A Study on the Influencing Factors and Enhancement Strategies of Undergraduates’ Research Quality in the Context of Online Education

With the rapid development of technology, the global education system has been undergoing profound transformation, particularly in the realm of higher education, which bears the critical mission of cultivating future innovative talents (Z​h​o​n​g​,​ ​2​0​0​7). To meet the demands of the digital age, many universities have begun implementing online teaching models to maintain the continuity of educational activities and broaden the accessibility of education (L​i​u​ ​&​ ​Z​h​a​n​g​,​ ​2​0​2​0). This novel teaching approach, with its flexible learning environment and interactive features, presents new opportunities for fostering students’ research interests, practical abilities, and innovative spirit (X​u​e​ ​&​ ​G​u​o​,​ ​2​0​2​0). Despite the widespread impact of this shift on educational models, research on the impact of online teaching on undergraduates’ research quality remains insufficiently explored. In this context, it is particularly important to examine the cultivation of students’ research quality within an online teaching environment.

This study aims to explore the impact of online teaching models on undergraduates’ research quality within the specific context of educational transformation and to propose corresponding improvement suggestions. The primary research questions are as follows: What is the current state of undergraduates’ research quality in the online teaching model? What are the main factors influencing the research quality? How can the optimization of teaching models enhance the research quality? Strategies were formulated in this study to improve the research quality of undergraduates to address these questions, thereby enhancing their research capabilities within the online teaching model and promoting their overall development.

The remainder of this study is structured as follows: Section 2 provides a literature review of related fields. Section 3 defines the core concepts and research methods. Section 4 covers the design and reliability analysis of the research tools. Section 5 presents the result analysis. Section 6 concludes this study and discusses future prospects.

It is essential to clarify the concepts of online teaching and research quality, facilitating the smooth progress of this research.

Originated in the United States in the 1960s, online teaching refers to a new teaching model where learners engage in real-time online learning through internet technology platforms. It involves using the internet to disseminate and provide a comprehensive set of knowledge solutions to create and enhance knowledge performance (T​z​e​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​0​6). In the 2000 Education White Paper (Y​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​2) released by the United States Department of Education, online education has three core elements: (1) implementation of educational and teaching activities via the internet; (2) provision of a new learning method where learners can study anytime and anywhere, altering the relationship between teaching and learning; (3) occurrence within traditional campus teaching environments, unlike traditional distance education. A​n​d​e​r​s​o​n​ ​(​2​0​0​4​) posited that online learning is an effective process for acquiring knowledge and skills through an interactive learning model, where both teaching parties utilize the internet to access high-quality online learning resources. V​a​r​g​a​s​ ​&​ ​T​i​a​n​ ​(​2​0​1​3​) pointed out that online learning is a dynamic concept that fully considers social context, culture, ethics, and other issues, transforming the fundamentally one-sided knowledge exchange between teachers and students.

As the name implies, research quality refers to the qualities that researchers should possess. The abilities encompassed by research quality may vary across different fields. L​u​o​ ​(​2​0​1​4​) proposed that research literacy is the quality demonstrated by researchers through learning or practice in the research process. Z​h​a​o​ ​(​2​0​0​6​) pointed out that teachers’ research literacy refers to their knowledge and cognitive structures in educational research, as well as their specific abilities and scientific qualities for conducting research. Based on the aforementioned literature, the research quality of undergraduates was defined in this study as the qualities that they should possess when engaging in exploratory research, research practice, patent development, and other research activities under the guidance of a mentor. It is a collection of various literacies and abilities, primarily including fundamental qualities such as learning and practice, as well as competencies such as literature retrieval.

Online teaching, a product of the information age, has evolved from early open courses to the current massive open online courses (MOOC). Y​a​n​g​ ​e​t​ ​a​l​.​ ​(​2​0​2​2​) pointed out that early online teaching primarily focuses on distance education. With the development of internet technology, it has gradually transformed into a new educational model. X​i​e​ ​e​t​ ​a​l​.​ ​(​2​0​2​0​) highlighted the advantages of online teaching, such as its flexibility and accessibility, allowing students to learn according to their own schedules and pacing. Additionally, teachers can leverage abundant online resources for instruction. However, online teaching also faces numerous challenges, including low student engagement, insufficient interactivity, and difficulties in ensuring learning effectiveness (Z​h​a​o​ ​e​t​ ​a​l​.​,​ ​2​0​1​8).

