Factors Affecting Chinese English as a Foreign Language Teachers’ Technology Acceptance: A Qualitative Study

Abstract

This article explores Chinese English as a Foreign Language (EFL) teachers’ attitudes toward technology use and the factors that influence their technology acceptance. A qualitative study was conducted with data obtained from semistructured, in-depth interviews of 14 university teachers from six provinces. The interview data revealed that Chinese EFL teachers generally maintained a positive attitude toward technology use in teaching. Facilitating conditions driven by modernization, perceived usefulness, subjective norm, and technology mania are major factors influencing their technology acceptance. It is worth noticing that the degree of reliance on technology varied in terms of age and experience. Overall, the findings were consistent with previous studies, while leading to a broader and deeper understanding of technology acceptance theories by analyzing contextual and cultural phenomenon in China. Implications for future research and suggestions to improve Continuing Professional Development were provided in order to promote technology integration among Chinese teachers.

Keywords

technology acceptance EFL teachers continuing professional development China

Introduction

The rapid development of information and communication technology (ICT) has dramatically transformed education. For many years, ICT has been a focus of interest among educational researchers for its ability to induce a paradigm shift, extend teachers’ abilities to manage and disseminate knowledge (Wong, Teo, & Russo, 2012), make learning meaningful, and enhance teaching effectiveness and productivity (Baydas & Goktas, 2016). Effectiveness of technology integration has been reported in diverse learning fields, such as science (McFarlane & Sakellariou, 2002), reading, and math (Carrasco & Torrecilla, 2012). There is a consensus that advances in computer technologies and their diffusion have motivated the development of new teaching strategies, enriched teaching materials, and increased students’ learning motivation (Teo, 2011). Therefore, the Chinese government has invested heavily in building technology infrastructure within schools and in allocating opportunities for teachers’ technology training (Li & Ni, 2011), driven by technology-related policies in China. For example, in 2012, the Ministry of Education in China issued “Education information: 10 years development plan (2011–2020)” which explicitly put forward the requirement of integrating technology into teaching and learning across subjects, including facility investment, technical supports, and teachers’ technological and pedagogical skills to ensure technology integration into education.

With China stepping into the globalization scene, the use of ICT as a teaching and learning tool has been acclaimed as a catalyst for educational transformation by policy makers and teachers (Yang, 2012), more so in English as a foreign language (EFL) teaching. Integration of ICT into EFL teaching and learning greatly facilitates the creation of an authentic language-rich environment, bridges the gap derived from the identities of teachers and nonnative speakers (Wang & Coleman, 2009), and promotes interactive language teaching and learning activities (Golonka, Bowles, Frank, Richardson, & Freynik, 2014). Furthermore, it also increases students’ listening and speaking proficiency (Zou, 2013), helps teachers increase students’ learner autonomy (Wang & Coleman, 2009), and strengthens student learning engagement, problem-solving, and higher order thinking skills (Tsai, 2013).

In this article, we examined EFL teachers’ views on using ICT technology in higher education in China and factors that influence their intentions to use ICT technology in teaching. This study contributes to further understanding of technology acceptance theory by contextualizing it to one developing country, China, and the results also provide informative evidence and suggestions for policy makers and administrators to improve technological professional training.

Literature Review

Technology Acceptance Model

In any educational setting, teachers have the autonomy to determine technology use in terms of the type, frequency, and quantity. This partly explains why technology acceptance study becomes a focus of interest among educational researchers (Teo & Zhou, 2017). Among various technology acceptance theories and models, the technology acceptance model (TAM; Davis, Bagozzi, & Warshaw, 1989) is among the first to include psychological factors in predicting users’ technology acceptance. It specifies causal relationships between perceived usefulness, perceived ease of use, attitude toward computer use, and behavioral intention to use technology (Teo & Zhou, 2017). In this model, an individual’s technology actual usage is determined by his or her behavioral intention to use technology, and behavioral intention is in turn influenced by the individual’s attitude toward technology use. Perceived usefulness (PU) and perceived ease of use (PEU) are the most important fundamental determinants of attitude toward technology use. PU directly influences attitude toward technology use and behavioral intention to use technology, and PEU directly influences PU and attitude toward technology use; in this way, it indirectly influences behavioral intention to use technology. In TAM, PU refers to the degree to which a person believes technology will help him or her perform a certain task in an efficient and productive manner. PEU refers to the extent to which a person believes the use of technology will be relatively effortless. PU and PEU are the most important fundamental determinants of attitude toward technology use: PU directly influences attitude toward technology use and behavioral intention to use technology, and PEU directly influences PU and attitude toward technology use and indirectly influences behavioral intention to use technology.

