Using Structural Equation Modeling to Assess a Model for Measuring Creative Teaching Perceptions and Practices in Higher Education

Abstract

Considering the differences in academic backgrounds and majors, diversity of faculty members’ perceptions, and complete shift to digital education, energy must be expended toward ensuring that the teaching practices of faculty members are innovative and distinctive by providing advanced methods and models for evaluation operations. Thus, this study aimed to assess a model for measuring perceptions of both the teaching profession and creative teaching practices among faculty members that explains the relationship between faculty members’ perceptions about teaching and their creative practices that was constructed to explain the nature of this relationship and enable the development of the faculty members’ academic and professional performance. Two instruments were developed in this study, and the study sample consisted of 250 faculty members. Structural equation modeling was used to assess the proposed model. The results of the modified construction model showed an improvement in the goodness of fit indicators, which points toward this being the best model for interpreting the study data. The developed assessment model and scales can be used as tools to measure faculty members’ perceptions and predict the improvement of their creative teaching practices as well as for their professional development during distance learning.

1. Introduction

Distance learning has imposed itself strongly as a result of the coronavirus pandemic. Many faculty members faced challenges imposed by the technical reality and the available potential solutions. In terms of mental unpreparedness for this sudden stage, there was a shortage of necessary strategies and tools and a lack of experience in the technical side. For the success of the distance educational process, it is necessary to focus on three elements that form the educational triangle: teacher, learner, and knowledge. Therefore, it is imperative to choose appropriate teaching methods and strategies as well as means and tools, in addition to having assessment tools for these elements.

The education sector was and still is the cornerstone for the advancement of societies. Perceptions that are a type of emotional variable influence actual teaching practice, which in turn leads to an understanding of mechanisms and strategies related to student learning. The study of perceptions represents a method for improving teaching methods and perhaps increases output. Making the necessary modifications in the teaching and learning processes starts with faculty members’ perceptions toward learning [1,2]. The goal of perception research is to first interpret and predict behavior, then modify it to the individual’s preferences.

Perceptions play a significant role in social and psychological studies. The majority of issues are psychological and pedagogical in nature, but attitudes and opinions have also been examined. Perceptions is a broad topic that adds to our understanding of social psychology. It is critical to assess people’s impressions so that unfavorable parts can be identified and modified [3].

Most researchers have emphasized the importance of perceptions and beliefs of teachers in providing them with insight into aspects of the professional world. This leads to improvement of their understanding of both educational practices and professional preparation processes, enabling an improvement of their actual practices [4,5,6]. “Perceptions and beliefs” are a vital matter to educational practice, and the most obvious scale for observation and professional guidance of teachers [4,7,8]. Understanding perceptions is an effective way to determine the quality of a teacher’s interaction and performance. Perceptions and beliefs are more influential than knowledge in defining and organizing tasks and problems. They are also considered the strongest indicator of behavior. There is a strong relationship between teachers’ perceptions and their classroom planning, procedures, materials, decision making, and practices [8,9]. Understanding this relationship is important for improving their professional development [4,7,10].

Studying the perceptions of faculty members is important in changing their behavior and perception of teaching. Faculty members are employed to assess new creative teaching ideas. Therefore, some perceptions should be changed to improve new teaching practices [11]. Perceptions have a great influence on training, which is most apparent in classroom practice. This means that innovations are interpreted and responded to in ways that relate to current beliefs and practices [8,12]. Perceptions influence the way that the teacher translates new approaches into practices that are consistent with their own concepts [13]. The teachers’ perceptions about the nature of learning and teaching explain most of their attitudes and behaviors in teaching and are a good predictor of teaching practices [14,15]. Perceptions toward teaching and learning influence the practices of faculty members and their professional development. Perceptions and beliefs have an important role in students’ academic performance because they are used to evaluate the ideas and concepts related to teaching that faculty members are exposed to during the teaching process [4].

Higher education, and university education in particular, is an essential process in the lives of peoples in developed nations and constitutes an opportunity for the progress of individuals within societies. Universities have a distinct role in transferring knowledge and technology as well as in making changes in society through the important and active role assigned to faculty members [16,17]. Higher education has an important role in developing creativity [18].

University education is considered an important way of preparing specialized and qualified cadres for community service, in order to face challenges, problems, and difficulties and to achieve sustainable comprehensive development under the current difficult circumstances. Since faculty members are one of the pillars of university education, they have a significant role to play in overcoming such difficulties and challenges. Therefore, it is imperative that faculty members use creative teaching strategies to develop the skills and abilities of students. Creativity in teaching is based on the beliefs and ideas of the faculty member in which they believe and on which they base their teaching practices [5,19,20]. Creativity in teaching is achieved when a faculty member uses modern teaching methods and strategies, which helps in developing creative abilities. It also promotes research, inquiry, creativity, and self-learning [21]. In light of this pandemic, the role of the faculty member has changed in terms of organizing educational content to effectively achieve the goals, take into account students’ educational needs, define appropriate goals and the means to achieve them, and choose measurement and feedback tools. In addition to choosing the appropriate educational software and an effective and widespread means of communication among students, it is necessary to determine the appropriate measurement tools. There is a weakness in the reliability of the evaluation and difficulty in controlling the implementation of tests, which leads to an inability in controlling cheating [22,23]. New teaching methods need to be based on increasing student independence [24].

