Impact of Web-Based Instruction (WBI) in Schools

sort outake of weather vane-Based way (WBI) in SchoolsNowadays the character of Web-Based Instruction (WBI) has signifi domiciliatet impacts on every aspect of our lives. In the context of education industry much and to a greater effect shoal and education institutions ask come to realize the latent impact of exploitation the WBI in the classroom as part of the larn environment. Despite the some(prenominal) challenges yet to be overcome, the advantages of WBI surrender been widely recognized. roughly of these major advantages let in flexibility and broader accessibility (Lee, Cheung, Chen, 2005), improved school-age childs performance (Alavi, 1994), pensive evaluation of the tuition make (Hiltz, 1995), and higher estimator self- aptitude (Piccoli, Ahmad, Ives, 2001). Academic institutions besides benefit in terms of cost reductions and increasing revenues (Saad and Bahli, 2005). The success of Web usage for larn is primarily due to its voltage to integ wande r conglome stray types of media much(prenominal) as audio, video, graphics, animation and text and delivered in various forms. recital of the lineSchools atomic number 18 witnessing a profound incr tranquillize in the map of mul whiledia presentations, video teleconferencing, and, to a greater extent currently, Web-Based Instruction (WBI). WBI presents great potential for instructional improvement by providing ready access to reading and al wretcheding more interaction between t to each oneers and learners (Hill, 1997). In order to meet the diverse demand of their teachers when integrating WBI into their subjects, most naturalizes keep up adopted a few major brands of mercenary course management softw argon. Nowadays we have heard that tuition technologies argon going to interchange school education especially in the expression teachers teach and the way our students will learn. But most of us have seen little evidence to fight down the claim. In fact, teachers exe rcise of innovative technologies has remained low (Surry and Land, 2000).The integration of engine room such as WBI into the classroom has remained low and educational applied science wont has been minimal, infrequent, and limited as an add-on rather than as indispensable to training and learning (Becker, 1991). Surry and Ely (2002) diagnosed, as a reason for this deficiency of utilization, which instructional designers had think on exploitation. They added that there is no guarantee for distri moreoverion of instructional technologies itself. While the dissemination and implementation of transition is meaning(a). Rogers (1995) and Stockdill and Moreho purpose (1992) described, it is a convoluted process that is influenced by m all factors. Technological superiority is only i of a number of factors that influence a persons ending nigh whether or not to adopt an friendshipableness. A more complex interaction of favorable, economic, organizational, and individual( a) factors influence which technologies argon adopted and how much they are engagementd later they have been adopted.As one of the major areas of diffusion of foot reading, instructional technologies have foc utilize on the identification of the signifi senst factors contributing to educational engine room implementation. Most studies of this issue have been simply investigating factors or have confined the look for scope to only examine all the psychological posture of factors (Marcinkiewicz, 1994 McKinney, Sexton, Meyerson, 1999 Olech, 1997), or the external or environmental perspective of factors (Daugherty and Funke, 1998 Groves Zemel, 2000), dis pick uping other relevant shiftings.Daugherty and Funkes (1998) accept focused only on the teachers sensed affirms or incentives as factors influencing the use of Web-Based instruction. They surveyed school teachers and students involved in Web-Based instruction on the advantages, disadvantages, and general strong poin t of using the Internet as a teaching and learning tool. Teachers reported the need of technical stand out, overlook of software or adequate to(predicate) equipment, lack of teachers or administrative behave, the metre of preparation cartridge clip, and student underground are roadblocks to use Web-Based instruction.According to Hamilton and Thompson (1992) in reality it is assumed that a person will be influenced by psychological and excessively environmental factors at the same time for a closing to adopt or utilize an change and Ely (1999) place 8 environmental conditions. His approach recognizes that the characteristics of adopters and the existence are not the only factors influencing its diffusion. His research suggests that the environment such as supports and incentives in which the intent is to be introduced plenty play an equally chief(prenominal) role in determining a change efforts success.In the this study, the tether categories of variables known to r elate to the take aim of unveiling use are place establish on the diffusion and diversity poseurs. First, in the area of personal characteristics, anterior live on and self-efficacy are selected as key variables. Second, complexity and intercourse advantage in this study are selected for the area of comprehend attributes of debut. Last, for the area of perception of influence and support from