E-Learning Readiness in Intermediate Schools in Al-Madinah

Cite this

Introduction

From the wake of the 1990s, it has become increasingly clear that we are living in the Information Age and that our societies are becoming more knowledge-based, rather than manufacturing-based. Saudi Arabia, for instance, is not exempt from this global trend. To maintain its competitiveness has opted to transform itself into an information society. As a consequence, over the past few years’ diverse life-changing reforms have been introduced in general, but in particular, in the education sector.

Cut 15% OFF your first order
We’ll deliver a custom Sciences, Tech & Engineering paper tailored to your requirements with a good discount
Use discount
322 specialists online

According to the report prepared by both IBM and the Economist in 2010, the overall ranking of e-learning readiness of Saudi Arabia is ranked 52nd of out 70 countries around the world (The Economist & IBM, 2003). Also, the Saudi Arabian Minister for communication and information technology had observed that the Saudi Arabian eLearning business was projected to reach $125m in 2008. More so, this industry was in the same way anticipated to develop at a composite yearly rate of 33% in a span of the next five years, as established in a recent study carried out by Madar Research.

With the direct support of King Abdullah bin Abdulaziz, the government has established an education development project “Tatweer” which is one of the main projects called Classroom Presentations Toolkit. it is widely mentioned that (Classroom Presentation Toolkit) is an electronic educational less that would be used daily by teachers when necessary. The users are expected to depend on the techniques of electronic presentations. This would entail being linked with medium interactivity, including the use of advanced techniques such as PowerPoint. Also, this involves the use of other similar electronic programs. These programs are explicitly designed by distinct experts and teachers specialized in diverse academic disciplines and are competent in computer usage. With the supervision from the curriculum development program, also the participation of those concerned with the King Abdullah Bin Abdulaziz Project for developing public education plays a central role in this scheme. Others who have shown interest and participated in the program include; teams members, distinct teachers capable of designing educational situations, technicians able to translate the educational situations into suitable electronic presentations, or specialized institutions able to prepare and develop such kinds of support and programs.

The last stage of e-learning that Saudi Arabia does is the specialty to establish the National Centre of E-learning & Distance Learning, known as the ELC with a cost greater than 47 million Rails [B6]. This center would monitor and manage the schools and universities that would insert e-learning into their teaching systems.

As the readiness of English language teachers, students, and Administrators to use the new technology is critical to the success of implementing e-learning in schools. It is worthy to investigate if they are prepared to embrace the new technologies in their teaching and learning activities. The purpose of this research is thus to find out how ready English language teachers, students, and Administrators of Intermediate Private and Public Schools in Al-Madinah are to use the new technologies, and what factors are influencing their readiness in terms of computer literacy, online access, e-learning, School Administration and the obstacles and difficulties that in teaching the English language. It is hoped that the experience gained from this research is beneficial to other countries exploring the use of e-learning technology in new teaching and learning activities.

Research Problem

E-learning is still at its early level and it needs more development, research study (Mousa 2002, Awaid and Hamid 2003). Contemplate on the fact that technical administrators of e-learning are fully aware that the area desperately needs the efforts of intensive and continuous development support (Saleh 1999), and as test e-learning recently of the Covenant and therefore the study learned and the experiences in the field of e-learning, the experience of e-learning in the Faculty of Communication and Information Technology in Riyadh, Riyadh College of Technology, e, and some private schools such as schools and schools in Dhahran, Riyadh, Kingdom of civil and King Faisal School, etc… (Ministry of Communications and Information Technology) Due to the recent experiences of e-learning in educational institutions in the Kingdom of Saudi Arabia, they need to make a study on the fact the use of e-learning in public schools in the Kingdom of Saudi Arabia (Alkarem 2007-2008).

The purpose of the study

  • Identify the impact of specialization (Arts, Science) to use e-learning among teachers and administrators.
  • Determine the impact of work experience (less than five years, five to nine years more than ten years) the use of e-learning among teachers and administrators.
  • Set the impact of training courses (in the use of computers) to use E-learning among teachers and administrators.
  • Verify the impact of computer literacy (in the use of computers) to use E-learning among students, teachers, and administrators.
  • Discover the impact of School Administration providing the requirements of e-learning to use E-learning.
  • Find out the impact of E-Learning knowledge to use E-learning students, teachers, and Administrators.
  • Identify the impact the teachers of the English language will face when they use E-learning in their activities or lessons.

Research Question

Based on the objectives and scope of the study, the Literature Review, and the Conceptual Framework, five-question of research questions have been formulated and used as a guide to evaluating the e-learning in the Intermediate private and public schools in Al-Madinah :

On-Time Delivery!
Get your customized and 100% plagiarism-free paper done in as little as 3 hours
Let’s start
322 specialists online
  1. What is the level of e-learning readiness in the Intermediate Private and Public Schools in Al-Madinah in terms of interaction with e-learning?
  2. What is the status of e-learning readiness in the Intermediate Private and Public Schools in Al-Madinah in terms of online access with e-learning?
  3. What is the standard, of e-learning readiness in the Intermediate Private and Public Schools in Al-Madinah in terms of computer literacy?
  4. What is the grade of e-learning readiness in the Intermediate Private and Public Schools in Al-Madinah in terms of school administration with e-learning?
  5. What are the difficulties that teachers face when are they using E-learning in their teaching?