Research quality is an indicator that measures the abilities and qualities a student needs to conduct research activities. T​z​e​n​g​ ​e​t​ ​a​l​.​ ​(​2​0​0​6​) proposed that research quality encompasses several aspects, including mastery of specialized knowledge, application of research methods, innovative thinking, and teamwork. In recent years, with the continuous deepening of educational reforms, an increasing number of studies have started to focus on the cultivation of undergraduates’ research quality (M​e​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​1​3). For example, Z​h​a​o​ ​(​2​0​0​6​) found through survey analysis that the lack of practical opportunities is one of the significant factors affecting undergraduates’ research quality. Additionally, H​u​a​n​g​ ​&​ ​C​a​o​ ​(​2​0​0​2​) constructed an evaluation index system to measure the comprehensive quality of research-oriented medical graduate students, which provides a reference for evaluating undergraduates’ research quality.

The continuous advancement of technology has greatly propelled the development of online teaching, leading to a technology-driven transformation of the global education system. Particularly in higher education, the application of technology has brought unprecedented changes to teaching models and student learning experiences. X​i​e​ ​e​t​ ​a​l​.​ ​(​2​0​2​0​) emphasized the widespread application of online teaching, ensuring the continuity of education. Additionally, K​o​n​g​ ​e​t​ ​a​l​.​ ​(​2​0​1​0​), through a comparative study of online teaching models in Chinese and American universities, proposed strategies to enhance the quality of online teaching. Although online teaching promotes flexibility and accessibility in education and provides students with more diverse learning resources and opportunities for autonomous learning, it has unique impacts on undergraduates’ research activities. M​a​ ​(​2​0​2​1​) studied the impact of online teaching on undergraduates’ learning engagement and found that those students face numerous challenges in an online learning environment, such as insufficient self-management skills and difficulties in accessing learning resources. These factors may indirectly affect their research quality. Furthermore, due to the limitations of field research, undergraduates have significantly fewer opportunities for research practice, which is particularly detrimental to the cultivation of their research quality (Y​e​,​ ​2​0​0​0).

Using “undergraduates’ research quality” as the keyword, an index search of all literature in China National Knowledge Infrastructure (CNKI) was conducted in this study to select data from the past decade (2014-2024) for analysis. As shown in Figure 1, academic attention to undergraduates’ research quality fluctuated between 2014 and 2019. It reached a peak in 2018, with an overall declining trend in the past five years. As shown in Figure 2, although the academic dissemination of research generally increased over the past decade, it showed a declining trend in the past two years. As shown in Figure 3, the disciplinary distribution of research is mainly concentrated in higher education, medicine, biology, and organic chemistry. As shown in Figure 4, the keywords include research quality, undergraduates, innovation ability, and research capability.

Although existing studies have explored online teaching and undergraduates’ research quality to some extent, research on the research quality of those students within this new teaching model remains insufficient in the context of the current digital transformation. Particularly in the face of continuously evolving educational environments and learning methods, effective enhancement of undergraduates’ research quality has become an urgent issue. This study aims to fill this research gap by empirically analyzing the current state of undergraduates’ research quality in the context of online teaching and proposing enhancement strategies. The goal is to provide references for higher-education teaching reforms and the cultivation of undergraduates’ research quality.

Taking undergraduates from the Capital University of Economics and Business as an example, four dimensions were analyzed in this study, i.e., foundational research qualities, research competencies, research outputs, and online learning engagement. The aim is to thoroughly examine the current state of undergraduates’ research quality in the online teaching model and explore potential differences across various backgrounds and environments. The main research methods employed in this study include a literature review, a questionnaire survey, and interviews.

