Post-Graduation Plans among Pre-Service Early Childhood Teachers in Higher Vocational Education in China: Patterns and Associated Factors
—A Survey of 567 Students across Three Higher Vocational Institutions in Jiangsu Province ()
1. Introduction
The move from teacher education into employment is seldom a single, linear decision. Students preparing to work in early childhood education (ECE) may enter a kindergarten, childcare, or early-education post; continue to a bachelor’s degree; look for work in another sector; or defer the choice altogether. In Chinese higher vocational education these options carry particular weight, since programmes are expected to link occupational preparation with routes for further study. Demographic change and shifting demand across kindergarten, childcare, and early-education services complicate this planning further. Knowing what students intend to do before they graduate therefore matters both for preparing the workforce and for improving the programmes themselves.
Research on preservice teachers has produced a substantial body of evidence on why people choose teaching and on professional identity, commitment, and the intention to enter or stay in the profession (Heinz, 2015; Watt & Richardson, 2007; Wu et al., 2025). Within ECE, motivation, professional identity, and perceived working conditions have been tied to career choice and occupational commitment (Huang et al., 2022; Liu & Boyd, 2020; Wang et al., 2024; Zhou et al., 2026). Much of this work, however, frames the transition as teaching versus non-teaching, a contrast that can flatten quite different plans into one. Further study, for instance, may be an attempt to strengthen qualifications for later ECE work rather than a decision to leave it, and indecision may reflect unresolved exploration rather than a settled alternative career.
A multidimensional approach also lets us ask whether particular aspects of the training experience map onto particular pathways. For analysis, the questionnaire included three related single-item evaluations. Perceived training-career fit was intended to capture whether students saw the programme’s goals as congruent with their future development; curriculum-work alignment concerned whether course content appeared closely tied to kindergarten work; and career preparedness reflected whether students believed their professional learning could meet future career needs. These items targeted different intended domains, but the study did not test their discriminant validity and therefore does not establish that they are empirically distinct constructs.
Students also arrive with different motivations and accumulate different amounts of workplace exposure. Choosing the major out of interest may give a more durable basis for an ECE career, whereas being reassigned into it suggests a less self-determined starting point. Practicum can then confirm or unsettle these early expectations. Where students meet meaningful work and good guidance, professional experience has been shown to strengthen self-efficacy, identity, and career commitment (Cai et al., 2022; Moore et al., 2023)—which makes both motivation and practicum exposure plausible correlates of where students head and how sure they are about it.
The present study takes up two of these gaps. It distinguishes four plans reported by current students, rather than reading questionnaire responses as if they were observed graduate destinations, and it places programme perceptions, entry motivations, practicum duration, and grade in a single multinomial model before testing whether students with different plans favour different reforms. Doing both connects how individuals plan their transition with concrete choices about curriculum, practicum, and career support.
Accordingly, the study asked three research questions:
1) What patterns of post-graduation plans are reported by preservice ECE teachers in higher vocational education?
2) How are major-choice motivations, perceived training-career fit, curriculum-work alignment, career preparedness, practicum duration, and grade associated with different post-graduation plans?
3) Do students with different post-graduation plans differ in the programme reforms they prioritise?
2. Literature Review and Theoretical Framework
2.1. Post-Graduation Plans as a Multidimensional Transition Outcome
Career intention is often taken as an early sign of occupational entry, but an intention is not a realised destination. Plans stated during enrolment stay open to revision as students take in new information, labour-market signals, family expectations, and further chances to study. This matters especially for ECE students, whose field spans kindergartens, childcare institutions, and early-education organisations, and who may also pursue academic upgrading. A four-category outcome therefore captures more of this variation than a teaching-versus-non-teaching split.
Comparative work shows that preservice ECE teachers’ career identities and choices are shaped by both personal meaning and institutional context (Liu & Boyd, 2020), and Chinese studies similarly find that entry and retention intentions reflect influences at several levels rather than one underlying attitude (Wang et al., 2024; Wu et al., 2025). On this view, ECE employment, further study, other-industry employment, and indecision do not sit at ordered points on a single continuum; they are distinct transition strategies and are best modelled together.