Effective teaching is creative teaching, and thus, it is imperative for faculty members to encourage students to acquire creative thinking skills by providing a more challenging environment [25,26]. In addition, they need to employ their creative thinking in planning, implementation, and evaluation [27]. An effective creative teacher has innate creativity, and hence promoting and encouraging creativity and innovation enhances the quality of teaching [28]. In order to create an attractive environment from a distance, the lesson must be presented in an interesting and innovative way, and creative ideas and opinions should be exchanged and discussed.

The necessity of relying on alternative assessment methods, which reflect the students’ real performance level and knowledge of their strengths to enhance them, as well as of their weaknesses to address them, is one of the creative practices that a faculty member must adopt in addition to their choice of modern teaching strategies and their support with a set of educational methods that achieve a creative classroom atmosphere [19].

Distance creative teaching is instruction that develops the student’s ability to connect and reorganize different elements in new ways, which are characterized by fluency, flexibility, and originality [5]. Distance creative teaching practices are teaching methods and patterns of behavior that are practiced and preferred by the faculty member and that distinguish them from others [16].

All faculty members and lecturers in universities come with different backgrounds, perceptions, and beliefs about teaching processes and mechanisms. They possess knowledge and experience in their field of specialization, but they may face the problem of their knowledge of ways and strategies for imparting this knowledge and specialized experiences to students. Here lies the major problem of their possession of knowledge and experience in the field of specialization, and of their differing perceptions and beliefs about effective teaching methods and practices for imparting information to students.

Thus, the previous circumstances and obstacles may impose on universities the need to provide educational experts and consultants to draw up policies and regulations to identify roles, responsibilities, and optimal teaching practices. The advisory body should identify the perceptions and beliefs of faculty members, study and analyze them, and in light of this, build training programs that help faculty members distinguish between positive and negative perceptions, support what is positive, and develop a roadmap for the roles, responsibilities, and practice of teaching that achieve sustainable professional development of faculty members. Hence, the availability of some models that include standards for creative teaching practices and are based on the different perceptions and beliefs of faculty members is commendable and, of course, helps to identify existing shortcomings, and a list is made of training programs that help faculty members translate these perceptions into effective teaching practices. Therefore, the current research seeks to answer this question: What is the proposed perception for assessing a model measuring the creative teaching perceptions and practices of faculty members?

2. Literature Review

Constructivism theory describes the relationships between the variables this study aims to investigate, such as perceptions of teaching tasks (PTT) and creative teaching practices (CTP). Constructivism emphasizes the independence of interpretation of an individual’s experience. It also indicates that learners actively participate in product knowledge and are not passive participants. Constructivist perspectives also provide more opportunities for students to produce solutions to the challenges they face and encourage them to actively participate in learning practices. Therefore, the development of cognitive processing is more important than the acquisition of specific knowledge [29,30].

Faculty members play an important role in the educational process in universities, so they must be effective and efficient, and they must be professionally developed to in turn develop and improve the efficiency and effectiveness of teaching [31]. Professional development is achieved through the exchange of ideas between faculty members and students, and it can also be improved by developing and refining faculty skills in academic research to enhance their professionalism [31,32]. Professional development increases opportunities to understand and develop faculty members’ perceptions and beliefs about teaching and learning [33,34].

The practices of faculty members can be determined by their teaching methods and experiences, and by their perceptions and interpretations of general education policies. These practices should emphasize the importance of training faculty in assessing learners’ needs and raising awareness about how the method used in teaching impacts and supports this [35,36,37]. This is in addition to the need for there to be integration among faculty members in the continuous assessment tasks of students’ performance [38].

The study by Awad and Halles showed positive attitudes toward distance education technology [39]. There were high and positive attitudes among faculty members toward using e-learning [40,41]. The study by Mofreh et al. aimed to investigate lecturers’ perceptions in order to improve teaching practice by changing their teaching roles [42]. Many studies have addressed the impact of the relationship between faculty members’ beliefs and their practices, and these beliefs lead to understanding and improving teaching practices [8,43]. Mofreh, Ghafar, and Omar assessed and revealed that demographic factors have a weak influence on the lecturer’s beliefs in teaching, and they lack beliefs about the professional practice of teaching [11]. Some studies have revealed that the relationship between faculty members’ beliefs and their practices is complex [44,45]. Fakih and Abi Mawlud explored teachers’ beliefs about teaching English, so it is necessary to take these beliefs into account in order to create change in actual teaching practices [15]. Chan and Yuen investigated teachers’ beliefs about creativity, cognitive aspects, and personality in their creativity-enhancing practices [46]. The study by Aboud uncovered obstacles to creative teaching for faculty members. The results showed that there are strong obstacles related to students, curricula, and teaching environments [47]. Many studies have stimulated creativity and creative teaching in higher education, and teaching staff’s practice in methods of developing creative thinking [5,20,25,48].

