Assessment of instructors’ readiness for implementing e-learning in continuing medical education in Iran

Abstract

Back ground: E-learning provides new levels of flexibility in learning and teaching. This contribution of e-learning is dependent on the levels of readiness in several critical factors particularly in an educational organization.

Aim: The purpose of this study was to assess instructors’ readiness and to identify the most important factors that affect their readiness in e-learning in CME programs in order to use the effective opportunities that facilitate e-learning in CME programs.

Methods: A 5-point Likert scale instrument consisting of two domains (technical and pedagogical) was constructed according to four subdomains (knowledge, attitude, skills, and habits) and distributed to 70 faculty members. A factor analysis was employed to extract significant factors.

Results: The results revealed that the mean of readiness on e-learning for faculty members was 3.25 ± 0.58 in technical and 3.37 ± 0.49 in pedagogical domains on a 5-point Likert scale (1–5). The factors such as “familiarity with learning management system,” “willingness to teach by adopting a new technology,” “willingness to use e-learning as a viable alternative,” “ability to deliver e-material and to provide e-content for teaching,” and “being accustomed to the virtual environment and utilization of the computer and the internet” were extracted on technical readiness domain. In addition, the pedagogical readiness factors were: “familiarity with online teaching principle and method,” “willingness to use technology in instruction and material development,” “ability to design content for e-material and online course evaluation,” and “being accustomed to providing information back up regularly and employing eclectic methods and multiple approaches in teaching.”

Conclusion: The findings of this study suggest that training should be offered to instructors on a continuous, rather than a one-off basis so that their IT knowledge and skills are upgraded over time. In addition, results indicate that pedagogical innovations are required to develop and implement an effectiveness e-learning program.

Introduction

The health sector in Iran has a geographically disperse workforce and constantly faces the challenge to provide learning and development opportunities in many effective training programs. Using e-learning as a solution, offers the possibility of widespread use, access, and sharing unmatched by other types of instruction. E-learning allows physicians to learn new knowledge and skills for professional development, without traveling to training sites or waiting for scheduled classes. But when e-learning becomes more common place in training departments, there are concerns about the acceptance of the medium as an effective way to learn. Therefore, understanding instructors and their attitudes and behaviors toward e-learning is a very important factor to its implementation of Continuing Medical Education (CME) programs in University of medicine.

Although e-learning seems to be the answer for delivering CME, adopting e-learning without careful planning will most likely end with cost overruns, unappealing training products, and ultimately, failure. Thus, Clark and Mayer warned managers to assess the readiness for e-learning before adopting this innovation (Clark & Mayer 2003).

There are some factors for assessing e-learning readiness that are identified and should be taken seriously in considering e-learning as a viable option to deliver training and instruction. Knowledge-intensive organizations, a medical university for example, will undoubtedly spend an enormous amount of resources to develop e-learning solutions. Therefore, there is a need to take a serious look into these factors to decrease the risk of failure (Borotis & Poulymenakou 2004).

One of the most common and major influencing factors on organization's readiness for e-learning is content. An e-learning program needs content or subject matter that is focused on the instructor's activity. In addition, successful online teaching depends on learning experiences properly planned and facilitated by knowledgeable educators. Online educators must have ability to design activities that address the learner's modes of learning to provide significant experiences for each class participant. In designing online courses, this can best be accomplished by utilizing multiple instructional strategies (Gagne et al. 2005). Brock suggested that computer literacy (an individual competency in using computer and related technology) and motivation for learning (the receptivity to self-directed learning and self-management skills) are two main ingredients that a teacher must have before embarking on the online journey (Brock 2003). As well, Watkins (2005) further suggested that two essential skills for success in e-learning are adapting old skills and habits from the traditional classroom for use in e-learning and developing and applying new e-learning skills and habits for e-learning. This is because this paradigm shift in instruction and learning puts the learner at the center of the learning process and gives the instructor more time for individual interaction with students.

