A Study on Improving Teachers’ Teaching Competence with the Assistance of Information Technology in Early Childhood Education

Teachers are the practitioners of curriculum gardening and the designers, practitioners and reflectors of thematic teaching activities. Optimizing teaching methods and improving teaching ability are the basic guarantee for promoting teachers’ professional development. Since 2018, the state has taken information technology application ability as the core literacy of high-quality teachers in the new era through the implementation of the Education Informatization 2.0 Project [1–2]. Young children are naturally lively and active, have strong image thinking ability, and are good at learning from imitation and observation, while the information technology teaching method is conducive to transforming abstract and stereotyped knowledge and single activities into more vivid and vivid multimedia forms such as graphic, sound, and video, which is conducive to stimulating young children’s interest in participating in the study, and to enhancing the effect of teaching [3]. Therefore, as early childhood teachers must keep abreast of the times, combine information technology with early childhood education, update the educational model, educational means, educational concepts in early childhood education activities, improve their own information technology teaching ability, present vivid, visualized and diversified teaching activities for young children, improve the subjective initiative of young children to participate in learning activities, and promote the better development of the cause of early childhood education [4]. However, in the construction of early childhood education informatization, there are still problems of weak support from governmental authorities, insufficient attention from kindergarten leaders, and inexperience of early childhood teachers, resulting in that the informatization teaching ability of most of the early childhood teachers at this stage is unable to meet the needs of curriculum reform and quality education in the information age [5–6]. At present, kindergartens generally still have the problems that information resources and subject areas cannot be organically integrated, teachers’ information technology application to regional activities is not enough, the information technology teaching is in a single form and the information technology support service system is not sound enough. In view of the above problems, teachers need to actively participate in information technology teaching training and learning, continuously improve their information technology teaching ability, master more advanced teaching methods, educational concepts, and improve their comprehensive quality [7–8].

Teachers are the soul of kindergarten’s internal development, and it is urgent to improve teachers’ teaching ability. Literature [9] found that the ICT integration training program can effectively improve the teaching ability of early childhood teachers through practical case studies, which helps teachers to improve the quality of ICT teaching practice and promotes the successful integration of ICT in early childhood education. Literature [10] took early childhood education teachers in Kundian City, West Kalimantan Province as the research object, and investigated whether digital literacy training could effectively improve the digital literacy competence of early childhood teachers through the experimental method of “one set of pre-test-post-test design”, and the results of the experiment showed that the digital literacy training could effectively improve the teaching competence of teachers. Literature [11] explored the views of pre-service early childhood teachers on the application of information technology in early childhood education through the experiential teaching method, and the study helps future early childhood teachers to form a positive attitude towards the use of information technology in pre-school children’s education, which has a little significance in improving teachers’ teaching ability. Literature [12] points out the impact of ICT on people’s quality of life, and through a systematic review of the literature on digital competence and teachers’ professional development over the years, it reveals the problem of insufficient teacher training and ICT training, and provides a theoretical basis for promoting teachers’ professional development and teaching competence. Literature [13] indicates that the task of modern teachers is to continuously improve their digital skills and educational technologies, and after studying the nature of the digitization of education and the current global trends in education, it points out the key directions of the digitization of education in order to facilitate the improvement of teachers’ information and digital competence.

