Research on the Engagement of University Students in Practical Learning of Ideological and Political Theory Courses Using the Smart Teaching System ()
1. Research Background
The ideological and political work in colleges and universities is related to three fundamental questions (Wu & Hu, 2016): What kind of individuals are colleges and universities shaping? How are they cultivating these individuals? And for whom are they nurturing these individuals? Ideological and political practice education in colleges and universities serves as an effective complement to classroom-based theoretical education. It plays a vital role in promoting students’ understanding of ideological and political theory and their ability to apply theoretical knowledge to practical situations (Liu & Huang, 2022).
In recent years, with the continuous development of information technology such as big data, cloud computing, and artificial intelligence, higher education is transitioning from the information age to the intelligent age (Zhang, 2019). Consequently, there is a growing number of teachers of ideological and political theory courses in colleges and universities relying on the increasingly popular smart teaching system to employ digital methods for practical teaching. They have extended and expanded the practical teaching of ideological and political theory in both content and format, achieving certain levels of success and effectiveness.
The smart teaching system refers to an integrated educational technology platform that leverages artificial intelligence, data analytics, and interactive digital tools to facilitate teaching and learning processes. According to Chen and Li (2020), smart teaching systems typically incorporate features such as personalized learning paths, real-time feedback mechanisms, interactive content delivery, and learning analytics to enhance educational outcomes. Wang (2021) further defines smart teaching systems as digitalized platforms that support collaborative learning environments while providing adaptive content based on learner behaviors and performance data.
From a nationwide perspective, smart teaching in colleges and universities is currently in a phase where both hardware and software facilities are becoming more widespread (Jiang et al., 2021). Teachers’ utilization of smart teaching systems for practical teaching is also in the early stages of practical teaching reforms. To further enhance the positive impact of information technology in practical teaching for ideological and political theory courses, it is crucial to understand the learning dynamics of university students within the smart teaching system.
The key to the reform of practical teaching in ideological and political theory courses lies in harnessing the active role of students. Scholars widely agree that learning engagement is no longer conceptualized as an inherent attribute of an individual, but rather as a malleable state influenced by various factors such as the environment and individual characteristics (Lu et al., 2021). A comprehensive understanding of the level of engagement of university students in practical teaching in a smart learning environment is beneficial for colleges and universities to optimize the design of practical teaching in ideological and political theory courses, offering effective guidance and regulation for the thoughts and behaviors of university students. In this paper, a random sampling approach is adopted to investigate the participation of university students in the central region of China in practical ideological and political theory teaching activities within a smart learning environment. The research aims to conduct an in-depth analysis of the characteristics of student engagement in practical activities related to ideological and political theory courses.
2. Literature Review
2.1. Smart Teaching Systems in Higher Education
Smart teaching systems have gained significant attention in educational research over the past decade. Huang et al. (2019) highlighted that smart teaching systems represent the integration of multiple technologies that create personalized learning environments responsive to students’ needs and learning styles. Zhang (2019) emphasized that these systems utilize artificial intelligence to provide adaptive learning experiences and generate data-driven insights about student performance.
In the context of ideological and political education, smart teaching systems offer unique opportunities to transform traditionally lecture-based courses into more interactive and engaging learning experiences. Yang (2022) found that digital technologies can enhance ideological and political education by providing more diverse learning resources and creating more accessible platforms for student discussion and reflection. However, as Liu (2021) points out, the mere implementation of technology does not guarantee improved educational outcomes without appropriate pedagogical adaptation.
2.2. Learning Engagement Theories
Learning engagement has been extensively studied as a critical factor in educational outcomes. Fredricks et al. (2004) conceptualized engagement as a multidimensional construct encompassing behavioral, emotional, and cognitive components. Behavioral engagement refers to observable participation in learning activities; emotional engagement involves affective reactions to learning; cognitive engagement refers to the psychological investment in understanding complex ideas and mastering difficult skills.
The Social Cognitive Theory developed by Bandura (1986) provides a theoretical foundation for understanding engagement in learning environments. This theory posits that the interplay among individuals, their environments, and their behaviors forms a triadic reciprocal causation structure (Fan & Zhang, 2007). This perspective underscores that learning is a product of the interaction between individuals and their surroundings. Starting from the triadic reciprocal determinism of “individual-environment-behavior,” it explores and discusses the role of self-efficacy, its conditions, and its regulatory effects on behavior.
