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Research Article
Open Access Peer-reviewed

Levels of Technostress Resulting from Online Learning among Language Teachers in Palestine during Covid-19 Pandemic

Amnah Jameel Abo Mokh, Shaheen Jameel Shayeb, Amjad Badah, Islam Asim Ismail , YaffaJumah Ahmed, Laila K. A. Dawoud, Hanan Essam Ayoub
American Journal of Educational Research. 2021, 9(5), 243-254. DOI: 10.12691/education-9-5-1
Received March 24, 2021; Revised May 02, 2021; Accepted May 09, 2021

Abstract

This study examines the effect of online learning on technostress levels among language teachers in Palestine during the Covid-19 pandemic. The research method that is used is quantitative with a database of research respondents. The researchers used a scale and validated the instrument carefully to measure the technostress levels among language teachers in Palestine. The collected data were analyzed using (SPSS) to provide answers to the questions of the study. The sample consisted of 101 Palestinian English language teachers who teach at private and public schools. Results indicate that the level of technostress among Palestinian English language teachers is moderate; this shows that teachers seem to be comfortable with both styles of teaching; face to face and virtually. Other promising finding is that there were no statistically significant differences in the technical stress levels of Palestinian English language teachers in terms of gender, length of service, educational level, and levels of frequent internet use. Moreover, the results also demonstrate that technical field sores the highest rate of technostress. Technological causes related to technology ranked first in terms of technical stress levels. The researchers recommend the Palestinian Ministry of Education to enhance teachers’ proficiency in using technology, specifically integrating technology into the educational process in the long run in Palestine.

1. Introduction

This research constitutes a relatively new area that has emerged from using technology in the learning process. The fast development in using technology and its ubiquity has made teachers heavily rely on technology in their teaching-style. Teachers are extensively using technology for automating the learning process and promoting their teaching quality. Technology is widely used by all parties of the learning process i.e. administration, teachers, parents, and students 1.

Technology has proved itself to streamline education for 21st-century students through different mobile applications. Not surprisingly, teachers exponentially use technology in their teaching for its multi-benefits. Technology can decrease paperwork, bring transparency, and facilitate distance learning. Therefore, government incentives aimed at using technology to ensure the continuation of the learning process during the Covid-19 crisis 2.

Despite the fact there are many benefits of technology, there has been an ongoing argument in understanding the negative sides of technology for end-users. Teachers are suffering from what is called “technostress”. Studying technostress that is resulting from online learning during Covid-19 is now a mature field that is being spun out to be investigated. This term has been studied in the literature for years by many researchers. It can be best defined as “inability to cope with new technology.” 3, 4, 5, 6.

A careful review of previous work, there is a dearth of empirical pieces of research that have dealt with the prevalence of technostress among language teachers. Technostress can lead teachers to a decrease in their productivity because they are not used to using technology in their teaching style. This paper proposes that teachers are facing many problems with dealing with technological apps in their teaching; therefore, the researchers intend to study the prevalence levels of technostress among English language teachers.

Based on the foregoing, the researchers use a scale and validate the instrument carefully to measure the technostress levels among English language teachers in Palestine. This paper aims at addressing the following main questions:

1. What is the level of technostress among Palestinian English language teachers?

2. What is the level of technostress among Palestinian English language teachers in terms of teaching and learning process-oriented?

3. What is the level of technostress among Palestinian English language teachers in terms of profession-oriented?

4. What is the level of technostress among Palestinian English language teachers in terms of Technical Issue Oriented?

5. What is the level of technostress among Palestinian English language teachers in terms of Social Oriented?

2. Literature Review

2.1. Advantages of Technology

Studies on technology are well documented, it is also well acknowledged that the world has been witnessing a technological revolution in all fields of life, one of which is education. It is very essential to shed light on this field particularly in the light of sudden changes such as the diffusion of the global virus of COVID-19. This situation requires physical distance to avoid the possible dangers of the virus. Technology is a wise solution that bridges the gaps in education. Fortunately, technology is available and students can use technological information everywhere and at any time 7.

Many studies have been conducted on the advantages of online learning. Shaba 8 indicated that learning through technology affected students positively and increased the chances to develop their levels of learning.

Evans and Fan 9 pointed out three advantages of investing in technology in the educational process. They are presented as follow:

1- The flexibility of students' learning in terms of their choices and the place of learning.

2- Enhancing the self-learning of students, they can learn whenever they want during the organization and management of their time.

3- Students can learn in a way that suits their pace without being influenced by the speed of others' learning.

Fuller 10 has confirmed the advantages of learning through E-tools, one of which is that online learning does not cost like traditional learning. It is cheaper than face-to-face learning as well as how online learning decreases the danger of cars' gases on the environment. After the pandemic has been hitting the educational system, the instructional orientations toward making the classes live 11.

2.2. Disadvantages of Technology

Many authors in literature have discussed disadvantages of technology. The researchers found in the literature that teachers face difficulties in employing teaching strategies and methods in e-learning, especially in distance learning through digital media such as zoom. Moreover, some teachers do not have sufficient technological knowledge 12, 13.

Some researchers believe that teaching with technology is dehumanizing. This means that some teachers deal with their students as they are machines or robots during the learning process; without considering human basis 14.

The authors bring some information about the background of the problem. It is found in the literature that using the internet is on the rise, especially in the teaching fields, whether the user is a teacher, student, or family. As a result, this constitutes to become a source of concern for users that their privacy is breached and making them feel unsafe. So, teachers' and parents' concern is increasing towards students, especially towards young students, whose privacy is compromised in technology 14.

As has been previously reported in the literature, technology has negative effects on the health and physical effects of the body, especially on those who use technology constantly. In general, those effects include frequent eye strain, headache, blood pressure, back pain, stomach problems, irritability, and heart attacks 15.

Some studies indicate that persons who work constantly for long hours in front of the computer will cause stress, burnout, and a feeling tired. As a result, this reduces performance quality, job satisfaction, and continuance commitment 16, 17, 18.

