the perceived usefulness (PU) of MOOCs.
H2-b. Academic support (AS) positively influences the perceived ease of use (PEoU) of MOOCs.
2.5. Emotional Support in MOOC Learning
Emotions play a crucial role in students’ learning, as they can either hinder or inspire the learning process [
46,
48]. Emotional support, in general, involves providing empathy, concern, affection, love, trust, acceptance, intimacy, encouragement, or caring [
49]. In the context of using MOOCs for learning, emotional support primarily comprises encouragement that convinces students of the usefulness of MOOCs and their capability to master the relevant courses, ultimately leading to a stronger sense of self-efficacy. When students feel isolated in the online environment, the providence of emotional support can also alleviate the sense of loneliness.
In research related to MOOCs, emotional isolation is a frequently mentioned term. Vilkova and Shcheglova [
10] state that MOOC platforms provide a self-paced, open-ended, and non-linear learning environment, which can help cultivate students’ learning autonomy. However, this also requires students to take responsibility for their own learning process. In this process, students are prone to developing feelings of emotional isolation, making it easier for them to disengage from the course [
10,
18,
50].
Although many studies suggest that learners can reduce emotional isolation through the discussion forum [
47], relying solely on discussion forums may not be sufficient. Vilkova and Shcheglova [
10] emphasized that despite the widely accepted importance of interactions and social engagement, “a MOOC environment does not allow participants to interact easily with other learners and instructors”. This significantly restricts students’ ability to receive emotional support. Additionally, some MOOC platforms send emails to students when there is new information in the discussion forum, but certain students may post meaningless questions. This can lead to students receiving a large number of spamming emails, further diminishing their trust in the MOOC platform and making them hesitant to participate in the discussion forum.
Discussion forums may also fail to provide emotional support for certain types of learners. Researchers noted that low-achieving students tend not to engage in peer interactions or discussions but prefer learning from their peers’ discussions [
18]. Based on the Felder–Silverman Learning Style Model (FSLSM), researchers highlight that learners have different types, with some prefer learning through participation in discussion forums (active learners), while some prefer processing information internally, indicating a preference for observing information generated by others (reflective learners) [
40,
51]. If these students need interaction with teachers and peers on discussion forums for emotional support, not getting enough of it could lead to disengagement or even dropout of MOOC courses.
Offering emotional support through alternative channels, specifically excluding discussion forums, is possible. In instructional videos, teachers can consciously incorporate eye contact with potential learners, increase the use of praise in classroom language, and use encouraging tones [
27]. The MOOC platforms can incorporate game elements such as points, badges, leaderboards, sound effects, etc., to make students feel emotionally cared for [
36,
52]. The MOOC platform can also generate learners’ progress reports, enabling learners to share them on their social networking sites (e.g., Twitter, Facebook, WeChat) and receive emotional support through peers’ comments and likes [
53].
Researchers argue that typical xMOOC models primarily focus on didactic education, emphasizing information delivery [
22]. When students perceive less emotional support, negative emotions may arise, such as frustration, confusion, boredom, and emotional isolation [
54]. These emotions experienced by online learners may hinder the learning process and fail to provide sufficient intention or motivation for students to persist [
55]. Building on this literature, we propose the following two hypotheses:
H3-a. Emotional support (ES) positively influences the perceived usefulness (PU) of MOOCs.
H3-b. Emotional support (ES) positively influences the perceived ease of use (PEoU) of MOOCs.
Some research has implied that high perceptions of academic quality positively influence the PU of online education. To be specific, Alraimi, Zo and Ciganek [
56] stated that academic support influences the online learning outcomes of students. Accordingly, we establish the fourth hypothesis (H4):
H4. Academic support (AS) positively influences emotional support (ES) provided by MOOCs.
2.6. Platform Reputation and Technology Acceptance
The role of reputation has been highlighted in different fields [
56]. Notable platforms like Coursera and edX offer high-quality courses by partnering with highly reputable institutions and universities from different countries [
56]. The reputation of an institution of higher education is a subjective reflection of the institution’s quality, influence, and trustworthiness [
57]. Reputation is a valuable and intangible asset (Tella et al., 2021), which has a significant influence on an individual’s decision-making process when selecting institutions or MOOC platforms [
57,
58]. Researchers have found a significant and positive impact of the perceived reputation of MOOCs on users’ acceptance intention [
14,
56].
Researchers also indicate that perceived usefulness and perceived ease of use are significantly and positively influenced by platform reputation [
14,
59]. MOOC platforms with a high reputation usually have more abundant funds and development teams, enabling their MOOC platforms to achieve better development in educational attributes and technological operational convenience. We can also hypothesize that if a MOOC platform can provide better academic and emotional support, its platform reputation will also be enhanced. Therefore, we propose the following hypotheses:
H5-a. In MOOC learning, platform reputation (PR) positively influences academic support (AS).
H5-b. In MOOC learning, platform reputation (PR) positively influences emotional support (ES).
H5-c. In MOOC learning, platform reputation (PR) positively influences perceived usefulness (PU).
H5-d. In MOOC learning, platform reputation (PR) positively influences perceived ease of use (PEoU).
The theoretical framework and hypotheses are depicted in
Figure 1.