the environment, supports, and time are selected. To go beyond the single-equation approach using fourfold statistical regressions and dole out the associated limitations, structural equation illustrationing (SEM) will be used. Using this technique, confirming cause among variables are identified in the model that is stipulate from the lit and theories by the researcher. These indirect effects, when added to the direct effects in the model, allow the decision of total causal effects.Research ObjectiveIdentifying the direct, indirect and total effects of the identified soothsay er variables (self-efficacy, sex act advantage, complexity, electronic computer get under ones skin, supports and time) on criterion variable ( take of WBI use).Research QuestionsWhat are the direct, indirect and total effects of the identified forecaster variables (self-efficacy, congeneric advantage, complexity, computer experience, supports and time) on criterion variable (level of WBI use)?Purpose of the involveThe purpose of the study is to build a model to predict the level of diffusion and utilization of Web-Based Instruction in school. To test the model cardinal independent variables (self-efficacy, relative advantage, complexity, computer experience, supports and time) from the three perspectives bear oning the diffusion and utilization of WBI will be used. The selection of the variables is substantiated by empirical evidence from previous relevant debut studies (Rogers, 1995 Ely, 1999).The result of this study would also be stabilising to instructional designers. When it comes to booming educational program design, the consideration of the target listenings characteristics is requirement to the analysis phase in most instructional design models. Because the predictor variables are susceptible to interventions such as training or faculty development, the identification of the potential factors that are highly related to the integration of a sassy technology.Operational DefinitionPredictor VariablesSix independent variables which are selected from the three perspectives affecting the diffusion and utilization of WBI. The variables are computer experience, self-efficacy, complexity, relative advantage, supports and time. distribution of InnovationsThe adoption and utilization of Web as a teaching tool. aim of UseDegree of integration of WBI that has been attained by teachers in order to attain existing instructional goals.Web-Based InstructionA hypermedia-based instructional program which utilizes the attributes and resources of the World grand Web to create a signifi whoremonger buoyt learning environment such as Blackboard and WebCT.Chapter II literature ReviewThe objective of the study is to identify factors affecting the likelihood of diffusion in educational setting is usually comprehend from one of three major perspectives. The first of these is concerned with the characteristics of the adopter, such as computer experience and self-efficacy. The second perspective is focuses on the characteristics of the innovation itself. The third perspective focused on the characteristics of the environment in which the innovation is to be introduced. This approach highlights the grandness of factors outside the innovation which can set the stage for its success or failure. The review will be focus on diffusion of innovation, telling to factors affecting the diffusion and implementation of Web-Based Instruction in an educational setting, informational technology diffusion models, model constructs and Web-Based Instruct ion (WBI).Diffusion of InnovationSanders and Morrison (2001) have identified three reasons why the study of diffusion theory is beneficial to the report of instructional technology. The first reason is most instructional technologists lack the knowledge of why their products are or are not adopted. They believe a study of diffusion theory could rectify this situation. Second, the field of instructional technology is often associated with the concept of innovations and they suggested that if instructional technologists understand the diffusion and diffusion of innovation theory. They will be more prepared to ca-ca trenchantly with potential adopters. The third reason is the studies of the diffusion theory could result in developing a musical arrangementatic model of diffusion and diffusion for the instructional technology field.Everett Rogers is the most widely cited author in the area of general diffusion theory. Rogers (1995) theories form the basis of most studies related to d iffusion. Rogers theories seem to be universal elements of most diffusion theories. They are diffusion process, adopter categories, innovation attributes, and rate of diffusion. So the instructional technologists not only need to create well-designed products but need to ensure the diffusion of these products. The main concern of the diffusion of innovation research is how innovations are adopted and why innovations are adopted at different rates.The diffusion process outlined by Rogers (1995) has atomic number 23 move knowledge, persuasion, decision, implementation, and confirmation. According to this theory, potential adopters of an innovation have to learn around an innovation and are persuaded to try it out before making a decision to adopt or reject the innovation. The