Ji (2018) proposed the ICAP cognitive engagement learning model, which categorizes student behaviors into four types based on the degree of cognitive engagement demonstrated in their external behaviors: Interactive, Constructive, Active, and Passive. Among these, Constructive and Interactive learning fall under deep cognitive engagement, while Passive and Active learning are associated with shallow cognitive engagement. This model provides a useful framework for analyzing students’ engagement with smart teaching systems.
2.3. Practical Teaching in Ideological and Political Courses
Practical teaching in ideological and political courses has been recognized as essential for translating theoretical knowledge into lived experience. Wang (2021) noted that practical teaching builds on and expands upon theoretical teaching, with its main advantage lying in being intuitive, which helps to engage students’ emotions through real-life scenarios, and fosters their agency and creativity.
Several researchers have examined the integration of technology into the practical teaching of ideological and political courses. Jiang et al. (2021) found that online practical teaching faces unique challenges related to teacher preparedness and system design. Liu and Huang (2022) highlighted the importance of innovation in practical teaching methods to maintain relevance and effectiveness in the digital era.
Despite growing interest in this area, there remains a gap in understanding how university students engage with smart teaching systems, specifically in the context of practical activities for ideological and political theory courses. This study aims to address this gap by examining student engagement patterns and identifying factors that influence the effectiveness of smart teaching systems in this specific educational context.
3. Research Methodology
3.1. Theoretical Framework
This research is grounded in the Social Cognitive Theory of Bandura, which posits that the interplay among individuals, their environments, and their behaviors forms a triadic reciprocal causation structure. Triadic reciprocal determinism suggests that there are mutual influences and determinants between any two of the three elements: individual, environment, and behavior. This research seeks to analyze the impact of smart teaching systems on individuals through behavioral measurement, thereby providing robust insights into optimizing teaching strategies and instructional design.
Behavioral engagement refers to observable behaviors related to learning, such as persistence, interaction, participation, and more. These behaviors serve as a means to understand and characterize cognitive and emotional engagement (Wang & Feng, 2019). Behavioral engagement exhibits observable characteristics, and by measuring these external behaviors, one can assess students’ levels of cognitive engagement.
3.2. Research Design and Instruments
The practical teaching content in the ideological and political theory course, when using the smart system, consists of four main parts: practical project design, practical project data support, practical activity process management, and practice results publication and evaluation. In this research, the four aspects of practical teaching activities in ideological and political theory courses are taken as the horizontal dimension, and the Interactive, Constructive, Active, and Passive behaviors in the ICAP cognitive engagement learning model are taken as the vertical dimension.
Based on this framework, a questionnaire was developed with a set of 48 core questions designed to assess specific aspects of university students’ engagement in practical teaching activities using smart teaching systems. These questions examined how students use smart teaching systems to access practical projects, obtain practical data, participate in practical activities, and present and evaluate practice results.
3.3. Sample and Data Collection
This research focuses on full-time undergraduate students attending colleges and universities in the central region of China. The rationale behind this choice is that this region falls within the median range of demographic and income indicators in China, making it a more convincing representative compared to other regions.
The survey targeted full-time undergraduate students and employed a simple random sampling method. A total of 1,372 questionnaires were distributed, with 1,211 returned and 1,122 of them considered valid, representing an effective response rate of 93%. Among the respondents, 875 were male, accounting for 78% of the total, while 247 were female, constituting 22% of the total. In terms of academic disciplines, there were 816 students from engineering disciplines, 191 from natural sciences, and 115 from humanities and social sciences. Regarding their household registration, the majority of respondents came from rural areas, 56.3%, while those with urban household registration accounted for 43.7%.
3.4. Data Analysis Methods
The data were analyzed using SPSS software. Descriptive statistics were used to understand the frequency distributions and percentages of responses across different dimensions of engagement. Correlation analysis was employed to examine relationships between system usage and student satisfaction.
Based on the results of quantitative data analysis and the purpose of this research, 31 individuals were selected from the survey respondents for individual case interviews. These interviews were recorded, transcribed, and analyzed using thematic analysis to identify common patterns and themes in students’ experiences with the smart teaching system.
