Keywords
COVID-19, Education, Faculty readiness, Administration, Remote working.
This article is included in the Emerging Diseases and Outbreaks gateway.
This article is included in the Coronavirus (COVID-19) collection.
COVID-19, Education, Faculty readiness, Administration, Remote working.
The introduction section of the manuscript is edited. In the method section, the use of confirmatory factor analysis is stated. The cut-off values of CFI, the reason for CFI and RMSEA equivalence is described. Few unnecessary tables were removed and table numbers were reordered. Figure 1 has been updated and data link has been provided.
Also, the related references (Daumiller et al. 2021; Valsaraj et al., 2021) are provided at the end of the manuscript.
See the authors' detailed response to the review by Shahul Hameed Pakkir Mohamed
Coronavirus disease 2019 (COVID-19) initially started in Wuhan city, China and then spread severely, affecting Western countries. It has infected approximately 16 million people and caused the death of approximately 600,000 individuals worldwide. In the U.S., more than 4 million people have been infected; and especially, in the Kingdom of Saudi Arabia (KSA), the cases of infection and deaths are increasing steadily. The transmission rate from infected people was found to be higher than that of the influenza virus with reproductive numbers between 1.4 and 2.5. In the KSA, to date (08.04.21), the total number of cases is 394,952 with 6,719 deaths and 381,189 recoveries (https://www.worldometers.info/coronavirus/).
To contain the spread of this viral infection, strict social distancing, quarantine and rapid testing are suggested to control the COVID-19 crisis (Giordano et al., 2020). Inadvertently, the important role of information technology has been felt in higher education (Ayers, 2004; Carr-Chellman & Duchastel, 2000). In the Kingdom of Saudi Arabia (KSA), the government suspended all onsite activities of universities and initiated digital-based distance learning and remote working strategies to control the spread of COVID-19. Based on the World Health Organization and Ministry of Health guidance, certain orders were issued such as staying home, working from home, being safe, and maintaining good hygiene. In the case when going out is a necessity, social distancing (2 m) should be maintained. The sudden health crisis affected the educational sectors and inflicted a long-term financial revision state pertaining to online education. In response to the Saudi government instructions, Imam Abdulrahman Bin Faisal University (IAU) swiftly moved to online teaching (March, 2020). It is a leading university promoting academic and advanced scientific research in the Eastern Region. It has various graduate courses and branches. It started with the College of Medicine and College of Architecture and provides strong health care services through the establishment of King Fahd University Hospital. The IAU campus and its 21 colleges spread across various places of the Eastern Province with student enrolment is currently approximately 45,000 students.
Besides, web-based advanced learning tools for online teaching have long been considered a prime importance for student coaching (Beaudoin, 1990; Beaudoin, 1998; Cohn, 2002; Zhang et al., 2020). Fortunately, various technological updated measures have already been recommended based on the KSA’s Vision 2030 (https://ndu.gov.sa/en/). Accordingly, several technological readiness measurements have been implemented by IAU. The advancement of the digital age with computer-based information technology was well realized, leading to the establishment of the Deanship of E-Learning and Distance Learning, IAU in 2010. The goal of IAU is to provide an e-learning platform to on-and off-campus students and expand the technology from universities to integrate regions and spread across the KSA. Currently, the digital platform that IAU uses is the Blackboard eLearning management system. The Deanship of E-Learning and Distant Learning lab at IAU is integrated with advanced high-performance IOS computers (Mac), Windows, platforms, visual viewers, studios, and soundproof capsules (to view and recording services). The presence of a digital lab enables interactive sessions, displays, video meetings, lectures, workshops, training sessions, uploading data in the Blackboard system and recording. IAU has advanced eLearning digital management facilities.