The current research is drawn upon TAM, which has been empirically witnessed across a broad range of computing technologies and user populations (Tarhini, Hone, Liu, & Tarhini, 2016). Despite the accolades given to TAM for its predictive ability, this model has also been criticized as too parsimonious (e.g., Teo & Jarupunphol, 2015; Wong et al., 2012), as it does not specify external variables that may also influence users’ technology acceptance and use. TAM only provides general information concerning the acceptance of a specific technology (Tsai, 2015), and factors that influence Chinese EFL teachers’ technology acceptance and usage have been more than what TAM has suggested (Li, 2014). Therefore, this research aims to provide further insights into this topic by examining Chinese EFL teachers’ acceptance of technology using a qualitative approach.

Qualitative Approach in Technology Acceptance Studies

Investigating factors affecting teachers’ intention to use technology is increasingly arousing researchers’ attentions and efforts (Teo, Huang, & Hoi, 2017). Previous studies have examined teachers’ acceptance of technology in language teaching (Hu & McGrath, 2011; Li, 2014; Yang & Huang, 2008). A review of these studies indicated that the TAM could only explain a certain portion of the variance of intention to use technology, since the decision-making process of the teachers is more complicated than that of TAM (Li, 2014). Dong (2009) also indicated that the predictable power of existing theories (e.g., TAM) should be questioned across cultures and examined in different cultural contexts considering the influence of culture on technology user acceptance has been long recognized in the academic field (Straub, Keil, & Brenner, 1997; Tarhini et al., 2016; Teo et al., 2017). Thus, the researchers such as Li (2014) and Dong (2009) made a call for future research for seeking other possible contributors to the model. Different from previous researches that were usually conducted in one university, or schools at primary and secondary level, this study investigated factors influencing university EFL teachers’ technology acceptance by including teachers from diverse universities in China, and in looking at teachers from multiple sites, information we obtained in this study will be more inclusive and richer than previous studies that only involved one site.

Previous qualitative studies indicated that Chinese EFL teachers’ decision-making process in technology adoption is even more complicated than what TAM suggested (Li, 2008, 2014). Chinese education is highly centralized, and there are top–down official policies stipulating technology integration in teaching EFL in China (e.g., College English Curriculum Requirement, 2007). However, policies do not necessarily guarantee teachers’ decisions, and this is seen from their lukewarm responses toward using ICT in the classrooms due to factors such as the lack of pedagogical and technological training and insufficient technology equipment (Li, 2014). When they did use technology, it was not as productive and effective as expected (Li & Walsh, 2011; Yang & Huang, 2008). For example, Li (2008, 2014) found that besides technical support and access to technology resources, EFL teachers in China were also concerned with the availability of time to prepare to teach with technology. It is noteworthy that this factor has not been identified in previous quantitative studies, as Tondeur, Kershaw, Vanderlinde, and van Braak (2013) argued that it was difficult to understand technology integration solely based on quantitative studies that often focus on the impact of individual- and system-related features.

Since Chinese education is highly centralized, it remains to be confirmed whether the centralized policy influences EFL teachers’ technology attitude and adoption. Compared with quantitative studies, qualitative studies observe what is actually occurring in the classroom, thus enabling researchers to collect detailed, in-depth information and describe how this information is interrelated, through examinations and interviews (Tondeur et al., 2013). The above discussion reveals the need for a more in-depth investigation to encompass personal, pedagogical, and organizational factors influencing the integration of technology (Tondeur, Van Keer, van Braak, & Valcke, 2008) in the context of Chinese EFL teaching.

Present Study

Mainland China has been characterized as a collectivist society wherein people are sensitive to power distance (Hofstede, 1984) and place great emphases in meeting requirements from upper authorities and superiors. This is also well reflected in its centralized educational system wherein promoting technology acceptance and use among teachers becomes most effective in the top-down policy (Hu & McGrath, 2011). Therefore, it is not surprising that English teachers in China generally hold positive attitudes toward the College English Curriculum Requirement (CECR, 2007) which specified and promoted technology use in classrooms, although they were not well prepared with technology integration in teaching, due to the lack of effective pedagogical and technological training (Hu & McGrath, 2011).

The aim of this study is to explore the influential factors of Chinese university EFL teachers’ technology acceptance for three considerations. First, existing studies with Chinese samples mostly focused on preservice teachers (e.g., Sang, Valcke, van Braak, Tondeur, & Zhu, 2011) or teachers at K-12 or secondary school level (e.g., Li, 2014; Li & Ni, 2012). Very few studies reported teachers’ technology use at the university level (see Hu & McGrath, 2011, as an exception). Second, the CECR (2007) specified the necessity of ICT use in achieving the teaching objectives of improving effective communication and students’ intercultural competence (Wang & Coleman, 2009). The document also promoted the teaching mode featured by the use of ICT. Last, there has been a lack of research published internationally, studying Chinese university teachers’ understanding of ICT integration in teaching (Sang et al., 2011). Hence, this study aims to obtain a deeper understanding of English teachers’ perceptions of influential factors in technology acceptance in Chinese universities.