2.2. Major-Choice Motivation and the FIT-Choice Perspective
The FIT-Choice framework accounts for teaching-career choice through intrinsic value, personal and social utility value, prior experiences, perceived ability, task demands, returns, and social influences (Watt & Richardson, 2007). Internationally, preservice teachers are known to enter preparation programmes for a mix of reasons, and those reasons track different levels of commitment (Heinz, 2015). A person-centred study of Chinese preservice ECE teachers likewise found several distinct motivation profiles rather than one uniform type (Zhou et al., 2026).
Our questionnaire did not include the full FIT-Choice scale, so the framework serves here as an interpretive lens rather than a model to be formally tested. Two available indicators were directly relevant: choosing the major out of personal interest, and entering through reassignment. Interest-based choice stands in for intrinsic value, while reassignment marks a more constrained entry route. Both were expected to differentiate occupational direction, though later training experiences could amplify or dampen their early influence.
2.3. Perceived Training-Career Fit and Curriculum-Work Alignment
Person-environment fit theory holds that good outcomes are more likely when a person’s preferences, needs, or capacities match what the environment demands and supplies. Subjective fit perceptions are empirically distinct from related job and organisational attitudes (Cable & DeRue, 2002), and meta-analytic work links several forms of fit to satisfaction, commitment, performance, and turnover (Kristof-Brown et al., 2005). In a teacher-education setting, then, perceived training-career fit can be read as students’ sense that the programme’s cultivation goals match their own future development.
Curriculum-work alignment is more task-specific: it concerns whether what is taught looks connected to actual kindergarten work. A student may see this relevance yet not intend immediate ECE employment—for instance, if further study seems the better route to stronger credentials. Another may report good overall fit while judging particular courses too far removed from practice. Analysing the two single-item measures separately allows their association patterns to be compared, without claiming that their discriminant validity has been established.
2.4. Practicum Exposure and Perceived Career Preparedness
Practicum places students in the work environment their coursework anticipates, offering mastery experiences, feedback, role models, and a realistic picture of the job. Evidence from preservice teacher education indicates that internship experience can support professional identity through self-efficacy and learning engagement (Cai et al., 2022). In ECE, stronger professional experience can also shape career choice by deepening students’ sense of connection with children, educators, and the profession (Moore et al., 2023).
Exposure alone, however, guarantees nothing. Practicum can expose the constraints of the job, or make clear that another path suits the student better. Duration is therefore treated as an opportunity for occupational learning, not as an inherently beneficial treatment. Career preparedness was included as a separate observed item from practicum duration: it asked whether current professional learning could meet future career-development needs and may reflect coursework, practice, feedback, and self-evaluation together.
2.5. Integrated Analytical Framework
The integrated framework separates four things: a starting orientation, experienced congruence, occupational exposure, and self-assessed readiness. Major-choice motivation stands for the starting orientation; training-career fit and curriculum-work alignment for two kinds of perceived congruence; practicum duration for accumulated exposure; and career preparedness for an overall readiness judgement. Grade is included to reflect where students sit in the programme and how much time they have had for experience and for making up their minds. The framework predicts associations with the relative probabilities of the four plans, not causal effects.
It also implies that reform needs may differ by pathway: students heading into ECE employment may want expanded field-specific opportunities, those bound for further study may look for cross-disciplinary learning, and undecided students may need broader exploration and transition support. Testing reform priorities therefore carries the analysis from explaining plans to identifying the different responses institutions might make.
3. Method
3.1. Research Design and Participants
The study used a cross-sectional, institution-based questionnaire design. Data were collected through Wenjuanxing, an online survey platform widely used in China, between 20 and 23 April 2026. Participants were recruited using convenience sampling. Before data collection, the researchers contacted departmental administrators at the three participating institutions to explain and confirm the content and purpose of the questionnaire. Eligible participants were students enrolled in preschool-education programmes at the participating institutions, including those in five-year integrated and three-year programmes. Teachers at each institution then distributed the Wenjuanxing survey link to eligible students, who chose voluntarily whether to participate. A total of 582 questionnaires were submitted. After 15 questionnaires were excluded based on the data-quality criteria described in Section 3.3, 567 valid responses were retained, yielding a usable-response rate of 97.4%. Because the exact number of students who received the survey invitation could not be determined, an overall response rate could not be calculated. As recruitment was institution based rather than probability based, the sample should not be interpreted as nationally representative.
