Preparing TVET Teachers for Sustainable Development in the Information Age: Development and Application of the TVET Teachers’ Teaching Competency Scale

Abstract

Echoing research interests in recent concepts and models of TVET teachers’ teaching competency, it is clear that the focus of existing scales needs to be updated. The paper summarizes six aspects of TVET teachers’ competency in the information age and develops the corresponding scale using 88 items. The data from 461 TVET teachers confirm the reliability and validity of the scale, which serves as a measuring instrument the teaching competency of TVET teachers in the information age. The paper collects answers from 815 TVET teachers, who are clustered into six types by k-means clustering, each representing shared characteristics of a group of TVET teachers. The paper develops a feasible method to classify TVET teachers according to the characteristics of their teaching ability in six aspects, which can provide valuable clues for the designing of tailored teacher training programs and teacher development strategies for vocational education teachers in the information age.

1. Introduction

Technology has changed almost every aspect of people’ lives. In the Industry 4.0 era, the digital transformation of the world has created gaps in new knowledge and skills that need to be filled by the future workforce and the teachers who train it. To meet the demands of in-service teachers and trainers, as well as TVET (Technical and Vocational Education and Training) leaders who want to upscale their professional learning and development, there is a need to clarify the status quo of teachers’ teaching competency. A scale can be an efficient instrument in the evaluation of teacher teaching. It is commonly used for profiling in-service teachers, examining whether they meet the necessary competence requirements, and giving directions regarding their career development [1]. Scales can also be used for self-assessment of one’s professional competency level so as to plan one’s career trajectory accordingly.

In recent years, TVET teachers’ teaching competency has gained increasing attention [2]. As Nessipbayeva noted, teaching competency is essential to an educator’s pursuit of excellence [3]. Researchers and policymakers believe that promoting TVET teachers’ competency can enhance teaching practices, which will further increase student achievement and the cultivation of application-oriented talents [1,4,5,6]. However, there is a lack of knowledge related to the fundamental questions: What is the exact meaning of the concept of TVET teachers’ competency in the information age and how can it be assessed? Some definitions, models, or frameworks regarding TVET teachers’ competency already exist [7,8], but none has taken the historical background of the information age into consideration. Neither has the corresponding competency scale been well examined in empirical research. Some studies tried to measure TVET teachers’ teaching competency, but few show enough evidence of the quality of the measurement instruments [9,10].

Therefore, this study aims to analyze the scales for TVET teachers’ teaching competency in the information age and develop and validate a corresponding scale using empirical evidence.

2. Literature Review

In the last 20 years, two kinds of technology transformation have fundamentally changed the landscape of TVET: the transformation of TVET through ICT and the technological transformation of the world of work. Transforming TVET through ICT has been accelerated since the Third International Congress on Technical and Vocational Education and Training, held in Shanghai in 2012 [11]. As a result, digitalization, blended learning, and online learning have become the catchphrases in TVET, although the degree of their implementation differs from country to country [12].

2.1. Measurement of Teachers’ Competency in the Information Age

The relevant research on the framework of teachers’ teaching competency measurement in the information age comes mainly from two main theoretical frameworks, TPACK and DTC.

2.1.1. Relevant Research Based on TPACK

Technological Pedagogical Content Knowledge (TPACK) has been introduced as a theoretical framework for understanding the teachers’ knowledge needed for effective technological integration. The TPACK framework is constructed based on Shulman Pedagogical Content Knowledge (PCK), including three core elements, namely, content knowledge (CK), pedagogical knowledge (PK), and technical knowledge (TK) [13]. Schmidt et al. developed a questionnaire to measure the teaching competency of pre-service teachers’ [14]. Archambault and Crippen developed a 24-item scale, which consists of seven dimensions: pedagogy, content, technology, pedagogical content, technological content, technological pedagogy, and technological pedagogical content [15], to evaluate 596 K-12 teachers in the United States.

Based on TPACK, Bostancioglu et al. developed a self-reported questionnaire regarding English language teaching, using 36 computer-assisted language learning international experts to assess the content validity [16]. They also employed the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to explore and validate its potential factors of structure through a survey of 542 English teachers. Eventually a 5-point Likert scale of 76 items was developed. Ge and Han, also inspired by the TPACK measurement scale, developed a 30-item, 5-point Likert scale questionnaire with four dimensions; in total, 465 undergraduate college teachers and 682 TVET teachers took part in the survey [17].

A self-reporting scale, based on the TPACK framework, helps teachers reflect on themselves, and tests teachers’ self-efficacy. However, assessing one’s own abilities accurately is a difficult task because people may be unaware of their lack of knowledge and abilities, or may underestimate their own competency [18].

2.1.2. Relevant Research Based on DTC (Digital Teaching Competence)

The DTC framework is the basis on which three major standards are built. In the European Union, the DigCompEdu framework has been used to develop a self-assessment tool, known as DigCompEdu CheckIn, currently being pre-tested among educators in member states. The questionnaire has three versions for teachers in different types and levels of educational institutions and divides teachers’ information literacy into six levels: newcomer, explorer, integrator, expert, leader, and pioneer [19]. The scale has been widely used in the European Union. For example, Trindada et al. translated the scale and applied it to 127 primary and secondary school teachers in central and southern Portugal, finding it of good reliability and validity [20].

The National Institute of Educational Technologies and Teacher Training (INTEF) has proposed a Common Framework for Digital Teaching Competence, which consists of five areas: information and information literacy, communication and collaboration, digital content creation, safety, and problem solving. Each area consists of 3 to 6 competencies that serve as a benchmark for digital teaching competency (DTC), with a total of 21 questions for teachers’ self-evaluation [21].

Lázaro and Gisbert proposed the COMDID (Competència Digital Docent) framework in which DTC is grouped into 4 dimensions [22]: didactic, curricular and methodological; planning, organization and management of digital technological resources and spaces; relational aspects, ethics and security; and personal and professional aspects. The questionnaire rates teachers’ information literacy at four levels, namely the beginner, the average, the expert, and the transformer, with a total of 23 items. Although COMDID, INTEF, and EU DigCompEdu have different structures, they have relatively clear inter-relationships, as shown in

Table 1. Inter-relationship among COMDID, INTEF, and DigCompEdu.