E-learning enhances student-centered learning, because learning becomes a two-way discussion, not a one-way delivery system. Thus, it is required that academicians equip themselves with the requisite skills and demonstrate the prescribed level of competence for content development of e-learning to fully exploit their skills and competence in the digital learning environment with respect to their disciplines. For example, Reigeluth (1999) stated that one of the most important developments in the “knowledge age” is to create an electronic personal tutor for learners. The electronic tutors or online facilitators help to customize online content and to be fit with the needs, interest, and learning style. Thus, technology plays a huge role in the e-learning readiness process (Reigeluth 1999). Argyris (1999) posed that the most essential assumption about learning is that the people involved in the learning process want to contribute and can be trusted. He pointed out that it is necessary for them to have some basic skills of how to access and use the technology and have the knowledge and skills.

Ellet and Naiman (2003) also suggested since the e-learning environment has the potential to permit a full range of interactive methodologies, instructors must adapt their courses to online models. As such, attention must be paid to the instructional design of their courses. This flexibility in the use of instructional strategies requires knowledge on the use of technology and media to accompany these changes. Muirhead (2000) posed that teachers will be frustrated without reliable knowledge and skills in the use of computer technology. For e-learning, instructors’ knowledge may include things, such as working with multiple versions of a software package, providing technology support to students, using multiple operating systems, and the absence of mature integrated content development tools. Palloff and Pratt (2000) stated that the instructors not only must be trained to use technology, but must also be able to shift the way in which they organize and deliver material by proper technology. In addition, Valentine (2002) pointed out that the misuse of technology may arise from lack of knowledge and training, instructor's attitudes, or hardware problems.

This study focuses on this aspect of e-learning process, namely the instructors’ readiness factors on implementing e-learning in CME programs in Iran. For this purpose (identifying the factors on readiness for e-learning), the researchers followed issues pertaining to knowledge, attitude, skills, and habits (KASH) readiness (Gugliemino & Guglielmino 2003) with respect to technology and pedagogical issues for instructors (medical academic members who teach in CME programs). It is focused on the KASH of the individual as important determinants in e-learning readiness. In this study, research questionnaire comprised items of important factors that may help make an instructor to be a more effective and efficient online educator, with internal consistency and good scale validity in each following domain.

• Technical knowledge: To use an instructional technology for achieving the goals of teaching and learning, teachers must have adequate knowledge on technology (O’Quinn & Corry 2002). For example, the instructor would need to have the basic knowledge on how to use learning management system (LMS), design web pages for e-learning, design an online course for learning environments, and use computers as an instructional tool.

• Technical attitude: A positive attitude toward technology is needed to make any educational program a success. For example, if teachers regard computers negatively or with suspicions, the educational utilization of computer will be limited (Woodrow 1991).

• Technical skills: For the instructors to be good facilitators for online learning, they must have the technological skills and competencies of basic computer operation and technical issues relating to internet usage, such as web searching and conferencing and managing a LMS.

• Technical habits: Habits in actually using the technology must be a requirement for e-learning instructors. Just like self-directedness and self-discipline are the main focus for learners, instructors must acquire the habits to use technology as a tool for delivery of their instructional materials.

In addition, for implementing a successful e-learning it is necessary that the instructors’ pedagogical readiness has to be analyzed. Readiness in terms of instructional strategies or pedagogy in this study, has to do with the knowledge, skills, attitude, and habits of instructors to use the appropriate strategies acquired through normal face-to-face classroom interaction to accommodate the e-learning “classroom” and learners.

• Pedagogical knowledge: Since effective learning depends on appropriately designed learning experiences, designers and instructors must be able to design teaching/learning activities. It is essential to have a good knowledge on appropriate instructional strategies relating to the selection of instructional media and delivery methods, management of small/large group discussion, and internet interaction (Gagne et al. 2005).

• Pedagogical attitude: Attitude plays an important role in the educational process. As an e-learning instructor, attitude toward the changing paradigm of teaching and instruction must be taken into consideration. Willingness to participate as a facilitator will have an effect on the online interaction with the learners.