In addition, literature [14] qualitatively analyzed the status of professional competence of early childhood education teachers in mountainous areas through observation, questionnaires and in-depth interviews, found that early childhood teachers have limitations in applying information technology and developing their own professional skills, and pointed out the factors affecting the development of early childhood teachers’ professional competence, which is intended to provide reference value for enhancing the teaching competence of early childhood teachers in educational innovation. Literature [15] reveals the individual and collective process of constructing technology-integrated knowledge and skills of pre-service early childhood education teachers through a praxis approach in order to guide them through the important digital transformation and high pre-service early childhood teachers’ pedagogical technological competence. Literature [16] emphasizes the importance of information technology in the development of educational innovation and conducts a survey of graduates from 20 colleges and universities in order to explore the supportive elements, key issues, and possible paths for developing pre-service teachers’ ICT teaching competence in colleges and universities at present, and proposes some strategies to better develop pre-service teachers’ ICT teaching competence. Literature [17] investigated kindergarten teachers in S city by using questionnaire survey method and statistical analysis method in order to explore the application of new media technology in the informatization teaching of early childhood education, and the results showed that early childhood teachers realized the positive role of information technology in early childhood teaching, and that strengthening the further integration of teaching and information technology would help to improve the teaching ability of early childhood teachers. Literature [18] takes the survey data of information technology literacy of teachers of 0-3 years old child care institutions in Xi’an City as an example, and explores the strategy of improving the information technology literacy of early childhood teachers based on modern information technology, so as to provide a reference basis for comprehensively improving the information technology literacy and teaching ability of teachers of child care institutions. After investigating preservice educators’ attitudes toward digital technology, literature [19] integrated digital technology into China’s early childhood teacher training program, aiming to improve the ICT infrastructure of preschools and enhance the teaching ability of early childhood teachers.

The study draws on the theory of situational expected value to construct a research model for the enhancement of information technology-assisted teachers’ teaching ability and put forward relevant research hypotheses. After collecting data from teachers of several kindergartens in a certain place by means of questionnaires, the study utilizes structural equation modeling to explore the role mechanism of IT-assisted teachers’ teaching ability enhancement through the assessment of the model’s goodness-of-fit, the testing of research hypotheses, and the analysis of potential profiles. Based on this, the path to improve teachers’ teaching ability with the assistance of information technology is proposed from the three dimensions of reconfiguration of teaching process, innovation of teaching mode and innovation of teaching thinking. Subsequently, teachers of a kindergarten were selected and divided into two groups, and teachers in the observation group adopted IT-assisted teaching strategies. After the experiment, the teachers’ teaching ability, teaching ability difficulties and teaching creativity were compared to explore the actual effect of the teachers’ teaching ability improvement path.

2

Impact of information technology assistance on teachers’ teaching ability

2.1

Modeling

This study is based on the contextual expectation value theory and the teaching ability standard of early childhood teachers, combined with the existing literature research, comprehensively considered the influence factors of the enhancement of the teaching ability of early childhood teachers under the assistance of information technology, and tried to construct a model of the influence factors of the early childhood teachers in the information technology support of information technology teaching and independent learning, and the research model of the enhancement of teaching ability of the information technology-assisted teachers is shown in Fig. 1. Among them, information technology assistance is mainly intelligent technology equipment support to provide early childhood teachers with external support. Perceived usefulness and self-efficacy, as personal value expectations of early childhood teachers, are intrinsic factors influencing information technology-supported informationalized teaching and independent learning of early childhood teachers. IT-supported informationalized teaching refers to the ability of ECE teachers to integrate subject knowledge and IT in designing the teaching process and practicing teaching. IT-supported self-directed learning refers to ECE teachers’ personalized learning and development of subject matter pedagogical knowledge through the use of IT.

This study hypothesizes that all the influencing factors have a positive impact on the improvement of early childhood teachers’ teaching competence in information technology support. Based on the contextual expected value theory, information technology assistance influences teachers’ expected value beliefs and thus teachers’ independent learning and informationalized teaching supported by information technology, as hypothesized below:

H1: Information technology assistance has a positive effect on teachers’ perceived usefulness of technology.

H2: Information technology assistance has a positive effect on teachers’ self-efficacy.

H3: Information technology aids have a positive effect on teachers’ self-directed learning supported by information technology.

H4: Information technology assistance has a positive effect on teachers’ in information technology supported teaching and learning.

H5: Self-efficacy has a positive effect on teachers in information technology-supported self-directed learning

H6: Self-efficacy has a positive effect on teachers in information technology-supported informative teaching.

