Teacher Readiness and Learner Competency in Using Modern Technological Learning Spaces

Abstract

The educational space and its many aspects influence the teaching and learning process. Traditionally, educational institutions deal with learning spaces in the light of distance learning and formal education, such as classrooms, laboratories, libraries, and others. This study aimed at defining the readiness degree of teachers for using modern technological learning spaces and their relationship to the enhancement of learners’ competency. Its randomly selected sample consisted of 397 schoolteachers in the Green Line area that has been occupied by Israel since 1948. A questionnaire was used to achieve the study objectives. Statistical Package for Social Sciences (SPSS 25) was used to analyze the data. The findings of the study are: (i) the readiness degree of teachers for modern technological learning spaces and the degree of enhancement of learners’ competency were moderate, (ii) there was a statistically significant correlation between the readiness degree of teachers for modern technological learning spaces and the enhancement of learners’ competency, (iii) the importance of using technological learning spaces in the educational field, and (iv) teachers had sufficient knowledge about the important role of technology in raising the outcomes of the teaching and learning process.

1. Introduction

The large developments that are taking place in the field of information and communication technology have called on scholars, policymakers, and teachers to examine how to benefit from this technology for educational purposes [1,2]. Technology affects the components of education (learners, teachers, and the educational environment) and its motives. It raises the degree of learning, which influences and increases production and overcomes obstacles. In this field, current learning patterns require learning spaces that are usually found in schools, where work should be done to design educational spaces and modify them according to educational needs [3]. In light of the changes that take place in this regard, which lead to digital technologies, it is important to focus on the perception and formation of the classroom. This classroom is the power behind the innovation of lecturers and students who work on integrating digital technologies to form technological learning spaces based on current educational theories and models [4]. This innovation allows the integration of learning activities in which the student is proactive and follows an open and constructive approach as a result of the use of digital technologies.

Technology-based learning and technological learning spaces are some of the main tributaries that support the integrated education system in modern societies to meet the current and future needs of comprehensive development [5]. Thus, the global trend today aims to keep pace with the rapid and successive developments in the field of information and communication technology [6]. Technological learning spaces are also defined as those spaces in which technology is integrated into the learning process to achieve a response to different learning activities by adapting and integrating learning units in a manner that takes advantage of technologies and technological developments so that the learning environment becomes a technology-rich environment [3]. Technological learning spaces are also known as a set of modern technologies that enable learners to actively participate in learning activities. Due to the provision of an educational climate with diverse technological experiences and the availability of a capable teacher who encourages learners to study hard, their academic performance is high [7].

According to recent visions about how contemporary students prefer to use technology and how its use affects their learning, in fact, the use of technological learning spaces leads to an increase in the level of students’ learning and interaction because technology helps them enjoy learning [8]. This means that students’ minds tend to work faster as a result of being helped by the use of modern technology.

On the other hand, the process of developing students’ competencies meets the requirements of contemporary education, such as skills in communication, critical thinking, analysis, organizing and planning, and the use of information and communication technologies [9]. According to Zamfir and Mocanu [10], perceived competence is a critical variable that enables students to participate and persevere in learning. As a result, they are unable to (i) handle difficult tasks and challenges and are more likely to follow negative trends in which lower expectations lead to less effort and less success, and (ii) avoid anxiety and depression, which negatively affect their academic motivation and performance. In this context, Martins and Santos [11] indicate that high rates of efficiency are related to the ability to learn. Those students who see themselves as having high levels of competence tend to persist with more challenging tasks and organize the learning process itself. They also use several learning strategies and search for the most suitable one to deal with different types of tasks to improve their academic performance.

Some scholars have several concepts about competency. For instance, Filippou [12] introduces competency as students’ belief that they are able to successfully complete a task in a specific environment, and their success depends on the types of learning environments and interactions that exist. Competency is an important factor that contributes to students’ academic success. On the other hand, Handrianto et al. [13] and Basith, Syahputra, and Ichwanto [14] see student competence as students’ beliefs that their ability to perform a set of instructional academic tasks boosts their confidence in their ability to perform the required set of activities and behaviors, and accomplish the tasks assigned to them professionally. Indeed, competence is defined as an individual’s confidence in his or her ability to organize and implement actions to achieve the desired goals. In the academic environment, competence is one of the important factors that have a significant contribution to the success of students because it significantly affects the choices and actions to achieve the expected goals, which depend on students’ beliefs that they are able to successfully achieve academic tasks and learning goals at high levels.