• Pedagogical skill: Adopting the e-learning environment require some competencies on the part of the instructor to design and develop instructional materials appropriate for the web. These include practical skills, such as web-design, moderation of online interaction, and use appropriate resources that are available through the internet.

• Pedagogical habits: The knowledge, attitude, and skills of instructors on instructional strategies will not materialize into actual and effective instruction, unless the appropriate habits in actually doing these activities are acquired by them. Readiness to move into the e-learning environment requires discipline and good habits on the part of the instructor in using appropriate instructional strategies for delivery instruction.

This study investigated instructors’ readiness and identified components of the technical and pedagogical readiness which influence the successful adoption of e-learning in the field of CME for use in medical education.

Table

Practice points

Computer literacy (an individual competency in using computer and related technology) and motivation for learning (the receptivity to self-directed learning and self-management skills) are two main ingredients that a teacher must have before embarking on the online journey. Factors such as willingness to develop teaching via new technology and using e-learning as viable alternative to traditional methods showed that faculty members desire change in the educational system. In the University of medicine, toward the implementation of e-learning for the training of their human resources, a particular model is needed to assess and identify factors influencing instructors’ readiness to improve their skills for the development of e-learning. The findings of this study suggest that training should be offered to instructors on a continuous, rather than a one-off basis so that their IT knowledge and skills are upgraded over time.

Methodology

The research questionnaire consists of statements generated from review of the literature on e-learning readiness including Guglielmino and Guglielmino (2003) as well as Sadik's (2007) readiness instruments. The instrument included four categories which aimed to measure the knowledge, attitudes, skills and habits toward e-learning in both technology and pedagogy domain. The content validity of the instrument was assessed based on an expert panel; the following questions were responded by the panel:

• Are the questions appropriate according to the objectives?

• Are the questions comprehensive and mutually exclusive?

• Are there any other questions needed to be added in the questionnaires?

• Are there any revisions to the items?

The face validity and feasibility of questionnaire was also examined by a group of five content experts with adequate experience in pedagogical and technical issues in e-learning. The purpose of these interviews was to clarify basic concepts and issues concerning e-learning readiness, as well as laying the framework for a more legitimate research design. Panel members were asked to suggest addition or deletion of any items and comment on each item's importance within each domain based on their understanding of the conceptual definition of each domain. The revised items were used to develop the rating scale of subscales. It was pilot-tested on 15 faculty members in University of Medical Sciences in Kerman, Iran to assess acceptability.

Based on results from the pilot, changes were made to reduce redundancy and to increase the information about academic rank and teaching experience. The questionnaires were disseminated to all (N = 70) instructors (medical academic members) who teach in the CME programs at University of Medical Sciences in Kerman, Iran.

The questionnaire comprised of items measured on a 5-point Likert scale, with 5 indicating “strongly agree” and 1 indicating “strongly disagree.” Of the 70 questionnaires, 60 were analyzed for completeness of data and were thus included in the analysis, giving an effective response rate of 85%. Factor analysis, correlations, and ANOVA were the main methods of data analysis. Factor analysis was conducted to extract major factors that influence the e-learning readiness using Varimax rotation with Kaiser Normalization. In this process, three major sequential steps were undertaken. The first step involved identifying the number of meaningful factors to retain, based on the scree plot and the percentage of variance accounted for by a given factor. Using the scree plot, we plotted the eigenvalue (i.e., the amount of variance that is accounted for by a given factor) associated with each factor and looked for a break between the factors with relatively large eigenvalues. Factors that appeared with eigenvalues equal to or more than one were assumed to be meaningful and were retained for rotation (Stevens 1996). The second step involved an oblique rotation on the retained factors to help with interpretation. An oblique rotation was applied and later confirmed that the factors would be correlated with one another. Step 3 involved interpreting the rotated solution by identifying which items load on each retained factor, the conceptual meaning of items that load on the same factor, and conceptual differences in items that load on different factors. In the factor designation, individual loadings of 0.4 or greater were used to interpret the results (Field 2005).