Using the qualitative approach, the present study addressed the question, “What factors influence Chinese university EFL teachers’ technology use?” The findings will contribute to the existing technology acceptance theories by exploring factors that were not reported in past researches, which enrich the model and improve its applicability in Asian cultures. It will also contribute to practice by providing informative evidence for policy makers and administrators to better understand existing scenarios, and offer suggestions in terms of improving continued professional development.

Method

Given that technology is comprehensively used in complex learning settings such as classrooms, and this can usually be examined with qualitative research methods (Palvia, Mao, Salam, & Soliman, 2003), this study used interviews to probe teachers’ attitudes, thoughts, and perceptions about technology use. Tondeur, Kershaw, Vanderlinde, and van Braak (2013) argued that it is difficult to understand technology integration solely based on quantitative studies that often focus on the impact of individual- and system-related features. Compared with quantitative studies, qualitative studies observe what is actually occurring in the classroom, thus enabling researchers to collect detailed, in-depth information and describe how this information is interrelated (Tondeur et al., 2013). As qualitative research would reveal new perspectives on well-known research topics (Strauss & Corbin, 1998), research problems framed as open-ended questions would support the discovery of new information, thus updating our knowledge on the topic (Hoepfl, 1997).

Researchers using qualitative methods found that leadership (Kavanagh & Ashkanasy, 2006), personality (Ouadahi, 2008), and trust in teammates and supervisors (Vogelsang, Steinhüser, & Hoppe, 2013) had an impact on technology acceptance. These constructs were relevant to technology acceptance, but would not have been revealed without the use of qualitative approaches. All in all, this reveals the need for a more in-depth investigation to encompass personal, pedagogical, and organizational factors influencing the integration of technology in teaching (Tondeur et al., 2008).

Settings

Different from previous research that was usually conducted in one university or school, this study involved multiple universities. The Chinese government classifies Chinese universities into key universities and nonkey universities based on factors such as academic strength, management strength, and so on (Wang, 2009). The key universities are superior to nonkey universities in terms of financial support from the government to facilitate technology use by and training for teachers, hence easing the process of technology use and promoting the intention to use technology (Zhou, Zhang, & Yang, 2012). These are important factors that influence teachers’ technology attitudes and intentions (Teo, 2009). Thus, the unbalanced educational informationalization development in Chinese universities (Zhou et al., 2012) would result in differences in teachers’ attitudes toward technology use in teaching. Therefore, it is necessary to involve participants from different cities and types of universities to consider potential differences from various locations. Based on university types and three indices for economic development (i.e., the per capita gross national product, the per capita income, and the rural per capita net income), the settings in this study are classified into key universities and nonkey universities located in developed areas (e.g., Shandong and Fujian provinces) where their indices for economic development are above the national average, medium developed areas (e.g., Yunnan, Heilongjiang, and Anhui provinces) where their indices for economic development are just at the national average, and underdeveloped areas (e.g., Xinjiang autonomous region) where their indices for economic development are below the national average (Zhou et al., 2012). In doing so, the findings would be more informative and representative to deepen our understanding of the use of technology in Chinese higher education and existing technology acceptance theories.

Participants

Fourteen teachers were specifically selected based on several factors. First, the selected participants were from developed areas (e.g., Shandong and Fujian), medium developed areas (e.g., Yunnan, Heilongjiang, and Anhui), and underdeveloped areas in China (e.g., Xinjiang autonomous region). Second, the participants varied based on several individual factors including gender, age, professional rank, and technology use experience. We believed that a range of answers would better reflect teachers’ perspectives. Last, half the teachers were currently working in key universities in China while the other half worked in nonkey Chinese universities. Key universities belong to the “Project 211” and “Project 985” initiatives, entitled by the Ministry of Education of China, with the intent of promoting the development and reputation of the Chinese higher education system, by raising the research standards of high-level universities. Accordingly, Wang (2009) suggested with the continuous perfections of key universities (“Project 211” and “Project 985” initiatives) that the technology facilities in those universities are significantly superior than nonkey universities in terms of technology quality and quantity, because key universities generally have more priorities than universities with normal rankings in terms of government funding support and technology equipment installation, and this may influence teachers understanding of technology-related pedagogy, based on the finding that teachers from different levels of Chinese universities varied in technology integration (Zhu, 2015). Table 1 illustrates detailed information of the participants (pseudonyms are used to ensure their confidentiality).

Table 1.

Demographic Information of Participating Teachers.

