Vol. 7, No. 2, November 2022, pp. 143 – 153 e-ISSN: 2550-1461
https://ijeisr.net
TEACHER SELF-EFFICACY ON ICT USE IN MALAYSIAN SECONDARY SCHOOL
Mohd Norakmar Omar1 Siti Noor Ismail2
1Pejabat Pendidikan Daerah Baling, Kedah, Malaysia (E-mail: [email protected])
2School of Education, Universiti Utara Malaysia, Kedah, Malaysia (E-mail: [email protected])
Abstract: Teacher self-efficacy is a term used to express the confidence and ability of a teacher to carry out a task diligently, especially in the teaching process. Therefore, an instrument developed by Tschannen-Moran and Hoy (2001), namely the Teacher Sense of Efficacy Scale (TSES). In this study, TSES was used to measure teachers' confidence and ability to use ICT tools in teaching. The instrument has also adapted in Malay through two versions, of which one has 12 items while the other contains 24 questions. The study makes a comparison between the instrument TSES-24 and TSES-12 in the context of ICT in Malaysian secondary school education. A total of 130 secondary school teachers in Kedah, Malaysia, were involved as respondents to test the validity and reliability of the instrument. Based on the study, it finds that the TSES-24 showed higher Cronbach's alpha compared to the TSES-12 involving the three components, namely teaching strategies, classroom management, and student engagement. The exploratory factor analysis (EFA) test found that the TSES-24 instrument produced three parts, while the TSES-12 produced only two dimensions. Thus, the EFA proves that the TSES-24 is in line with the original TSES created in 2001. From this study, it recommended that TSES-24 is an excellent tool for measuring teacher self-efficacy, especially using ICT to enhance teaching and learning effectiveness.
Keywords: Teacher Self-Efficacy, ICT, Factor Analysis, Secondary School, TSES.
1. INTRODUCTION
The use of information and communication technology (ICT) is an approach that is often applied in various organizations to ensure that tasks perform more smoothly. The influence of ICT is limited to engineering or industrial organizations, but its use has long been practiced in education systems worldwide. During its early emergence, ICT was highly synonymous with school administration as well as correspondence documentation. Today, ICT is well-established and widely integrated with improving the quality of teaching and student learning outcomes (Lawrence & Tar, 2018). This development will invite problems if educators are less concerned about cultivating ICT in the learning environment. Ideally, the considerable potential of ICT could open up space for educators to diversify teaching strategies and change the classroom environment to be more enchanting (Dong & Newman, 2018; Drossel, Eickelmann, & Gerick, 2017).
This decade, ICT has undergone dramatic changes after the emergence of various mobile technology devices. Devices such as laptops, smartphones, notebooks, and tablets continue to craze technology users, including teachers and students. The dumping of this device's use needs to be better managed to be integrated based on the regulations provided.
Accordingly, principals need to emphasize by allocating specific clauses and aligning them with existing school rules. In this way, principals can ensure that using ICT in schools can be integrated more legally, safely, and ethically (Altinay, Altinay, Dagli, & Altinay, 2018). Indeed, this legitimate, safe, and ethical use of ICT has been recommending by the National Educational Technology Standards for Administrators (NETS-A) (International Society for Technology in Education, 2009; Raamani & Arumugam, 2018a).
Therefore, school principals need to take the opportunity and evaluate the potential of the latest ICT that benefits students, teachers, and school organizations. Students' interest in observing each learning activity will erode if principals do not encourage teachers to integrate ICT in teaching. In reality, teachers' skills in using ICT are also triggering to increase self- efficacy, especially to create a technology-based learning environment (Mohd Norakmar Omar, Siti Noor Ismail, & Abd Latif Kasim, 2019). Besides, principals have a strong influence on the quality of administration and the more systematic use of ICT. Previous studies have proven that ICT can improve the quality of organizational management and administration systems more efficiently and structured (Arumugam & Som Shariff, 2018; Unal, Uzun, & Karatas, 2015).
In examining this phenomenon, principals are expected to face problems in organizing ICT-based school planning. This case is because ICT is a technical nature and requires specific skills to integrate perfectly. Like it or not, a principal should note what role they need to inculcate in the school organization to realize maximum use of ICT (Moreira, Rivero, &
Alonso, 2019). Roughly speaking, not all principals in Malaysia are proficient in using ICT because less emphasis is given to these courses' elements. Finally, principals do not have the necessary competencies to manage an educational organization based on a technological learning environment (Gallego-Arrufat, Gutierrez-Santiuste, & Campana-Jimenez, 2017).