Significance of the Study

Due to the recent experiences of e-learning in Saudi Arabia, the study of those experiences and lessons learned can provide useful information to strengthen this type of education:

  • Many of the educational institutions in Saudi Arabia trying to develop methods and methods of teaching and learning, which calls for a study of e-learning in the field to provide a knowledge base, can also be a team of researchers and decision-makers in research and education initiatives-mail.
  • Few studies deal with the experiences based on e-learning, especially since this type of education is still in its infancy in the public and private schools in Saudi Arabia.
  • Existing models have so far been designed for and assessed only against business organizations and higher education institutions such as universities (Borotis & Poulymenakou, 2004; Chapnick, 2000, Kaur & Abas,2004). Up till now, there have only been very few validated models for primary and secondary schools.
  • Given the significant investment of government resources and IT implementation into schools in Saudi Arabia, the educational establishment (as well as the teachers themselves) urgently need a sound and thoroughly validated model to assist in the integration of e-learning in schools.

Literature Review

Acceptance of e-learning (AEL)

Dillon and Morris (1996, p. 4) defined students’ acceptance as “the demonstrable willingness within a user group to employ information technology for the tasks it is designed to support”.

Learners who accept e-learning as a learning medium have not been well-researched.

Hong, Lai, and Holton (2003) explored an e-learning based scholarly course at the University of Malaysia in Sarawak and established that an estimated ratio of 50% about both student and teachers participants had demonstrated a soaring standard of endorsement of the web-based schooling. The scholars who had embraced and accepted web-based illustrates that web-based learning was opportune and adaptable. On the other hand, some scholars had complications with the web-based learning setting. They established web-based learning to be a novel learning occurrence and felt that they required more direct time to become accustomed to the learning atmosphere (Hong et al., 2003). Meanwhile, Poon et al. (2004) examined dissimilar e-learning settings within copious home-based universities in Malaysia and consequently reported that a large number of the concerned students were not totally at ease with this method of learning.

Likewise, Poon et al. (2004) observed that one of the key reasons was that the scholars were not wholly conscious or had little contact with the e-learning apparatus as well as settings. On the positive side, Hong et al. (2003) and Poon et al. (2004) claimed that learners, by and large, approved that e-learning was helpful and was also fundamental to their studies. nevertheless, past studies present several issues such as scholars’ and instructors’ traits (Hong et al., 2003; Ndubisi, 2004; Poon et al., 2004), expert support and structure (Poon et al., 2004; Rafaeli & Sudweeks, 1997), institutional support (Passmore, 2000; Latifah & Ramli, 2005), course substance as well as knowledge management (Selim, 2005; Rosenberg, 2001), and online undertakings and discussion assemblages (McDonald, 2001; Webb, Nemer, Chizhik, & Surgue, 1998) could manipulate learners’ approval of e-learning.

Get a custom-written paper
For only $13.00 $11/page you can get a custom-written academic paper according to your instructions
Let us help you
322 specialists online

Students’ characteristics

Poon et al. (2004), Folorunso, Ogunseye, and Sharma (2006), Selim (2005), and Volery and Lord (2000) claimed that students’ attributes such as their gratification with period and place buoyancy of the system; students’ participation and involvement; students’ cognitive commitment; students’ degree of self-confidence; learners’ know-how self-efficacy; students’ inventiveness, enthusiasm, and students’ apprehension could manipulate approval of e-learning amongst students.

Internet service and knowledge of one of the hindrances that fail to employ e-learning. There is a great concern among researchers regarding the issue of the digital divide. As is well known, a significant section of individuals still does not have access to the Internet or do not have the required IT skills. Consequently, in most countries, e-learning is not for everyone (Kearsley, 2002).

Learning, however, from the screen is not a natural method. For a student to adjust his/her traditional learning strategies to meet the challenges of the new format there is a need for training. According to Laurillard “Hypertext is not a stand-alone learning medium… it needs additional support from the teacher, just as library work does,” (1993).

Ogunseye and Sharma (2006) established that lack of knowledge, low level of computer knowledge in addition to cost were set as the critical factors influencing the tolerability of e-learning by scholars and trainers of Nigerian universities.

E-Learning has broadened the learner’s use of technology and has switched control and responsibility upon the learners. All the participants, learners, and facilitators interplay extensively with computers.

Teachers

Teacher preparation has grown to be one of the essential factors which sway e-Learning progression (e-learning readiness rankings). E-Learning preparation is measured as the paramount predictor which is statistically considerable for both e-Learning recognition, and e-Learning promptness in Malaysia (Agboola 2006). It ought to be noted that e-Learning development contains both positive policy development and well-planned employment strategies.

Hong et al. (2003) and Shea, Swan, Fredericksen, and Pickett (2001) are certain that tutors played an imperative part regarding successful e-learning familiarity. Lecturers must certify the most advantageous level of interactions and discussions with students to develop the e-learning experience. Additionally, trainers could cause and stimulate students to acknowledge e-learning settings (Ndubisi, 2004; Ndubisi &Chukwunonso, 2004; Selim, 2005).