3. Methodology

3.1. Research Model and Procedure

In this study, a quantitative descriptive survey was adopted as the research strategy because it considers one of the forms of organized scientific analysis and interpretation to describe a specific phenomenon or problem by collecting, classifying, and analyzing standardized data, and it gives more accurate results. The questionnaires were developed to assess the relationship between faculty members’ perceptions of teaching tasks and creative teaching practices. Ethical approval was obtained from King Faisal University to conduct the research. The scale was applied to an exploratory sample and then to the sample. Finally, statistical treatments, analysis, and an interpretation of the findings were conducted.

3.2. Population and Sampling

The population included all faculty members at Saudi universities during the aca-demic year 2020/2021, and these universities were distributed over five regions: the north, south, east, west, and middle of the Kingdom of Saudi Arabia. The questionnaires were completed by 250 faculty members in total. The sample of the study has been constructed through random selection from the five universities of each region as shown in

Table 1. The distribution of the study sample.

Region	University	Percentage	Sample Size
North	Northern Border University	13%	33
South	King Khalid University	15%	37
Middle	King Saud University	20%	49
East	King Faisal University	30%	75
West	King Abdulaziz University	22%	56

.

The administration of the universities was contacted to distribute the questionnaire with the ethics statement of scientific research attached. The universities then sent messages to faculty members requesting their participation. Some colleagues also helped in the process of distribution. The data were collected through Google Forms, and questionnaires were sent to all potential respondents through email and WhatsApp.

3.3. Structural Equation Modeling (SEM)

The structural equation model is a comprehensive statistical model for testing hypotheses about the relationships between observed and latent variables. It is also defined as a hypothesized pattern for direct and indirect linear relationships between a set of latent and observed variables. It considers a complete path model for the relationship between a group of variables that can be described or represented in a path diagram. Structural equation modeling (SEM) and confirmatory factor analysis (CFA) can determine, estimate, evaluate, and present a new model to demonstrate relationships among variables [1,49].

The use of SEM enables researchers to have a good appreciation of the measurement model and the structural model. Many researchers in the social sciences have used this method because of latent variables, which cannot be directly observed or measured [50,51]. The problem under study is viewed as a phenomenon or variable that can be measured and quantified by constructing a model to measure it. This model includes a set of indicators, and its validity is tested through a set of advanced statistical methods (i.e., CFA) [52]. The aim of the confirmatory factor analysis is to eliminate high measurement errors and poorly loaded expressions in order to obtain a model with appropriate matching indicators between the observed and measured models [50].

The methodology of SEM depends on representing the studied phenomenon and the relationships among its elements (variables) through a model that simulates them in reality, simplifying them with expression and symbolic representation. The model represents a description of the phenomenon in terms of its variables, determining the relationships between them and controlling the conditions accompanying its study in a way that can predict its future. SEM has become the latest method for testing hypothetical models of phenomena in behavioral sciences and theoretical structures represented by factors and variables that can be measured indirectly through a set of indicators (latent variables) [53]. As a result, and based on the objective of this study, structural equation modeling (SEM) was used to assess the measurement model of faculty members’ perceptions about the creative teaching practice.

3.4. The Questionnaires

After reviewing the previous studies, the questionnaires were developed to assess the relationship between faculty members’ perceptions of teaching tasks and creative teaching practices. SEM was used to measure the relationship between both latent and observed variables, test the relationships between constructs with items, analyze model fit, and investigate the relationship between perceptions of teaching tasks (PTT) and creative teaching practices (CTP). SEM and confirmatory factor analysis (CFA) using AMOS can determine, estimate, evaluate, and present a new model to demonstrate relationships among the variables PTT and CTP.

For measuring perceptions of teaching tasks (PTT) and creative teaching practices (CTP), two instruments were developed and tested. The objective of the questionnaires was defined, and the dimensions of the instruments were determined; then, the items of instruments were developed. The PTT questionnaire comprised five constructs namely, (1) planning and classroom management (PCM) that includes five items, (2) creative teaching strategies (CTS) that includes seven items, (3) creative communication with students (CCS) that includes four items, (4) creative assessment of learning (CAL) that includes four items, and (5) enhancing teaching practices (ETP) that includes four items. The CTP questionnaire comprised four constructs, namely (1) creative planning for teaching (CPT) that includes 10 items, (2) creative teaching methods and strategies (CTMS) that includes 13 items, (3) a creative presenting for teaching (CPFT) that includes 14 items, and (4) the comprehensive assessment (CA) that includes 13 items. The validity and reliability of questionnaires generated by PTT and CTP are assessed using the Rasch model.