The readiness of teachers to employ and use technological learning spaces is one of the most important elements of the success of e-learning [15]. This is crucial to the success of using technological learning spaces, which includes the skills the students possess to employ technological learning spaces that help them perform their work and their attitudes toward it. This expresses the state of mental and psychological readiness that stems from their experiences and is based on directing their behavior toward agreeing to its application [16].

Consequently, the success of using technological learning spaces is largely dependent on teachers and their motives for employing them in the learning process. Enthusiastic teachers who have positive attitudes seek to raise the levels of benefit from their employment, and this calls for raising their competencies, motivating them, and developing their capabilities [17,18]. Teacher Enthusiasm is defined as “the degree of enjoyment, excitement, and pleasure that teachers typically experience in their professional activities” [19]. Consequently, the success of using technological learning spaces is largely dependent on teachers and their motives for employing them in the learning process. Enthusiastic teachers who have positive attitudes seek to raise the levels of benefit from their employment, and this calls for raising their competencies, motivating them, and developing their capabilities [18,19].

The Green Line area in Palestine is a term used to describe the line separating the occupied territories in 1948 from the occupied territories in 1967 [20]. Bicchi and Voltolini state that “In the absence of an internationally and locally recognised border between Israel and Palestine, the Europeans have aimed at constructing one on the 1949 armistice line, the so-called Green Line” [21]. It was defined by the United Nations after the 1949 armistice that followed the war waged by the Arabs against Israel in 1948 to liberate their land from Israelite Zionism. The Palestinian people who live in the regions that were occupied by Israel in 1948 are called the “Palestinians of the Interior” (within the Green Line area) or the “Arabs of 48” (because most of them are Arabs) [22]. They are the Palestinians who remained in their homes within the borders of the State of Israel when it was established in 1948, and some of them were also displaced from their homes. They obtained Israeli citizenship in 1952. According to the Israeli Central Statistics (2019), the Arab population was estimated at 1,890,000 people, representing 20.95% of the country’s population. They consider themselves Arabs or Palestinians by nationality [23]. This study examines the relationship between the readiness of teachers and the competency of students in their dealings with modern technological learning spaces in Palestine.

2. Review of the Literature

A lot of studies have discussed the technological learning space; for example, Ghavifekr and Rosdy [24] conducted a study in Malaysia that identified teachers’ perceptions of the effectiveness of technological learning spaces in supporting the teaching and learning process. The study sample consisted of 101 male and female secondary school teachers who were chosen randomly. A questionnaire was used to collect the data. The results of their study show that (i) the level of effectiveness of technological learning spaces in supporting the teaching and learning process from teachers’ point of view is high, and (ii) working on preparing teachers appropriately and providing appropriate training programs for the use of technological tools and means is one of the main factors for the success of the teaching and learning process.

On the other hand, Daemi, Tahriri, and Zafarghandi [25] examine the relationship between the classroom environment and academic competence among students who are learning English as a foreign language in Iran. The study sample consisted of 200 male and female students. A questionnaire was used to collect data. The results show that (i) there is a positive, statistically significant relationship between the classroom environment of EFL learners and academic efficiency; (ii) the highest relationship was between task orientation and self-efficacy, followed by the relationship between student cohesion and self-efficacy, and then between cooperation and self-efficacy.

Marta [3] investigated the integration of technology in learning spaces according to the needs of teachers in Spain. The study sample consisted of 819 male and female teachers at preschool, primary, and secondary levels. It concluded that (i) teachers see it as necessary to reconfigure classrooms using technological learning spaces in order to break away from the traditional learning environment, and (ii) there are statistically significant differences in teachers’ perceptions about the level of necessity of integrating technology into learning spaces, in favor of secondary school teachers in terms of educational stage and in favor of 36–50 years in terms of age variable, while there are no differences in the light of the gender variable.

At the same point, Khan et al. [26] conducted a study in Pakistan to compare the academic efficiency levels of secondary school students in rural and urban areas of the Peshawar district in Pakistan. The study sample consisted of 300 male and female students who were selected by the stratified random method. A questionnaire is used to collect data. The study reveals that there are no statistically significant differences between the levels of academic efficiency among secondary school students.