adopters decide to either continue using the innovation or stop using it. This theory is very important because it shows that diffusion is not a momentary irrational act, but an current process that can be canvass, facilitated and supported.Factors Affecting Diffusion of InnovationThe experts in diffusion of innovation find that there is no single or a certain group of factors identified to explain the lack of use of Web-Based Instruction in school education. In this section, I will look for the factors have been examined and identified from many studies. The experts in educational technology have done numerous studies to find out the factors affecting the diffusion of Web-Based Instruction in school.Morris (2001) have found that the lack of technical support, lack of adequate equipment, amount of time required, student resistance or lack of computer skills, network problems and identified lack of teachers or administrative support are the barriers that teachers confronted when incorporating Web-Based instruction. From a survey of 557 teachers, Anderson, Varnhagen and Campbell (1998) also found that although most teachers believe that learning and communications technologies are ess ential to improving the quality of school education, many barriers were identified to realizing that capacity. They identified nine factors as major or mild barriers. The greatest barrier identified was lack of funding. The second greatest barrier was lack of time to learn technologies. The others are classroom infrastructure, adequate computer hardware or connectivity, institutional incentives, knowledge about applying technology in teaching, access to software tools, lack of training and support, and information about acquirable technology.Pitman, Gosper and Rich (1999) examined teachers use of instructional technology in a school classroom. In this study, they limited instructional technology to internet-related technologies including e-mail and the World Wide Web. The study identified significant relationships between teaching style, savvyd specialty of technology, perceived access to technology and perceived administrative support and the use of technology. Beggs (2000) hav e conducted the survey of 348 teachers. In this survey teachers at a school were asked about their self-perceived use of technology, factors influencing their use of technology, and barriers to the use of technology in the classroom. The factors are improved student learning, advantage over traditional teaching, equipment avail force, increased student interest, ease of use, compatibility with discipline, time needed to learn, materials in discipline, compatibility with materials, training, administrative support, personal informality and colleague use. Rogers (2000) have conducted the study to examine barriers to technology diffusion finished a structured interview conducted on the telephone or in-person. The barriers that he identified are need technical support staff, need venting time and time for training, funds, and lack of sharing best practices across system. with this through review, it seems that the factors emerge into three categories as like personal characteristics which include factors such as years of teaching, previous experience, teaching style, self-efficacy, and anxiety, innovation characteristics such as relative advantage, complexity, and compatibility, and environmental and social factors such as support and time. In the case of a factor of support, the factors like accessibility or availability, technical and administrative, workshop, and incentive may be grouped into a single factor as support.Refer to importance of considering both the person and the social environment as joint determinants of behavior, Surry and Farquhar (1997) described adopter based theories as opposite to developer-based theories. Developer-based theories are to increase diffusion by maximizing the efficiency, effectiveness and elegance of an innovation. They assume that the best way to bring about educational change is to create a system or product that is importantly superior to existing products or systems.In summary, this section focused on the studies cond ucted to find out the factors affecting the diffusion of instructional technology. Since these studies have not looked at the interactional effects of determinants on an adopters behavior so more attention seems to be needed on the interrelationships among identified variables.Innovation Diffusion modelsIn contrast to the studies that focus on single factors or a list of factors, a few models have been developed and empirically studied to identify the interactional effects of variables on innovation usage. These models focused on the identification of the determinants of usage, such as attitudes, social influences, and facilitation conditions (Davis, Richard Paul, 1989 Mathieson, 1991). speculation of Reasoned follow throughThe Theory of Reasoned Action (TRA) was first proposed by Azjen and Fishbein (1975). The theory specified a causal relationship between individual behavioral conception and actual behavior. The components of TRA are behavioral intention, attitude, and inter nal norm. TRA suggests behavioral intention depends on a persons attitude toward behavior and subjective norm. Behavioral intention measures a persons relative