Results

Of the 60 medical academic members who participated in the study, 67% were male and 33% were females. The mean age for men was 43 and 44 for female. In terms of teaching experience, 42% of the participants had between 11and 20 years of teaching experience, while 12% had more than 21 years. Also, 81% of them were assistant professors, 17% associate professors, and only 2% professors. The results showed that the respondents had a positive attitude related to e-learning and there was a significant difference between instructors’ computer competency with technical and pedagogical readiness on e-learning. Results also showed that the mean of readiness on e-learning for faculty members was 3.25 ± 0.58 in the technical and 3.37 ± 0.49 in the pedagogical readiness domains. There was no significant correlation observed between variables, such as gender (r = 0.04, p = 0.74), age (r = 0.02, p = 0.88), academic ranking (r = 0.09, p = 0.48), and teaching experiences (r = 0.15, p = 0.24) with technical readiness for e-learning. But the results showed that instructors’ technical readiness scores were associated with computer competency (IT skills) among instructors (r = 0.64, p < 0.05). The information is summarized in Table 1.

Table 1.  Correlations between demographic with technical and pedagogical readiness

Category	Technical readiness	Pedagogical readiness
Gender
Pearson correlation	0.04	0.12
Significance (two-tailed)	0.74	0.36
N	60	60
Age
Pearson correlation	0.02	0.18
Significance (two-tailed)	0.88	0.17
N	60	60
Academic rank
Pearson correlation	0.09	0.10
Significance (two-tailed)	0.48	0.40
N	60	60
Teaching experience
Pearson correlation	0.15	0.25
Significance (two-tailed)	0.24	0.05
N	60	60
IT skills
Pearson correlation	0.64**	0.59**
Significance (two-tailed)	0.001	0.001
N	60	60

Note: **Correlation is significant at the 0.01 level (2-tailed).

Concerning correlation between categories that involved technical readiness, the highest readiness scores were obtained regarding technical skills and habits (r = 0.95, p < 0.05) as well as knowledge and skills (r = 0.75, p < 0.05) whereas the lowest ones obtained were related to technical knowledge and attitude (r = 0.07, p < 0.05) and attitude with skills (r = 0.19, p < 0.14). The results are summarized in Table 2.

Table 2.  Correlations between technical and pedagogical readiness factors based on category among instructors

Category	Technical factors	Pedagogical factors
KA
Pearson correlation	0.067	0.071
Significance (two-tailed)	0.000	0.59
KS
Pearson correlation	0.72**	0.57**
Significance (two-tailed)	0.000	0.000
KH
Pearson correlation	0.75**	0.31*
Significance (two-tailed)	0.61	0.01
AS
Pearson correlation	0.19	0.31*
Significance (two-tailed)	0.14	0.18
AH
Pearson correlation	0.21	0.42**
Significance (two-tailed)	0.10	0.001
SH
Pearson correlation	0.95**	0.83**
Significance (two-tailed)	0.000	0.000

Notes: K, knowledge; A, attitude; S, skills; H, habits.

*Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed).

Table 3 shows the extracted factors with Factor Loadings and interpretative labels. In this exploratory factor analysis, with respect to technical knowledge readiness, two factors were identified that explained 77% of the total variance among items that represented having knowledge regarding “how to search for e-resources, design, develop, delivering e-material, and communicate with students by providing study guides for e-learning.”

