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Analysis of Students’ Online Learning Engagement during the COVID-19 Pandemic: A Case Study of a SPOC-Based Geography Education Undergraduate Course

School of Teacher Education, Nanjing Normal University, Nanjing 210023, China
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(5), 4544;
Submission received: 10 December 2022 / Revised: 27 February 2023 / Accepted: 2 March 2023 / Published: 3 March 2023
(This article belongs to the Special Issue Sustainable Transition to Online Learning during Uncertain Times)


With the long-lasting impact of the COVID-19 pandemic, online learning has gradually become one of the mainstream learning methods in Chinese universities. The effectiveness of online learning is significantly influenced by learning engagement, and studies into this topic can help learners by providing them with process-based learning support and focused teaching interventions. Based on the online learning environment, this research constructs an online learning engagement analysis model. Additionally, this study explores the relationship between students’ online learning engagement and their online learning performance by taking the Secondary School Geography Curriculum Standards and Textbooks Research, a small-scale private online course (SPOC) of the geography education undergraduate course at Nanjing Normal University, as an example. The findings are as follows: In the cognitive engagement dimension, only “analyze” is significantly positively correlated with learning performance; in the behavioral engagement dimension, the “number of question and answer (Q&A) topic posts,” the “replies to others,” and the “teachers’ replies” are all significantly positively correlated with learning performance. In terms of the emotional engagement dimension, “curiosity” and “pleasure” are positively correlated with learning performance; as for the social engagement dimension, “point centrality” and “intermediary centrality” are positively correlated with learning performance. The findings of this case study reveal that the student’s engagement in higher-order cognitive learning is obviously insufficient. Students’ online learning performance can be enhanced both by behavioral engagement in knowledge reprocessing and positive emotional engagement. Further research should be focused on finding ways to increase students’ enthusiasm for social engagement.

1. Introduction

With the advent of the information age, online learning has been implemented around the world to connect teachers and students effectively. This is especially true when there is a public crisis like the COVID-19 pandemic outbreak [1]. Since the outbreak of the COVID-19 pandemic, there has been a flurry of research on online higher education. Researchers investigated a wide array of topics, such as the use of various technologies and strategies [2,3], redesigned curriculum [4], student perceptions [5], psychological impacts [6], and factors associated with the adoption of pandemic-imposed online learning [7]. In the past three years, we have witnessed a sharp growth in the literature on students’ experiences of emergency online learning. Some researchers have begun to explore the issue of student engagement in emergency online learning. This touches the core of students’ learning experiences because student engagement has been widely recognized as one of the most important determinants of college students’ academic success [8]. Empirical evidence suggests that effectively engaging students in the online classroom is critical to the quality and effectiveness of online education [9]. However, due to the complexity of student engagement as a multifaceted and multidimensional construct, the definition and measurement of student engagement in technology-mediated learning contexts are still issues of heated debate. Researchers’ increased interest in examining how students’ engagement in online environments influences their learning outcomes constitutes a breakthrough in education research in recent years. Thus, it is necessary to explore how certain contextual factors in this situation promote or thwart students’ engagement, which in turn will have important effects on students’ academic achievement when taking mandatory online learning.
To address the gaps in the current literature and explore how online learning can be transmitted and sustained in various learning environments, the present study constructs a multidimensional online learning engagement analysis model to investigate student engagement in emergency online learning during the COVID-19 pandemic. Additionally, this study explores the relationship between students’ online learning engagement and their online learning performance by taking the Secondary School Geography Curriculum Standards and Textbooks Research, a small-scale private online course (SPOC) of the geography education undergraduate course, as an example. The Secondary School Geography Curriculum Standards and Textbooks Research is an introductory geography education course for pre-service teachers. Geography’s inherently interdisciplinary nature is its strength in advancing sustainability education. This discipline can develop a more holistic understanding of global environmental challenges in that it encompasses all the sciences (including social sciences and humanities) and possesses a realization of the sheer magnitude of human impact on the global environment. Therefore, geography education is a crucial tool for educating citizens of all ages about the complexity of human-nature interconnections, how to make more reasoned decisions for the planet, and what can (and should) be conducted to ensure a more sustainable future [10].
We attempt to answer the following three questions: (1) What are the main characteristics of student engagement—on the cognitive, behavioral, emotional, and social dimensions—in online learning in Chinese higher education during the COVID-19 pandemic? (2) What is the relationship between students’ online learning engagement and their learning performance in Chinese higher education during the COVID-19 pandemic? (3) What are the main implications for online learning in Chinese higher education?