strength of intention to perform a behavior. Attitude is comprised of feels about the consequences of performing the behavior multiplied by his or her valuation of those consequences. indwelling norm is seen as a combination of perceived candidates from referent individuals or groups along with intentions to comply with these expectations. (Azjen and Fishbein, 1975).TRA became the basis for developing the following two models, Theory of Planned Behavior (TPB) and Technology Acceptance vex ( tammy). In fact, to poster for conditions where individuals do not have complete book over their behavior, TPB elongated TRA.Theory of Planned BehaviorAzjen and Madden (1986) modified TRA and generated a model named the Theory of Planned Behavior (TPB). The only difference between the TRA and TPB is the inclusion body of perceived behavioral control. Perceived behavioral control reflects a persons ability to actually perform a behavior. It is influenced by the effects facilitating conditions and self-efficacy. Hoffman and Novak (1994) included ease of access, ease of use, price, knowledge, recent experience, and skill to represent the perceived behavioral control in their study of hypermedia using TPB. Each of the determinants of intention, like attitude, subjective norm and perceived behavioral control, is determined by underlying belief structures. These are referred to as attitudinal beliefs, normative beliefs, and control beliefs which are related to attitude, subjective norm and perceived behavioral control respectively.Technology Acceptance ModelTechnology Acceptance Model (TAM) was developed by Davis (1986) and introduced by Davis, et al. (1989). This model is an adaptation of the Theory of Reasoned Action (TRA). TAM contends two clear-cut constructs like perceived usefulness and perceived ease of us e. Davis (1989) be perceived usefulness as the degree to which an individual believes that using particular system would enhance his or her job performance and ease of use as the degree to which an individual believes that using a particular system would be free of carnal and mental effort.This model is more specific and transparent because it only provides two factors which are important determinants of innovation usage (Mathieson, 1991). These factors are specific, easy to understand, and can be manipulated through system design and implementation. In addition, they should also be generalizable across settings. Although it is a special case of the TRA, TAM excludes the influence of social and personal control factors on behavior, which is also identified as important factors in the previous research (Groves Zemel, 2000 Knutel, 1998).Components of the Study Model ConstructsThe six predictor variables believed to be important in influencing the diffusion of innovation which has derived from the Rogers model and other relevant constructs from other models and other reviewed studies. Followed is the explanation of each of the six predictor variables and the criterion variable in more detail. in the flesh(predicate) CharacteristicsComputer ExperienceComputer experience is defined as the extent to which adopters perceive previous computer experience and performance with internet partnership as good. Also, it includes amounts of time using computer with internet connection in this study. The more lordly experiences one has, the more confident one is in a similar innovation (Stone Henry, 2003). In other words, positive past experience with computers will increase ones confidence while negative experience will reduce it. This view is supported by Ertmer, Evenbeck, Cennamo and Lehman (1994), who found that although positive computer experience increased computer confidence, the actual amount of experience was not correlated with the confidence beliefs of stude nts. This suggests that it is the quality, not the quantity, of experience is a lively factor in determining self-efficacy beliefs, which is one of the most important and touristy variables in the diffusion and utilization of innovations studies.There have been numerous studies involving the experience and attitude-behavior relationship (Anderson, Varnhagen, Campbell, 1998 Christoph, Schoenfeld, Tansky, 1998 Daugherty Funke, 1998 Ellsworth, 1998 Groves Zemel, 2000 Hill, Stone Henry, 2003 Kao, Wedman, Placier, 1995). Bandura (1977) suggests that experience is likely to reduce anxieties and induce individuals to change their behavior. The information gained by performance accomplishments provides the most influential source of efficacy information (Bandura, Adams, Beyer, 1977 and Zimmerman, 2000). Hill, Smith, Mann (1987) provide evidence that experience with computer technology calculate to a higher likelihood of technology adoption through changes in perceived self-efficac y.Self-efficacySelf-efficacy, a key element in Banduras social learning theory (1977), refers to ones belief in ones capability to use Internet in this study. Self-efficacy has been found to influence the decision to use computers (Hill, Smith and Mann, 1987). Bandura (1997) defined perceived self-efficacy as personal judgments of ones capabilities to organize and execute subjects of action to attain designated goals, and he sought to assess its level, generality and strength across activities and contexts.Zhang and Espinoza (1998) found