The study was approved by the Science and Technology Ethics Committee of Changchun Normal University. All participants provided voluntary consent to participate. Prior to the start of the survey, participants were fully informed of the study’ objectives and explicitly informed of their right to withdraw at any time. Additionally, participants were assured that their identities would remain confidential and that all collected data would be anonymized.

Respondents utilized the Questionnaire Star software for questionnaire completion. Before responding, all participants provided informed consent. They were informed that “submitting the questionnaire” would be considered as giving consent. Overall, participants spent about 8 min to complete the electronic questionnaire.

According to the literature review, researchers generally consider online self-regulated learning to encompass motivation, self-efficacy, and learning strategies. Among these, learning strategies primarily focus on cognitive learning strategies, metacognitive learning strategies, and resource management learning strategies. Therefore, this survey’s sub-dimension items were derived from published sources, translated into Chinese, and subsequently refined. The questionnaire utilized in this study comprised two sections. The first segment elicited participants’ demographic details, including gender, education qualifications, schooling stages, school location, and years of service. The second segment encompassed items gauging each sub-dimension of OSRL. Responses for all items were recorded on a 7-point Likert-type scale, ranging from 1 denoting “strongly disagree” to 7 indicating “strongly agree.”

To ensure the validity and reliability of the OSRL questionnaire, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted using SPSS 26 and AMOS 26, respectively. The EFA identified five distinct five-factor OSRL instruments, that is OLM (6 items), OLSE (7 items), OLCS (10 items), OLMS (13 items), and OLRM (7 items). The reliability (alpha) coefficients for the five factors ranged from 0.91 to 0.97. The Composite Reliability (CR) values ranged from 0.90 to 0.96. Additionally, the variables exhibited a Kaiser-Meyer-Olkin (KMO) measure of 0.966. The CFA results also supported the five-factor structure and high model fit indices (CMIN/DF = 2.57, RESEA = 0.07, TLI = 0.93, CFI = 0.94). These results signify a robust fit of the proposed model to the observed data, providing strong support for the questionnaire’s reliability and validity. The details of each scale are as follows, and further information can be found in Appendix A:

A hybrid approach combining stratified sampling and random sampling was adopted to recruit 500 teachers from primary, middle, and high schools in Northeast China, respectively. Incomplete responses and questionnaires with a response time of less than 3 min were excluded. Ultimately, 1,443 valid responses were collected, yielding a valid data rate of 96.2%. Among the 1,443 K12 teachers, 498 were primary school teachers, 496 were middle school teachers, and 449 were high school teachers. The demographic distribution included 72.7% female (n = 1,049) and 27.3% male (n = 394). In terms of location, 59.4% were urban teachers (n = 858), while 40.6% were rural teachers (n = 585). Regarding education qualifications, 10.1% held an associate degree (n = 146), 81.5% held a bachelor’s degree (n = 1,176), and 8.4% held a graduate degree (n = 121). Teaching experience was diverse, with 9.7% having 0–5 years, 11.4% having 5–10 years, 8.1% having 11–15 years, 8.1% having 16–20 years, 24.3% having 11–15 years, 21.3% having 16–20 years, 32.7% having 21–25 years, and 13.8% having more than 25 years of teaching experience.

The collected data followed a normal distribution, and a series of analyses were conducted using SPSS 26 software. Firstly, independent samples t-tests were conducted using SPSS 26.0 to examine the OSRL abilities of K12 teachers across different demographic categories, including gender and region. Subsequently, ANOVA was employed to investigate differences in OSRL abilities among primary, middle, and high school teachers. A significance level of p < 0.05 was considered statistically significant. Lastly, Pearson correlation analysis was undertaken to explore the relationships between K12 teachers’ OSRL abilities and their education qualifications as well as years of service.