2. Literature Review

2.1. Online Learning

Rapid developments in technology have made distance education easy [11]. Online learning, as a form of distance education, is defined as “learning experiences in synchronous or asynchronous environments using different devices (e.g., mobile phones, laptops, etc.) with internet access.” “In these environments, students can be anywhere (independently) to learn and interact with instructors and other students [12].” Moreover, online learning can make the teaching–learning process more student-centered, innovative, and flexible. In the shadow of the global COVID-19 pandemic, online learning has become the most dominant way of learning. At the same time, the weaknesses of online learning are hard to ignore. Online learning can hamper communication between the learner and the educator, which means a lot of face-to-face communication is lost. Inadequate compatibility between the design of the technology and the components of psychology required by the learning process and inadequate customization of learning processes can obstruct the teaching process and create an imbalance. Therefore, it is crucial at this stage to enhance the quality of the process of online teaching–learning [13].

2.2. Small-Scale Private Online Course (SPOC)

SPOC is an acronym that refers to a small-scale, private online course [14]. Small refers to a small number of students (the number is generally less than 120 students), and private refers to the students enrolled in the course at the school where the course has started, or the number of students is limited according to the course’s characteristics. The teaching mode of SPOC is based on the high-quality video content of massive open online courses (MOOCs), which students can utilize to gain a basic understanding of a specific topic before class. As a result, teachers can teach higher-order content, respond to students’ questions, and provide additional learning materials or exercises to provide a more comprehensive learning experience [15]. The advantage of SPOC lies in its customization and privacy. SPOC can fully customize a series of links from time and space to learning objects and teaching content. At the same time, SPOC teachers can choose whether the customized teaching contents are public, which not only ensures the teaching quality of SPOC but also protects the personal privacy of SPOC learners. SPOC provides more detailed and accurate personal data analysis services, which effectively monitor learners’ learning behavior and the learning effect in each specific time period [16].

2.3. Online Learning Engagement

With the rapid development of online learning, online learning engagement has attracted more and more attention from researchers. In an earlier study, Paul et al. argued from the perspective of work engagement that the more people put into their work, the greater the gain [17]. Subsequently, Schaufeli et al. introduce the ideas of work engagement to the learning process, arguing that learning engagement refers to a state closely related to learning, divided into three dimensions: vigor, dedication, and absorption [18]. Starting from the factors that are most directly related to the learning process, Martin focuses on learning engagement in two dimensions: cognitive engagement and behavioral engagement [19]. Behavioral engagement refers to learners’ high involvement in learning activities, which can reflect various behaviors of learners in the learning process [20]. Mazzolini analyzes posts in 400-course forums and has found that teacher participation rate, posting time, and the contents of posts affected learners’ participation in online discussions [21]. Nandi argues that students’ willingness to discuss in the online learning environment is easily influenced by teachers’ behavior [22]. According to Khe’s study, online learning behaviors include learners’ discussion, recognition, and response [23]. Feng Xiaoying points out that online learning behaviors included individual behaviors associated with learners’ interactions with learning platforms and interactive behaviors with groups such as teachers and students [24]. Cognitive engagement is a high level of mental and emotional involvement in learning, especially the level of mental engagement after deep thought [25]. The research suggests that a clear understanding of learners’ perception, regulation, and emotional experience of the course is conducive to improving the effectiveness of online teaching. Based on Bloom’s revised taxonomy of educational goals, Fredricks proposes that online learning engagement refers to the positive state displayed by learners in the online learning process, focusing on three dimensions: cognitive engagement, behavioral engagement, and emotional engagement [20]. Among them, emotional engagement refers to the emotional responses presented by learners in the process of learning, such as curiosity and disgust [26]. By compiling the remote learning engagement evaluation scale, Li Shuang et al. divided the evaluation dimensions into more details from these three aspects [27]. Liang evaluates students’ cognitive and emotional engagement in online learning from the perspective of online peer evaluation through the method of measuring. In Liang’s study, online learning needs to interact with different learners to achieve a better learning effect [28]. Therefore, Fredricks et al. added social engagement based on the original three dimensions, emphasizing the social interaction between teachers and students as well as between students themselves [29].
Although the research on student engagement in online learning contexts has attracted increasing attention, there are still some problems with conceptual and measurement issues. Henrie et al. [30] reviewed 113 studies measuring student engagement in technology-mediated learning. Although student engagement has been widely recognized as a multidimensional construct, 43% of the 113 studies measured engagement along only one dimension. While it is considered important to measure emotional engagement at the K-12 level, there is less research on students’ emotional engagement in higher education. Instead, student engagement in online learning should be assessed and understood from the students’ perspective and through their engagement with learning materials and activities. The present research aims to address these gaps in the literature.

3. Research Method

3.1. Online Learning Engagement Model Dimensions

With the development of the information age, the division of dimensions in online learning engagement is constantly improving and deepening. The focus of research has shifted from learning states to learning behaviors and cognitive states to learning emotional experiences. Researchers have recently concentrated on the social interaction of online learning and have proposed the dimensions of social engagement [28,29]. The components of the online learning engagement model are thus divided into four dimensions in this study: cognitive engagement, behavioral engagement, emotional engagement, and social engagement.