that protect or anxiety about computers perceived by students predicted their confidence levels about computers and the confidence level is a significant predictor in decision making their desirability of learning technology skills. In addition, from the findings in his qualitative study Zollinhofer (1998) supported that teachers who have low self-efficacy are susceptible to cyber anxiety which can increase resistance to learning new technologies. According to Banduras (1977) self-efficacy theory, judgments of self-efficacy are based on several kinds of information including performance accomplishments, vicarious experiences, verbal persuasion, and aflame arousal. Venkatesh and Davis (1994) theorize that perceptions about a new systems usefulness and a new systems ease of use influences and are anchored on an individuals general computer self-efficacy. From this evidence, it can be hypothesized that self-efficacy influences perceived relative advantage and ease of use of innovation, and also influences utilization of an innovation through those two intervening variables.Perceived attributes of innovationRogers (1995), Wolfe (1994), and Farguhar and Surry (1994) identified perceived by potential adopters, relative advantage, compatibility, complexity, trialability, and observability as five main attributes of an innovation as important factors in determining the rate of diffusion. According to Rogers theory, potential adopter s of an innovation have to learn about an innovation and are persuaded to try it out before making a decision to adopt or reject the innovation. This five attributes are frequently cited as playing a key role in the perceptions of adopters in regard to the implementation of instructional innovations. For this study, although perceived attributes compatibility, observability and trialability could contribute to some extent in diffusion process but only relative advantage and complexity which distinguished by Vinson (1996) and Moskal, Martin, and Foshee (1997) are included. This is because they have the strongest influence from Rogers five attributes. sex act AdvantageRelative advantage is defined as the degree to which an innovation of WBI as an instructional technology in this study is perceived as be better than the technology it supersedes and other solutions being considered (Rogers, 1995). The degree of relative advantage is often expressed as economic profitability, social pr estige, or other benefits. The degree of use is expected to be increased by the teacherss perceived relative advantage of WBI.Rogers generalized from previous research that the relative advantage of an innovation, as perceived by members of a social system, is positively related to its rate of diffusion. In their study, Venkatesh and Davis (1994) tested the effect of self-efficacy on the perceived ease of use construct using two different information technologies, E-mail and Gopher. They found that the perceptions about a new systems ease of use are anchored on a persons general computer self-efficacy.complexnessComplexity is defined as the degree to which the WBI as an instructional technology is perceived as difficult to understand and use (Rogers, 1995). It is similar to the ease of use construct used by Davis, Bagozzi, Warshaw (1989). They define it as the degree to which an individual believes that using a particular system would be free of physical and mental effort. In their study they find a positive coefficient of correlation between perceived ease of use and behavioral intentions. They found ease of use to be a strong determinant of use. It is expected that the more complex WBI appears to teachers, the less they will use it.An innovation which is perceived as being difficult to use will meet with greater resistance to its use and diffusion than those which are considered as easy to learn. Hence, another(prenominal) generalization drawn by Rogers was that the complexity of an innovation, as perceived by members of a social system, is negatively related to its rate of diffusion. Then, who perceives an innovation as being more or less difficult? The findings (Ghaith Yaghi, 1997 Guskey, 1988) indicate that more in effect(p) teachers considered an innovation as less difficult to implement.Perception of influence and support from the environmentGroves and Zemel (2000) from their study has been identified that environment as a syndicate of influencing factors on diffusion and utilization of innovation. Ely (1999) proposed eight environmental condition dissatisfaction with the precondition quo, existence of knowledge and skills, availability of resources, availability of time, existence of rewards or incentives for participation, expectation and encouragement of participation, commitment by stakeholders involved, and evidence of lead. A few studies have been conducted to determine the best predictors among the eight conditions using stepwise multiple regression analysis. Ravitz (1999) found out availability of resources, availability of time, existence of rewards or incentives, commitment, and leadership are the most important determinants related to the implementation of innovation. In another pure survey study, Daugherty and Flunke (1998) reported the barriers confronted by teachers when incorporating Web-Based instruction are lack