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Promotion of self-directed learning abilities among Chinese medical students through preparing for career calling and enhancing teaching competencies in medical education: a cross-sectional study

BMC Medical Education volume 24, Article number: 386 (2024) Cite this article

Abstract

Background

Medical students face a heavy burden as they are tasked with acquiring a vast amount of medical knowledge within a limited time frame. Self-directed learning (SDL) has become crucial for efficient and ongoing learning among medical students. However, effective ways to foster SDL ability among Chinese medical students are lacking, and limited studies have identified factors that impact the SDL ability of medical students. This makes it challenging for educators to develop targeted strategies to improve students’ SDL ability. This study aims to assess SDL ability among Chinese medical students and examine the effects of career calling and teaching competencies on SDL ability, as well as the possible mechanisms linking them.

Methods

Data were collected from 3614 respondents (effective response rate = 60.11%) using cross-sectional online questionnaires and analyzed using IBM SPSS Statistics 22.0. The questionnaire comprised a Demographic Characteristics Questionnaire, Self-directed Learning Ability Scale (Cronbach’s alpha = 0.962), Teaching Competencies Scale, and Career Calling Scale.

Results

The average SDL ability score of Chinese medical students was 3.68 ± 0.56, indicating a moderate level of SDL ability. The six factors of the Self-directed Learning Ability Scale—self-reflection, ability to use learning methods, ability to set study plans, ability to set studying objectives, ability to adjust psychological state, and willpower in studying—accounted for 12.90%, 12.89%, 12.39%, 11.94%, 11.34%, and 8.67% of the variance, respectively. Furthermore, career calling was positively associated with SDL learning ability (β = 0.295, p < 0.001), and SDL learning ability was positively associated with teaching competencies (β = 0.191, p < 0.01). Simple slope analysis showed that when the level of teaching competencies was higher, the influence of career calling on SDL ability was stronger.

Conclusions

Chinese medical students’ SDL ability has room for improvement. Medical students could strengthen their willpower in studying by setting milestones goals with rewards, which could inspire their motivation for the next goals. Teachers should guide students to learn experience to improve students’ reflective ability. Educators play a crucial role in bridging the gap between career calling education and SDL ability enhancement, highlighting the significance of optimal teaching competencies. Colleges should focus on strengthening teachers’ sense of career calling and teaching competencies.

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Background

Medical education functions in a highly dynamic environment [1]. Both during their time in college and in their future professional careers, medical students need to continually update their medical knowledge to maintain their clinical skills [2]. They are required to acquire more information than students of other subjects and expected to develop a lifelong learning ability [3]. However, the overwhelming volume of medical information [4], extensive literature [5], and limited time [6] impose a huge burden on medical students. In the face of these challenges and the evolving nature of medical education, it has become an urgent challenge for educators to help develop efficient and ongoing self-directed learning (SDL) abilities among medical students.

After Malcolm Knowles first introduced the concept of SDL, several scholars understood that SDL would significantly advance medical students’ careers [5,6,7,8]. Since then, educators have increasingly focused on medical students’ abilities to effectively plan their time and acquire the necessary professional skills for their future careers. Holec deeply studied the concept of SDL ability, considering it the capability to take responsibility for one’s learning [9], including setting learning objectives, deciding on learning content and pace, choosing learning methods and technologies, monitoring learning progress, and evaluating learning outcomes. SDL has gradually become an indispensable competency for medical students [10], helping them stay abreast of the latest medical advancements [11]. Without a sense of SDL for academic learning, medical students may struggle to meet professional demands in the present and future [12]. Therefore, it is critical to integrate a sense of SDL into daily life to adequately prepare medical students for their careers.

Nevertheless, many medical students struggle with effective time management [13]. Due to the traditional exam-oriented education system in China, some Chinese medical students, accustomed to acquiring knowledge from teachers, remain passive learners with limited learning activity [14, 15]. These students may not have the ability to learn independently when faced with problems [16] and may lack a sense of learning consciousness [17], ultimately lagging behind the pace of medical development. This is a significant problem that could affect the quality of medical services in China in the coming years. To become outstanding medical practitioners, Chinese medical students must urgently enhance their SDL ability. Fostering an adaptive and sustainable SDL ability among Chinese medical students is an imminent requirement that medical educators must address.

Before proposing appropriate strategies to enhance this ability, it is imperative to evaluate the current SDL ability of Chinese medical students. However, after reviewing the literature, we found minimal research on measuring the current level of SDL ability among medical students. Therefore, we required a suitable tool to assess the current SDL ability of Chinese medical students and identify effective strategies to enhance it. Based on previous literature, this study explored two factors that may have a significant influence on Chinese medical students: career calling [18, 19], and teaching competencies [20, 21].