3.1.1. Cognitive Engagement Dimension

Due to the unique nature of online learning, Akyol et al. believe that, compared with the offline learning environment, online learners need to pay more attention to cognitive engagement to cope with complex learning situations [31]. Learners with high cognitive engagement tend to re-examine ideas and have a strong thirst for knowledge. On the contrary, learners with low degrees only show superficial engagement, such as memorizing knowledge. Based on this, this study, which focuses on the cognitive process of learners, adopts Bloom’s revised taxonomy of educational goals in the dimension of cognitive engagement, from concrete to abstract successively: remember, understand, apply, analyze, evaluate, and create.

3.1.2. Behavioral Engagement Dimension

The learning platform can record learners’ learning behaviors in different periods in detail, such as browsing resources and posting.
Based on prior research by Khe and Feng et al. on the division of the behavioral engagement dimension, this study includes four distinct learning behaviors that are frequently utilized in online learning platforms into the behavioral engagement dimension [22,23,24]. These behaviors are as follows: (1) Publication of posts; (2) Replies to others; (3) Teachers’ replies; and (4) Peers’ replies.

3.1.3. Emotional Engagement Dimension

To some extent, emotional engagement can affect cognition, behavior, and interaction with peers in the course. Students will show a positive state when involved with highly positive emotions. Lee et al. measure the value of whether learners on the online learning platform are satisfied with the course [32]. Skinner et al. propose the classic emotional engagement scale, in which emotional responses include interest, happiness, boredom, and sadness [33]. It is also noted that emotional engagement should include students’ identification with the school, which involves a sense of belonging and value. Li Shuang et al. agree with this view. They have conducted empirical research and analysis and discovered that “a sense of belonging” is more significant than “sadness” as a common emotion in distance learning [27].
Combining the research of Skinner and Li Shuang et al., this study divides the dimension of emotional engagement into four dimensions, which are: (1) Curiosity, which means that learners are curious about the course content, resources, and teaching methods; (2) Pleasure, referring to learners’ pleasure in the course content, resources, and teaching methods; (3) Belonging, which refers to the fact that learners actively interact with teachers and other students and have a sense of belonging to the content, object, and process of interaction in online learning; (4) Boredom, meaning that learners’ negative emotions such as boredom of course content, resources, and teaching methods.

3.1.4. Social Engagement Dimension

With the updates and iterations of technology, online learning presents a variety of interactive methods. Handelsman et al. add interaction engagement to the online learning engagement measurement scale and find that interaction enhanced their sense of social presence [34]. Wen Shufeng et al. divide behavioral engagement into interactive learning engagement, focusing on the learning processes of different learners through communication [35]. Wang Lu adopts the method of social network analysis and finds that the characteristics of interaction behavior networks, such as point centrality and feature vector, could truly reflect the interaction state of students [36].
Based on previous studies, this study divides the dimension of social engagement into four dimensions as follows: (1) Degree centrality, which refers to the total number of people the learner contacts in the course interaction network; (2) Closeness centrality, which means that the sum of the distance between the learner and all other people connected with him in the course interaction network; (3) Betweenness centrality, referring to the number of shortest paths that pass through a learner in the course interaction network; and (4) Cohesive subgroup, meaning that the number of groups formed by learners in the course interaction network.

3.2. Online Learning Engagement Model Construction

3.2.1. Cognitive Engagement Based on Content Analysis

The most commonly used method of cognitive engagement analysis is to analyze online forum posts through content analysis. This study adopts the cognitive domain in Bloom’s revised taxonomy of educational goals, which can clearly distinguish learners’ cognitive engagement from simple to complex cognitive processes, effectively evaluating learners’ cognitive level in the process of online learning. In this study, we take the SPOC course Secondary School Geography Curriculum Standards and Textbooks Research as an example, organize discussion posts through content analysis and coding, and record the frequency of learners in each dimension. The specific dimensions and their descriptions are shown in Table 1.

3.2.2. Behavioral Engagement Based on Learning Platform Data Analysis

The learning platform can not only monitor the learning dynamics of learners but also carry out targeted teaching interventions. The online learning platform collects data from users’ personal behavior logs. By entering the course management background, the course data statistics can be checked, and four types of learning behaviors closely related to students’ course operation can be chosen, which belong to the discussion area. After collecting and exporting the data, it is necessary to screen and eliminate the information. The four kinds of learning behaviors are recorded by frequency, and finally, the engagement data of learning behaviors based on the learning platform data is obtained.

