Assessing the Factors of Lecturers’ Readiness in Open and Distance Learning
Sarah Yusoff1*, Nursyazni Mohamad Sukri1, Najlaa’ Nasuha Mohd
Radin2, Norkamruzita Saadon 3, Nor Ashikin Yusof 4, Nur Athirah Mohamad Hatta4
1Faculty of Computer and Mathematical Sciences,
Universiti Teknologi MARA, 21080 Kuala Terengganu, Terengganu, Malaysia
2Academy of Language Studies,
Universiti Teknologi MARA, 23000 Dungun, Terengganu, Malaysia
3Faculty of Chemical Engineering,
Universiti Teknologi MARA, 23200 Bukit Besi, Terengganu, Malaysia
4Academy of Language Studies,
Universiti Teknologi MARA, 23200 Bukit Besi, Terengganu, Malaysia
*Corresponding Author: [email protected] Accepted: 15 August 2022 | Published: 1 September 2022
DOI:https://doi.org/10.55057/ijares.2022.4.3.4
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Abstract: The Covid-19 pandemic pushes lecturers to adopt new norms, particularly open and distant learning (ODL), in their teaching. The first lockdown had a significant influence on the educational system at all levels, forcing all the lecturers at the university where the research was conducted to carry on with the teaching and learning process by utilising any online teaching resources that were available. The research aims to determine the relationship between ICT-equipment readiness, content readiness, ODL training readiness, students’
readiness, towards lecturers’ readiness. It also aims to explore the influence of all four factors towards lecturers’ readiness. A total of sixty-nine lecturers from various faculties responded in the online survey, and the data were analyzed using Pearson's correlation and multiple linear regression. The result reveals the existence of a relationship between the readiness of ICT equipment, content, ODL training, students, towards lecturers’ readiness. The regression model revealed the content readiness, and ODL training readiness factors significantly influenced lecturers’ readiness. The significance of the study is to suggest the educational institutions to take initiative in providing staff training so they can create instructional materials that suit their students' needs and promote open and distance learning for them.
Keywords: distance learning, higher education, online applications, online teaching, ODL, Covid-19
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1. Introduction
The deadly virus of Covid-19 has tremendously affected the education system across the world. Online learning becomes an essential element in ensuring the continuity of the teaching-learning process, specifically in higher education institutions. As the Covid-19 pandemic spreads, universities have taken measures by shifting from traditional method to the modern approach of teaching and learning with the use of various online tools by the lecturers.
These include online communication platforms like Skype, Microsoft Teams, Google Meet, Zoom, and Cisco Webex as well as social media applications such as Facebook, WhatsApp,
Twitter, and Instagram, which have turned into online educational tools used for teaching and learning. Several studies were done to discover the different forms of online tools adopted by educators during the pandemic. This includes a study on university students and lecturers in Indonesia which revealed that the five most favourite online applications used by them were Google Classroom, Zoom, WhatsApp, Google Meet, and Youtube (Yulitriana, 2020).
Another similar study was also carried out on the perceptions of stakeholders towards online teaching-learning process during the lockdown period which revealed that majority of the lecturers and students in the Mizoram University, India were using WhatsApp, Telegram and email to communicate with each other, submit assignments, and conduct class tests in spite of having numerous kinds of online modes of teaching and learning which even include the university’s own Learning Management System (LMS) (Mishra et al., 2020).
The university, which the research was conducted, developed its own LMS known as UFuture to complement the i-Learn system which was used previously by the lecturers and students (Chung et al., 2020). Nevertheless, many lecturers still prefer some other free platforms which are more user-friendly like Google Classroom and other social media apps like WhatsApp, Telegram, and YouTube for their teaching and learning activities (Chung, Noor, & Mathew, 2020). Students were also taught by the lecturers with the use of combination of online learning materials which include steps like pre-recording lectures which then uploaded to YouTube, posting the video links on Google Classroom, live streaming their lectures through Google Meet, Zoom, and Webex, as well as interacting with their students using instant messengers such as WhatsApp and Telegram (Chung, Subramanian, & Dass, 2020). In this Covid-19 pandemic situation, a high level of readiness is required so that educators can easily adapt to the new norms and adjust themselves to using a variety of teaching approaches and methods specifically in online learning (Dhawan, 2020).