Saal and his colleagues’ study 19 indicates that a teacher can enhance social interaction and communication between himself and with his students, however, the opposite is true for students. Saals' study has shown that students feel bored about the lesson with technology because of the teacher who manages the technological tool. This teacher's control will lead to a disruption in communication between students and their teacher. In another study 20, the absence of social communication between teacher and student can lead to many students deciding not to continue learning. As a survey of 50% of academic students in Pakistan who saw their unwillingness to continue, the survey also showed 78.6% of students felt that face-to-face communication with their teacher was important for effective learning that lacks a distance learning status.

The results of Hornaes found that technology has negative effects on student’s self-efficacy. Also, results showed that few men stated that technology has negatively affected their self-efficacy, while a third of women showed that technology affects their self-efficacy 21.

Teachers take time to become familiar with computer hardware and software. Because technology producers are constantly upgrading their products, schools are always getting new computer hardware and software. This is a recurring problem in schools, and they cannot relate between the new product and teaching goals. Teachers point out that even if they become accustomed to computers and software in their schools, teaching with them becomes less efficient than teaching with traditional methods 22.

The weakness of the infrastructure of the internet networks, the lack of technical support for any malfunction, as well as the specialists in the technological side of everything related to digital media and platforms such as Zoom and others. Teachers and students suffer from this dilemma, especially when the network is interrupted for a long time and the great pressure on the internet due to the intense and continuous use of teachers and students at the same time, as well as power cuts, or when facing any technical or technical problem in the digital platform 12.

Some teachers do not have the technical knowledge that enables them to deal with e-learning smoothly and easily, and to manage distance learning, for example, with all its requirements 12, 23.

2.3. What is Technostress?

Current studies examine the effect of technology on our lives. Recently, technology has become an essential pillar of 21st-century careers. Previous studies show that 21st-century employees are massively using technology in their work. Some researchers believe that workers are available to communicate and work all the time due to modern technology 17. Subsequently, stress will increase among individuals while the level of performance will decrease.

In 1984, technostress was widely known as a disease caused by an individual's inability to deal with technology 24. Will and Rosen defined technostress as "any negative effect on attitudes, thoughts, behaviors, or body physiology caused directly or indirectly by technology" ( 25, p. 5).

Recently one of the most prominent definitions of technostress has been developed as "user stress as a result of multitasking in the application and continuous communication, repeated information, repeated system improvements and the resulting uncertainty, continuous re-learning and the resulting functional insecurity and technical problems associated with the ICT use organization" (Tarafdar et al., pp. 304-305). However, one of the most accepted and widely used definitions of technostress in the literature states that "phenomenon of technostress experienced by end-users in organizations as a result of their use of information and communication technologies" (Ragu-Nathan et al. 16, pp. 417-418).

The authors bring some information about the background of the term. Some authors suggested that technostress is related to some terms like anxiety, mental exhaustion, skepticism, and ineffectiveness that is caused by the inability to focus on the use of ICTs or their future use 26. The demands of work that can provoke technostress are called techno-stressors or technostress creators 27.

Concerning technostress levels, a thorough investigation in the literature would reveal that little research has been conducted on this area. It can be argued that researchers have been more interested in exploring this relatively new emerging phenomenon. However, Çoklar and his colleagues developed what is called “Teachers’ Techno-stress Levels Defining Scale (TTLDS)”to define teachers’ technostress levels 28. Scale development was the main goal of the study that tried to find a way for measuring teachers’ technostress level. The authors argue that their study is important as “literature review didn’t present any measurement instrument that can provide a multi-perspective on the reasons of techno-stress among teachers' 28. The authors go on to clearly say that their study is a “scale development” one.

The study targeted 395 teachers where they were asked to respond to a 28-item questionnaire with five-level Likert items. The items fall into five main categories as follows: "Learning-Teaching Process Oriented", "Profession Oriented", "Technical Issue Oriented, "Personal Oriented” and "Social Oriented” 28. The study ends up encouraging researchers who will investigate teachers’ technostress to use that scale.

2.4. Causes of Technostress

Over time, an extensive literature has developed on the causes of technostress. Technostress' causes are classified by researchers into several classifications, the most important of which is the Meyer 29 classification. Meyer argues that these are the main causes of technostress a) functional characteristics b) organizational and c) personal characteristics of ICT users 30.

A series of recent studies have examined other causes of technostress. The researchers found the following to be the possible causes of technostress a) an overload of information: due to the large number of sources that provide workers with large amounts of information, this may result in a feeling of inability to know and control this information, which causes a feeling of burden 31; b) due to the availability of information and communication technology intake of smartphones and devices tablets, computers, and internet connectivity are now available at any time and place. This fact reinforces the expectation that continuous communication with employees and their response to the requests of officials and operators without interruption 32; c) the intensity of remote work 33; (d) frequent interruptions during work due to various disturbances 34; e) receiving many emails, and the low quality of email messages 35.

The majority of previous literature adopts the classification of Tarafdar and his colleagues. The invasion of technology for the users’ lives, lack of respect for their privacy, forcing employees to work more and faster, and changing the pattern of work. Admittedly, technology users feel inadequate due to technological complexity. The loss of security sense and the fear of being replaced by those who are more proficient in using technology than them are stressing the low-skilled employees 3.

Previous research has shown that technostress causes are associated with behavioral and psychological stress outcomes 16, 17, 36. Stress occurs through a virtual process where environmental demands go beyond individual resources. In this process, stress refers to psychological and behavioral responses to stress in the environment of the workplace.

Joo, Lim, and Kim show that TPACK and school support had significant effects on technostress. TPACK refers to technological-pedagogical and content knowledge Ozgur 37. The TPACK theory simply refers to the skills that teachers should have in teaching their students. These skills include the ability to teach students a subject effectively using technology.