H7: Perceived usefulness has a positive effect on teachers’ self-directed learning supported by information technology.

H8: Perceived usefulness has a positive effect on teachers’ in information technology-supported informative teaching.

H9: Teachers’ independent learning supported by information technology has a positive effect on informationalized teaching and learning.

2.2

Research tools

In this paper, based on the proposed research hypotheses, a questionnaire was used to collect data and structural equation modeling was applied to test the hypotheses.

2.2.1

Questionnaires

The questionnaire was divided into two parts: the first part included basic information about the early childhood teachers, including gender, specialty and computer application basics, etc. The second part measured the degree of influence on the enhancement of the teaching ability of the early childhood teachers in five aspects: information technology assistance, perceived usefulness, self-efficacy, information technology support for self-directed learning, and information technology support for informationalized teaching, respectively. A five-point Likert scale was used, with 1 = “very poorly” and 5 = “fully”. The questionnaire was conducted in an online manner, and the target respondents were the teachers of several kindergartens in a certain place, 250 questionnaires were distributed, and after excluding the invalid questionnaires, the final recovered questionnaires were 207, with a validity rate of 82.8%. SPSS was used to complete the test of reliability and validity of the questionnaire.

2.2.2

Research methodology

1)

Structural Equation Modeling

Structural equation modeling (SEM) is a statistical method used to describe complex relationships between multiple variables. The most basic structural equation model is factor analysis model, including exploratory factor analysis model (EFA) and validation factor analysis model (CFA).The main purpose of EFA is to find a limited number of uncorrelated potential factors for a given series of externally observed variables to reveal the internal relationship of these variables as a method of data exploration.CFA is mainly used to build a more accurate validation factor analysis model under a certain theory and assumptions. CFA is mainly used to build a more accurate validated factor analysis model under certain theoretical assumptions. This type of model is usually identified by given fixed parameters, and the results obtained have a certain degree of interpretability. However, in CFA, correlations between latent variables are given rather than regression relationships, i.e., reflecting the effects of certain latent variables on other latent variables. Therefore, further generalization based on CFA yields more generalized SEM models, the most classical of which is the LISREL model.

The model consists of two parts, the measurement equation as well as the structural equation. The measurement equation is defined by the following validated factor analysis model: 1 $y_{i} = Λ_{1} η + ε_{y} i = 1, 2, \dots, p_{1}$ 2 $x_{i} = Λ_{2} ξ + ε_{x} i = 1, 2, \dots, p_{2}$ where y_i and x_i are the p₁ × 1 - and p₂ × 1 -dimensional extrinsic observables, Ʌ₁ and Ʌ₂ are the p₁ × q₁ - and p₂ × q₂ -dimensional factor loading matrices, η and are the q₁ × 1 - and q₁ × 1 -dimensional latent variables, and ε_y and ε_x represent the corresponding random error terms. It is assumed that ε_y and ε_x are uncorrelated with their respective latent variables η and ξ and their respective distributions follow a normal distribution with mean 0. The relationships between the different latent variables are then determined by the following equation.

The relationship between the different latent variables is then defined by the following structural equation: 3 $η = Π η + Γ ξ + δ$ where η represents the endogenous latent variable in q₁ × 1 dimensions, Wang represents the exogenous latent variable in q₂ × 1 dimensions, and Π and Γ are the unknown parameter matrices indicative of the relationship between the latent variables in q₁ × q₁ and q₁ × q₂ dimensions, respectively. δ is the q₁ × 1 -dimensional random error term. It is usually assumed that 1 – Π is non-singular and there is no correlation between ξ and δ, with mean values of 0. Assumptions Ф, Ψ_δ, Ψ_εy, and Ψ_εx are the covariance matrices of ξ, δ, ε_y, and ε_x, respectively. Thus the total covariance matrix is: 4 $Σ = (\begin{matrix} Λ_{1} {(1 - Π)}^{- 1} (Γ Φ Γ^{T} + Ψ_{δ}) {(1 - Π)}^{- T} Λ_{1}^{T} + Ψ_{ε_{y}} & Λ_{1} {(1 - Π)}^{- 1} Γ Φ Λ_{2}^{T} \\ Λ_{2} Φ Γ^{T} {(1 - Π)}^{- T} + Γ Φ Λ_{1}^{T} & Λ_{2} Φ Λ_{2}^{T} + Ψ_{ε_{y}} \end{matrix})$

