Smart teaching abilities of junior high school teachers in Thailand

Abstract

Smart teaching is an essential skill for teachers to effectively transform their classrooms into active learning environments. However, teachers need to have specific abilities to apply the smart teaching approach which comprised of pedagogy, technology, and classroom management. This research was conducted based on the Khon Kaen University Smart Learning Project which has been implementing in junior high schools in Thailand to enhance students’ competencies in active learning environments for five years. The research aimed to study the smart teaching abilities of teachers in the project which composed of: (1) creating the student’s expected learning outcomes, (2) course contents management, (3) application of teaching technique and technology, and (4) organization of learning activities in a digital learning environment. A survey method was done using questionnaires sent to teachers of grades 7–9 who were teaching in three subjects; science, mathematics and English language, of which 1,226 were responded. Data was analyzed by using descriptive statistics. The results of smart teaching abilities of teachers based on their backgrounds: teaching subjects (science, mathematics, and English language), teaching classes (grades 7, 8, and 9), and teaching experiences (1–10 years, 11–20 years, and >20 years) were presented. It was found that overall, mathematics teachers have higher smart teaching abilities than those of science and English teachers. Teachers of grade 7 and teachers with 1–10 years of teaching experiences were found to have higher smart teaching abilities that the others in their dependent variables. This research provides an understanding of the situation which will be useful for the teachers’ skills development. In addition, the information is useful for junior high school teachers and administrators to use as a guideline for enhancing smart teaching ability in the context of new learning environments.

Keywords:

• Smart teaching
• teaching abilities
• smart learning
• junior high schools
• teachers

1. Introduction

The modernization of education in the 21^st century has changed the pace of education and transformed the environment of traditional teaching into the smart classroom (Li Liu et al., 2021). Strengthening teachers’ abilities requires paying attention to the interdependencies and multidimensionality present in education today. Additionally, increasing teachers’ skills and sense of competence is necessary to transmit the core competencies of the 21^st century and the Digital Education Action Plan 2021–2027 (European Commission, 2019). These skills consist of technical skills, information skills, communication skills, collaboration skills, critical thinking skills, creative skills, and problem-solving skills (Van Laar et al., 2020). Meanwhile, the concept of being smart teachers has traditionally been used in education and psychology in the meaning of being knowledgeably and skillful (Barab & Plucker, 2010). Few scholars have focused in-depth research examining smart teaching as the cognitive ability that determines intelligence type (Fulmer & Barry, 2004). A few research has been done to examine smart teaching in the context of the teacher’s ability. In the light of recent phenomenon, the digital age gap is a problem for many teachers; young children are the first to grow up in the age of smart technology and a digital environment, so neither their parents nor teachers know how to adequately equip this young generation with word skills (DQ Institute, 2017). However, a teacher’s teaching style may not be efficient for some or most learners; to accommodate a variety of learning and teaching styles, a multifaceted approach is needed (Hawk & Shah, 2007; Moazeni & Pourmohammadi, 2013). Therefore, teachers’ abilities are associated with the elements of cognitive ability and should be concerned with the physical nature and teaching approach needed to overcome the impediments and attempt to integrate technology into the smart learning environment (Alhubaishy & Aljuhani, 2021).

Smart teaching contains methods of a new teaching paradigm emphasizing development in student learning and competency; it is focused on the design of teaching contents, pedagogy, and developing an effective learning environment that will lead to teaching and learning indoors and outdoors in a manner consistent with the learning style of learners in the digital learning environment (Tuamsuk, 2019). It is essential to create smart teaching environments to improve, share, and furnish education, in addition to changing teaching information dissemination and storage, creating teaching content, and obtaining plentiful resources (Li Liu et al., 2021). Meanwhile, Zhang et al. (2020) stated that it is important to integrate information technology into education and teaching within a smart teaching environment (smart classroom and flipped classroom). Benita et al. (2021) pointed out the relevance of a smart learning ecosystem using the Internet of Things to manage learning activities for students’ thinking and skills. This requires teachers to put forward new requirements of teaching ability for the teaching process, change the teaching method of the teacher, reform the teaching mode and learning styles of students, and be aware of the change and rebuilding of educational concepts and systems. Li Liu et al. (2021) identified informatization teaching ability as a requirement of teachers to understand and apply information technology to optimize their teaching skills. They also stated that the formation of the wisdom gained by using information technology should be used to innovate teaching, solve complex teaching problems, and handle challenges of educational concepts, methods, and educational ecology.