To address our first research question, we conducted a descriptive statistical analysis on the collected valid data about various dimensions of OSRL among K-12 teachers, as reported in Table 1. Among the five dimensions, OLSE exhibited the lowest level of personal perception (M = 4.02, SD = 0.87), followed by OLMS (M = 4.11, SD = 0.63). The mean of OLRM (M = 4.28, SD = 0.68) was slightly higher than that of OLMS. Conversely, OLM (M = 4.73, SD = 1.40) and OLCS (M = 4.68, SD = 1.04) exhibited the highest and second-highest mean levels of personal perception, respectively.

To address research question 2, independent samples t-tests were employed to analyze the differences in OSRL levels among K-12 teachers of different genders (male = 1, female = 2) and regions (urban = 1, rural area = 2). Additionally, ANOVA was used to analyze differences in OSRL among K-12 teachers across various educational stages (primary school teachers = 1, middle school teachers = 2, high school teachers = 3). The findings showed no notable distinction in OSRL dimensions between male and female K-12 teachers. However, a notable finding emerged from the independent samples t-test, revealing a significant difference in OLSE between urban and rural K-12 teachers, as depicted in Table 2. The mean scores of OLSE for urban K-12 teachers (M = 4.12) were higher than those of rural K-12 teachers (M = 3.86).

The results of the variance analysis of OSRL for K12 teachers are shown in Table 3. We found the OLSE and OLM of high school teachers were higher than that of primary school teachers (F = 6.50, p < 0.05, F = 3.90, p < 0.05), but there were no significant differences between high school teachers and middle school teachers. On the other hand, the high school teachers have higher OLSE and OLM. High school teachers are more willing to participate in online learning, and they are confident in the functionality of the platform, online communication, technology integration, and the ability to complete online learning tasks very well.

To address research question 3, we conducted an analysis examining the correlation between education qualifications and years of service with OSRL among K-12 teachers. Among the respondents, 10.1% held an associate degree (n = 146), 81.5% held a bachelor’s degree (n = 1,176), and 8.4% held a graduate degree (n = 121). To elucidate the relationship between education qualifications and OSRL among K-12 teachers, separate Pearson correlation analyses were performed. The correlations between education qualifications and OSRL among K-12 teachers are outlined in Table 4. Results showed a positive correlation between education qualifications and OLSE (correlation coefficient = 0.129, p < 0.01), while no significant correlation was observed with the other four dimensions. In essence, these findings suggest that as education qualifications advance, K-12 teachers exhibit heightened self-efficacy and confidence in online learning endeavors.

The years of service among K-12 teachers were categorized into six groups: 0–5 years, 6–10 years, 11–15 years, 16–20 years, 20–25 years, and more than 25 years. To facilitate analysis, the years of service were converted into virtual continuous variables, represented by the corresponding numerical values: 1, 2, 3, 4, 5, and 6, respectively. Table 5 displays the correlations between years of service and OSRL among K-12 teachers. Results revealed a significant negative correlation between years of service and OLSE (correlation coefficient = −0.126, p < 0.01), with no significant correlation observed with other dimensions. This finding suggests that K-12 teachers with longer teaching experience tend to be older and may possess weaker network operation skills compared to younger teachers, which could impact their confidence in online learning to some extent.

The results of this study indicate that the mean scores of K-12 teachers’ OSRL across dimensions range between 4 and 5 on a seven-point scale. Among the five scales of the OSRL survey, they scored relatively lower on the OLSE, OLMS, and OLRM compared to others. According to the relevant research on teachers’ OLSE, researchers proposed that teachers’ OLSE is changeable and can be developed through teacher training (Michalsky, 2021; Karlen et al., 2023). To potentially augment K-12 teachers’ OLSE, teacher educators can implement a range of strategic approaches. Initially, teacher educators should consider continuously integrating various online professional development plans tailored to K-12 educational professionals based on the characteristics and evolving trends of K-12 teachers’ OSRL. This deliberate incorporation ensures a sustained exposure of K-12 teachers to technology-enhanced learning modalities across the duration of the program (Liu et al., 2021; Basaran and Yalman, 2020). Subsequently, teacher educators can proffer targeted support mechanisms for K-12 teachers engaged in online learning endeavors. These mechanisms encompass the facilitation of online learning partnerships, the management of online learning materials, the provision of timely feedback on learning progress, and the mitigation of the apprehension and uncertainty inherent in K-12 teachers’ online learning experiences arising from the technological milieu. By perpetually bolstering K-12 teachers’ confidence in online learning and refining their self-efficacy in this domain, teacher educators can cultivate a more proficient cadre of practitioners adept at leveraging digital platforms for learning and teaching.