COMDID	INTEF	DigCompEdu
1. didactic, curricular, and methodological	1. information and information literacy 5. problem solving	3. teaching and learning 4. assessment 5. empowering learners 6. equitable access
2. planning, organization, and management of digital technological resources and spaces	1. information and information literacy 3. digital content creation	2. digital resources
3. relational aspects, ethics, and security	2. communication and collaboration 3. digital content creation 4. safety	1. professional engagement 5. empowering learners 6. equitable access
4. personal and professional aspects	5. problem solving	1. professional engagement

.

2.2. Measurement of TVET Teachers’ Competency

There are different perspectives on the measurement of teachers’ teaching competency in vocational education.

Some researchers have transferred the curriculum development method of vocational education to TVET teachers’ teaching competency development, which is a great innovation. DACUM, or developing a curriculum, is a method of analyzing and determining the abilities required for a certain occupation. Currently, it has become a scientific, efficient, and economical method of job analysis to determine the desired abilities of job positions. Zhu Jianliu developed a measuring instrument using the DACUM method for higher vocational college teachers, which consists of 45 5-point Likert items, covering 10 areas [23].

Some scholars have adopted statistical models and developed questionnaires. For example, the Rasch model is used to measure latent traits, such as attitude or ability. It shows the probability of an individual choosing a correct response on a test item [24]. Based on the Rasch model, Aziz et al. constructed a scale for TVET teachers. A total of 45 questions were used to evaluate the abilities of 53 teachers in a vocational college [25]. Md Yunos et al. also developed a survey questionnaire, with 84 5-point Likert items in 6 dimensions, based on the same model. The questionnaire proved to be reliable and valid through a survey of 183 TVET teachers from Malaysia and Indonesia [26].

Some scholars have applied the framework of student competency to teacher competency assessment. The KOMET competency assessment framework was originally developed by the TVET Research Group at the University of Bremen [27]. The competency model comprises requirement, content, and action dimensions [28]. Later, the Chinese TVET experts adjusted KOMET into four dimensions: nominal competence, functional competence, process competence, and design competence. Through two rounds of tests, the questionnaire showed good reliability and validity.

Through literature research, we find that: firstly, the structure of teaching competency evaluation under the TPACK and DTC frameworks is clear, and they have been widely used, showing good reliability and validity, which provides academic literature support for this study. Secondly, the evaluation of teachers’ teaching competency in the existing research is mainly aimed at general teachers (such as primary school, secondary school, and university teachers). The research is rare relative to the evaluation of the teaching competency of teachers in vocational colleges. TVET teachers concentrate on practical abilities and pay specific attention to practical operation and mastery of occupational skills. Under the digital background, TVET teachers are facing digital transformation and spend a significant amount of time on the application of information technology to practical teaching Therefore, the measurement of TVET teachers’ teaching competency needs to take teachers’ digital ability, practical skills, operational ability, and general teaching ability into account. The ability to integrate these key elements and measure TVET teachers’ teaching competency is insufficient in the existing research. Therefore, this study will make further explorations and attempt, on the basis of the existing teacher teaching competency scale, to develop and compile a teaching competency measurement scale that conforms to the teaching characteristics of TVET teachers.

2.3. Multiple-Role Characteristics of TVET Teachers in the Information Age

TVET teachers and general education teachers have certain similarities. As for TVET teachers, they should share basic competences that are necessary for all teachers, such as curriculum development and curriculum teaching abilities. However, TVET teachers should also have unique qualities. They are required to play three additional roles: technician/engineer, digital citizen, and lifelong learner (As is shown in Figure 1) [29].

Based on previous studies (

Table 2. Basis of preliminary criteria construction.

First-Level Criteria	Main Reference Sources
Curriculum development	Wahba, 2006 [4]; Research group, 2010 [30]
Curriculum teaching	Peterson, 2003 [31]
Professional knowledge	Ally, 2019 [32]
Occupational ability	Rofiq et al., 2019 [10]
Information literacy	Ministry of Education of PRC, 2020 [6]
Research and development	Ministry of Education of PRC, 2020 [6]

) and the analysis of the multiple-role characteristics of TVET teachers (Figure 1), in this study, the first-level criteria are determined as follows: curriculum development, curriculum teaching, professional knowledge, occupational ability, information literacy, and research and development.

3. Methods

This section consists of the instrument development, the participants, the reliability test, and the validity test.

3.1. Instrument Development

As stated in the literature review, several domains of TVET teachers’ teaching competency in the information age are identified: curriculum development, curriculum teaching, professional knowledge, occupational ability, information literacy, and research and development. All the detailed behaviors are analyzed and compared; the same or similar behaviors were merged into one item, and behaviors inconsistent with our definition were deleted. Finally, we come up with a pool of potential scale items for each domain. A response format using a 5-point scale (1 = strongly disagree, 2 = relatively disagree, 3 = neutral, 4 = relatively agree, 5 = strongly agree) is adopted to measure teachers’ teaching competency. Sub-dimensions (sections) and the number of items in each sub-dimension are as follows:

• Curriculum development: Job analysis, Professional task analysis, curriculum system construction, and project curriculum development, with 18 items in total;
• Curriculum teaching: Teaching design, teaching implementation, and implementation evaluation, with 19 items in total;
• Professional knowledge: Professional basic knowledge and knowledge of new technology, with 6 items in total;
• Occupational ability: Occupational communication and cooperation skills, occupational practice skills, and occupational service skills, with 14 items in total;
• Information literacy: Information awareness and attitude, information knowledge and skills, information application and innovation, information social responsibility, with 17 items in total;
• Research and development section: research on teaching, professional development, and professional ethics education, with 14 items in total.

3.2. Participants

A total of 461 Chinese TVET teachers, from a variety of specialties, in Shaanxi province, Shandong province, and Jilin province participated in our study from 16 December 2020 to 8 January 2021. All teachers were informed that their participation was voluntary, and the confidentiality of their responses was assured. Demographic characteristics are specified in

Table 3. Sample characteristics (N = 461).