This covariance matrix contains all the unknown parameters. Let S be the sample covariance matrix of the observable data, which can be used as an unbiased estimate of the true value of the covariance matrix. Thus, a statistical method based on S can be established to analyze Σ. Define f [S, Σ] as the objective function that measures the difference between S and S and that is minimized to obtain an estimate of the unknown parameter in Σ. Under the assumption of normality, the estimation of the parameters can be based on the generalized least squares method or the great likelihood method.

2)

Generalized least squares

Assuming that X = c(y_i, x_i) is a p × 1 -dimensional observed random vector with covariance matrix Σ₀ containing q ×1 -dimensional unknown parameters, its variance function can be expressed as: 5 $\begin{array}{l} F_{G L S} (θ) & = \frac{1}{2} [{(S - Σ (θ))}^{T} (V \times V) (S - (θ))] \\ = \frac{1}{2} t r {[(S - Σ (θ)) V^{- 1}]}^{2} \end{array}$ where matrix V is a p × p constant positive definite matrix in the standard GLS, V = S. By minimizing the F_GLS(θ) function, an estimate ${\hat{θ}}_{G L S}$ of the unknown parameter can be obtained, which approximates θ the true estimate θ₀ under large sample conditions. when V = Σ₀, nF_GLS(θ) asymptotically obeys the chi-square distribution with $\frac{p (p + 1)}{2} - q$ degrees of freedom. Under a given significance level α condition, when $n F_{G L S} ({\hat{θ}}_{G L S})$ is smaller than the corresponding chi-square critical value, the corresponding ${\hat{θ}}_{G L S}$ is not rejected, and the constructed SEM can be considered as a possible model of the true model.

3)

Great likelihood method

Suppose X = c(y_i, x_i) is a p × 1 -dimensional, random sample from a multivariate normal distribution N(u₀, Σ₀), and Σ₀ contains q × 1 -dimensional unknown parameters whose sample covariance matrix S follows a Wishart distribution with a density function denoted as: 6 $f (S ∣ Σ_{0}) = C^{*} \frac{\exp (- \frac{n - 1}{2} t r S Σ_{0}^{- 1})}{{| Σ_{0} |}^{\frac{n - 1}{2}}}$ where C is a regularization constant. Its negative log-likelihood function is $- \log C + \frac{n - 1}{2} [\log | Σ (θ) | + t r S Σ {(θ)}^{- 1}]$ , and θ denotes a vector containing all unknown parameters. Thus, its discrepancy function can be expressed as: 7 $\begin{array}{l} F_{M L} (θ) & = \log | Σ (θ) | + t r S Σ {(θ)}^{- 1} - \log | S | - p \\ = t r S Σ {(θ)}^{- 1} - \log | S Σ {(θ)}^{- 1} | - p \end{array}$

Let θ_M be the great likelihood estimate of θ, which approximates the true estimate θ₀ of θ under large sample size conditions, while the corresponding standard error estimate can be derived from the inverse matrix of the information matrix. The model fit goodness-of-fit test can be assessed with the help of the likelihood ratio, i.e.,: 8 $L R = \frac{f (S {| \sum}^{} (θ_{M}))}{f (S | (n - 1) n^{- 1} S)}$ where the numerator is the variance function under the current set of θ_M parameter estimates and the denominator is expressed as the variance function under any parameter space. Based on the theory of great likelihood, the asymptotic distribution of the negative logarithmic form of LR is a chi-square distribution with $\frac{p (p + 1)}{2} - q$ degrees of freedom, and statistical inferences are made under

the given significance level a conditions. In this paper, parameter estimation is performed using the great likelihood method.