Concerning the faculty members, those were in place to suddenly move from traditional to online teaching without preparedness during COVID 19 pandemic. Such unexpected change made them puzzled and uncertain of managing the condition. It triggered them to highly concern about the teaching-learning outcomes (Daumiller et al., 2021; Valsaraj et al., 2021). Moreover, E-Learning has often been a challenging learning space that has exposed confrontation in acceptance from faculty members and students (Al-Hujran et al., 2013; Rosenberg & Foshay, 2002). Recognizing the desires and experiences of faculty members is essential to reveal their response towards online teaching and adaptation of techno-educational practices during the pandemic (Valsaraj et al., 2021). A recent study revealed the faculty members’ attitudes to the shift from traditional to online teaching and observed their associations with underlying drives and fatigue/engagement, and student learning. It is found that the faculty’s learning goals were associated to their perception of the shift as an optimistic encounter and useful for their competence development (Daumiller et al., 2021). A qualitative study has recently studied the experiences of faculty members over emergency remote teaching during COVID-19 pandemic. However, it has not included the faculty members of Saudi Arabia (Valsaraj et al., 2021). Therefore, the aim of this study was to analyze the significant role of the digital system and evaluate the readiness of IAU faculty members to transition to online teaching during COVID-19 using survey-based methods.
The exploratory study design was used to study the level of eLearning experience among the faculty members of IAU. Considering the abrupt changes in teaching mode during this pandemic situation, a questionnaire could effectively predict the characteristics and management of the advantages of e-learning by faculty members. The study was conducted from 8th March to 12th March 2020.
The study was approved by the Institutional Review Board (Standing Committee for Research Ethics on Living Creatures) with reference no. IRB-2020-17-148). Completion of the questionnaire by faculty members was taken as consent to participate.
This study was conducted at Imam Abdulrahman Bin Faisal University (IAU), which is located in the Eastern Region of Saudi Arabia. A convenience sampling was used in this study. All faculty members (N=2227) of IAU who were involved in online teaching during the COVID-19 crisis in the 2019–2020 academic year were considered the population of this study, as only these faculty members used and experienced IAU e-learning facilities. Access to QuestionPro by external (non-IAU) persons was prohibited; therefore, only IAU teaching faculty were included. Nonteaching staff/faculty of IAU were excluded. In order to address potential sources of bias, the population of this study only included faculty members.
A QuestionPro questionnaire with 22 questions on eLearning experience, training experience and skills and knowledge in the educational process of IAU faculty was implemented. Questionnaire was sent to participants using their university e-mail with a link to the questionnaire. The faculty members had to use their university email and password to log into the questionnaire via Blackboard dashboard. A specified time duration of 14 days to respond to the questionnaire was given to potential respondents. Two follow-up emails were sent that included reminders regarding answering the questionnaire.
The questionnaire was created through four brainstorming meetings with higher education experts and faculty members.
Three sections were included in the questionnaire, which aimed to evaluate: (section 1) the overall eLearning experience using Blackboard; (section 2) the skills and training provided to IAU faculty members to use eLearning; and (section 3) the management of classes and tests using the online learning tools. Section 1 had 8 items, section 2 had 9 items and section 3 had 4 items (total 21 items). The last item (22) was ‘How satisfied are you with our services’. Each item was a statement, and the answers respondents could choose from were as follows: strongly agree (marked as 1 in the data), agree (2), true sometimes (3), disagree (4), and strongly disagree (5).
Descriptive statistics were applied to reveal the level of eLearning experience among the faculty members of IAU. The internal consistency of the questionnaire was assessed using Cronbach’s alpha reliability test. Confirmatory factor analysis (CFA) with the principal component method was used to determine the construct validity of the questionnaire used. Furthermore, structural equation modelling (SEM) analysis was conducted using the AMOS (Analysis of Moment Structures) software 2020 to study the adequacy of the e-learning variables involved in the questionnaire. Pearson’s correlation was also used to examine the relationship between the e-learning variables and the faculty’s overall satisfaction. Besides, the effect of e-learning variables on the faculty’s overall satisfaction was evaluated using multiple regression analysis. All statistical analyses were conducted using SPSS version 22.0 at a 5% significance level. There were no missing data to address in this study.
