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Article

Improving Sustainability of Learning Outcomes: An Empirical Study of Medical Students’ Autonomous Learning

by
Lei Zhao
1,*,†,
Ruijie Zhu
1,†,
Xu Cai
2 and
Junchao Zhang
3,*
1
School of Education, Hangzhou Normal University, Hangzhou 311121, China
2
College of Innovation and Entrepreneurship Education, Wenzhou Medical University, Wenzhou 325035, China
3
School of Education, Huazhong University of Science and Technology, Wuhan 430074, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sustainability 2023, 15(7), 5668; https://doi.org/10.3390/su15075668
Submission received: 25 January 2023 / Revised: 19 March 2023 / Accepted: 21 March 2023 / Published: 23 March 2023
(This article belongs to the Special Issue Approaches and Strategies of Teaching and Learning in Higher Education)
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Abstract

:
Achieving sustainable learning outcomes for medical students requires the assessment of their engagement in autonomous learning, and the development of sustainable autonomous learning skills. This study examined the relationship among autonomous learning, academic support, school satisfaction, and learning outcomes. It used structural equation modeling to analyze data from 725 medical students studying at Huazhong University of Science and Technology, Wuhan. The findings showed that autonomous learning was positively related to academic support, school satisfaction, and learning outcomes. Furthermore, both school satisfaction and learning outcomes were positively correlated with academic support. Similarly, school satisfaction was positively correlated with learning outcomes. Academic support and school satisfaction mediated and serially mediated the relationship between autonomous learning and learning outcomes, respectively. Additionally, autonomous learning had positive direct and indirect effects on learning outcomes through the serial mediation of academic support and school satisfaction. The serial mediating effects of academic support and school satisfaction were significant. Thus, autonomous learning was considered to be an important aspect of sustainable learning outcomes; educational administrators could systematically encourage students’ autonomous learning to increase their invested time and effort, and help students improve their learning outcomes.

1. Introduction

Sustainable development is a strategic idea for global, human, and future development recognized by many international organizations, such as the United Nations. Since the 1970s, there have been at least 26 different sustainability declarations emphasizing Education for Sustainable Development (ESD) [1]. It is believed that ESD helps graduates to balance social, environmental, and economic costs and benefits when making decisions about their post-graduation careers [2,3]. In 2005, the United Nations Decade of Education for Sustainable Development (DESD) stated that the overall goal of sustainable education was to integrate the concept of sustainable development into all aspects of learning, to change people’s behavior and build a more sustainable and just society [4]. In November 2015, UNESCO issued the Education 2030 Framework for Action, which defined ESD as encouraging changes in knowledge, skills, values, and attitudes to ensure more sustainable, just, and quality education for all [5].
Teaching and learning in the 21st century revolve around three major skill categories: learning and innovation (i.e., creativity, critical thinking, and collaboration); information, media, and technology (i.e., digital literacy); life and career skills [6]. In recent years, with the Chinese higher education system’s shift from extension to connotation development, the concept of student learning and development-centered education has become prominent in the field of higher education research [7]. Another key discussion topic that has become key in the scientific community is how to improve college students’ sustainable learning outcomes as part of the process of developing high-quality higher education in China. As well as upholding the goal of using education to promote sustainable development in all disciplines, achieving positive and sustainable learning outcomes in all disciplines will ensure that students are equipped with the experience, knowledge, and skills they need to address local and global challenges.
According to the American Association for Sustainability in Higher Education, “Sustainability learning outcomes are statements that outline the specific sustainability knowledge and skills that students should acquire and demonstrate for successful completion of a unit, course, or project. Learning outcomes do not necessarily need to use the term ‘sustainability.’ As long as they work together as an integrated concept with social, economic and environmental dimensions that address sustainability issues” [8]. Thus, students’ learning outcomes are influenced by many factors. In the 1930s, Tyler introduced the concept of “time of task,” arguing that students’ learning time is directly proportional to their learning outcomes [9]. Meanwhile, Austin emphasized the role of both the environment and the individual student’s initiative, arguing that if students want to learn appropriately, they must be actively engaged in the activities offered by the school; such engagement functions as a measure of the quality of college education [10]. Pascarella argues that students’ prior experience, effort, and level of interaction with their teachers and peers directly influence their cognitive development. Furthermore, the structural and organizational characteristics of the university indirectly influence students’ development; these characteristics include the campus environment, faculty–student relationships, student–student relationships, and individual students’ effort [11]. Kuh argues that two main factors influence student learning outcomes: what students do (e.g., students’ autonomous learning behaviors, such as the amount of time and effort they devote to learning) and what institutions do (e.g., the university’s support for students’ learning and development, including provision of educational resources, and the campus environment) [12]. These studies posit that students’ learning outcomes mainly depend on their autonomous learning, and the university’s support for their learning and development. Therefore, a combination of both internal and external factors contributes to students’ sustainable learning outcomes.
In this essence, learning can be understood as being intrinsically autonomous, which is characterized by independence and self-direction [13]. Thus, learner autonomy is one of the goals of education; accordingly, the ability to learn autonomously is one of the core literacies of learners. Yurdakul argues that autonomy refers to the learners’ ability to take charge of their own learning; autonomy is significantly and positively associated with lifelong learning, which refers to the student’s continuous, voluntary, and self-motivated learning [14]. Some scholars have identified academic expectations, academic support, evaluation and feedback, and student engagement as the four key elements that influence students’ academic success [15]. However, despite the importance of autonomous learning for students’ development, many students are unprepared to learn autonomously [16].
The quality of medical students’ training is significant in improving medical standards and coping with public health emergencies, especially during major crises, such as the COVID-19 pandemic. Scholars showcased that medical students have experienced the impacts of the COVID-19 pandemic in a meaningful yet negative way. Crises such as the pandemic may leave students anxious about whether they have been able to master the appropriate skills to practice medicine [17]. This study’s literature review shows that learners’ autonomous learning has been examined primarily within the context of language learning [18,19]. This indicates that knowledge about the effect of motivation and emotions on students’ academic outcomes is limited in classroom and clinical settings. Moreover, the factors that influence medical students’ autonomous learning and strategies that improve their learning outcomes by enhancing autonomous learning remain relatively unexplored. Elucidating these factors is particularly relevant in the context of the ongoing COVID-19 pandemic, which has highlighted the urgent need for an increase in the availability of trained healthcare professionals worldwide.
Previous researchers have explained that student autonomy is a basis of sustainable learning, and that these two concepts are inseparable [20]. A study showed that medical students’ autonomous motivation was significantly associated with higher levels of meaning orientation, which was reflected in learning, academic achievement, and intention to continue studying [21]. Therefore, this study investigates the relationship between autonomous learning and learning outcomes, examines the role of academic support and school satisfaction in this relationship, provides an effective path for sustainable learning, and further improves the effect of sustainable learning and lifelong learning abilities of medical students.