3.2.3. Emotional Engagement Based on Self-Report Analysis

Emotional engagement can reflect the emotional response and state of learners throughout the whole teaching activity. Self-report is a questionnaire-based self-report scale, which is also a common measurement tool for assessment and analysis. Combined with a 5-point Likert scale, self-report can describe the intensity of an emotional state. This study adopts the research of Skinner and Li Shuang et al., which divides emotional investment into four dimensions with three questions in each dimension, and quantifies the intensity level into ones, twos, threes, fours, and fives respectively. Consequently, it takes the average of the three questions in each dimension as the value of this dimension for each learner. The specific dimensions, reliability, and questions of the four emotional engagements are shown in Table 2.

3.2.4. Social Engagement Based on Social Networking Analysis

Social engagement mainly comes from the processes of teacher–student interaction and student–student interaction, which effectively suggest the position of different learners in the course interaction network. From the perspective of individual learners, each learner is not a single isolated individual but exists in a close relationship with complementary roles. In terms of groups in the course, online learning has similar relationships with real society. The greater the degree of centrality, the richer the information, such as knowledge and methods, that can be obtained in the course interaction network. The smaller the closeness centrality, the closer the point is to all other points, indicating that it is in the center of a course interaction network. Betweenness centrality can indicate an active state in the course interaction network. The more cohesive subgroups there are, the higher the density will be. In the internal group, the learners are more closely connected, and the division of labor and cooperation is more orderly. The data for the four dimensions of social engagement mainly come from the interaction situation in the discussion area. The interaction frequency between each learner and others is recorded, to calculate the value of the four dimensions. The four sub-dimensions of social engagement are analyzed using UCINET software.
To sum up, according to the existing engagement analysis model of online learning, this research divided the online learning engagement model into these four dimensions: cognition, behavior, emotional, and social engagement, in combination with different analysis methods. The process of online learning engagement is comprehensively analyzed to construct an online learning engagement analysis model, as shown in Figure 1.

4. Data Sources

The research data came from the SPOC course Secondary School Geography Curriculum Standards and Textbooks Research, which was taught in Chinese. The teaching process was recorded on the SPOC learning management platform, including students watching courseware, participating in discussions, teachers releasing learning tasks, and organizing teaching activities and assessments. The platform data can reflect the course learning interaction process more completely. In this study, a semester course during the pandemic was selected as the research subject. The course content was composed of six modules, and there were fifty-nine students, two teaching assistants, and one teacher in the whole class. The students participating in this course were all undergraduate normal students of geography science. In this study, two discussion forums in the course were examined: the course assignment forum and the voluntary question and answer (Q&A) forum. There were thirteen topics (Table 3) and 658 interactive discussion posts in the course assignment forum, known as course assignment posts in the study. The topics in the course assignment forum were the content of the coursework and course assignments assigned by the instructor that were part of the course requirements. Course assignment posts were used for cognitive engagement analysis. The voluntary Q&A forum had thirteen topics and twenty-six discussion postings, known as Q&A posts in the study. The discussions were about students’ queries in the course and were voluntary. Posting and responding to peers’ posts in the voluntary Q&A forum was encouraged during the course. Q&A posts were used for behavioral engagement analysis and social engagement analysis.
This study took two weeks as the data collection period and collected students’ behavior data and text data in sections several times. In the dimension of cognitive engagement, first of all, 658-course assignment posts in the course assignment forum were organized according to the time sequence. Then, according to Bloom’s revised taxonomy of educational goals in cognition, the course assignment posts were analyzed and coded. In the dimension of behavioral engagement, the individual behavior logs of the platform were mainly analyzed. Additionally, the data for the emotional engagement dimension mainly came from distributed self-reports; a total of fifty-nine self-reports were collected. The social engagement dimension data mainly came from the interaction situation of the Q&A forum. The interaction frequency of the Q&A forum was recorded to calculate the social engagement of the participants.
In this study, the learning performance was strictly evaluated according to the course standard, where the usual grade accounts for 50% and the final grade accounts for 50%. In terms of the usual grade, students’ performance on in-class supplemental tests and their course assignment posts were taken into account. In addition, students gained bonus points for actively participating in class discussions and posing inquiries in the voluntary Q&A forum. In terms of the final grade, students participated in the final exams organized by the university to determine final grades. The accounting was carried out by the teaching assistant to ensure the authenticity and effectiveness of the learning performance.