Out of the 2227 potential responses, 634 completed responses were received (response rate, 28.5%).
Cronbach’s alpha was used as a benchmark to study the reliability of the questionnaire (Schakib-Ekbatan et al., 2019). The reliability value of Cronbach’s α coefficient ranges from 0.00–1.00. In the present study, the reliability of the statistics on the eLearning questionnaire using Cronbach’s α coefficient was found to be 0.940. This indicates that the questionnaire achieved a reliable standard of high consistency. Faculty’s perception of eLearning variables could be graded as ‘‘Good’’ (mean, 89.15; variance, 153.168; std. dev., 12.376). Cronbach’s alpha for each section was as follows: section 1 (evaluation of overall e-learning experience), 0.874; section 2 (training received), 0.940; and section 3 (applying skills and knowledge in the educational process through eLearning), 0.872.
Furthermore, the dimensionality of the instrument was analysed using CFA. KMO value (KMO=0.943) and Bartlett’s test of sphericity (value=10061.978, p<0.05) demonstrated that the raw data were suitable for the application of factor analysis. The common communalities of all the items had a value greater than 0.50, which indicated that the quality of the measurement was satisfactory. The factor analysis extracted four factors which conjointly described 70.767% of the variance in e-Learning experience of IAU faculty members (Table 1).
In this study, SEM analysis resulted in the model depicted in Figure 1, and the following characteristics: n=634, df=184, chi-squared=966.286, and p=0.000 (<0.05). Therefore, it is concluded that the proposed SEM model used in this study adequately fits the sample data representing IAU faculty members. The results of the relationship between each item and the proposed three dimensions show that the path coefficient between each item and the proposed 21-item questionnaire is positive and significant (p-value<0.05). The results show that there is a positive significant relationship between each item and the proposed three dimensions ranging from 0.290 to 1.339, which is given in Table 2. In this study, the values of Normed Fit Index (NFI), Relative Fit Index (RFI), Incremental Fit Index (IFI), Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) were observed as 0.905, 0.892, 0.922, 0.911, and 0.922, respectively (Table 3). These findings met the recommended values for model fit indices i.e. CFI ≥ 0.90; NFI ≥ 0.90; relative fit index (RFI) close to 1; IFI ≥ 0.90 ; and TLI ≥ 0.90 (Byrne, 2001; Kline, 2011; Renganathan et al., 2012; Shadfar & Malekmohammad, 2013). In addition, the proposed model demonstrated the Root Mean Square Error of Approximation (RMSEA) is 0.08 (p<0.05) (Table 4), which is equal to the recommended value, i.e., ≤0.08 (Byrne, 2009; Kline, 2011). From these results, it observed that the proposed model is a good fit since it met the recommended values of model fit indices.
Model | NFI Delta1 | RFI rho1 | IFI Delta2 | TLI rho2 | CFI |
---|---|---|---|---|---|
Default model | 0.905 | 0.892 | 0.922 | 0.911 | 0.922 |
Saturated model | 1.000 | 1.000 | 1.000 | ||
Independent model | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
Model | RMSEA | LO 90 | HI 90 | PCLOSE |
---|---|---|---|---|
Default model | 0.080 | 0.077 | 0.087 | 0.00 |
Independent model | 0.274 | 0.269 | 0.279 | 0.000 |
Table 5 shows the percentage of responses for each statement. The faculty’s perception of the quality of eLearning experience at IAU was found to be high (Table 6). A positive correlation existed between the eLearning variables that indicate an overall satisfaction with the provided services (Table 7).