4. Results and Analysis
4.1. Overall Analysis of the Relationship between the Use of the
Smart Teaching System in Ideological and Political Theory
Courses and Satisfaction
The survey indicates a positive correlation between the active use of the smart teaching system for ideological and political theory courses and the sense of gain from ideological and political theory courses. The stronger the initiative of the students, the stronger their sense of gain and the higher their satisfaction. “The smart teaching platform is very user-friendly. As long as you put in some effort, you can find a lot of high-quality and accurate materials, which can save a lot of energy and time” (said W, a pseudonym, the same below). “During the practical activities, I use the platform for group discussions and establish shared resources. We write and revise the practice results together, and the effect is really good” (said L). “The teacher can track the progress of our group’s practical work through the smart teaching system, and we are also encouraged by watching the progress bar change” (said Q). (Table 1)
Table 1. Correlation analysis between engagement and satisfaction.
|
|
Do you consider yourself actively using the smart teaching system for ideological and political theory courses? |
Do you feel that you have gained a lot from practical activities in ideological and political theory? |
Do you consider yourself actively using the smart teaching system for ideological and political theory courses? |
Pearson correlation |
1 |
0.055** |
Significance (bilateral) |
|
0.000 |
N |
1112 |
1090 |
Do you feel that you have gained a lot from practical activities in ideological and political theory? |
Pearson correlation |
0.055** |
1 |
Significance (bilateral) |
0.000 |
|
N |
1090 |
1090 |
**Significantly correlated at the .01 level (bilateral).
4.2. Students Tend to Show Underactive Exploration and Predominantly Use the Smart Teaching System Passively
From the distribution of survey data, it can be observed that 77% of university students have utilized the smart teaching system in the practical teaching activities of ideological and political theory courses. When asked, “Why do you use the smart teaching system?”, 88.7% of the respondents stated that they used the smart teaching system because their teachers required it for conducting practical activities. When further questioned about “What practical teaching tasks do you complete using the smart teaching system?”, over half mentioned checking in completed tasks, filling in practical projects, receiving homework assignments from their teachers, etc. Only 12.3% indicated that they occasionally used the system to search for more suitable materials and for self-diagnosis.
Further interviews found that the reasons for university students’ passive use of the smart teaching system in their majors are as follows:
Firstly, the smart teaching systems currently used in colleges and universities are all general education teaching systems, which offer abundant but often too heterogeneous information. “There is so much and so diverse content in the smart teaching system that I have no idea how to find the materials” (said C). “All sorts of information are piled up together, and it’s exhausting to sift through and identify what’s relevant to me. I’d rather use professional search engines like Baidu, which are faster and more accurate” (said L).
Secondly, there are numerous task points, but the requirements are not particularly challenging, and they seem to be designed mainly to monitor students’ shallow cognitive behaviors. “Each practical activity has multiple task points, including attendance check-in, reading check-in, and presentation check-in. Each task point contributes to the final score, so we have to remind each other not to miss any check-in” (said D). “There are too many task points in the process assessment, and just keeping up with the tasks assigned by the teacher is exhausting” (said F).
Thirdly, the setup of various components in the practical teaching of ideological and political theory courses limits the space for students’ independent exploration. According to the survey, 69% of students mentioned that practical projects can only be assigned by teachers, and students have limited autonomy in choosing them. Every aspect of the practical process is teacher-led, and students must align with the teacher’s requirements. “The practical projects are determined by the teacher, and we can only choose from the ones provided” (said C). “The way practical activities are conducted is decided by the teacher, and if we don’t follow it, we can’t guarantee it will be deemed qualified” (said Z).
From an overall perspective, teachers of ideological and political theory courses primarily rely on the smart teaching system to control the entire practical teaching process. This process is predominantly characterized by “teacher-led, student compliance”, where teachers have not effectively employed a combination of optimal strategies to stimulate students’ proactivity and engagement. Consequently, university students’ usage of the smart teaching system remains largely confined to fundamental functions.
