Abstract
While Massive Online Open Courses (MOOCs) have seen a surge in enrollments in higher education around the world especially during the Covid-19 pandemic, it is unclear if learners from the economically disadvantaged regions (EDR) are also able to capitalize on them. Specifically, challenges related to using MOOCs in these regions have been reported in the literature. Thus, the objective of this paper is to address the pedagogical challenge by investigating approaches to leverage MOOCs for learners in EDR. Drawing from the ARCS (i.e. Attention, Relevance, Confidence and Satisfaction) model, we proposed an embedded MOOCs approach where bite-sized MOOCs segments are integrated into in-class lectures under the guidance of the instructors. The effectiveness of the embedded MOOCs approach was evaluated and compared with other instructional methods. Results from randomized experiments showed that the embedded MOOCs approach had higher evaluations in terms of attention, relevance and satisfaction than face-to-face learning approach. In addition, the embedded MOOCs approach outperformed asynchronously blended MOOCs in enhancing students’ relevance perception. Regression analysis further revealed that attention, confidence, and satisfaction perceptions were positively associated with students’ intention to adopt the embedded MOOCs approach in their future studies. The findings shed light on how to utilize MOOCs and re-use content in MOOCs for global benefits and enable new pedagogical developments. The findings also underscore the importance of local social support and offline interactions to support the online learning materials.
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1 Introduction
During the COVID-19 pandemic, universities worldwide have to switch to online delivery of lessons. As a result, various Internet teaching tools and online education resources are widely employed, including Massive Online Open Courses (MOOCs) (Chakraborty et al., 2021; Duan, 2021; Pinto et al., 2022). In particular, MOOCs provide free quality course content from elite universities worldwide and allow global higher education learners to participate regardless of age, background or geographic location (Deng et al., 2019). For learners in higher education from economically disadvantaged regions (EDR) whereby quality course resources are lacking, MOOCs promise to bridge the global knowledge divide to benefit learners in these regions (Ma & Lee, 2019b). Indeed, worldwide enrollment for MOOCs has surged during the pandemic and it is likely that MOOCs will continue to play important roles in higher education after the pandemic (Broom, 2020). However, it is unclear how learners in EDR can leverage MOOCs as their learning challenges and information needs are unique in terms of technological, social, and financial problems (Adnan, 2020; Lambert, 2020).
Notably, learners in higher education from these regions encounter numerous challenges when using MOOCs. First, accessing content from MOOCs outside the classroom can be difficult due to inadequate infrastructure and network services (Barclay & Logan, 2013). More than 3.7 billion people in the world still have no Internet access in their homes and most of them are in less affluent countries (Broom, 2020). Learners in EDR may also lack the required computing skills or may not be able to afford the computing devices (Ma & Lee, 2019b). Second, the learners in these regions are likely to have poorer levels of proficiency in the English language compared to the more affluent areas (Ma & Lee, 2019a). The content of MOOCs is primarily in English, which means that learners from EDR whose native languages are non-English will face challenges in understanding the content unless the course content is translated. Third, the learning cultures in MOOCs are rooted in American and European learning cultures and contexts, which may create a “socio-culturally exclusionary” environment for learners who are from different social and cultural contexts (Lambert, 2020). In particular, a report by UNESCO advocated that the social and economic contexts should be taken into consideration when promoting MOOCs in developing countries, and further calls for the adaption and localization of international MOOCs to cater to local learners (Patru & Balaji, 2016). It is not well-documented in the literature how learners in EDR should adapt and navigate these challenges as the majority of MOOCs studies are based on western-centric learning cultures typically conducted in developed countries (Zhu et al., 2022). Hence, our understanding of the challenges of MOOCs use focusing on learners in EDR within Asia is still limited (Bulger et al., 2015; Deng et al., 2019). Taken together, it is imperative to examine approaches to integrate MOOCs effectively to cater to learners in EDR.
The present study attempts to propose a new approach to integrate MOOCs into higher education in EDR. The blended MOOCs approach discussed in prior studies typically requires learners to view MOOC videos at home and then participate in face-to-face in-class discussions (Rasheed et al., 2020). While this has been effective, it is challenging for learners in EDR as discussed in the earlier section. Thus, we proposed an “embedded MOOCs” approach in this study which is defined as integrating multiple selective bite-size MOOCs segments into the traditional face-to-face lessons and allowing students to consume the content during class under the guidance of the instructors. Two main benefits of this approach are to be noted. First, the MOOCs content can be “localized” to suit the specific backgrounds and needs of local students (Lambert, 2020). Generally, short slices of content help students to perform better in retaining information compared with giving students lengthy content at once (Giurgiu, 2017). Second, there are impacts on pedagogical knowledge sharing. Learners in EDR can now leverage quality educational resources shared on this platform and tap into the teaching expertise of the world’s best universities. The public accessibility of MOOCs means that instructors all over the world can access courses of other instructors and benefit from their ideas and pedagogical knowledge. The objective of the present study is to investigate and compare whether the embedded MOOCs approach is effective in motivating and engaging learners in EDR. To achieve this objective, this study utilizes a randomized experiment to compare the three types of approaches: the embedded MOOCs, the asynchronously blended MOOCs, and the traditional face-to-face classroom. The ARCS motivational design model is applied to evaluate the motivational appeals of the different learning approaches in terms of attention, relevance, confidence, and satisfaction perceptions (Keller, 1999; Keller & Suzuki, 2004).