3. Methodology

3.1. Theoretical Framework

Based on a review of the literature, unfortunately, no study has discussed the relationship between the readiness of teachers and the competency of students in their dealings with modern technological learning spaces in Palestine. This study examines the relationship between the readiness of teachers and the competency of students in their dealings with modern technological learning spaces in Palestine. The theoretical framework of the study was guided by the research question, “What is the relationship between the readiness of teachers and the competency of students in their dealings with modern technological learning spaces in Palestine?”

3.2. Research Design

The research methodology of this study is based heavily on quantitative methodology. Indeed, many reasons encourage the scholar’s choice in adopting it, such as: (i) data is collected from large participants rapidly, (ii) the sample is selected randomly, and (iii) the findings can be generalized because it represents a large sample [27].

3.3. The Population and Sample

The population of this study involved all the Arab teachers at the Arab schools inside the Green Line area in Palestinian lands that have been occupied by Israel since 1948. The population was 21,000 teachers. Based on Krejcie and Morgan’s table [28], the model sample for 21,000 is 317. Due to the coronavirus pandemic and its rules, the questionnaire was distributed to the teachers via social media (Facebook). A total of 412 teachers responded to the questionnaire, and 15 surveys were not convenient to analyze. Therefore, 397 were suitable to be analyzed. The rate of valid responses was %125.32. Figure 1 demonstrates the details of participants:

Criteria for Selecting the Sample

The sample should be (i) teachers, (ii) Palestinian, (iii) sex: male and female, (iv) ages from 25 to 55, (v) educational levels: (Bachelor, Master, and PhD).

3.4. Tools for Data Collection

To achieve the objectives of the current study, a questionnaire was developed to measure.

3.4.1. First Questionnaire

This was to determine the degree of teachers’ readiness to use modern technological learning spaces. A questionnaire was developed by adopting and adapting the study of Hinnawi and Najm [29]. The questionnaire, in its initial form, consisted of 26 items divided into two domains: the domain of beliefs, which consisted of 15 items, and the domain of competencies, which consisted of 11 items.

The Validity of the Questionnaire

The validity of the content of the questionnaire was verified by presenting it to five experts in educational administration. They were asked to provide their opinions on the level of appropriateness of the items, the integrity of the language, and their clarity. The proposed amendments approved by the experts had been taken into account. Thus, the questionnaire, in its final form, consisted of 26 items divided into two domains: the domain of beliefs, which consisted of 12 items, and the domain of competencies, which consisted of 14 items.

Construct Validity

In order to extract the significance of the construction validity of the scale, the scholar extracts (i) the correlation coefficients of every item and the total score, (ii) the correlation coefficients between every item and its connection with the domain to which it belongs, and (iii) the correlation coefficients between the domains with each other and the total score through a survey sample. This sample of the pilot test consists of 30 male and female teachers. The result indicates that the item’s correlation coefficients with the tool (0.36–0.88) and with the field (0.37–0.90) are high. The following

Table 1. The Coefficient of Correlation between the Items, the Overall Score, and the Domain to which They Belong.

Item No.	Correlation Coefficient with Field	Correlation Coefficient with the Tool	Item No.	Correlation Coefficient with Field	Correlation Coefficient with the Tool
1	0.51 **	0.55 **	14	0.86 **	0.86 **
2	0.87 **	0.83 **	15	0.61 **	0.58 **
3	0.37 *	0.36 *	16	0.79 **	0.82 **
4	0.90 **	0.88 **	17	0.71 **	0.68 **
5	0.73 **	0.67 **	18	0.68 **	0.62 **
6	0.81 **	0.84 **	19	0.78 **	0.76 **
7	0.75 **	0.73 **	20	0.70 **	0.69 **
8	0.51 **	0.53 **	21	0.85 **	0.88 **
9	0.61 **	0.59 **	22	0.56 **	0.59 **
10	0.83 **	0.82 **	23	0.85 **	0.36 *
11	0.67 **	0.69 **	24	0.46 *	0.50 **
12	0.60 **	0.55 **	25	0.78 **	0.76 **
13	0.58 **	0.51 **	26	0.84 **	0.84 **

* Statistically significant at the significance level (0.05). ** Statistically significant at the significance level (0.01).

shows that.

Table 2. Coefficients of Correlation between Domains and the Total Degree.

Beliefs	Beliefs	Competencies	Teachers’ Readiness
Competencies	1
Teachers’ Readiness	0.948 **	1
	0.985 **	0.989 **	1

** Statistically significant at the significance level (0.01).

explains coefficients of correlation between domains and the total degree.