2. Literature Review and Research Hypotheses

2.1. Autonomous Learning

There is no consensus among academics, especially linguists and educators, on what constitutes autonomy. Holec defines autonomy as “the ability to adjust to one’s own learning”, and autonomous learning as taking responsibility for one’s own learning [22] (p. 124). Furthermore, according to Dickinson, autonomy is “a situation in which the learner is fully responsible for all decisions related to his or her learning and for the implementation of those decisions” [23]. Moreover, according to Boud, autonomy is “an approach to educational practice” that emphasizes the learner’s independence and responsibility [24] (p. 57). Additionally, Kenny notes that autonomy is not only the freedom to learn, but also “the opportunity to become a person” [25] (pp. 431–442). These definitions emphasize the learners’ initiative in the learning process, and their responsibility for what, how, and when they learn. However, autonomous learning does not imply that the teacher transfers all control to the individual learner. Masouleh and Jooneghan argue that students’ ability to take responsibility for their own learning is not innate, and requires teachers’ guidance and support [26]. Balcikanli’s study suggests that student autonomy refers to the teacher’s role of encouraging or motivating students to independently set goals, determine the content and development of their learning, and choose the methods and techniques that will be adopted [27].
This study draws on the definition and measurement of autonomous learning presented in the National Survey of Student Engagement (NSSE). Therefore, in this study, the term “autonomous learning” refers to students’ ability to take responsibility for their own learning pertaining to metacognition, self-management skills, and autonomous learning methods [28].