2.5. Factors that may Contribute to Alleviating the Severity of Technostress and Their Negative Effects among Lecturers and Teachers
2.5.1. Computer Self-efficacy

A self-effective computer refers to the general beliefs of individuals in their ability to perform any task 38. The theory of self-efficiency states that an individual's attitude towards his or her competence in performing a particular task affects emotional response (including stress, anxiety, and feeling of overburdened) and actions 39. Computer self-effectiveness is defined on a self-foundation basis that shows a person's confidence or attitude to their ability to use technologies 40.

Teachers’ self-competence beliefs regarding their ability to use certain technologies are a very important factor in shaping their attitudes to technologies and the way teachers integrate and use technologies in teaching 41, 42. The results of previous studies indicate that computer high self-efficiency has contributed to solving difficulties and mitigating the negative effects of computer technology 43, 44. Besides, if teachers are more self-sufficient in technology integration, it may mean that teachers have a higher TPACK 45, 46. Therefore, this study can assume that working to strengthen Computer Self-efficacy effects among lecturers and teachers may contribute to alleviating the severity of technostress and their negative effects on them.


2.5.2. TPACK Framework

Shulman 47 developed the TPACK framework to provide qualified teachers with educational content knowledge (PCK) that combines content knowledge (CK) and pedagogical knowledge (PK), to design and organize curricula that meet students' needs and their different interests. With the arrival of the information age, the ability of teachers in the educational uses of technology was one of the key elements of educational innovation 48. Koehler and Mishra 49 proposed additional knowledge arising from the synthesis of PK, CK, and technological knowledge (TK) as technological content knowledge (TCK), technological pedagogical knowledge (TPK), and technological pedagogical content knowledge (TPCK/TPACK).

Teachers must have comprehensive knowledge and skills to adapt to educational technology. Teachers' lack of TPACK-rated knowledge is one of the main constraints on teachers' technological integration. Teachers with comprehensive knowledge and skills need to adapt educational technology in the design and organization of curricula in effective ways 50. The absence of TPACK has been identified as one of the main barriers to technological integration 51, 52.

Studies indicate that there is a negative relationship between the TPACK and the technostress of teachers regarding computer use. Research has indicated that the high level of TPACK teachers has reduced teacher training concerning computer use 53.


2.5.3. School Support

Support from the school environment is described as the main factor for promoting teachers' intention to use technology 54, 55, 56. Therefore, a strong infrastructure and pedagogical technological support must be provided and established to facilitate the use of e-learning technology. School support is also shown through mutual assistance, collaboration, psychological and knowledge support, and fellow teacher administrative support 57, 58.

3. Research Methodology

This study applied the descriptive-analytical method. Based on Brown & Rodgers ( 59: 117) Brown and Rodgers ( 59: 117) definition, a descriptive study is "a research that describes group characteristics or behaviors in numerical terms." To achieve this, the design was quantitative design to explore the levels of technostress among Palestinian EFL teachers in the scholastic year 2020\2021. This study has adopted a 28-item questionnaire. The questionnaire was distributed to teachers online via google form because of Covid 19 lockdown.

3.1. Instrument

This study adopted a 28-item questionnaire developed by Turkish researchers. It is a five-Lickert questionnaire that includes five domains to be investigated: teaching and learning process-oriented, profession-oriented, technical issues-oriented, personal-oriented, and social-oriented.

To achieve the objectives of the study, the researchers used a questionnaire consisted of two sections; the first focused on the demographic profile such as gender, experience, study level, and Frequency of using the internet. The scores of responses to each item were calculated according to a five-point Likert scale, in which Strongly Totally Agree =5 points, Agree =4 points, Undecided = 3, Disagree = 2 points, and Totally Disagree = 1 point.

3.2. Validity

The Turkish experts have approved the validity of the original questionnaire. In terms of the questionnaire's content and face validity for this study, a panel of experts comprised of two assistant professors of English language and literature and two non-native EFL teachers with a master's degree in ELT was asked to assess its comprehensiveness acceptability, and clarity. Two items were deleted from the questionnaire. The researchers acted after receiving input from these four experts. Cronbach alpha reached 0.96.

To ensure the validity of the questionnaires, it was rated by a jury of experts in the field of TEFL and Education at the Faculties of Education and Arts at the Palestinian universities. The respondents’ comments and the jury's suggestions were taken into consideration to modify and improve the questionnaire's content and wordings by omitting, adding, or rephrasing items bringing the number of items from 30 to 28 the final drafts.

3.3. Reliability of the Questionnaire

The reliability of the questionnaire was calculated through the Cronbach Alpha formula. Cronbach Alpha coefficient was (0.956) for the questionnaire. This value is excellent and acceptable for the study.

3.4. Sample

The participants of the study were the Palestinian English language teachers in the academic year 2020/2021. The questionnaire was distributed via google form in all educational groups on social websites including Facebook and WhatsApp. Only 101 questionnaires were answered. Male teachers outnumber females. The number of male language teachers who responded was 85, constituting 84.2%, while the number of female language teachers responding to was 16, constituting 15.8%.

The sample consisted of 101 Palestinian English language teachers in Palestine in the academic year 2021/2012 as shown in Table 1.

3.5. Data Analysis

The data collected were analyzed using (SPSS) to provide answers to the questions of the study. Means, frequencies, standard deviations, t-tests for Independent Samples, and One-Way Analysis of Variance (ANOVA). To analyze the findings, the researchers used the following scale to represent the estimation level of students' responses.

4.5 4.50 and more:Very High

4 – 4.49:High

3-50–3.99:Moderate

3- 3- 3.49 Low

less than 3: Very Low

4. Results and Discussion

This section describes the data obtained concerning the study questions. The results related to each question were presented in tables, where means and standard deviations are shown. The researchers interpret such findings based on their understanding of the Palestinian contexts.

4.1. Results Related to Study Questions
1-Results related to the First Question

Q 1: What is the level of technostress among Palestinian English language teachers?