As claimed by Salmon (2000); Abouchedid and Eid (2004), instructors’ attributes such as recognition, optimistic behaviors, facilitation, information sharing in addition to resourcefulness could encourage interactions and prompt students to study in an e-learning atmosphere.

Charalambos Vrasidas (2010) mentioned in his article that the teachers realize the benefits of ICT integration, many of these teachers are resistant to integrating technologies and using online learning environments. This is due to several factors, such as a decrease in time, the ill-structured design of the public school curriculum, and the lack of infrastructure and tools to support teachers and learners more effectively. To aid teachers in integrating technologies, more robust skillful development programs, as well as appropriate technologies, need to be developed programs that would provide continuous support to teachers, so they can deal with these challenges and problems.

(Heinrich, 1995; Fullan, 1994; Wang, 2002) sustains the observation that the manner teachers instruct is a creation of their schooling, preparation as well as experiences. It is not coherent to look ahead to teachers to expand their existing educational procedures if they have not been maintained with adequate and apposite training on how to merge ICT (Information and Communication Technology) and new coaching skills into their tutoring programs.

Teachers’ experience in the use of computers in education will reduce the importance of computers in teaching. According to Al-Muhaisin (2000) conducted the study determines the reality of the use of computers in colleges of education in Saudi universities in terms of hardware, the possibilities, and the use of faculty members have, and the result shows that the use of computers in low even they have a high trend in the use of computer in their teaching.

Administrators

Poonsri pointed out in this research about “Readiness of eLearning Connectivity in Thailand” in the segment reactions from the open-ended queries relating to strategies to augment the value of eLearning. It has been established that there was a lofty requirement for teacher preparation for eLearning in addition to improved conveniences for both hardware and networks. It is imperative to note that school superintendents indicated the call for for having proper course ware in view of the fact that Thai online course resources are limited (Poonsri 2007).

“ICT has penetrated tertiary education, but has had more impact on administrative services (e.g. admissions, registration, fee payment, purchasing) than on the pedagogic fundamentals of the classroom.” (OECD, 2005, p. 15)

Interestingly, school administrators all over the world are recognizing some basic classroom technology requirements. Blanco (1996) notes that all instructors should have a computer for use in the classroom, and their offices and classrooms must include telecommunication capabilities so that they and their students can easy access to e-mail and the internet. He also recommends that institutions should consider technology use as a central component in advance, and tenure decisions, and that teachers should be encouraged to attend technology-related conferences in order to learn from other’s experiences.

Technology

In regard to ICT (Information and communications technology) contemporary learning relies heavily on the exploitation of ICT platforms in all possible but dynamic procedures (vertical and horizontal). The phrase e-education (electronic education) is presently used to signify this brand of learning. This task aims at the creation of a nationalized institute for e-Learning to provide diverse academic service. This would entail preparing core regulations, strategies and policies central the e-learning process, preparing an incorporated representation for e-learning using benchmark specifications, improving quality assurance standards for e-learning, approving quality assurance documentations for e-learning schemes, evaluating the competence of diverse in technologies being exploited as aids for the e-learning procedures.

Organisations in both public and private industry increasingly view continuous learning as the basic to maintaining their competitive advantage (Goldstein & Ford, 2001). E- Learning is considered the suitable solution to the call for a just-in-time, accessible, ubiquitous method to providing learning at a little cost (Borotis & Poulymenakou, 2004). Because the ways in which the online curriculum is delivered are new – and unlike the traditional approach – a major factor influencing the achievement of e-learning is teacher training. Instructors must themselves be develop in how to take advantage of these updated teaching methods. An ineffective teacher can waste the time of 30 or 40 students. But bad teaching online can touch thousands. ‘We can care- ate mass damage quickly’.” (The Economist, 2003; p. 12).

Wells (1999) argued that the delivery of on-line instruction is laboriously dependent on network technologies. Piccoli et al.(2001) agreed and further mentioned that technology quality, reliability and accessibility is important elements within the e-Learning environment. Serdiukov (2001) divided technologies into computer technology (e.g. spreadsheets, word processors and presentation software) and telecommunications technology (e.g. e-mail, bulletin boards and chat rooms).

As indicated by Sahney, Banwet and Karunes (2003) that education is a service industry; as they study education industry by measuring the quality of its services and the acceptation of its customers. The most important is the perceived quality of the institution and the graduates it produces. Further with the advancement of the ICT, the requirement of the industry change ever more rapidly as industry become more flexible, adopts changing technologies and claims different skills and expertise. Thus, conventional distance education in the nation also faced the tidal wave of the ICT on the introduction of the e-learning approach.

Al-Kahtani (2001) argues that to successfully integrate computer technology into language learning classrooms, institutions need to understand the point that most strongly affect technology use, and to provide their faculties with the provide required to blend the technology into their teaching methods. In addition, teachers need to be apprise of the role that technology can play in their classrooms.

In support of English courses, the Ministry began developing supplementary e-learning materials for students and teachers. Some private companies developed additional software for the secondary school English curriculum that included exercises and other supporting tools (Bedaiwi 2007). Today, education in Saudi Arabia is facing huge reforms as King Abdullah pursues a new academic endeavour, “Tatweer”. This project includes the requalification of teachers and educators, curriculum development, and conscientious development of the school environment.