Teacher	Gender	Age	Title	CALL experience	University type	Province	Interview type
A	Female	20–30	Assistant lecturer	1 year	Key	Anhui	Face-to-face
B	Female	50–60	Professor	10 years	Key	Shandong	Face-to-face
C	Male	50–60	Professor	10 years	Key	Shandong	Face-to-face
D	Male	40–50	Professor	13 years	Key	Heilongjiang	Face-to-face
E	Male	30–40	Associate professor	13 years	Key	Heilongjiang	Face-to-face
F	Female	20–30	Lecturer	5 years	Key	Fujian	Face-to-face
G	Male	30–40	Associate professor	10 years	Key	Shandong	Face-to-face
H	Female	20–30	Lecturer	8 years	Nonkey	Yunnan	Online
I	Female	50–60	Professor	14 years	Nonkey	Shandong	Face-to-face
J	Female	30–40	Lecturer	14 years	Nonkey	Shandong	Face-to-face
K	Female	30–40	Lecturer	12 years	Nonkey	Shandong	Face-to-face
L	Male	40–50	Associate professor	5 years	Nonkey	Shandong	Face-to-face
M	Female	30–40	Lecturer	12 years	Nonkey	Shandong	Face-to-face
N	Female	20–40	Lecturer	10 years	Nonkey	Xinjiang	Online

Instrument and Data Collection

Semistructured interviews were conducted individually, following a protocol of interview questions (see Appendix). All the interviews except for teachers located in Xinjiang and Yunan provinces were conducted face-to-face when the researchers traveled to those universities in 2016. Interviews for participants from Xinjiang and Yunan provinces were conducted through WeChat (an online tool with audio and video functions), because of the extreme inconvenience to reach these remote places. All the interviews either conducted face-to-face or on the WeChat platform were audio-taped and transcribed for further data analysis.

Generally, interviews lasted for about 30 minutes while some face-to-face interviews lasted about 1 hour. Additional questions were asked to clarify and explore the unique experiences of the interviewees. Informed consents were obtained from the participants to record interviews. For the online interviews, the researchers used online communication tools (e.g., WeChat) to conduct the briefing about this study to each participant, including the research purpose, the use of pseudonym to protect participants’ privacy, and the participant’s right to withdraw at any stage of the study. Afterwards, the consent forms were sent to the participants through the online communication tool for their digital signatures. All the interviews were conducted in 3 months. Explanations of the research purposes and procedures were fully distributed.

Data Analysis

Analysis of interview data was guided by the grounded theory, which provides systematic procedures to identify categories and their connections (Urquhart, 2012). Specifically, the coding process operates inductively and involves the construction of theory through the analysis of data. We followed the coding process suggested by Creswell (2009) and Strauss and Corbin (1998), using open coding, axial coding, and selective coding. It began with a collection of data based on a list of questions. When researchers reviewed the data, repeated concepts became apparent and were grouped into categories (open coding). For example, if interviewees consistently talked about the usefulness of technology in English lessons, each time an interviewee mentioned about it, or any aspect related to its usefulness, “perceived usefulness” would become a concept, and “attracting students’ attention” and “providing authentic materials” would become categories. The first author read the interview transcripts line-by-line and used highlights to distinguish concepts and categories, which formed the basic units of our analysis. During this process, a list of codes emerged which represented concepts that later became part of the theory (O’Connor, 2012).

The first author performed a qualitative analysis to develop codes based on meaningful statements in each transcript and across all 14 transcripts. The disagreement initially emerged when the third author checked the codes emerged in the open coding to define concepts and categories. To eliminate disagreement in codes and categories in open coding, the third author checked the codes, while rereading the data to confirm that the concepts and categories accurately represented interview responses and to explore how the concepts and categories were related (axial coding). For example, the category of “using technology to help teachers save lecturing time” was initially coded as “improved efficiency in teaching” for the concept of “perceived usefulness,” but the third author found an axial code might be a phrase like “teachers’ perceptions of using technology from time-consuming to time-saving.” This discusses the context of the categories, and suggests that we might need a new category labeled “teacher perception change.”

Because categories merely described the data, they must be further integrated to form the theory (O’Connor, 2012). In the last step of integrating and refining the theory (selective coding), the second author identified the “core” category to which all other categories must relate. For example, the policy influence on teachers’ technology use was initially considered as an independent category. The second author considered it as external pressure since Chinese educational system is highly centralized and teachers usually obey what the policy requires them to do (Sang et al., 2011). After discussion, the agreement was achieved among the three authors that policy influence was included in the concept of “Subjective norms” which is highly related to the core concept of “technology use intention.” In this way, the long list of codes was reduced to a smaller number by constant checking and comparisons. Based on the criteria of whether the codes were exhaustive and sensitive to the data, or reflected the purpose of the research, some codes were excluded because they were neither keeping to the point nor highly relevant to the study. This coding process is illustrated in Figure 1.

Figure 1.