The sample included 523 women (92.24%) and 44 men (7.76%). Most students were enrolled in a five-year integrated programme (n = 542, 95.59%); 25 students (4.41%) were in a three-year programme. By grade, 54 participants were in Year 1, 46 in Year 2, 117 in Year 3, 251 in Year 4, and 99 in Year 5. A total of 523 students (92.24%) reported some kindergarten observation or practicum experience: 194 reported less than one month and 329 reported one month or more. The remaining 44 reported no practicum experience.
Ethics and data protection. The survey protocol was reviewed by the Research Office and the Department of Preschool Education at Suzhou Early Childhood Education College. The study received institutional permission and, because it was an anonymous, minimal-risk educational survey, was determined not to require full institutional review board (IRB) review. Before accessing the questionnaire, students viewed an introductory statement explaining the study purpose, the voluntary nature of participation, anonymous completion, and the exclusive use of the data for research. Electronic informed consent was obtained before participation. No names, student identification numbers, telephone numbers, class information, or other direct identifiers were collected. The survey data were exported from Wenjuanxing and stored on an encrypted local drive accessible only to the two authors. The data will be retained for five years following publication and then securely deleted.
3.2. Survey Instrument and Variables
3.2.1. Post-Graduation Plans
The outcome was based on the item, “What is your career plan after graduation?” Responses indicating work as a kindergarten teacher, in a childcare institution, or in an early-education institution were combined as ECE-related employment. The remaining options were upgrading to a bachelor’s degree (further study), working in another industry, and not yet decided. The four-category variable records intended pathways among current students; it does not record actual destinations after graduation. ECE-related employment was the reference category in regression models.
3.2.2. Major-Choice Motivation
Students selected one or more reasons for choosing preschool education. Two binary indicators were used: personal interest and reassignment admission. Each was coded 1 if selected and 0 otherwise. The indicators were entered separately because they represent different motivational or constraint-related features and were not mutually exclusive.
3.2.3. Perceived Fit, Alignment, and Preparedness
Three targeted single-item measures assessed related aspects of students’ training experience. Perceived training-career fit was measured by evaluating the congruence between the programme’s cultivation goals and the student’s future career development (1 = completely incongruent, 5 = highly congruent). Curriculum-work alignment assessed the perceived relevance of course content to practical kindergarten work (1 = seriously disconnected, 5 = very closely connected). Career preparedness captured students’ assessment of whether their current professional learning could meet future career-development needs (1 = completely unable, 5 = completely able). The items were intended to represent different domains, but the study did not test their discriminant validity. They were therefore analysed as separate observed variables on their original five-point scales, and the results should not be interpreted as evidence that they constitute empirically distinct latent constructs. Single-item measures may be useful when respondent burden is a concern, but they do not permit assessment of internal consistency or within-construct factor structure (Fisher et al., 2016).
3.2.4. Practicum Duration and Grade
Practicum duration was coded as an ordinal exposure variable: 0 = none, 1 = cumulative duration below one month, and 2 = cumulative duration of one month or more. Grade was coded from 1 (Year 1) to 5 (Year 5). The primary model used the 0-1-2 practicum coding as an ordered score. Because these categories represent unequal duration ranges, the one-unit coefficient tests an imposed linear trend in the log odds across ordered categories; it should not be interpreted as the effect of an equal increment in time. A sensitivity model replaced the practicum score with two indicator variables so that no linearity across categories was assumed.
3.2.5. Programme Reform Priorities
A multiple-response item asked what institutions should do in response to changing kindergarten employment conditions. Six binary priorities were analysed: expand directions such as childcare and early education; strengthen innovation capacity; improve comprehensive quality; increase cross-disciplinary learning opportunities; strengthen career-planning guidance; and provide more practicum and employment channels. Each option was coded 1 if selected and 0 otherwise.