5. Results

5.1. Descriptive Analysis of Online Learning Engagements

A descriptive analysis is conducted of the sub-dimensions under the online learning engagement separately, as shown in Table 4. The maximum value, minimum value, mean value, and standard deviation jointly reflect each dimension of the online learning engagement. More detailed discussions based on the descriptive data are portrayed below.
According to Bloom’s revised classification method, the six cognitive engagement subdimensions,—namely, remember, understand, apply, analyze, evaluate, and create—are used to reflect students’ cognitive engagement. As the course progresses, the cognitive demands placed on students by the course tasks gradually develop from the concrete (e.g., Topics two and three mainly required students to “remember” and “understand”) to the abstract (e.g., Topics twelve and thirteen mainly required students to “evaluate” and “create”). Course assignment posts were assigned values according to the frequency of each cognitive engagement dimension in student discussion. The results show that among the six sub-dimensions, only “analyze” applies to all the course assignment posts, while the other five are absent in some of the course assignment posts. In terms of frequency, “analyze” is the most, much higher than the other sub-dimensions, followed by “apply,” but “understand” is the least. In terms of individual variability, the number of students who fail to reach the average course assignment post on “analyze” is the largest, while the greatest variation is found in “analyze,” followed by “evaluate,” and “understand“ is the lowest.
Behavioral engagements were divided into four specific learning behavioral engagements based on the number of Q&A topic posts, replies to others, peers’ replies, and teachers’ replies to collectively represent this dimension. The results show that the overall frequency was low. The data for the behavior “Q&A topic posting,” which appears most frequently in comparison, shows that the average number of topic posts in a voluntary Q&A forum is 0.2 per person, with a standard deviation of 0.58, indicating that most students do not have behavioral engagement when learning online, and the difference in this kind of learning behavior between students is the largest.
Emotional engagement is investigated using self-reports on the curiosity, pleasure, belonging, and boredom that fifty-nine students engaged in when learning online. According to the principle that there are three questions in each dimension and five points for each question, the final score is the average of each dimension, and the full score is five. Students have a maximum score of five in terms of curiosity, pleasure, and sense of belonging, but only a maximum score of four for boredom. In comparing the amount of engagement in each dimension, curiosity is the most invested by students, followed by pleasure, and boredom is the least. In terms of individual variability, students differ more in their sense of belonging compared to the other emotional engagements.
The four sub-dimensions of social engagement are degree centrality, closeness centrality, betweenness centrality, and cohesive subgroups. UCINET software is used to analyze these sub-dimensions. The results show that degree centrality has the greatest individual variability, with a maximum of four and a minimum of zero people connecting to the learner in the course, and a standard deviation of 0.83, indicating a large variation in course learning interactivity among students. Compared to the other social engagement dimensions, the cohesive subgroup has less variability, with each student participating in at least one learning group.

5.2. The Relationship between Online Learning Engagements and Learning Performance

The Pearson correlation analysis between the sub-dimensions under the online learning engagement dimension and learning performance are conducted separately, using a two-tailed test at the significance level (p < 0.05) as shown in Table 5.
Among the cognitive engagements, only “analyze” is significantly positively correlated with learning performance (p < 0.05) with a correlation of 0.271, while “memory,” “comprehension,” “evaluation,” and “creativity” are not significantly positively related to learning performance. Three dimensions of behavioral engagement are all significantly positively correlated with learning performance (p < 0.05). In particular, the correlation between replies to others and learning performance is highly significant (p < 0.01), with correlations of 0.293, 0.352, and 0.305, respectively, while the behavior of peers’ replies is not significantly positively correlated with learning performance. Two dimensions of emotional engagements, curiosity and pleasure, are significantly positively correlated with learning performance, with highly significant correlations (p < 0.01), with correlations of 0.379 and 0.373, respectively. However, belonging is not significantly positively correlated with learning performance, and boredom is not significantly negatively correlated with learning performance. Two social engagement dimensions, degree centrality and betweenness centrality, are significantly positively correlated with learning performance (p < 0.05), with correlations of 0.311 and 0.320, respectively. While closeness, centrality, and cohesiveness within a subgroup are not significantly positively correlated with learning performance.

6. Discussion

Students’ participation in different dimensions of online learning engagement varies widely, and especially the highest in emotional engagement. Every student has different degrees of emotional engagement when learning online, followed by cognitive engagement, while behavioral engagement is the lowest. Most students do not participate in the behavioral engagement in this study. Due to the low participation in behavioral engagement, the information reflected in social engagement is also not optimistic.

6.1. Engagement in Higher-Order Cognitive Learning Is Obviously Insufficient

Even though the course assignment discussion tasks progressively demanded a higher level of abstract cognition from students, the data indicates that most students concentrate on “analyzing” at the cognitive level but fail to enter the “evaluating” and “creating” stages. This suggests that online learning allows students to make connections between old and new knowledge and develop problem-solving skills but does not provide substantial improvement at higher cognitive levels [37,38]. These results imply that we cannot be too optimistic about the quality of student engagement under the auspices of emergency online learning. In this study, the cognitive level of students does not reach the stage of application and innovation. The reason for this may be that online learning relies more on the autonomy of students, and students need to make more effort to complete online learning than offline learning. However, it is difficult to achieve a high cognitive level of “evaluation” and “creation” in short-term learning, which needs further follow-up research.