2.2. Autonomous Learning and Learning Outcomes

In the field of education, the term “student learning outcomes” has emerged to clarify how the purpose of education is defined and expressed [29]. Allan examined multiple definitions of the term “learning outcomes”.
Learning outcomes comprise statements of what learners should know, understand, and be able to demonstrate by the end of the learning period. They are usually expressed as competencies, skills, and abilities. However, the definition of the concept of sustainable learning outcomes remains unclear [20]. Ott’s definition of learning effectiveness was used as a measure of learning outcomes. It is argued that learning outcomes encompass more than just the outcome of a course of study; it is a multidimensional concept [30]. The term “learning outcomes” is used in higher education to include core discipline-based learning outcomes, individual transferable outcomes (e.g., general transferable competencies such as verbal communication skills), and general academic outcomes (e.g., a balance of knowledge, skills, creative thinking, and motivation) [31].
Previous studies have shown that students’ learning outcomes are influenced by several factors, including individual characteristics, family environment, and the institutional learning environment [32,33]. Among these factors, students’ autonomous learning engagement is the most important factor affecting their learning outcomes. Numerous foreign studies have shown that college students’ learning engagement positively influences their learning gains [34,35]. Additionally, Rulland et al. found a significant correlation between the metacognitive skills, learner autonomy, and outcomes of students in Indonesian language courses [6]. Students tended to be interested in the overall learning process if they were involved in the decision making related to their language proficiency. Therefore, a significant relationship between university students’ autonomous learning strategies and their performance in Indonesian language learning was demonstrated.
According to Salimi and Ansari, learning autonomy is a crucial factor in the learning process; it serves as a benchmark of progress, especially for language learning, because it allows learners to act more effectively [36]. McCombs et al. argue that autonomous learning has a positive effect on learning outcomes through the mediation of self-belief; for this positive effect to occur, students must believe that their efforts will lead to learning success and achievement of meaningful personal goals [13]. College students’ autonomous learning under the guidance of a teacher facilitates their learning, personal development, and self-improvement [37]. Furthermore, the teacher’s encouragement helps students to ask more questions, which may lead to higher learning scores. Students who receive satisfactory feedback upon asking questions tend to ask further questions, resulting in out-of-class questioning or inspiring other autonomous learning behaviors [38]. Based on these studies, we formulated the following hypothesis:
Hypothesis 1 (H1).
Autonomous learning positively influences learning outcomes.

2.3. The Mediating Role of Academic Support and Student Satisfaction

Academic support is broadly defined as the various direct or indirect social resources that promote students’ academic achievement, such as emotional and instrumental support [39]. Furthermore, Chen defines academic support as the interpersonal, cognitive, emotional, behavioral, and instrumental resources obtained from parents, teachers, and peers to promote students’ academic achievement [40]. This study argues that academic support is the most important aspect of the support provided by the university for the students’ learning process. Academic support from the university plays a key role in their learning and development [41]. Additionally, Pascarella and Terenzini posit that all policies, management, and resource allocation in universities should encourage students to participate in various activities [42] (p. 112). This study analyzes the dimensions of academic support; the study is based on the NSSE as an indicator system, as it specifically includes university campus facilities’ and faculty teachers’ support.
Yan points out that students can only achieve high efficiency in autonomous learning if they gradually enrich, encourage, recognize, and adjust themselves throughout the process of teacher evaluation and feedback [43]. Learners need the support of their teachers in the process of autonomous learning to achieve the highest possible level. As a supporter, the teacher should make every effort to make learning easy and help learners reach their full potential. Accordingly, Masouleh emphasizes that student autonomy and teacher autonomy are interdependent, and that in the initial stages of student autonomy, learners require support from their teachers to enhance their learning process [26].
Perceived parental and teacher support are both directly related to academic achievement, though perceived teacher support contributes more (directly and indirectly) to student achievement. Furthermore, perceived parental, teacher, and peer support are all indirectly related to students’ perceived academic engagement. Indeed, US researchers have shown that students’ positive interactions with their teachers and peers enhance their motivation, academic achievement, and psychological functioning, whereas poor interactions put them at risk of exhibiting behavioral problems, which could lead to poorer academic performance [44]. Similarly, a Hong Kong study reached the conclusion that teacher support plays an important role in students’ motivation to learn and achieve, and the extent to which students perceive teacher support influences their academic performance. Moreover, students’ perceptions of teacher support have been significantly associated with their academic engagement, as indicated by their interest in learning and their motivation to pursue academic excellence [40]. We formulated our next hypothesis based on these studies, which is described herein:
Hypothesis 2 (H2).
Academic support mediates the relationship of autonomous learning and learning outcomes.
Research on satisfaction can be traced back to the 1970s, when the American scholar Cardozo proposed and defined this concept in the context of customer satisfaction; Cardozo defined satisfaction as the emotional response that customers generate when they consume [45]. Since then, this concept has been used in multiple fields (e.g., psychology and education) worldwide. Within an educational context, scholars have defined school satisfaction from different perspectives. According to Tough, school satisfaction refers to students’ feelings or attitudes when assessing whether their motivations and needs are being met during the learning process [46] (p. 76). Wiers–Jenssen et al. view school satisfaction as students’ assessment of the services provided by the school. This criteria can be divided into the following categories: (1) quality of teaching (academic and instructional); (2) quality of faculty instruction and feedback; (3) curriculum, content, and structure; (4) balance between different forms of organized teaching and learning activities, and student-directed learning; (5) quality of support facilities; (6) quality of infrastructure; (7) quality of and access to leisure activities, and; (8) campus climate [47]. This study uses the NSSE to measure student satisfaction based on four indicators [48].
For many students, the learning process encompasses more than the acquisition of certain skills and theoretical knowledge; it is related to personal growth and development, because school satisfaction may positively impact students’ academic training or experience. Additionally, various researchers have conducted studies regarding universities’ impact on students’ learning process and outcomes [47]. In nations such as the UK, universities foster autonomous learning [49]. Further evidence suggests that poor student satisfaction is often owed to students’ poor relationships with their teachers [40]. Furthermore, some researchers have found that student satisfaction and the quality of university services have a positive and significant impact on student loyalty [50]. Based on these studies, we propose the following research hypothesis:
Hypothesis 3 (H3).
School satisfaction mediates the effect of autonomous learning on learning outcomes.
Previous research reports that academic support and school satisfaction have multiple effects on the relationship between autonomous learning and learning outcomes. Specifically, adequate academic support increases students’ motivation to learn autonomously and improves their learning outcomes [51]. Students with higher school satisfaction are more motivated to learn autonomously and work more efficiently; as a result, they have better learning outcomes [52]. Thus, we developed the following hypothesis:
Hypothesis 4 (H4).
Autonomous learning positively impacts learning outcomes through academic support and school satisfaction.