Online learning has received much attention worldwide, especially when the COVID-19 pandemic hits the world and many institutions have shifted from offline to online learning pedagogy (Dhawan, 2020). To ensure that the teaching and learning process is continued, most of the operations at the higher learning institutions have been digitalised to cope with the current pandemic situation that requires minimal face to face interactions to contain the spread of the virus. The abrupt change of education landscape due to the catastrophe, triggers chaos and apprehension to both instructors and students. Recent literatures associate some of the prominent challenges faced throughout the open and distance learning which include technological, personal, environment, institutional and community (Baticulon et al., 2021; Dhawan, 2020; Jena, 2020).
Hence, this research was conducted to determine the relationship between ICT-equipment readiness, content readiness, ODL training readiness, students’ readiness, towards lecturers’
readiness. This study also aims to explore the influence of ICT-equipment readiness, content readiness, ODL training readiness, students’ readiness factors towards lecturers’ readiness 2. Review of Literature
Challenges faced by other universities during Open and Distance Learning (ODL) With the advancement of technology, open and distance learning requires both the instructors and learners to be able to fully utilise the digital technology. According to Anderson and Simpson (2012), the current ODL method adapts the use of teleconferencing, and extensively aided by vast online resources to support the learning process. However, recent literatures revealed that one of the most prominent challenges during ODL is technological aspects.
Dealing with unstable internet coverage and highly priced internet package, having insufficient skills and abilities with the use of technology in education and coping with unreliable and inconsistent platforms are among the most highlighted problems related to technology in ODL (Almohammed et al., 2021; Adnan & Anwar, 2020; Jena, 2020; Ilonga et al., 2020). This is further supported by Baticulon et al. (2021), where they pointed out that the abrupt shift of pedagogy affects their respondents’ learning process due to lack of technical facilities and limited access to devices and internet. These problems mostly arise because before the pandemic, most of the institutions have adopted the combination of online and offline pedagogies, and most of the facilities are prepared by the institutions. However, when everyone is bound to stay at home and obliged to continue their learning process via ODL, some of them do not have suitable devices and access to stable internet connection due to monetary and digital divide issue.
Apart from that, the absence of face-to-face interaction is also highlighted as one of the challenges faced by the learners during ODL. An effective teaching and learning process requires two-way communication between both parties, the teachers, and the learners. A recent study conducted by Almohammed et al. (2021) indicated that the respondents were mentioned to have difficulties to communicate with their training coordinators. Adnan and Anwar (2020), Ilonga et al. (2020) and Jena (2020) also highlighted similar problem in their studies, whereby insufficient face-to-face interaction with the instructor and other classmates caused the learners to have hard times during their ODL process.
ODL activities can be carried out in both synchronous and asynchronous modes. However, when the lesson is conducted in asynchronous mode, the communication becomes less effective due to less frequent response time. This is illustrated by Ilonga et al. (2020) which revealed that the participants received a delayed response time from the lecturer, thus making the communication becomes less successful. Similarly, Almohammed et al. (2021) also highlighted that the participants in their study were reported to experience problems to meet their classmates and work on team-based activities. This somehow affects their communication process to complete the task assigned to them. Johar, Elizar, Annisa, and Mailizar (2021) also carried a similar study among teachers attending online workshop during pandemic, and they concluded that the nature of asynchronous communication with the group members and instructors lead to difficulties to have effective communication with the other participants. Hence, this causes them to have hard time to engage with the others and complete the tasks assigned to them.
Suffice it to say, the education landscape has dramatically changed due to the pandemic and ODL activity has been extensively used by many educators worldwide. Though various challenges have arisen since its implementation, it is believed that everyone is still in the midst of adapting themselves with the new norm of learning.
3. Methodology
Population and Sample
All the university's lecturers were included in the population of this descriptive study, and 69 of them responded to the survey that was distributed online to lecturers throughout the university's three campuses.
Procedures and Data Collection
The questionnaire was distributed online to all lecturers in the university to assess their readiness in shifting the mode of teaching, from face-to-face to online classroom. Clear
instructions were provided in the form to ensure that all the respondents are lecturers.
The online survey questionnaire contains 2 sections; (1) lecturers were asked to describe their general demographics, such as age, gender, campus, field, faculty, higher degree level, year of service and rank, (2) there are four factors identified to measure the relationship of ICT- equipment readiness, content readiness, ODL training readiness, students’ readiness, towards lecturers’ readiness.