Demographics and Professional Experiences	Number (%)
Gender
Female	293 (63.56%)
Male	168 (36.44%)
Age
$\le$30	35 (7.59%)
31–40	166 (36.01%)
41–50	146 (31.67%)
51–60	113 (24.51%)
>60	1 (0.22%)
Years of teaching experience
1–5 years	61 (13.23%)
6–10 years	67 (14.53%)
11–20 years	155 (33.62%)
>20 years	178 (38.61%)
Years of industrial experience
None	195 (42.3%)
<1	112 (24.3%)
1–2	63 (13.67%)
2–3	20 (4.34%)
3–5	23 (4.99%)
5–10	22 (4.77%)
>10	26 (5.64%)
Highest diploma/degree attained
Bachelor’s	183 (39.7%)
Master’s	249 (54.01%)
Doctoral	3 (0.65%)
Other degrees	26 (5.64%)
Subject taught
agriculture and forestry, animal husbandry, and fishery	12 (2.6%)
civil construction	12 (2.6%)
equipment manufacturing	49 (10.63%)
biology and chemical engineering	10 (2.17%)
transportation	6 (1.3%)
electronic information	53 (11.5%)
food and grain	4 (0.87%)
medicine and health	123 (26.68)
finance and business	30 (6.51%)
culture and art	34 (7.38%)
education and physical education	123 (26.68%)
public security, judicature, public administration	5 (1.08%)

.

3.3. Reliability Test

This study uses SPSS 24.0 to conduct the internal consistency test of the coefficient of the Cronbach’s alpha reliability, the KMO, and the Bartlett tests, followed by Mplus 7.0 for confirmatory factor analysis.

According to the general principles of questionnaire preparation, the evaluation of each question item mainly includes six indicators, and if it shows any of the following characteristics, the question should be modified or removed: (1) missing values—more than 10% of the questions are not filled in; (2) mean—the mean of a question is higher than 4.5 or lower than 1.5; (3) skewness coefficient—the absolute value of the skewness coefficient of the topic is higher than 1; (4) t-test analysis—the t-test of independent samples from the high and low groups does not reach the level of significant difference; (5) correlation between the revised questions and the overall score—the correlation coefficient between the revised questions and the total score is lower than 0.3; (6) Cronbach’s alpha coefficient—the Cronbach’s alpha coefficient of an item is higher than the overall α coefficient of the questionnaire [17].

Based on the data collected, the results of the item analysis are: (1) missing values—none of the 88 questions show missing values; (2) mean—the mean of the 88 questions ranges from 3.34 to 4.25; (3) skewness coefficient—the coefficient ranges from −0.802 to −0.107, and the absolute value is less than 1; (4) t-test analysis—the t-test coefficients of the items have reached the significant difference level; (5) correlation between the revised questions and the overall score—the total correlation range of topics is between 0.644 and 0.855; (6) Cronbach’s alpha—the Cronbach’s alpha coefficient of the questionnaire is 0.990, and the Cronbach’s alpha coefficient of each second-level criterion is lower than 0.990 (see

Table 4. Reliability test.

First-Level Criteria	α	Items(n)	Second-Level Criteria	α
A Curriculum development	0.968	18	A1 Job analysis	0.937
			A2 Professional task analysis	0.847
			A3 Construction of curriculum system	0.933
			A4 Development of project curriculum	0.919
B Curriculum teaching	0.976	19	B1 Teaching design	0.931
			B2 Teaching implementation	0.945
			B3 Implementation evaluation	0.956
C Professional knowledge	0.929	6	C1 Basic professional knowledge	0.913
			C2 Knowledge of new technology	0.880
D Occupational ability	0.967	14	D1 Occupational communication and cooperation	0.935
			D2 Occupational practice skills	0.919
			D3 Occupational service skills	0.948
E Information literacy	0.949	17	E1 Information awareness and attitude	0.897
			E2 Information knowledge and skills	0.943
			E3 Information application and innovation	0.946
			E4 Information social responsibility	0.918
F Research and development	0.975	14	F1 Research on teaching	0.972
			F2 Professional development	0.965
			F3 Professional ethics education	0.934
	overall α		0.990

). Therefore, the scale has high reliability, and no items need to be removed.

3.4. Validity Test

When the KMO value is less than 0.50, factor analysis is not suitable among the variables. If the KMO value is greater than 0.80, the relationship between the item variables is good, and the item variables are suitable for factor analysis. If the KMO value is greater than 0.90, the relationship between the item variables is deemed as excellent, which means that it is suitable to conduct factor analysis among the item variables [33].

In this study, the KMO is 0.977, which is greater than 0.8. The result of Bartlett’s sphericity test reaches the significant level, and the cumulative interpreted variance is 75.78%. This indicates the data are suitable for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) (see

Table 5. KMO and Bartlett tests.

KMO		0.977
Bartlett’s test for sphericity	approximate chi-square	6754.422
	degrees of freedom	2441
	significance	<0.001

).

A total of six common factors were extracted through PCA (principal component analysis) and PAF (principal axis factoring), of which the eigenvalue was greater than 1. Then exploratory factor analysis was performed using the maximal variance method, and direct oblimin was used for the interpretation of factors. According to the six factors, this study sorted out the numerical analysis of load interpretation, eigenvalue, and percentage of interpretation variance for each factor (See Appendix A,

Table A1. EFA of items.