In recent years, there has been an increasing focus on medical practitioners’ career calling. Scholars have defined career calling as a subjective experience in which individuals are determined to work voluntarily and positively [22], indicating a passion or drive toward working in a particular field [23]. Bunderson noted that when individuals strongly identify with their jobs, they tend to focus all their attention on work [24]. Moreover, a high level of career calling is related to positive emotions [25], and this active feeling can lead to proactive behaviors [26]. In essence, career calling can maintain the passion of medical students for learning, encouraging them to actively plan and conduct their studies [27]. Can it be extrapolated that the higher the career calling of a Chinese medical student, the better their SDL ability? Based on these predictions, career calling may serve as a protective factor in fostering SDL ability. Therefore, this study aimed to explore the relationship between career calling and SDL ability, along with constructive factors to mobilize SDL ability.

Teaching philosophy reflects an individual’s beliefs and values about teaching and learning. It discusses the self-identity of teachers and how they educate others [28]. Thus, teachers can play the role of a bridge between career calling education and medical students’ learning. Teachers with strong beliefs and values related to career calling may influence students in a subtle way. Thus, it is important to focus on teachers’ teaching capacity. Studies have defined teaching competencies as comprising teachers’ personal characteristics, knowledge, skills, and attitudes required in various teaching environments [29]. Teachers with appropriate characteristics that align with educational requirements can benefit students’ academic achievements [30]. Deep subject knowledge can also improve students’ grades [31], while good teaching skills can direct students’ focus toward learning [32]. Additionally, positive attitudes toward teaching can promote students’ positive attitudes [33]. Overall, teachers’ teaching competencies influence students’ learning and academic achievements and are highly significant for nurturing future talents. Therefore, this study posits that teaching competencies play a positive moderating role between Chinese medical students’ career calling and SDL ability. In practical teaching, teachers’ teaching competencies directly impact students, who observe and judge these competencies more objectively and comprehensively. To better evaluate teaching competencies, this study used “students’ perception of their teachers’ competencies in teaching” as an evaluation method.

This study aimed to measure Chinese students’ SDL ability level and explore the correlations among career calling, teaching competencies, and SDL ability. To accomplish these aims, we proposed the following two hypotheses:

Hypothesis 1

Career calling is positively associated with SDL ability among Chinese medical students.

Hypothesis 2

Teaching competencies positively moderate the relationship between career calling and SDL ability among Chinese medical students.

Methods

Ethics statement

The procedures of this study adhered to the guidelines of the Declaration of Helsinki and were reviewed and approved by the Ethics Committee of the Institutional Review Board of Harbin Medical University(ECHMU: HMU202072). Each participant provided written online informed consent before participating in this study. All data collected from the participants were kept anonymous and confidential to protect their privacy.

Survey design and data collection

Initially, according to the calculation method and standard requirements for the cross-sectional sample size based on Zhou et al. [34], the minimum sample size for this study was calculated to be 1824. Considering a minimum response rate of approximately 40% based on previous online survey experience, the sample size was expanded to 4560. To further ensure data quality, we determined the final number of respondents to be 6000.

After determining the sample size, six medical universities were selected based on their size, academic programs, research performance, admission scores, and number of students. Different specialties and grades were then randomly selected in each university. These universities are located in Nanjing, Guangzhou, Dalian, Harbin, Mudanjiang, and Daqing.

To ensure the cost-effectiveness, time-effectiveness, and accessibility of the study [35], a cross-sectional anonymous online survey was conducted using a multistage stratified convenient sampling method to collect data from medical students from July to September 2021. Based on the characteristics of medical students, we used a multi-staged stratified convenient sampling method, with quotas allocated by the division of students’ years and majors. First, we grouped medical students according to their majors. Next, we further divided these groups into smaller groups based on their years. Finally, we distributed questionnaires and received responses in accordance with the predetermined quantity. The survey was conducted through the online survey platform “Questionnaire Star.” The researchers monitored the collected questionnaires in real-time through the platform and used it to effectively manage the data.

Data quality control

Data quality is key to ensuring the reliability and validity of a study. In this study, a data quality control process was implemented in three stages: questionnaire design, survey administration, and data processing.

Questionnaire design

The questionnaire included three “seriousness test questions” placed at the beginning, middle, and end. These questions prompted respondents to select specific answers to test their seriousness [36]. Additionally, a “self-evaluation question of answer quality” was included at the end of the questionnaire for respondents to evaluate the quality of the questionnaire. Each participant was allowed to respond only once.

Survey administration

One or two research leaders were selected from each university to conduct an “accurate survey” of the target participants. This ensured that all the questionnaires were completed by the target groups.

Data processing

During data processing, strict data screening criteria were applied. Responses with incorrect selections to any of the “seriousness test questions” were deleted. Respondents who took less than three hundred seconds to complete the questionnaire were considered “speeders,” and their questionnaires were deleted. Questionnaires that participants suggested deleting were also excluded. Finally, each remaining questionnaire was reviewed by the authors, and those with an irregular distribution of answers were deleted.

Study instruments

A Demographic Characteristics Questionnaire, Self-directed Learning Ability Scale, Teaching Competencies Scale, and Career Calling Scale were used. Permissions were obtained for using the Teaching Competencies Scale and the Career Calling Scale.