4.3. Information Dissemination Primarily Occurs in One Direction,
with a Lack of Effective Communication for Diverse and Mixed Information
According to a survey, 81% of university students held that there is little difference between using the smart teaching system and platforms like WeChat and QQ groups, which are all used to receive various types of information. In the smart teaching system, teachers of ideological and political theory courses assign practice tasks, and then students receive them; teachers post the practice process check-ins, and students check in every task completed; teachers distribute practical assignments, and students complete these assignments; and teachers offer practical materials, and students access and read them. The primary difference between the smart teaching system and social media platforms lies in the system’s ability to record each step of the practical teaching process, providing evidence for the final comprehensive evaluation. From the students’ perspective, “the smart teaching system, in reality, adds to our workload, as it merely delivers information but doesn’t address our questions” (said W). “We wish to have more face-to-face communication with our teachers. There are many areas where we lack clarity and need direct guidance from our teachers, but the smart teaching system cannot fulfill this need” (said L).
According to the classification of the ICAP cognitive engagement learning model, Table 2 reveals that 90% of university students are in a state of shallow cognitive engagement, and only around 10% are engaged in deep cognitive learning. Interviews with students indicated that they were not particularly satisfied with this degree of learning engagement. “I actually look forward to participating in practical projects that interest me, but I don’t have many options,” said one student. “Sometimes, the teachers ask us to design our own practical projects and upload them to the smart platform. However, I’m not very skilled at it, and the teachers also provide a lot of choices, so I don’t see the need to do it” (said Z). Despite their dissatisfaction with how they access practical projects, students showed no actively seeking change. The primary reason for this is that the smart teaching system has not effectively played a role in stimulating students’ intrinsic motivation in the practical teaching of ideological and political theory courses.
Table 2. Sources of practice projects—methods of acquiring practice projects.
Practical Project Access |
Frequency |
Percentage |
Effective Percentage |
Assigned by teachers, picked up by students |
776 |
69.16 |
69.16 |
Provided by teachers, selected by students |
235 |
20.94 |
20.94 |
Determined through communication between teacher and students |
107 |
9.53 |
9.53 |
Explored by students, supported by teachers |
4 |
0.36 |
0.36 |
Similar situations to those in Table 2 are also observed in other aspects of practical teaching in ideological and political theory courses, as indicated in Table 3 and Table 4. Close to 90% of students relied on teachers to provide extended materials through the smart teaching system. Only a very small number of students collected relevant practical teaching materials within the system. “The practical projects are given by the teacher, so the materials the teacher pushes are surely the most effective” (said F). “Viewing materials set by the teacher earns us points, but looking at projects we find ourselves doesn’t earn us any points.” Similarly, almost 88% of students completed the practical activities of ideological and political theory courses under the guidance of teachers. The teacher’s pre-designed activities make up a larger portion of the total practical activities, and students play a role in executing project activity designs. This approach tends to direct the goals of student practical activities towards more utilitarian outcomes. “Practical activities in ideological and political theory courses are quite easy to pass. You just need to check in on time...With today’s technology, I don’t even have to go to the practice site. I can ask my classmates to take a photo for me or bring my phone to check in and complete the attendance, by which I can get some points” (said T). This attitude has significantly diminished the effectiveness of education of practical teaching in ideological and political theory courses.
Table 3. Access to practice information—extended materials.
Access to Extended Practice Materials |
Frequency |
Percentage |
Effective Percentage |
Teachers post audio and video material assignments |
678 |
60.43 |
60.43 |
Teachers provide links to audio and video materials |
324 |
28.88 |
28.88 |
Students suggest, and teachers adopt and then push |
69 |
6.15 |
6.15 |
Students rely on the platform for free access |
51 |
4.55 |
4.55 |
Table 4. Practical activity promotion—process recording.
Practice Process Record |
Frequency |
Percentage |
Effective Percentage |
Teachers set up a single check-in way in advance |
812 |
72.37 |
72.37 |
Teachers offer multiple check-in ways |
172 |
15.33 |
15.33 |
Teachers negotiate with students on recording methods |
81 |
7.22 |
7.22 |
Students innovate multiple ways of recording |
57 |
5.08 |
5.08 |
According to the survey, it is evident that the smart teaching system has not enhanced the interactivity of practical teaching activities in ideological and political theory courses. The system is still predominated by one-way communication. Teachers in colleges and universities who teach ideological and political science courses have not yet shifted to embrace a more progressive approach to teaching. They are not well-versed in utilizing new media technology and lack a comprehensive understanding of online practical teaching. Consequently, they struggle to adapt to the non-face-to-face mode of teaching ideological and political science courses online (Jiang et al., 2021).