3. Materials and Methods

3.1. Data Collection

The structured data analyzed were obtained from the fourth Student Survey on Learning and Development (SSLD), conducted in 2021 by the Huazhong University of Science and Technology, a leading university in China. The SSLD is based on Astin’s I-E-O model, Tinto’s institutional action model for student success and related practices in Chinese and foreign universities, and the NSSE; the SSLD considers the specific orientation and talent cultivation objectives of the university. The SSLD has been conducted every two years since 2014, except for in 2020; the 2020 survey was delayed until 2021 because of the COVID-19 pandemic. Through internal consistency reliability coefficients, exploratory factor analysis, and correlation analysis, the developers of SSLD conducted preliminary tests on its reliability and structural validity. The tests showed that the SSLD has good reliability and validity; it also served as an exploration of internationalization and localization practices in Chinese institutions, as it exhibited a Cronbach’s alpha value of 0.955 [53].
Since the beginning of the COVID-19 pandemic, there has been a high demand for medical and public health talents; thus, this study focused on medical students. It was conducted using an online questionnaire, and students participated in the survey by accessing the questionnaire module in the HUB system on the university’s website. Upon accessing the online questionnaire, an introductory statement was presented, describing the purpose of the survey. A peculiarity of this study is that the target population of this study (i.e., medical students) comprised medical students with eight years of education from the Huazhong University of Science and Technology. These students were chosen because of certain specificities, such as: (a) most have participated in the SSLD 2021 and already had some knowledge of the survey; (b) we believed that students entering medical school amid the COVID-19 pandemic had different insights about personal sustainability, and these are likely to be reflected in the learning outcomes, and; (c) medical students of this university were divided into two groups—one comprising students who chose to get a Bachelor of Medicine degree, and the other with students who chose to directly pursue PhD studies in medicine—as we believed that this would make the research results more interesting. The questionnaire design and focus group protocols were approved by the Huazhong University of Science and Technology’s Research Ethics Committee.
Participation in this research was on a voluntary basis, and all respondents were informed that their answers would be kept confidential. A total of 801 questionnaires were retrieved, while 725 valid responses were identified after eliminating invalid questionnaires (valid return rate: 90.5%). The sample included more women (55.45%) than men (44.55%). There was a greater number of eighth-year medical students with a bachelor’s degree (92%); this finding could be related to the specificity of the academic system, and the possibility that many students who responded were unable to successfully apply to a doctoral program after completing their bachelor’s degree.

3.2. Measures

3.2.1. Autonomous Learning Scale

This study drew on the NSSE to measure students’ autonomous learning, and combined it with the study by Orakci and Gelisli, to develop an autonomous learning scale for medical students in Chinese universities [28,54]. The scale consisted of nine items: “I have a clear development plan for my future,” “At the beginning of the semester, I set learning goals and plans for the semester,” “At the beginning of a new course, I set learning goals and plans for the new course,” “I analyze and improve my learning methods from time to time,” “I check the implementation of my learning plan from time to time and make appropriate adjustments,” “At the end of the semester, I evaluate my learning outcomes and summarize my learning experience and lessons,” “I arrange time to participate in activities to regulate my anxiety or depression during learning,” “Even if there are environmental distractions, I can study hard without losing my focus,” and “When my learning tasks are boring or monotonous, I can persist in completing them.” These items were measured on a four-point Likert scale (1 = “strongly conforming”–4 = “strongly not conforming”). The reliability and validity of the scale are well established in the literature; we confirmed its strong internal consistency as it exhibited a Cronbach’s α value of 0.893.