Measurement of demographic characteristics

Eight demographic information was collected using a self-designed questionnaire: gender, grade, major, experience of leadership, hometown, monthly living expenses, parenting style, and education level of parents. Student grade was collected as a continuous variable ranging from 1 to 5. The majors of students were categorized into eight groups: “basic medical science,” “clinical medicine,” “stomatology,” “public health,” “pharmacy,” “medical technology,” “nursing,” and “others.” Leadership experience was divided into “student leaders” and “ordinary students.” Students’ hometowns were categorized as “rural” or “urban.” The monthly living expenses of students were categorized into four groups: RMB “0 ∼ 1000”, “1000 ∼ 1500”, “1500 ∼ 2000,” and “2000 and above”. Parenting style was divided into four categories: “neglecting,” “permissive,” “authoritarian,” and “authoritative.” The education level of parents was categorized as “primary school or below,” “junior middle school,” “high school,” “junior college,” or “bachelor’s degree or above.”

Measurement of SDL ability

According to the definition of SDL ability in previous studies [37, 38], SDL ability was divided into six dimensions: ability to set studying objectives, willpower in studying, ability to set study plans, ability to use learning methods, ability to adjust psychological state, and ability to self-reflect. A 28-item instrument designed by the authors was used to measure SDL ability level. In a previously published article, the self-designed SDL ability scale was tested and implemented [39]. To ensure the applicability of the scale, a pre-survey was conducted with 454 students, which showed good reliability and validity. Items were scored on a 5-point Likert scale ranging from 1 “totally inconsistent” to 5 “totally consistent,” with higher scores representing a higher degree of SDL ability.

Measurement of teaching competencies

The teaching competencies of the teachers were assessed using a 5-item Teaching Competencies Scale, a questionnaire developed for German students by Thomas and Müller [40]. Items were scored on a 5-point Likert scale ranging from 1 “totally not in line with” to 5 “fully in line with,” with higher scores indicating a higher level of teachers’ teaching competencies. The cross-cultural adaptation of the scale into Chinese included performing forward and backward translations, with an assessment of its cultural equivalence and clarity. High reliability was demonstrated in the reliability analysis, with a Cronbach’s α-coefficient of 0.943 for the scale in this study.

Measurement of career calling

Medical students’ career calling level was assessed using the 4-item Career Calling Scale revised by Dik et al. [41]. The scale has been cross-culturally adapted and verified in other studies in China [42, 43]. Items were scored on a 5-point Likert scale ranging from 1 “never” to 5 “every day,” with higher scores indicating a higher degree of career calling. Cronbach’s α-coefficient for the Career Calling Scale in this study was 0.843.

Statistical analysis

This study utilized Amos version 24.0 software and SPSS version 22.0 for statistical analysis, and a two-tailed p < 0.05 was considered statistically significant. We assessed the suitability of the data for factor analysis by conducting the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s χ [2] test of sphericity. Subsequently, exploratory factor analysis (EFA) was conducted to explore the causal structure. We employed the principal component analysis (PCA) and varimax-rotation method to extract six factors, removing items with factor loadings lower than 0.4.

Confirmatory factor analysis (CFA) with maximum likelihood was used to validate the factor structure of the Self-directed Learning Ability Scale. Various indexes were used to assess model fit, including root mean square error of approximation (RMSEA), goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), and normed fit index (NFI), among others. The normed chi-square (χ [2]) and goodness-of-fit test (χ2/df) were used to evaluate the null hypothesis that the model fits the data. However, achieving this in large sample sizes can be challenging, so we utilized the aforementioned indexes as criteria for our analysis. Cronbach’s alpha coefficient was used to measure the reliability of our instrument.

We used descriptive statistics and frequencies to analyze the demographic variables and total scores of the three scales. SDL ability scores across different demographic categories were examined using independent samples t-test or one-way ANOVA. In cases where one-way ANOVAs were found to be significant, we conducted least-significant-difference (LSD) tests for multiple comparisons. Pearson correlation analysis was used to examine correlations among SDL ability, teaching competencies, and career calling. Hierarchical multiple regression analysis was employed to test the moderating effect of teaching competencies on the relationship between career calling and SDL ability. All variables related to SDL ability in univariate analysis (p < 0.05) were included in the hierarchical multiple regression model. We performed the model estimation using PROCESS, a convenient, free, and easy-to-use computational add-on for SPSS documented by Hayes [44]. Before conducting the regression analysis for moderating effects, we employed mean centering (subtracting raw scores from the mean) to mitigate multicollinearity.

Results

Results of EFA, CFA, and reliability

A total of 6012 students were invited to participate in this study. Of these, 3614 questionnaires were completed and passed the quality control procedure, yielding a response rate of 60.11%. Results from both KMO and Bartlett’s tests demonstrated that the samples met the criteria for factor analysis criteria, with a KMO measure of sampling adequacy of 0.975.

The six-factor model explained 70.12% of the variance, with each factor contributing as follows: ability to self-reflect (12.90%), ability to use learning methods (12.89%), ability to set study plans (12.39%), ability to set studying objectives (11.94%), ability to adjust psychological state (11.34%), and willpower in studying (8.67%). The pattern and structures of the rotated common factors are shown in Table 1.