4.4. The Utilization of Interactive Functions Is Low, Resulting in Insufficient Student Engagement
Existing research has demonstrated that social interaction has a positive impact on both deep and shallow cognitive engagement among students (Lu et al., 2021). Additionally, positive relationships between teachers and students, as well as interpersonal relationships, significantly influence students’ cognitive engagement (Tucker et al., 2010). The smart teaching system incorporates various interactive features, such as a group project section, intra-group and inter-group evaluation section, and teacher-student discussion section. These features overcome the limitations of physical space and time, enabling broader interactions between students and teachers, among classmates, and among project groups. This not only enhances vertical connections but also facilitates horizontal connections, effectively addressing the shortcomings of traditional practical teaching methods that are limited by factors such as manpower, resources, and environmental constraints, which hinder real-time interaction. However, the findings of this survey indicate that the smart teaching system did not improve the practical teaching of ideological and political theory courses in this regard. (Table 5)
Table 5. Presentation of practice results—project evaluation.
Practical Project Evaluation |
Frequency |
Percentage |
Effective
Percentage |
Teachers give the total score directly |
697 |
62.12 |
62.12 |
Teachers give scores based on practice stages |
292 |
26.02 |
26.02 |
Set the attention level and give scores based on the level of enthusiasm |
65 |
5.79 |
5.79 |
Combination of inter-group evaluation and teacher’s overall evaluation |
68 |
6.06 |
6.06 |
Currently, in the widely adopted smart teaching systems at colleges and universities, there are modules for student peer evaluation and team evaluation. These features reduce the complexity of using multiple evaluation methods and enhance the accuracy and traceability of evaluations. However, the survey revealed that nearly 90% of practical teaching activities in ideological and political theory courses relied on direct teacher grading, where teachers played a significant role in evaluating students’ practice performance, and students had a limited sense of participation. Only 6.06% of students had ever used a combined approach of peer evaluation and teacher evaluation. “Teachers are not always fully aware of each student’s effort. Many students are dedicated and enthusiastic in their practical activities, but they receive low scores” (said Q). “Some students may not be skilled at presenting themselves. Their uploaded materials may lack embellishment. On the other hand, some students are adept at online presentations. Even though they may not invest much in practical activities, they present their work effectively. We feel it’s not very fair” (said P).
4.5. The Linkage between Online and Offline Teaching Is Weak, Leading to a Relatively Poor Student Experience
Practical teaching in ideological and political theory courses builds on and expands upon theoretical teaching. Its main advantage lies in being intuitive, which helps to engage students’ emotions through real-life scenarios, and fosters their agency and creativity (Wang, 2021). In this context, the smart teaching system plays an intermediary role in bridging the offline experience with online accumulation, offline perception with online reflection, and offline intuition with online expansion. It’s not just a tool for disseminating information; rather, it serves as a crucial medium for the spiral progression from theory to practice and back to theory.
According to the survey (refer to Tables 2-5), there is a problem with the weak linkage between online and offline components in practical teaching of ideological and political theory courses in colleges and universities, including practical project design, practical project data support, practical activity process management, and practice results publication and evaluation. As a result, students have a poor experience in these aspects. Moreover, there is a varying degree of disconnect between students’ offline practical activities and the online aspects related to accumulation, reflection, and expansion. “The smart teaching system is just like a mobile notebook where we just input practical content according to the teacher’s requirements,” said one student. “There are so many features in today’s smart teaching systems, and I don’t feel like they provide any substantial help to me. Instead, they increase the workload. Initially, all we had to do was write a report after completing a practical activity, but now we have to submit a lot of materials, and it doesn’t seem to be very useful” (said P).
4.6. Summary of Findings
The results from the analysis of both quantitative survey data and qualitative interview data reveal several key patterns in university students’ engagement with smart teaching systems in ideological and political theory courses. Overall, there is a positive correlation between active system use and learning satisfaction. However, the current usage patterns demonstrate significant limitations that hinder the full potential of these systems.
Students predominantly use the system passively and primarily in response to teacher requirements rather than for self-directed learning. Information flow is largely unidirectional from teachers to students, with limited utilization of the interactive features that could promote deeper engagement. The evaluation process remains teacher-centered despite the availability of peer assessment tools. Furthermore, there is a disconnect between online system activities and offline practical experiences, creating a fragmented learning experience for students.