2 Literature review
2.1 Blended MOOCs
Despite the wide array of MOOCs studies in the literature, there is still no known effective approach to blending MOOCs into traditional classrooms. A widely used approach is to assign students to consume MOOCs contents outside (before or after) the class to complement in-class lectures (Israel, 2015; Rasheed et al., 2020). This is referred to as asynchronously blended MOOCs as the section using MOOCs and in-class lecture are conducted asynchronously. The aim of using MOOCs is to complement the in-person class which is conducted by a local instructor. As students can learn according to their own pace, the advantages of such an blended MOOCs approach include flexibility, convenience in accessing learning materials, and autonomy (Deschacht & Goeman, 2015; Ocak, 2011). The related studies of blended MOOCs are summarized in Table 1.
Despite the promising benefits of blended MOOCs, it has been revealed that the asynchronous approach of blending MOOCs into in-person courses has not been successful to enhancing students’ satisfaction and learning motivations (Bruff et al., 2013; Griffiths et al., 2015; Onah et al., 2022). There are several reasons. First, the lack of immediate feedback and interactions in MOOCs led to a negative learning experience. This is because online learning has been criticized for the absence of face-to-face interaction, lack of instant support, and feelings of isolation (So & Brush, 2008; Yousef et al., 2015). Second, the learning outcomes in MOOCs are not integrated into students’ final course assessments. Local instructors usually do not have the authority to monitor and assess students’ online performance in the MOOCs platforms (Griffiths et al., 2015). Without recognition, students are likely to be less serious in their learning and adopt superficial learning strategies such as fast-forwarding or skipping when watching the online course videos. In addition, as the blended MOOCs approach requires more time to prepare the class, students may perceive this as an extra workload requiring extra effort and resulting in dissatisfaction (Deng et al., 2019). The lack of motivation further negatively affects learning satisfaction and performance (López-Pérez et al., 2011). Indeed for students who lack self-regulation, the online component of blended learning has imposed various challenges (Rasheed et al., 2020).
Particularly for learners in EDR, there are obstacles to accessing MOOCs outside the classroom. Since online learning requires students to access the internet and digital devices (e.g., computers, smartphones, tablets), technological accessibility may become a major barrier for them as they may not have the necessary devices or internet connection (Ma & Lee, 2019a). In addition, due to technological incompetence and language barriers, they may be unable to participate in online activities in MOOC, such as peer interaction, help-seeking, and group tasks (Lambert, 2020). As a result, they may have difficulties in adapting to online learning environments (Ma & Lee, 2019b). However, concerns about how learners in EDR can better leverage learning resources on the internet from a pedagogical perspective are not limited. Put differently, MOOCs are not only underutilized in EDR but are also understudied in these regions.
2.2 A motivational design perspective
Aligning MOOCs with an existing face-to-face course is challenging, as most MOOCs are originally designed to be stand-alone online courses and not for classroom teaching (Griffiths et al., 2015). One approach to blending MOOCs is considering learners’ motivational needs in designing the course (Ustun & Tracey, 2020). Here, motivational design refers to arranging resources, strategies, and instructional tactics to make the learning process appealing and motivating (Keller & Suzuki, 2004). It is important to understand students’ motivations and perceptions towards the designed instruction as learning motivations are found to exert significant influence on students’ learning activities and engagement (Magen-Nagar & Cohen, 2017; Shapiro et al., 2017). In order to evaluate whether an instructional design effectively motivates students, the present study utilizes the ARCS motivational design model (Keller, 1999) as the framework to analyze and improve the motivational appeals of designed instruction methods. Especially for self-regulated learning, motivational design helps to create a learning environment to attract students’ attention and enhance students’ confidence and competence (Albelbisi et al., 2021; Pittenger & Doering, 2010; Song & Keller, 2001). Based on behavioral, cognitive, and affective learning theories, the ARCS motivational design model aims to improve the motivational appeals of instructional design of computer-based learning (Huang et al., 2006; Keller, 1999). It provides a systematic framework on how to create instructional tactics to stimulate and maintain students’ learning motivations (Cheng & Yeh, 2009; Keller & Suzuki, 2004).
Generally, the ARCS model is based on a synthesis of four dimensions of motivational concepts, including attention, relevance, confidence, and satisfaction (Keller, 1999). Attention refers to the extent to which the instructional design can attract students' interests and curiosity; relevance measures the extent to which the course is related to students' learning experiences and goals; confidence addresses whether the course can stimulate learners’ positive attitudes and expectancy towards the learning tasks, and satisfaction assesses the degree students are satisfied with the course design and their achievements (Huang & Hew, 2016; Keller, 1999).