3.3. Data Screening and Preparation
Through Wenjuanxing, 582 questionnaires were submitted. Fifteen questionnaires were excluded because they met one or more data-quality criteria: a completion time below two minutes, more than 10% missing responses, or straight-lining across applicable scale items. The final analytical sample comprised 567 valid records, yielding a usable-response rate of 97.4%. All retained records had valid responses for the outcome and seven predictors used in the primary model, and no exact duplicate response patterns were detected in the substantive questionnaire fields. A sensitivity analysis additionally excluded the fastest 5% of retained responses. Ordered predictors were mean centred for estimation. Binary predictors remained coded 0/1.
3.4. Data Analysis
First, frequencies and percentages described the four post-graduation plans. Group-specific means or proportions summarised the predictors. Second, multinomial logistic regression estimated the odds of further study, other-industry employment, and being undecided relative to ECE-related employment. Predictors were entered simultaneously: training-career fit, curriculum-work alignment, career preparedness, interest-based major choice, reassignment admission, practicum duration, and grade. Odds ratios (ORs), 95% confidence intervals (CIs), likelihood-ratio model fit, McFadden’s pseudo-R-squared, and variance inflation factors were reported.
Because multinomial logit coefficients are difficult to compare across outcomes, average marginal effects (AMEs) were computed for predicted probabilities. For binary predictors, AMEs represent the average discrete change from 0 to 1; for ordered predictors, they represent the average derivative for a one-unit change on the observed scale. Percentile 95% CIs were obtained from 1,000 successful nonparametric bootstrap resamples.
Third, six 4-by-2 chi-square tests compared reform-priority selection across plan groups. Effect size was expressed as Cramer’s V, and Benjamini-Hochberg adjustment controlled the false discovery rate across the six tests (Benjamini & Hochberg, 1995). Statistical significance was evaluated at q < 0.05 for the reform comparisons. Robustness checks re-estimated the multinomial model among five-year programme students, after excluding the fastest 5% of responses, and with practicum duration represented categorically. The analyses were conducted on the de-identified survey dataset.
4. Results
4.1. Distribution of Post-Graduation Plans
The most common plan was further study (n = 223, 39.3%), followed by ECE-related employment (n = 164, 28.9%), being undecided (n = 131, 23.1%), and employment in another industry (n = 49, 8.6%). Thus, fewer than one third reported an immediate ECE-employment plan, but the largest alternative was educational progression rather than departure to another industry. Figure 1 displays the four-category distribution.
Figure 1. Distribution of students’ reported post-graduation plans (N = 567).
Descriptive differences were consistent with distinct pathway profiles. Students planning ECE employment reported the highest training-career fit and career preparedness, the largest share of interest-based major choice, and the largest share with at least one month of practicum. Students planning other-industry employment reported the lowest fit, alignment, preparedness, and interest share. The further-study group reported relatively high curriculum-work alignment despite lower preparedness than the ECE-employment group (Table 1).
Table 1. Descriptive statistics by post-graduation plan.
Post-graduation plan |
n |
Training-career fit
M (SD) |
Curriculum-work alignment M (SD) |
Career preparedness M (SD) |
Interest-based choice % |
Reassigned % |
Practicum ≥ 1 month % |
ECE-related employment |
164 |
4.21 (0.80) |
4.38 (0.68) |
4.24 (0.73) |
57.9 |
7.3 |
67.1 |
Further study |
223 |
3.70 (0.72) |
4.22 (0.72) |
3.66 (0.84) |
38.1 |
10.3 |
60.5 |
Other industry |
49 |
2.92 (0.86) |
3.59 (0.93) |
3.10 (1.01) |
14.3 |
10.2 |
51.0 |
Undecided |
131 |
3.59 (0.94) |
4.09 (0.79) |
3.50 (0.88) |
24.4 |
10.7 |
45.0 |
Note: Fit, alignment, and preparedness were rated from 1 to 5. Interest-based choice and reassignment were binary indicators from a multiple-response item. Practicum ≥ 1 month is the percentage reporting a cumulative duration of at least one month. Values are descriptive and unadjusted.