Questionnaire Stability

To ensure the stability of the study tool, the test–retest stability method is verified by applying the scale and reapplying it after two weeks to a group outside the study sample consisting of 30 male and female teachers, and then the Pearson correlation coefficient is calculated between their estimates at both times.

The stability coefficient is also calculated by the internal consistency method according to Cronbach’s alpha equation, and

Table 3. Cronbach’s Alpha Internal Consistency Coefficient and Repetition Invariance for Domains and Total Score.

Domain	Replay Stability	Internal Consistency
Beliefs	0.88	0.81
Competences	0.90	0.84
Teachers’ Readiness	0.89	0.87

shows the internal consistency coefficient according to Cronbach’s alpha equation, the recursion stability of the domains, and the total score. These values are considered appropriate for the purposes of this study.

3.4.2. The Second Questionnaire

This determines the degree of upgrading the competencies of learners. It is initially composed of two areas: academic competency, which consists of 12 items, and social competency, which consists of 12 items.

The Validity of the Questionnaire

The validity of the content of the questionnaire is verified by presenting it to five experts from the faculty members in educational administration. Their proposed amendments have been taken into account. Thus, the questionnaire in its final form consists of two domains: the domain of academic competence, which consists of (12) items, and the domain of social competence, which consists of (12) items.

Construct Validity

In order to extract the construct validity of the scale, the correlation coefficients of each item, the total score, between each item, its connection to the domain to which it belongs, the domains to each other, and the total score are extracted in a pilot test of a survey sample from outside the study sample. The pilot study consists of (30) male and female teachers, and the items’ correlation coefficients ranged with the tool as a whole between (0.37 and 0.85), and with the field (0.50 and 0.86), and the following table shows that.

Table 4. The Correlation Coefficients between the Items, the Total Score, and the Domain to which They Belong.

Item No.	Correlation Coefficient with Field	Correlation Coefficientwith the Tool	Item No.	Correlation Coefficient with Field	Correlation Coefficient with the Tool
1	0.73 **	0.71 **	13	0.79 **	0.80 **
2	0.73 **	0.72 **	14	0.65 **	0.67 **
3	0.78 **	0.78 **	15	0.71 **	0.75 **
4	0.64 **	0.62 **	16	0.54 **	0.52 **
5	0.66 **	0.62 **	17	0.50 **	0.50 **
6	0.85 **	0.81 **	18	0.64 **	0.58 **
7	0.84 **	0.37 *	19	0.79 **	0.78 **
8	0.84 **	0.82 **	20	0.78 **	0.81 **
9	0.86 **	0.84 **	21	0.60 **	0.53 **
10	0.59 **	0.59 **	22	0.61 **	0.52 **
11	0.74 **	0.72 **	23	0.83 **	0.85 **
12	0.77 **	0.79 **	24	0.57 **	0.55 **

* Statistically significant at the significance level (0.05). ** Statistically significant at the significance level (0.01).

shows the correlation coefficients between the items, the total score, and the Domain to which They Belong.

It should be noted that all correlation coefficients are acceptable and statistically significant to varying degrees, and, therefore, none of these items are deleted. The following table shows that.

It should be noted that all the correlation coefficients were acceptable and statistically significant, and, therefore, none of these items were deleted. The domain correlation coefficient with the total score, the correlation coefficients between the domains and each other, and the following table shows that.

Table 5. Correlation Coefficients between Domains.

Domain	Academic Efficiency	Social Competence	Efficiency of Learners
Academic Efficiency	1
Social Competence	0.826 **	1
Efficiency of Learners	0.883 **	0.910 **	1

** Statistically significant at the significance level (0.01).

shows that all correlation coefficients were acceptable and statistically significant degrees, which indicates an appropriate degree of construct validity.

Questionnaire Stability

To ensure the stability of the study tool, the test–retest stability was verified by applying the scale and reapplying it after two weeks on a group outside the study sample consisting of 30 male and female teachers, and then the Pearson correlation coefficient was calculated between their estimates in both times.

The stability coefficient was also calculated. It uses the internal consistency method according to Cronbach’s alpha equation. The

Table 6. Cronbach’s Alpha Internal Consistency Coefficient and Repetition Invariance for Domains and Total Score.

Domain	Replay Stability	Internal Consistency
Academic Efficiency	0.86	0.75
Social Competence	0.83	0.71
Efficiency of Learners	0.85	0.82

show the cronbach’s alpha internal consistency coefficient and repetition invariance for domains and total score.