Table 2 demonstrates that the level of technostress among Palestinian English language teachers is moderate (3.08). Interestingly, the technical factors related to the use of technology in the teaching process come in the first place with an average of (3.53). However, the personal factors constitute the least factors that lead to technostress with an average of (2.65).

Such results are not surprising for the researcher for many reasons. Most importantly, it can be argued that the Palestinian English language teachers rarely merge technology in teaching in the traditional face-to-face mode. With the rapid shift to E-learning due to the spread of the COVID-19 pandemic in Palestine, teachers have been forced to instruct online using different computer-mediated applications. Such movement has noticeably affected the English teachers’ performance when adopting e-learning.


2-Results related to the Second Question.

What is the level of technostress among Palestinian English language teachers in terms of teaching and learning process-oriented?

To answer this question, the researchers used means and standard deviations, and estimation levels are calculated as shown in Table 3.

An examination of Table 3 demonstrates that the total degree for the level of technostress among Palestinian English language teachers in terms of the teaching-learning process is low (3.00). Questionnaire statement 3, which is about forcing teachers to use the internet in the educational process, comes in the first place with an average of (3.49). This result reveals that English teachers still consider e-learning education an obligatory process at least at the time of data collection. It is not an option at all, especially in the presence of the COVID-19 pandemic.

However, questionnaire statement 7 which is about the technology‘s role in blunting students’ research skills got the lowest average (2.74). Undeniably, students enjoy learning through technology-based applications. Thus, technology does not affect students’ willingness to search for a given piece of information. On the contrary, the researchers believe that technology positively enhances students’ research skills.


3-Results related to the Third Question.

What is the level of technostress among Palestinian English language teachers in terms of profession-oriented?

To answer this question, the researchers used means and standard deviations, and estimation levels are calculated as shown in Table 4.

Table 4 demonstrates that the total degree for the level of technostress among Palestinian English language teachers in terms of profession-oriented is very low (2.89). This might be ascribed to the fact that English language teachers are forced to stay at their jobs regardless of obstacles. They have to find coping strategies to meet the emerging challenges, particularly e-learning. The highest mean was given to the questionnaire statement 13 where teachers think technology increased their workload. This important finding suggests e-learning has negatively affected the teachers. Teachers are required to prepare digital materials, develop their technological competencies and further deliver the intended outcomes online Such tasks are considered an additional burden on teachers

On the other hand, teachers are less worried about losing their prestige when compared with the newer teacher who can use technology better (questionnaire statement 12). It seems that English language teachers are self-confident and do not care about the new teacher who is more capable of using technology.


4-Results related to the Fourth Question.

What is the level of technostress among Palestinian English language teachers in terms of Technical Issue Oriented?

To answer this question, the researchers used means and standard deviations, and estimation levels are calculated as shown in Table 5.

A thorough look at the Table 5 shows that the total degree for the level of technostress among Palestinian English language teachers in terms of technical issues is moderate (3.53).It is clear that English language teachers are more worried when it comes to dealing with technological information like passwords and account numbers (questionnaire statement 16). As stated earlier, this is the first time for English language teachers to shift to e-learning, where technology has constituted the main barrier for them. Therefore, it is normal that English language teaching experience such difficulties.

English language teachers, on the other hand, are less worried when it comes to virus infection (i.e. questionnaire statement 14). Such a result could be attributed to the fact that teachers are not familiar with the technical aspects of viruses including their impact.


5-Results related to the Fifth Question.

What is the level of technostress among Palestinian English language teachers in terms of Personal Oriented?

To answer this question, the researchers used means and standard deviations, and estimation levels are calculated as shown in Table 6.

Table 6 shows that the total degree for the level of technostress among Palestinian English language teachers in terms of personal oriented factors is very low (2.65). English language teachers are more worried about technology use due to the necessity to keep up with constantly developing technology (questionnaire statement 21). On the contrary, they are less worried about their learning ability to use technology (questionnaire statement 21) with an average of (2.41).

Overall, the very low level of technostress related to this domain could be attributed to the fact that the Palestinian teachers constantly develop their skills in different fields. Besides, they easily manage the challenges they face, especially if such challenges are personal ones.


6-Results related to the sixth Question.

What is the level of technostress among Palestinian English language teachers in terms of Social Oriented?

To answer this question, the researchers used means and standard deviations, and estimation levels are calculated as shown in Table 7.

Table 7 shows that the total degree for the level of technostress among Palestinian English language teachers in terms of social-oriented factors is low (3.33). Respondents believe that the social interaction between everyone in the educational processes is damaged due to technology use (questionnaire statement 26). Undeniably, e-learning not only affected the intended learning outcomes but also it has negatively decreased the interactive side of the educational process. Respondents, on the other hand, are less worried about having problems with their colleagues about technology use (questionnaire statement 27) with an average of (2.76). Being in a formal environment, teachers are supposed to act professionally.

4.2. Results Related to Study Hypothesis

1. Results related to the first hypotheses, which is: There are no significant differences in the levels of technostress among Palestinian English language teachers in terms of gender.

To answer the hypotheses, t-tests for Independent Samples, was used and the following table shows the results:

Table 8 shows that there are no statistically significant differences in the levels of technostress among Palestinian English language teachers in terms of gender. The significant value was (0.689) which is more than (0.05). Also, no statistically significant differences in the five domains.

2. Results Related to Second Hypotheses Which is: There are no significant differences in the levels of technostress among Palestinian English language teachers in terms of length of service.

To answer the hypothesis, the One Way ANOVA test was used and the following tables show the results:

Table 9 shows that there are differences in means of the levels of the length of service. To show these differences, the One Way ANOVA test was used and Table 10 shows the results:

Table 11 shows that there are no statistically significant differences in the levels of technostress among Palestinian English language teachers in terms of length of service. The significant value was (0.439) which is more than (0.05).Also, no statistically significant differences in the five domains.

3. Results Related to Third Hypotheses Which is: There are no significant differences in the levels of technostress among Palestinian English language teachers in terms of the level of education.