4.2. Factors Associated with Post-Graduation Plans
The multinomial logistic regression was statistically significant, LR chi-square (21) = 178.61, p < 0.001, with McFadden’s pseudo-R-squared = 0.123. The maximum variance inflation factor was 2.73, providing no indication of severe multicollinearity. Table 2 reports adjusted ORs relative to ECE-related employment.
Table 2. Multinomial logistic regression of post-graduation plans.
Predictor |
Further study vs ECEOR [95% CI] |
Other industry vs ECEOR [95% CI] |
Undecided vs ECEOR [95% CI] |
Training-career fit |
0.61 [0.43, 0.85]** |
0.28 [0.17, 0.47]*** |
0.63 [0.43, 0.92]* |
Curriculum-work alignment |
1.51 [1.03, 2.20]* |
0.83 [0.48, 1.41] |
1.39 [0.91, 2.11] |
Career preparedness |
0.42 [0.29, 0.60]*** |
0.40 [0.24, 0.67]*** |
0.39 [0.26, 0.59]*** |
Interest-based choice |
0.74 [0.46, 1.20] |
0.30 [0.11, 0.76]* |
0.35 [0.19, 0.62]*** |
Reassignment admission |
1.09 [0.49, 2.44] |
0.67 [0.19, 2.32] |
0.80 [0.32, 1.97] |
Practicum duration |
0.53 [0.29, 0.96]* |
0.81 [0.33, 2.02] |
0.31 [0.16, 0.62]*** |
Grade |
1.49 [1.08, 2.06]* |
0.95 [0.57, 1.58] |
1.45 [1.003, 2.10]* |
Note: N = 567. ECE-related employment is the reference outcome. Ordered predictors were entered as one-unit terms; interest-based choice and reassignment were binary. OR = odds ratio; CI = confidence interval. *p < 0.05, **p < 0.01, ***p < 0.001.
Higher training-career fit and career preparedness consistently distinguished ECE-related employment from the three alternative plans. For example, a one-point increase in preparedness was associated with 58% lower odds of further study, 60% lower odds of other-industry employment, and 61% lower odds of being undecided rather than planning ECE employment. Stronger fit was also associated with lower odds of all three alternatives. Interest-based major choice was associated with lower odds of other-industry employment and indecision, while reassignment was not statistically significant after adjustment. Longer practicum exposure was associated with lower odds of further study and indecision relative to ECE employment. Higher grade was associated with higher odds of further study and indecision relative to ECE employment.
Curriculum-work alignment showed a different pattern from general training-career fit. Higher alignment was associated with higher odds of further study rather than ECE employment (OR = 1.51, 95% CI [1.03, 2.20]) and was not statistically significant in the undecided comparison. In short, seeing the curriculum as occupationally relevant does not necessarily go with wanting to enter the workforce right away.
AMEs translated the model into changes in predicted probability. The probability of planning ECE-related employment was 14.8 percentage points higher for each one-point increase in career preparedness (95% bootstrap CI [9.2, 20.7]), 12.7 points higher for a one-level increase in practicum duration [4.1, 21.6], 10.2 points higher for interest-based choice [2.7, 18.8], and 9.0 points higher for a one-point increase in fit [3.1, 15.1]. Grade was associated with a 5.9-point lower probability of ECE employment [−10.7, −1.5]. The CIs for curriculum-work alignment and reassignment included zero. Figure 2 presents these ECE-employment AMEs.
Figure 2. Average marginal effects on the predicted probability of planning ECE-related employment.
The remaining AMEs clarified how factors differentiated specific alternatives. Interest-based choice (−12.1 percentage points, 95% CI [−19.1, −4.4]), practicum duration (−12.8 points [−21.0, −4.3]), and preparedness (−5.3 points [−10.3, −0.5]) were associated with a lower probability of being undecided. Curriculum-work alignment was associated with a 6.9-point higher probability of further study [0.5, 13.0], whereas preparedness was associated with an 8.2-point lower probability [−14.0, −2.5] and grade with a 5.8-point higher probability [0.05, 11.3]. For other-industry employment, fit (−5.9 points [−8.9, −2.9]) and curriculum-work alignment (−3.4 points [−6.0, −0.5]) were the clearest negative correlates.