Compared with other motivational learning theories, the ARCS model provides a systematic framework to identify and evaluate the motivational aspects of instructional design, as well as implementing strategies (Li & Keller, 2018). Rather than focusing on a single motivational variable such as satisfaction, the ARCS model attempts to investigate the effectiveness of an instructional design from a multi-dimensional perspective which is deemed to be comprehensive and systematic (Cheng & Yeh, 2009; Keller, 1999; Turel & Sanal, 2018). The ARCS model has been widely applied to design and evaluate the motivational appeals of different instructional approaches, such as online self-paced learning (Pittenger & Doering, 2010), computer-assisted learning (Karakis et al., 2016), MOOCs (Li & Moore, 2018), blended learning (Chang & Chen, 2015; Ma & Lee, 2020), and has been validated in different nations (Keller & Suzuki, 2004; Li & Keller, 2018). Through the lens of the ARCS model, the present study investigates approaches to integrating MOOCs in a traditional classroom.
2.3 An embedded MOOCs approach
Based on the ARCS model, the present study proposes an embedded MOOCs approach, especially for learners in EDR to take advantage of the online quality course content. The embedded MOOCs approach integrates selective MOOCs videos into the in-class teaching and allows students to consume the learning materials in MOOCs during class hours. Instructors can choose segments of the video content from the selected MOOC course and play the video segments according to the progress of the in-class modules. The video segments can be restructured and redesigned to fit into the existing course. As instructors can monitor the process of learning, they can sense the reactions of students towards the MOOCs content and respond to the questions raised by students simultaneously (Duan, 2022). For example, the instructors can pause at any stage and explain to complement the content of MOOCs if the students cannot understand it well. Meanwhile, synchronous discussion on the MOOCs content can be organized in class under the guidance of the local instructors who will facilitate the understanding of the MOOCs content for the local learners (Bulger et al., 2015). This is tailoring the MOOC course content to a local context and is deemed favorably as the quality of online courses can be utilized while the social presence and instant support of instructors can be guaranteed (Bruff et al., 2013). In addition, such a teaching approach also fosters global pedagogical knowledge sharing and enables teaching expertise to be shared on a global level.
It should be noted that the embedded MOOCs approach is different from simply using online videos and materials in class. First, the video segments derived from MOOCs will be aligned with the in-class teaching content. That is, rather than occasionally playing videos from the Internet, the embedded MOOCs approach allows instructors to utilize MOOCs content to complement, and customize content for local learning needs. This will facilitate learning as the online learning materials will be aligned with the in-class teaching. In addition, the affordances of MOOCs (e.g., course videos, learning materials, and quizzes) allow instructors to focus more on the design of discussion and interaction during class (Israel, 2015). This frees up the instructor’s time to design the course content and so the instructor can play a value-added role as a facilitator in this approach (Smith & Suzuki, 2015). Specifically, the facilitator can help students to digest the MOOC knowledge and clarify their doubts. Last but not least, students have opportunities to be exposed to different social and cultural learning contexts via MOOCs, which may help diversify their learning experiences and arouse their learning motivations (Khan et al., 2018; Zhou et al., 2020). The following sections will further illustrate how the embedded MOOCs approach may overcome the weakness of the asynchronously blended MOOCs in terms of attention, relevance, confidence, and satisfaction.
2.3.1 Attention
Attention refers to how to catch and maintain students’ focus and interest during the learning process. In terms of attracting learners’ attention, the embedded MOOCs approach has several advantages in stimulating and sustaining students’ interest and curiosity. For example, as the content of MOOCs is usually from top universities, this should arouse students’ attention and curiosity at the beginning, especially for students from regions where quality course content is lacking (Alraimi et al., 2015; Zhou, 2016). Furthermore, with the synchronous guidance and support of instructors in class, students’ questions can be answered directly and their attention can be maintained and sustained. For students who have problems with self-regulated learning and time management, the embedded MOOCs approach is more effective in keeping them focused on learning compared to the options (e.g. accessing learning the MOOC content before/after class by themselves). Therefore, the embedded MOOCs approach should outperform the asynchronously blended learning (blended MOOCs approach) and traditional face-to-face learning in capturing and maintaining students’ attention. Thus, the following hypothesis is proposed:
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H1: The embedded MOOCs approach is more effective in attracting learners’ attention when compared to asynchronously blended MOOCs and traditional face-to-face learning,.