Table 1: Statistical Analysis
Objectives Statistical Analysis
To determine the relationship between ICT-equipment readiness, content readiness, ODL training readiness, students’ readiness, towards lecturers’
readiness.
Pearson’ Correlation
To explore the influence of ICT-equipment readiness, content readiness, ODL training readiness, students’ readiness, towards lecturers’ readiness.
Multiple Linear Regression
Table 1 shows the objective and statistical analysis of this paper. An overview of demographic information is given in the form of numbers and percentages. Pearson’ Correlation test is used to determine the relationship between ICT-equipment readiness, content readiness, ODL training readiness, students’ readiness, towards lecturers’ readiness among the 69 lecturers. Pearson’ Correlation value, which ranges from -1 to 1, can be used to determine the strength and direction of a relationship between two pairs of variables. If the statistical significance value (i.e., p-value) is less than 0.05, this indicates that the two variables are associated. However, if the statistical significance value (i.e., p-value) is more than 0.05, no additional examination on the strength or direction of the link is required. Additionally, Multiple Linear Regression is used to know what extend the influence of ICT equipment, content, ODL training, and students’ readiness towards lecturers’ readiness.
4. Results
Demographic Profiles
Table 2 displays the demographic profile of those who responded to the online survey. In this study, 84.1% of respondents were female while another 15.9% were males. Out of the three campuses, Dungun Campus had the highest percentage of responders (68.1%), followed by Kuala Terengganu and Bukit Besi Campuses. Additionally, the rank and year of service can be used to gauge a lecturer's experience. Table 2 shows six different categories of years of service, and 31.9% of the respondents to this survey had taught for between 11 and 15 years.
On top of that, senior lecturer made up 59.4% of the replies.
Table 2: Demographic data of the respondents to the online survey questionnaire
Variable Category Number of Subject %
Age 30 - 39 30 43.5
40 – 49 18 26.1
50 - 59 18 26.1
Less than 30 years 3 4.3
Gender Female 58 84.1
Male 11 15.9
Campus Bukit Besi 8 11.6
Dungun 47 68.1
Kuala Terengganu 14 20.3
Year of service Less than a year 4 5.8
1 - 5 years 6 8.7
Variable Category Number of Subject %
11 - 15 years 22 31.9
15 - 20 years 10 14.5
6 - 10 years 18 26.1
Over 20 years 9 13
Rank Contract lecturer (PTFT) 3 4.3
Lecturer 24 34.8
Senior Lecturer 41 59.4
Associate Professor 1 1.4
The division of the five-point Likert scale into mean-level scales is shown in Table 3. The Likert scale had five options, ranging from 1 (strongly disagree) to 5 (strongly agree). 5 is divided by 3 and subtracted from 1 to determine the mean difference, which divides the mean into three categories: low, medium, and high mean. As a result, the range for each mean is 1.22.
According to Table 3, the low mean level ranges from 1.00 to 2.33, the moderate mean level is between 2.34 and 3.67, and the high mean level ranges from 3.68 to 5.00. Ismail et al., (2022) also classified preparedness levels into three groups.
Table 3: Mean Score Range
Mean Scale Readiness Level 1.00 – 2.33 Low 2.34 – 3.67 Moderate 3.68 – 5.00 High
Table 4 shows the descriptive statistics for lecturers’ readiness. It is found that the mean value of lecturers’ readiness, ICT-equipment readiness, content readiness, and ODL training readiness are at high level, between 3.68 to 5.00 mean scale. While students’ readiness has moderate level, 3.12 mean scale.