To answer the hypothesis, the One-Way ANOVA test was used and the following tables show the results:

Table 11 shows that there are differences in means of the levels of the length level of education. To show these differences, the One Way ANOVA test was used and Table 12 shows the results

Table 12 shows that there are no statistically significant differences in the levels of technostress among Palestinian English language teachers in terms of the level of education. The significant value was (0.978) which is more than (0.05). Also, no statistically significant differences in the five domains.

4. Results Related to Third Hypotheses which is: There are no significant differences in the levels of technostress among Palestinian English language teachers in terms ofthe level of internet use frequently.

To answer the hypothesis, the One Way ANOVA test was used and the following tables show the results:

  • Table 13. Frequencies, Means and Standards Deviations of the levels of technostress among Palestinian English language teachers in terms of the level of internet use frequently for the total degree

Table 13 shows that there are differences in means of the levels of the level of internet use frequently. To show these differences, the One Way ANOVA test was used and Table 14 shows the results

  • Table 14. Results of One Way ANOVA of the levels of technostress among Palestinian English language teachers in terms of the level of internet use frequently

Table 14 shows that there are no statistically significant differences in the levels of technostress among Palestinian English language teachers in terms of the level of internet use frequently. The significant value was (0.053) which is more than (0.05). Also, no statistically significant differences in the five domains.

5. Conclusion and Recommendation

In light of the present study results, it is clear that EFL teachers' technical skills are poor. The researchers recommended that the competent Palestinian authorities develop technical courses in line with this century's technological development and let teachers be ready for any inconvenience. They also recommended providing teachers with laptops and internet service to facilitate their mission. Finally, regarding recommendations for future studies, to study the technostress levels on Palestinian teachers of other subjects such as science and mathematics. The coming researchers can study the relationship between teachers' technostress levels and their motivations toward online teaching.

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[18]  Mahapatra, M. &Pati, S. P. (2018). Technostress creators and burnout a job demands-resources perspective. In Aubert, B., Compeau, D. &Tarafdar, M. (Eds.) Proceedings of the 2018 ACM SIGMIS conference on computers and people research, (pp. 70–77). New York, USA: Association for Computing Machinery.
In article      View Article  PubMed
 
[19]  Saal, P. E., van Ryneveld, L., & Graham, M. A. (2019). The Relationship between using Information and Communication Technology in Education and the Mathematics Achievement of Students. International Journal of Instruction, 12(3), 405-424.
In article      View Article
 
[20]  Adnan, M. & Anwar, A. (2020). Online learning amid the COVID-19 pandemic: Students perspectives. Journal of Pedagogical Research, 1(2), 45-51.
In article      View Article
 
[21]  Hornaes, H. P., &Royrvik, O. (2000). Aptitude, gender, and computer algebra systems. Journal of Engineering Education, 89(3), 323.
In article      View Article
 
[22]  Dogan, T., & Ilhan, V. (2006). In Annual Proceedings of Selected Research and Development [and] Practice Papers Presented at the National Convention of the Association for Educational Communications. In Technology Explosion and Its Impact on Education. https://files.eric.ed.gov/fulltext/ED470179.pdf.
In article      
 
[23]  Uluyol, C. &Sahin, S. (2016). Elementary School Teachers’ ICT Use in the Classroom and Their Motivators for Using ICT. British Journal of Educational Technology, 47(1), PP 65-75.
In article      View Article
 
[24]  Brod, C. (1984). Technostress: The human cost of the computer revolution. Reading, Mass.: Addison-Wesley.
In article      
 
[25]  Weil, M.M., & Rosen, L.D. (1997). TechnoStress: Coping with Technology @Work @Home @Play.
In article      
 
[26]  Salanova, Cifre & Nogareda, (2007). Salanova, M., Llorens, S., & Ventura, M. (2014). Technostress: The Dark Side of Technologies. Technostress among users of information and communication technologies, International Journal of Psychology, 48:3, 422-436.
In article      View Article
 
[27]  Molino, M., Ingusci, E., Signore, F., Manuti, A., Giancaspro, M. L., Russo, V., ... & Cortese, C. G. (2020). Wellbeing Costs of Technology use during Covid-19 remote working: An investigation using the Italian translation of the technostress creators scale. Sustainability, 12(15), 591.
In article      View Article
 
[28]  Çoklar, Efilti, &Sahin, (2017). Çoklar, A., Efilti, E., &Sahin, Y. (2017). Defining Teachers’ Technostress Levels: A Scale Development. Journal of Education and Practice, 8, 28-41.
In article      
 
[29]  Meyer, B. (2012). Mediation and the genesis of presence. Towards a material approach to religion.
In article      
 
[30]  Oladosu, K. K., Alasan, N. J., Ibironke, E. S., Ajani, H. A., &Jimoh, T. A. (2020). Learning with Smart Devices: Influence of Technostress on Undergraduate Students' Learning at University of Ilorin, Nigeria. International Journal of Education and Development using Information and Communication Technology, 16(2), 40-47.‏
In article      
 
[31]  Derks, D., van Mierlo, H., & Schmitz, E. B. (2014). A diary study on work-related smartphone use, psychological detachment and exhaustion: examining the role of the perceived segmentation norm. Journal of occupational health psychology, 19(1), 74.
In article      View Article  PubMed
 
[32]  Ghislieri, C., Emanuel, F., Molino, M., Cortese, C. G., & Colombo, L. (2017). New technologies smart, or harm work-family boundaries management? Gender differences in conflict and enrichment using the JD-R theory. Frontiers in psychology, 8, 1070.‏
In article      View Article  PubMed
 
[33]  Suh, A., & Lee, J. (2017). Understanding teleworkers’ technostress and its influence on job satisfaction. Internet Research.
In article      View Article
 
[34]  Ninaus, K., Diehl, S., Terlutter, R., Chan, K., & Huang, A. (2015). Benefits and stressors – Perceived effects of ICT use on employee health and work stress: An exploratory study from Austria and Hong Kong. International Journal of Qualitative Studies on Health and Well-being, 10(1), 28838.
In article      View Article  PubMed
 