4. Findings

4.1. Validity and Reliability of PTT and CTP Questionnaires

The questionnaires were presented to seven specialized faculty members from King Faisal University, and based on their comments on the questionnaire, some items were changed and some other items were reformulated as shown in Appendix A. Through Winsteps software version 3.68.2, RM analysis was used to test the validity and reliability of PTT and CTP questionnaires. The validity of the questionnaires was assessed using MNSQ infit values of 0.4 to 1.5, item polarity analysis (PTMEA) values of 0.2 to 1, and standardized fit statistic (ZSTD) values of −2 to 2. Dimensionality aspects were used to determine that every instrument was measured in one direction and one dimension, and the effect of one attribute or dimension at a time to ensure content validity and construct validity. The criteria for dimensionality are that the raw variance explained by measures should be higher than 40% and the unexplained variance in the first contrast should be less than 15%. Rasch analysis determines the validity of the response probabilities being spread fairly by grading scale calibration analysis for scales. The person and item reliability were used to assess the instrument reliability [54,55,56].

Items T11 and H6 were excluded because their MNSQ values of infit and outfit were larger than 1.5, as shown in

Table 2. CTP questionnaire item polarity and fit analysis.

Measure	Model S.E	Infit MNSQ ZSTD		Outfit MNSQ ZSTD		Pt-measure CORR EXP		Exact OBS%	Match EXP%	Items
1.12	0.22	1.65	2.7	2.45	3.8	0.53	0.70	51.1	55.8	T11
−1.00	0.23	1.59	1.2	1.61	2.2	0.59	0.67	59.6	57.3	H6
−0.06	0.22	1.25	1.3	1.36	1.4	0.60	0.65	57.4	55.1	H3
−0.35	0.23	1.23	1.2	1.10	0.5	0.61	0.65	61.7	57.4	T2
0.37	0.25	1.36	1.7	1.40	1.7	0.61	0.70	61.7	60.7	T4
−1.00	0.28	1.12	0.6	1.08	0.4	0.62	0.65	61.7	67.5	H1
−0.73	0.23	1.37	1.7	1.28	1.2	0.62	0.69	59.6	59.3	H5
−0.31	0.24	1.16	0.8	1.25	1.1	0.62	0.66	61.7	58.3	T3
−0.33	0.23	1.11	0.6	1.06	0.3	0.63	0.65	53.2	56.5	T10
0.01	0.22	1.08	0.4	1.01	0.1	0.63	0.64	61.7	56.2	I5
0.64	0.23	1.27	1.2	1.33	1.3	0.63	0.70	61.7	60.1	I13
0.46	0.22	1.27	1.2	1.11	0.5	0.64	0.67	66.0	57.9	A8
−0.07	0.24	1.17	0.9	1.20	−0.2	0.64	0.68	55.3	57.6	T12
0.34	0.24	1.14	0.7	1.32	0.5	0.64	0.68	59.6	61.5	A4
0.34	0.22	1.18	0.9	1.11	−0.2	0.64	0.67	66.0	59.6	A11
−0.43	0.24	1.03	0.2	0.93	0.0	0.65	0.65	63.8	60.1	H7
0.34	0.23	1.16	0.8	1.10	0.5	0.65	0.68	53.2	56.8	A9
0.22	0.22	1.00	0.1	0.93	0.4	0.65	0.65	51.1	58.1	A1
−0.24	0.24	1.01	0.1	0.99	0.1	0.66	0.66	59.6	58.6	H9
0.25	0.25	1.12	0.6	1.09	0.0	0.66	0.69	66.0	62.0	T5
−1.09	0.23	1.00	0.1	0.88	−0.2	0.66	0.66	70.2	59.2	H10
0.11	0.24	1.07	0.4	1.00	1.2	0.67	0.68	63.8	60.7	H4
−0.60	0.26	1.03	0.2	0.98	−0.4	0.67	0.67	68.1	63.3	H2
−0.65	0.21	0.97	0.0	0.93	0.0	0.67	0.68	55.3	57.8	A6
0.13	0.22	0.91	−0.4	1.31	−0.3	0.67	0.67	55.3	53.2	T8
0.31	0.22	0.94	−0.2	0.88	−0.5	0.67	0.66	59.6	57.2	A5
−0.57	0.21	1.00	0.1	0.99	−0.4	0.67	0.68	70.2	59.4	A10
0.24	0.24	0.98	0.0	0.91	−0.8	0.68	0.68	68.1	62.3	A3
−0.04	0.22	0.87	−0.4	0.85	−0.6	0.68	0.65	55.3	54.0	I2
−0.24	0.25	0.94	−0.2	0.89	−0.5	0.69	0.67	61.7	61.7	T1
−0.66	0.23	0.86	0.1	0.81	−0.9	0.69	0.65	70.2	56.9	T7
−0.76	0.27	0.90	0.0	0.85	−1.2	0.70	0.66	72.3	65.6	T9
0.34	0.23	0.91	−0.7	0.88	−0.2	0.71	0.68	51.1	56.8	A13
−0.30	0.26	0.85	−0.2	0.80	−0.7	0.71	0.67	72.3	64.0	H8
0.33	0.21	0.79	−0.8	0.70	−0.7	0.71	0.66	53.2	51.9	I9
0.51	0.24	0.94	−0.4	0.93	−0.8	0.71	0.69	74.5	63.2	A12
0.40	0.24	0.91	−0.4	0.83	−1.3	0.71	0.69	61.7	62.7	I4
0.21	0.24	0.88	−0.6	0.84	−0.8	0.72	0.68	57.4	59.7	T6
0.36	0.23	0.86	−1.1	0.80	−0.8	0.72	0.68	72.3	63.0	I14
−0.71	0.22	0.78	−0.2	0.71	−1.4	0.72	0.69	63.8	59.4	T13
0.54	0.22	0.87	−0.6	0.80	−0.9	0.72	0.69	57.4	57.1	A7
0.15	0.25	0.85	−0.7	0.80	−1.6	0.72	0.68	63.8	59.1	I3
−0.01	0.23	0.75	−1.3	0.70	−1.6	0.73	0.66	74.5	53.0	A2
0.41	0.23	0.83	−0.8	0.79	−1.4	0.75	0.69	57.4	64.2	I7
0.38	0.23	0.70	−1.6	0.67	−1.6	0.75	0.69	66.0	59.1	I6
0.76	0.21	0.69	−1.7	0.62	−1.4	0.75	0.69	66.0	53.0	I12
0.21	0.25	0.73	−1.3	0.70	−1.5	0.75	0.69	74.5	64.2	I1
0.38	0.23	0.70	−1.6	0.66	−1.6	0.76	0.69	66.0	59.1	I8
0.66	0.22	0.75	−1.3	0.70	−1.4	0.77	0.70	72.3	56.2	I10
−0.37	0.22	0.74	−1.3	0.71	−1.5	0.77	0.71	68.1	54.8	I11