1. Literature review: In line with the research subjects of this study, this method involves extensively collecting and reading master’s and doctoral theses, journal articles, books, and other materials related to online teaching models in universities, undergraduates’ learning conditions in online teaching, and research quality, both domestically and internationally. The goal is to summarize existing research findings on undergraduates’ research quality.
2. Questionnaire survey: Based on the research theme and the current state of related research, a questionnaire was designed and distributed to undergraduates at the Capital University of Economics and Business. The collected questionnaire data were then statistically analyzed to understand the current state of their research quality and provide a basis for further research on influencing factors.
3. Interviews: One-on-one interviews were conducted with those undergraduates to understand their actual research quality and their subjective perceptions of factors affecting their research quality. The findings were used to identify factors influencing their research quality in the online teaching model and to propose targeted practical suggestions for improving their research quality.

The questionnaire designed for this study consists of two parts. The first part gathers basic information on the respondents, and the second part investigates the current state of their research quality.

(a) Basic information: This section mainly includes gender, ethnicity, location, age, major, average daily online learning duration, and primary online learning platforms. This information is used to understand the basic profile of the respondents, thereby analyzing the influence of personal background on their research quality in online teaching.

(b) Current state of research quality: This section employs a Likert five-point scale, which covers four dimensions, i.e., foundational research qualities, research competencies, research outputs, and learning engagement. The first three dimensions were determined based on the competency dictionary for talents in the science and engineering system proposed by Z​h​a​o​ ​(​2​0​1​9​) and the comprehensive quality evaluation indicators for research-oriented graduate students proposed by X​u​ ​e​t​ ​a​l​.​ ​(​2​0​0​4​). Using the undergraduates’ learning engagement in online teaching during the COVID-19 pandemic in the study by M​a​ ​(​2​0​2​1​) as a reference, the dimension of learning engagement is used to measure the specific impact of online teaching on undergraduates’ research quality.

The interview scope and questions were determined in this study based on the questionnaire content and survey results, combined with a literature review. The interviews mainly cover the following four aspects: the learners’ self-assessment of their research quality; the problems and difficulties encountered in online learning; the main influencing factors and the extent of their impact on learners’ research quality in the online teaching model; and the improvement measures taken by learners in response to the aforementioned influencing factors.

The questionnaire was distributed online to undergraduates at the Capital University of Economics and Business via the Questionnaire Star platform for a preliminary test. A total of 187 questionnaires were collected, all of which were valid. SPSSAU software was used for reliability and validity analysis.

Reliability refers to the consistency and dependability of the measurement data. Cronbach’s alpha coefficient (Cronbach α) is a commonly used measure of questionnaire reliability. Generally, a value above 0.7 is acceptable, and a value above 0.8 indicates excellent stability and very high reliability. As shown in Table 1, the Cronbach’s α coefficient for this questionnaire is greater than 0.8, indicating very high reliability.

Validity refers to the extent to which a measurement accurately captures the construct it is intended to measure. Factor analysis was employed in this study for the structural validity analysis, which extracts common factors from a group of variables and examines the relationships among the variables to test the validity of the structure. The closer the Kaiser-Meyer-Olkin (KMO) value is to 1, the more suitable the data are for factor analysis. As shown in Table 2, the KMO value for the current state section of the questionnaire is greater than 0.8, indicating that it is suitable for factor analysis.

The factor analysis method was applied to each of the four dimensions separately to determine the principal components of each dimension. Based on eigenvalues greater than 1, items with factor loadings or communalities less than 0.4 were deleted using the maximum variance method. Taking the first dimension of foundational research qualities as an example, it includes five items, i.e., a1, a2, a3, a4, and a5. Each item was individually subjected to factor analysis to test its factor loadings and communalities, all of which are greater than 0.4, indicating no need for deletion or modification. Following this method, the factor analysis was conducted for the other three dimensions, and the results are presented in Table 3.

Except for the dimension of research outputs, each of the other three dimensions has only one principal component, with factor loadings and communalities all greater than 0.4, indicating no need to delete any items. In the dimension of research outputs, the communality of item a12 is less than 0.4. However, considering the short duration of undergraduates’ exposure to research and the difficulty of patent research, as well as the fact that existing related evaluation systems include this indicator, it was decided to retain this item.