2.3.2 Relevance
Relevance means how the course content is related to students’ learning goals and prior knowledge. In this aspect, the embedded MOOCs approach can alleviate the problem of misalignment between the online course video and the in-class course content compared to the asynchronously blended MOOCs approach. Instructors can interact with students based on the video content in class and explain the details of the selected MOOCs segments. This means that the resources in MOOCs can be embedded in the course design more tightly and cohesively (Bruff et al., 2013). In addition, instructors can help to guide the learning process to cater to students’ learning goals and academic requirements (Huang & Hew, 2016). Last, instructors can customize global content to ensure learning is relevant to their students’ learning styles and the local class’s learning culture, which facilitates students to link with their previous learning experiences and knowledge. So, students will likely feel the course design is related and relevant to their conventional on-campus learning experiences. Therefore, the present study states the following hypothesis:
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H2: The embedded MOOCs approach is more effective in enhancing learners’ relevance perception when compared to the asynchronously blended MOOCs and traditional face-to-face learning.
2.3.3 Confidence
Students should have the confidence to succeed when participating in a new course. In online learning, students might be frustrated due to the lack of instructor support and synchronous communication (So & Brush, 2008). In contrast, in the embedded MOOCs approach, support from instructors and peers is easily accessible in class when they have problems. This would provide opportunities for students to interact with each other and with the instructor regarding the MOOCs content they consume (Cocquyt et al., 2019). Furthermore, the embedded MOOCs g approach fosters a strong sense of community, and students can seek help from peers easily. The social presence and support of the instructors also help to establish students’ confidence in successfully finishing the course tasks (Owston et al., 2019). For students in EDR who lack internet connection and digital equipment, the embedded MOOCs approach can help them to reap the benefits of MOOCs together under the support of instructors and educational institutions. Furthermore, learning quality course materials from worldwide top universities should broaden the local students’ horizons and is likely to lead to enhanced confidence. Accordingly, the following hypothesis is stated:
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H3: The embedded MOOCs approach is more effective in stimulating learners’ confidence when compared to the asynchronously blended MOOCs and traditional face-to-face learning.
2.3.4 Satisfaction
Students’ satisfaction with courses plays an important role in evaluating learning effectiveness (So & Brush, 2008). The embedded MOOCs approach may help to decrease the excessive workload introduced by learning MOOCs before/after class (Griffiths et al., 2015). The well-structured course design and alignment between MOOCs content and in-class lessons should facilitate students’ learning process. The social presence and direct feedback of instructors is also strong predictor of student satisfaction and learning perceptions (So & Brush, 2008). Furthermore, learning with peers would make students feel not isolated but connected and supported (Bulger et al., 2015). All these factors should contribute to students’ positive attitudes toward the embedded MOOCs approach. Thus, the presents study proposes the following hypothesis:
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H4: The embedded MOOCs approach is more effective in enhancing learners’ satisfaction when compared to the asynchronously blended MOOCs and traditional face-to-face learning.
2.3.5 Continuous usage intention
The present study investigates how the motivational design factors affect students’ intention to adopt the embedded MOOCs approach in their future learning pursuits. One of the essential goals of an instructional design is to promote learners’ willingness to continuously and actively use the designed learning approach (Cheng & Yeh, 2009). If the learning procedure is interesting, goal-oriented, and makes students feel confident and satisfied, they should not only feel motivated but also be willing to adopt such learning methods in their future studies (Tseng & Walsh, 2016; Turel & Sanal, 2018). Based on the ARCS model, the present study would further investigate how motivational factors exert influence on students’ intention to engage with MOOCs content under the embedded MOOCs approach. The following research question is proposed:
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RQ: What motivational factors (i.e., attention, relevance, confidence, and satisfaction) would exert significant influence on students’ intention to adopt the embedded MOOCs approach in their further studies?
3 Methodology
The present study designed a randomized experiment to compare students’ perceptions of the three instructional methods (i.e. the proposed embedded MOOCs approach, the asynchronously blended MOOCs approach, and the traditional face-to-face classroom learning). Based on the experiments, the findings would uncover which instructional design would be more effective in motivating students in terms of attention, relevance, confidence, and satisfaction perceptions. Furthermore, the motivational factors that promote students to use the embedded MOOCs approach continuously were also investigated.
3.1 Experiment design
A randomized experiment was conducted in a local university in an EDR of China to test the motivational appeals of the different learning approaches. The methodology of randomized controlled trials under identical conditions is more accurate in comparing the effectiveness of different teaching methods (Drits-Esser et al., 2014). This means that the same instructor, the same course content, and the same pool of students randomly assigned to different conditions will help reduce potential confounding effects and enable more accurate comparison (Eesley & Wu, 2019; Stockwell et al., 2015).
This study was conducted in China. We chose China because educational resources are not equally distributed in China and quality course content is needed in some regions. The location selected for this study is regarded as one of the least developed areas in China of which the GDP per capita was around two thousand and nine hundred US dollars in 2019 (Gansu Provincial Bureau of Statistics, 2019). Meanwhile, because of the poor infrastructure and lack of internet connection, students face difficulties in accessing online learning materials from Internet platforms such as MOOCs using their own devices. Participants were recruited from a local university. The design of the three experimental groups is described in Table 2.