How do you evaluate your e-learning experience | Training | Skills and knowledge | Overall satisfaction with e-learning | |
---|---|---|---|---|
How do you evaluate your e-learning experience | 1 | |||
Training | 0.333** | 1 | ||
Skills and knowledge | 0.357** | 0.447** | 1 | |
Overall satisfaction with e-learning | 0.354** | 0.465** | 0.622** | 1 |
This study observed a significant regression model (p<0.05), and three e-Learning variables described 18% % of the total variation in overall satisfaction among IAU faculty members. The value of R (0.424) indicated a weak positive relationship between e-Learning variables and overall faculty’s satisfaction (Table 8). Table 9 shows that three e-Learning variables such as e-Learning experience, training received, and knowledge and skills are significant predictors of overall satisfaction among IAU faculty members (p<0.05).
Model | R | R2 | Adjusted R2 | SE of estimation | F-value |
---|---|---|---|---|---|
Overall satisfaction with the e-learning process at IAU | 0.424 | 0.180 | 0.176 | 0.832 | 0.0001* |
Dimensions | Unstandardized β | Coefficients SE | Standardized coefficients β | t-value | p-value |
---|---|---|---|---|---|
Constant | 1.409 | 0.242 | 5.827 | 0.0001* | |
How do you evaluate your e-learning experience (as a faculty member)? | 0.231 | 0.054 | 0.179 | 4.286 | 0.0001* |
Training received | 0.206 | 0.55 | 0.177 | 3.737 | 0.0001* |
Applying skills and knowledge in the educational process | 0.207 | 0.062 | 0.160 | 3.356 | 0.001* |
IAU promotes leadership qualities, encourages and supports high-end basic and applied research activities (medicine, arts and sciences, and computing), and enhances researcher skills with state-of-the-art facilities. IAU has students and faculty members from different cities and regions. During onsite/traditional classes, the chance for infection and spread is high among students due to mingling. The online management and workload assessment of faculty are critical for strategic balance (Conceição & Lehman, 2011; Davies et al., 2005). This study was conducted to evaluate eLearning variables from the perspective of IAU faculty members using a questionnaire. The questionnaire’s reliability was studied using Cronbach’s α coefficient. The criterion value was statistically studied with KMO (Kaiser-Meyer-Olkin) and Bartlett’s test. The results indicated that all the items had a value greater than 0.50, which indicated that the quality of the measurement was satisfactory. Besides, SEM was used to evaluate the experience of eLearning at IAU. This model has been effectively used to analyse the structural variables in educational-based research (Jansson et al., 2019). Based on the survey study, a model was constructed using SEM analysis (Figure 1). The SEM study showed that items studied under the proposed three dimensions are acceptable for measuring the eLearning experience of IAU faculty members during the COVID-19 pandemic. Overall, the modules were found to be effective in the present situation and able to continue the practice of teaching and learning in the online mode of action. The expressed eLearning satisfaction level by faculty and online trainings adopted by IAU can be an effective strategy to combat online teaching challenges.
In the first section of the questionnaire, the eLearning experience of faculty was evaluated. The faculty members were asked about their experience using Blackboard, training, and applying their learned skills and knowledge through eLearning. Bower (2001) stated that online distance education requires effective training sessions and a change in the pedagogical approach. In addition, such a web-based teaching approach requires certain preassessment measures to ensure the validity and results (Buchanan, 1999; Carnevale, 2004; Schifter, 2000a; Schifter, 2000b). Our results show a unanimous level of satisfaction of faculty members using the Blackboard eLearning tool. In the first instance, the ease of using Blackboard received mostly positive responses of ‘strongly agree’ (50.3%) and ‘agree’ (38.7%), indicating a higher proportion of faculty members with a strong commitment to the online working mode of action. Broadcasting and recording lectures via Zoom using Blackboard received mostly ‘strongly agree’ (59.3%) and ‘agree’ (33.4%) responses. Very few responded ‘true sometimes’ (6.2%), ‘disagree’ (1.1%) and ‘totally disagree’ (0.0%). The positive responses of respondents indicate the ease of using the Blackboard platform to provide course lessons using menu items and conducting Zoom classes with students through built content options. In the case of Blackboard collaboration (virtual classroom), the ‘true sometimes’ (32.5%) responses increased, similar to the ‘strongly agree’ (33.1%) and ‘agree’ (30.8%) responses. Impressively, the disagreement response still has a lower proportion (<4%). An increase in ‘true sometimes’ indicates that respondents have some reluctance or reservation of using Blackboard as a video tutoring platform. Conducting online tests using this software was found to be easier as most respondents positively agreed (58.5%). In total, 26.8% of respondents answered ‘true sometimes’ while few disagreed (11.2%) and strongly disagreed (3.5%). Faculty members expressed positive agreement and strong satisfaction with the provided technical support (strongly agree, 49.8%; agree, 34.5%). Less than 4% expressed disagreement, while 12% responded ‘true sometimes’. Furthermore, stronger agreement was given by faculty members for the easy contact, responses and services provided by technical support assistance.