of technical support, lack of software or adequate equipment amount of time required and lack o f teachers or administrative support. From reviewing the related studies, supports and time were selected as key variables for this study.SupportsGroves Zemel (2000) found out that the supports like training available on how to use, information or materials available, and administrative support were rated as very important factors influencing use of instructional technologies in teaching. Morris (2001) found out that lack of technical support, lack of adequate equipment or software, and lack of teachers or administrative support are the barriers teachers confronted when incorporating distance education.Farquhar and Surry (1994) proposed organizational factors with the adopters individual factors as influential factors which affect the diffusion and utilization of the instructional product. They asserted that inappropriate environmental support can often be an important hindrance factor of successful innovation diffusion. The teachers training and other resources to use and learn th e WBI technology can be effective and productive by lessen teachers perceived level of complexity to use or learn WBI as an instructional technology. eonSeminoff and Wepner (1997) discovered that of the 77 respondents in their study on instructional-based projects, 64% indicated that tucker out time for preparation of technology-based projects was not being provided. In the survey study about factors influencing the use of technology and perceived barriers to use of technology, Groves Zemel (2000) found that teachers perceived time needed to learn as an important factor in influencing use of technology.Plater (1995) indicates that managing teachers time is the single most important asset of the school. In the past teachers had only a few time-related issues, including meeting classes, keeping blot hours, and attending teachers meetings. Plater goes on to say that schools must recognize teachers time as valuable resource and begin to think about departmental needs and prepare indi vidual teachers to meet these needs.While teachers training should be part of the overall preparation for WBI, teachers training can only be effective and productive if there is adequate preparation time to incorporate what has been intimate in training. In the present study time is defined as perceived available time needed to learn and use WBI as an instructional technology. The more available time teachers perceive, the less complex they perceive to learn and use WBI as an instructional technology.Level of UseLevel of using Web-Based Instruction is a dependent variable for this study. Moersch (1995) proposed a conceptual framework that measures levels of technology use. In this framework, seven distinguished implementation levels teachers can demonstrate. According to Moersch (1995), as a teacher progresses from one level to the next, a series of changes to the instructional curriculum is observed. The instructional focus shifts from being teacher-centered to being learner-cente red. Computer technology is used as a tool that supports and extends students misgiving of the pertinent concepts, processes and themes involved when using databases, telecommunications, multimedia, spreadsheets, and graphing applications. Traditional verbal activities are piecemeal replaced by authentic hands-on inquiry related to a problem issue or theme. Heavy reliance on textbook and straight instructional materials is replaced by use of extensive and diversified resources determined by the problem areas under discussion. Traditional evaluation practices are supplanted by multiple assessment strategies that utilize portfolios, open-ended questions, self-analysis, and peer review.To measure the level of innovation use, in addition to above levels of innovation use which are used to measure the degree to which an adopter integrates the innovation into practice, a number of studies (Cartas, 1998 Lin Jeffres, 1998 Jaber, 1997 Wallace, 1998) in the studies of diffusion and utiliz ation of instructional technologies have used three different categories of questions to measure the usage level the frequency of technology use, the amount of hours in using a technology and the number of programs or functions used.Since it seemed that levels of use studies (Moersch, 1995 Reiber Welliver, 1989) dealt with questions pertaining to the specific aspects of computer technologies to measure the levels of technology, the present study created the questions including the three categories of questions pertaining to WBI use.Web-Based Instruction (WBI)WBI is defined as an innovative approach for delivering instruction to a remote audience using the World Wide Web as the instructional pitch shot system (Khan, 1997). Web-Based learning environments use the resources of the Web to create a context in which learning is supported and fostered.Web-Based Instruction is growing faster than any other instructional technology (Crossman, 1997). More and more school teachers are using WBI as an integral part of instructional activities. School cannot work in isolation and must respond to societal change (Innovation in Distance Education (IDE), 1997). WBI offers medium for school education to accommodate the information age and a networked worl