Computer literacy and Online Access

According to the communications and information technology commission in Saudi Arabia. in their study about “Computer And Internet Usage In The Kingdom Of Saudi Arabia (2007 – 2009)” Internet penetration is relatively high among education institutes in Saudi Arabia, at 75%. However only 25% of the computers in education institutes have access to the internet and only 11% of the students have access to the internet. The number of students accessing the internet increase along with the level of education from preliminary to college/university/technical/institutes see Figure 1.

ALL PRELIMNAR PRIMARY SECONDARY COLLEGE
2007 2008 2007 2008 2007 2008 2007 2008 2007 2008
Ave. # of students 658 621 568 519 532 603 800 639 1708 1148
Ave. # of computer 28 34 18 16 18 15 32 47 121 120
% of computers with Internet access 20% 25% 19% 17% 22% 24% 18% 27% 45% 47%
% of student accessing
Internet
9% 11% 6% 6% 8% 6% 12% 17% 25% 39%

Figure 1.

Internet usage will keep on growing rapidly in the KSA. In addition to the new Internet structure that can cut the prices of Internet access, other factors can speed up the growth of Internet usage in Saudi Arabia.

One reason for the growth is that 60 % of the Saudi population comprises teenagers and young adults who are adapting to new technologies faster than expected ( internet gov so ).

Sultan & Alphentuch(1999) survey of 120 teachers and 580 secondary schools students revealed that more than 70% of teachers and students support the use of computers in the classroom; that computer acquisition in the Kingdome in the heights in the region, where 40% of teachers and 37.4% of students in the study own computer set that computer set has increased in public secondary schools to hit the number of 24045 in 1998, thus decreasing the ratio of students to computer sets to one computer set for every 12.4 students in that year and only 30% of the teacher were not in favor the use of computer in the school because of the language barrier, information illiteracy, perceived increase in teaching workload and need to learn new teaching method.

Technology Acceptance Theories and models

Introduction

Researchers in the area of computer-assisted language learning are interested in investigating the theories and models that will have power in predicting and explaining behavior across many domains. The main objectives of these studies are to investigate how to promote usage, the readiness of users of e-Learning, and also examine what hinders usage and intention to use the technology. Each prominent technology acceptance theory or model which has not been superseded by more recent research has different premises and benefits. It is therefore important to study them intentionally since it is expected that theoretical concepts from these theories will help to provide a sound basis for the theoretical framework for creating a research model that could properly demonstrate the acceptance of Technology for this research.

The Technology Acceptance Model (TAM)

This study is based on the technology acceptance model (TAM) proposed by Davis (1989) based on the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975) in psychology research and which has been extended and applied to different information technologies, work environments, and end-users. In the TAM, Davis proposes that the effect of other variables on technology acceptance is mediated by two individual beliefs: perceived ease of use (PEU) and perceived usefulness (PU). Perceived usefulness (PU) – This was defined by Fred Davis as “the degree to which a person believes that using a particular system would enhance his or her job performance “.Perceived ease-of-use (PEOU) Davis defined this as “the degree to which a person believes that using a particular system would be free from effort” (Davis, 1989).

TAM was originally developed for studying technology at work. Later it has been used as such or modified to study user acceptance of consumer services such as Internet services or e-commerce (Kaasinen, 2005). The Technology Acceptance Model constitutes a solid framework for analyzing issues that may affect user acceptance of technical solutions. As Davis and Venkatesh (2004) have proved, the model can be upgraded from the original purpose of studying user acceptance of existing products to study planned product concepts, e.g. in the form of mock-ups. This indicates that TAM could also be used in connection with technology development projects and processes to assess the value of proposed solutions. Applied in this way, the model also supports the human-centered design approach.

TAM is well thought-out as one of the most overriding and frequently employed theories for illuminating an individual’s reception of information systems (Lee et al. 2003) since it advocates for a small number of factors − supposed usefulness and supposed simplicity of use − which mutually adds up for usage. These aspects are explicit, uncomplicated, clear to comprehend, and can be influenced through structure design and use (Taylor and Todd 1995a). In addition, it has been tried and tested more than a few times in experimental research, and the tools utilized with the model have been demonstrated to be of eminence and have capitulated statistically dependable results (Legris et al. 2003; Moon and Kim 2001).

TAM
TAM (Davis 1989).

even though TAM has in general been used to elucidate users’ primary objective to espouse an information system after a short interlude of contact with the system, it has as well been engaged for prognosticating users’ spur to utilize an information system after having an elongated interlude of knowledge with the system. Taylor and Todd (1995b) observed that TAM can be modified to comprehend the conduct of both untested and knowledgeable users, with diverse prominence on the basis of intent. In addition, TAM has been exploited in longitudinal researches (Venkatesh and Davis 2000; Venkatesh and Morris 2000; Kim and Malhotra 2005) in addition to the studies attesting that both alleged usefulness and alleged ease of application remain considerable verifiers of behavioural objective over time, as well as the major effectual of alleged simplicity of use on supposed convenience. This verification means that TAM orientations are proper for foretelling the aim to persist exploiting the information system. Therefore, this project hypothesizes that:

H1: alleged usefulness of e-learning will optimistically persuade citizen’s persistence objective to utilize e-learning in school.