In this regard, principals need to form a corresponding character in organizing the best strategies to manage schools in the world of sophisticated technology. Technology in the school environment is unstoppable and will become increasingly contagious due to its need and importance to daily life. Thus, principals should change their character nowadays concerning current technology issues and situations (Banoglu, Vanderlinde, & Cetin, 2016). The characteristic of a technology leader is an aspect that needs to be played by the principal to shape the management and administration of the school organization more systematically.
Thus, the principal uses his influence in encouraging school people to cultivate ICT, thus increasing teachers 'teaching and students' academic achievement.
2. LITERATURE REVIEW
Teacher self-efficacy refers to the confidence and ability of teachers to use the existing knowledge and skills to make teaching and learning processes more effective (Maulod, Chua, Ahmad, Leong, & Alias, 2016; Mehdinezhad & Mansouri, 2016; Poulou et al., 2019; Yoo, 2016). In simple terms, teacher self-efficacy can change teacher teaching patterns to produce the best impact on holistic student learning (Choi & Lee, 2018; Mahasneh & Alwan, 2018;
Sakiz, Ekinci, & Saricam, 2019). Therefore, Tschannen-Moran and Hoy (2001) has established a TSES for measuring teacher self-efficacy through three key components:
(a) Instructional Strategies is how teachers develop effective teaching processes using a variety of methods appropriate to the current situation. To diversify teaching methods, teachers can use whatever equipment is available or create a new concept of activity that can present a stimulating learning environment. The use of technology devices, such as computers and mobile devices, also helps teachers design more practical teaching activities. With this, teachers can assess student performance levels as well as reflect on the learning process (George et al., 2018).
(b) Classroom management is how teachers administer a classroom that is conducive to student learning. How to manage a classroom is essential to a well-planned method (Schipper, Goei, de Vries, & van Veen, 2018). These include ensuring that the learning environment is always conducive to students, no noise, and no disruption to the learning process either from inside or outside the classroom.
Without interruption, the learning process will be more smooth, and the learning objectives will be achieved successfully (Cocca et al., 2018). In other words, students are more receptive to the learning process presented when the classroom is better organized.
(c) Student engagement is how teachers develop positive student behaviour to generate student interest in engaging in every activity planned in the classroom. To be honest, students will be more focused on learning if a teacher can draw their attention to a planned learning process. Teachers can use a variety of activities that involve the whole student, such as the presentation, one stay three stray, gallery walk, and even student acting in-jokes. The use of digital resources such as video, models, animations, and teaching simulations is also a catalyst for student engagement in the classroom (Krause, Pietzner, Dori, & Eilks, 2017).
Previously, studies from De Smul, Heirweg, Van Keer, Devos, and Vandevelde (2018) have adapted the TSES using only 23 items. A study involving 165 teachers in Belgium aimed at testing the effectiveness of teacher self-efficacy based on self-regulated learning. The results of their research found that TSES-23 is best to use in increasing the effort and competence of teachers to implement continuous self-regulated learning. However, according to the factor analysis report, the TSES is broken down into four factors, and it is opposite of the original TSES. In contrast to the unique TSES instrument, Tschannen-Moran and Hoy (2001) has divided teacher self-efficacy into three components, namely instructional strategies, classroom management, and student engagement.
In Spain, Burgueno et al. (2019) revealed that the appropriate TSES instrument contained only 11 items. This study of 358 teachers demonstrated that there is one item in the classroom management component that should drop to form a best-fit model with the focus of the research involving teachers' psychometry. The results of the CFA test indicate that 11 items used to measure teacher self-efficacy had higher validity than either TSES-24 or TSES-12.
Previously, the TSES-12 also divided into three components, each consisting of four elements (George et al., 2018; Tschannen-Moran & Hoy, 2001). However, the model published by Burgueno et al. (2019) found that the defective items in the TSES-11 were in the classroom management component. The components of instructional strategies and student engagement remain with each of the four questions.