Table 1 Rotated factor loading matrix of all items
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The results of the CFA are presented in Table 2. The model fit the data reasonably well, with GFI, AGFI, NFI, and RMSEA all indicating a good fit. While the χ2/df was slightly higher than ideal, it is considered acceptable in large sample sizes [45]. The path diagram with standardized parameter estimates is shown in Fig. 1.

Table 2 Summary of fit indices
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Fig. 1
figure 1

Path diagram for the model with standardized parameter estimates

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In this study, Cronbach’s alpha coefficients were used to assess the internal reliability of the instrument. The Cronbach’s alpha coefficient for the total score was 0.962. The alphas for the sub-scales of ability to set studying objectives, willpower in studying, ability to set study plans, ability to use learning methods, ability to adjust psychological state, and ability to self-reflect were 0.88, 0.84, 0.89, 0.87, 0.90, and 0.89, respectively.

Current SDL ability level among Chinese medical students

The results indicated that the SDL ability among Chinese medical students was at a moderate level (M = 3.68, SD = 0.56). The scores for specific aspects of SDL ability, from highest to lowest, included the ability to set studying objectives (M = 3.88, SD = 0.68), ability to use learning methods (M = 3.81, SD = 0.61), ability to set study plans (M = 3.71, SD = 0.65), ability to adjust psychological state (M = 3.61, SD = 0.70), willpower in studying (M = 3.56, SD = 0.65), and ability to self-reflect (M = 3.52, SD = 0.70), as presented in Table 3; Fig. 2.

Table 3 The Means (M), Standard Deviations (SD) score of SDL ability among Chinese medical students (n = 3,614)
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Fig. 2
figure 2

Radar chart of SDL ability among chinese medical students

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Difference in SDL ability based on participant characteristics

Significant differences were observed in SDL ability scores depending on students’ demographics, including gender, grade, major, experience of leadership, hometown, monthly living expenses, parenting style, and education level of parents. Details of the scores under different demographic characteristics and LSD test results are detailed in Table 4. The demographic breakdown of participants indicated that 74.41% were women and 25.59% were men. Regarding grades, the majority were freshmen (56.79%), followed by sophomores (18.26%). In terms of majors, 4.10% were in basic medicine, 34.26% in clinical medicine, 6.34% in stomatology, 4.73% in public health and preventive medicine, 15.55% in pharmacy, 11.73% in medical technology, 14.78% in nursing, and 8.52% in other majors. Over half of the participants (53.90%) had experience as student leaders. Regarding hometowns, 55.76% were registered as urban residents, while the rest were from rural areas. In addition, 45.63% of students reported monthly living expenses between 1000 ∼ 1500 RMB. Regarding parenting types, the majority of students (61.23%) reported experiencing permissive parenting. Finally, the education levels of the participants’ parents varied as follows: primary school or below (5.67%), junior middle school (32.57%), high school (28.17%), junior college (12.04%), and bachelor’s degree or above (21.56%).

Table 4 Sample characteristics and one-way ANOVA analysis / independent samples t-test of SDL ability of Chinese medical students
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Correlations among continuous variables

Table 5 presents the correlations among SDL ability, teaching competencies, and career calling. The three variables were found to be significantly correlated with each other. The level of SDL ability was positively correlated with career calling and teaching competencies. Career calling was positively correlated with teaching competencies. Therefore, Hypothesis 1 was supported.

Table 5 Means, Standard Deviation (SD) and correlations of continuous variables (n = 3614)
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Career calling, Teaching competencies, and SDL ability

Following the suggestions by Aiken and West [46], the data were centered (by subtracting the average value), indicating that teaching competencies significantly moderated the association between career calling and SDL ability, as shown in Table 6; Fig. 3. Therefore, Hypothesis 2 was confirmed, suggesting that teaching competencies positively moderated the relationship between career calling and SDL ability among Chinese medical students.

Table 6 Hierarchical multiple regression model (n = 3,614)
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Fig. 3
figure 3

Moderated effect of teaching competencies on the association between career calling and SDL ability

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Discussion

SDL ability among Chinese medical students

This study investigated the level of SDL ability in Chinese medical students. The results derived from this study indicate that the instrument measuring SDL ability had high reliability and validity, with Cronbach’s α exceeding 0.90 and the designed six-factor structure confirmed by CFA. The standardized factor loading coefficient of the items and the cumulative variance contribution rate also confirmed the reliability and validity of the instrument. In summary, the instrument appears to be appropriate for the assessment of SDL ability among Chinese medical students.

The mean score of SDL ability among surveyed medical students was 3.68 ± 0.56 (Mean ± SD). Similar results were found by Yang et al. [47], suggesting that the SDL ability of Chinese medical students is at a moderate level. Among demographic characteristics, gender, grade, major, experience of leadership, hometown, monthly living expenses, parenting style, and education level of parents were found to have an impact on the SDL ability of Chinese medical students.

