Computer and Information Science » Information and Knowledge Engineering E-Learning-Organizational Infrastructure and Tools for Specific Areas Edited by Elvis Pontes, Anderson Silva, Adilson Guelfi and Sergio Takeo Kofuji, ISBN 978-953-51-0053-9, 194 pages, Publisher: InTech, Chapters published February 17, 2012 underCC BY 3.0 license DOI: 10.5772/2466 Technology development, mainly for telecommunications and computer systems, was a key factor for the interactivity and, thus, for the expansion of e-learning. This book is divided into two parts, presenting some proposals to deal with e-learning challenges, opening up a way of learning about and discussing new methodologies to increase the interaction level of classes and implementing technical tools for helping students to make better use of e-learning resources. In the first part, the reader may find chapters mentioning the required infrastructure for e-learning models and processes, organizational practices, suggestions, implementation of methods for assessing results, and case studies focused on pedagogical aspects that can be applied generically in different environments. The second part is related to tools that can be adopted by users such as graphical tools for engineering, mobile phone networks, and techniques to build robots, among others. Moreover, part two includes some chapters dedicated specifically to e-learning areas like engineering and architecture. Editor: Prof. Adilson Guelfi University of São Paulo, Brazil EXPERIENCE University of São Paulo EDITED BOOKS E-Learning-Organizational Infrastructure and Tools for Specific Areas BOOK CONTENTS Chapter 1 Factors that Influence Academic Teacher's Acceptance of E-Learning Technology in Blended Learning Environmentby Snježana Babić Chapter 2 Towards Economical E-Learning Educational Environments for Physically Challenged Studentsby Amir Zeid, Sarah S. Sakit, Noor A. Al-AbdulRazzaq, Mariam M. Al-Tattan, Fatima S. Sakit, Abrar Amin, Mariam Al- Najdi and Aisha Al-Rowaished Chapter 3 Advanced Pedagogical Approaches at Slovak Universitiesby Pavol Molnár and Ildikó Némethová Chapter 4 Digital Faces on the Cloudby S. L. Jones Chapter 5 Lego Based Computer Communication for Business and Learningby Rapelang Marumo Chapter 6 Multimodal Intelligent Tutoring Systemsby Xia Mao and Zheng Li Chapter 7 Using the Smith Chart in an E-Learning Approachby José R. Pereira and Pedro Pinho Chapter 8 Intelligent Tutoring System with Associative Cellular Neural Networkby Michihiro Namba Chapter 9 Proposing Two Algorithms to Acquire Learning Knowledge in Problem-Based Learning Environmentby Akcell Chiang Chapter 10 E-Learning in Architecture: Professional and Lifelong Learning Prospectsby Matevz Juvancic, Michael Mullins and Tadeja Zupancic 1 Factors that Influence Academic Teacher's Acceptance of E-Learning Technology in Blended Learning Environment Snježana Babić Polytechnic of Rijeka, Business Department, Rijeka, Croatia 1. Introduction The idea of distance learning as the concept of learning at one's own pace independent of time and place, originated in 19th century. The Open University of United Kingdom, which introduced blended learning in 1969, had the crucial role in introducing the distance learning into the higher education. The term e-learning (electronically supported learning) was introduced in 1995, and its most common definition is: learning and teaching using information and communications technology, or more broadly, e-learning technology. Blended model of learning combines different models of learning and teaching: in traditional classroom (which provides e-learning technologies) and virtual learning environment. Virtual Learning Environment (VLE) is a component or subsystem of the Managed Learning Environment (MLE), where students and teachers take part in different types of online interaction, and whose focus is on managing and facilitating the learning process while providing the required resources. The commonly used synonym for VLE is Learning Management System (LMS). MLE includes various information systems and processes of the higher education, and together with VLE they make a part of virtual campus (The Joint Information System Committee [JISC], 2011). One of the definitions of virtual campus is: “...refers to a specific format of distance education and on-line learning in which students, teaching staff and even university administrative and technical staff mainly 'meet' or communicate through technical links” (benchmarking of Virtual Campuses [BENVIC], 2011). Higher education teacher can find the service of using VLE at certain institutions, which can use the service developed within the institution or at the university level. In practice, most commonly used are commercial software packages (integrated set of tools for communication, knowledge evaluation, collaboration, monitoring and other) such as WebCT and Blackboard, and among Open Source packages, Moodle and Claroline. Introducing e-learning into higher education institution brings about changes on organizational, economical and