6.2. Knowledge Reprocessing Behavior Promotes Learning Performance

Publication of Q&A topic posts, replies to others, and teachers’ responses are all significantly positively correlated with learning performance, with “replies to others” having the strongest correlation, and behavioral engagement in online learning has a strong effect on learning performance. Publication of Q&A topic posts and responses to others are both knowledge-reprocessing behaviors that strengthen students’ deep understanding of knowledge and improve their learning performance. The correlation between teachers’ responses and learning performance reflects the positive influence of teacher support strategies in online education, which can effectively play the role of the teacher as a scaffold and improve the effectiveness of online learning [39]. However, students’ participation in behavioral engagement is low, which may be because this study is limited to a specific online learning platform; nevertheless, there are many novel and flexible online communication platforms from which students can choose. If the discussion mode of the learning platform is not attractive enough, students’ enthusiasm will be inadequate.

6.3. Positive Emotional Engagement Is Beneficial to Learning

The average value of curiosity and pleasure in the dimension of emotional engagement is close to the full score. It indicates high levels of student satisfaction with the course offered online. Compared with other engagement dimensions, emotional engagement has the greatest correlation with learning performance, showing that positive emotional engagement is helpful to improve students’ learning. It is the motivation and product of learning, which are reflected in students’ internal processes and external expressions [40]. The sense of curiosity is the intrinsic motivation for people to pursue new things and acquire new knowledge. Previous studies have shown that many factors trigger it, but online learning as a new form of learning gives students more autonomy, embraces students’ differences, and easily stimulates them to explore knowledge. Berlyne and Gruber et al. show that curiosity can promote the memory effect of the material [41,42]. The assessment of learning performance in this study focuses on students’ cognitive level, and curiosity had a positive impact on learning performance. According to Gao Shenchun, the emotional response is one of the ways for individuals to form self-efficacy [43], and pleasure is a positive academic emotion that can form a higher sense of self-efficacy, which can encourage students to take the initiative to learn and consciously increase their learning investment. However, the sense of belonging was not significantly correlated with learning performance, which is inconsistent with the research of Liu Fenghua et al. [44]. This could be because there is less interactive learning among students in this study, failing to form a high-quality learning group and thus identifying the affiliation relationship of this course.

6.4. Social Engagement Has Great Potential to Improve Learning Performance

This study applies degree centrality, closeness centrality, betweenness centrality, and cohesive subgroup to mutually reflect the influence of social engagement on learning performance. Among them, degree centrality and betweenness centrality are significantly correlated with learning performance. This indicates that when students interact with more peers and teachers in the process of learning and play a mediating role in the communication of other peers, the closer they are to the center of interaction, the better their learning performance will be. The results of the research confirm the conclusion of Blasco-Arcas et al. that interactive learning between teachers and students and between students can effectively improve students’ learning performance [45]. However, in this study, it is obviously noticeable that students’ participation in the dimension of social engagement is very low, and the social difference among students is very evident. Existing studies generally reflect this problem, and improving students’ social learning enthusiasm is an urgent problem to be solved in online learning at present. Wen Shufeng et al. proposed solutions for teachers and students to address this issue: students should consciously strengthen interaction and establish study partners to encourage and cooperate with one another. Meanwhile, teachers should add interesting activities to the course, guide the establishment of study groups, strengthen the proportion of mutual evaluation among students in formative evaluation, and mobilize the positivity of students [35].
Several limitations to this study must be considered. First, a small number of subjects participated in this study, so the universality of the research results may be limited. Future research can combine multiple different online platforms or various courses to conduct online learning engagement studies. Second, in the dimension of cognitive engagement, students’ course assignment discussions are mostly the unified outcome of the learning group, which reflects the overall cognitive level. It could not accurately reflect individual cognitive levels. Third, there are a few dimensions of behavioral engagement, and between behaviors, there is no progression, so it may not be comprehensive enough to measure students’ behavioral engagement in online learning. Future research can set more behaviors with increasing difficulty. Fourth, the questionnaire on emotional engagement had few questions, insufficient to cover all the elements of measuring. Future research methods can include in-depth interviews with students to increase accuracy through qualitative and quantitative research. A serious shortage of effective data on social engagement fails to reflect the real learning context of students, where students’ participation is low. This is also the major problem found in this study. Future research can pay attention to the factors affecting students’ social engagement in online learning. Fifth, in this study, the four dimensions of online learning engagement are quite separate. In fact, the dimensions are not independent of each other. Previous studies have shown that behavioral engagement is the carrier of emotional and cognitive engagement, and emotional and cognitive engagement positively affect learning performance only through behavioral engagement [46,47]. Future studies on the relationship and interaction between the four dimensions of online learning engagement can be carried out.