The above values were considered appropriate for the purposes of this study.

The Instrument of Data Analysis

SPSS 20 R software was the tool of the analysis. The five-point Likert scale was adopted to answer the first questionnaire: the degree of teachers’ readiness to use modern technological learning spaces, and the second one: the degree of raising the competencies of learners. This scale includes five degrees (very high, high, medium, low, very low), which are digitally represented as (5, 4, 3, 2, 1), respectively, and the following scale was adopted for analysis purposes:

• From 1.00 to 2.33 Low
• From 2.34 to 3.67 medium
• From 3.68 to 5.00 high

Etc.

The scale was calculated by using the following equation:

Upper end of scale (5)—lower end of scale (1).

     Number of classes required (3)

  5-1  = 1.33

     3

Then, add the answer (1.33) to the end of each category.

4. Findings

When the analysis was completed using SPSS, the following results were obtained:

4.1. Result of the First Question

What is the degree of teachers’ readiness to use modern technological learning spaces, from their point of view?

Table 7. Degree of Teachers’ Readiness to Use Modern Technological Learning Spaces.

Rank	Serial Number	Domain	Mean	Standard Deviation	Level Degree
1	1	Beliefs	2.96	0.793	Medium
2	2	Competencies	2.84	0.756	Medium
		Teachers’ Readiness	2.89	0.758	Medium

shows that the mean is ranged between (2.84 and 2.96), and the standard deviation (SD) is ranged between (0.756 and 0.793), where beliefs occupy the first rank with the mean (2.96), and their SD is 0.793, while competencies come in the last rank with the mean (2.84), and the SD is 0.756. The mean of the degree of the teachers’ readiness to use modern technological learning spaces from their viewpoint as a whole is (2.89), and the SD is 0.758.

4.1.1. The First Domain: Beliefs

Table 8. The Means and Standard Deviations of the Beliefs.

Rank	No.	Items	Mean	Standard Deviation	Level Degree
1	1	I believe that technological learning spaces make learning fun and exciting for students.	3.82	0.901	High
2	3	I believe that technological learning spaces enhance students’ capabilities in the field of technology and keep pace with its developments.	3.55	0.948	Medium
3	8	I believe that technological learning spaces provide students with access to educational materials at any time.	3.31	1.130	Medium
4	12	I think that technological learning spaces provide flexibility for students to access educational materials from anywhere.	3.16	1.260	Medium
5	10	I believe that technological learning spaces contribute to increasing students’ culture, knowledge, and general awareness.	2.94	1.319	Medium
6	4	I believe that technological learning spaces provide channels of communication among students, teachers, and between the school and the parents of the students.	2.92	1.245	Medium
7	9	I believe that technological learning spaces increase students’ motivation to learn.	2.74	1.161	Medium
8	2	I believe that technological learning spaces contribute to improving student achievement.	2.72	1.336	Medium
9	7	I believe that the application of technological learning spaces works to raise the teacher’s technical and pedagogical competencies.	2.65	1.210	Medium
10	5	I believe that technological learning spaces develop students’ self-learning.	2.59	1.387	Medium
11	6	I believe that technological learning spaces enhance learning with diverse activities inside and outside the classroom through the application of their diverse forms.	2.57	1.265	Medium
12	11	I see that technological learning spaces provide continuous feedback to the parties involved in the educational process.	2.52	1.053	Medium
		Beliefs	2.96	0.793	Medium

shows the means and standard deviations related to the beliefs arranged in descending order according to the mean.

Table 8 shows that the mean ranged between 2.52 and 3.82, where item no. (1) stating “I believe that technological learning spaces make learning fun and exciting for students”, came in the first place, with a mean of (3.82) and SD (0.901), while item no. (11) stating “I see that technological learning spaces provide continuous feedback to the parties involved in the educational process”, came in the last place, with a mean of (2.52) and SD (1.053). The mean of the field of beliefs as a whole was (2.96).

4.1.2. The Second Domain: Competencies

Table 9. The Means and Standard Deviations of the Competencies.