technical level, however, the practice shows that e-learning has been introduced into such institutions in various ways which resulted in different quantity and quality of the education processes using e-learning technology. To improve the effectiveness of e-learning, the need occurred for developing the quality management system in the field of e-learning (Kermek et al., 2007). Those standards are: ISO/IEC 19796- www.intechopen.com 4 E-Learning – Organizational Infrastructure and Tools for Specific Areas 1:2005 (Information Technology – Learning, Education and Training – Quality Management, Assurance and Metrics – Part 1: General Approach, 2005) which provides a framework for quality management and consists of reference model describing the education processes and subprocesses in e-education, and ISO/IEC 19796-3:2009 (Information Technology – Learning, Education and Training – Quality Management, Assurance and Metrics – Part 3: Reference methods and metrics, 2009) which extends the previous reference framework by providing methods and metrics required to implement quality management and quality assurance systems for stakeholders designing, developing or utilizing e-learning technology. Processes related to e-education are compared to the software development process, where the basis for quality standards is taken from the domain of software engineering (Kermek et al., 2007). Based on this, Marchall & Mitchell (2004) defined E-learning maturity model for estimating the organization's level of maturity relating to the e-education processes and their improvement. The improvement of education processes depends on the development of capabilities in all their elements, from the institution in charge to the every single individual involved in the educational system, and in this case it is important to emphasize teacher competences. On the other hand, the quality and usability of the virtual learning environment are the key influencers on the learning outcome, i.e., student satisfaction. The usability of the e-learning technologies, as the main element of the e-learning success, includes pedagogical and technical usability. Pedagogical usability refers to the support in the process of teaching and learning, while technical usability refers to the interaction between the user and the computer (Melis et al., 2003). Due to the mentioned facts, to create a virtual learning environment, apart form the teacher as an expert in a certain field of study, a team of experts is required: multimedia experts, programmers, administrators, instructional designers and similar experts. However, the practice shows that often teachers are the ones who perform many different roles themselves. With regards to the complexity of the proper use of e-learning in teaching, the results of the research indicate the slow manner of teachers accepting e-learning. For that reason, a question is being asked: Which factors influence the higher education teacher's acceptance of e- learning? Numerous authors have researched many factors from different aspects, they have monitored introducing e-learning as an innovation diffusion in organization, introducing and accepting new information system, communication between human and the machine, psychology, pedagogy, reengineering the education/business process and other. During the research they have used existing theories and models of technology and innovation acceptance. Keller (2009) approaches the teacher's acceptance of VLE as an innovation diffusion from the aspect of organizational learning, while Nanayakkara and Whiddett (2005) group factors as individual, organizational and system factors. Argawal (2000) defines the following categories of factors related to the personal acceptance of the information technology in organizations: personal differences, situational factors, social influence, organizational factors, beliefs and attitudes. Osika and Buteau (2009) monitor acceptance of the e-learning technology through motivational factors, which they group as intrinsic factors (beliefs, sense of competence, anxiety) and extrinsic factors (institutional factors). In professional development individual's commitment to the quality of his or her work is shown through the change in attitudes and values, development of skills and competences, www.intechopen.com Factors that Influence Academic Teacher's Acceptance of E-Learning Technology in Blended Learning Environment 5 and using certain tools and instruments which results in quality work (Ehlers, 2007). Baia (2009) confirmed the influence of the factor commitment to pedagogical quality on technology acceptance, which is influenced by: belief about learning technologies, academic title and years of work experience. Competence perception and confirmation of the initial expectation (attitude) influence the teacher's satisfaction through perception of usefulness, where the attitude related to the teacher's education (Ø. Sørebø & A. M. Sørebø, 2008) is the confirmation of the initial expectation. The following pages contain the overview of the most commonly used theories and models of accepting technology and innovation, as well as key responsibilities of teachers in blended learning process for better understanding of the concept of higher education teacher competence in the field of e-learning. Furthermore, categories of factors have been singled out in which there is an overview of those factors which, as found in recent studies, showed connection with teacher's accepting e-learning technology. The conclusion contains the categories with key factors which can aid future researchers in defining theoretic models as the foundation for future empirical researches. 