Meanwhile, a study of the validity and reliability of TSES conducted in Malaysia involving 35 Islamic education teachers. Research by Jaafar (2018) also uses EFA to test items that are relevant to the context in Malaysia. Nevertheless, the EFA test results indicate that four factors make up the Islamic teacher's self-efficacy when using the instrument in Malay. Thus, the new component is named Academic and Character Guidance in the form of the fourth component. Again, this study is contrary to the original instrument of the TSES, which provides for only three parts. This situation is also different because they are researching Islamic education while the research focused on the context of ICT in improving teacher self-efficacy.
3. METHODOLOGY
Research Design
This study conducted to compare the two research instruments TSES-24 and TSES-12 in the context of ICT translated into Malay. Thus, the design of appropriate research involves cross- sectional surveys based on quantitative approaches. Quantitative data is best to conclude a phenomenon or event that occurs over a given period (Ary, Jacobs, Sorensen, & Razavieh, 2010). For this reason, engaging in a questionnaire form is the most appropriate way to get data from respondents quickly, easily, and save time during the data collection process (Fauzi Hussin, Jamal Ali, & Mohd Saifoul Zamzuri Noor, 2014).
As with the initial objective, each item will be tested through an exploratory factor analysis (EFA) process. In this case, quantitative data is the most appropriate method for determining the validity and reliability of the instrument. Through the EFA, each item was organized according to uniform factors and formed groups that expressed similar characteristics based on respondents' understanding as they answered the questionnaire (Creswell, 2014; Fauzi Hussin et al., 2014). Of course, the EFA generation will only be successful if this study conducted using a quantitative approach.
Population And Sampling
A population is a group of individuals or institutions composed of the same characteristics that allow a generalization to take place concerning a phenomenon (Creswell, 2014). For this study, a target population is a group of secondary school teachers in the North of Peninsular Malaysia.
In fact, the selection of these teachers because they have the same characteristics as having a certificate in education, teaching using the same educational curriculum, and dealing with students of a similar age range.
To realize this intention, the cluster sampling technique used to determine the population that should be the study respondents. This sampling technique has its advantages, where each selected respondent has a mutually exclusive trait that can guarantee more accurate study results (Ary et al., 2010; Fauzi Hussin et al., 2014). As such, a total of 130 secondary school teachers around the state of Kedah, North Peninsular Malaysia, selected as the respondents of this study. According to the survey, 36 respondents (27.7%) were male teachers, while 94 (74.3%) were female teachers. The teachers served in the urban areas of 61 people (46.9%), while the remaining 69 teachers (53.1%) taught in rural areas. Table 1 below shows the demographics of the respondents involved in this study.
Table 1: Demographics of Respondents
Demographics Categories Frequency %
Gender Male
Female
36 94
27.7 72.3
Location Urban
Rural
61 69
46.9 53.1
Instrument
As described earlier, the instrument used in this study adapted from the original TSES built by Tschannen-Moran and Hoy (2001). A total of 24 items were used and divided into two types of instruments: TSES-24 and TSES-12 (just 12 items only). Since the original instrument was in English, the back-translation method used to translate it into Malay. According to Brislin (1970), the three steps to perform in the back translation are (a) translate the original instrument to the desired language, (b) translate the instrument back to the original language, (c) compare the original instrument with the translation instrument. Three linguists, as well as proficient in education, are used to review the back-translation process. After the review, the contents of the instrument were reviewed by three other experts to prove that the tool had content validity and construct validity. These experts comprise a lecturer in educational leadership at Universiti Utara Malaysia (UUM), and two others are lecturers at the Aminuddin Baki Institute (IAB).
This instrument uses five scales ranging from 1 (strongly disagree) to 5 (strongly agree).
Data Analysis
An exploratory factor analysis (EFA) process implemented to determine the validity and reliability of each item studied. According to Taherdoost, Shamsul Sahibuddin, and Jalaliyoon (2014), EFA is used to isolate items into relevant components that are better known as factors.
EFA is also a necessary process to provide researchers with an initial picture of the suitability of the item before it adapted to the actual study. In other words, the EFA can help researchers identify problematic items and propose to the process of improvement or abortion (Williams, Onsman, & Brown, 2010). According to the study, the EFA process performed twice. First, the EFA generated to test the loading factor for the TSES-24 instrument, followed by the TSES- 12. Values, such as eigenvalue and Kaiser-Mayer-Olkin of Sampling Adequacy (KMO), are recorded.