Rank	No.	Item	Mean	Standard Deviation	Degree Level
1	17	I have the ability to manage files on my computer, such as copying, pasting, and deleting files.	3.45	1.172	Medium
2	18	I can use YouTube to watch, learn, and download videos.	3.34	1.103	Medium
3	23	I can use email for correspondence and attaching files.	3.30	1.082	Medium
4	13	I can browse the web and download and upload files.	3.27	1.116	Medium
5	15	I have the ability to use social networks such as Facebook and Twitter.	2.80	1.249	Medium
6	21	I can use a word processor (MS Word).	2.73	1.274	Medium
6	22	I can use presentation software (MS Powerpoint).	2.73	1.121	Medium
8	16	I can search through search engines and do advanced searching on the Internet.	2.67	1.414	Medium
9	19	I have the basic skills to deal with the Windows system (Windows).	2.60	1.138	Medium
10	14	I possess theoretical knowledge within the framework of technological learning spaces.	2.58	1.248	Medium
10	24	I can use forums and chat sites on the Internet.	2.58	1.381	Medium
12	25	I can use the spreadsheet program (MS Excel).	2.58	1.151	Medium
13	26	I can use virtual classroom software on the Internet.	2.57	1.239	Medium
14	20	I can use chat programs (writing, audio, and video) on the Internet.	2.52	1.072	Medium
		Competencies	2.84	0.756	Medium

shows the mean and standard deviations related to the competencies, arranged in descending order according to the mean.

Table 9 explains the competencies in terms of means and standard deviations. The means were ranged between 3.45 and 2.52, where item no. (1) stating “ I have the ability to manage files on my computer, such as copying, pasting, and deleting files” occupied the first place, with a mean of 3.45 and SD 1.172, while item no. 14 stating “I can use chat programs (writing, audio, and video) on the Internet” occupied the last place, with a mean of 2.52 and SD 1.072. The mean of the field of competencies as a whole was 2.84 and the SD was 0.756.

4.2. Results and Discussion of the Second Question:

From the teachers’ point of view, what is the degree of raising the competencies of learners inside the Green Line area in Palestine?

To answer this question, the mean and standard deviations of the degree of upgrading learners’ competencies inside the Green Line area were extracted from the teachers’ point of view, and the table below illustrates this.

Table 10. Learners’ Competencies.

Rank	No.	Domain	Mean	Standard Deviation	Degree Level
1	1	Academic Efficiency	3.21	0.733	Medium
2	2	Social Efficiency	3.20	0.715	Medium
		Learner Efficiency	3.21	0.706	Medium

shows that the mean ranged between (3.20 and 3.21) and the SD ranged between (0.706 and 0.733), where academic efficiency ranked first with the highest mean (3.21) and SD (0.733), while social efficiency came in last with a mean of (3.20) and SD (0.715), and the mean of a degree was calculated as follows: raising the competencies of learners within the Green Line area from the point of view of teachers as a whole (3.21) and SD (0.706).

The mean and standard deviations of the study sample estimates were calculated on the items of each field separately, and they were as follows:

4.2.1. Domain One: Academic Efficiency

Table 11. Academic Efficiency.

Rank	No.	Item	Mean	Standard Deviation	Degree Level
1	1	Students have the will to succeed academically.	3.78	0.912	High
2	2	Students can apply what they have learned outside the school.	3.73	0.943	High
3	3	Students have the ability to succeed in competitive academic assignments.	3.72	1.038	High
4	7	Students have the ability to submit their homework in a timely manner.	3.56	1.166	Medium
5	9	Students can identify the main points and ideas in the learning material.	3.55	1.129	Medium
6	6	Students have the ability to prepare well for exams.	3.45	1.172	Medium
7	5	Students can perform the required learning tasks.	3.27	1.116	Medium
8	4	Students have the ability to deal with challenging learning content.	2.86	1.234	Medium
9	12	Students can write articles and short reports independently.	2.73	1.219	Medium
10	8	Students have the ability to plan and organize their learning materials well.	2.67	1.414	Medium
11	10	Students can find information efficiently using various search engines.	2.60	1.138	Medium
12	11	Students can assess their learning outcomes independently.	2.57	1.265	Medium
		Academic Efficiency	3.21	0.733

shows the mean and standard deviations related to academic efficiency, arranged in descending order according to the mean.

Table 11 shows that the means ranged between (2.57 and 3.78), where item no. (1) stating “students have the will to achieve academic success” came in the first place with a mean of (3.78) and SD of (0.912), while item no. (11) stating “Students can assess their learning outcomes independently”, ranked last, with a mean of (2.57) and SD of (1.265). The mean for the academic efficiency domain as a whole was (3.21) and an SD of (0.733)

4.2.2. Domain Two: Social Efficiency

Table 12. Social Efficiency.