3.2.2. Learning Outcomes Scale

We referred to the NSSE, and the research by Scholl and Olsen on the adaptation of the Student Assessment Learning Outcomes Scale. We considered 14 questions in the following three fields as important for measuring the students’ learning outcomes in Chinese universities [55]: academic knowledge (e.g., the degree of systematic knowledge and theory of the subject), cultural heritage (e.g., the understanding of personal social responsibility), and innovation awareness (e.g., interest and willingness to explore the unknown). All items were measured using a four-point Likert scale ranging from 1 (“greatly improved”) to 4 (“did not improve”). The reliability and validity of the scale are well established, and it exhibited a Cronbach’s alpha value of 0.961.

3.2.3. Academic Support Scale

The Academic Support Scale was adapted from Malecki and Elliott’s study on student social support, and Mazer and Thompson’s study on student academic support based on the stakeholder model. This model argues that the scale comprises two subscales: the Academic Faculty Support Scale (e.g., “Faculty members clearly articulate course objectives, scheduling, and assessment methods”), and the Campus Facility Support Scale (e.g., “The library’s basic services meet my needs”). All items were measured using a four-point Likert scale ranging from 1 (“agree”) to 4 (“disagree”). The reliability and validity of the scale are well established [56,57]; we confirmed its strong internal consistency, as it exhibited a Cronbach’s alpha value of 0.908.

3.2.4. School Satisfaction Scale

We referred to the studies by Kumar and Dileep, and by Huebner et al., and focused on the student satisfaction measure on the overall campus perception aspect according to the needs of this study. The initial scale had seven items, but these were reduced to four items after multiple rounds of testing; the final items are presented herein: “The school takes students’ education very seriously,” “The school takes students’ opinions very seriously,” “I am proud to be a student of this university,” and “If I could choose again, I would choose this school.” These items were assessed on a four-point Likert scale ranging from 1 (“agree”) to 4 (“disagree”). The reliability and validity of the scale are well established [58] (p. 15) [59]; we confirmed its strong internal consistency, as it exhibited a Cronbach’s alpha value of 0.855.

3.3. Data Analysis

Prior to the formal data analysis, Cronbach’s alpha coefficients were calculated for all scales to determine their reliability. As mentioned above, the reliability of all four scales was good, as it exceeded 0.8. SPSS software version 26.0 (IBM) was used for the descriptive and validation analyses of missing values, while Mplus Version 8.3 software was used to build structural equation models (SEMs) for the data. Reliability, normality tests, and correlation analyses were also included.
After performing descriptive statistics on the study variables, we calculated Pearson correlations between them. We then checked the validity of the four constructs (i.e., autonomous learning, academic support, school satisfaction, and learning outcomes) via various analyses, including inter-item relationships, latent variables, and fit indices. The fit of the measurement model (assessing the validity of the underlying variables or constructs by exploring indicator variables or items) and the structural model (addressing dependencies between constructs or underlying variables) were assessed using the following: (i) the S-Bχ2, degrees of freedom (df), and p-values; (ii) the comparative fit index (CFI) as an incremental fit index, and; (iii) the 90% confidence intervals (CI) with approximate root mean square error (RMSEA). Considering the sample size (250+) and the number of indicator variables, an adequate model fit was defined as S-Bχ2, p ≥ 0.05, CFI > 0.85, with TLI > 0.85, SRMR < 0.08, and RMSEA ≤ 0.06 [60]. To test the research hypotheses, we standardized the path coefficients for the direct effects of each variable, while the indirect effects were tested by bootstrapping (sampling 5000 times at 95% bias-corrected CIs) with a statistical significance level of p < 0.05.

4. Results

4.1. Descriptive Statistics

Table 1 shows the means, standard deviations, and Pearson correlation coefficients for the latent variables. Results showed that autonomous learning was positively correlated with academic support (r = 0.289, p < 0.01), school satisfaction (r = 0.33, p < 0.01), and learning outcomes (r = 0.499, p < 0.01). Both school satisfaction and learning outcomes were positively correlated with academic support, exhibiting correlation coefficients of 0.6245 and 0.499, respectively. Similarly, school satisfaction was positively correlated with learning outcomes (r = 0.585, p < 0.01).