2.3

Data statistics and analysis of results

AMOS 26.0 structural equation modeling software was used to test the effect of factors on the improvement of teachers’ teaching competence with the assistance of information technology through goodness-of-fit assessment and parametric assessment.

2.3.1

Goodness-of-fit assessment

Fit refers to the degree of suitability in constructing a model, and in general, the higher the model fit, the more usable the model is when the values of the fit indicators are within the measurement range. Referring to the evaluation criteria of structural equation modeling, this study comprehensively evaluates the fit of the model from three fit indicators, namely, absolute fit, parsimony fit, and value-added fit, in which each fit indicator is within the measurement range, and the results of the fit evaluation are shown in Table 1. In terms of the absolute fit metrics, the chi-square degrees of freedom ratio (x²/df) is 1.883, which is between 1.0 and 3.0, and the fit metrics, such as RMSEA (0.057) and RMR (0.036), are within the critical values. The other metrics of the parsimonious and value-added fit metrics met the fit requirements. In conclusion, the initial model developed in this study has a good fit and is suitable for carrying out further hypothesis testing.

Table 1.

The results of the fitting assessment

Fitting index		Critical value	Actual value
Absolute fitting index	x²/df	<3.00	1.883
	RMSEA	<0.08	0.057
	RMR	<0.05	0.036
Contracted fit index	PGFI	>0.50	0.862
Contracted fit index	PNFI	>0.50	0.738
Value-added fitting index	TLI	>0.90	0.935
	CFI	>0.90	0.924
	IFI	>0.90	0.927

2.3.2

Research hypothesis testing

According to the structural equation modeling, the results of hypothesis testing of the research model are shown in Table 2, with * denoting p<0.05 and *** denoting p<0.001.The research hypotheses H1~H9 are all valid, with path coefficients of 0.548, 0.554, 0.083, 0.098, 0.577, 0.081, 0.439, 0.214, and 0.687, and the p-values are all less than 0.05. The above results indicate that IT assistance positively affects perceived usefulness, and perceived usefulness in turn positively affects ECE teachers’ self-directed learning and informationalized teaching. IT-assisted positively affects ECE teachers’ self-efficacy in IT-supported environments, which in turn affects ECE teachers’ IT-supported self-directed learning. In addition, IT-supported self-directed learning positively influenced IT-supported informationalized teaching.

Table 2.

The study assumes the results of the test

Hypothesis	Path	Estimate	S.E	P	Assumed acceptance
H1	Information technology —>Perceptual usefulness	0.548	0.056	***	Acceptance
H2	Information technology —> Self-efficacy	0.554	0.087	***	Acceptance
H3	Information technology —> Autonomous learning	0.083	0.043	*	Acceptance
H4	Information technology —> Informationization teaching	0.098	0.031	*	Acceptance
H5	Self-efficacy —> Autonomous learning	0.577	0.082	***	Acceptance
H6	Self-efficacy —> Informationization teaching	0.081	0.036	*	Acceptance
H7	Perceptual usefulness —> Autonomous learning	0.439	0.029	***	Acceptance
H8	Perceptual usefulness y —> Informationization teaching	0.214	0.053	***	Acceptance
H9	Autonomous learning —> Informationization teaching	0.687	0.036	***	Acceptance

2.3.3

Potential profile analysis

Individual-centered potential profile analysis was used to identify heterogeneity and to explore whether there are different potential categories for different levels of expected value beliefs of IT-assisted and early childhood teachers as well as whether there are differences in instructional competence enhancement among the different category groups.