The results of the scoring order of SDL ability in each dimension indicate that Chinese medical students can actively set studying objectives and plans, and are able to use learning methods correctly. However, in the process of SDL, the ability to adjust psychological state, willpower in studying, and ability to self-reflect were relatively low. This indicates that students’ executive ability and reflective ability were poor, affecting the effectiveness of SDL, or even making the study plan formalistic. Scholars have found that students may be disturbed by minor distractions before fully engaging in the learning process, leading to potential disruptions in their ability to execute their learning goals, even when they have meticulously planned their studying routines in advance [48]. Medical students could add milestones achievement rewards to their study plans. The sense of achievement gained from completing small milestones of learning goals could inspire medical students to move on to the next goal, and thus enhance their willpower to learn. Additionally, studies have pointed out that students may face challenges in describing the influence without drawing lessons from experience [49]; such reflection may be ineffective. In this context, teachers could guide medical students to delve deeply into their experiences hidden behind various events, thereby improving their reflective ability.

Career calling and its positive association with SDL ability among Chinese medical students

The findings of this study confirm that career calling can positively affect SDL ability among Chinese medical students. This result is similar to Lang’s findings, which suggest that students with a strong career calling or a steadfast commitment to their professions tend to have higher levels of energy and a greater sense of control over their professional success [50]. For medical students, a stronger sense of career calling is associated with a greater SDL ability. Chinese medical students’ societal value is closely tied to their academic skills. Additionally, the medical industry requires its workers to cultivate the capacity for lifelong learning to keep up with the latest developments [51]. In essence, Chinese medical students must continue learning on the job to maintain their societal value and status. Therefore, Chinese medical students are encouraged to develop SDL abilities during their undergraduate education to become qualified medical practitioners and smoothly transition into formal work.

It is therefore crucial for medical universities to devote sufficient effort to developing medical students’ sense of career calling during higher education. Chinese medical universities could implement a series of curriculum changes focused on the missions of the medical profession, aiming to enhance students’ sense of responsibility and morality, which in turn would promote self-regulation in learning. By using real-life cases to highlight the responsibilities that medical practitioners bear concerning human life, Chinese medical universities can help students cultivate a noble sense of career calling. This can motivate students to invest more energy and time in academic learning, leading to higher academic achievements through enhanced SDL abilities.

Moderating role of teaching competencies in the positive association between career calling and SDL ability among Chinese medical students

This study provides evidence that teaching competencies can play a positive moderating role between Chinese medical students’ career calling and SDL ability. Strong teaching competencies can capture students’ attention during lectures. For instance, medical teachers can use engaging teaching techniques to make the transfer of seemingly dull knowledge interesting and memorable. Teaching competencies, such as a passionate teaching attitude, can inspire students to unlock their learning potential [52]. Accordingly, when students’ learning potential is unleashed, teachers’ strong teaching competencies, coupled with a broad knowledge base, can cater to students’ academic curiosities. This mutual relationship can stimulate students’ interest, leading them to immerse themselves in learning and create a virtuous cycle. As a result, Chinese medical students may recognize the significance of SDL and proactively improve their SDL ability.

The path to a medical professional learning career is undoubtedly challenging and lengthy, but it should not lack academic assistance and motivation. Properly combining extrinsic teaching competencies with intrinsic career calling can provide the physical and psychological energy needed for medical students to advance further. Therefore, from the perspective of medical colleges, addressing how to improve medical teachers’ teaching competencies seems to be an urgent issue. Medical colleges could design questionnaires to evaluate existing teaching competencies and gather feedback from students to target improvements in teachers’ teaching competencies. Moreover, colleges could invite teachers from other disciplines to deliver lectures and provide training for medical teachers, as few medical teachers have received systematic educational training and may lack knowledge in educational theory and practice [53]. Enhancing teaching competencies is an ongoing endeavor, but it can greatly assist Chinese medical students in improving their SDL abilities and optimizing the quality of education.

Limitations

Although the present study reveals important findings, it has some limitations. First, the data collected are cross-sectional, indicating that establishing causal relationships among the factors was not possible. Second, considering that each medical college has its own unique circumstances and our sample did not include all medical students in China, the generalizability of the results may be limited. Third, the questionnaires were collected online, which may have introduced response bias and made it challenging to control data quality. In future studies, scholars could consider researching a wider and more diverse sample through face-to-face investigations to address these limitations.

Conclusions

This study displayed the research and development process of the SDL ability and verified the reliability and validity of the SDL ability scale for 6 factor 28 items once again. We found that Chinese medical students’ SDL ability is at a moderate level, suggesting room for improvement. We also identified eight demographic factors that influence Chinese medical students’ SDL ability and explored the relationships among career calling, teaching competencies, and SDL ability. Both career calling and teaching competencies were found to be effective factors that can strengthen Chinese medical students’ SDL ability.

Data availability

The datasets used and/or analyzed during this study are available from the corresponding authors on reasonable request hydzhangshue@163.com.

Abbreviations

SDL:

Self-directed learning

KMO:

Kaiser–Meyer–Olkin

EFA:

Exploratory factor analysis

PCA:

Principal component analysis

CFA:

Confirmatory factor analysis

RMSEA:

Root mean square error of approximation

GFI:

Goodness-of-fit index

AGFI:

Adjusted goodness-of-fit index

NFI:

Normed fit index

LSD:

Least-significant-difference

References

  1. van Woezik TE, Koksma JJ-J, Reuzel RP, et al. There is more than ‘I’in self-directed learning: an exploration of self-directed learning in teams of undergraduate students. Med Teach. 2021;43(5):590–98. https://doi.org/10.1080/0142159X.2021.1885637.