Besides OLSE, the OLMS and OLRM of K-12 teachers are relatively low. The OLMS refers to K-12 teachers’ self-planning, self-monitoring, and management and regulation of online goal setting, and learning process. This aligns with certain findings derived from prior research. Existing research has found that adults can monitor and reflect on their strategy usage. However, there is still a lack of metacognitive knowledge, especially in online learning environments (Anthonysamy et al., 2020). Some researchers support that the utilization of OLMS among adults is still relatively limited (Hashemyolia et al., 2015; Moreno-Marcos et al., 2019). A wealth of research indicates that OLMS is a crucial dimension of learners’ OSRL abilities, significantly impacting online learning performance (Shen and Liu, 2011; Cho and Heron, 2015; Goradia and Bugarcic, 2017; Dumford and Miller, 2018).

The OLRM primarily involves the strategic scheduling of online learning time, effective effort management, and seeking assistance when facing challenges. Observed differences in the application of OLRM strategies have been noted across traditional and online learning settings (Broadbent and Poon, 2015). The effectiveness of resource administration strategies may differ between traditional and online settings. Learners transitioning from traditional to online environments may encounter unfamiliar challenges, potentially requiring adjustments in their approach to resource management strategies. For example, when learners encounter learning difficulties in a traditional setting, they can easily seek help from teachers and peers. However, in an online learning context, interactions between teachers and learners, as well as among learners themselves, occur asynchronously in terms of time and space. Learners seeking help from teachers and peers may not receive feedback as promptly. Moreover, some learners may not know how to utilize online tools to seek assistance (Broadbent, 2017; Anthonysamy et al., 2020).

Therefore, K-12 teachers can be supported through targeted interventions in online professional development programs to promote the development of OLMS and OLRM. Educational administration departments should establish avenues for K-12 teachers to enhance their knowledge, skills, and practical experience, enabling them to effectively acquire and refine OLMS (Anthonysamy et al., 2021; Kasalak and Dağyar, 2020). Additionally, we recommend that online learning platforms integrate intelligent feedback systems and real-time assessment tools, while visually presenting K-12 teachers’ learning paths and role models to encourage reflection on their online learning and timely adjustments to their learning pace. Support teachers can provide scaffolding for K-12 teachers engaged in online learning, such as learning plan prompts, reflection frameworks, and personalized learning path recommendations, to continuously enhance their OLMS. Moreover, teacher educators should focus on improving K-12 teachers’ OLRM by utilizing intelligent agents, recommending learning partners, offering time management tools, and providing regular learning reminder emails to strengthen their OLRM abilities.

The findings of this study indicate that gender does not significantly influence the OSRL abilities of K-12 teachers. The previous research findings regarding whether gender affects learners’ SRL have been inconsistent. Some studies have found no gender disparities in SRL among US or Turkish samples (Aydoğmuş and Ibrahim, 2022; Liu, 2017). Existing literature examination reveals a consistent trend where past studies on students frequently indicate that females exhibit higher levels of self-regulated learning abilities than males, especially in traditional learning environments (Wang et al., 2022; Zheng et al., 2022). Furthermore, K-12 teachers have been exposed to pedagogical training and instructional methodology throughout their professional development, a distinction that sets them apart from students (De Smul et al., 2018). The variability in research conclusions can primarily be ascribed to differences in study populations and their respective educational environments, encompassing both online and traditional learning settings (Cheng et al., 2023).