2. Education process in blended learning environment and the teacher competence concept To describe a teaching scenario in any form of e-learning and in different educational environments, a reference model ISO/IEC 19796-1 can be used, which includes the complete life-long learning cycle. The model is a framework consisting of two parts: generic process model and generic descriptive model. Generic process model is divided into 7 basic processes and 38 subprocesses, and the following is the description of the basic processes (Pawlowski, 2006): Needs Analysis: identification and description of requirements, demands, and constraints of an educational project Framework Analysis: identification of the framework and the context of an educational process Conception /Design: conception and design of an educational process Development /Production: realization of concepts Implementation: description of the implementation of technological components Learning Process: realization and use of the learning process Evaluation/Optimization: description of the evaluation methods, principles, and procedures There are numerous instructional design models (systematic approach to analysis, design, development, implementation and evaluation of the study material for learning according to the set learning outcomes, following the analysis of student needs) which teachers can use to design different education processes in blended form. Some of the instructional design models are: Dick and Carey, rapid prototyping, Knirk and Gustafson and others, among which the most commonly used in higher education is ADDIE (Analyze, Design, Develop, Implement, Evaluate) model. Academic teachers most frequently use their own non-standardised models, and very often use the virtual learning environment only for access to study material. In practice, the search for the best blended learning model in a particular context boils down to combining the advantages and disadvantages of traditional teaching activities and technology-mediated activities (Fig. 1) (Rothery et al., 2008). www.intechopen.com 6 E-Learning – Organizational Infrastructure and Tools for Specific Areas Fig. 1. Searching for the best blended learning model (Rothery et al., 2008). The quality of the education process is one of the factors responsible for students achieving success. Creating the blended learning environment is not easy and it requires teachers to redefine the existing competences and develop new ones, during which is essential to understand the concept of the quality of e-education. Numerous definitions of competence concept have been published, and according to Weinert (2001) it “...is a specialized system of abilities, proficiencies, or skills that are necessary to reach a specific goal”. From this definition, it can be inferred that the concept of personal e-competence of the higher education teacher includes: teacher's ability to implement e-learning in his or her education process, as well as ability to adopt new competences for implementing e-learning in the education process. With the aim of defining the concept of e-competence, numerous authors used the general competence concept, developed by Weinert (2001), as their basis. Its central idea is the learning process which together with practical experience develops new knowledge and skills that change values and form a certain attitude. Weinert (2001) emphasizes the importance of the experience and explains that competences can be learned and developed through practical values. The foundation for action lies in: attitude, knowledge and skills, and great importance is put on action competence which includes “available cognitive, motivational and social requirements for successful learning or performing an action”. Based on the mentioned general competence concept, Schneckenberg (2007) defined the e- competence concept applicable to all levels, from institution, group, to every stakeholder in higher education environment. The concept assumes knowledge, skills and attitude as the basis for performance, which can be looked at from the aspect of pedagogical, technical, organizational and sociocultural dimension, and the action competence can be seen through four core competences: subject matter, methodology, social competence and personal competence. It is important to emphasize that the teacher's personal competence for e- learning application cannot be defined without identifying situational