The second section of the questionnaire was related to the experience of the training received. Cho & Berge (2002) reported that a major barrier in distance training is administrative, technical experts and the infrastructure system. However, in the present study, a strong positive response was given to training experience. Respondents were also impressed and agreed on the trainer’s knowledge expertise on training topics. Strong affirmative statements were recorded for the trainer’s session management and the way they handled participants’ questions. Similarly, the trainer’s ability to communicate with trainees and the level of discussion received strong positive responses. Training experience using the Zoom platform, training time and training materials received positive responses. For the overall training sessions, approximately 7–15% of respondents expressed the statement of ‘true sometimes’ while very few provided negative responses.
The third section of the questionnaire was related to the application of skills and knowledge in the educational process through eLearning at IAU. Substantial positive responses with 47.3% of respondents answering ‘strongly agree’ and 42.7% answering ‘agree’ indicated that the organized training was consistent with faculty’s job goals. Similarly, the faculty revealed that they were able to apply the learned experience during their educational process (agreement of 43.7% and 43.8%, respectively). A high percentage of respondents agreed that training also contributed to developing specific skills that can boost their success in the workplace and accepted that they would also promote this training course to their colleagues. Overall, the faculty members expressed satisfaction with the provided Blackboard service.
The level of perception of faculty members with respect to eLearning experience at IAU was found to be impressively high with a mean score higher than 4 (Table 4). A positive correlation exists between eLearning variables that indicates an overall satisfaction with the provided services (Table 5). The results of the factor loadings on the eLearning scale showed that all items had values greater than 0.5, which indicated that the survey’s result quality was satisfactory (Table 6). The observed positive results of eLearning experience can be correlated to several IAU training initiatives offered to faculty members through the Deanship of Academic Development (DAD). Key training program approaches to online classes are classified into short training programmes, intensive training programmes and material resource support. The professional development training programme involves improving competency in teaching/learning, lecture preparations and mentorship training programmes. Training topics are based on assessment, surveys, reports to the Deanship of Quality and Accreditation (DQAA), student course evaluations, faculty, academic program evaluations, benchmarking teaching and learning practices, trainer questionnaires, and DAD forum recommendations. In addition, the training content materials were updated in the training portal on Blackboard and IAU website (DAD, 2020).
Mainly, the key strategy points focus on faculty online communication skills, leadership skills, conceptual thinking, learning as a team, teaching in a creative way, interpersonal student communication skills, deep learning, lecture planning, an artistic teaching approach and class management.
A faculty professional development series was conducted by IAU. The topics was related on utilizing educational technology and teaching methods. The framework includes theoretical backed interactive sessions, using technological tools to improve student engagement, motivating the students by improving the learning environment and intellectual concept activities, improving competency and fluency in English, microteaching (teaching through practice), metacognition (higher-order thinking), effective questioning strategies, avoiding common teaching mistakes, flipped classrooms (instructional strategy), knowing students’ learning styles and welcoming students on the first day of class.