4. FINDINGS
Before EFA generated, a reliability test is required to see the Cronbach's alpha (α) values for each component. Reliability is a test to determine the consistency or stability of the instrument used (Creswell, 2014). If the reliability value is low, then the studies conducted may produce inconsistent and inconsistent findings. Therefore, the proposed Cronbach's alpha value is higher than 0.70 (Hair, Black, Babin, & Anderson, 2014). This value needs to be kept in mind so that the item used will no longer be questionable. Table 2 below shows the reliability values for TSES-24 and TSES-12.
Table 2: Reliability of Instrument
Components TSES-24 TSES-12
Instructional Strategies Classroom Management Student Engagement
0.93 0.93 0.95
0.88 0.87 0.93
Overall 0.97 0.93
Based on the reliability results it was found that the instrument TSES-24 (α = 0.97) was significantly higher than the TSES-12 (α = 0.93). For the TSES-24, component instructional strategies recorded Cronbach's alpha values of α = 0.93, classroom management (α = 0.93) and student engagement (α = 0.95). Meanwhile, Cronbach's alpha TSES-12 values for instructional strategies were α = 0.88, classroom management (α = 0.87) and student engagement (α = 0.93).
In summary, the TSES-24 instrument is more consistently used in studies involving elements of ICT use among Malaysian secondary school teachers.
KMO and Bartlett’s Test
Based on the tests, it found that the Kaiser-Mayer-Olkin of Sampling Adequacy (KMO) value for TSES-24 was 0.93, with a value of approx. chi-square was x2 = 3029.80, df = 276 and had a significant p = 0.00 (p <0.05). For the TSES-12 instrument, the KMO value is 0.86, approx.
The chi-square is x2 = 1194.50, df = 66 and has a significant p = 0.00 (p <0.05). According to Yong and Pearce (2013), the KMO value must be higher than 0.60, which means that the sample size of the study used is sufficient, and the rotation can be performed to determine the factor loading. This finding proves that TSES-24 and TSES-12 can use in furthering the EFA process.
The KMO and Bartlett’s Test formulas for both instruments are as follows in Table 3.
Table 3: KMO and Bartlett’s Test
Test TSES-24 TSES-12
KMO 0.93 0.86
Bartlett’s Test Approx. Chi-Square Df
Sig.
3029.80 276 0.00
1194.50 66 0.00
EFA For TSES-24 Instrument
This study uses the Principal Components Analysis (PCA) method and Varimax rotation to generate factor analysis. Through the EFA, three components were rotated and showed an eigenvalue greater than 1.0. According to Total Value Explained (TVE), the eigenvalue of the first component was 13.65, followed by the second component (2.11) and the third component (1.32). The overall TVE value of TSES-24 is 71.18%. Table 4 shows the TVE results from the EFA process, where each item has a loading factor greater than 0.50. A minimum value of 0.50 in EFA is required to ensure that each item has high consistency (Hair, Gabriel, da Silva, &
Braga, 2019).
Table 4: EFA and TVE for TSES-24 Instrument
Components Items Factors
1 2 3
Student Engagement
Instructional Strategies
SE7 SE6 SE8 SE5 SE2 SE4 SE1 SE3
IS2 IS3 IS4
0.88 0.78 0.77 0.75 0.73 0.71 0.68 0.68
0.82 0.76 0.76
Classroom Management
IS5 IS1 IS7 IS6
CM2 CM1 CM3 CM8 CM6 CM5 CM4 CM7
0.75 0.72 0.72 0.68
0.77 0.76 0.75 0.69 0.69 0.68 0.68 0.66
Eigenvalue Variance (%) Cumulative (%)
13.65 56.87 56.87
2.11 8.80 65.67
1.32 5.51 71.18
The following Figure 1 shows a Scree Plot that proves the value of eigenvalue is more than 1.0. The Scree Plot is visible when three small circles descend before the horizontal line formed. According to the Scree Plot, the first three small circles represent the existence of three components in the TSES-24 instrument.