Borawska-Kalbarczyk et al. (2019) examined smart teaching and smart learning within smart pedagogy features. They underlined smart teaching’s importance in supporting teachers’ mental awareness and understanding the new perspective between the roles of the teacher and student. They assumed that smart teaching inferred a process of the teacher constructing a learning environment organized in the novel method. The most important aspect of smart pedagogy is the transfer of the educational process decisively using invariable, stationary structures of transmission-based pedagogy to a fluent and flexible model used by teachers to students without restrictions. Jeffrey and Troman (2013) indicated their research focused on smart teaching combining two discourses—that of performativity and creativity—and investigated how primary teachers managed these policies and how they were influenced by them. Their major finding of smart teaching described how teachers could integrate performative and creative policies in their teaching while ensuring pedagogic and professional success and maintaining their professional status in primary school. Therefore, smart teaching recognizes the potential that creativity, planning, and organizing teaching contents and pedagogy have as tools by incorporating them into technology and as individual skills in the modern learning environment to create deep learning at school (Fullan & Langworthy, 2014).

Khon Kaen University Smart Learning Project (KKUSL) has been implemented since 2016 at junior high schools in the northeast of Thailand to enhance learners’ competence through innovative pedagogical methods. Regarding this, teaching and learning activities have been designed to organize and change the classroom, teaching methods, learning environment, learning contents with the integration of technology and application of digital devices. This project focused on improving students’ knowledge, skills and attitudes from Grade 7 to 9 with three core subjects (namely, English, Mathematics and Science). Teachers under the project were expected to have smart teaching ability based on the KKUSL’s concept which included four aspects: (1) creating the learning outcomes, (2) course contents design and delivering, (3) applications of teaching techniques and digital technology in the class teaching, and (4) organization of learning activities in a digital learning environment. (Tuamsuk, 2019) as shown in Figure 1. This research, therefore aimed to explore the smart teaching ability of the teachers under the KKUSL project in order to understand the situation and use the information for their skills development. In addition, this research would provide useful information for junior high school teachers and administrators to use as a guideline for enhancing smart teaching ability in the context of new learning environments.

Figure 1. Smart teaching ability concept model.

Alt Text: A research conceptual framework with the details of relationships between smart teaching components and teachers’ abilities.

2. Literature reviews

Related literature provides studies on teachers’ abilities in many contexts and aspects, such as cognitive ability, teaching affective, teachers’ ability, or teaching aspects. This understanding focused on smart teaching ability describes different subjects of teacher ability and authority and has been discussed, as detailed hereunder:

2.1. Teaching ability

The aim of teaching ability requiring the core competencies of the 21st century as determined from the literature review covers various aspects. It targets the teacher profession accompanied by teachers’ competency, which is described in qualitative and quantitative contexts: first as an indicator of ability and a concept that includes cognitive, effective, and action aspects as well as the implementation of scaffolding (Alkharusi, 2011). Similarly, Hongxia (2021) has given the perspective that teaching ability has become one of the most important basic skills in the 21st century, and to improve the smart teaching ability of teachers in college, it is necessary to pay attention to teachers’ professional technical skills and create a team of high-quality teachers. Furthermore, Bardach and Klassen (2020) noted that smart teacher literature on teachers’ cognitive abilities and effectiveness in terms of intelligence is related and needed to outline a path for future research on teachers’ cognitive abilities and teacher effectiveness. It was approved in the earlier statement of Ernst and Clark (2008), which stated that a teachers’ learning preferences and cognitive abilities are essential functions and affect teachers’ training outcomes.