4.2. Structural Equation Model

4.2.1. Item Packaging Analysis

In this study, we used a strategy based on unique information packaging, known as an a priori questionnaire construct [61]. It consists of packaging based on topic content or presentation (e.g., each group contains one reverse presentation topic each). Afifi and Olson used packaging based on topic content and obtained favorable results [62]. The results showed that the packaged model was a better predictor of the latent variable learning outcomes (S-Bχ2 = 719.561, df = 74, p < 0.001; χ2/df = 9.724; CFI = 0.936; TLI = 0.921; SRMR = 0.041; RMSEA = 0.110 [90% CI = 0.102–0.117]). The Harman’s one-way test revealed that the model exhibited a poor fit, compared with the packaged model (S-Bχ2 = 2089.932, df = 54, p < 0.001; χ2/df = 77; CFI = 0.800; TLI = 0.764; SRMR = 0.072; RMSEA = 0.190 [90% CI = 0.170–0.199]). Similarly, we used a packaging strategy for the mediating variable of academic support (S-Bχ2 = 728.321, df = 89, p < 0.001; χ2/df = 8.183; CFI = 0.886; TLI = 0.865; SRMR = 0.054; RMSEA = 0.100 [90% CI = 0.093–0.106]). The packaged model was able to more accurately predict the latent variable of academic support, while the results of Harman’s one-way test for the model revealed that it had a relatively poor fit, compared with the packaged model (S-Bχ2 = 1730.828, df = 90, p < 0.001; χ2/df = 19.231; CFI = 0.706; TLI = 0.657; SRMR = 0.109; RMSEA = 0.159 [90% CI = 0.142–0.166]).

4.2.2. Path Analysis

As shown in Figure 1, we tested the complete model using structural equation modelling to examine the relationships among the variables of autonomous learning, academic support, school satisfaction, and learning outcomes. We then performed a series of path analyses. All values of the fit indices indicated a good level of fit for our model: S-Bχ2 = 3228.472, df = 808, p < 0.001; χ2/df = 3.995; CFI = 0.889; TLI = 0.882; SRMR = 0.053; RMSEA = 0.064 [90% CI = 0.062–0.067]. Owing to the large sample size, the model as a whole was nearly in the acceptable range. A cut-off criterion of CFI ≥ 0.90 was initially proposed; however, it has been recently shown that a value > 0.90 is needed to ensure that mis-specified models are not accepted [60].
Figure 2 shows the estimates of the study model, confirming the significant positive effect of autonomous learning on academic support (β = 0.404, p < 0.001) and learning outcomes (β = 0.296, p < 0.001), but not on school satisfaction (β = 0.014, p = 0.096). However, both academic support (β = 0.267, p < 0.001) and school satisfaction (β = 0.339, p < 0.001) had a significant positive effect on learning outcomes. In addition, academic support also had a significant positive effect on school satisfaction (β = 0.883, p < 0.001). Thus, these findings confirmed our hypothesis.
To investigate the indirect effects of autonomous learning and learning outcomes, bootstrapping was performed on a sample of 5000 iterations (Table 2). Firstly, the mediating effect of academic support was 0.063, excluding 0; this result established the presence of a mediating effect. Secondly, the mediating effect of school satisfaction was 0.075, excluding 0, which was significantly higher than that of academic support. Thirdly, we tested the serial mediating effects of academic support and school satisfaction, which were significant (β = 0.077). These findings provide evidence to support H2, H3, and H4.
Overall, the findings supported our proposed hypotheses, and show that autonomous learning has significant direct and indirect effects on learning outcomes through the serial mediation of academic support and school satisfaction.

5. Discussion

This study explored the relationship between autonomous learning and sustainable learning outcomes; it provided empirical evidence supporting the impact of autonomous learning on medical students’ sustainable learning outcomes. In addition, the study separately examined the moderating role of academic support and school satisfaction in autonomous learning. The findings suggested that autonomous learning was significantly and positively related to learning outcomes, and that academic support and school satisfaction mediated the relationship between them. These findings have the following theoretical and practical implications.