Rank	No.	Item	Mean	Standard Deviation	Degree Level
1	16	Students express their anger and frustration without hurting others.	3.67	0.945	Medium
2	15	Students do not panic easily about impulsive colleagues.	3.66	1.071	Medium
3	24	Students have the ability to communicate non-verbally.	3.62	0.966	Medium
4	23	Students adapt to each other regardless of the differences between them.	3.60	1.079	Medium
5	17	Students actively participate in activities.	3.55	0.948	Medium
6	14	Students defend their rights and needs in an appropriate manner.	3.39	1.115	Medium
7	21	Students are able to negotiate and reach a settlement on many matters.	3.17	1.283	Medium
8	18	Students participate in discussions and make a clear contribution to the discussion topic.	2.96	1.311	Medium
9	13	Students clearly express their desires, preferences, and their behavior.	2.93	1.283	Medium
10	19	Students adapt easily and quickly.	2.72	1.336	Medium
11	20	Students express their interest in others and request information from others.	2.58	1.248	Medium
12	22	Students do not draw attention to themselves.	2.58	1.381	Medium
		Social Competence	3.20	0.715

presents the means and standard deviations related to social efficiency, arranged in descending order according to the means.

Table 12 shows that the mean ranged between (2.58 and 3.67) and the SD ranged from (0.945 to 1.381), with item no. 16 coming in first place with a mean of (3.67) and SD of (0.945), which stated that “students express their anger and frustration without harming others”; the last two items (20 and 22) came in last place, with a mean of (2.58) and SD of (1.381). The two items 20 and 22 stated “Students express their interest in others and request information from others” and “Students do not draw attention to themselves”, respectively. The mean for the domain of social competence as a whole was (3.20) and the SD was (0.715).

4.3. Results and Discussion of the Third Question

Is there a statistically significant correlation at the level (α ≥ 0.05) between the degree of teachers’ readiness to use modern technological learning spaces and the degree of raising learners’ competencies within the Green Line area?

To answer this question, Pearson’s correlation coefficient was extracted between the degree of teachers’ readiness to use modern technological learning spaces and the degree to which learners’ competencies were raised inside the Green Line area.

Table 13. Teachers’ Readiness to Use Modern Technological Learning Spaces and the Degree of Raising Learners’ Competencies.

Domain		Academic Efficiency	Social Competence	Efficiency of Learners
Belief	Correlation Coefficient R	0.875 **	0.907 **	0.913 **
	Statistical Significance	0.000	0.000	0.000
	The Number	397	397	397
Competencies	Correlation Coefficient R	0.930 **	895 **	0.935 **
	Statistical Significance	000	0.000	0.000
	The Number	397	397	497
	Correlation Coefficient R	0.922 **	0.918 **	0.942 **
Teachers’ Readiness	Statistical Significance	000	000	000
	The Number	397	397	397

** Statistically significant at the significance level (0.01).

shows that there is a positive, statistically significant relationship between the degree of teachers’ readiness to use modern technological learning spaces and the degree of raising learners’ competencies inside the Green Line area.

5. Discussion

In the twenty-first century, the e-learning space strategy has become widespread in the majority of the world’s countries. This study explained how teachers realize the importance of using technological learning spaces since the shift toward different types of technology has become a clear reality in the educational field. Those teachers also understand the importance of integrating technology into the teaching and learning process, and this involves their acceptance of this fact. Thus, this reflects positively on their beliefs.

Through the analysis of the data, unfortunately, the results point out that the competencies are ranked last, with a mean of (2.84) and a standard deviation of (0.756). This indicates the weakness of training programs in preparing teachers to use learning spaces, which is one of the modern educational fields that entered the educational field recently. This confirms the need for designing and providing training and professional development programs that deal with the skills of technological learning spaces.

The result differs from the study of Hinnawi and Najm [29] in Palestine, which indicated that the degree of readiness of primary school teachers at public schools to employ technological learning spaces was high. It used a sample of teachers from basic stage schools who did not need a lot of technological skills, while the current study used a sample from high secondary school teachers (397) who needed a high level of skills in technological learning spaces.

The result also explained the fact that teachers had obtained training and professional development programs that contributed significantly to the formation of positive beliefs about employing the skills of technological learning spaces, and this was evident through the results of the current study. University courses also work on developing positive attitudes and beliefs toward employing technology in the teaching and learning process, as faculties of education in various countries realize the importance of attitudes in the behavioral patterns of teachers, which makes them focus on changing the negative attitudes of male and female teachers. This study agreed with Ghavifekr and Rosdy’s [24] study, which focused on the importance of teacher technology training.