    Article  Google Scholar 

  2. Hill M, Peters M, Salvaggio M, et al. Implementation and evaluation of a self-directed learning activity for first-year medical students. Med Educ Online. 2020;25(1):1717780. https://doi.org/10.1080/10872981.2020.1717780.

    Article  Google Scholar 

  3. Ramamurthy S, Er HM, Devi Nadarajah V, et al. Medical students’ orientation toward lifelong learning in an outcome-based curriculum and the lessons learnt. Med Teach. 2021;43(sup1):S6–11. https://doi.org/10.1080/0142159X.2019.1646894.

    Article  Google Scholar 

  4. Sohail N. Stress and academic performance among medical students. J Coll Physicians Surg Pak. 2013;23(1):67–71.

    Google Scholar 

  5. Murad MH, Varkey P. Self-directed learning in health professions education. Annals Acad Med Singap. 2008;37(7):580.

    Article  Google Scholar 

  6. Karakose T. The relationship between medical students’ time management skills and academic achievement. Stud Ethno-Medicine. 2015;9(1):19–24.

    Article  Google Scholar 

  7. Liu T-H, Sullivan AM. A story half told: a qualitative study of medical students’ self-directed learning in the clinical setting. BMC Med Educ. 2021;21(1):1–11. https://doi.org/10.1186/s12909-021-02913-3.

    Article  Google Scholar 

  8. Greveson G, Spencer J. Self-directed learning–the importance of concepts and contexts. Wiley Online Library; 2005. pp. 348–49.

  9. Holek H. Autonomy and foreign language learning. xford. 1981.

  10. Ricotta DN, Richards JB, Atkins KM, et al. Self-directed learning in medical education: training for a lifetime of discovery. Teach Learn Med. 2022;34(5):530–40. https://doi.org/10.1080/10401334.2021.1938074.

    Article  Google Scholar 

  11. Morris TH. Self-directed learning: a fundamental competence in a rapidly changing world. Int Rev Educ. 2019;65(4):633–53. https://doi.org/10.1007/s11159-019-09793-2.

    Article  Google Scholar 

  12. Kemp K, Baxa D, Cortes C. Exploration of a collaborative self-directed learning model in medical education. Med Sci Educ. 2022;32(1):195–207. https://doi.org/10.1007/s40670-021-01493-7.

    Article  Google Scholar 

  13. Tewari S. Exploring the Time Management skills among First-Year Medical undergraduates: an early sensitization. Int J Life Sci Biotechnol Pharma Res 2023.

  14. chunyan W, Jingwei C, Fei W, et al. Discussion on Teaching Mode of cultivating critical thinking of medical students. China Continuing Med Educ. 2023;15(10):37–41.

    Google Scholar 

  15. Current situation on exam-oriented education in. China and the outlook for quality-oriented education. 2021 3rd International Conference on Literature, Art and Human Development (ICLAHD 2021); 2021. Atlantis Press.

  16. An overview on the impact of the exam-oriented education in China. SHS Web of Conferences. 2023. EDP Sciences.

  17. Comparative Analysis on Contemporary Exam-oriented Education in Colleges and Universities in China and Western Liberal Educational Model. 2016 4th International Education, Economics, Social Science, Arts, Sports and Management Engineering Conference (IEESASM 2016); 2016. Atlantis Press.

  18. Chen J, Zhang X. The impact of career calling on higher vocational nursing students’ learning engagement: the mediating roles of career adaptability and career commitment. Front Psychol. 2023;14:1111842. https://doi.org/10.3389/fpsyg.2023.1111842.

    Article  Google Scholar 

  19. Wang Y, Zhou Y, Li T, et al. A cross-sectional study in college‐based nursing education: the influence of core self‐evaluation and career calling on study engagement in nursing undergraduates. Nurs Open. 2023;10(6):3561–69. https://doi.org/10.1002/nop2.1598.

    Article  Google Scholar 

  20. Analysis on Teaching Competence of Clinical Teachers in Applied Undergraduate Medical Colleges. 2019 International Conference on Advanced Education, Service and Management; 2019. The Academy of Engineering and Education.

  21. Ren R, Chen G, Yan J, et al. Development and validation of a core competence instrument for clinical nursing teachers: a mixed-methods study. Nurse Educ Today. 2024;132:106011. https://doi.org/10.1016/j.nedt.2023.106011.

    Article  Google Scholar 

  22. Yang C, Chen A. The double-edged sword effects of career calling on occupational embeddedness: mediating roles of work–family conflict and career adaptability. Asian Nurs Res. 2020;14(5):338–44. https://doi.org/10.1016/j.anr.2020.09.005.

    Article  Google Scholar 

  23. Dobrow SR, Tosti-Kharas J, Calling. The development of a scale measure. Pers Psychol. 2011;64(4):1001–49. https://doi.org/10.1111/j.1744-6570.2011.01234.x.