H2: alleged simplicity of use of e-learning will optimistically persuade citizen’s persistence intention to exploit e-learning in school.

H3: alleged easiness of use of e-learning will absolutely manipulate perceived value of e-learning in school.

The Technology Acceptance Model (TAM)

Research replica of citizen’s continuation objective to utilize e-learning in school.

For the time being, TAM recommend that alleged ease of use as well as alleged effectiveness of technology are forecasters of user approach towards making use of the know-how, ensuing behavioural intents and genuine usage. alleged ease of application was also considered to manipulate alleged expediency of technology.

Original technology acceptance model
Original technology acceptance model(Davis, 1989).

TAM has been functional in various studies testing user core comprehension of IT, for instance, word processors (Davis et al., 1989), spreadsheet appliances (Mathieson, 1991), internet, and the email e-mail

(Szajna, 1996), network browser (Morris & Dillon, 1997), telemedicine expertise (Hu, Chau, Sheng, & Tam, 1999), websites (Koufaris, 2002), e-partnership (Dasgupta, Granger & Mcgarry, 2002), and blackboard (Landry, Griffeth & Hartman, 2006). In this project, e-learning was measured as a method that allows exploitation of the Internet as well as web expertise in achieving its mission of transferring information to and interrelated with the students through a computer crossing point in addition to expanding the use of computers by instructors and administrators in matters of education and managerial.

The technology acceptance model (TAM) is generally considered as the most efficacious and common theory in the information systems field (Lee et al., 2003), and has been received through affluent empirical supports. TAM is based on the theory of reasoned action (Fishbein and Ajzen, 1975), which mentioned how attitude impacted behavior. TAM related the two core predictors: perceived usefulness and perceived ease of use and the dependent variable: behavior intention. Since TAM was presented in 1989, researchers adapted this model into several research streams. Some researches spotlighted on identifying the determinants of key predictors, namely, perceived ease of use and perceived usefulness (Karahanna and Straub, 1999; Koufaris, 2003; Wixom and Todd, 2005). Some papers broadened the TAM by other theories to increase the predictive power (Dishaw and Strong, 1999; Venkatesh et al., 2003; Gefen, 2004). Others would use the meta-analysis to test the effects by involving user type and usage type (King and He, 2006), the competing role of behavioral intention, facilitating condition, and behavioral expectation (Venkatesh et al., 2008), environment-based voluntariness (Wu and Lederer, 2009).

The Technology Acceptance Model Approach

The technology acceptance model is an information system theory, which purpose is simply to predict and explain the user acceptance of information technology. The model addresses the reasons why users either accept or reject a particular piece of information technology. The revised model by Davis et al. (1989) is constructed from external variables (external stimulus), perceived usefulness and perceived ease of use (cognitive response), behavioral intention, and actual usage (behavior). (Davis et al. 1996)

The deep-seated idea of the presumption is that alleged usefulness and alleged relief of use manipulate the users’ objective to use IT either unswervingly or interceding via approach towards the deeds, leading to the concrete tradition of the scheme. Attitude Towards (AT) and Behavioural Intention (BI) are common with the Theory of Reasoned Action. Perceived ease of use (PEOU) has a strong influence on AT through perceived usefulness, but also directly. Perceived Usefulness (PU) has a strong direct effect via both AT and BI. PU was defined as “the degree to which a person believes that using a particular system would enhance his or her job performance”. “A system high in perceived usefulness, in turn, is one for which a user believes in the existence of a positive use-performance relationship”. PEOU was described as “the degree to which a person believes that using a particular system would be free from effort”. (Davis, 1989). The original TAM was revised by leaving attitude from the model, as empirical validation proved that intention to use is only partly mediated by attitude (Davis and Venkatesh. 19961).

The Technology Acceptance Model and e-learning readiness

Several field studies adopt a technology acceptance model as a research method, Zemskey and Massy’s study (2004) only considered the US context. One example is a 2005 report on e-learning maturity in the NZ tertiary sector (Marshall, 2005), which is based on the data collected from six of the eight NZ universities and three polytechnics. Marshall’s study evaluated the institutional capability to sustain and deliver e-learning.

Another NZ university research study (Butson, 2005) on the use of web-based technologies recommends that e-learning adoption may be driven by the technology itself as, according to the survey data, teachers see no significant positive in using web-based technologies and there are no institutional or faculty drivers for web-based teaching. If this hypothesis is true, and the technology (LMS in this case) does drive e-learning adoption, poor virtue of e-learning is to be expected (Elgort, 2005).

Rogers (1995) displays that providing incentives for the adoption of innovation may change the patterns of appropriation; the use of incentives may guide to adoption by individuals different from those who would have adopted it otherwise, and may negatively affect the sustainability of adoption. It may increase the rate of adoption but lead to a diminution in quality.

Work done by Elgort (2005) on E-learning adoption clearly shows that the e-learning adoption decision is frequently motivated by student pressure. Elgort noted that “like organizational incentives, student pressure may facilitate the rate of adoption of e-learning at the expense of its quality, resulting in a ‘surface’ approach to e-learning”.