4.3. Differences in Programme Reform Priorities
Three of the six reform priorities differed significantly across the four plan groups after false-discovery-rate adjustment. The largest difference concerned cross-disciplinary learning (q < 0.001, Cramer’s V = 0.246). It was selected by 67.3% of the other-industry group and 59.2% of the further-study group, compared with 32.3% of the ECE-employment group. Providing more practicum and employment channels also differed (q = 0.005, V = 0.165), with the highest selection among students planning further study (40.8%). Expanding directions such as childcare and early education differed more modestly (q = 0.030, V = 0.136) and was most frequently selected by the ECE-employment group (54.9%). Innovation capacity, comprehensive quality, and career-planning guidance did not differ significantly (Table 3 & Figure 3).
Table 3. Programme reform priorities by post-graduation plan.
Programme reform priority |
ECE employment% |
Further study% |
Other industry% |
Undecided% |
chi-square (3) |
Cramer’s V |
FDR q |
Expand childcare/
early-education directions |
54.9 |
44.8 |
40.8 |
36.6 |
10.43 |
0.136 |
0.030 |
Strengthen innovation capacity |
37.2 |
33.6 |
28.6 |
28.2 |
3.12 |
0.074 |
0.453 |
Improve comprehensive quality |
31.1 |
31.8 |
26.5 |
28.2 |
0.89 |
0.040 |
0.828 |
Increase cross-disciplinary learning |
32.3 |
59.2 |
67.3 |
47.3 |
34.24 |
0.246 |
<0.001 |
Strengthen
career-planning guidance |
17.1 |
22.0 |
14.3 |
22.9 |
3.09 |
0.074 |
0.453 |
Provide more practicum/employment channels |
22.0 |
40.8 |
30.6 |
32.8 |
15.38 |
0.165 |
0.005 |
Note: Entries are within-group percentages selecting each option; multiple selections were allowed. FDR q values use the Benjamini-Hochberg adjustment across six chi-square tests. No expected cell count was below 5.
Figure 3. Selection of programme reform priorities across post-graduation plan groups.
4.4. Robustness Checks
The main conclusions were broadly similar in the restricted models. Among five-year programme students (n = 542), McFadden’s pseudo-R-squared was 0.128; after excluding the fastest 5% of responses (n = 538), it was 0.121. Replacing the ordinal practicum score with categorical indicators yielded a pseudo-R-squared of 0.132. In this categorical model, the estimate for having at least one month of practicum versus none in the undecided-versus-ECE comparison was negative but imprecise (OR = 0.25, 95% CI [0.06, 1.07], p = 0.062). Because the confidence interval included 1.00, this specification did not provide conclusive evidence of an association. The primary ordinal model supported an association, but that result depends on the imposed one-unit linear trend and is less conclusive when practicum duration is modelled categorically. The wider confidence interval may partly reflect the small no-practicum reference group (n = 44), but the data cannot distinguish limited precision from model-specification uncertainty. Practicum findings should therefore be interpreted cautiously.
5. Discussion
5.1. Post-Graduation Planning Is a Multidimensional Transition Process
This study examined four post-graduation plans among 567 preservice ECE teachers in higher vocational education, and the distribution sits awkwardly with a simple retention-versus-attrition reading. Further study was the largest group and other-industry employment the smallest, with nearly a quarter of students undecided. Each category follows its own logic—immediate occupational entry, upgrading one’s qualification, moving away from the field, and unresolved exploration—and folding them into a single non-ECE bucket would hide both the scale of academic progression and the particular needs of undecided students.
The further-study result deserves particular attention in a vocational setting. A bachelor’s degree may look to students like a route to stronger credentials, wider job options, or later advancement. These data cannot show whether such students will eventually enter ECE, but they give no warrant for writing them off as lost to the field either. Distinguishing a temporary detour through further study from a lasting move out of the profession will require longitudinal follow-up.