[35]  Brown, R., Duck, J., &Jimmieson, N. (2014). E-mail in the workplace: The role of stress appraisals and normative response pressure in the relationship between e-mail stressors and employee strain. International Journal of Stress Management, 21(4), 325.
In article      View Article
 
[36]  Al-Fudail, M., &Mellar, H. (2008). Investigating teacher stress when using technology. Computers & Education.
In article      View Article
 
[37]  Özgür, H. (2020). Relationships between teachers’ technostress, technological pedagogical content knowledge (TPACK), school support and demographic variables: A structural equation modeling. Computers in Human Behavior, 112, 106468.
In article      View Article
 
[38]  Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986, 23-28.‏
In article      
 
[39]  Bandura, A. (1997). The anatomy of stages of change. American journal of health promotion: AJHP, 12(1), 8-1.
In article      View Article  PubMed
 
[40]  Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-21.
In article      View Article
 
[41]  Blonder, R., Jonatan, M., Bar-Dov, Z., Benny, N., Rap, S., &Sakhnini, S. (2013). Can You Tube it? Providing chemistry teachers with technological tools and enhancing their self-efficacy beliefs. Chemistry Education Research and Practice, 14(3), 269-285.
In article      View Article
 
[42]  Yes¸ ilyurt, E., Ulas¸, A. H., & Akan, D. (2016). Teacher self-efficacy, academic self-efficacy, and computer self-efficacy as predictors of attitude toward applying computer-supported education. Computers in Human Behavior, 64, 591-601.
In article      View Article
 
[43]  Paul, N., & Glassman, M. (2017). Relationship between internet self-efficacy and internet anxiety: A nuanced approach to understanding the connection. Australasian Journal of Educational Technology, 33(4).
In article      View Article
 
[44]  Shu, Q., Tu, Q., & Wang, K. (2011). The impact of computer self-efficacy and technology dependence on computer-related technostress: A social cognitive theory perspective. International Journal of Human-Computer Interaction, 27(10), 923-939.
In article      View Article
 
[45]  Lo´pez-Vargas, O., Duarte-Sua´rez, L., & Iba´n˜ez-Iba´n˜ez, J. (2017). Teacher’s computer self-efficacy and its relationship with cognitive style and TPACK. Improving Schools, 20(3), 264-277
In article      View Article
 
[46]  Semiz, K., & Ince, M. L. (2012). Pre-service physical education teachers' technological pedagogical content knowledge, technology integration self-efficacy and instructional technology outcome expectations. Australasian Journal of Educational Technology, 28(7).
In article      View Article
 
[47]  Shulman, L.S. (1986). Those Who Understand: Knowledge Growth in Teaching. Educational Researcher, 15, 14-4.
In article      View Article
 
[48]  Pineida, F. O. (2011). Competencies for the 21st century: integrating ICT to life, school and economic development. Procedia-Social and Behavioral Sciences, 28, 54-57.
In article      View Article
 
[49]  Koehler, M. J., & Mishra, P. (2005). What happens when teachers design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2), 131-152.
In article      View Article
 
[50]  Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPACK) the development and validation of an assessment instrument for preservice teachers. Journal of research on Technology in Education, 42(2), 123-149.
In article      View Article
 
[51]  Blackwell, C. K., Lauricella, A. R., & Wartella, E. (2016). The influence of TPACK contextual factors on early childhood educators’ tablet computer use. Computers & Education, 98, 57-69.
In article      View Article
 
[52]  Koh, J. H. L., Chai, C. S., & Lim, W. Y. (2017). Teacher professional development for TPACK-21CL: Effects on teacher ICT integration and student outcomes. Journal of Educational Computing Research, 55(2), 172-196.
In article      View Article
 
[53]  Joo, Y. J., Lim, K. Y., & Kim, N. H. (2016). The effects of secondary teachers’ technostress on the intention to use technology in South Korea. Computers & Education, 95, 114-122.
In article      View Article
 
[54]  Drossel, K., Eickelmann, B., & Gerick, J. (2017). Predictors of teachers’ use of ICT in school–the relevance of school characteristics, teachers’ attitudes and teacher collaboration. Education and Information Technologies, 22(2), 551-573.
In article      View Article
 
[55]  Eickelmann, B., Gerick, J., & Koop, C. (2017). ICT use in mathematics lessons and the mathematics achievement of secondary school students by international comparison: Which role do school level factors play?.Education and Information Technologies, 22(4), 1527-1551.
In article      View Article
 
[56]  Inan, F. A., & Lowther, D. L. (2010). Factors affecting technology integration in K-12 classrooms: A path model. Educational Technology Research and Development, 58(2), 137-154.
In article      View Article
 
[57]  Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010). Predicting collaboration technology use: Integrating technology adoption and collaboration research. Journal of Management Information Systems, 27(2), 9-54.
In article      View Article
 
[58]  Weber, D. M., & Kauffman, R. J. (2011). What drives global ICT adoption? Analysis and research directions. Electronic commerce research and applications, 10(6), 683-701.
In article      View Article
 
[59]  Brown, J. D., & Rodgers, T. S. (2002). Doing second language research. New York: Oxford University Press.
In article      
 

Published with license by Science and Education Publishing, Copyright © 2021 Amnah Jameel Abo Mokh, Shaheen Jameel Shayeb, Amjad Badah, Islam Asim Ismail, YaffaJumah Ahmed, Laila K. A. Dawoud and Hanan Essam Ayoub