Factor	Items	Common Factor Variance	Factor Loading	Eigenvalue	Explained Variance Ratio
A. Curriculum Development	A1–1 Able to design investigation forms according to the requirements of specialty investigation programs.	0.660	0.625	42.75	59.38%
	A1–2 Able to analyze investigation data and write reports.	0.704	0.617
	A1–3 Able to participate in writing specialty construction plans.	0.646	0.612
	A1–4 Able to collect and analyze professional competence standards in the industry.	0.704	0.614
	A1–5 Able to use professional competence standards based on students’ actual situation.	0.772	0.639
	A2–1 Able to design task and professional competency analysis forms according to investigations.	0.778	0.641
	A2–2 Able to select experts according to task analysis requirements.	0.781	0.588
	A2–3 Able to organize or participate in task analysis conferences.	0.746	0.603
	A3–1 Familiar with the specialty curriculum system, curriculum content requirements, and the interface between the various courses, to build a specialty curriculum system.	0.782	0.722
	A3–2 Able to design and write a teaching schedule.	0.750	0.659
	A3–3 Able to participate in the formulation of a curriculum plan.	0.767	0.721
	A3–4 Able to write specialty talent cultivation plan according to the specialty curriculum system.	0.774	0.672
	A3–5 Able to design the comprehensive practical training teaching program and entrepreneurship teaching program.	0.771	0.663
	A3–6 Able to interpret the logical relationship between professional competence standards and talent cultivation plans.	0.772	0.639
	A4–1 Able to formulate curriculum standards according to the professional competence standards of industry practitioners.	0.743	0.665
	A4–2 Able to formulate the implementation plan and main measures of the curriculum standards.	0.738	0.612
	A4–3 Able to interpret teaching plans.	0.699	0.477
	A4–4 Able to write a complete project curriculum implementation plan.	0.647	0.485
B. Curriculum teaching	B1–1 Make clear the knowledge, skills and attitude goals of instructional design.	0.713	0.670	4.43	65.53%
	B1–2 Able to determine learning tasks and projects.	0.772	0.709
	B1–3 Able to determine teaching strategies.	0.750	0.665
	B1–4 Able to prepare training materials, equipment, and tools.	0.738	0.564
	B1–5 Able to design the practical teaching environment.	0.772	0.520
	B1–6 Able to design a diagnostic evaluation.	0.689	0.610
	B1–7 Able to design a formative evaluation.	0.730	0.663
	B2–1 Able to use physical objects, media display, teaching aids demonstration, experiments, and other situational guidance methods.	0.763	0.734
	B2–2 Able to organize practical training activities.	0.781	0.787
	B2–3 Able to organize simulated teaching activities.	0.787	0.771
	B2–4 Able to organize entrepreneurship teaching activities.	0.700	0.703
	B2–5 Have keen observation, analysis, and coping ability.	0.766	0.705
	B3–1 Able to organize and implement course evaluation.	0.791	0.696
	B3–2 Able to analyze and provide feedback for course evaluation.	0.790	0.715
	B3–3 Able to determine the content and standard of teaching evaluation.	0.812	0.738
	B3–4 Able to organize and implement teaching evaluation.	0.834	0.704
	B3–5 Able to analyze and provide feedback for teaching evaluation.	0.820	0.760
	B3–6 Able to organize and implement student learning evaluations.	0.799	0.743
	B3–7 Able to analyze and provide feedback on student learning evaluation.	0.790	0.715
C. Professional knowledge	C1–1 Have the basic knowledge related to the specialty.	0.762	0.798	2.57	69.10%
	C1–2 Have relevant work experience.	0.755	0.749
	C1–3 Have the practical application of basic professional knowledge.	0.780	0.786
	C2–1 Able to continuously learn advanced technical knowledge in related fields.	0.772	0.667
	C2–2 Able to understand and strive to learn the application of new technical knowledge.	0.760	0.649
	C2–3 Able to analyze the application of new technical knowledge.	0.749	0.629
D. Occupational ability	D1–1 Able to analyze industry training needs and identify industry training needs.	0.742	0.373	2.04	71.94%
	D1–2 Cooperate with industry personnel on projects and training.	0.765	0.343
	D1–3 Able to assist local government in talents-training ser-vices.	0.725	0.356
	D2–1 Able to arrange teaching tasks in the campus training base according to the professional teaching process.	0.716	0.624
	D2–2 Able to check and evaluate the operational status of the campus training base (such as security risks).	0.742	0.603
	D2–3 Able to guide students to obtain qualification certificates.	0.746	0.668
	D2–4 Able to guide students to participate in skills competitions.	0.747	0.748
	D2–5 Able to guide students regarding internships.	0.795	0.748
	D2–6 Able to participate in the establishment of an off-campus professional training base.	0.703	0.652
	D3–1 Able to analyze industry training needs and identify industry training needs.	0.816	0.626
	D3–2 Able to set training plans according to industry competency standards.	0.800	0.617
	D3–3 Able to implement training and evaluate its effectiveness.	0.821	0.623
	D3–4 Able to participate in technical activities of industry enterprises.	0.813	0.564
	D3–5 Able to produce industrial enterprises’ technological achievements.	0.783	0.631
E. Information literacy	E1–1 Able to understand the important role of the effective application of information technology in innovating the teaching mode, improving the quality of vocational education, and promoting the teaching reform of vocational education.	0.804	0.638	1.47	73.98%
	E1–2 Have the consciousness to carry out the integration of information technology and course teaching in teaching, and carry on the education and teaching reform accordingly.	0.811	0.656
	E1–3 Have the awareness of building and sharing digital teaching resources, such as online courses and virtual simulation training systems.	0.742	0.628
	E1–4 Focus on the latest development of information technology (such as big data, cloud computing, Internet of things, VR/AR, artificial intelligence, 5G network, blockchain, etc.) and education concepts, and try to apply them to talent cultivation in vocational education.	0.763	0.636
	E1–5 Have the consciousness that applies the evaluation to the ICT teaching.	0.837	0.703
	E2–1 Understand the basic concepts and theoretical basis of ICT teaching.	0.775	0.615
	E2–2 Understand the characteristics and functions of digital teaching resources and teaching tools.	0.796	0.627
	E2–3 Know how to create digital teaching resources.	0.747	0.557
	E3–1 Able to apply information technology to communicate with students about learning.	0.771	0.601
	E3–2 Able to use information technology to create family-school cooperation.	0.773	0.615
	E3–3 Able to use information technology to collaborate and communicate with colleagues in teaching and research.	0.754	0.614
	E3–4 Able to use information technology to construct the teaching mode of “theory-practice” and “learning-working,” combining the virtual and the real.	0.776	0.597
	E3–5 Able to apply information technology to implement the teaching process and production process of the school-enterprise cooperation teaching model.	0.800	0.622
	E3–6 Able to use mobile terminals, VR/AR, Internet of things, 5G, and other technologies to build a new model of experiment, practical training, and practical teaching.	0.821	0.635
	E4–1 Able to ensure that all students have equal access to learning resources, tools, and environments.	0.771	0.774
	E4–2Able to cultivate students’ knowledge of information security, awareness of protecting their own and others’ privacy, awareness of distinguishing healthy information from harmful information, awareness of using information technology in a safe and healthy way.	0.775	0.747
	E4–3 Able to teach students the knowledge of laws and regulations related to the use of information technology and ethical concepts, cultivate students’ legal awareness, and demonstrate the relevant normative behavior.	0.811	0.757
F. Research and Development	F1–1 Able to carry out applied science and technology research related to the specialty, and can put forward constructive suggestions for the school’s scientific research management.	0.767	0.689	1.29	75.78%
	F1–2 Able to host applied science and technology research projects.	0.751	0.755
	F1–3 Able to carry out vocational education teaching reform research, and actively put forward constructive suggestions for school education and teaching reform.	0.809	0.635
	F1–4 Able to host vocational education teaching research projects.	0.761	0.665
	F1–5 Able to transform scientific research achievements into specialty construction, and actively put forward constructive suggestions for the specialty construction of the school.	0.781	0.662
	F2–1 Able to master professional skills related to specialty.	0.740	0.539
	F2–2 Able to propose goals, tasks, and measures for personal professional development.	0.737	0.507
	F2–3 Able to participate in on-the-job training and short-term training.	0.739	0.557
	F2–4 Able to organize, design, and participate in teaching and research activities.	0.694	0.469
	F2–5 Able to promote the development of team building.	0.717	0.496
	F3–1 Familiar with and consciously abide by the national vocational education laws, regulations, and policies.	0.774	0.787
	F3–2 Able to comply with professional ethics and relevant industry rules and regulations.	0.771	0.785
	F3–3 Able to educate students about professional ethics, laws, and regulations in related industries.	0.746	0.773
	F3–4 Able to evaluate the performance of students’ professional ethics.	0.694	0.756