5.2. Career Preparedness and Training-Career Fit Showed Different Association Patterns
Career preparedness was the strongest positive correlate of the predicted probability of ECE employment. Students who felt their current professional learning could meet future career needs were more likely to report an immediate ECE-employment plan and less likely to report further study or indecision. This pattern is consistent with, but does not establish, the interpretation that preparedness reflects perceived readiness to move into work.
Training-career fit also mattered, most clearly in separating ECE employment from other-industry employment. This fits person-environment fit research, in which subjective congruence relates to commitment and to withdrawal-related outcomes (Cable & DeRue, 2002; Kristof-Brown et al., 2005): students who saw the programme’s goals as aligned with their own future were less likely to plan work outside ECE. When the two single-item predictors were entered together, their coefficients showed different patterns; however, the study did not test discriminant validity, and the items may capture overlapping perceptions.
Curriculum-work alignment behaved differently, and its positive link with further study rather than immediate ECE employment may look counterintuitive at first. Students can recognise that their courses are practically relevant and still want a higher qualification before entering the labour market; academically oriented students, in particular, may rate the curriculum highly yet prefer to keep studying. Because the design is cross-sectional, these readings stay tentative, and the finding should not be taken to mean that a practically relevant curriculum puts students off employment.
5.3. Interest-Based Entry and Practicum Exposure Were Associated with Direction and Certainty
Choosing the major out of interest was linked to a higher probability of ECE employment and a lower probability of indecision, in line with the FIT-Choice emphasis on intrinsic value and with evidence that motivation profiles differ in commitment (Heinz, 2015; Watt & Richardson, 2007; Zhou et al., 2026). This does not mean that students who entered for other reasons cannot build professional commitment; it simply marks interest as one resource that helps with direction and certainty.
In the primary ordinal specification, practicum duration was associated with a higher probability of ECE employment and a lower probability of indecision; however, the categorical sensitivity estimates for at least one month versus none was imprecise and included the null. Time in real settings gives students concrete information about the daily work, a chance to test their developing skills, and a firmer sense of belonging to the profession—mechanisms in keeping with research tying internship experience to self-efficacy, engagement, and identity (Cai et al., 2022) and with ECE evidence on the career influence of stronger professional experience (Moore et al., 2023). Duration is only a rough proxy, though: a long but poorly supported placement need not deliver what a shorter, well-mentored one does.
Once the other variables were controlled, reassignment admission had no independent association with pathway. The null result is instructive: a constrained route into the major seems to matter less once students’ later fit, preparedness, interest, and practicum exposure are taken into account, and it warns against assuming that reassigned students are bound to be disengaged.
5.4. Further Study and Indecision Require Different Interpretations
The model also pulled further study and indecision apart. Curriculum-work alignment and grade were positively associated with further study, whereas preparedness was negatively associated with it relative to immediate ECE employment. That profile fits a deliberate progression strategy: students may value their training yet not feel ready, or may want a higher credential in hand before they start work.
Indecision looked different. It went with lower preparedness, less interest-based entry, and shorter practicum exposure, which makes it read less as a chosen option than as a decision still in progress. The positive grade coefficient for indecision relative to ECE employment shows that uncertainty does not simply resolve as students move through the programme; for some, the trade-offs sharpen as graduation nears, so decision support needs to run across all years, not just the first.
5.5. Theoretical Contributions
Three contributions follow. Treating post-graduation planning as a nominal, multidimensional outcome keeps further study and indecision from being misread as occupational exit. Combining a bounded FIT-Choice account of major-entry motivation with person-environment fit and experiential learning showed that initial interest, perceived congruence, workplace exposure, and current readiness were associated with plans in different patterns. Because the programme-evaluation measures were single items, these patterns should not be interpreted as evidence of empirically distinct constructs. And linking reform priorities to transition pathways demonstrates that the changes students want are not uniform, which ties the analysis directly to institutional design.
The findings also fit a process reading. Entry motivation sets an initial orientation; training and practicum supply the experiences against which students judge fit and capability; preparedness sums up where they stand; and their stated plans express a provisional transition strategy. A cross-sectional design cannot test this sequence over time, but it offers a coherent starting point for longitudinal work.