The results of the differential analysis suggest that there are disparities in OLSE between urban and rural K-12 teachers, with urban teachers demonstrating higher levels compared to their rural counterparts. In alignment with the viewpoints of existing research, some studies suggest that due to remote geographical locations and inadequate hardware facilities, rural K-12 teachers exhibit relatively lower levels of OLSE. This is reflected in their lack of confidence in utilizing technology for both learning and teaching purposes (Kellerer et al., 2014; Ogodo et al., 2021). Some researchers believe the online learning experience of learners can influence their OLSE (Moos and Azevedo, 2009; Peechapol et al., 2018) Meanwhile, the simplicity and user-friendliness of the online learning platform, along with learners’ digital literacy, can influence their OLSE (Prior et al., 2016; Tsai et al., 2011; Yeşilyurt et al., 2016). Additionally, students’ digital literacy also impacts K-12 teachers’ OLSE in rural areas, where online interactions rely on digital tools. Teachers must not only possess strong digital skills but also address disparities in student proficiency (Xu et al., 2023). In rural regions, limited access to devices and technology often leads to lower student digital literacy, which may undermine teachers’ confidence in delivering effective online instruction (Kellerer et al., 2014).

Therefore, the measures are required to enhance K-12 teachers’ OLSE, with a particular emphasis on rural K-12 teachers. This involves improving hardware facilities in rural schools and implementing online learning support strategies to aid rural K-12 teachers in boosting their OLSE.

Data analysis indicates that high school teachers demonstrate significantly higher levels of OLSE and OLM compared to their counterparts in primary education. Self-reports from high school teachers suggest a prevalent perception that their professional responsibilities are demanding, often necessitating extended hours on campus each day. They perceive online learning as offering flexible scheduling, which minimally disrupts their routine teaching duties. Furthermore, in high schools, there is a relatively higher proportion of young teachers with advanced education qualifications, combined with their proficient use of information technology, which notably contributes to the cultivation of their self-efficacy and motivation towards online learning.

On the other hand, in primary school settings, the developmental stage of students may require the adoption of hands-on and personalized teaching methods. Overcoming challenges associated with young students, coupled with limitations on the use of computer devices in the classroom to protect children’s visual health, typically restricting teachers’ use of technology to no more than 20 min. Consequently, these limitations on accessing and applying online resources may impact the self-efficacy and motivation of primary school teachers in online learning.

The correlation results of this study indicate that the teachers’ education qualifications are positively correlated with OLSE. That is, K-12 teachers with higher qualifications tended to perceive themselves as having higher levels of OLSE. In this study, survey data demonstrates that among the 121 teachers with graduate degrees, 109 are high school teachers, accounting for as much as 90%. This reciprocal validation reinforces the conclusion drawn from our study, suggesting that high school teachers demonstrate a high level of OLSE. Moreover, this conclusion is also consistent with previous research. Prior studies have shown that K-12 teachers with advanced education qualifications tend to exhibit higher levels of OLSE and are perceived as more proficient in effectively integrating technology into teaching and learning practices (Liang et al., 2013; Lee et al., 2020; Peechapol et al., 2018).

Results showed a negative association between K-12 teachers’ years of service and OLSE, suggesting that teachers with more teaching experience in K-12 settings tend to exhibit lower levels of personal confidence in OSRL. This finding aligns with prior research, which has similarly observed a negative relationship between technology-related self-efficacy and either years of service or age (Lin et al., 2018; Cardullo et al., 2021). Concurrently, K-12 teachers with longer years of teaching experience typically correspond to older individuals. These teachers have amassed substantial teaching experience and refined pedagogical techniques. However, their receptivity to emerging technologies diminishes, and they encounter greater challenges in adapting to new tools, environments, and online resources (Pham et al., 2023).

In future online teacher professional development programs, we anticipate a focused emphasis on the K-12 teachers with long years of teaching experience, particularly those situated in rural areas, to furnish them with timely online learning support and assistance. This proactive approach aims to mitigate the challenge of inadequate online self-regulated learning abilities stemming from diminished online learning efficacy.