).

The results show that the items in the questionnaire can be extracted into six factors, which correspond to the six dimensions of the TVET teachers’ teaching competency in the information age. In the correlation analysis of the six dimension and 88 items, it is found that:

(1) The items A4–3 and A4–4 are grouped into the Curriculum Teaching dimension; (2) the items D1–1, D1–2, and D1–3 are grouped into the Research and Development dimension. This means that the boundary between Curriculum Development and Curriculum Teaching is not clear. Hence, the A4–3 and A4–4 are modified to “Able to interpret curriculum plans,” and “Able to design the project-based course,” respectively. A few words in F1 and D1, such as “project” and “explore” are prone to cause confusion, so the researcher changed these statements.

Confirmatory factor analysis (CFA) is used to confirm whether the questions contained in the questionnaire at all levels are in line with the original theoretical expectations. Structural equation modeling (SEM) software is used to verify and explore whether the factor structure of the questionnaire is compatible with the samples. According to the questionnaires based on multiple-role characteristics of TVET teachers in the information age, an SEM is established and tested by using Mplus 7.0. The six-factor model demonstrates an acceptable fit to the data.

The χ2/df value is 2.77, the Tucker–Lewis index (TLI) and the comparative fit index (CFI) are all above 0.9, and the RMSEA is 0.062. The model fitting effect is good (see

Table 6. Evaluation indicators of model fit.

Statistic	Standard Value of Fitness	Actual Fitting Value
χ2/df	<8.0	2.77
RMSEA	<0.08	0.062
CFI	>0.90	0.905
TLI	>0.90	0.901

). The results show that the sample data can be well fitted to the six-dimensional factor model, thus verifying the validity of the structural framework of the questionnaire [17,34].

Based on the research process discussed above, an assessment instrument is proposed (see

Table 7. TVET teachers’ teaching competency scale.