below.

The findings of the Rasch model showed that all items of the CTP questionnaire have positive value after deleting the inappropriate items. According to the Rasch model, these values are adequate and acceptable for constructing validity. The PTT questionnaire had a good item correlation and item fit, as shown in

Table 3. PTT questionnaire item polarity and fit analysis.

Measure	Model S.E	Infit MNSQ ZSTD		Outfit MNSQ ZSTD		Pt-Measure CORR EXP		Exact OBS%	Match EXP%	Items
−0.21	0.27	1.43	1.7	1.45	1.8	0.66	0.76	63.6	63.2	CTS16
0.64	0.28	1.45	1.9	1.41	1.6	0.70	0.80	68.2	62.5	CAL14
−0.21	0.27	1.31	1.4	1.44	1.5	0.70	0.76	63.6	63.2	CCS13
1.23	0.29	1.32	1.5	1.46	1.5	0.71	0.76	54.5	66.0	CCS22
1.29	0.30	1.30	1.4	1.16	0.7	0.72	0.77	56.8	67.5	PCM2
−0.91	0.25	0.97	−0.1	1.10	0.4	0.73	0.73	70.5	63.4	CTS6
0.34	0.27	1.28	1.3	1.42	1.8	0.73	0.78	70.5	62.6	CCS15
−0.07	0.27	1.29	1.3	1.23	1.0	0.73	0.77	59.1	62.3	PCM3
1.06	0.29	1.12	0.6	1.04	0.2	0.74	0.76	68.2	66.3	ETP12
−0.65	0.27	1.03	0.2	0.90	−0.2	0.74	0.74	59.1	64.5	CTS20
−0.52	0.26	1.20	0.9	1.16	0.7	0.75	0.76	61.4	63.6	CTS5
−1.01	0.26	0.74	−1.1	0.74	−0.8	0.76	0.72	81.8	64.3	PCM10
0.54	0.32	0.90	−0.4	0.86	−0.5	0.76	0.74	70.5	72.1	PCM1
0.03	0.27	1.06	0.4	0.98	0.0	0.77	0.76	79.5	64.0	ETP21
−0.70	0.29	0.82	−0.8	0.75	−0.9	0.78	0.74	72.7	66.7	ETP7
−0.34	0.31	0.84	−0.7	0.93	−0.6	0.79	0.76	77.3	69.8	CTS8
−0.82	0.26	0.64	−1.6	85	−1.8	0.80	0.73	70.5	64.3	CCS23
0.17	0.26	0.74	−1.2	0.54	−0.1	0.80	0.78	79.5	62.5	CAL18
−0.45	0.28	0.77	−1.1	0.94	−1.1	0.81	0.76	72.7	64.2	CTS9
−0.50	0.30	0.67	−1.6	0.72	0.1	0.81	0.76	77.3	68.0	CAL24
0.54	0.32	0.68	−1.6	1.00	−1.6	0.81	0.74	84.1	72.1	CAL19
0.97	0.28	0.65	−1.8	0.63	−1.7	0.81	0.75	81.8	65.7	ETP17
0.04	0.28	0.82	−0.8	0.53	−1.0	0.81	0.78	75.0	63.4	PCM4
−0.46	0.28	0.59	−2.2	0.78	−1.8	0.84	0.76	77.3	65.6	CTS11