The lecture for the study was a basic statistics course that lasted around forty-five minutes. Though the duration of the experiments is relatively short, such a design is effective to control for potential confounding factors that may affect the evaluations of the different learning approaches. For instance, the three groups had the same course content and were delivered by the same instructor. The asynchronously blended MOOCs approach assigned students to watch an online video course about statistics before the class while the embedded MOOCs approach instructed students to watch the segments of the same video in the in-person class. It might be noted that participants in the asynchronously blended MOOCs group had to spend more learning time for online video course than the face-to-face learning or the embedded MOOCs learning group. This is consistent with real life where the asynchronously blended MOOCs approach also requires additional learning hours before or after the class.
One hundred and fifty-four undergraduates from the business school in a local university were recruited and randomly assigned into the three instructional groups. However, as some students were absent when the experimental classes were taught or did not submit the questionnaire survey after the trial class, they were excluded from the sample. Nine participants in the asynchronously blended MOOCs learning group reported that they had yet to learn the online video course before attending the class. Thus, they were also excluded from the sample as they did not fulfill the criteria as blended MOOCs learners in the experiment. The students who participated in the experiments were given course credits as incentives. The demographics of the final participants in each experimental sample are presented in Table 3.
3.2 Measurements
After participating in the experimental classes, the students of each group were asked to fill a questionnaire based on their perceptions about the instructional approach they were assigned to participate in. The questionnaire was to measure the students' motivational perceptions on the basis of the ARCS model (Gutiérrez-Santiuste et al., 2015; Keller, 1999). Eighteen question items were adapted from previous studies utilizing the ARCS model to measure students' learning motivations, including attention, relevance, confidence, and satisfaction (Huang et al., 2006; Keller, 1999; Pittenger & Doering, 2010). In addition, individuals’ self-regulation abilities (such as time management, persistence, help asking) are deemed to impact students’ performance and perceptions in a blended leaning context (Barnard et al., 2009; Broadbent, 2017). Thus, students’ self-regulation ability was also measured and considered as a covariate to be controlled when comparing the performances of students in different instructional designs (Broadbent, 2017). Last, students’ intention to adopt the assigned learning approach was measured in each experimental group (Venkatesh et al., 2003). All the question items were measured through a five-Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Cronbach’s alpha coefficients were calculated to test each construct's reliability. Beyond citing an arbitrary threshold, the alpha values in education studies are often described as strong and excellent (0.93–0.91), robust and reliable (0.81–0.90), high (0.71–0.80), moderate and reasonable (0.61–0.70), acceptable and sufficient (0.55–0.60), not satisfactory (0.41–0.54) and low (0.1–0.4) (for a comprehensive review, refer to Taber (2018)). Therefore, all the Cronbach’s alpha values of the variables in this study are acceptable (presented in the Appendix). The details of the measurements are presented in the Appendix.
3.3 Analyses
In order to compare the differences of the three experimental groups in terms of motivational perceptions, one-way ANCOVA with post hoc tests were applied to analyze the questionnaire data in SPSS 22.0. The one-way ANCOVA (analysis of covariance) is considered as an extension of one-way ANOVA, which allows controlling of the impact of the covariate or the confounding variables while comparing the differences of group means (Field, 2018). In the present study, one-way ANCOVA analysis was utilized to compare students’ perceptions across three experimental groups while controlling the impact of individual students’ self-regulation ability. In addition, post hoc tests were applied to test the mean differences between pairs of the three experimental groups and further reveal how the embedded MOOCs approach performed by comparing with the asynchronously blended MOOCs approach and traditional face-to-face learning respectively. Lastly, multiple regression analysis with the bootstrapping method was conducted to examine the influential factors that exerted influence on students’ intention to continuously use the embedded MOOCs approach. The other two experimental groups were also analyzed by regression analysis for comparison. Particularly, this study used the bootstrapping method in regression analysis. Bootstrapping is a self-sustaining process in which the sample is used to represent an estimate of the whole population, and many simulated samples are resampled to calculate standard errors and construct confidence intervals for hypothesis testing (Mooney & Duvall, 1993). This method is widely used because this procedure is easier for comprehension and it does not require distributional assumptions (such as normally distributed errors) of the variables (Field, 2018). Considering that the number of the participants in each experimental group was relatively small (less than fifty), the distributions of the variables may not follow the normal distribution. Thus, to get reliable and accurate results, this study chose the bootstrapping method when running regression analysis.
4 Findings
The results of one-way ANCOVA are presented in Table 4. After controlling the impact of self-regulation, it was found that the three groups of students showed significant differences in terms of attention (F = 9.352, p < 0.001), relevance (F = 3.408, p < 0.05), and satisfaction perceptions (F = 8.507, p < 0.001). However, these three teaching groups showed no significant difference regarding confidence perception (F = 0.681, p = 0.508). In addition, partial eta-squared was used to determine the effect size of the comparisons. The partial eta-squared values of the four comparisons were 0.126, 0.050, 0.010, and 0.116 respectively. According to Field (2018), the partial eta-squared values greater than 0.01 represent small effect size, 0.06 as medium, and 0.14 as large. Thus, the effect size for the comparisons regarding attention and satisfaction was considered as medium, while that for the comparisons of relevance and confidence was regarded as small.