Abdel-Wahab (2008) wrote on “modeling students’ intention to adopt e-learning: a case from Egypt”, and the results of the study suggest that the best subset of predictors that can be used in modeling a student motivate to adopt e-learning involves: attitudes towards e-learning, the usefulness of e-learning, ease of e-learning use, pressure to use e-learning, and the availability of resources needed to use e-learning.

Ndubisi (2004) also found out from his study that ‘attitude has an important direct influence on intention to adopt e-learning. Attitude is anchored usefulness, ease of use, and system’s security. Alleged behavioral control was also established as another imperative determinant of communication. Ndubisi concluded that “to enhance e-learning adoption intention and in turn acceptance among Malaysian students, interested parties to this learning arrangement must try to build favorable attitude through enhanced usefulness and ease of use perceptions, as well as security”.

Research Approach

To accomplish the objectives of the study, the survey instrument was developed to gain as much information as possible by using the theory of technology acceptance, regarding the factors that affect students, English teachers, and the administrator’s intentions to adopt e-learning and the readiness of using e-learning in the school.

The overall research project, of which this paper reports an early set of results, is an inductive study designed to evaluate the e-learning readiness of students, English language teachers, and administrators in Intermediate private and public schools in Al-Madinah. The overall study will survey the English language teachers, students, and administrators from a range of schools in Al-Madinah, to ascertain background, experience, and satisfaction with existing methods of e-learning preparation.

References

Abdel-Wahab (2008) Modeling Students’ Intention to Adopt E-Learning: a case from Egypt. EJISDC (2008) 34, 1, 1-13.

Abouchedid, K., & Eid, G.M. (2004). E-learning challenges in the Arab world: Revelations from a case study profile. Quality Assurance in Education, 12(1), 15-27.

Adult Learning in Asia. (Open University of Hong Kong, P.R. China, 2005.

Agbool, A. K. (2006), “Assessing the Awareness and Perceptions of Academic Staff in Using E-learning Tools for Instructional Delivery in a Post-Secondary Institution: A Case Study [electronic version],” The Innovation Journal: The Public Sector Innovation.

Alkarem, Abdul Aziz Al-budl (2007-2008).” The verity of the use of e-learning in private school” kingdom school” in Riyadh” King Saudi UniversityJournal, vol. 11, pp. article 4.

Al-Kahtani, Saad Ali (2001) Computer-assisted language learning in EFL instruction at selected Saudi Arabian universities: Profiles of faculty. Ph.D. dissertation, Indiana University of Pennsylvania, United States –Pennsylvania.

Al-Muhaisin, I. A. (2000). The Barriers in utilizing computers in Colleges of Education in Saudi Universities. Almajallah Altarbawiah, Volume 15, Issue 57, pp. 31-70. [In Arabic]

Aurillard, D. (1993) Rethinking University Teaching: a framework for the effective use of educational technology (London, Routledge). (Buythe 2001 edition in paperback from Amazon)

Awaid, Mohamed Saleh Hamid, Ahmed bin Abdullah, (2003 ). E-Learning in the Faculty of Communication and Information in Riyadh: A Case Study, Working Paper Introduction to Education Seminar is open in the King Faisal School, Riyadh.

Bedaiwi, T. (2007). Saudi Secondary Islamic teachers’ perception of using computers to teach Islamic courses. J.King Saud university, Educ. Sci. & Islamic studies, 20(1).

Blanco, C. (1996). Faculty use of technology resources: frequency, purpose, and instructional assignments for students. Unpublished doctoral dissertation, the university of Arizona.

Borotis, S. and Poulymenakou, A. (2004). e-Learning Readiness Components: Key Is- sues to Consider Before Adopting e-Learning Interventions. Web.

Butson, R. (2005). Determination of New Zealand tertiary institution e-learning capability: an application of an e-learning maturity model – Report on the e-learning maturity model evaluation f the New Zealand tertiaty sector. Web.

Chapnick, S. (2000). Are You Ready for E-Learning? Web.

Charalambos Vrasidas.(2010). “Why Don’t Teachers Adopt Technology?” Communications and information technology commission in Saudi Arabia.

(2007 – 2009). “Computer And Internet Usage In The Kingdom Of Saudi Arabia” Communications and Information Technology Commission

(2008),” Internet Usage in the Kingdom of Saudi Arabia” The Second year ( 2008 ) Report. Web.

Dasgupta, S., Granger, M. & Mcgarry, N. (2002). User acceptance of e-collaboration technology: an extension of the technology acceptance model, Group Decision and Negotiation, 11, 87-100.

Davis, F. D. and Venkatesh, V. (2004). Toward preprototype user acceptance testing of new information systems: implications for software project management. IEEE Transactions on Engineering Management, Vol. 51, No 1.

Davis, F.D. (1989). “Perceived usefulness, perceived ease of use, and user acceptance of information technology”. MIS Quarterly, 13 (3), pp. 318-340.

Davis MA, Radnedge L, Martin KA, Hayes F, Youngren B and Austin SJ (1996) The P1 ParA protein and its ATPase activity play a direct role in the segregation of plasmid copies to daughter cells. Mol Microbiol, 21, 1029–1036.