Example of coding process. Solid lines indicate final codes and dotted lines indicate initial codes.

To avoid researcher bias and ensure the interrater reliability (Miles & Huberman, 1994), the third author checked the first author’ coding adequacy by checking the codes with the original statements and sought verifications from each participant while coding his or her transcript. During the recoding process, the first author and the third author reached an agreement of about 92% regarding the concepts and categories. Approximately 8% of the data were recoded by the third author to ensure interrater consistency, rigor, dependability, and credibility (Miles & Huberman, 1994). Any coding differences encountered were discussed and reconciled through consultation among the three authors. The first author and the third author coded the interview transcripts and the second author helped check codes and participated in the discussion procedure to finalize the codes.

The dual identity of being a researcher and an English teacher brought sympathy (Li, 2014) for the first author when interviewing the participants. However, this sympathy also helped close the distance between the researcher and participants, making participants more willing to share. When interviewing the participants, the first author reminded herself to act innocent and not to mention any theories to participants. The second author and the third author listened to the recordings and checked the transcripts to ensure no materials indicating research bias were included. Before data analysis, all the transcriptions were sent to the participants to ensure accuracy with the original recordings (Morse, Barrett, Mayan, Olson, & Spiers, 2008).

Findings

Redefining Facilitating Conditions: Equipment Access or Technical Support Availability?

Our participants expressed satisfaction in terms of access to equipment, and they agreed that it is an important precondition for technology use. They all had easy access to computers, projectors, and the Internet. Both key and nonkey universities recommend using computers to create electronic tools such as PowerPoint presentations, Flash links, and webpage links as frequent teaching activities.

Chinese universities are very good in terms of equipping classrooms with technologies. Equipment resource is actually a very important achievement, which leaders report to the higher authorities. They are very proud if both the hardware and software facilities are superior. (Teacher L)

Though our university is a non-key university, most classrooms are equipped with computers and projectors, which are equipment resource in key universities. If you need to use them, you can obtain the keys from the classroom administrative office, which is very convenient. (Teacher H from a nonkey university)

Each classroom in my university is equipped with computers, and nearly 90% of English teachers use computer applications, such as PowerPoint, word processing, and projectors. (Teacher F from a key-university)

Nonetheless, accessibility of equipment resource by no means implies the effective use of this equipment. As Taylor and Todd (1995) argued, facilitating conditions not only elaborate the hardware equipment but also include availability of technical support provided for users in the environment that encourages and facilitates technology adoption. In educational settings, physically installed equipment, available materials and resources, and technical and administrative support combine to enhance users’ technology behavioral intention (Groves & Zemel, 2000). However, the interview data did not provide a consensus in terms of teachers’ perceptions about technical support availability: key universities provide more technical support than nonkey universities for teachers. Specialized technical supports are rarely available for teachers in nonkey universities, which impeded their technology use decisions. Whereas, they are consistently available in key universities—specialized technical staff who assist teachers when they face technical problems. For example,

When my class is stuck due to unexpected technical problems, I must pretend to be calm and quickly reorganize the planned activities, though actually I am very nervous. I wish I could ask technical staff for help to solve those technical problems quickly. (Teacher M from a nonkey university)

Each classroom is equipped with a telephone and the contact information of technical staff. I can call them and they will come to the classroom very quickly to solve technical problems so that I can continue teaching with the technologies. I do not worry about this at all. (Teacher B from a key university)

PU in English Teaching: Motivator and Information Sources

Teachers perceived two aspects of the usefulness of technology in English classes: (a) motivating and engaging students and (b) providing additional information sources relevant to teaching and learning. Prior researchers have repeatedly reported the effective use of technology in engaging students in English classes (e.g., Hwang & Wang, 2016; Rogan & San Miguel, 2013). Our data concur with these conclusions, as one of the teachers commented, “Lifting their heads is preliminary for communicative teaching” (Teacher A). The following quotes elaborated this perspective:

Unlike students in middle and high schools who are highly motivated to achieve high scores in their College Entrance Exams, university students are not attentive in class. College English teaching strengthens listening and speaking. Audio and video clips are very helpful to attract their attention and make them lift their weary heads to look at you. (From Teacher A)

My students do not like to answer questions in class according to the roll call. So I inserted a small race-to-be-the first software program in my PPT slides. Whenever I ask students questions, I use it. Students are very interested in this novelty and thus are motivated to answer questions. (From Teacher F)

In China, Mandarin is often used as the instructional language in English teaching, especially for non-English majors. Therefore, the lack of authentic English-teaching materials and learning environment is a severe disadvantage. Information technologies have been known to play a key role in providing the learners with ready access to information and knowledge (Paswan & Wittmann, 2009). With technology and the Internet, all the interviewees consented that technologies are indeed advantageous in providing authentic input and valuable teaching materials.