Table 4: Descriptive Statistics for Lecturers’ Readiness
Construct Items Mean SD
Lecturers’
Readiness I know what ODL is. 4.28 0.725
I am ready to teach through ODL. 3.72 0.938
I am able to prepare my own ODL materials. 3.88 0.832
I am familiar with at least one ODL web application. 4.33 0.721 I am willing to spend time in preparing teaching materials for ODL. 4.36 0.747 I am interested to improve my teaching performance through ODL. 4.45 0.607 I can instil discipline my students to follow my ODL course. 3.97 0.84 I take any opportunity to explore more about the ODL web applications. 4.32 0.737
I have sufficient web skills to conduct ODL. 3.54 0.917
If any technical problem happens, I can overcome it. 3.51 0.98
Mean of Lecturers’ Readiness 3.98 0.628
ICT- equipment readiness
I have an internet connection at home. 4.51 0.834
I have a strong internet connection to conduct ODL. 4.04 0.962
The internet home is stable. 3.94 1.11
I have sufficient IT competencies to support ODL. 3.61 1.046 I am willing to buy new gadget (ipad, tablet, laptop, or webcam, etc.) for
my ODL courses. 3.78 1.069
I am willing to purchase the app(s) which in need to use in my ODL
courses. 3.65 1.012
Table 5: Cronbach’s Alpha
Variables Cronbach's Alpha Number of Items Level
Lecturers' readiness 0.927 11 Best
ICT-equipment readiness 0.796 7 Good
Content readiness 0.886 7 Better
ODL training readiness 0.892 7 Better
Students’ readiness 0.845 7 Better
39
The Cronbach's alpha value was used to provide the researchers with a quick and simple method of evaluating the reliable of a measurement. It is used by the expectation and assumption on a several variable while measuring the same underlying construct. A Cronbach's alpha value of 0.70 or higher is generally considered to be good, 0.80 or higher is better, and 0.90 or higher is the best (George & Mallery, 1999). Table 5 shows the Cronbach's alpha value
Overall, I’m willing to spend extra money from my ODL courses. 3.75 0.914
Mean of ICT-equipment readiness 3.94 0.691
Content
readiness I have adequate time to prepare online materials. 3.57 0.931 I can use more than one web application in my ODL courses. 3.86 0.959 I believe i could make my students understand the content through F2F
online discussions. 3.77 0.807
I am able to prepare good contents for my ODL courses. 3.68 0.795 I have sufficient content knowledge to prepare my ODL teaching
materials. 3.8 0.815
I have no problem in the English language when preparing my ODL
teaching materials. 4.17 0.727
Overall, I am confident with my ODL teaching materials. 3.72 0.838
Mean of content readiness 3.80 0.649
ODL training readiness
The institution provides me with online class trainings for online
pedagogy. 4.16 0.918
The institution provides me with appropriate trainings for ODL. 4.16 0.816 The institution provides me with trainings which could help me to prepare
for my ODL teaching materials. 4.23 0.910
I am willing to join online training classes on the ODL applications. 4.48 0.584 The online trainings provided by the institution help me to be more
confident to teach through ODL. 4.13 0.821
The online trainings provided by the institution help me to prepare better
teaching materials for ODL. 4.20 0.719
Overall, online trainings are important in helping lecturers to prepare for
ODL materials. 4.62 0.545
Mean of ODL training readiness 4.28 0.601
Students’
readiness My students know what ODL is. 3.74 0.7
My students have enough IT skills to learn through ODL. 3.49 0.72 My students do not have problem to access to ODL courses. 2.97 0.907 My students prefer online meeting instead of attending lecture in class. 2.7 0.896
My students have their own internet connection. 3.22 0.802
My students’ internet connection is stable for ODL. 2.52 0.851
Overall, my students are ready for ODL. 3.14 0.791
Mean of Students’ Readiness 3.12 0.585
for each variables used. The variable for lecturers' readiness with 11 items of questions had high reliability which Cronbach’s Alpha is 0.927 while the variables content readiness, ODL training readiness, and students’ readiness had better reliabilities which Cronbach’s Alpha is more than 0.8. The Cronbach’s Alpha value for the variable ICT-equipment readiness is 0.796 which means almost approach to better level of reliability. Overall, the result suggests that internal consistency of lecturer readiness is quite high.
Table 6: Correlation Analysis
Variables Pearson Correlation Significance Value Level
Lecturers' readiness
ICT-equipment readiness 0.479** 0.000 Moderate
Content readiness 0.886** 0.000 Very High
ODL training readiness 0.659** 0.000 Moderate
Students’ readiness 0.676** 0.000 Moderate
*Significant at 0.05 level of significance
As shown in Table 6, Pearson correlation test was run to determine the association between ICT-equipment, content, ODL training, students’ readiness towards lecturers’ readiness. All variables significantly correlated with lecturers’ readiness (p-value<0.05). With a significant level of less than 0.05 (p-value = 0.000) and r = 0.479, 0.659, and 0.676, respectively, there is a moderately positive linear correlation between ICT equipment, ODL training, and students' readiness with lecturers' readiness. The content readiness variable and lecturers' readiness variable have a strong correlation (r = 0.8886).
Table 7: ANOVA test and Model Summary Model
Sum of Squares df
Mean
Square F Sig.