Dillon, A., & Morris, M.G. (1996). User acceptance of information technology: Theories and models. Annual Review Of Information Science and Technology, 31, 3-32.

Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1), 9-21.

Elgort, I. (2005). E-learning adoption: bridging the chasm, ascilite 2005: Balance, mobility: maintaining the momentum?.

Fishbein, M. & Ajzen, I. (1975), Belief, attitude, intention and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.

Folorunso, O., Ogunseye, O.S., & Sharma, S.K. (2006). An exploratory study of the critical factors affecting the acceptability of e-learning in Nigerian universities. Information Management and Computer Security, 14(5), 496-505.

Gefen, D. (2004). What makes an ERP implementation relationship worthwhile: linking trust mechanism and ERP usefulness. Journal of Management Information Systems, 21 (1), 263-288.

Goldstein, I. and Ford, J. (2001). Training in Organizations (4PthP Ed.): Wadsworth Heinrich, P. (1995). Developing a Whole School IT Policy. London: Pitman.

Hong, K.S., Lai, K.W., & Holton, D. (2003). Students’ satisfaction and perceived learning with a Webbased course. Journal of Educational Technology & Society 6(1). Web.

Hu, P. J., Chau, P. Y. K., Sheng, O. R. L. and Tam, K. Y. (1999) Examining the technology acceptance model using physician acceptance of telemedicine, Journal of Management Information Systems, 16.

InfoDev (2001). E-Readiness as a Tool for ICT Development. Web.

Kaasinen, Eija. 2005. User acceptance of mobile services – value, ease of use, trust and ease of adoption. (http://www.vtt.fi/inf/pdf/publications/2005/P566.pdf) VTTIT , Espoo. 151 s. VTT Publications 566. ISBN 951-38-6640-8. 951-38-6641-6.

Karahanna, E. and D.W. Straub. (1999). “The psychological origins of perceived usefulness and ease-of-use,” Information & Management, 35 , 237-250.

Kaur, K. and Abas, Z. (2004). An Assessment of e-Learning Readiness at the Open University Malaysia. International Conference on Computers in Education (ICCE2004), Melbourne, Australia.

Kearsley, G. (2002).online learning for everybody?. Educational Technology, 42(1), 41–44.

Kim, S.S. and Malhotra, N.K. (2005) “A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena”, Management Science, Vol. 51, No. 5, pp. 741−755.

King, W. and He, J. (2006). A Meta-Analysis of the Technology Acceptance Model. Information and Management, 43 (6), 740-755.

Koufaris, M. (2003). Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior,” Information Systems Research, Volume forthcoming,

Landry, B.J.L., Griffith, R. , & Hartman, S. (2006). Measuring student perceptions of blackboard using the technology acceptance model. Decision Sciences, 4(1), 87-99.

Latifah, A.L., & Ramli, B. (2005). Priority-satisfaction survey: A tool in developing effective retention strategies. Paper presented at the Conference on Research in Distance.

Lee, Y., Kozar, K.A. and Larsen, K.R.T. (2003) “The Technology Acceptance Model: Past, Present, and Future”, Web.

Legris, P., Ingham, L. and Collerette, P. (2003) “Why Do People Use Information Technology? A Critical View of the Technology Acceptance Model”, Information & Management, Vol. 40, No. 3, pp. 191−204.

MacDonald, J. (2001). Exploiting online interactivity to enhance assignment development and feedback in distance education. Open Learning, 16(2), 179-189. Web.

Marshall, S. (2005). Determination of New Zealand Tertiary Institution E-Learning Capability: An Application of an E-Learning Maturity Model: Report on the E-Learning Maturity Model Evaluation of the New Zealand Tertiary Sector. Report to the New Zealand Ministry of Education. 132pp.

Mathieson, K. (1991), “Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory ,” Information Systems Research, 2, 173-191.

Moon, J. and Kim, Y. (2001) “Extending the TAM for a World-Wide-Web Context”, Information & Management, Vol. 38, No. 4, pp. 217−230.

Morris, M.G., & Dillon, A. (1997). The influence of user perceptions on software utilization: application and evaluation of a theoretical model of technology acceptance, IEEE Software, 14(4), 56-75.

Musa, Abdullah bin Abdul Aziz (2002 ) e learning concept, characteristics, benefits, obstacles, working paper submitted to the School of the Future Symposium, King Saud University College of Education.

Ndubisi, N. O.; Gupta, O. K and Ndubisi, G. C. (2004). The Mijuls’ model of computing: Integrating the moderating impact of users’ persona into the technology acceptance model, Journal of Global Information Technology Management.

Ndubisi, N. & Chukwunonso, N. (2004) On-line learning adoption intention: Comparing the predictive power of two competing models, in Transforming Knowledge into Wisdom, Proceedings of the 27th HERDSA Annual Conference, Miri, Sarawak, 4-7 July 2004: pp 242.

OECD (2005). E-learning in Tertiary Education: Where do we stand? Passmore, D.L. (2000). Impediments to adoption of web-based course delivery among university faculty. ALN Magazine, 4 (2).

Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic it skills training. MIS Quarterly, 25, 4, 401-426.

Poon, W.C., Low, L.T., & Yong, G. F. (2004). A study of Web-based learning (WBL) environment in Malaysia. The International Journal of Educational Management, 18(6), 374-385.