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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Normal Style
Amnah Jameel Abo Mokh, Shaheen Jameel Shayeb, Amjad Badah, Islam Asim Ismail, YaffaJumah Ahmed, Laila K. A. Dawoud, Hanan Essam Ayoub. Levels of Technostress Resulting from Online Learning among Language Teachers in Palestine during Covid-19 Pandemic. American Journal of Educational Research. Vol. 9, No. 5, 2021, pp 243-254. http://pubs.sciepub.com/education/9/5/1
MLA Style
Mokh, Amnah Jameel Abo, et al. "Levels of Technostress Resulting from Online Learning among Language Teachers in Palestine during Covid-19 Pandemic." American Journal of Educational Research 9.5 (2021): 243-254.
APA Style
Mokh, A. J. A. , Shayeb, S. J. , Badah, A. , Ismail, I. A. , Ahmed, Y. , Dawoud, L. K. A. , & Ayoub, H. E. (2021). Levels of Technostress Resulting from Online Learning among Language Teachers in Palestine during Covid-19 Pandemic. American Journal of Educational Research, 9(5), 243-254.
Chicago Style
Mokh, Amnah Jameel Abo, Shaheen Jameel Shayeb, Amjad Badah, Islam Asim Ismail, YaffaJumah Ahmed, Laila K. A. Dawoud, and Hanan Essam Ayoub. "Levels of Technostress Resulting from Online Learning among Language Teachers in Palestine during Covid-19 Pandemic." American Journal of Educational Research 9, no. 5 (2021): 243-254.
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  • Table 3. Levels of technostress among Palestinian English language teachers in terms of learning-teaching process factors
  • Table 4. level of technostress among Palestinian English language teachers in terms of profession-oriented factors
  • Table 5. Level of technostress among Palestinian English language teachers in terms of technical oriented factors
  • Table 6. Levels of technostress among Palestinian English language teachers in terms of personal oriented factors
  • Table 7. Levels of technostress among Palestinian English language teachers in terms of social-oriented factors
  • Table 8. T-test for Independent Samples of the levels of technostress among Palestinian English language teachers in terms of gender
  • Table 9. Frequencies, Means and Standards Deviations of the levels of technostress among Palestinian English language teachers in terms of length of service for the total degree
  • Table 10. Results of One Way ANOVA of the levels of technostress among Palestinian English language teachers in terms of length of service
  • Table 11. Frequencies, Means and Standards Deviations of the levels of technostress among Palestinian English language teachers in terms of the level of education for the total degree
  • Table 12. Results of One Way ANOVA of the levels of technostress among Palestinian English language teachers in terms of the level of education
  • Table 13. Frequencies, Means and Standards Deviations of the levels of technostress among Palestinian English language teachers in terms of the level of internet use frequently for the total degree
  • Table 14. Results of One Way ANOVA of the levels of technostress among Palestinian English language teachers in terms of the level of internet use frequently
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[17]  Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831-858.
In article      View Article
 
[18]  Mahapatra, M. &Pati, S. P. (2018). Technostress creators and burnout a job demands-resources perspective. In Aubert, B., Compeau, D. &Tarafdar, M. (Eds.) Proceedings of the 2018 ACM SIGMIS conference on computers and people research, (pp. 70–77). New York, USA: Association for Computing Machinery.
In article      View Article  PubMed
 
[19]  Saal, P. E., van Ryneveld, L., & Graham, M. A. (2019). The Relationship between using Information and Communication Technology in Education and the Mathematics Achievement of Students. International Journal of Instruction, 12(3), 405-424.
In article      View Article
 
[20]  Adnan, M. & Anwar, A. (2020). Online learning amid the COVID-19 pandemic: Students perspectives. Journal of Pedagogical Research, 1(2), 45-51.
In article      View Article
 
[21]  Hornaes, H. P., &Royrvik, O. (2000). Aptitude, gender, and computer algebra systems. Journal of Engineering Education, 89(3), 323.
In article      View Article
 
[22]  Dogan, T., & Ilhan, V. (2006). In Annual Proceedings of Selected Research and Development [and] Practice Papers Presented at the National Convention of the Association for Educational Communications. In Technology Explosion and Its Impact on Education. https://files.eric.ed.gov/fulltext/ED470179.pdf.
In article      
 
[23]  Uluyol, C. &Sahin, S. (2016). Elementary School Teachers’ ICT Use in the Classroom and Their Motivators for Using ICT. British Journal of Educational Technology, 47(1), PP 65-75.
In article      View Article
 
[24]  Brod, C. (1984). Technostress: The human cost of the computer revolution. Reading, Mass.: Addison-Wesley.
In article      
 
[25]  Weil, M.M., & Rosen, L.D. (1997). TechnoStress: Coping with Technology @Work @Home @Play.
In article      
 
[26]  Salanova, Cifre & Nogareda, (2007). Salanova, M., Llorens, S., & Ventura, M. (2014). Technostress: The Dark Side of Technologies. Technostress among users of information and communication technologies, International Journal of Psychology, 48:3, 422-436.
In article      View Article
 
[27]  Molino, M., Ingusci, E., Signore, F., Manuti, A., Giancaspro, M. L., Russo, V., ... & Cortese, C. G. (2020). Wellbeing Costs of Technology use during Covid-19 remote working: An investigation using the Italian translation of the technostress creators scale. Sustainability, 12(15), 591.
In article      View Article
 
[28]  Çoklar, Efilti, &Sahin, (2017). Çoklar, A., Efilti, E., &Sahin, Y. (2017). Defining Teachers’ Technostress Levels: A Scale Development. Journal of Education and Practice, 8, 28-41.
In article      
 
[29]  Meyer, B. (2012). Mediation and the genesis of presence. Towards a material approach to religion.
In article      
 
[30]  Oladosu, K. K., Alasan, N. J., Ibironke, E. S., Ajani, H. A., &Jimoh, T. A. (2020). Learning with Smart Devices: Influence of Technostress on Undergraduate Students' Learning at University of Ilorin, Nigeria. International Journal of Education and Development using Information and Communication Technology, 16(2), 40-47.‏
In article      
 
[31]  Derks, D., van Mierlo, H., & Schmitz, E. B. (2014). A diary study on work-related smartphone use, psychological detachment and exhaustion: examining the role of the perceived segmentation norm. Journal of occupational health psychology, 19(1), 74.
In article      View Article  PubMed
 