Technology provides teachers and students with authentic English materials including language and culture. Technology assisted language teaching greatly broadens students’ vision and knowledge. (From Teacher H)

It is so awkward when students ask me something that I am not sure. In many cases, we need to confirm the appropriateness of some English expression or phrases. Whenever I am asked about words or phrases that I am not sure or I do not know, I need computer software or the Internet to search for its meaning. (From Teacher M)

Teacher Perception Change in Technology Use: From Time Consuming to Time Saving

Teachers’ conceptions of teaching and learning have been documented as a key factor in their acceptance of using technology (Teo & Zhou, 2017). Preparation for teaching students in a class size of 60 or so, due to the expansion of student enrollment in Chinese universities, is usually very time consuming for teachers to design effective class activities (Hu, 2002). Therefore, when teachers choose strategies to perform teaching tasks, time is one of the major concerns (Li & Ni, 2011). Our data showed a transition from initially considering using technology as a time-consuming teaching behavior to perceiving it as a time-saving teaching strategy in the long term. For example:

I usually search online, copy and paste important contents onto PowerPoint slides, and listen to the disc to ensure its appropriateness for teaching. In the first teaching year, it takes time to select materials from massive resources, but eventually, I can use the slides repeatedly and it saves a lot of time. (From Teacher A)

Using PowerPoint slides is like getting something done once and forever. If you do it carefully the first time, you will just need to revise it a little bit and add something new occasionally. It really saves your time. (From Teacher M)

Subjective Norms: From External Pressure to Internal Initiatives

Social influences on using technology in teaching are clearly revealed in the interviewees’ responses. In this study, all the teachers mentioned different groups who affected their decision to adopt technology. At the micro level, social influence includes school leaders, colleagues, and students, while at the macro level, it includes teacher assessment systems and school policies. Specifically, micro social influences involve pressure from school leaders, colleagues’ observations, and expectations from students. The quotes below illustrate each of these:

The dean often reiterates the importance of using technology during the regular faculty meeting…He also asks teachers to use the teaching platform, and even checks the frequency of platform use by teachers. If a teacher’s webpage receives the highest click rate, he will praise the teacher during the meeting and set him or her as a good model. (From Teacher N)

Every semester we have a mid-term teaching assessment by both leaders and peers. They come to my classroom without informing me beforehand. When this occurred, I would get nervous and had to remind myself to use technology more often. For example, I played the audio instead of reading texts. (From Teacher M)

Students think teachers who use technologies innovatively are fashionable, instead of being outdated. (From Teacher A)

In comparison, macro social influences involve external pressure from teacher assessment and awarding systems and curriculum requirements. The quotes below illustrate each of these:

In my university, using technology in teaching is a criterion for teaching assessment by both students and leaders. It does not matter if you (teachers) can use it in a very innovative way. (From Teacher G)

In my university, the title of “jiaoxue mingshi” (distinguished teacher) helps you gain credits for your promotion evaluation. One university level award equals to one research paper published in a Chinese academic journal. (From Teacher A)

In my university, being awarded at the provincial level will benefit your future promotion. A teacher who is barely in her thirties was promoted to a professorship, largely because she won the first-class teaching award in Heilongjiang Province, and the third prize in the national English teaching competition. Of course, using technology in a good way is important in the competition. (From Teacher D)

In China, several national and local governmental policies specified technology use, for example, the National Plan for Medium and Long-Term Education Reform and Development (2010–2020) and the CECR. Policy requirements played an important role in teachers’ technology use and facilitated technology-integrated pedagogical innovation (Sang et al., 2011), although the implementation of these policies varied across regions in China (Wang, 2011), considering geographic diversity and unequal economic development. Driven by policies, teachers’ consciousness of using technology increased (see the following discourse by Teacher A), and further promoted their intention to use technology.

Yes, I heard of College English Curriculum Requirements about technology use during regular faculty meeting but not the details. Due to this policy, we use technologies to improve listening and speaking English teaching. (From Teacher A)

An interesting finding was that the interviewees did not express any concerns, complaints, or resentments to these social influences. Instead, they agreed with the leaders, policy-makers, and curriculum designers’ bid to integrate technology. Thus, the external pressure that the teachers initially perceived eventually became triggers for their internal initiatives.