Figure 1: Scree Plot for TSES-24 Instrument
EFA For TSES-12 Instrument
As with EFA for TSES-24, TSES-12 also uses the same approach that generates the PCA method and Varimax rotation. Based on the EFA test, it found that only two components rotated and the eigenvalue was more significant than 1.0. It was detected when the eigenvalue in TVE for the first component is 6.73, while the second component is 1.55. However, the eigenvalue of the third component (0.94) was less than 1.0, resulting in only two components for consideration. Overall, the TVE for TSES-12 recorded a value of 68.95%, as shown in Table 5 below.
Table 5: EFA and TVE for TSES-12 Instrument
Components Items Factors
1 2
Classroom Management +
Student Engagement
Instructional Strategies
CM2 CM1 CM3 SE2 SE4 SE3 CM4
SE1
IS1 IS4 IS2 IS3
0.85 0.83 0.79 0.73 0.72 0.68 0.65 0.62
0.84 0.82 0.82 0.76 Eigenvalue
Variance (%) Cumulative (%)
6.73 56.07 56.07
1.55 12.88 68.95
Based on Table 5, all items exhibited a factor loading value higher than 0.50. Like the TSES-24, the TSES-12 instrument also provided the impression that each item had a high consistency because it exceeded the minimum value of 0.50 (Hair et al., 2014). The findings also show that components of classroom management and student engagement combine and form one common component. As in Figure 2, only two components have an eigenvalue higher than the value of 1.0 that rotated through the Scree Plot.
Figure 2: Scree Plot for TSES-12 Instrument
5. DISCUSSIONS
This study was conducted based on TSES instruments that use a version of the Malay language.
The TSES instrument broken down into two TSES-24 and TSES-12. Every instrument will be making a significant difference. Through reliability tests, it found that the TSES-24 instrument had a higher Cronbach's alpha value than the TSES-12. This argument has been supported by
original instruments Tschannen-Moran and Hoy (2001) which prove that TSES-24 is more consistent than TSES-12. Many other studies involving teaching strategies, student motivation, classroom best practices, and the influence of principal leadership have also used the TSES-24 instrument as the basis for this study (De Smul et al., 2018; Omar et al., 2019; Poulou et al., 2019; Sabet et al., 2018). Even with the elements of ICT, the TSES-24 instrument still has high reliability in measuring teacher self-efficacy in Malaysia.
Interestingly, the TSES-24 and TSES-12 instruments show conflicting findings.
Through the EFA test, the TSES-24 instrument based on three existing factors, namely instructional strategies, classroom management and student engagement. Studies by Mehdinezhad and Mansouri (2016) and also Cansoy and Parlar (2018), prove that teacher self- efficacy is compatible and needs to be developed through three different components as suggested by Tschannen-Moran & Hoy (2001). The effectiveness of using the EFA test also proves that the items used in the instrument have specific clusters and grouped to form an important factor (Omar, Ismail, & Kasim, 2020). It is because these three components have different meanings and roles in explaining teacher self-efficacy.
In contrast to the TSES-12 instrument, the EFA test results show that it based on only two components. The components of classroom management and student engagement have been incorporated into a new component while instructional strategies can stand on its own through existing components. The integration of the two components due to the probability of the items used has the same meaning as explaining the components (Hair et al., 2014). Earlier studies from Alt (2018) have stated that self-efficacy in ICT can motivate teachers to emphasize classroom control while engaging students in activities. Whereas Choi and Lee (2018) find classroom management and student engagement intertwined as long as teachers have self- efficacy in high communication skills.
In a nutshell, teacher self-efficacy can be demonstrated by their success in shaping meaningful teaching and learning processes as well as producing more positive student behaviour. It is an advantage for teachers when they have the knowledge and skills in ICT to translate the potential of ICT in the educational era (Krause et al., 2017). In this modern age, teachers and students cannot escape being overwhelmed by the rapidity of technology. It forms the present and future life of the educational world. Therefore, teachers need to be prepared and equipped with a wide range of knowledge and increase their motivation for future challenges. Increasing teacher self-efficacy in the context of ICT can create a new dimension to teachers' confidence and ability to organize the learning process more effectively.
6. CONCLUSION
Although the TSES-24 and TSES-12 instruments are widely adopted in many languages, not all of the items used have the best effect on the purpose of the study. According to the study, ICT elements have been included in the TSES instrument and translated into Malay.