. Such a result is indicative of a good item, and all of the items were found to be appropriate. These values are adequate and acceptable for constructing validity, according to the Rasch model.

These values were confirmed to be appropriate and acceptable to construct validity from previous statistics for both PTT and CTP surveys to assure the validity construct according to the Rasch model. The category structure on scale gradation and size structure of the junction is summarized in

Table 4. Calibration scaling analysis of CTP questionnaire.

Category Label	Observed Count %	Observed Average	Sample Expect	Infit MNSQ	Outfit MNSQ	Structure Calibration	Category Measure
2	1 2	−4.51	−3.60	0.19	0.24	Non	(−5.00)
3	6 13	−0.40	−0.51	0.83	0.79	−2.85	−2.556
4	27 57	0.94	0.80	1.53	1.27	−0.26	0.45
5	13 28	1.90	2.18	1.30	1.29	3.11	3.24

and

Table 5. Calibration scaling analysis of PTT questionnaire.

Category Label	Observed Count %	Observed Average	Sample Expect	Infit MNSQ	Outfit MNSQ	Structure Calibration	Category Measure
3	7 16	−1.05	−1.01	0.87	0.83	Non	−2.59
4	25 57	0.59	0.66	0.97	0.87	−2.02	0.54
5	12 27	3.30	3.14	0.87	0.87	2.02	3.67

and Figure 1 and Figure 2. In the surveys, the timetables for grading scale calibration analysis are also shown.

Table 4 shows that the most common response is the scale of participants ranking 4 for 27 (57%), followed by the scale 5 for 13 (28%), then the scale 3 for 6 (13%), and finally the scale 2 for 1 (2%). The observed averages column shows the pattern of respondent movement from negative to positive (−4.51 to 1.90). Based on the Rasch model, this shows a normal pattern.

Table 5 shows that the most common response is the scale of participants ranking 4 for 25 (57%), followed by the scale of participants ranking 5 for 12 (27%), and finally the scale 3 for 7 (16%). The observed averages column reveals that the respondents’ pattern shifts from negative to positive (−1.05 to 3.30), which indicates a normal pattern based on the Rasch model.

The raw variance explained by measures was 49.4% and 58.2%, respectively, as shown in

Table 6. Item dimensionality of PTT questionnaire.

	Empirical				Modeled
Total raw variance in observations	98.9		100%		100%
Raw variance explained by measures	48.9		49.9%		59.3%
Raw variance explained by persons	29.2		29.5%		39.3%
Raw variance explained by items	19.7		19.9%		20.0%
Raw unexplained variance (total)	50	50.6%		100%	50.5%
Unexplained variance in 1st contrast	9.6		9.7%		19.2%
Unexplained variance in 2nd contrast	5.6		5.7%		11.3%
Unexplained variance in 3rd contrast	3.7		3.8%		7.4%
Unexplained variance in 4th contrast	3.3		3.3%		6.6%
Unexplained variance in 5th contrast	2.8		2.8%		5.5%

and

Table 7. Item dimensionality of CTP questionnaire.

	Empirical				Modeled
Total raw variance in observations	57.5		100%		100%
Raw variance explained by measures	33.5		58.2%		57.0%
Raw variance explained by persons	22.3		38.8%		38.1%
Raw variance explained by items	11.1		19.4%		19.0%
Raw unexplained variance (total)	24.0	41.80%		100%	43.0%
Unexplained variance in 1st contrast	2.9		5.1%		12.2%
Unexplained variance in 2nd contrast	2.4		4.3%		10.2%
Unexplained variance in 3rd contrast	2.4		4.2%		10.0%
Unexplained variance in 4th contrast	2.0		3.5%		8.3%
Unexplained variance in 5th contrast	2.0		3.4%		8.1%

. In the first contrast, the unexplained variance was 9.7% and 5.1%, respectively. As a result, dimensionality data results follow the Rasch model.

To ensure reliability, the Rasch model should verify the person and item reliability. The criteria for reliability should be above 50%. Furthermore, item and person separation values should be more than two to be acceptable [55,57].