First-Level Criteria	Second-Level Criteria	Items
A. Curriculum Development	A1. Job analysis	(1) Able to design investigation forms according to the requirements of specialty investigation programs. (2) Able to analyze investigation data and write reports. (3) Able to participate in writing specialty construction plans. (4) Able to collect and analyze professional competence standards in the industry. (5) Able to use professional competence standards based on students’ actual situation.
	A2. Professional task analysis	(1) Able to design task and professional competency analysis forms according to investigations. (2) Able to select experts according to task analysis requirements. (3) Able to organize or participate in task analysis conferences.
	A3. Construction of curriculum system	(1) Familiar with the specialty curriculum system, the curriculum content requirements, and the interface between the various courses in order to build a specialty curriculum system. (2) Able to design and write a teaching schedule. (3) Able to participate in the formulation of a curriculum plan. (4) Able to write a specialty talent cultivation plan, according to the specialty curriculum system. (5) Able to design a comprehensive practical training teaching program and entrepreneurship teaching program. (6) Able to interpret the logical relationship between professional competence standards and talent cultivation plans.
	A4. Development of project curriculum	(1) Able to formulate curriculum standards according to the professional competence standards of industry practitioners. (2) Able to formulate the implementation plan and main measures of the curriculum standards. (3) Able to interpret curriculum plans. (4) Able to design the project-based course.
B. Curriculum teaching	B1. Teaching design	(1) Able to make clear the knowledge, skills, and attitude goals of instructional design. (2) Able to determine learning tasks and projects. (3) Able to determine teaching strategies. (4) Able to prepare training materials, equipment, and tools. (5)Able to design a practical teaching environment. (6) Able to design diagnostic evaluations. (7) Able to design formative evaluations.
	B2. Teaching implementation	(1) Able to use physical objects, media display, teaching aids demonstrations, experiments, and other situational guidance methods. (2) Able to organize practical training activities. (3) Able to organize simulated teaching activities. (4) Able to organize entrepreneurship teaching activities. (5) Have keen observation, analysis, and coping ability.
	B3. Teaching evaluation	(1) Able to organize and implement course evaluation. (2) Able to analyze and provide feedback regarding course evaluation. (3) Able to determine the content and standard of teaching evaluation. (4) Able to organize and implement teaching evaluation. (5) Able to analyze and provide feedback regarding teaching evaluation. (6) Able to organize and implement student learning evaluation. (7) Able to analyze and provide feedback regarding student learning evaluation.
C. Professional knowledge	C1. Professional basic knowledge	(1) Have the basic knowledge related to the specialty. (2) Have relevant work experience. (3) Have the practical application of basic professional knowledge.
	C2. Knowledge of new technology	(1) Able to continuously learn advanced technical knowledge in related fields. (2) Able to understand and strive to learn the application of new technical knowledge. (3) Able to analyze the application of new technical knowledge.
D. Occupational ability	D1. Occupational communication and cooperation skills	(1) Able to collect and analyze industry information. (2) able to cooperate with industry personnel on projects and training. (3) Able to assist local government in talents-training services.
	D2. Occupational practice skills	(1) Able to arrange teaching tasks in the campus training base according to the professional teaching process. (2) Able to check and evaluate the operational status of the campus training base (such as security risks). (3) Able to guide students to obtain qualification certificates. (4) Able to guide students to participate in skills competitions. (5) Able to guide students regarding internships. (6) Able to participate in the establishment of an off-campus professional training base.
	D3. Occupational service skills	(1) Able to analyze and identify industry training needs. (2) Able to set training plans according to industry competency standards. (3) Able to implement training and evaluate its effectiveness. (4) Able to participate in technical activities of industry enterprises. (5) Able to produce industrial enterprises’ technological achievements.
E. Information literacy	E1. Information awareness and attitude	(1) Able to understand the important role of the effective application of information technology in innovating the teaching mode, improving the quality of vocational education, and promoting the teaching reform of vocational education. (2) Have the consciousness to carry out the integration of information technology and course education in teaching, and to carry out the educational and teaching reform accordingly. (3) Have the awareness to build and share digital teaching resources, such as online courses and virtual simulation training systems. (4) Focus on the latest developments of information technology (such as big data, cloud computing, Internet of things, VR/AR, artificial intelligence, 5G network, blockchain, etc.) and education concepts, and try to apply them to talent cultivation in vocational education. (5) Have the consciousness to apply the evaluation to the ICT teaching.
	E2. Information knowledge and skills	(1) Understand the basic concepts and theoretical basis of ICT teaching. (2) Understand the characteristics and functions of digital teaching resources and teaching tools. (3) Able to create digital teaching resources.
	E3. Information application and innovation	(1) Able to apply information technology to communicate with students about learning. (2) Able to use information technology to create family-school cooperation. (3) Able to use information technology to collaborate and communicate with colleagues in teaching and research. (4) Able to use information technology to construct the teaching mode of “theory-practice” and “learning-working,” combining the virtual with the real. (5) Able to apply information technology to implement the teaching process and production process of the school-enterprise cooperation teaching model. (6) Able to use mobile terminals, VR/AR, Internet of things, 5G, and other technologies to build a new model of experiment, practical training, and practical teaching.
	E4. Information social responsibility	(1) Able to ensure that all students have equal access to learning resources, tools, and environments.
		(2) Able to cultivate students’ knowledge of information security, awareness of protecting their own and others’ privacy, awareness of distinguishing healthy information from harmful information, and awareness of using information technology in a safe and healthy way.
		(3) Able to teach students the knowledge of laws and regulations related to the use of information technology and ethical concepts, cultivate students’ legal awareness, and demonstrate the relevant normative behavior.
F. Research and Development	F1. Research on teaching	(1) Able to carry out applied science and technology research related to the specialty, and can put forward constructive suggestions for the school’s scientific research management. (2) Able to host applied science and technology research projects. (3) Able to carry out vocational education teaching reform research and actively put forward constructive suggestions for school education and teaching reform. (4) Able to host vocational education teaching research projects. (5) Able to transform scientific research achievements into specialty construction and actively put forward constructive suggestions for the specialty construction of the school.
	F2. Professional development	(1) Able to master professional skills related to the specialty. (2) Able to propose goals, tasks, and measures for personal professional development. (3) Able to participate in on-the-job training and short-term training. (4) Able to organize, design, and participate in teaching and research activities. (5) Able to promote the development of team building.
	F3. Professional ethics education	(1) Familiar with and able to consciously abide by the national vocational education laws, regulations, and policies.
		(2) Able to comply with professional ethics and relevant industry rules and regulations.
		(3) Able to educate students about professional ethics, laws, and regulations in related industries.
		(4) Able to evaluate the performance of students’ professional ethics.

). It consists of 3 levels of criteria, with 6 in level 1, 19 in level 2, and 88 in level 3.

The proposed assessment instrument can be used as a reference point when formulating national policies for supporting TVET teachers’ professional development. Besides, it can also help analyze the status quo of a country’s TVET teachers’ competency level and identify strengths and areas for improvement.

4. Process and Results

This section includes the survey design and implementation, sample background characteristics, classification of these TVET teachers, and validation of clustering.

4.1. Survey Design and Implementation

Based on the scale, an online questionnaire survey was conducted to analyze and investigate the teaching competency level of TVET teachers in the information age. Larger amounts of sample data are used to analyze the characteristics of teachers’ teaching competency and classify teachers accordingly. The target group is the teachers of higher vocational and secondary vocational colleges in China. Convenient sampling is adopted. The survey started 23 March 2021 and ends 23 May 2021. A total of 1203 questionnaires were collected. The study eliminated the questionnaires if: (1) the response time is longer than 200 s, which means about 1 s for each of the 104 items in the questionnaire. This caused 247 questionnaires to be eliminated; (2) all items have the same answers, due to which 103 questionnaires were eliminated; (3) the answers follow certain patterns or are obviously illogical; 39 questionnaires were deemed invalid because of this. After data cleaning, 815 responses were considered valid, the rate of effectiveness of the questionnaire being 67.7%.

4.2. Sample Background Characteristics

The samples are from 11 schools in 8 provinces across China, including 6 higher vocational colleges and 5 secondary vocational schools. See

Table 8. The details of the institutions surveyed.

Institutions	Region	Higher Vocational Colleges/Secondary Vocational Schools	Number	Proportion (%)
SDKJ	East	Higher vocational colleges	142	17.4
GDGM	East	Higher vocational colleges	38	4.7
TJGY	East	Higher vocational colleges	21	2.6
GDQG	East	Secondary vocational schools	41	5.0
SHGS	East	Secondary vocational schools	19	2.3
SDZY	East	Higher vocational colleges	101	12.4
BDDL	Middle	Higher vocational colleges	61	7.5
YCZZ	West	Secondary vocational schools	52	6.4
WSCK	West	Secondary vocational schools	53	6.5
LZZY	West	Higher vocational colleges	259	31.8
WSTY	West	Secondary vocational schools	28	3.4

for details.

As can be seen from the data, the sample covered a wide range of TVET teachers from different backgrounds (see

Table 9. The situation of the sample surveyed.