Comparisons have also been made between the use of TSES-24 and TSES-12 to verify appropriate items. In conclusion, the findings have shown that the TSES-24 is highly compatible as a research instrument involving teacher self-efficacy in integrating ICT based on the study site in Malaysia. The seventh item in the student engagement component (SE7) recorded the highest factor loading factor and easily understood by the majority of respondents.
The question reads, "Through ICT, I can inspire student creativity”.
However, it would be incomplete if the instrument used the EFA approach only to determine the validity and reliability of the instrument. Advanced methods such as Confirmatory Factor Analysis (CFA) should be developed to confirm the consistency of the TSES items, to establish a robust model. Also, the level of each item should be a highlight to determine which item has the highest mean value. The mean level used to measure respondents' average agreement on whether an item has a high acceptance rate or not.
REFERENCES
Alt, D. (2018). Science teachers’ conceptions of teaching and learning, ICT efficacy, ICT professional development and ICT practices enacted in their classrooms. Teaching and Teacher Education, 73, 141–
150.
Ary, D., Jacobs, L. C., Sorensen, C., & Razavieh, A. (2010). Introduction to research in education (8th ed.).
Belmont, California: Wadsworth Cengage Learning.
Brislin, R. W. (1970). Back translation for cross-cultural research. Journal of Cross Cultural Psychology, 1(3), 185–216.
Burgueno, R., Sicilia, A., Medina-Casaubon, J., Alcaraz-Ibanez, M., & Lirola, M.-J. (2019). Psychometry of the teacher’s sense of efficacy scale in Spanish teachers’ education. The Journal of Experimental Education, 87(1), 89–100.
Cansoy, R., & Parlar, H. (2018). Examining the relationship between school principals’ instructional leadership behaviors, teacher self-efficacy, and collective teacher efficacy. International Journal of Educational Management, 32(4), 550–567.
Choi, E., & Lee, J. (2018). EFL teachers’ self-efficacy and teaching practices. ELT Journal, 72(2), 175–186.
Cocca, M., Cocca, A., Martinez, E. A., & Bulnes, M. G. R. (2018). Correlation between self-efficacy perception and teaching performance: the case of Mexican Preschool and Primary School teachers. Arab World English Journal, 9(1), 56–70.
Creswell, J. W. (2014). Research design : qualitative, quantitative, and mixed methods approaches (4th ed.).
Thousand Oaks, California: SAGE Publications, Inc.
De Smul, M., Heirweg, S., Van Keer, H., Devos, G., & Vandevelde, S. (2018). How competent do teachers feel instructing self-regulated learning strategies? Development and validation of the teacher self-efficacy scale to implement self-regulated learning. Teaching and Teacher Education, 71, 214–225.
Dogan, Y. B., Akar, H., & Ustuner, M. (2019). Examining the measurement invariance of the teachers’ sense of self-efficacy scale in terms of gender. International Journal of Evaluation and Research in Education, 8(2), 213–220.
Fauzi Hussin, Jamal Ali, & Mohd Saifoul Zamzuri Noor. (2014). Kaedah penyelidikan & analisis data SPSS [Methods of research & analysis of SPSS data]. UUM Sintok, Kedah: UUM Press.
George, S. V., Richardson, P. W., & Watt, H. M. G. (2018). Early career teachers’ self-efficacy: A longitudinal study from Australia. Australian Journal of Education, 62(2), 217–233.
Hair, J. J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Essex:
Pearson Education Limited.
Hair, J. J. F., Gabriel, M. L. D. S., da Silva, D., & Braga, J. S. (2019). Development and validation of attitudes measurement scales: Fundamental and practical aspects. RAUSP Management Journal, 54(4), 490–507.
Jaafar, N. (2018). The validity and reliability of self-efficacy instrument for Islamic education teachers.
International Conference on Economy, Entrepreneurship and Technology, 0(0), 1–14.
Khosim, F., & Awang, M. I. (2020). Validity And Reliability Of The MSLQ Malay Version In Measuring The Level Of Motivation And Self - Regulated Learning. International Journal of Scientific & Technology Research, 9(02), 903–905.
Krause, M., Pietzner, V., Dori, Y. J., & Eilks, I. (2017). Differences and developments in attitudes and self- efficacy of prospective chemistry teachers concerning the use of ICT in education. Eurasia Journal of Mathematics, Science and Technology Education, 13(8), 4405–4417.