5.1. Theoretical Implications

Firstly, one of the important innovations of this study lies in its perspective. Sustainable development means that present development is the basis and condition for future development. Some previous researchers have focused on the learning effects and influencing factors of college students during their college experience [63,64]. Meanwhile, this study focused not only on students’ learning effects during their period studying at the university, but also on students’ post-college sustainable development and lifelong learning abilities.
Secondly, this study demonstrated that autonomous learning directly improved medical students’ learning outcomes, contributing to the literature by providing a new perspective on the topic and novel evidence. It has been shown that college students’ commitment to autonomous learning was a key factor influencing learning outcomes [6]. While this study validated the findings of previous studies, it also differentiated itself by focusing on medical students and clarifying their independent learning behaviors.
Thirdly, the findings delivered additional evidence of the mediation of academic support and school satisfaction in the relationship between autonomous learning and learning outcomes. These results suggested that, when schools provided adequate support for students’ learning and development, students’ autonomous learning initiatives and motivation were enhanced; this support increased students’ willingness to devote more time and energy to their own learning, thereby enhancing learning outcomes. Scholars have shown that the higher the students’ satisfaction and sense of belonging to the school, the higher their autonomy and motivation to learn, and the better their learning outcomes [62]. In summary, these results corroborated those of previous research [65] and demonstrated the influence of the level of academic support and school satisfaction on the association between autonomous learning and learning outcomes.
Finally, the evidence emphasized the serial mediating role of academic support and school satisfaction in the relationship between autonomous learning and learning outcomes. The rigorous data analysis results depicted this serial mediating role with clarity, and highlighted both the influencing factors of the relationship of interest and ways to improve students’ involvement in sustainable learning. Although these findings were obtained from an analysis of data from a Chinese university, they lended support to other studies positing that academic support and school satisfaction are positively related to learning outcomes. Specifically, the findings suggested that if students associated academic support with school satisfaction, their engagement in learning increased. Thus, autonomous learning may be a potential prerequisite for the effectiveness of academic support, which is critical for school satisfaction [66], and, in turn, for learning outcomes. This finding emphasized the need for further research on the potential multifaceted effects of autonomous learning engagement among medical students.

5.2. Practical Implications

Education enables learners to embrace sustainability as a lifestyle choice [67]. How can universities, which are the mainstay of talent development, ensure that they are producing people with a sense of sustainable responsibility and potential for sustainable development? Most prior studies suggested that autonomous learning is important not only in university life, but also for sustainable student development [37]. Developing university students’ autonomous learning skills poses a major challenge for both teachers and schools. Recognition of the factors affecting the medical students’ academic success is one of the most important challenges and concerns in medical schools [68]. Accordingly, the findings of this study have important practical implications for teachers, school administrators, and higher education policy makers; this study may serve as an important evidence-based framework for their efforts to improve teaching and learning. The adequate use of the evidence in this study may help enhance the effectiveness of educational and pedagogical management aimed at facilitating students’ learning and development. Autonomous learning is the foundation of lifelong education and one of the core qualities of modern learners. Accordingly, autonomous learning can directly affect students’ ability to develop sustainably. Universities could regard cultivating students’ autonomous learning abilities as one of their main educational goals, and focus on improving students’ motivation and initiative.
From teachers’ perspectives, the findings show that the provision of adequate teaching support and learning guidance for students can help ensure that the university meets students’ learning needs and enhances their autonomous learning abilities. Therefore, teachers should treat students with an attitude of sustainable development, pay attention to their overall development, care for their inner needs, and awaken their sense of subjectivity. Teachers should provide students with effective teaching support, and learning guidance, reasonably arrange course instruction, and help students master the methods and strategies of autonomous learning. Simultaneously, according to different students’ learning needs, teachers should appropriately increase the academic challenge to improve students’ learning motivation, initiative, creativity, and ability to identify, analyze, and solve problems.
Prior research highlights the importance of school satisfaction, as students’ evaluation and satisfaction related to academic support obtained from the school directly affects their autonomy and motivation to learn; the quality of the academic support available to students has the greatest impact on student satisfaction [69]. When students are satisfied with their school and have a strong sense of belonging, they are willing to devote more time and energy to autonomous learning, more likely to achieve the school’s educational and teaching goals; they may then achieve improved school outcomes [70]. Therefore, schools could endeavor to provide students with the best possible learning environments by improving their laboratories, libraries, classrooms, and other infrastructure. Improved learning conditions can help universities to meet students’ diversified learning needs, to create both a good learning atmosphere, and a campus culture of autonomous learning and knowledge exploration.

5.3. Limitations and Future Research

The first limitation is the single-source origins of the sample data, which limits the representativeness of the sample. Therefore, to validate these results in different contexts, and enhance the reliability and validity of the findings, the researchers aim to conduct further studies including a larger sample of medical students from different universities, regions, and countries.
Secondly, although autonomous learning was proven to significantly affect learning outcomes through the mediation of academic support and school satisfaction, the mechanisms through which this occurs remain unclear. Future research should construct specific models to explore in-depth the mechanisms and pathways of autonomous learning’s impact on learning outcomes.
Thirdly, this was a cross-sectional study, which makes it impossible to assess whether these findings would change gradually. Therefore, the researchers plan to conduct a follow-up study every two years to explore the temporal trends of the relationships between autonomous learning, academic support, school satisfaction, and learning outcomes.