variables in specific education scenarios which are determined by the following elements (Schneckenberg, 2007): pedagogical model (set of methods for optimum realization of communication between teacher, content and student), choice of e-learning technology, student competences for using ICT in learning activities and the characteristics of the education content, i.e., the course. Education scenario is performed in specific context with specific characteristics, therefore the more specific and less specific education contexts are the key elements of the www.intechopen.com Factors that Influence Academic Teacher's Acceptance of E-Learning Technology in Blended Learning Environment 7 aforementioned competence model. Assuming that a competent person will not apply and develop his or her competences unless motivated, the motivation component is of crucial importance and it can be intrinsic (teacher's personality, attitude and values) and extrinsic (situational and institutional factors). Taking into consideration the same general competence concept in organization (Weintert, 2001) and the fact that e-learning is introduced into education to improve the education quality (dependent of the desire for quality performance of all the stakeholders in the educational system), Ehlers (2007) defined the concept of competence as “quality literacy”. Thus he describes the ability of education stakeholders to improve in quality while emphasizing the importance of professionalism as the crucial component in quality development. He looks at the “quality literacy” concept through four dimensions of competence which lead to professionalism and quality development on all levels: quality knowledge, quality experience, quality innovation and quality analysis. “Quality literacy” is the competence concept which, besides knowledge and skills, includes: the responsibility of the stakeholders towards the surroundings, i.e., professionalism in the field of quality development in e-education. 3. Theories and models of accepting technology and innovation With the aim of understanding the factors which influence teachers accepting the e-learning technology, different existing theories and models have been used, and this paper mentions only the ones used frequently in recent studies. The model of accepting technology has its foundations in the theory of social psychology, developed by Fisbein and Ajzen (1975) as Theory of Reasoned Action (TRA) which points out key factors influencing the behavioral intent: attitude toward behavior and subjective norm; if users have the intention of accepting technology, they will do so, but under the strong influence of the environment. In his Theory of Planned Behavior (TPB) model, Ajzen (1991) later added the factor of perceived behavioral control to the factors attitude toward behavior and subjective norm, which stems from the self-efficacy theory and is a condition for change in behavior. One of the first models of accepting technology, and most commonly used in the research is Technology Acceptance Model (TAM) (Fig. 2) developed by Davis (1989), according to which the user's attitude towards technology is mainly influenced by the following factors: perceived usefulness and perceived ease of use. According to Davis (1989), perceived usefulness is defined as “the prospective user's subjective probability that using a specific application system will increase his or her job performance”, while perceived ease of use is defined as “degree to which the prospective user expects the target system to be free of effort”. Fig. 2. Technology Acceptance Model (TAM) developed by Davis (1989). www.intechopen.com 8 E-Learning – Organizational Infrastructure and Tools for Specific Areas TAM model was later updated by its author adding numerous factors, and so have other authors; Venkatesh and Davis (2000) developed TAM2 model in which the TAM model is upgraded with the processes of cognitive influence: job relevance, output quality and result demonstrability, and the processes of social influence: subjective norm, voluntariness and image, which influence the perceived usefulness. The next important model, very often used in the field of e-learning, was developed by Venkatesh et al. (2003) as Unified Theory of Acceptance and Use of Technology (UTAUT), according to which the following four factors influence the user's technology acceptance: performance expectancy, effort expectancy, social influence and facilitating conditions. The model emphasizes the importance of four moderators: age, gender, experience and voluntariness of use, as individual differences between users towards technology acceptance. From the aspect of diffusing new ideas and innovations, according to Rogers (1995), four main elements have a direct influence: innovation, communication channels, time and social system. In Innovation Diffusion Theory (IDT) Rogers (1995) defined five steps through which the user goes through when deciding about accepting new technology: knowledge, persuasion, decision, implementation and confirmation. In