Besides student’s fondness and influence from observing my colleague’s teaching, leaders also promoted technology use. Eventually, I accepted this innovative teaching model. (From Teacher M)

Technology Mania: Variation in Age and Teaching Experience

From our interview data, teachers’ age and experiences appeared to be additional factors in teachers’ different views on using technology. Novices and young teachers perceived themselves as the new generation who relied on technology in teaching. Senior teachers, however, believed that their solid content knowledge could compensate for the lack of technology use in teaching. Additionally, they lacked the confidence in keeping pace with the development of modern technology. For example,

I do not think about the reasons why I use computers to prepare lessons; I am used to this way. I use PPT slides in my class very easily. I studied with technology when I was a college student, so when I work, it (technology use) just happens… I put all my materials and notes in PPT slides, for example, the different meanings of a new word and sentence examples. I did not need to remember them, because the PPT slides reminded me when I forgot. Experienced teachers might not need this because they have been teaching for years and they remember content. One of my colleagues, who has been teaching for almost 20 years, can even teach students without a textbook. (From Teacher A)

Sometimes I use technologies sometimes I do not. Teachers at my age cannot compete with younger teachers in computer use, because in my teaching career (have been teaching for almost 30 years), very few training opportunities were provided to improve technological and pedagogical skills, although some were provided to novice teachers… I take too much time to search for good English materials from the Internet, let alone editing video films. I believe that if a teacher is familiar with teaching content and has enough knowledge to teach, he or she does not need to rely on technologies in teaching… I often explain content using my own life experiences. (From Teacher I)

Regardless of the teachers’ age and teaching experiences, all agreed that overreliance on technology was risky while teaching.

Sometimes the computer or projector just will not start. This has happened several times in my class. I then, need to contact technical staff for help, which takes up teaching time, and have to adjust my teaching materials quickly. (From Teacher G)

In summary, the above themes demonstrated positive attitudes toward technology use in EFL teaching. Infrastructural facilitation conditions in Chinese universities provide the necessary conditions for teachers’ technology use, although technical training and support are insufficient in some universities. PU in engaging students and providing course-relevant information is another major factor that influences teachers’ technology acceptance. Subjective norms or social influence, including significant others, and policy requirements influenced teachers’ decision-making process. In addition, teacher perception change in using technology and characteristics also influenced teachers’ acceptance.

Discussion

This study investigated factors that influence university EFL teachers’ technology acceptance in Chinese universities and investigated their understanding of these factors. Generally, most Chinese university EFL teachers use technology in teaching and hold positive attitudes toward technology assistance in English teaching. The interview data generated five themes: redefining facilitating conditions, PU, teacher perception change, subjective norm, and technology mania.

In line with previous findings based on TAM (Groves & Zemel, 2000; Teo, 2009), this study suggested the importance of facilitating conditions for teachers’ intention to use technology. As an important element in facilitating conditions, the availability of technical support varied among Chinese universities in that key universities provided better technical support to facilitate teachers’ technology use in teaching. This is understandable given that key universities usually have more funding support and pay more attention to teaching quality. Besides, equipment access as an important factor supports the notion of Ertmer (1999) and Sadaf, Newby, and Ertmer (2016), in that they indicated access to technology resources was one of the first-order barriers and considered a precondition to teachers’ technology adoption. Different from the previous study in a Chinese university (Hu & McGrath, 2011), this study suggested that access to technology-equipped classrooms is no longer a major concern, but rather, technical support which is an element both in first-order barrier and facilitating conditions mattered to a larger degree.

Technological pervasiveness and advancement have brought teachers in Chinese universities to a position where they always consider if technology provides them with actual benefits and to what degree technology is indispensable. In accordance with TAM, PU was considered an important determinant that influenced teachers’ intention to use technology in China. The usefulness was embodied in motivating students and providing accurate information resources, which has been documented in a large body of past studies (Hwang & Wang, 2016; Rogan & San Miguel, 2013). It is also worth noticing that English teachers perceived that materials play an important role in English teaching in China. Just as Li (2014) suggested, the advantages of technology in providing accurate teaching materials were highly appreciated by Chinese EFL teachers.

The change in teachers’ perception of time issues when using technology challenged some prior research. For example, Li (2014) suggested that time was one of the major factors that impeded English teachers’ technology use in China. However, in this study, university EFL teachers experienced a transition from spending more time preparing teaching materials and activities with technology initially to spending less time in retrieving these materials and activities later. Admittedly, technology helps teachers maintain the teaching materials, yet also requires frequent updates not only in terms of the teaching strategies but also in updating the technology to be used in class. This unfortunately is not realized by the interviewees.

Previous studies suggested that subjective norm played a significant role in predicting users’ PU and further influenced users’ attitudes and behavioral intention to use technology (Pierce & Ball, 2009; Teo, Milutinović, & Zhou, 2016; Venkatesh & Bala, 2008). This study further unpacked how subjective norm influenced teachers’ technology use. External forces covered school leaders’ promotions and awards for technology use, colleagues’ peer evaluation, students’ expectations of teachers’ technology use, and curriculum requirement. However, it is enlightening and encouraging to observe that the external pressures teachers face changed into their willingness and initiative to use technology. The internalization of such external pressures or requirements is well documented in literature, wherein employees may accept and internalize the values conveyed by leaders, thereby seeing their work as congruent with their own self-concepts (e.g., Bono & Judge, 2003; Shamir, House, & Arthur, 1993). This was especially true in Chinese individuals who “feel an obligation to show their conformity to the social group to which they belong” (Hue & Li, 2008, p. 32). Thus, it is not surprising that these teachers comply with social expectations and policy requirements, gradually taking the initiative to use technology.