Item	Category	Number	Proportion (%)
Gender	Male	290	35.6%
	Female	525	64.4%
Age	Under 31	83	10.2%
	31–40	287	35.2%
	41–50	258	31.7%
	51–60	186	22.8%
	61 and above	1	0.1%
Length of time working in schools	1–5	156	19.1%
	6–10	100	12.3%
	11–20	360	44.2%
	21 and above	199	24.4%
Length of time working in enterprises	Under 1	137	34.8%
	1–2	74	18.8%
	2–3	39	9.9%
	3–5	37	9.4%
	5–10	45	11.4%
	10 and above	62	15.7%
Highest degree	Bachelor’s	309	37.9%
	Master’s	409	50.2%
	Doctoral	17	2.1%
	other	80	9.8%
Disciplinary	Education and Physical Education	217	26.6%
	Cultural and Artistic	129	15.8%
	Electronic Information	112	13.7%
	Equipment Manufacturing	91	11.2%
	Finance and Commerce	91	11.2%
	Energy Power and Materials	44	5.4%
	Civil construction	22	2.7%
	Transportation	19	2.3%
	Medicine and Hygiene	18	2.2%
	Biology and Chemicals	13	1.6%
	Public Administration and Services	13	1.6%
Professional titles	Junior	178	21.8%
	Intermediate	345	42.3%
	Associate professor	257	31.5%
	Professor	35	4.3%

).

4.3. Classification of the TVET Teachers

In order to analyze and characterize the teaching competency level of different types of TVET teachers, this study used SPSS 24 and Excel to cluster the sample teachers.

In this paper, the questionnaire results were first normalized to Z-score, and the data with a mean of 0 and a standard deviation of 1 are in a normal distribution (see

Table 10. Z-score of first-level indicator (excerpt).

Case/Indicator	A	B	C	D	E	F
C1	1.24	1.27	1.30	1.60	1.60	1.14
C2	0.70	1.27	1.30	0.44	1.26	1.53
C3	0.85	1.12	−0.03	0.83	0.75	0.45
C4	0.94	0.54	1.08	0.57	0.74	0.84
C5	−1.38	−0.08	1.30	1.29	0.07	0.55
C6	−0.50	−0.55	0.41	0.17	−0.29	0.33
C7	−0.73	−1.42	−0.03	−0.72	−0.77	0.55
C8	−0.70	−0.72	−1.37	−0.72	−1.11	−1.04
C9	−1.36	−1.60	−1.59	−0.73	−1.03	−1.21
C10	0.85	1.27	−0.03	1.22	−0.10	1.04

).

With SPSS, the two-order clustering, k-means clustering method, and systematic clustering method were used to carry out tentative analyses, and the clustering results obtained by k-means clustering were found to be ideal, with no category with too many or too few people and each cluster showing clear characteristics, which had the best explanatory power. Therefore, the k-means clustering method was selected for this study, and the teachers were divided into six categories (see

Table 11. Clustering results.

Indicator/Clustering	1	2	3	4	5	6
Z-score A (Curriculum Development)	0.94	−2.08	−1.22	−0.53	0.38	−0.54
Z-score B (Curriculum Teaching)	1.03	−2.38	−1.19	−0.61	0.14	0.10
Z-score C (Professional Knowledge)	1.00	−2.4	−1.23	−0.52	0.03	0.44
Z-score D (Occupational Ability)	0.96	−2.18	−1.19	−0.55	0.31	−0.36
Z-score E (Information Literacy)	0.98	−2.41	−1.17	−0.63	0.23	0.03
Z-score F (Research and Development)	1.01	−2.15	−1.32	−0.63	0.22	0.04

).

The study attempted to determine the level and characteristics of teaching competency of six types of teachers; see

Table 12. The level and characteristics of teaching competency of six types of teachers.

Type/Indicator	A Curriculum Development	B Curriculum Teaching	C Professional Knowledge	D Occupational Ability	E Information Literacy	F Research and Development
1	skillful teachers	teaching experts	skillful teachers	skillful teachers	skillful teachers	teaching experts
2	beginners	beginners	beginners	beginners	beginners	beginners
3	advanced beginners	advanced beginners	advanced beginners	advanced beginners	advanced beginners	advanced beginners
4	competent teachers	competent teachers	competent teachers	competent teachers	competent teachers	competent teachers
5	skillful teachers	skillful teachers	skillful teachers	skillful teachers	skillful teachers	skillful teachers
6	competent teachers	skillful teachers	skillful teachers	competent teachers	skillful teachers	skillful teachers

. Inspired by the COMET competence model [28], the paper adopted five notions to describe teachers’ teaching competence in each aspect. From the lowest to the highest, they are beginners, advanced beginners, competent teachers, skillful teachers, and teaching experts.

4.4. Validation of Clustering

The advantages and disadvantages of clustering must be judged comprehensively by researchers, according to their own professional knowledge and experience. This study adopted the following two methods to verify the clustering effect.

Cluster analysis can be verified by comparing the variables between categories. As shown in

Table 13. ANOVA.

	Cluster		Error		F	Sig.
	Mean Square	df	Mean Square	df
Z-score(A)	119.47	5	0.27	809	446.15	0.000
Z-score(B)	128.24	5	0.21	809	600.34	0.000
Z-score(C)	127.32	5	0.22	809	580.51	0.000
Z-score(D)	118.51	5	0.27	809	432.94	0.000
Z-score(E)	125.33	5	0.23	809	541.27	0.000
Z-score(F)	127.41	5	0.22	809	582.46	0.000

, all variables showed significant differences among categories (sig < 0.000), indicating that the clustering results are credible.

The study then adopted the clustering results as the dependent variable to establish canonical discriminant equations to examine the effect of clustering (Equation D1-D5, D1′-D5′). The results (

Table 14. The classification results (a,c).

		Case Number	Predicting Group Membership Information						Total
			1	2	3	4	5	6
Original	Count	1	230	0	0	0	5	0	235
		2	0	34	0	0	0	0	34
		3	0	1	99	1	0	0	101
		4	0	0	1	130	0	3	134
		5	1	0	0	0	227	3	231
		6	0	0	0	0	2	78	80
	%	1	97.9	0	0	0	2.1	0	100.0
		2	0	100.0	0	0	0	0	100.0
		3	0	1.0	98.0	1.0	0	0	100.0
		4	0	0	0.7	97.0	0	2.2	100.0
		5	4	0	0	0	98.3	1.3	100.0
		6	0	0	0	0	2.5	97.5	100.0
Cross validation method	Count	1	230	0	0	0	5	0	235
		2	0	34	0	0	0	0	34
		3	0	2	97	2	0	0	101
		4	0	0	1	130	0	3	134
		5	2	0	0	1	225	3	231
		6	0	0	0	4	2	74	80
	%	1	97.9	0	0	0	2.1	0	100.0
		2	0	100.0	0	0	0	0	100.0
		3	0	2.0	96.0	2.0	0	0	100.0
		4	0	0	0.7	97.0	0	2.2	100.0
		5	0.9	0	0	0.4	97.4	1.3	100.0
		6	0	0	0	5.0	2.5	92.5	100.0

) showed a high rate of recall, indicating that the clustering effect was good.