The questionnaire link for this study was distributed through teaching WeChat groups, and a total of 200 undergraduates participated in the survey. Among these, 187 valid questionnaires were collected, resulting in an efficiency rate of 93.5%. The basic statistics of the collected questionnaires are shown in Table 4 and Figure 5. The gender distribution of respondents is roughly balanced; the ethnic distribution is skewed towards Han nationality; the location distribution shows a higher concentration in urban areas; the grade distribution is fairly balanced; and the distribution of majors shows a higher proportion of science and engineering disciplines compared to other fields. These distribution patterns are consistent with the actual situation.

As shown in Figure 6, the majority of respondents have an average daily online learning duration of two to four hours, followed by those who study for four to six hours. This indicates that online learning has become the primary learning mode for undergraduates, with most students spending no more than six hours per day on their studies.

As shown in Figure 7, over 70% of the respondents use Tencent Meeting for online learning, making it the most popular platform, followed by Chaoxing Learning (50.27%), Chinese University MOOC (45.99%), DingTalk (36.36%), Tencent Classroom (17.65%), and other platforms (6.42%), such as Qihang Education and Bilibili.

The statistical scores for each dimension of undergraduates’ research quality are shown in Table 5. The dimensions of foundational research qualities, research competencies, and learning engagement have a midpoint of 3 using a Likert five-point scale. The dimension of research outputs consists of binary questions, where 0 represents no and 1 represents yes.

The statistical results indicate that the mean scores for foundational research qualities, research competencies, and learning engagement are all greater than the theoretical average of 3 on the Likert scale, but are still relatively low. This suggests that under the influence of online teaching, there is room for improvement in undergraduates’ foundational research qualities as well as their more specialized research competencies. Additionally, the overall learning engagement in online courses is moderate. Furthermore, the mean score for the research outputs is 0.3619, indicating that undergraduates have limited experience in participating in research projects, publishing research papers, and obtaining patents. Most students maintain a high level of interest and enthusiasm for research activities. Therefore, there is significant room for improvement in the research quality of undergraduates under the online teaching model. The following sections provide an in-depth analysis of the current state of undergraduates’ research quality across various dimensions of the online teaching model.

Foundational research qualities refer to the basic abilities that researchers should possess, including theoretical foundation, practical skills, research attitude, and collaboration abilities. The statistical results for this dimension in this study are shown in Table 6.

The above analysis reveals that the mean score for the foundational research qualities is 3.6652, which is higher than the theoretical average but is still relatively low, indicating that undergraduates’ basic abilities need further improvement. The standard deviation is 1.1711, suggesting a low level of dispersion in undergraduates’ foundational research qualities. By combining the mean scores of individual items with the overall mean score for this dimension, it becomes evident that undergraduates perform better in theoretical foundation and teamwork, while their practical skills and attitudes toward research are not yet ideal. This indicates that under the online teaching model, educators should focus on enhancing undergraduates’ understanding and application of specialized knowledge and emphasize fostering students’ motivation and enthusiasm for engaging in research activities.

Research competencies primarily refer to the abilities that students acquire through learning and practice outside of professional courses, which facilitate the smooth conduct of research activities. These include information retrieval skills, research presentation skills, and data analysis and processing abilities. The statistical results for this dimension in this study are shown in Table 7.

Research outputs refer to the achievements obtained in research activities, which for undergraduates primarily include research papers, awards from research competitions, and patent inventions. The statistical results for this dimension in this study are shown in Table 8.

The above analysis reveals that the average acquisition rate of research outputs is 0.3636, which is significantly lower than the theoretical average of 0.5, indicating a substantial deficiency in undergraduates’ research outputs. Only about one-third of the respondents have achieved research awards, research papers, or patent inventions. This suggests that under the current teaching model, mentors should focus on guiding students in their research activities to improve the conversion rate of undergraduates’ research outputs.

Learning engagement primarily measures the time and effort learners invest in learning activities under the online teaching model. According to the study by M​a​ ​(​2​0​2​1​), it includes four aspects, i.e., overall learning utilization, in-depth understanding of content, teacher-student interaction, and effective guidance from teachers. The statistical results for this dimension in this study are shown in Table 9.