EFL teachers in this study showed technology mania or reliance at different levels based on their age and teaching experiences. Novices and younger teachers usually had a higher dependency on technology than experienced teachers, indicating that younger teachers had higher technology competence and confidence than older teachers. This finding supported the features of digital natives (Prensky, 2001), who were keen on experimenting and adopting technology with a particular purpose. For experienced and senior teachers, their sufficient content knowledge and pedagogical skills were believed to compensate for the lack of technology use, so they felt they could teach effectively even without technology.

Limitations

Considering the geographical diversity in China, its small scale limited this study. The findings might not be inclusive and it is possible that certain specific contextual factors may have been omitted by informants in this study. Therefore, further inquiries are necessary to gain deeper insights into Chinese EFL teachers’ perceptions of technology integration and factors that influence their decision-making process, by involving more teachers from different universities (key, nonkey, and third-level colleges) and different provinces. In addition, it might be enlightening to interview university administrative staff and leaders, given that they might have different perceptions on technology-related policies for teachers.

Conclusion

This study contributed to a deeper understanding of existing technology acceptance theories by identifying and interpreting factors affecting university EFL teachers’ technology use in the Chinese context. The study provided implications for both theory and practice. Previous technology acceptance theories did not necessarily hold true across cultures (Srite, 2006). When they were applied in non-western developing countries, their accountability might be questioned; besides, their application in an educational setting was insufficient (Teo, 2009). This study enriched technology acceptance theories by providing insights into teachers’ perceptions of factors affecting technology use in Chinese universities. The study theoretically and empirically demonstrated the explanatory power of the TAM in the Chinese context, and more importantly extended TAM by new themes that emerged from the interview data, including teachers’ perception and individual characteristics.

In terms of practice, this study suggested that technology support and continuing professional development are urgently needed to facilitate teachers’ technology use. This would help increase the Chinese teachers’ intrinsic motivation to use technology, from the current passive compliance with hierarchical powers to internal willingness to integrate technology in teaching. In addition, the interviews expressed a concern that Chinese university EFL teachers need to improve their technological, pedagogical, and content knowledge for good design and use of technology to meet instructional objectives. The use of technology in current teaching practices still takes a rudimentary form of technology use. More advanced deliberation and preparation is necessary so that Chinese teachers will discover technology to be a good tool to improve the efficiency of their English teaching.

Appendix A

Interview protocol

Basic information: What is the name of your university? Your age? Your English teaching experience? Tell us about your experience using technology in teaching. How has it been? Did you enjoy it? Why or why not?

How do you think of the role technologies play in teaching and learning? What are the driving factors influencing your intention to use technology? If any, how do you perceive them? Do you have any specific examples you would like to share?

What are the worries or concerns preventing your intention to use technology? Do you have any specific examples you would like to share?

How familiar are you with CECR (2007) and other technology-related policies in China? What do you think of these policy requirements? How much do policies influence your teaching behavior?

Do you think your technology integration decision is influenced by others’ opinion? How do others’ opinions (leaders, colleagues, students) influence your decision?

How much does technology use influence your teaching methods or strategy choice, organization of teaching activities, and teaching efficiency and effectiveness?

Examples of additional questions:

Besides others’ opinions (e.g., leaders and students), participants mentioned about importance of technology use in the teaching competition and teaching assessment, then, some additional questions were asked, for example: How is it important that technology use in scoring teachers’ performance? Is technology use listed as a criterion in teaching competition and assessment?

Footnotes

Acknowledgments

The authors are grateful to the editor and the anonymous reviewers for their insightful comments and suggestions. Appreciation is also given to Professor Yuhuan Wang of Qingdao Agricultural University, for her encouragement and support in getting access to participants.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is supported by the research project “Theme-based Intercultural English Teaching in Chinese Universities” (Grant No. 14CWYJ20), funded by Social Science Project Management Office in Shandong Province.

Author Biographies

Fang Huang is currently a PhD candidate at the University of Macau. She is also a faculty in the College of Foreign Languages at Qingdao Agricultural University, China. Her research interests are teachers’ technology use and intercultural English education.

Timothy Teo is a distinguished professor at the University of Macau. His research interests include ICT in education, educational psychology, and quantitative methods.

Mingming Zhou is an assistant professor at the University of Macau. Her research interests are use of technology in teaching and learning, self-regulated learning, and self-identity.

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