These findings suggest that while smart teaching systems have the technological capability to enhance practical teaching in ideological and political theory courses, pedagogical approaches and system implementation strategies need significant improvement to foster deeper cognitive engagement among students.
5. Conclusion
In the wake of the advancement of the information society, the smart teaching system has the potential to save teachers’ energy and time while effectively enhancing the precision, traceability, and objectivity of educational goals. In the context of practical teaching of ideological and political theory courses in colleges and universities, there is a positive correlation between students’ level of engagement and their satisfaction in using the smart teaching system. However, the full potential of smart teaching systems has not been effectively realized, as evidenced by the following: students tend to show underactive exploration and predominantly use the system passively; the system is predominated by teacher disseminating information, with a lack of effective communication for diverse and mixed information; the utilization of interactive functions is low, resulting in insufficient student engagement; and the linkage between online and offline teaching is weak, leading to a relatively poor student experience. University students’ use of smart teaching systems for practical activities in ideological and political theory courses primarily involves shallow cognitive engagement, with limited instances of deep cognitive engagement. Consequently, the educational impact of practical teaching is suboptimal.
According to the research, the reasons for the above problems are as follows:
5.1. Teachers of Ideological and Political Theory Courses Possess Limited Skills in Information Technology, Which Restricts the Teaching Effectiveness
On the one hand, the current teachers of ideological and political theory courses in colleges and universities generally have limited skills in information technology. They are quite proficient in using the basic functions of the smart teaching system but may not be familiar with more advanced modules. On the other hand, these teachers are heavily influenced by traditional teaching methods. They tend to rely on one-way communication, assign tasks, and design standardized processes for practical teaching.
All of these factors undermine the effectiveness of teaching and learning in scenarios involving the smart teaching system.
5.2. The Ineffective Blend of Theoretical and Practical Teaching Methods in Ideological and Political Theory Courses Hampers
the Proper Functioning of the Smart Learning System
Due to various factors, when looking at the per-student engagement, the funding for practical teaching in ideological and political theory courses is limited. There is also a shortage of qualified teaching staff, inadequate educational research in practical teaching, and an absence of up-to-date practical teaching designs and corresponding syllabi or teaching facilities. This results in a disconnect between the practical and theoretical teaching of the course, making it challenging for the smart teaching system to effectively bridge the gap in content deficiencies.
5.3. There Is a Lack of a Course Evaluation System that Aligns with
the Smart Teaching System
The high ratio of teachers to students in ideological and political theory courses is a problem that has persisted for a long time, making it challenging for teachers to cater to the diverse needs of different students. Encouraging individualized intrinsic motivation among university students has been a persistent issue in these courses. Smart teaching systems with adaptive features such as precise content push, automated grading, and real-time tracking can effectively alleviate this problem. However, the implementation of these self-adaptive functions depends on an evaluation system that is in line with the goals of the practical course.
Currently, the practical teaching in ideological and political theory courses in colleges and universities suffers from a dual challenge, namely the lack of a systematic teaching syllabus and the absence of a scientific evaluation system. The traditional evaluation method is severely out of sync with the personalized training goals, thus restricting the capabilities and effectiveness of the smart teaching system.
For the purpose of further leveraging the positive role of smart teaching systems in practical teaching in ideological and political theory courses in colleges and universities, this research suggests the following approaches: Firstly, there should be an emphasis on enhancing the digital skills of teachers of ideological and political theory courses in colleges and universities. This can be achieved through training, seminars, and demonstrations to raise their awareness and competence in information technology. Secondly, widespread research activities in practical teaching should be encouraged. Teachers should be motivated to thoroughly understand the essence of the theory, gain insights into societal and public sentiments, innovate teaching content, and develop up-to-date evaluation standards. This includes developing an evaluation system that combines qualitative and quantitative evaluations, knowledge and value evaluations, outcome and process evaluations, as well as consistency and personalized evaluations. By effectively integrating smart teaching systems with the evaluation system, it becomes possible to achieve sustained motivation for university students and attain the desired educational objectives.
Acknowledgements
This work was financed by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant No. 18JDSZK095).