Author Contributions

Conceptualization, X.Z. and Q.G.; methodology, Y.H. and Z.S.; software, Y.H. and Z.S.; validation, Y.H. and Z.S.; formal analysis, Q.W.; investigation, Q.W.; resources, X.Z.; data curation, Y.H. and Z.S.; writing—original draft preparation, Q.W.; writing—review and editing, Q.G. and F.L.; visualization, Z.S.; supervision, Q.G.; project administration, X.Z.; funding acquisition, X.Z. and Q.G. All authors have read and agreed to the published version of the manuscript.


This research was funded by the Jiangsu Province Office for Education Science Planning, grant number A/2021/05, and by the Jiangsu Education Department, grant number 2022SJYB0235.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Online Learning Engagement Analysis Model.
Figure 1. Online Learning Engagement Analysis Model.
Sustainability 15 04544 g001
Table 1. Description of cognitive engagement dimension.
Table 1. Description of cognitive engagement dimension.
RememberLearners can recall and recognize what they have learned before and can tell the facts as they are.Be familiar with the content and objectives of the secondary school geography curriculum.
UnderstandLearners can understand things, from the existing teaching content to elaborate their own views, and establish the new knowledge and the original knowledge of the connection.We hope to master the meaning, value, and application of secondary school geography standards through this course.
ApplyLearners can use existing knowledge to solve problems, which is closely related to procedural knowledge, and can apply what they have learned to real cases.I hope that through my well-designed curriculum, I can make the knowledge understandable and easy to memorize so that students can develop a love for geography.
AnalyzeLearners are able to break down complex knowledge, understand the connections between various parts, and disassemble and analyze the questions and content provided.As geography educators, we should pay attention to new ideas and concepts in the fields of education and psychology in our geography teaching activities, draw on their research results appropriately in teaching, pay attention to the research and use of geography teaching methods, make full use of modern media such as cameras, photography, video, and slide projection to increase the capacity of teaching activities and stimulate students’ enthusiasm and interest in learning.
EvaluateLearners can raise questions, make value judgments on what they have learned according to internal and external standards, and effectively evaluate daily case teaching.It is in line with students’ cognitive rules, is closer to students’ lives, facilitates students’ better experience of geographic knowledge, focuses on the investigation of geographic problems, and pays attention to the cultivation of students’ geographic practical power.
CreateLearners can reorganize elements into new patterns or structures, combine what they have learned, and independently complete personalized research programs.I think that in addition to the four core literacies, the skills of using maps, analyzing problems from a spatial perspective, having a sense of home and country, and having a sense of local feeling are also important.
Table 2. Specific dimensions and questions of emotional engagement.
Table 2. Specific dimensions and questions of emotional engagement.
CuriosityQ1-1: I am curious about the course content.0.773
Q1-2: I am curious about the course resources.
Q1-3: I am curious about the way the course is taught.
PleasureQ2-1: I am pleased with the course content.0.787
Q2-2: I am pleased with the course resources.
Q2-3: I am pleased with the way the course is taught.
BelongingQ3-1: I feel a sense of belonging to the interactive content of the course.0.893
Q3-2: I feel a sense of belonging to the interactive objects of the course.
Q3-3: I feel a sense of belonging to the interactive process of the course.
BoredomQ4-1: I am bored with the course content.0.816
Q4-2: I am bored with the course resources.
Q4-3: I am bored with the way the course is taught.
Table 3. Topics in the course assignment forum.
Table 3. Topics in the course assignment forum.
NumberDiscussion TopicDiscussion Content Introduction
1Pre-course Learning Needs SurveyThink carefully and discuss the questions below:
What knowledge do you want to acquire through this course (Secondary School Geography Curriculum Standards and Textbook Research)? What competencies do you hope to develop? What are your aspirations for your future career as a geography teacher? What is your biggest confusion at the moment?
2Guid question: How effective has the reform of geography education in China been in the last 40 years?Review the literature and discuss the questions below: Since the reform and opening to the outside world, what has been the process of geography education reform in China? What outstanding achievements have been made? What are the problems that need to be solved in the current geography curriculum reform?
3Classroom Seminar: Stages in the development of the geography curriculum after the founding of the People’s Republic of ChinaReview the literature and discuss the questions below: What are the broad stages in the development of the geography curriculum after the founding of the People’s Republic of China? What are the main features of each stage?