R R Square Adjusted R Square
Regression 21.695 4 5.424 68.306 .000b 0.900 0.810 0.798
Residual 5.082 64 0.079
Total 26.777 68
a. Dependent Variable: lecturers' readiness
b. Predictors: (Constant), students’ readiness, ODL training readiness, ICT- equipment readiness, Content readiness
To assess the second objective, regression as well as an analysis of variance (ANOVA) were performed. ANOVA test results in Table 7 indicated that the model is significant with a p- value of 0.000 and a F value of 68.306. The regression analysis revealed that the model's accuracy in predicting the dependent variable was R = 0.900. R2 = 0.81 indicates how well the model explained the variance in the dependent variable. It is noticeable from these coefficients that the model seems to do a great job of estimating the dependent variable.
Table 8: Regression Analysis
Variable Beta Coefficients Sig. Correlation
(Constant) 0.207 0.462
ICT- equipment readiness 0.027 0.643 0.479
Content readiness 0.682 0.000 0.886
ODL training readiness 0.201 0.007 0.659
Students’ readiness 0.069 0.444 0.676
This study examines whether ICT-equipment readiness, content readiness, ODL training
readiness and student readiness contribute to lecturers’ readiness. The results of the regression analysis of two insignificant factors are show in Table 8, with the coefficient for ICT- equipment readiness is B = 0.027, p = 0.643, and for student’ readiness B = 0.069, p = 0.444 where p > 0.05. This result shows that ICT-equipment readiness and student readiness factors are not significant factor to lecturers’ readiness.
For content readiness, the coefficient is B = 0.682, p = 0.000, where p < 0.05. This result shows that content readiness factor is a significant factor to lecturers’ readiness. Content readiness factor has a strong positive relationship with lecturer readiness. The beta coefficient value indicates that every 1% increase in content readiness contributed to the improvement of lecturers’ readiness by 0.68%.
The beta coefficient for ODL training readiness is B = 0.201, p = 0.007, where p < 0.05. This result shows that ODL training readiness factor is a significant factor to lecturers’ readiness.
ODL training readiness factor has a moderate positive relationship with lecturer readiness.
The beta coefficient value indicates that every 1% increase in ODL training readiness contributed to the improvement of lecturers’ readiness by 0.20%.
5. Discussion and Conclusion
This study conducted to assess the factors of lecturers’ readiness towards open and distance learning. The findings in investigation phase revealed that while students' readiness is at moderate level, ICT-equipment readiness, content readiness, and ODL training readiness all exhibit high levels of readiness. Relationships between the four readiness factors were also examined. High correlations appear between lecturers' readiness and content readiness.
Another three factors, ICT-equipment readiness, ODL-training and students’s readiness shows moderate relationship towards lecturers’ readiness. Chen et al., (2022) is supporter of this result.
Based on the results of the regression analysis, it can be concluded that the readiness of the lecturers is significantly influenced by their readiness for ODL training and content.
Lecturers’ readiness in open and distance learning strongly depends on the contents or teaching material and ODL training to host online classes during the Covid-19 pandemic. Our findings were confirmed by Junus et al. (2021), who also contend that lecturers require training to enhance their capacity to provide online instruction and assist learners in preparing for it. These findings suggest that educational institutions should provide their lecturers with training to prepare engaging teaching materials and support online and distance learning for their students. Our results are consistent with the findings by Haron et al., (2012), who suggested that effective instruction on the benefits of technology plays a crucial role in realising the adoption of blended learning among academicians. Similarly, Gay (2016) highlighted the importance of knowledge and use of technology tools in online teaching.
According to García-Alberti et al., (2021), most students voiced their concern about instructors' lack of digital abilities and the time taken to generate new materials for online education takes a long time, even though it can be utilised in future sessions. In another study by Menchaca & Bekele (2008), discovered that an important component of success factors in open and distance learning is course design, such as structuring instructional materials into modules or units. According to Caliskan et al., (2020), universities should be prepared to for open and distance learning so that lecturers can get technological assistance. Integration of online technologies into educational processes can drive change among educators, while a
lack of organisational commitment to change can demotivate instructors and prevent change.
(Tonduer et al., 2019).
In general, technology in higher education is not a recent development. Malaysia universities are moving toward blended learning. Towards globally renowned university by 2025, an academician might consider the benefits of open and distance learning as they offer opportunities for educational innovation.
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