the phase of persuasion about positive characteristics of the product/service, the user is influenced by: relative advantage, compatibility, complexity, trialability and observability. According to the decision-making about innovation acceptance, Rogers (1995) groups the users as following: innovators, early adopters, early majority, late majority and laggards (Fig. 3). Fig. 3. Rogers Innovation Adoption Curve (Rogers, 1995). Among early and late adopters (Fig. 3) there are systematic differences in three areas: socioeconomic, personality variables, communication behavior, and other characteristics: previous practice, wants and needs, innovativeness and social norms. Based on Rogers' theory (1995), Moore and Benbasat (1991) developed a model for measuring user's perception of information technology's characteristics as innovation. The model was applied in the field of adopting information systems, and it consists of the following: relative advantage, compatibility, trialability, ease of use (replacement for: complexity (Rogers, 1995)), visibility and result demonstrability (replacement for: observability (Rogers,1995)), image and voluntariness. 4. Factors that influence academic teacher's acceptance of e-learning technology What follows are the factors connected to the academic teacher's acceptance of e-technology, grouped in several categories. www.intechopen.com Factors that Influence Academic Teacher's Acceptance of E-Learning Technology in Blended Learning Environment 9 4.1 Teacher competence (knowledge and skills) Certain knowledge and skills encourage changes in individual's values and attitudes which influence the user's behavior, as well as belief about self-efficacy. The main prerequisite for the use of e-learning technology is: computer literacy, and the lack of computer knowledge is closely related to computer anxiety and the level of perceived usefulness of e-learning technology (Liu, 2005). Computer literate person is more likely to experiment with new software. Therefore, the level of experience in working with e-learning system (LMS) is the powerful motivator in teacher's adoption of e-learning (Gautreau, 2011). It is well known that after having accepted the e-learning system, it is used on different levels. Renzi (2008) proved the existence of differences in competences between certain groups of teachers. Teachers who create virtual learning environments according to the instructional design principles transform their way of teaching. Knowledge and skills from using the instructional design model, i.e., designing the education scenario, are related to the following factors: formal education, teacher's experience and perceived technology usefulness (Renzi, 2008). E-moderating is the key teacher competence influencing the success of the online part of the lessons, and which (according to Salmon (2000)) refers to: knowledge and skills of online moderating and online mentoring. On the organizational level of e-learning, besides the pedagogical and technical dimension of the teacher competence, Shenckenberg (2008) points out the importance of the sociocultural and organizational dimension of the competence profile when adopting e-learning. In this case, sociocultural dimension refers to the teacher's readiness to adopt new knowledge from the field of e- learning, as well as communication and sharing of knowledge within certain networks, and the competence profile of academic teachers in organizational dimension includes taking part in deciding about implementation of e-learning at institutional level, working in interdisciplinary teams on solving problems due to the complexity of education using e-learning technology and managing e-learning projects which are a part of university's e- learning strategy (Shenckenberg, 2008). 4.2 Attitude and values In the process of accepting innovation in teaching, teacher's belief about the usefulness of the innovation plays one of the main roles and it encourages changes in the curricula (Colorado & Eberle, 2009). Teacher's attitude and values are important motivational factor in developing and applying e-learning competence. There have been many researches about teacher's attitude towards e-learning technology: positive (confirmation) or negative (anxiety) (Mihhailova, 2006). Less researches are oriented towards beliefs which form certain values and attitudes (Agarwal, 2000). Researches have shown that users' behavior is influenced by different beliefs or e-learning technology attributes, and according to Moore and Benbast (1991) they are: relative advantage, compatibility, trialability, ease of use, result demonstrability, observability. Most frequently confirmed attributes are: ease of use and usefulness (Gibson et al., 2008; Renzi, 2008; Keller, 2009). Ozkan and Findik (2010) confirm the importance of the e-learning technology compatibility attribute in relation to the differences in certain academic departments, where the difference has been confirmed. Kundu et al. (2010) confirm the importance of compatibility attribute www.intechopen.com