Through the LSD post hoc tests, pairwise comparisons were conducted to reveal the differences in motivational perceptions between pairs of the three experimental groups. The findings are shown in Table 5. It was found that both the embedded MOOCs approach (mean difference = 0.423, p < 0.001) and asynchronously blended MOOCs approach (mean difference = 0.311, p < 0.01) performed better in attracting students’ attention than the traditional face-to-face learning. So H1 was partly supported. Regarding the relevance perception, the embedded MOOCs approach outperformed both the blended learning (mean difference = 0.229, p < 0.05) and face-to-face learning (mean difference = 0.231, p < 0.05). Thus H2 was supported. In terms of satisfaction, both the embedded MOOCs approach (mean difference = 0.412, p < 0.001) and asynchronously blended MOOCs approach (mean difference = 0.263, p < 0.05) attained higher satisfaction compared to face-to-face learning, and H4 was partly supported.
After comparing motivational perceptions of different experimental groups, multiple regression analysis with the bootstrapping method was conducted to further reveal what motivational factors may contribute to students’ continuous use of the embedded MOOCs approach in their future studies. The motivations of adopting the asynchronously blended MOOCs approach and traditional face-to-face learning were also analyzed for comparison. The control variables (i.e., gender, age, MOOC learning experience, self-regulation ability) were entered into the regression analysis as the first block and the motivational factors (i.e., attention, relevance, confidence, and satisfaction) as the second block. The findings are presented in Table 6.
It was found that attention (B = 0.582, p < 0.01) was the strongest predictor of students’ intention to adopt the embedded MOOCs approach, followed by satisfaction (B = 0.483, p < 0.05) and confidence (B = 0.357, p < 0.05). In contrast, only relevance (B = 0.579, p < 0.05) could significantly predict students’ intention to use the asynchronously blended MOOCs approach in their future studies. Both of the regression models were statistically significant and could explain the variances of the dependent variable by 65.6% (the embedded MOOCs approach) and 45.4% (the asynchronously blended MOOCs approach) respectively. Besides, after entering motivational factors into the model, the explanation power reflected by the adjusted R square was also increased significantly in both of the groups, which may indicate that motivational factors have significant power in explaining students’ intention of adopting new instructional methods. In contrast, none of the motivational factors were significant in the regression model of the face-to-face learning group.
5 Discussion
Based on the ARCS model, the present study proposed an embedded MOOCs approach. It investigated the effectiveness of the approach compared with other approaches namely the asynchronously blended MOOCs approach and traditional face-to-face learning. The study found that the embedded MOOCs approach outperformed the face-to-face approach in attracting and retaining students’ attention and ensuring satisfying outcomes. In addition, the embedded MOOCs approach performed better than the blended MOOCs in enhancing students’ relevance perception. Furthermore, the underlying motivators of adopting the embedded MOOCs approach were analyzed. Results indicate that attention, confidence, and satisfaction exerted significant influences on students’ intention to adopt the embedded MOOCs approach. The findings shed light on how embedded MOOCs approach can be leveraged to benefit learners in EDR where the internet infrastructures are inadequate and the quality course content from internet platform providers such as MOOCs is much needed.
Interestingly but unsurprisingly, the embedded MOOCs approach performed best in triggering students’ relevance perception among the three experimental groups. By definition, relevance perception includes familiarity, goal orientation, and the learning needs of students (Turel & Sanal, 2018). The embedded MOOCs approach effectively linked students’ prior experiences and knowledge with the current learning context. The reason is that instructors can adapt the MOOCs content according to students’ learning goals and progress. Notably, this suggests that the instructor in EDR does not need to be solely responsible for providing all the sources or knowledge required for the course. Nevertheless, he/she can potentially play multiple roles as a facilitator, translator, coach, and examiner of the learning as they can re-use the course content shared by other MOOCs content creators (i.e. other course instructors). Understandably, the content creators may have different pedagogical goals and can be socio-culturally exclusionary for learners who are non-native English speakers (Lambert, 2020). Further, while the videos in MOOCs can be translated through subtitles, the translation of the discussion forum content is not feasible. Hence the cultural and language differences further create barriers for non-native English speakers from other cultures to interact with other learners in the online learning space. By adapting the video segments from MOOCs to the local students, the course instructors play important roles in catering to the local students’ learning needs and fostering a more interactive and engaging learning environment by accessing and sharing quality course content in MOOCs. More broadly, this open access, shared, and embedded MOOC approach may lead to the emergence of a new pedagogy where course contents are shared among global instructors and bring us a step closer to the notion that quality education is a common good that needs to be shared.