Past studies in terms of teaching abilities provide information that helps to develop critical thinking. Few studies examined the teachers’ ability in informatization teaching as the core ability (He-Hai Liu et al., 2019; Acosta Corporan et al., 2020; Zhang et al., 2020). This is because information technology is used to support teaching and learning, and its purpose is to develop technology to promote learning (Gibson et al., 2018). Subsequently, Yang et al. (2021) classified the characteristics of teachers, according to integrated information technology application abilities standards for primary and secondary school teachers for informatization teaching, into five dimensions: informatization teaching literacy, informatization teaching plan and preparation ability, informatization teaching implementation and monitoring ability, informatization teaching evaluation and diagnosis ability, and informatization teaching learning and development. On the other hand, Manakul and Tuamsuk (2021) published the digital intelligence for teaching in the digital environment to explain the body of knowledge resulting from previous articles related to the teaching abilities of teachers and its impact, which educational managers should be conscious of in terms of training for teaching. Therefore, to prescribe a continuous advancement of teaching abilities in smart learning environments, a new education pattern represented by smart education and smart classrooms has been discussed.

The growth of smart teaching abilities in smart education should enable teachers to carry out a diverse range of knowledge and skills related to information literacy and digital literacy skills for smart instruction (Ibrahim et al., 2013; Yang et al., 2021; Yu & Liao, 2021). However, Yu and Liao (2021) defined smart teaching as being integrated with teaching tools and involving the implementation of the teaching process and objectives; it is a new teaching method that relies on intelligent teaching tools and organizes teaching intelligently to achieve the cultivation of intelligent talents. It consists of three aspects: intelligent and advanced information technology, intelligent teaching by teachers, and the cultivation of intelligent talents. This is consistent with the research by Sarnok et al. (2019), and Manakul and Tuamsuk (2021) affirmed that teachers’ abilities need to develop digital knowledge and digital intelligence skills as the tools for improved teaching in a digital learning environment. In contrast, Twining et al. (2013) claimed that to develop smart teaching abilities needed to support the adoption of technology-enhanced teaching strategies, it is necessary to focus on teachers’ individual skills and beliefs. Alkharusi (2011) pointed out that improving and developing teacher capacity depends on the duties and profession of the teacher, which include the ability to design a plan for implementing learning, managing learning, and implementing learning. Therefore, this study focusing on smart teaching abilities involves smart learning concepts by KKUSL.

Many of the studies have confirmed the importance of the teacher’s role in modeling technology integration in smart education. Baba and Aziz (2009) revealed that the ability to think creatively is required to convey smart teaching and learning successfully. Interestingly, the research reported by Ibrahim et al. (2013) demonstrated the success involved in learning various aspects of smart instruction, such as planning smart teaching, managing smart instruction, and managing the smart classroom.

However, many scholars focused on the role of teaching abilities when combining new technologies with smart education; for example, mobile internet, artificial intelligence, big data, and cloud computing technology can cause ongoing changes in smart teaching (Tian & Xie, 2017). From the academic context, there was a research gap that this study will illustrate: the substantial nature of teachers’ smart teaching abilities.

2.2 Smart teaching ability of teachers

Our literature review identified the following concerning smart teaching abilities of teachers. Ma et al. (2021) sorted smart teaching abilities of teachers as manifested in the design and implementation into three key elements: question, scenario, and evaluation. These elements were major points and guidelines needed to build teachers’ smart teaching abilities. Question and scenario refer to instructional learning materials—which teachers create in advance to help students understand how to learn—and depend on the wisdom of teaching content and design. Evaluation is a constructive conversation platform in which teachers timely encourage their students to learn based on the wisdom and knowledge of students’ learning conditions in the learning procedure. Therefore, smart teaching ability suggests smart pedagogy in the context of a digital environment (Borawska-Kalbarczyk et al., 2019).