Table 8. Person and item separation and reliability of PTT questionnaire.

	Score	Count	Measure	Error	Infit		Outfit
					IMSQ	ZSTD	IMSQ	ZSTD
Mean	190.9	50.0	0.92	0.24	1.01	−1.0	0.99	1.0
S.D	29.6	0.0	1.62	0.07	0.81	4.1	0.82	4.0
Real RMSE	0.29
Adj. SD	1.59
Separation	5.52
Person reliability	0.97
Mean	194.4
SD	5.6	50	0.0	0.23	1.00	0.0	0.99	0.1
Real RMSE	0.24	0.0	0.50	0.01	0.20	1.0	0.30	1.1
Adj. SD	0.44
Separation	2.81
Item reliability	0.77

and

Table 9. Person and item separation and reliability of CTP questionnaire.

	Score	Count	Measure	Error	Infit		Outfit
					IMSQ	ZSTD	IMSQ	ZSTD
Mean	94.0	24.0	1.07	0.40	1.07	0.40	1.07	−0.3
S.D	14.2	0.0	1.92	0.12	0.75	2.5	0.81	2.4
Real RMSE	0.49
Adj. SD	1.94
Separation	3.99
Person reliability	0.94
Mean	102.4	50.0	0.00	0.28	0.99	−0.1	1.07	0.2
SD	4.9	0.0	0.68	0.02	0.28	1.3	0.52	1.6
Real RMSE	0.3
Adj. SD	0.61
Separation	2.56
Item reliability	0.81

below show the per-son and item separation and reliability for both PTT and CTP questionnaires. The person reliabilities are greater than 0.5, with values of 0.97 and 0.94, respectively. The item reliabilities are greater than 0.5, at 0.77 and 0.81, respectively. Furthermore, the person separations are greater than two, at 5.52 and 3.99, respectively. The item separations are greater than two, at 2.81 and 2.56, respectively. The questionnaires have a high level of reliability, as indicated by these reliability values based on the Rasch model.

4.2. SEM Analysis of the Theoretical Model for the Relationship of CTP and PTT

First, a suitable initial measurement model is required. An appropriate model is one that fits appropriately with the data, so appropriateness indices must be calculated and model estimates computed. Figure 3 below describes the initial model fitness. Before starting statistical analysis, the data were examined to ensure that essential assumptions, such as validity, reliability, and unidimensionality, were satisfied. Since the construct items have good satisfactory factor loadings, this represents unidimensionality, as shown in Figure 3. The composite reliability (CR) was examined to ensure good construct validity. As shown in Figure 3, the standardized loadings for all the observed variables were higher than 0.50 [58]. Because the squared correlation between each pair of constructs is opposite to the average of the AVEs for these two constructs, discriminant validity exists. The PTT constructs’ average variance extracted (AVE) values varied from 0.89 to 0.94, whereas the CTP constructs’ AVE values ranged from 0.75 to 0.95. Thus, all the constructs that have been used in this study showed good reliability and validity, as shown in Figure 3.

For a model to fit the data, the following goodness of fit indices should be met. The comparative fit index (CFI), the normed fit index (NFI), the Tucker Lewis index (TLI), and the incremental fit index (IFI) are acceptable if their values are greater than 0.90. The root mean squared error of approximation (RMSEA) should be less than 0.08 to be acceptable [58,59,60]. The Chi-squared model assesses overall fit as well as the gap between the sample and fitted covariance matrices. The p-value should be greater than 0.05.

The Chi-square was significant, the CFI value was 0.928, the TLI value was 0.887, the IFI value was 0.928, the NFI value was 0.882, the RMSEA value was 0.126, and the Chi-square/df value was 4.59, as shown in Figure 3. The Chi-square, CFI, IFI, and Chi-square/df values indicate that the measurement was well fit. The goodness of fit indexes for TLI, NFI and RMSEA, on the other hand, indicate low goodness of fit.

Since the initial proposed measurement model did not fit for some fit indices, a modified measurement model was proposed. By conducting covariance between errors, goodness of fit indices recalculated. Figure 4 showed that the Chi-square was significant, with a value of 0.943 for the CFI, 0.902 for the TLI, 0.943 for the IFI, 0.912 for the NFI, 0.075 for the RMSEA, and 3.92 for the Chi-square/df. As a result, this modification led to a model with satisfactory goodness of fit. Figure 4 shows that there is a relationship and correlation between faculty member perceptions and creative teaching.

5. Discussion

Paying attention to the perceptions of faculty members can lead to an understanding of educational practices, and thus they can improve their professional preparation processes and creative practices. Understanding perceptions is an effective way to determine the quality of faculty members’ interaction and performance. Faculty members believe that there are moderate obstacles to the implementation of creative teaching [47]. Therefore, the perceptions of faculty members toward creative teaching tasks and practices are important for developing and improving the educational process in a creative way.