4Classroom Seminar: What are the main functions of the Geography Curriculum Standards?Think about and discuss the questions below:
What are the main functions played by the Geography Curriculum Standards in the implementation of the curriculum? Which of these functions plays a more important role?
5Classroom Seminar: Insights from the development of Geography Curriculum Standards (Syllabus)Think about and discuss the questions below:
What trends in geography education reform can the development of the Geography Curriculum Standards (Syllabus) illustrate? What insights have you gained as a future teacher?
6Classroom Seminar: Criteria for a good lessonReview the literature and discuss the question below:
In combination with your own classroom observations, what basic criteria do you think a quality geography lesson should meet?
7Pre-class Seminar: The most important geography curriculum ideasRead the various versions of the Geography Curriculum Standards and discuss the questions below in groups:
What do you think are the three most important geography curriculum ideas? And why do you think so?
8Classroom Seminar: Curriculum ideas reflected in the given teaching segmentRead the teaching segment from Ms. Zhu’s lesson on “Spatial Structure of Cities” and discuss the questions below:
Which geography curriculum ideas are reflected in this teaching segment? What geographic skills does this teaching segment help to develop in students?
9Classroom Seminar: Apart from the four geography core literacies, what other geographical literacies are also important?Review your own learning and life experiences and discuss the questions below:
Apart from the core geographical literacies, what other geographical literacies do you think are also important in the lifelong development of people?
10Classroom Seminar: What teaching methods and approaches are used in the lesson “Meteorological Hazards”?Watch the video of the lesson “Meteorological Hazards” and discuss the questions below in groups:
What are the methods and approaches used in the lesson from both the teaching and learning perspectives? Which of these are inquiry-based?
11Post-class analysis: The main teaching methods used in the lesson “The Hydrosphere and the Water Cycle”In conjunction with the lesson “The Hydrosphere and the Water Cycle,” discuss the question below:
What teaching methods are used during the lesson?
12Cooperative study task: Explore the characteristics of the geography textbook compilationComplete the following tasks in groups of six, with a clear division of labor:
Select a set (or a volume) of high school geography textbooks, skim them, and analyze how they reflect the Geography Curriculum Standards.
Express individual views and record them on draft paper.
Organize the group’s opinions, summarize the features of the textbooks’ compilation, and draw a visualization. Analytical reports are expected to be submitted.
Present the findings and send a representative to share them.
Comment on each other’s work, possibly by designing evaluation scales for intergroup assessment.
13Pre-class Seminar: Characteristics of your ideal geography textbookGeography textbooks can improve the quality of the population and develop the core geography literacy of middle school students. The new curriculum reform emphasizes the importance of being a textbook developer. Think about and discuss the questions below:
What are the characteristics of an ideal geography textbook in your mind? What suggestions do you have for the construction of geography textbooks?
Table 4. Descriptive Analysis of Online Learning Engagement.
Table 4. Descriptive Analysis of Online Learning Engagement.
DimensionMaxMinMeanSD 1
Cognitive EngagementRemember501.951.09
Behavioral EngagementNumber of Q&A Topic Posts300.20.58
Replies to Others100.050.22
Peers’ Replies200.050.29
Teachers’ Replies300.190.57
Emotional EngagementCuriosity52.334.160.65
Social EngagementDegree Centrality400.290.83
Closeness Centrality1.9200.260.66
Betweenness Centrality300.110.55
Cohesive Subgroup311.150.41
1 Standard Deviation.
Table 5. Correlation between online learning engagements and learning performance.
Table 5. Correlation between online learning engagements and learning performance.
DimensionLearning Performance
Cognitive EngagementRemember0.069
Analyze0.271 *
Behavioral EngagementNumber of Q&A Topic Posts0.293 *
Replies to Others0.352 **
Peers’ Replies0.022
Teachers’ Replies0.305 *
Emotional EngagementCuriosity0.379 **
Pleasure0.373 **
Social EngagementDegree Centrality0.311 *
Closeness Centrality0.256
Betweenness Centrality0.320 *
Cohesive Subgroup0.206
* p < 0.05, ** p < 0.01.
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Zhu, X.; Gong, Q.; Wang, Q.; He, Y.; Sun, Z.; Liu, F. Analysis of Students’ Online Learning Engagement during the COVID-19 Pandemic: A Case Study of a SPOC-Based Geography Education Undergraduate Course. Sustainability 2023, 15, 4544.

AMA Style

Zhu X, Gong Q, Wang Q, He Y, Sun Z, Liu F. Analysis of Students’ Online Learning Engagement during the COVID-19 Pandemic: A Case Study of a SPOC-Based Geography Education Undergraduate Course. Sustainability. 2023; 15(5):4544.

Chicago/Turabian Style

Zhu, Xuemei, Qian Gong, Qi Wang, Yongjie He, Ziqi Sun, and Feifei Liu. 2023. "Analysis of Students’ Online Learning Engagement during the COVID-19 Pandemic: A Case Study of a SPOC-Based Geography Education Undergraduate Course" Sustainability 15, no. 5: 4544.

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