Both the embedded MOOCs and blended MOOCs approaches performed better in attracting and retaining students’ attention than the traditional face-to-face classroom learning. It has been identified that short pieces of video content perform better in helping students to retain information because the information provided is digestible and manageable (Giurgiu, 2017). The finding suggests that MOOCs help to provide quality content (typically from top-tier universities) for learners in EDR which can be lacking in EDR. Furthermore, during the learning process of the embedded MOOCs, the instructors can explain the video content and interact with students by asking questions and organizing discussions according to the MOOCs’ segments and materials. Particularly for students who lack self-regulation skills, the embedded MOOCs approach is more effective to get learners’ attention and focus.
Regarding students’ satisfaction perception, both the embedded MOOCs approach and asynchronously blended MOOCs approach gained higher satisfaction than the traditional face-to-face classroom learning. The satisfaction level of the embedded MOOCs approach was also higher than the blended MOOCs group, though the difference was not statistically significant. The finding is consistent with prior studies (e.g., Bruff et al., 2013; So & Brush, 2008) which found that students preferred to learn with the local learning community on campus and with the social presence of instructors compared with pure online learning. Past works have emphasized the importance of the social presence of peer learners and instructors to ensure effective technology-mediated learning processes and outcomes (Gutiérrez-Santiuste et al., 2015; Lee et al., 2009). Specifically, the instructional elements of the embedded MOOCs approach, such as interactivity, peer support and instant feedback are found to predict students’ satisfaction with the course design (Turel & Sanal, 2018). This is in contrast to the blended MOOCs approach where learners were required to watch MOOCs videos alone. This explains the high drop-out rate in online learning environments since learners may feel isolated or disconnected from other learners (Bowen et al., 2014; Israel, 2015; Kintu et al., 2017). This finding is especially pertinent where learning and schooling are disrupted due to crises such as pandemics and civil unrest. While pure online learning is advocated in such extreme situations, the government and policymakers need to be aware of the difficulties and learning losses the learners in EDR face. Complementary efforts to support the learning needs of the local students need to be incorporated into the learning ecosystems (e.g. building local learning hubs) or designing physical classrooms that allow for hybrid learning.
Surprisingly, the embedded MOOCs approach showed no significant difference in enhancing students’ confidence perception compared with the asynchronously blended MOOCs approach or the traditional face-to-face learning. One possible reason is that as the results of students’ perceptions were based on an experimental trial class, the students were not sure how the course would be assessed and conducted in an actual situation. In retrospect, it was probably difficult to accurately evaluate students’ confidence or expectation for success in the course in such a short duration. It is also possible that because the experimental designs of the embedded and blended MOOCs approaches were relatively new to the students. Thus they were unsure how to strategize and adapt to the new learning environment which affected their perception on whether they could succeed with this new learning approach (Israel, 2015; Ma & Lee, 2019b). As a result, the confidence perceptions were generally low and showed no significant differences across the different instrumental groups.
Among the motivators of the ARCS model, attention, confidence, and satisfaction were found to significantly impact students’ intention to adopt the embedded MOOCs approach in their future studies. Specifically, attention was found to be the strongest predictor of students’ adoption intention, followed by satisfaction and confidence. As discussed above, a variety of instructional tactics, along with the quality content of MOOCs, can be used to stimulate and sustain students’ attention in the embedded MOOCs approach. Social support of peer students and instant feedback from instructors are likely to increase students’ satisfaction and engagement, and further motivate students to adopt such a learning approach (Griffiths et al., 2015; Gutiérrez-Santiuste et al., 2015; Tseng & Walsh, 2016). The MOOC content can be delivered and explained by local instructors which is likely to enhance confidence perception as the students get to participate in the learning process. Thus, the confidence perception is found to contribute to students’ intention to adopt the embedded learning. It should be noted that relevance perception was not significant in motivating students to adopt the embedded MOOCs approach, though it attained the highest score across these three learning groups in the experiments. This may be explained from the perspective of the motivation-hygiene factor theory or two-factor theory (Herzberg et al., 1967). According to the two-factor theory, factors that influence individuals’ satisfaction and performance can be classified into two categories. One category is regarded as “motivators” or “satisfiers”, which can lead to satisfaction if fulfilled. The other is labeled as “hygiene factors” or “dissatisfiers”, which may not contribute to satisfaction but could result in dissatisfaction if absent. In the present study, relevance might be considered as a hygiene factor by students. That is, relevance perception may not necessarily lead to satisfaction to motivate students to adopt the embedded MOOCs approach, but would make students dissatisfied if they find the course design is not relevant to their learning goals or prior knowledge. Therefore, although relevance is not significant, instructors should still keep the course design and MOOCs content relevant to students’ learning goals and experiences.