Poonsri Vate-U-Lan (2007).” Readiness of eLearning Connectivity in Thailand”. Rafaeli, S., & Sudweeks, F. (1997). Networked interactivity. Journal of Computer-Mediated Communications, 2(4).

Rogers, E. M. (1995). Diffusion of innovation: New York: The Free Press Rosenberg, M.J. (2001). E-learning: Strategies for delivering knowledge in the digital

age. New York: McGraw Hill. Web.

Salmon, G. (2000). E-moderating: The key to teaching and learning. London: Kogan Sahney, Sangeeta, Devinder Kumar Banwet, and Sabita Karunes (2003).

“Enhancing Quality in Education: Application of Quality Function Deployment – An Industry Perspective,” Work Study,Vo1.52, No.6, p297-309.

Saleh, Bader Abdullah, (1999).”The development of technical education in the Kingdom of Saudi Arabia in the light of trends in the sphincter area,” research paper presented to a seminar of information technology in education, King Saudi University.

Selim, H.M. (2005). Critical success factors for e-learning acceptance: Confirmatory factor models.Computers and Education. Retrieved February 9, 2007.

Serdiukov, P. 2001. Models of Distance Higher Education: Fully Automated or Partially Human? Educational Technology Review. Web.

Shea, P. J., Swan, K., Fredericksen, E. E., & Pickett, A. M. (2001). Student satisfaction and reported learning in the SUNY Learning Network. In J. Bourne & J.C. Moore (Eds.), Elements of Quality Online Education (Vol. 3). Olin & Babson Colleges: Sloan Center for Online Education.

Sultan, Abdul Aziz bin Abdullah and Alphentuch, Abdul Qader bin Abdullah.(1999). Internet in Education: e-school project, a Persian Gulf, No. 21. Web.

Taylor, S. and Todd, P.A (1995a). Understanding Information Technology Usage: A Test of Competing Model, Information Systems Research, 6 (2), 144-176.

Taylor, S. and Todd, P.A. (1995b) “Assessing IT Usage: The Role of Prior Experience”, MIS Quarterly, Vol. 19, No. 4, pp. 561−570.

The Economist. (2003). The 2003 e-Learning Readiness Rankings: A White Paper from the Economist Intelligence Unit 2003. Web.

Venkatesh, V. and Davis, F.D. (2000) “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies”, Management Science, Vol. 46, No. 2, pp. 186−204.

Venkatesh, V. and Morris, M.G. (2000) “Why Don’t Men Ever Stop to Ask for Acceptance and Usage Behavior”, MIS Quarterly, Vol. 24, No. 1, pp. 115−139.

Venkatesh, V. and Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Science, 39 (2), 273-312.

Venkatesh, V. and Davis, F.D.(1996). “A Model of the Antecedents of Perceived Ease of Use: Development and Test,” Decision Sciences (27:3), 1996, pp. 451-481.

Volery, T., & Lord, D. (2000). Critical success factors in online education. International Journal of Educational Management, 14(5), 216-223.

Wang, Y. M. (2002). When Technology Meets Beliefs: Preservice Teachers’ Perception of the Teacher’s Role in the Classroom with Computer. Journal of Research on Technology in Education, 35(1), p.150-161.

Webb, N.M., Nemer, K., Chizhik, A., & Surgue, B. (1998). Equity issues in collaborative groupassessment: Group composition and performance. American Educational Research Journal, 35(4),607-651.

Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102.

Wu, J. and Lederer, A. (2009). A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology. MIS Quarterly, 33 (2), 419-432.

Zemsky, R. and Massy, W (2004). Thwarted innovation: what happened to e-learning and why. The Learning Alliance at the University of Pennsylvania. Web.

Cite this paper

Select style

Reference

Premium Papers. (2022, November 2). E-Learning Readiness in Intermediate Schools in Al-Madinah. Retrieved from https://premium-papers.com/e-learning-readiness-in-intermediate-schools-in-al-madinah/

Reference

Premium Papers. (2022, November 2). E-Learning Readiness in Intermediate Schools in Al-Madinah. https://premium-papers.com/e-learning-readiness-in-intermediate-schools-in-al-madinah/

Work Cited

"E-Learning Readiness in Intermediate Schools in Al-Madinah." Premium Papers, 2 Nov. 2022, premium-papers.com/e-learning-readiness-in-intermediate-schools-in-al-madinah/.

References

Premium Papers. (2022) 'E-Learning Readiness in Intermediate Schools in Al-Madinah'. 2 November.

References

Premium Papers. 2022. "E-Learning Readiness in Intermediate Schools in Al-Madinah." November 2, 2022. https://premium-papers.com/e-learning-readiness-in-intermediate-schools-in-al-madinah/.

1. Premium Papers. "E-Learning Readiness in Intermediate Schools in Al-Madinah." November 2, 2022. https://premium-papers.com/e-learning-readiness-in-intermediate-schools-in-al-madinah/.


Bibliography


Premium Papers. "E-Learning Readiness in Intermediate Schools in Al-Madinah." November 2, 2022. https://premium-papers.com/e-learning-readiness-in-intermediate-schools-in-al-madinah/.