Teachers not only make progress by using smart teaching abilities in schools, but these skills are also necessary to interact in digital learning environments. Particularly in the smart classroom environment, teachers can manage learning communities, cooperative inquiries, and collaborative learning. They can also cultivate cooperative skills and improve teaching efficiency (He, 2020; Tseng, 2020). Simultaneously, the smart classroom helps encourage the use of technology, the internet, and other modern technologies in teaching, digital intelligence, and personalized education with a new form of education and modern teaching means. Additionally, smart teaching ability also revealed a comprehensive analysis of the characteristics of artificial intelligence technology, proposing a systematic way to construct smart teaching in schools and demonstrating that the teaching platform can connect teachers and students through many forms of communication. A review of the literature reveals three components of smart teaching that are assisted by AI: 1) abundant teaching resources, 2) diversified teaching models, and 3) effective teaching management (Li Liu et al., 2021).

While smart teaching abilities are crucial factors that need to be addressed, in this article, we concentrate means, standard deviations, components, and factors of smart teaching abilities on three different teachers and subjects who were trained in KKUSL Project. In summary, we aimed to fill the gap regarding how smart teaching abilities for teacher professional development programs address the needs and challenges of effectively integrating new content, technology and pedagogy, and digital learning environments.

3. Methods

This research was conducted using a survey method. The research process followed a procedure for collecting and analyzing data from the research questions (Creswell & Poth, 2016). The questionnaire’ contents were designed based on smart teaching concept of the KKUSL. This research proposal was approved by the Center for Ethics in Human Research, Khon Kaen University. (HE653006)

3.1 Research design and instrument

There were two variables in this study. The independent variables were junior high school teachers in distinctively different subjects, classes, and teaching experience. The dependent variables were smart teaching abilities consisting of four dimensions: 1) ability to create students’ learning outcomes (10 items), 2) ability to design and deliver the content management (10 items), 3) ability to apply teaching techniques and how to use digital technology in pedagogy (11 items), and 4) ability to organize learning activities in a digital learning environment (8 items). A total of 49 questions were designed to be rated according to the Likert-five scale. This section presents the results of the empirical study based on the analysis of variables using the Alpha measurement method to test the reliability of each dimension of the scale by α reliability coefficient. The α reliability coefficient of all dimensions was higher than 0.9, indicating perfect reliability and an acceptable result of the questionnaire (Hallinger et al., 1994; Olivier, 2001). (Table 1).

Table 1. Questionnaire reliability coefficient measurement for smart teaching ability dimensions

Smart teaching ability	Number of Items	Cronbach’s Alpha	Level of ability
			Mean	S.D.
1. Learning outcomes: Ability to create students’ learning outcomes	10	.975	3.94	0.781
2. Content management: Ability to design and deliver the content management.	10	.973	4.00	0.769
3. Pedagogy: Ability to apply teaching techniques and use digital technology in pedagogy.	11	.979	3.95	0.777
4. Organize learning environment: Ability to organize learning activities in a digital learning environment.	8	.977	3.92	0.840

3.2 Data collection and analysis

The target group of this study was 2,150 junior high school teachers of grade 7–9 in the northeast of Thailand who were teaching courses in three subjects: science, mathematics, and English language. These teachers had been working collaboratively with the KKUSL project by using the smart teaching approach designed by the project for four years (2017–2020). Questionnaires were delivered to the target teachers between November 2020 to July 2021 via several channels to ensure the high numbers of returned rate during the COVID-19 pandemic. Therefore, the researchers contacted the teachers by email, social media applications (Line, Facebook chat), video conference, and postal mail.