6. Conclusions

Only through lifelong learning and a sustainable development path can medical students keep pace with the rapidly evolving times, maximize their potential, become good doctors who save lives, and realize their value in life. According to UNESCO’s philosophy, there is a need to develop a range of learning skills in young people [71]. Promoting autonomous learning among college students is a topic of immense interest in current higher education policy making, as it is the basis of lifelong education. Students’ sustainable development cannot be achieved without autonomous learning. This study demonstrates the significant impact of autonomous learning on learning outcomes, and explores the mediating role of academic support and school satisfaction in this relationship. The findings revealed that adequate academic support, a higher sense of school satisfaction, and a feeling of belonging, can increase students’ autonomous learning and improve sustainable learning outcomes.

Author Contributions

Conceptualization, L.Z. and R.Z.; methodology, L.Z.; software, R.Z.; formal analysis, R.Z.; investigation, J.Z. resources, X.C.; writing—original draft preparation, L.Z. and R.Z.; writing—review and editing, L.Z. and R.Z.; visualization, R.Z. and X.C.; funding acquisition, L.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Major Projects on Philosophy and Social Sciences program of China’s Ministry of Education, “Research on the Construction of the University Innovation System within the context of self-reliance and self-improvement in science and technology” (grant number 21JZD057). It was also supported by Hangzhou Normal University Graduate Student Research Promotion Innovation Project “A study on the assessment of the implementation of general education from a field perspective” (grant number: 2022HSDYJSKY030), chaired by Ruijie Zhu.

Informed Consent Statement

Informed consent was obtained from all study participants involved.

Data Availability Statement

The data presented in this study are available on request from the corresponding authors.

Acknowledgments

We are grateful to all the students and teachers working at the participating university.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Research model.
Figure 1. Research model.
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Figure 2. Path relationship diagram of autonomous learning’s influence on learning outcomes. *** p < 0.001.
Figure 2. Path relationship diagram of autonomous learning’s influence on learning outcomes. *** p < 0.001.
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Table
Table 1. Means, standard deviations and correlations.
Table 1. Means, standard deviations and correlations.
MeasuresMSD1234
1. Learning 2.8970.5161---
2. Support3.3260.4760.289 **1--
3. Satisfaction3.3250.6270.330 **0.624 **1-
4. Outcomes3.0790.6470.499 **0.499 **0.585 **1
** p < 0.01; N = 725.
Table
Table 2. Bootstrap analyses of the significance of mediation.
Table 2. Bootstrap analyses of the significance of mediation.
Model PathwaysEffect95% Confidence Interval Percentage
LLCIULCI
Learning ⇒ Outcomes0.410 ***0.3390.481-
Learning ⇒ Support0.267 ***0.2020.331-
Learning ⇒ Satisfaction0.199 ***0.1280.269--
Support ⇒ Satisfaction0.761 ***0.6840.837-
Support ⇒ Outcomes0.238 ***0.1440.331-
Satisfaction ⇒ Outcomes0.380 ***0.3080.452-
Learning ⇒ Support ⇒ Outcomes0.063 ***0.0240.08015.36%
Learning ⇒ Satisfaction ⇒ Outcomes0.075 ***0.0350.08718.29%
Learning ⇒ Support ⇒ Satisfaction ⇒ Outcomes0.077 ***0.0380.08818.78%
*** p < 0.001; N = 725.
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Zhao, L.; Zhu, R.; Cai, X.; Zhang, J. Improving Sustainability of Learning Outcomes: An Empirical Study of Medical Students’ Autonomous Learning. Sustainability 2023, 15, 5668. https://doi.org/10.3390/su15075668

AMA Style

Zhao L, Zhu R, Cai X, Zhang J. Improving Sustainability of Learning Outcomes: An Empirical Study of Medical Students’ Autonomous Learning. Sustainability. 2023; 15(7):5668. https://doi.org/10.3390/su15075668

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Zhao, Lei, Ruijie Zhu, Xu Cai, and Junchao Zhang. 2023. "Improving Sustainability of Learning Outcomes: An Empirical Study of Medical Students’ Autonomous Learning" Sustainability 15, no. 7: 5668. https://doi.org/10.3390/su15075668

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