[32]  Ghislieri, C., Emanuel, F., Molino, M., Cortese, C. G., & Colombo, L. (2017). New technologies smart, or harm work-family boundaries management? Gender differences in conflict and enrichment using the JD-R theory. Frontiers in psychology, 8, 1070.‏
In article      View Article  PubMed
 
[33]  Suh, A., & Lee, J. (2017). Understanding teleworkers’ technostress and its influence on job satisfaction. Internet Research.
In article      View Article
 
[34]  Ninaus, K., Diehl, S., Terlutter, R., Chan, K., & Huang, A. (2015). Benefits and stressors – Perceived effects of ICT use on employee health and work stress: An exploratory study from Austria and Hong Kong. International Journal of Qualitative Studies on Health and Well-being, 10(1), 28838.
In article      View Article  PubMed
 
[35]  Brown, R., Duck, J., &Jimmieson, N. (2014). E-mail in the workplace: The role of stress appraisals and normative response pressure in the relationship between e-mail stressors and employee strain. International Journal of Stress Management, 21(4), 325.
In article      View Article
 
[36]  Al-Fudail, M., &Mellar, H. (2008). Investigating teacher stress when using technology. Computers & Education.
In article      View Article
 
[37]  Özgür, H. (2020). Relationships between teachers’ technostress, technological pedagogical content knowledge (TPACK), school support and demographic variables: A structural equation modeling. Computers in Human Behavior, 112, 106468.
In article      View Article
 
[38]  Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986, 23-28.‏
In article      
 
[39]  Bandura, A. (1997). The anatomy of stages of change. American journal of health promotion: AJHP, 12(1), 8-1.
In article      View Article  PubMed
 
[40]  Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-21.
In article      View Article
 
[41]  Blonder, R., Jonatan, M., Bar-Dov, Z., Benny, N., Rap, S., &Sakhnini, S. (2013). Can You Tube it? Providing chemistry teachers with technological tools and enhancing their self-efficacy beliefs. Chemistry Education Research and Practice, 14(3), 269-285.
In article      View Article
 
[42]  Yes¸ ilyurt, E., Ulas¸, A. H., & Akan, D. (2016). Teacher self-efficacy, academic self-efficacy, and computer self-efficacy as predictors of attitude toward applying computer-supported education. Computers in Human Behavior, 64, 591-601.
In article      View Article
 
[43]  Paul, N., & Glassman, M. (2017). Relationship between internet self-efficacy and internet anxiety: A nuanced approach to understanding the connection. Australasian Journal of Educational Technology, 33(4).
In article      View Article
 
[44]  Shu, Q., Tu, Q., & Wang, K. (2011). The impact of computer self-efficacy and technology dependence on computer-related technostress: A social cognitive theory perspective. International Journal of Human-Computer Interaction, 27(10), 923-939.
In article      View Article
 
[45]  Lo´pez-Vargas, O., Duarte-Sua´rez, L., & Iba´n˜ez-Iba´n˜ez, J. (2017). Teacher’s computer self-efficacy and its relationship with cognitive style and TPACK. Improving Schools, 20(3), 264-277
In article      View Article
 
[46]  Semiz, K., & Ince, M. L. (2012). Pre-service physical education teachers' technological pedagogical content knowledge, technology integration self-efficacy and instructional technology outcome expectations. Australasian Journal of Educational Technology, 28(7).
In article      View Article
 
[47]  Shulman, L.S. (1986). Those Who Understand: Knowledge Growth in Teaching. Educational Researcher, 15, 14-4.
In article      View Article
 
[48]  Pineida, F. O. (2011). Competencies for the 21st century: integrating ICT to life, school and economic development. Procedia-Social and Behavioral Sciences, 28, 54-57.
In article      View Article
 
[49]  Koehler, M. J., & Mishra, P. (2005). What happens when teachers design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2), 131-152.
In article      View Article
 
[50]  Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPACK) the development and validation of an assessment instrument for preservice teachers. Journal of research on Technology in Education, 42(2), 123-149.
In article      View Article
 
[51]  Blackwell, C. K., Lauricella, A. R., & Wartella, E. (2016). The influence of TPACK contextual factors on early childhood educators’ tablet computer use. Computers & Education, 98, 57-69.
In article      View Article
 
[52]  Koh, J. H. L., Chai, C. S., & Lim, W. Y. (2017). Teacher professional development for TPACK-21CL: Effects on teacher ICT integration and student outcomes. Journal of Educational Computing Research, 55(2), 172-196.
In article      View Article
 
[53]  Joo, Y. J., Lim, K. Y., & Kim, N. H. (2016). The effects of secondary teachers’ technostress on the intention to use technology in South Korea. Computers & Education, 95, 114-122.
In article      View Article
 
[54]  Drossel, K., Eickelmann, B., & Gerick, J. (2017). Predictors of teachers’ use of ICT in school–the relevance of school characteristics, teachers’ attitudes and teacher collaboration. Education and Information Technologies, 22(2), 551-573.
In article      View Article
 
[55]  Eickelmann, B., Gerick, J., & Koop, C. (2017). ICT use in mathematics lessons and the mathematics achievement of secondary school students by international comparison: Which role do school level factors play?.Education and Information Technologies, 22(4), 1527-1551.
In article      View Article
 
[56]  Inan, F. A., & Lowther, D. L. (2010). Factors affecting technology integration in K-12 classrooms: A path model. Educational Technology Research and Development, 58(2), 137-154.
In article      View Article
 
[57]  Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010). Predicting collaboration technology use: Integrating technology adoption and collaboration research. Journal of Management Information Systems, 27(2), 9-54.
In article      View Article
 
[58]  Weber, D. M., & Kauffman, R. J. (2011). What drives global ICT adoption? Analysis and research directions. Electronic commerce research and applications, 10(6), 683-701.
In article      View Article
 
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