As a result, researchers collected 1,226 valid questionnaires from respondents. Data analysis was done by using descriptive statistics: percentage, mean, and standard deviation. The 5 Likert scale was interpreted based on the mean’s value to describe the smart teaching ability of the respondents as: the highest (mean = 4.51–5.00), high (mean = 3.51–4.50), moderate (mean = 2.51–3.50), low (mean = 1.51–2.50), and the lowest (mean = 1.00–1.50). The smart teaching abilities of teachers with different backgrounds based on the teaching subjects (science, mathematics, and English language), the teaching class levels (grade 7, 8, and 9), and the teaching experiences (1–10, 11–20, and >20 years) were also analyzed and presented.

4. Results

4.1 Respondent characteristics

From a total of 1,226 respondents there were 434 (35.40%) science teachers, 385 (31.40%) mathematics teachers, and 407 (33.20%) English teachers. As for the gender, 913 (74.47%) were female, and 313 were male (25.53%). Among these, 444 (36.22%) were the teachers of grade 7, 362 (29.53%) of them taught at grade 8, and 420 (34.26%) of them taught at grade 9. Most of them, 622 (50.73%) had 1–10 years of teaching experiences. (Table 2)

Table 2. Data on the responses of junior high school teachers

Variables	Frequency	Percentage
Teaching subjects
Science	434	35.40
Mathematics	385	31.40
English	407	33.20
Gender
Male	313	25.53
Female	913	74.47
Grade class
Grade 7	444	36.22
Grade 8	362	29.53
Grade 9	420	34.26
Teaching experiences (Years)
1–10 yrs	622	50.73
11–20 yrs	295	24.06
>20 yrs	309	25.20

4.2 Smart teaching abilities

4.2.1. Smart teaching abilities divided by teaching subjects

A descriptive analysis of the different responses to the smart teaching abilities showed the statement approved the most and the least in each subject. Accordingly, the results revealed slightly different ratings for each. An overview of the performance of three subjects was summarized in a grand mean as follows: mathematics teachers (Mean = 3.99), science teachers (Mean = 3.98), and English teachers (Mean = 3.91) for each measure. More specifically, mathematics teachers had the significantly highest level of smart teaching abilities in the ability to design and deliver the content management than others. Next, science teachers also revealed a significantly high level in the ability to design and deliver content management. Last, English teachers were found to have the lowest mean scores among all dependent variables. The results are depicted in Table 3.

Table 3. Smart teaching abilities of junior high school teachers analyzed by teaching subjects

Smart teaching ability	Teaching subjects
	Science (N = 434)			Mathematics (N = 385)			English (N = 407)
	$\bar{x}$	S.D.	Interpret	$\bar{x}$	S.D.	Interpret	$\bar{x}$	S.D.	Interpret
1. Learning outcome: Ability to create students’ learning outcomes	3.97	.746	High	3.96	.795	High	3.91	.804	High
2.Content management: Ability to design and deliver the content management.	4.02	.752	High	4.04	.747	High	3.95	.805	High
3. Pedagogy: Ability to apply teaching techniques and use digital technology in pedagogy.	3.97	.758	High	3.99	.759	High	3.91	.814	High
4. Organize learning environment: Ability to organize learning activities in a digital learning environment.	3.96	.794	High	3.95	.838	High	3.88	.891	High
Total	3.98	.763	High	3.99	.785	High	3.91	.829	High

4.2.2. Smart teaching abilities divided by teaching class levels

Table 4 presents results showing how smart teaching abilities differ by teaching class level (Grade 7, Grade 8, and Grade 9). Each grade level examined has slightly different ratings for each ability. Furthermore, synthesized grade levels show a high level of smart teaching abilities. Teachers in grade 7 (Mean = 4.00) showed to have the significantly highest level, followed by grade 8 (Mean = 3.97) and grade 9 (Mean = 3.91). The descriptive analysis in each dimension found that teachers in grades 7 and 8 have equally highest mean scores in the ability to design and deliver the content management; grade 9 obtained the lowest mean scores. Secondly, teachers in grade 7 had higher mean scores than grades 8 and 9 in the ability to apply teaching techniques and use digital technology in pedagogy. Third, teachers in grade 7 also showed higher mean scores in the ability to organize learning activities in a digital learning environment than teachers in grades 8 and 9, in that order. Lastly, the results show that teachers in grade 8 had the distinctly highest mean scores in the ability to create students’ learning outcomes.