The above analysis reveals that the mean score for research competencies is 3.7741, which is higher than the theoretical average but is still relatively low, indicating that the overall level of undergraduates’ research competencies is moderate. By combining the mean scores of individual items with the overall mean score for this dimension, it becomes evident that respondents have relatively strong information retrieval skills. However, when it comes to more specialized research presentation skills and data analysis abilities, undergraduates’ performance is less than ideal. This indicates that online teaching should focus on developing students’ research presentation skills and data analysis abilities.

To understand the differences in undergraduates’ research quality under different background conditions, background conditions such as gender, ethnicity, and location were used as independent variables in this study to analyze and summarize the differences in research quality levels (W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​1​8).

Using gender as the independent variable, the collected data were subjected to an independent samples t-test, and the results are shown in Table 10. The results indicate that the p-values corresponding to each dimension are all greater than 0.05, suggesting that there are no significant differences in foundational research qualities, research competencies, research outputs, or learning engagement when gender is used as the independent variable. In other words, gender does not impact the level of research quality.

Using ethnicity as the independent variable, the collected data were subjected to an independent samples t-test, and the results are shown in Table 11. The results indicate that the p-values for foundational research qualities and research competencies are 0.001 and 0.007, respectively, which are less than 0.05. The p-values for the other two dimensions are greater than 0.05. This suggests that ethnicity has a significant impact on undergraduates’ foundational research qualities and research competencies, but no significant impact on research outputs or learning engagement. Considering the distribution characteristics of ethnic minorities in China, most of them are located in relatively remote areas where the educational level is relatively underdeveloped, leading to weaker research accumulation among ethnic minority undergraduates.

Using family location as the independent variable, the collected data were subjected to an independent samples t-test, and the results are shown in Table 12. The results indicate that the p-values corresponding to each dimension are all greater than 0.05, suggesting that using family location as the independent variable, there are no significant differences in undergraduates’ foundational research qualities, research competencies, research outputs, or learning engagement. In other words, family location does not impact the level of research quality.

Using grade level as the independent variable, the collected data were subjected to a one-way analysis of variance (ANOVA), and the results are shown in Table 13. The results indicate that the p-values corresponding to each dimension are all greater than 0.05, suggesting that there are no significant differences in foundational research qualities, research competencies, research outputs, or learning engagement among undergraduates of different grade levels. In other words, the grade level of undergraduates does not impact their level of research quality. It is worth noting that in the research outputs, the mean scores for freshmen, sophomores, juniors and seniors show an increasing trend, indicating that as grade level increases, undergraduates achieve more research outputs.

Using major as the independent variable, the collected data were subjected to a one-way ANOVA, and the results are shown in Table 14. The results indicate that the p-values corresponding to each dimension are all greater than 0.05, suggesting that there are no significant differences in foundational research qualities, research competencies, research outputs, or learning engagement among undergraduates of different majors. In other words, major does not impact the level of research quality.

Table 15 and Figure 8 show the combinations of the p-values for undergraduates’ research quality across the four dimensions, i.e., foundational research qualities, research competencies, research outputs, and learning engagement, under different background conditions. In the online teaching model, the p-values for the research quality levels of undergraduates based on gender, family location, grade level, and major are all greater than 0.05, indicating no significant differences. This suggests that these background factors do not have a significant impact on their research quality. However, for undergraduates of different ethnicities, the p-values for foundational research qualities and research competencies are both less than 0.05, indicating significant differences, while there are no significant differences in the other two dimensions. Furthermore, as shown in Figure 8, the scores for undergraduates in different majors are the most balanced across the four dimensions of research quality, indicating that the influence of major background on undergraduates’ research quality is minimal compared to other background conditions.

This section summarizes and analyzes the factors that respondents believe influence their research quality, based on the implementation of interviews and the subsequent review and analysis of the interview results. The basic information of the interviewees is shown in Table 16.

(a) Research preparation: The accumulation of professional knowledge and skills by undergraduates.

(b) Research motivation: The goals and attitudes of undergraduates towards engaging in research work.

(c) Research communication: Interactions related to research activities with mentors or peers.