Lailiyah, M., & Cahyono, B. Y. (2017). Indonesian EFL teachers’ self-efficacy towards technology integration (SETI) and their use of technology in EFL teaching. Studies in English Language Teaching, 5(2), 344–
357.
Mahasneh, A. M., & Alwan, A. F. (2018). The effect of project-based learning on student teacher self-efficacy and achievement. International Journal of Instruction, 11(3), 511–524.
Maulod, S. A., Chua, Y. P., Ahmad, H., Leong, M. W., & Alias, S. (2016). Kecerdasan emosi pengetua dan hubungannya dengan efikasi kendiri guru sekolah menengah [The principal's emotional intelligence and
its relation to the self-efficacy of secondary school teachers]. Jurnal Kepimpinan Pendidikan, 3(3), 54–
75.
Mehdinezhad, V., & Mansouri, M. (2016). School principals’ leadership behaviours and its relation with teachers’
sense of self-efficacy. International Journal of Instruction, 9(2), 51–60.
Moradkhani, S., Raygan, A., & Moein, M. S. (2017). Iranian EFL teachers’ reflective practices and self-efficacy:
Exploring possible relationships. System, 65, 1–14.
Omar, M. N., Ismail, S. N., & Kasim, A. L. (2019). Hubungan kepimpinan teknologi pengetua dan efikasi kendiri guru [The relationship of principal's technology leadership and teacher self-efficacy]. Jurnal Kepimpinan Pendidikan, 6(4), 1–21.
Omar, M. N., Ismail, S. N., & Kasim, A. L. (2020). Karakter kepimpinan teknologi pengetua dalam pengintegrasian ICT di sekolah menengah [The caracters of principals' technology leadership on ICT integration in secondary school]. Jurnal Kepimpinan Pendidikan, 7(1), 28–46.
Poulou, M. S., Reddy, L. A., & Dudek, C. M. (2019). Relation of teacher self-efficacy and classroom practices:
A preliminary investigation. School Psychology International, 40(1), 25–48.
Power, R., Cristol, D., Gimbert, B., Bartoletti, R., & Kilgore, W. (2016). Using the mTSES to evaluate and optimize mlearning professional development. International Review of Research in Open and Distance Learning, 17(4), 350–385.
Sabet, M. K., Dehghannezhad, S., & Tahriri, A. (2018). The relationship between Iranian EFL teachers’ self- efficacy, their personality and students’ motivation. International Journal of Education and Literacy Studies, 6(4), 7–15.
Sakiz, H., Ekinci, A., & Saricam, H. (2019). Teachers’ perceptions of their school managers’ skills and their own self-efficacy levels. International Journal of Leadership in Education, 0(0), 1–19.
Schipper, T., Goei, S. L., de Vries, S., & van Veen, K. (2018). Developing teachers’ self-efficacy and adaptive teaching behaviour through lesson study. International Journal of Educational Research, 88, 109–120.
Taherdoost, H., Shamsul Sahibuddin, & Jalaliyoon, N. (2014). Exploratory factor analysis: Concepts and theory.
Advances in Applied and Pure Mathematics, 375–382.
Tschannen-Moran, M., & Hoy, A. W. (2001). Teacher efficacy: capturing an elusive construct. Teaching and Teacher Education, 17, 783–805.
Tsigilis, N., Gregoriadis, A., Theodorakis, N. D., & Evaggelinou, C. (2019). Teachers’ self-efficacy and its association with their quality of relationships with pre and early adolescents: a hierarchical linear modelling approach. Education 3-13, 47(1), 64–73.
Williams, B., Onsman, A., & Brown, T. (2010). Exploratory factor analysis: A five-step guide for novices. Journal of Emergency Primary Health Care, 8(3), 1–13.
Yong, A. G., & Pearce, S. (2013). A Beginner’s guide to factor analysis: Focusing on exploratory factor analysis.
Tutorials in Quantitative Methods for Psychology, 9(2), 79–94.
Yoo, J. H. (2016). The effect of professional development on teacher efficacy and teachers’ self-analysis of their efficacy change. Journal of Teacher Education for Sustainability, 18(1), 84–94.