The professional training for faculty also includes improving effective assessment and evaluation skills. The module covers the different types of concepts, methods, types and concepts based on assessment. Increasing questioning, thinking skills, teaching strategies and question paper setting tend to improve higher-order thinking capabilities. Faculty members are guided to use performance-based assessment and portfolios; improve the capability of analysing test results; establish question items to motivate higher-order thinking; assess project work and lab-based learning; and improve soft skills such as emotional intelligence, team-based work, interactions, metacognition skills and leadership. Furthermore, faculty members are trained on grading practices, effective rubrics and constructive feedback.
Importantly, a survey finding by Bonk (2002) stated that faculty members should be trained for online teaching in the online world. Considering such recommendations, the development series focused on mentoring benefits, improving oral communications, and 21st century skills (collaboration, critical thinking, communications, creativity, and emotional intelligence) in higher education. Training includes assessing new learning and teaching strategies, similar to the COVID-19 pandemic situation; and how to publish in journals related to education. The module comprises observation of classroom behaviours and interactions and the promotion of learning through activities. Faculty members were taught strategies for formulating key principles of critical thinking and student engagement. The adult learning concept and principles were taught to be applied in knowledge transfer from classroom to actual work settings, as seen in the current pandemic situation. The concept of self-efficacy from the perspective of faculty and department was the focus. Similarly, preventing faculty burnout during adverse situations such as COVID-19 and different strategies to overcome faculty burnout are taught.
The COVID-19 pandemic presents an unprecedented challenge in higher education. This study explored faculty readiness for online teaching during the COVID-19 crisis at IAU. The survey responses by the faculty indicate their high satisfaction using eLearning tools. The Blackboard online teaching software tool, recording lectures using the Zoom platform, virtual classrooms and online tests received strong positive responses. Faculty responded positively to the technical and training support rendered by IAU. Overall, the study found that the eLearning training and modules provided by IAU were effective in the present pandemic situation.
This study is restricted to the faculty members of a single public university, and future work can be conducted with the enclosure of all Saudi universities. In further research, the demographic data of faculty members can be included. Further, the relationship between demographic variables of faculty members (such as age, gender, nationality, highest educational qualification, current designation, and work experience) and their e-learning experience, training, and applying skills and knowledge in the educational process through e-learning can be revealed in future studies. Besides, the difference in overall satisfaction among faculty members concerning their demographic variables can also be studied. It is suggested to study the influence of demographic variables on overall faculty satisfaction with the e-learning process at their respective universities. A qualitative or quantitative research can be further carried out with Saudi faculty members to reveal the challenges or barriers facing faculty members while using Blackboard. This study also recommends that higher education administrators frame and execute uniform regulations to improve teaching faculty’s satisfaction with Blackboard.
Figshare: E-learning datasheet of Faculty readiness for online teaching at Imam Abdulrahman Bin Faisal University during the COVID-19 crisis: a cross-sectional study, https://doi.org/10.6084/m9.figshare.14406434 (Almahasheer et al., 2021).
Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).
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Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
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References
1. Chaichaowarat R: Teaching and Learning during the COVID-19 Pandemic: Attributes and Readiness of Thai Teachers. The Clearing House: A Journal of Educational Strategies, Issues and Ideas. 2023; 96 (2): 70-78 Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Teacher Education, Teaching and Learning, Curriculum Development, Design Thinking for education, Professional Learning Community (PLC)
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
No
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
No
Are the conclusions drawn adequately supported by the results?
Partly
References
1. Daumiller M, Rinas R, Hein J, Janke S, et al.: Shifting from face-to-face to online teaching during COVID-19: The role of university faculty achievement goals for attitudes towards this sudden change, and their relevance for burnout/engagement and student evaluations of teaching quality. Computers in Human Behavior. 2021; 118. Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Faculty motivation, experiences, and only teaching; structural equation modelling
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Musculoskeletal physical therapy
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Musculoskeletal physical therapy
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