In addition to these three influencing factors, the state of general education also affects the cultivation of undergraduates’ research quality. D​u​ ​e​t​ ​a​l​.​ ​(​2​0​1​6​) posited that an emphasis on educational breadth can lead to the flattening of general education. Z​h​a​o​ ​e​t​ ​a​l​.​ ​(​2​0​1​8​) mentioned that research training is a new approach to cultivating undergraduates’ innovative abilities. It leverages university teachers and research resources to engage students in research activities early, thereby fostering their innovation and research capabilities. Based on the above content, research organization and management were summarized as another factor in this study, which refers to the organization of undergraduate research activities and related policies by institutions such as governments and universities (X​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​2).

In summary, the factors influencing undergraduates’ research quality can be categorized into four aspects: research preparation, research motivation, research communication, and research organization and management. The first three factors are internal, while the fourth factor is external and requires the joint efforts of schools, society, and the government to build a robust research organization and management system.

In the context of the current digital transformation of education, it is particularly crucial to improve undergraduates’ research quality. Based on the previous analysis, this study proposes a series of targeted recommendations aimed at comprehensively enhancing undergraduates’ research quality through four dimensions: research preparation, research attitude, research communication, and research organization and management.

(a) Regarding research preparation, educational institutions are recommended to incorporate more practical components into the curriculum, such as experiments and projects. At the same time, teachers can organize online seminars to familiarize students with online learning platforms and improve their self-learning abilities. However, this may face challenges such as resource allocation and time scheduling, requiring the joint coordination of educational institutions and teachers to resolve.

(b) In cultivating research attitudes, teachers and schools should jointly set clear research goals, and stimulate students’ interest in research through activities such as academic lectures and research competitions. Meanwhile, parents and peers could also help students establish a positive research attitude through encouragement and support.

(c) For research communication, educational institutions could set up online forums or social platforms to encourage students to actively communicate and share research experiences. At the same time, teachers should regularly conduct one-on-one guidance with students to provide professional research advice.

(d) In terms of research organization and management, educational institutions need to provide sufficient research resources, such as experimental equipment and research funds. Also, a research evaluation system should be established to evaluate students’ research outcomes in a fair and impartial manner, encouraging more students to engage in research activities.

In summary, the implementation of the above strategies can effectively enhance the research quality of undergraduates. However, this requires the joint efforts and cooperation of educational institutions, teachers, students, and parents. Undergraduates are expected to make continuous progress in their research journey through these comprehensive measures, laying a solid foundation for their future academic and career paths.

This study, based on the unique context of the digital transformation of education, comprehensively analyzes and discusses the research quality of undergraduates in online teaching models. It reveals that multiple factors affect the research quality of undergraduates, including research preparation, research motivation, research communication, and research organization and management. Based on these findings, this study proposes a series of suggestions to improve their research quality, aiming to provide useful references and inspirations for undergraduate education and teaching reform and research quality cultivation. In summary, this study not only has important theoretical significance for understanding how to better cultivate students’ research abilities in a digital teaching environment, but also provides important references for effective teaching reform and research quality cultivation in practice.

Although this study provides empirical analysis and improvement strategies for the research quality of undergraduates in online teaching models, it still has certain limitations. First, the scope of the study is limited to the Capital University of Economics and Trade, and the research results may not fully reflect the current status of undergraduates’ research quality in online teaching models in all educational institutions. Future research could consider expanding the sample scope to include educational institutions of different types and regions to enhance the generality and applicability of the research results. Second, the data in this study are mainly based on students’ self-reports, which may involve self-report bias. For example, when answering questions about research motivation and research communication, students may be influenced by social and personal expectations, resulting in subjectivity and deviation in their answers. Future research could consider adopting more objective measurement methods, such as teacher evaluations and peer evaluations, to improve the reliability and validity of the data. Lastly, the data in this study are cross-sectional, precluding the determination of causality. For example, while a positive correlation between research preparation and research quality was identified, it remains unclear whether research preparation enhances research quality or if high research quality encourages better preparation. Future research could adopt a longitudinal design or an experimental design to reveal causality.