D1 = 0.361 × Zscore(A) + 0.389 × Zscore(B) + 0.373 × Zscore(C) + 0.328 × Zscore(D) + 0.407 × Zscore(E) + 0.283 × Zscore(F)

D2 = 0.601 × Zscore(A) − 0.135 × Zscore(B) − 0.662 × Zscore(C) + 0.423 × Zscore(D) − 0.051 × Zscore(E) − 0.04 × Zscore(F)

D3 = −0.081 × Zscore(A) + 0.267 × Zscore(B) − 0.51 × Zscore(C) + 0.166 × Zscore(D) + 0.685 × Zscore(E) − 0.954 × Zscore(F)

D4 = 0.432 × Zscore(A) − 0.409 × Zscore(B) + 0.667 × Zscore(C) + 0.109 × Zscore(D) − 0.305 × Zscore(E) − 0.407 × Zscore(F)

D5 = 0.253 × Zscore(A) − 0.814 × Zscore(B) + 0.257 × Zscore(C) − 0.327 × Zscore(D) + 0.66 × Zscore(E) + 0.001 × Zscore(F)

Canonical discriminant functions using original variables can be obtained using the following equations:

D1′ = −22.328 + 0.799 × A + 1.133 × B + 1.064 × C + 0.729 × D + 1.149 × E + 0.888 × F

D2′ = 2.012 + 1.329 × A − 0.392 × B − 1.888 × C + 0.939 × D − 0.145 × E − 0.125 × F

D3′ = 1.221–0.180 × A + 0.777 × B − 0.147 × C + 0.369 × D + 1.933 × E − 2.994 × F

D4′ = 1.160 + 0.955 × A − 1.191 × B + 1.903 × C + 0.242 × D − 0.860 × E − 1.276 × F

D5′ = 0.128 + 0.559 × A − 2.367 × B + 0.732 × C − 0.726 × D + 1.862 × E + 0.003 × F

The cross-validation method is used to investigate the discrimination effect. As shown in Table 14, the correct rate of grouping the original cases was 97.9%, and the correctly classified rate of cross-validation was 96.9%, reaching a very high judgment rate, indicating that the establishment of discrimination was very effective.

5. Conclusions and Discussion

Responding to the recent call for a measuring instrument of TVET teachers’ teaching competency, the present study develops the TVET Teachers’ Teaching Competency Scale in the Information Age based on previous studies and an analysis of the multiple-role characteristics of TVET teachers in the information age. The questionnaire consists of 88 items in 6 aspects. In the pilot study, an analysis of data from Chinese TVET teachers from three provinces confirmed the reliability and validation of the scale.

The study then collected data from a larger sample size for further analysis. Another 815 TVET teachers from 8 Chinese provinces participate in an online questionnaire survey. The results reconfirmed the validity and reliability of the scale. The teachers were classified into 6 types based on their evaluation results; each type represents different characteristics of TVET teachers’ teaching competency.

Identifying the category to which a TVET teacher belongs using the scale is important for the sustainable development of teachers and institutions. The paper develops a method to classify TVET teachers according to the characteristics of their teaching ability in six aspects, which can provide valuable clues for the designing of tailored training for vocational education teachers in the information age. It also provides a sound basis for the lifelong learning of teachers. Through this scale, teachers will gain agility in learning and implementing up-to-date skills, improving the quality of educational output, and further promoting the sustainable development and digital transformation of vocational education. If applied in a wider context, the scale will contribute to formulating generalized guidelines for the sustainable development of teachers.

The purpose of this study is to develop a scale for the development of vocational education teachers’ teaching competency and to apply it in educational practice. From the practical perspective of education development, the level of teachers’ teaching competency is the key factor affecting the quality of teaching. Among the 17 goals of the United Nations Agenda for Sustainable Development in 2030, Goal 4 puts forward “ensuring inclusive and fair quality education and promoting lifelong learning opportunities for all” [35]. How can we ensure quality education? This study believes that high-quality education needs to provide high-quality teacher resources. Especially in the digital age, the rapid development of information technology breaks the limitation of learning time and space, which makes it possible for people to learn anytime and anywhere. This also provides more space for further promoting education equity and establishing more digital learning opportunities. To achieve this goal, it is necessary to train more excellent teachers, so that they can expand the scope of education through digital platforms. For the field of vocational education, the underdeveloped areas—rural marginal suburbs—are the main sources of vocational education students. However, the educational resources in these areas are relatively scarce, and it is difficult to attract excellent teachers to teach in these areas. The scarcity of high-quality teachers has a great impact on the teaching quality of local vocational education. If we can help these areas train more excellent teachers through information technology, it will help to improve the teaching quality in these areas. Regarding how to improve the teaching competency of TVET teachers, this study believes that in order to achieve this goal, we not only need the support of ICT ability, but also a more scientific scale of TVET teachers’ teaching competency to help teachers in education management institutes to formulate more appropriate teaching and training plans, effectively improving teachers’ teaching competency. From this point of view, the use of a TVET teachers’ teaching competency scale to improve the teaching quality of vocational education and the goal of sustainable development are closely linked. Only by providing more excellent teachers can we achieve inclusive and fair quality education to the greatest extent, providing more learning opportunities for the disadvantaged students.

The questionnaire employed in the study shows the potential to be a useful instrument in measuring TVET teachers’ teaching competency, but there are still limitations. First, the questionnaire is in Chinese and its validity needs to be tested in different countries and languages in future research. Second, this study adopts a convenience sampling method, with all participants from several Chinese provinces, representing only a very small part of China and the world. Hence, future research should collect samples from other regions across the world to better understand the issue.