This result differs from the study of Hinnawi and Najm [29], which indicated that teachers’ competencies and attitudes were high. It can be said that the result of the study by Hinnawi and Najm [29] agreed with the educational literature that dealt with the attitudes and competencies of electronic teachers. However, the current study dealt with the skills of technological learning spaces, which was a new concept that had not been adequately addressed in the educational principles due to the novelty of this concept and the lack of sufficient knowledge of teachers about the skills of learning spaces, which led to the level of their competencies in those skills being average.

The findings explained that teachers have sufficient knowledge about the important role of technology in raising the outcomes of the teaching and learning process, whether in terms of designing curricula or creating an appropriate learning process and school environment that enables teachers to employ technology optimally in order to raise the quality of the teaching and learning process. The mean of the beliefs is (2.96) and the standard deviation is (0.793). The findings of this study are consistent with the findings of Ghavifekr and Rosdy [24], Hinnawi and Najm [29], and Marta [3].

Indeed, the use of technology of all kinds develops the concept of independence among the students and makes the learning process centered on the students and not the teacher, as technology provides the necessary means for learners to rely on themselves in obtaining the learning content, and this opens up new horizons for them in raising their level of efficiency academy. In addition, the curricula focus in most of their aspects on raising the academic efficiency of students, and this is clearly evident in the results of the current study, as teachers and the educational system, in general, believe that learners’ competence is the main measure of the quality of education, and this is what makes them focus on this aspect.

The social competence requires communication and interaction with others in a large way, and this is what e-learning environments do not allow, which limits the social interaction between the teacher and students and between the students themselves, and does not develop social competencies. The mean of social competence as a whole was (3.20) and the SD was (0.715). In addition, the use of technology in education encourages students to be independent learners, which makes them self-reliant in their various academic tasks. It also weakens their level of communication with colleagues and peers, who in turn provide social interaction experiences that develop this aspect among students. This study’s findings are consistent with those of Marta [3].

The teachers’ use of modern technological learning spaces is consistent with students’ interests and desire to learn. In addition, the increase in the effectiveness of teachers in employing modern technological learning spaces means an increase in their ability to provide learning content using multimedia, videos, and social media. Unfortunately, teachers do not pay attention to videos and social media where these tools occupied the last rank, with a mean of 2.52 and SD of 1.072. Students also prefer accessing learning content using technology, as this allows them to view that content either on their mobile phones or laptops whenever they want. This positively affects their academic competencies in particular, as the learners are more willing to obtain the learning content if they are able to access it. Students at present have dealt with technological means since their early childhood and the daily use of technology. The provision of learning experiences through these means will reflect positively on their academic competencies. This proves the existence of a positive correlation between the degree of a teacher’s readiness to use technological learning spaces and the academic competence of the student. In addition, teachers’ employment of technology provides students with opportunities for virtual social interaction, which is based on sharing self-experiences and exchanging information and knowledge with others without the need to reveal the identity of the person conducting the communication. This confirms that students can talk about various aspects of their lives and receive advice and experience from others, which develops their social competence.

6. Conclusions

The study concludes that teachers’ readiness to use technological learning spaces is not high, and they should be motivated to improve themselves in this field. Therefore, their competencies in using technology are very important for learners as well as teachers. Moreover, the beliefs of the teachers regarding using technology were mixed. The study recommends the following: (i) providing training courses and professional development programs that develop the teachers’ readiness to use modern technological learning spaces; (ii) linking aspects of the use of modern technological learning spaces with the personal aspects of students, such as increasing the level of their academic self-concept and academic self-efficacy; (iii) and conducting future studies dealing with the degree of teachers’ readiness to use modern technological learning spaces with the behavioral and emotional variables of students.

This study suggests some future studies that pertain to modern technological learning spaces, such as the role of parents in technological learning spaces, the impact of COVID-19 on modern technological learning spaces, and the relationship between modern technological learning spaces and kindergartens.

7. Limitations

The study limited itself to Green Line schools in Palestine due to the difficulties of moving from one place to another. So, we did not enlarge the study. The coronavirus contributed to the use of Google Forms instead of face-to-face meetings. Time constraints were also one of the limitations of this study since it took a long time to collect and analyze the data. This was in addition to the funding limitations, which cost a lot and limited our research.