Table 3.  Factor loadings of the instructors’ e-learning technical readiness with interpretative labels

Category	Factor	Items per scale	Factor loading range
Knowledge	Factor 1 – familiarity with online education	6	0.83–0.92
	Factor 2 – familiarity with LMS	4	0.81–0.90
Attitude	Factor 3 – willingness to teach adopting new technology	7	0.70–0.87
	Factor 4 – willingness to have innovation in instruction	2	0.64–0.90
Skills	Factor 5 – ability to deliver e-material	5	0.68–0.85
	Factor 6 – ability to provide e-content	5	0.69–0.86
Habits	Factor 7 – being accustomed to the virtual environment	8	0.63–0.80

In addition, the results of factor analysis regarding technical attitude identified two factors that had also eigenvalues above one that explained 56% of total variance. Thus, comprised items related to “having a positive attitude toward using computer and Internet, improving the quality of teaching via using educational technology and taking a positive approach with respect to the use of new teaching method in education.” Factors such as “willingness to develop teaching via new technology and using e-learning as viable alternative to traditional methods” showed that faculties are comfortable with change and the development in the educational system.

The exploratory Principal Component Factor Analysis (PCFA) on technical skills identified two factors that explained 65% of the total variance among the items and represented “having ability to deliver e-material, ability for learning and teaching using e-learning technologies, and creating and providing e-material and technical guidance for e-learner.”

In addition, items such as “accustomed to use computer and Internet to provide, design, and deliver e-material, using virtual learning environment” loaded on a factor in technical habits readiness for e-learning and they are essential aspects in readiness that can be considered for e-learning (Table 3).

Factor analysis also was applied to identify the factors affecting the e-learning pedagogical readiness of educators. By PCFA, extracted factors and interpretative labels are suggested for each of factors according to their statements in this domain. Table 4 gives summary details of the extracted factors with labels. Factors such as “familiarity with online teaching principles in pedagogical knowledge domain,” “comfortable with using technology in instruction,” and “comfortable with developing course material” emerged in the attitude domain, and for the skills domain, factors that emerged were “ability in designing content and e-material,” “ability in online outcome evaluation for teaching” and “ability to use online management.” In the habits domain, factors discovered were “accustomed to the use of multiple strategy and multiplicity approach.” The results are summarized in Table 4.

Table 4.  Factor loadings of the instructors’ e-learning pedagogical readiness with interpretative labels

Category	Factor	Items per scale	Factor loading range
Knowledge	Factor 1 – familiarity with online teaching principles and methods	9	0.67–0.91
Attitude	Factor 2 – willingness to use technology in instruction	5	0.45–0.71
	Factor 3 – willingness to e-material development	5	0.64–0.90
Skills	Factor 4 – ability to use online management skills	1	0.84
	Factor 5 – ability to design content of e-material	5	0.69–0.86
	Factor 6 – ability to evaluate online outcome	6	0.65–0.91
Habits	Factor 7 – accustomed to multiple strategy	4	0.71–0.94
	Factor 8 – accustomed to multiplicity approach	4	0.68–0.88

Discussion

The purpose of this study was twofold. The first was to assess the readiness of instructors (faculty members) regarding e-learning and the second was to identify the most important factors that affect readiness in order to implement e-learning in CME programs at Universities of Medicine in Iran. The results showed that the medical academic members had a positive attitude related to e-learning and there was a significant difference between instructors’ computer competency with technical and pedagogical readiness on e-learning. Thus, it can be considered as an important aspect in readiness for e-learning. Tucker, Pigou and Zaugg (2002) recommended that to ensure the successfulness of implementing e-learning in an organization, the staff should be able to work easily and cosily with Web technology. Also, Driscoll (2002) stated that the tutors should be skilled and responsible for the teaching of asynchronous and synchronous e-learning programs. They should also participate in the evaluation of the educational process as well as in the design of the educational content. Moreover, those persons involved in the development of the e-learning program should have relevant knowledge and experience. In particular, Driscoll (2002) stated if the e-learning program is decided to be promoted inside the organization, the persons involved are required to demonstrate some experience on the e-learning design and delivery and to be familiar with an instructional systems development, which is necessary in order to lead the whole process through the stage of analysis, design, implementation, and evaluation.

The results of the PCFA identified factors on each category in technical readiness domain that indicated on the familiarity and ability to locate, evaluate, use information for their online learning, and also regarding the skills to use a variety of multimedia. The findings of this study are consistent with Muirhead (2000) who mentioned that educators without reliable computer knowledge and skills will be frustrated.