In order to explore the potential profiles of ECE teachers’ expected value belief levels, this study identified which IT-assisted and expected value belief profile categories ECE teachers might belong to based on the mean values of perceived usefulness and self-efficacy scores in IT-assisted and expected value beliefs. The number of potential profiles was determined by assessing the model fit metrics, and the main fit metrics selected were AIC, BIC, aBIC, LMR, BLRT, and Entropy (information entropy).

The results of the potential profile analysis are shown in Table 3, when the expected value beliefs of IT support and early childhood teachers when categorized into 3 categories, the values of LMR and BLRT are significant (p<0.05), the value of Entropy is 0.829 (greater than 0.8), and the coefficients of AIC and BIC are reduced, which indicates that the retention of the profile categories of 3 is achieved compared to the other categories of the and the optimal model for the Early Childhood teachers’ Expected Value Beliefs typology. Based on the results of the latent profiles and the scores of the three categories on IT-assisted and expected value beliefs, they can be divided into three main profiling categories:(1) low IT-assisted and expected value beliefs group, with a percentage of 18.4% and a number of 38, (2) medium IT-assisted and expected value beliefs group, with a percentage of 47.5% and a number of 98, and (3) high IT-assisted and Expected Value Beliefs group, 34.1%, numbering 71.

Table 3.

Results of the potential profile analysis

Model	1	2	3	4
AIC	1044.292	913.298	875.765	864.613
BIC	1053.33	929.253	898.467	893.227
aBIC	1046.221	917.758	881.813	872.804
Entropy	NA	0.751	0.829	0.854
LMR	NA	0.0008	0.0007	2.438
BLRT	NA	0.0003	0.0006	0.0007
Class probability	NA	0.439/0.561	0.184/0.475/0.341	0.0357/0.0821/0.3874/0.4948
Individual number	207	91/116	38/98/71	7/17/81/102

3

Information technology-assisted enhancement of teachers’ teaching ability

Based on the analysis of the factors influencing the teaching ability of early childhood teachers supported by information technology assistance in the previous chapter, a model diagram of information technology-enabled education and teaching is constructed from the four perspectives of information technology empowerment, endogenous driving force promotion (perceived usefulness and self-efficacy), information technology conceptual innovation, and information technology strategy innovation. Figure 2 shows the framework of teachers’ teaching ability enhancement, using information technology to empower teachers to optimize teaching methods, reconstruct the teaching process, innovate teaching models, create changes in teaching thinking and other aspects of the endogenous driving force to improve, for the professional development of teachers, for the optimization of the high-quality early childhood education system to make the value of the application of research.

3.1

Reconfiguration of the teaching and learning process by information technology

In the process of teaching process reconstruction, teachers should innovate the concept of information technology and information technology strategy, and apply information technology throughout the teaching process before, during and after class. Mapping and designing according to students’ personalized learning needs, teachers should give full play to their internal driving force, so as to realize the enhancement of information technology teaching ability.

In the teaching preparation before class, teachers should focus on students’ mastery of core basic knowledge and skills. With the help of using big data technology and students’ digital portraits, teachers can deeply analyze and mine students’ multi-dimensional data, including but not limited to information on learning habit monitoring, subject preference identification, learning performance analysis, and mental health assessment. Through the accurate extraction and analysis of these data, teachers can accurately set teaching goals and understand students’ learning needs and tendencies, thus providing strong support for personalized teaching.

In the in-class implementation phase, teachers should shift from focusing on students’ intellectual learning to focusing on learners’ qualities, measuring students’ creativity, critical thinking, teamwork, and complex problem solving skills. The figurative use of digital tools for classroom teaching and the efficient use of smart technologies and teaching methods to organize and implement teaching. Intelligent matching technology can be used to develop grouping programs. At the same time, an information teaching environment is created and VR and AR technologies are utilized to allow students to learn in an immersive way and stimulate their interest and participation in learning.