    Article  Google Scholar 

  24. Bunderson JS, Thompson JA. The call of the wild: zookeepers, callings, and the double-edged sword of deeply meaningful work. Adm Sci Q. 2009;54(1):32–57. https://doi.org/10.2189/asqu.2009.54.1.32.

    Article  Google Scholar 

  25. Duffy RD, Dik BJ, Douglass RP, et al. Work as a calling: a theoretical model. J Couns Psychol. 2018;65(4):423. https://doi.org/10.1037/cou0000276.

    Article  Google Scholar 

  26. Den Hartog DN, Belschak FD. Personal initiative, commitment and affect at work. J Occup Organizational Psychol. 2007;80(4):601–22. https://doi.org/10.1348/096317906X171442.

    Article  Google Scholar 

  27. Bonvin S, Stiefel F, Gholam M, et al. Calling situated: a survey among medical students supplemented by a qualitative study and a comparison with a surveyed sample of physicians. BMC Med Educ. 2022;22(1):619. https://doi.org/10.1186/s12909-022-03642-x.

    Article  Google Scholar 

  28. Bowne M. Developing a teaching philosophy. J Effective Teach. 2017;17(3):59–63.

    Google Scholar 

  29. Tigelaar DE, Dolmans DH, Wolfhagen IH, et al. The development and validation of a framework for teaching competencies in higher education. High Educ. 2004;48:253–68. https://doi.org/10.1023/B:HIGH.0000034318.74275.e4.

    Article  Google Scholar 

  30. Armstrong P. Teacher characteristics and student performance: an analysis using hierarchical linear modelling. South Afr J Child Educ. 2015;5(2):123–45.

    Google Scholar 

  31. Metzler J, Woessmann L. The impact of teacher subject knowledge on student achievement: evidence from within-teacher within-student variation. J Dev Econ. 2012;99(2):486–96. https://doi.org/10.1016/j.jdeveco.2012.06.002.

    Article  Google Scholar 

  32. Gultom S, Hutauruk AF, Ginting AM. Teaching skills of teacher in increasing student learning interest. Budapest Int Res Critics Inst (BIRCI-Journal): Humanit Social Sci. 2020;3(3):1564–69. https://doi.org/10.33258/BIRCI.V3I3.1086.

    Article  Google Scholar 

  33. Mensah J, Okyere M, Kuranchie A. Student attitude towards mathematics and performance: does the teacher attitude matter. J Educ Pract. 2013;4(3):132–39.

    Google Scholar 

  34. Zhou X, Liao X, Spiegelman D. Cross-sectional stepped wedge designs always reduce the required sample size when there is no time effect. J Clin Epidemiol. 2017;83:108–09. https://doi.org/10.1016/j.jclinepi.2016.12.011.

    Article  Google Scholar 

  35. Chang T-ZD, Vowles N. Strategies for improving data reliability for online surveys: a case study. Int J Electron Commer Stud. 2013;4(1):121–30. https://doi.org/10.7903/ijecs.1121.

    Article  Google Scholar 

  36. Yu F, Hu H, Du S. A study of data quality control in web-based questionnaires. Statistics and decision-making 2019;35(16):10–14. https://doi.org/10.13546/j.cnki.tjyjc.2019.16.002.

  37. Zimmerman BJ. A social cognitive view of self-regulated academic learning. J Educ Psychol. 1989;81(3):329. https://doi.org/10.1037/0022-0663.81.3.329.

    Article  Google Scholar 

  38. Weiguo P. On students’ independent learning. J East China Normal Univ (Education Sci Edition). 2001;0278–83. https://doi.org/10.16382/j.cnki.1000-5560.2001.02.009.

  39. Zhang H, Zhao C, Zhang S, et al. A quantitative study of influencing factors of self-directed learning ability in medical undergraduates in China. Chin J Med Educ. 2023;43(12):902–06. https://doi.org/10.3760/cma.j.cn115259-20221130-01504.

    Article  Google Scholar 

  40. Thomas AE, Müller FH. Skalen Zur Motivationalen Regulation Beim Lernen Von Schülerinnen Und Schülern. Wissenschaftliche Beiträge aus dem Inst für Unterrichts-und Schulentwicklung (IUS) 2011;5.

  41. Dik BJ, Eldridge BM, Steger MF, et al. Development and validation of the calling and vocation questionnaire (CVQ) and brief calling scale (BCS). J Career Assess. 2012;20(3):242–63. https://doi.org/10.1177/1069072711434410.

    Article  Google Scholar 

  42. Duan W, Tang X, Li Y, et al. Perceived organizational support and employee creativity: the mediation role of calling. Creativity Res J. 2020;32(4):403–11. https://doi.org/10.1080/10400419.2020.1821563.

    Article  Google Scholar 

  43. Zhang Z, Zhang Y, Jia M. Does a sense of calling facilitate sustainability? Research on the influence of calling on employee green behavior. Bus Strategy Environ. 2021;30(7):3145–59. https://doi.org/10.1002/bse.2795.

    Article  Google Scholar 

  44. Hayes AF. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach: Guilford publications 2017.

  45. Zhonglin Wen J, Hou M. Structural equation model testing: cutoff criteria for goodness of fit indices and Chi-square test. Psychol Dly 2004(02):186–94.