The goodness of fit indices showed improvement for the modified model, indicating that there was a good fit. All of the items in the measuring model were statistically significant according to the AVE results. The findings also revealed a strong and significant correlation between faculty member perceptions and creative teaching practices as shown by the proposed modified measurement model. This result indicates that changes in faculty members’ perceptions and beliefs about the teaching process will lead to changes in their behaviors and creative teaching practices. Faculty members’ perceptions of creative teaching guide and regulate their educational activities and practices. Thus, faculty members who have a highly positive perception of effective teaching have higher creative teaching practices than those who have low perceptions.

The proposed measurement model to predict the relationship and effect between faculty members’ perceptions and their creative teaching practices indicated changes in faculty members’ behaviors and their creative teaching practices.

Learning strategies are understood by knowing how emotional factors, such as perceptions, beliefs, and attitudes affect teaching practice. These variables refer to a strategy for improving outcomes and developing innovative teaching practices and methods. The goal of studying perceptions is to explain, predict, and then modify behavior [1].

The results showed that good correlation was observed between PTT and CTP. This indicated that the relationship between PTT and CTP were positive. This meant that the relationship between BCT and CTP of faculty members was significant, and PTT has an influence on CTP. Therefore, an increase in perceptions of faculty members toward teaching tasks leads to an increase of creative teaching practices. This finding is in line with the study findings of [4,44]. This result shows that a good evaluation of faculty members’ perceptions plays a vital part in their creative teaching practices, improving professional preparation, and improving their teaching effectiveness.

From their point of view, the teaching practices of the faculty members were of a high degree. This result is due to the fact that most teaching practices represent the positive side of most faculty members, in addition to the available material and moral capabilities, which are positively reflected on their teaching practices [61,62,63,64].

Knowing the faculty members’ perceptions about teaching a field of knowledge and evaluating this knowledge is a first step and a basis for planning and developing programs in this field. Therefore, perceptions play a role in determining the behaviors and practices of teachers, such as the cognitive that allows understanding reality and enables the acquisition of knowledge, as well as the identity that contributes to the social affiliation of individuals, in addition to guidance, where perceptions guide behaviors and practices of various activities [65].

The findings of Alghdoni showed that the relationship between beliefs and teaching skills was moderate [66]. There are also positive trends for teachers’ practice of the constructivist learning model. In addition, there are positive mental perceptions toward interactive communication, and support for the content of activities and learning strategies [67,68].

Perceptions and beliefs are important for teachers to improve and develop their professional preparation and teaching practices. They impart scientific quality that is reflected in their teaching performance, and their results are reflected in the development processes of teacher preparation programs [9,66]. The results of this study indicate that faculty members who have highly positive perceptions have highly creative teaching practices.

This study helps faculty members realize that their understanding and perceptions of their roles and responsibilities improve their professionalism and creative teaching practices. The list of practices extracted from this study can serve as the nucleus of a set of performance indicators that can be used as criterion references in the evaluation process. This study contributes to understanding the relationship between faculty members’ perceptions of creative teaching and their teaching practices on improving their classroom practices. In addition, providing faculty members with models and examples of how to apply these practices improves teaching effectiveness by enhancing faculty members’ awareness of their perceptions of classroom practices. Furthermore, this study also provides a model with the frameworks and conceptual background for the future analysis of perceptions about the roles, responsibilities, and practices of teaching.

6. Limitations and Future Directions

The degree of benefit from this study depends on the availability of university policies, deanships, and departments concerned with studying and supporting teaching practices and has the aim of considering and emphasizing the need both to pay attention to the field of teaching practices of faculty members and to be serious about taking into account the perceptions of faculty members when developing plans, policies, and required training for faculty members. In addition, there is the necessity of the presence of the feature of harmony and integration between the training packages and the sustainability of professional development processes for the faculty members.

One of the future directions in this regard is the possibility of researching other factors and influences that affect these perceptions, such as excessive workload, problems with student behavior and relationships with colleagues, and lack of resources and material requirements for teaching. It can also be suggested to conduct a study on creative teaching practices and their relationship to other personal variables, such as sociability, extraversion, self-efficacy, etc., in addition to the necessity of promoting positive perceptions through organizing meetings, workshops, and seminars on creative teaching skills and techniques and the adoption of educational consultants at the university to guide faculty members and follow up their educational activities. The developed scales can also be used as measuring tools to assess faculty members’ perceptions and predict the improvement of their creative teaching practices and professional development during distance learning. Moreover, the assessment model developed for faculty members’ perceptions and their creative teaching practices during distance learning can be used in universities. Furthermore, other factors that may have an impact on the relationship between perceptions and creative teaching practices during distance learning can be considered, such as customs, traditions, norms, values, challenges, and societal culture, in addition using a larger sample from more than one university and structural equation modeling to identify additional impacting factors and predict new variables for use.