For post-lesson summarization, teachers focus on evaluation and reflection on the teaching process. Teachers use intelligent recommendation tools and intelligent evaluation and diagnostic technology to customize personalized consolidation programs for students, instantly diagnose learning effectiveness and provide real-time feedback, so as to build a human-machine collaborative, efficient and interactive intelligent teaching environment. In addition, teachers need to accurately evaluate students’ learning effects, quickly identify weak links, and provide immediate feedback to promote students’ self-improvement.

3.2

Innovations in the teaching model by information technology

As the main leader of the classroom, the teacher’s role is not only to impart knowledge, but also to become a guide to inspire students’ thinking and cultivate their innovative ability. In order to effectively cope with this challenge, teachers not only need to innovate the traditional “transmission - acceptance” teaching method and mode, but also need to lead students to break through the traditional one-way transmission, passive acceptance of the learning mode, to stimulate students’ learning initiative and desire to explore. In the process of teaching mode innovation, information technology provides a rich variety of tools and resources for teachers to empower and help them optimize teaching methods and expand teaching thinking. For example: information teaching classroom for teachers to provide a real-time interactive, personalized teaching platform, through multimedia, virtual experiments and other ways to stimulate students’ interest in learning and participation.

3.3

The revolutionization of pedagogical thinking by information technology

In the era of smart education, early childhood teachers need to have a dynamic, open and innovative mindset and actively embrace intelligent educational technology as an important tool for teaching innovation. Early childhood teachers should continue to explore new teaching methods and tools, and utilize information technology to provide students with richer and more diverse learning experiences. Such teaching methods can not only stimulate students’ interest and initiative in learning, but also cultivate their critical thinking, creativity and innovative spirit.

4

Exploring the effects of improving teachers’ teaching ability

4.1

Experimental design

4.1.1

Experimental Objects

Two groups of 20 teachers each were selected from a kindergarten as the observation and control groups, and the teaching ability of the teachers in the two groups was assessed before the experiment, and the difference was not statistically significant (p > 0.05). The control group implemented regular early childhood teaching, based on the syllabus, face-to-face and practical courses were taught and taught, and the theoretical and practical knowledge was assessed after the completion of the teaching program. The observation group implemented information technology-assisted early childhood teaching.

4.1.2

Observation indicators

Compare the changes in the scores of the dimensions of teaching ability of the two groups of kindergarten teachers, count the difficulties of teaching ability of the two groups of teachers, and analyze the teaching creativity of the two groups of kindergarten teachers. Teaching ability is assessed by a self-made scale, and its dimensions mainly include: teaching awareness and attitude, teaching content innovation, combination of basic and skills and theory and practice, and the total score of each item is 10 points at the highest and 0 points at the lowest, and the higher the score suggests that the item is more excellent. Teaching ability where the difficulties lie, take self-made scale for assessment, the main statistics: web browsing, animation processing, audio processing and web production difficulties. Teaching creativity was assessed by a self-developed scale, which mainly assessed four major items, namely, forward-thinking ability, knowledge innovation ability, information technology ability, and flexible teaching ability, with a maximum score of 25 and a minimum score of 0. The scores of each item were added up to get the total score.

4.1.3

Statistical processing

Using SPSS 20.0 statistical software, statistical scores were expressed as mean ± standard deviation $(\bar{x} \pm s)$ and compared using the t-test, and teaching ability difficulties were expressed as n (%) using the x² -test, with p < 0.05 as the difference being statistically significant.

4.2

Analysis of experimental results

4.2.1

Comparison of teaching capacity

Comparison of the teaching ability of teachers in the two groups is shown in Figure 3. The scores of teaching awareness and attitude, teaching content innovativeness, combination of foundation and skills, and theory-to-practice in the dimensions of teaching competence of early childhood teachers in the observation group were significantly higher than those of the control group (p < 0.05), and the dimensions of teaching competence were higher than those of the control group by 58.2%, 30.0%, 31.7%, and 29.0%, respectively. It indicated that information technology-assisted early childhood teaching has positive significance in improving the teaching ability of early childhood education teachers.