6 Conclusion
The use of MOOCs in higher education can be a potential equalizer to bridge the knowledge divide. On a broader scale, the findings shed light on how to use Internet educational resources for global benefits and enable new pedagogical developments. Indeed, everyone has the right to quality education and access to quality educational resources is a starting point. MOOCs support this notion by providing a global platform to share this collective responsibility to enable education for a global common (Ossiannilsson, 2021). The findings of the present study contribute to the understanding of how to utilize MOOCs and re-use content in MOOCs to benefit learners in EDR. Based on the ARCS model, the findings identified that the embedded MOOCs approach could effectively stimulate students’ learning motivations such as attention, relevance, and satisfaction perceptions. Our findings also highlight that learning outcomes should be evaluated from a multi-dimensional perspective rather than based on single variables. Furthermore, the motivational appeals of the embedded MOOCs in terms of attention, confidence, and satisfaction are found to be significantly associated with students’ intention to adopt such a learning approach in their future studies. Specifically, the findings underscore the importance of social support and offline interactions with instructors and peer students in addition to the online learning materials. This is especially important for students in EDR where the internet connection is lacking and quality course materials are needed. In sum, the present study pointed out important implications on how MOOCs can be leveraged to benefit learners in EDR.
In order to promote the embedded MOOCs approach learning, educators should utilize a variety of instructional tactics to enhance students’ attention, confidence, and satisfaction perceptions. For example, as attention was identified as a significant predictor of students’ intention to adopt the embedded MOOCs approach, it is important to trigger students' curiosity and maintain their interests when using the MOOCs segments, such as asking questions and organizing discussions based on the MOOCs content. In addition, it is critical to build students’ confidence when applying the embedded MOOCs by encouraging them to actively participate in the learning process and helping them to adapt to the new learning environment. Last, since satisfaction was identified as a critical motivator, instructors should pay more attention on how to improve students' satisfaction when utilizing MOOCs in class, such as incorporating the MOOCs content with an existing module in a seamless manner, controlling the length of the video, interacting more on the video content in the class, etc. For MOOC platform providers, they should encourage course content providers to provide short course videos that are suitable to integrate into in-class learning and interaction activities. Meanwhile, copyright issues should be looked into by MOOC platforms and content providers to overcome the potential barriers. Specifically, MOOCs and other global learning platforms and learning content providers need to consider the local learning needs of the students from different regions to address the challenges of knowledge and the local divide.
Cautions are needed when interpreting the findings of the present study. First, this study was conducted in an economically disadvantaged area in China. Thus, replicating this study in other places may be necessary to verify the validity of the findings of the present study. In addition, the novelty effect of the instructional design may exert an influence on students’ motivational perceptions in the experiments and thus impact the findings of the study (Smith & Suzuki, 2015). Future studies should attempt to examine the long-term effects of the embedded MOOCs approach on students’ learning motivations in actual academic settings for an entire semester. Another concern with applying the embedded MOOCs approach is the copyright issue or intellectual property when the local instructors try to reuse MOOCs from third-party platforms. To what extent an instructor is allowed to adapt the MOOCs content for his/her own class remains unclear and controversial (Griffiths et al., 2015; Lambert, 2020). This means that policymakers, MOOCs content and platform providers need to work together to advance new learning pedagogical developments that will benefit global learners to the address educational digital divide and ensure that education is a common good for all. Despite the limitations, the present study proposes a sustainable model for integrating MOOCs into traditional classroom learning to address an important global issue on educational equity and social inclusion of students in EDR.
Data availability statement
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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This work was supported by the Philosophy and Social Science Research Project of Zhejiang Province (Grant numbers: 21NDJC076YB).
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Appendix
Appendix
1.1 Measurements
Constructs | Questions | Cronbach’s α |
|---|---|---|
Attention | This class has very little in it that captures my attention. (R) | 0.630 |
The students in this class seem curious about the subject matter | ||
The instructor uses an interesting variety of teaching techniques | ||
I often daydream while in this class. (R) | ||
My curiosity is often stimulated in this class | ||
Relevance | The things I am learning in this course will be useful to me | |
The subject matter of this course seems important | ||
The content of this course relates to my expectations and goals | ||
To accomplish my goals, it is important that I do well in this course | ||
I do NOT think I will benefit much from this course. (R) | ||
Confidence | I feel confident that I will do well in this course | 0.600 |
The subject matter of this course is just too difficult for me. (R) | ||
As I am taking this class, I believe I can succeed if I try hard enough | ||
Satisfaction | I feel that this course gives me a lot of satisfaction | 0.819 |
I enjoy working for this course | ||
I am pleased with the design of this class | ||
I feel satisfied with what I am getting from this course | ||
I feel rather disappointed with this course. (R) | ||
Self-regulation ability | I am good at resisting temptation | 0.744 |
I am self-disciplined at times | ||
People can count on me to keep on schedule | ||
Intention to adopt | Using the MOOC before/during class is a good idea | 0.776 |
I dislike the idea of using the MOOC before/during class. (R) | ||
I’d like to continue this kind of course design in I take the course |
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Ma, L., Lee, C.S. Leveraging MOOCs for learners in economically disadvantaged regions. Educ Inf Technol 28, 12243–12268 (2023). https://doi.org/10.1007/s10639-022-11461-2
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DOI: https://doi.org/10.1007/s10639-022-11461-2