Table 4. Smart teaching abilities of junior high school teachers analyzed by teaching class levels

Smart teaching ability	Teaching class levels
	Grade 7 (N = 444)			Grade 8 (N = 362)			Grade 9 (N = 420)
	$\bar{x}$	S.D.	Interpret	$\bar{x}$	S.D.	Interpret	$\bar{x}$	S.D.	Interpret
1. Learning outcome: Ability to create students’ learning outcomes	3.97	.798	High	3.99	.737	High	3.89	.799	High
2. Content management: Ability to design and deliver the content management.	4.03	.769	High	4.03	.723	High	3.95	.806	High
3. Pedagogy: Ability to apply teaching techniques and use digital technology in pedagogy.	4.00	.775	High	3.96	.761	High	3.90	.792	High
4. Organize learning environment: Ability to organize learning activities in a digital learning environment.	3.99	.839	High	3.91	.831	High	3.88	.848	High
Total	4.00	.795	High	3.97	.763	High	3.91	.811	High

4.2.3. Smart teaching abilities divided by teaching experiences

The descriptive analysis of smart teaching abilities in different levels of teaching experience is presented in Table 5. The overall values of each independent variable revealed slightly different ratings for each. The study indicated that teachers with 1–10 years of teaching experience (Mean = 4.02) had the highest mean scores of the four smart teaching components among the three groups; teachers with 11–20 years of teaching experience (Mean = 3.94) came next, and third was teachers with of >20 years teaching experience (Mean = 3.86). However, all groups showed high levels. Furthermore, statistically significant results in each ability domain showed that teachers with 1–10 years of teaching experience have the highest mean scores in the ability to design and deliver the content management, followed by teachers with 11–20 years of teaching experience; teachers with >20 years of experience had the lowest scores.

Table 5. Smart teaching abilities of junior high school teachers analyzed by teaching experiences (no. of year)

Smart teaching ability	Teaching experiences
	1–10 yrs. (N = 622)			11–20 yrs. (N = 295)			>20 yrs. (N = 309)
	$\overline{x}$	S.D.	Interpret	$\overline{x}$	S.D.	Interpret	$\overline{x}$	S.D.	Interpret
1. Learning outcome: Ability to create students’ learning outcomes	4.00	.762	High	3.92	.781	High	3.85	.809	High
2. Content management: Ability to design and deliver the content management.	4.05	.740	High	4.02	.765	High	3.90	.821	High
3. Pedagogy: Ability to apply teaching techniques and use digital technology in pedagogy.	4.02	.748	High	3.93	.790	High	3.85	.812	High
4. Organize learning environment: Ability to organize learning activities in a digital learning environment.	4.00	.819	High	3.88	.855	High	3.83	.860	High
Total	4.02	.767	High	3.94	.855	High	3.86	.860	High

5. Discussion

The survey research method was used to study the smart teaching abilities of junior high school teachers in Northeast Thailand. The findings show that smart teaching is a key component of smart education and is related to the smart teaching environment (Yu & Liao, 2021). There are four components of smart teaching abilities: learning outcomes, content management, pedagogy, and digital learning environment. This study is limited to teachers who trained at the KKU Smart Learning Project for three years. While data were analyzed, efforts were made to examine independent variables, including subject, grade, and teaching experience.

The descriptive statistic examined the smart teaching abilities in junior high school teachers by addressing our initial research question. The results show high levels of smart teaching abilities in learning outcome, content management, pedagogy, and learning environment. The findings for the three independent variables revealed that content management is the top smart teaching ability; the highest mean scores belonged to mathematics teachers. These results seem to support the concept of KKUSL (Tuamsuk, 2019) which designed the smart teaching concept used by math teachers to adequately improve their teaching ability to help learners understand conceptual ideas and correctly summarize mathematics using their own knowledge (Emery et al., 2021; Herbst & Chazan, 2012; Manduca et al., 2017). The previous results highlighted by Von Minden et al. (1998) and Froyen and Iverson (1999) affirmed that content management positively affects teachers’ ability and students’ academic achievement. Furthermore, results show that depth of knowledge of the content is a prerequisite for good teaching.