5.6. Implications for Higher Vocational Early Childhood Education
Programmes should resist a one-size-fits-all response. For students heading straight into ECE employment, the aim is to build preparedness through authentic tasks, clear competency standards, well-supported practicum, and feedback that ties performance to what the job actually demands. Because this group was relatively keen on expanded childcare and early-education directions, institutions would do well to present ECE as a wide employment field rather than kindergarten teaching alone.
For those planning further study, institutions should offer clear articulation pathways, academic advising, opportunities for research and inquiry, and cross-disciplinary options, all without diluting occupational preparation. This group’s strong interest in cross-disciplinary learning and in more practicum or employment channels suggests that progression and employability are best developed side by side.
Undecided students need structured exploration, not generic encouragement. Early diagnostic conversations, short observations across different service settings, mentoring by alumni or practitioners, and scenario-based career workshops can all help them weigh options. Since longer practicum exposure went with less indecision, programmes should make sure that uncertain students do not end up with less exposure; well-supported experience may itself be part of the intervention.
Students planning other-industry employment were a small but distinct group, low on fit and preparedness and high on interest in cross-disciplinary learning. They should not be treated merely as a retention problem. Institutions can make their transferable skills visible and help them carry capabilities such as communication, care, observation, and educational design into neighbouring occupations, while keeping the way back into ECE open should circumstances change.
5.7. Limitations and Directions for Future Research
Several limitations qualify the findings. First, the cross-sectional design supports association but not causal inference. It is possible that students’ plans shape their evaluations of fit and preparedness as well as the reverse. Second, plans were self-reported during enrolment and may change before or after graduation. Longitudinal research should follow students into actual educational and employment destinations. Third, the institution-based sample came from one province and was dominated by women and five-year programme students, limiting generalisability.
Fourth, fit, curriculum-work alignment, and preparedness were measured with single items. Future studies should use multi-item scales and test measurement validity. Fifth, the survey combined kindergarten, childcare, and early-education employment into one ECE category; larger samples should examine these destinations separately. Sixth, practicum duration did not capture placement quality, mentoring, task authenticity, or emotional experience. Finally, the model did not include family socioeconomic resources, academic achievement, local labour-market expectations, perceived pay and status, or social influences. Including these factors would provide a fuller account of educational progression, occupational choice, and indecision.
6. Conclusion
Post-graduation planning among preservice ECE teachers in Chinese higher vocational education is not a binary choice between entering teaching and leaving it. In this sample, further study was the most common plan, immediate ECE employment was reported by fewer than one third, nearly one quarter were undecided, and only a small group planned other-industry employment. These intentions should be interpreted as provisional transition strategies rather than observed graduate destinations.
Career preparedness, perceived training-career fit, interest-based major choice, and practicum exposure in the ordinal specification were the clearest correlates of an ECE-employment plan, while further study and indecision displayed different profiles. Students’ reform priorities also varied across pathways. The practical implication is not to steer every student toward the same immediate destination, but to build a differentiated transition system: strengthen work readiness for those entering ECE, connect vocational and academic progression for those continuing study, provide structured exploration for undecided students, and support transferable career development for those considering other sectors. Such a system can improve the alignment between training experiences, individual development, and a changing ECE employment landscape.
Funding
This work was supported by the Jiangsu Provincial Higher Education Teaching Reform Research Project “Optimisation of the Practical Teaching Evaluation Indicator System for Preschool Education Programmes in Higher Vocational Education Based on the CIPP Model” [grant number 2023JSJG749]; and the Suzhou Municipal Higher Education Teaching Reform Research Project (2024) “Research on an Innovative Talent Cultivation Model for Preschool Education through the Dual Integration of Industry-Education and Science-Education” [grant number 2024SZJG21].
Author Contributions
Jing Li conceived and designed the study and coordinated its implementation. She developed the questionnaire, collected and curated the data, performed the statistical analyses, interpreted the results, prepared the tables and figures, and drafted and revised the manuscript. Mengping Yang contributed to questionnaire design, data analysis, and manuscript revision. Both authors read and approved the final manuscript.