4.2.2

Comparison of Teaching Competency Difficulties

Comparison of the teaching ability difficulties of teachers in the two groups is shown in Figure 4. Teachers in the observation group have a better mastery of web browsing, animation processing, audio production and webpage production in teaching ability than the control group (p < 0.05), and the teachers in the observation group have an improvement degree of more than 75% in all dimensions of the information technology teaching ability difficulties. Information technology-assisted teaching can, to a certain extent, reduce the emergence of difficulties caused by web browsing, animation processing, audio processing and web production in the process of teachers’ information technology teaching.

4.2.3

Comparison of pedagogical creativity

Comparison of teachers’ teaching creativity between the two groups is shown in Figure 5. The scores of forward thinking ability, knowledge innovation ability, IT ability and flexible teaching ability in the teaching creativity of teachers in the observation group were 23.0, 21.8, 21.3 and 23.9 respectively, which were 59.7%, 29.8%, 23.8% and 42.3% higher than those of the control group, and all of them met the p < 0.05. The total scores of teaching creativity of the two groups were 89.9 and 65.3. Scores were 37.7% higher for teachers using IT-assisted teaching than for the other group. IT-assisted teaching has positive significance in improving the overall creativity of ECE teachers in teaching.

5

Conclusion

The rapid development of information technology has a revolutionary impact on the development of early childhood education. This project constructs a research model, adopts structural equation modeling to verify the hypotheses, and explores the influencing factors of teachers’ teaching ability improvement under the assistance of information technology. On this basis, we propose a path to improve teachers’ teaching ability under the assistance of information technology, and design a comparative experiment to verify the application effect of this path.

The hypotheses proposed in this paper are all valid, and perceived usefulness and self-efficacy play a mediating role (p < 0.05) in the influence of information technology assistance on the independent learning and informationalized teaching of early childhood teachers. The results of the latent profile analysis showed that the different levels of IT support and expected value beliefs could be categorized into three groups of high, medium, and low categories, accounting for 18.4%, 47.5%, and 34.1%, respectively. It shows the key role of information technology support in improving the teaching ability of early childhood teachers.

In terms of the practice path, information technology is analyzed to promote the reconstruction of teachers’ teaching process, the innovation of teaching mode and the innovation of teaching thinking. In turn, it enhances teachers’ information technology professional development ability, stimulates teachers’ internal driving force, and makes them better adapt to the educational needs of the information technology era.

After the experiment, teachers in the observation group improved their teaching ability, teaching ability difficulty and teaching creativity, and were better than the other group in teaching awareness and attitude (58.2%), teaching content innovation (30.0%), combination of fundamentals and skills (31.7%), and theoretical connection to practice (29.0%). Information technology-assisted teaching can effectively improve the informatization teaching ability of early childhood teachers, solve the difficulties of informatization teaching ability, and enhance teaching creativity.

In the era of “Internet+”, teachers should insist on advancing with the times, participate in the process of the informationization era with a high sense of responsibility and mission, continue to promote the development and application of information technology in teaching, and strive to improve the competence of teaching in early childhood education.

Sprache:: Englisch

Zeitrahmen der Veröffentlichung:: 1 Hefte pro Jahr
Fachgebiete der Zeitschrift:: Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere

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A Study on Improving Teachers’ Teaching Competence with the Assistance of Information Technology in Early Childhood Education

Xinying Li

Mingdi Chen

Online veröffentlicht: 24. Sept. 2025

Eingereicht: 25. Dez. 2024

Akzeptiert: 20. Apr. 2025

DOI: https://doi.org/10.2478/amns-2025-0951

SchlüsselwörterStructural equation modeling, Latent profile analysis, Statistical analysis, Information technology assisted, Teachers’ teaching ability

© 2025 Xinying Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Structural equation modeling, Latent profile analysis, Statistical analysis, Information technology assisted, Teachers’ teaching ability