  46. Aiken L. Multiple regression: testing and interpreting interactions. Sage Publications Google Schola. 1991;2:513–31.

    Google Scholar 

  47. Yang C, Zhu Y, Jiang H, et al. Influencing factors of self-directed learning abilities of medical students of mainland China: a cross-sectional study. BMJ open. 2021;11(10):e051590. https://doi.org/10.1136/bmjopen-2021-051590.

    Article  Google Scholar 

  48. Rabin LA, Fogel J, Nutter-Upham KE. Academic procrastination in college students: the role of self-reported executive function. J Clin Exp Neuropsychol. 2011;33(3):344–57. https://doi.org/10.1080/13803395.2010.518597.

    Article  Google Scholar 

  49. Su Y. An investigation into the contents and aspects of college students’ reflective thoughts during field experience. Innovations Educ Teach Int. 2015;52(3):322–34. https://doi.org/10.1080/14703297.2014.880364.

    Article  Google Scholar 

  50. Lang A. Analysis of burnout and career calling in undergraduate pre-medical students. J Interdisciplinary Undergrad Res. 2019;11(1):1.

    Google Scholar 

  51. Berkhout JJ, Helmich E, Teunissen PW, et al. Context matters when striving to promote active and lifelong learning in medical education. Med Educ. 2018;52(1):34–44. https://doi.org/10.1111/medu.13463.

    Article  Google Scholar 

  52. Mart CT. A passionate teacher: teacher commitment and dedication to student learning. Int J Acad Res Progressive Educ Dev. 2013;2(1):437–42.

    Google Scholar 

  53. Oliveira Td M, RLSFMd, Pires MPB, et al. Pedagogical Preparation for Physicians and their performance in the Medical Course. Revista Brasileira De Educação Médica. 2018;42:171–77. https://doi.org/10.1590/1981-52712015v42n3RB2017066.r2ING.

    Article  Google Scholar 

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Acknowledgements

The authors sincerely thank all participants who contributed to this study, particularly those who helped in collecting data, distributing questionnaires, and participating in our research. We would like to thank Editage (www.editage.cn) for English language editing.

Funding

This study was supported as the key commissioned project of the Higher Education Teaching Reform of Heilongjiang Province in 2022 (SJGZ20220070). The study was also part of a project of Chinese Medical Education on the mechanisms of influence of medical students’ professional cognition on learning motivation research (2023B088).

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Author notes

  1. Chen-xi Zhao and Zi-jiao Wang have contributed equally to this work.

  2. Shu-e Zhang, Qing-feng Guo and De-pin Cao have contributed equally to this work.

Authors and Affiliations

  1. Academic Affairs Office, First Affiliated Hospital of Harbin Medical University, 150001, Harbin, China

    Chen-xi Zhao, Ying Cui, Yan-xin Zhang, Xin-hui Cheng & Qing-feng Guo

  2. Department of Health Management, School of Health Management, Harbin Medical University, 150081, Harbin, China

    Zi-jiao Wang, Xiao-jing Yang, Shu-e Zhang & De-pin Cao

  3. Center for the Evaluation of Higher Education Teaching and Learning of Harbin Medical University, 150081, Harbin, China

    Xing Ma

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  1. Chen-xi Zhao
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Contributions

Conceptualization, Shu-e Zhang, Qing-feng Guo and De-pin Cao; Data curation, Xing Ma; Formal analysis, Ying Cui; Funding acquisition, Qing-feng Guo; Investigation, Chen-xi Zhao, Zi-jiao Wang, Xiao-jing Yang and Yan-xin Zhang; Methodology, Chen-xi Zhao and Zi-jiao Wang; Project administration, Xiao-jing Yang; Resources, Chen-xi Zhao; Software, Xin-hui Cheng; Supervision, De-pin Cao and Shu-e Zhang; Visualization, Chen-xi Zhao and Zi-jiao Wang; Writing– original draft, Chen-xi Zhao, Zi-jiao Wang and Xiao-jing Yang; Writing– review & editing, Xing Ma, Ying Cui, Yan-xin Zhang, Xin-hui Cheng.

Corresponding authors

Correspondence to Shu-e Zhang, Qing-feng Guo or De-pin Cao.

Ethics declarations

Ethics approval and consent to participate

This study adhered to the guidelines of the Declaration of Helsinki and was reviewed and approved by the Ethics Committee of the Institutional Review Board of Harbin Medical University(ECHMU: HMU202072). Due to the online survey approach, the written informed consent could not be received. Therefore, verbal informed consent for survey was approved by the Ethics Committee of the Institutional Review Board of Harbin Medical University and obtained from each participate.

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The authors declare no competing interests.

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Zhao, Cx., Wang, Zj., Yang, Xj. et al. Promotion of self-directed learning abilities among Chinese medical students through preparing for career calling and enhancing teaching competencies in medical education: a cross-sectional study. BMC Med Educ 24, 386 (2024). https://doi.org/10.1186/s12909-024-05330-4

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Keywords

BMC Medical Education

ISSN: 1472-6920

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