In addition, the extracted factors on pedagogical domain were corresponded to familiarity with online teaching principles and methods and also the ability to use online management, multiple strategies, and multiplicity approach that included the awareness of theoretical basis in instructional design and the ability to link theory to practice. In this regard, Dabbagh (2005) stated that instructors must have a reflexive awareness of the theoretical basis in primary instructional design and the ability to link theory to practice in a methodical approach. This is because awareness from the instructional strategy allows the online instructors to adopt a grounded design approach. This approach gives instructors an understanding of the differences in the online learner, course, and learning strategies, as well as fostering the understanding of the online learner's needs and challenges. In addition, it is necessary for faculty to have a fundamental understanding of the compound issues regarding the official and principled uses of technology. Because awareness from the instructional strategy allows the online instructors to adopt a grounded design approach, use of active learning method and compound strategy in course design and assessment of e-learner was one of the critical components that were emphasized by instructors. This was because in online learning system the instructors are not always present to conduct teaching; thus, it is essential to have good e-material course and clear instructions. In regard to this issue, Brookfield (1986) stated that if instructors were capable of creating a curriculum and setting for online learners, they will be able to develop their latent self-directed learning skills. Further, concerning the instructional strategy readiness, the Illinois Online Network (2007) recommended that it is important for educator to adapt multiple teaching strategies to meet the needs of diverse learning styles in an online class. Therefore, instructor readiness is one of the significant requirements for improving e-learning system, because other critical factors on successful e-learning, such as learning resources design and improve students’ capacity to prepare for online learning are related to this factor. Moreover, Ellet and Naiman (2003) pointed out that instructors must pay attention to the instructional design principles in their online course design, because basic knowledge and understanding of the legal and ethical use of technology are required to deliver online courses. Nevertheless, they pointed out although there are many skills that instructors need to be successful in an online environment, such as planning, organization, and self-discipline, they are the same ones they use in the traditional system. Nonetheless, they require more time and greater incentives for designing and developing an e-learning course. However, there are some differences compared to the traditional method, for example, the ways in which the online curriculum is delivered are new and very much different from the traditional approach. This is a critical factor influencing the success of e-learning. It is not only related to e-learning content and providing a volume of texts, Word, or PowerPoint documents, but is also an essential element of e-learning in the teaching process that emphasizes communication and interaction with students. Also, during the designing of the educational content, the teaching principles and theories should be taken into account (Lee & Owens 2000; Driscoll 2002).

Conclusion

Academics’ readiness is a critical factor influencing the success of e-learning. It is not only related to e-learning content and providing a volume of texts, but is also an essential element of e-learning in the teaching process, that emphasizes communication and interaction with students. Also, during the designing of the educational content, the teaching principles and theories should be considered. Thus, it is essential for instructors to update their teaching methods; in this paradigm shift from traditional to non-traditional education system, they will need a set of online content and resources to facilitate the learning process. Also, technical readiness is one of the significant requirements for improving e-learning system, because other critical factors on successful e-learning, such as learning resources design and improve students’ capacity to prepare for online learning are related to this factor. Thus, universities of medicine, just like more organizations, turn toward the implementation of e-learning for the training of their human resources. A particular model to assess and identify factors that influence instructors’ readiness to improve them for the development of e-learning with other certain criteria, such as the acquisition of adequate technological infrastructure and adequate educational content of persons with the necessary skills and a developed culture which encourages learning and sharing of knowledge, is needed. However, based on factors that we identified, it suggests, training should be offered to instructors on a continuous, rather than a one-off basis so that their IT knowledge and skills is upgraded over time. This also suggests that further research is needed to identify items and factors which corresponded to other aspect of e-learning in educational system.

Acknowledgments

We thank the academic members in Kerman University of Medicine who participated in this study, Associate Professor Dr Nozar Nakhaee and Associate Professor Dr Ali Akbar Haghdoost in the University of Medical Education Sciences in Kerman, Iran, for their expert statistical advice.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.