When comparing subjects, mathematics teachers were proven to have the highest mean scores in two dimensions: content management and pedagogy. In a similar study, Wongjansau (2020) noted that mathematics content knowledge and pedagogical knowledge were highly significant and intertwined. Furthermore, both results were important for developing mathematics learning management plans, teaching materials, and worksheets. In another, science teachers were proven to hold the second-highest mean scores in another two dimensions: learning outcome and learning environment. These results are consistent with previous research by Abdullah and Sheikh (2016), who found that most excellent science teachers in this study can conduct classes and choose appropriate learning environments. Moreover, these results correlate to the research of Kurniawati et al. (2017), who concluded that science teachers need teaching materials developed to improve students’ learning outcomes. However, it was expected to find that English teachers held the lowest mean.

The different grade levels indicated that the highest mean scores of junior high school teachers were in grade 7; these high scores were in the areas of content management, pedagogy, and learning environment. These findings corresponded with Kanik (2010), who noted that teachers in grade 7 were implementing highly illuminated teaching strategies. In addition, teachers in grade 8 showed the highest mean scores in learning outcome. The difference in teaching experience revealed that teachers with fewer years of teaching experience were most likely to be proficient in smart teaching abilities and use more developmentally appropriate teacher training programs, as recommended by Hwang and Evans (2011).

Thus, this research explores smart teaching abilities to examine mean differences by subject, grade, and teaching experience. Results were also obtained through ANOVA, which analyzed the hypotheses in differentiate of independents. However, the results found that the scores between different subjects and grades were not statistically significant in any dimension, except teaching experience. Teachers who have 1–10 years of teaching experience have higher smart teaching abilities than teachers with >20 years of teaching experience; it was also found that there were significant differences in all dimensions of smart teaching abilities.

6. Conclusion

The finding of smart teaching abilities of junior high schools in Northeast Thailand is suggested that there are many areas for improvement. According to the smart teaching abilities of teachers in the KKUSL, outstanding abilities are necessary for the teacher to construct a learning environment organized in the novel method. Sarnok et al. (2019), and Manakul and Tuamsuk (2021) affirmed that teachers’ abilities are tied into the digital learning ecosystem, and it is necessary to develop digital knowledge and digital intelligence skills as tools for improved teaching.

Smart teaching research shows rising development (Yu & Liao, 2021). Smart learning connected to technical support in smart teaching abilities can help teachers gradually understand how student learning styles are rapidly changing and how constructing teaching environments, smart classrooms, and exploration of teaching practices form the knowledge base of smart teaching research (Yu & Liao, 2021). The integration of smart teaching into teachers’ teaching ability is an organic advanced teaching concept and prepares for smart education. However, in Thailand, it is difficult to find research on smart teaching; this needs to be improved. Furthermore, junior high schools in Northeast Thailand largely lacked infrastructure and teaching support when faced with the COVID-19 pandemic.

Many other lines of research remain open. We agree that future research should deepen the theory of smart teaching, smart teachers and learners, smart teaching support environments, and evaluate the effectiveness of smart teaching implementation. An interesting finding was that the results of smart teaching abilities coupled with previous studies of the digital intelligence of teachers could impact student learning in digital environments. Therefore, it is important that educational managers raise awareness and provide training for teachers continually. These factors become a reference in the digital intelligence for smart teaching for junior high school teachers in Northeast Thailand that impacted the initial research and will be continued in future research.

Acknowledgement

This research is supported by the Graduate School Scholarship, Khon Kaen University, Thailand.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors received no direct funding for this research.