Research Article: 2024 Vol: 27 Issue: 3
The attitudes and perspectives of English language lecturers towards e-learning among students at Amboy University Wolso Campus.
Kedir Lemma Arega, Ambo University
Citation Information: Arega.K.L. (2024). The attitudes and perspectives of english language lecturers towards e-learning among students at amboy university wolso campus. Journal of Management Information and Decision Sciences, 27 (2), 1-13.
Abstract
In the opinion of English language lecturers, the use of supportive technology makes students more willing to learn English outside of the classroom and improves their language proficiency. Participation in e-learning depends on students' e-learning readiness and the attitude of English language lecturers and human resources, such as students and lecturers, are the most important components of e-learning programs. This study is a cross-sectional descriptive study, and the population of the study included all students and English language lecturers at Ambo University Woliso Campus. The reliability of the Watkins and Mishra attitude questionnaires in the present study was confirmed by calculating Cronbach's alpha coefficients of 0.91 and 0.90, respectively. The lecturers’ attitude toward e-learning was 90% moderate to good and 10% negative. The mean score of lecturers' attitudes showed a significant positive correlation with the mean scores of computers and Internet connection skills (r=0.48, p = 0.001). It can be concluded that the faculty members’ attitudes and student readiness regarding e-learning were at reasonable levels. Due to positive attitudes in universities about e-learning, it is recommended that instructors be taught continuously about technology awareness and how to acquire skills over time in e-learning so that the learning program can be optimally designed. Due to the increasing prevalence of the COVID-19 epidemic and the emphasis on distance education, it is recommended that infrastructure and other requirements be considered.
Keywords
Attitude; Education; E-learning; Willingness.
Introduction
Recent developments in e-learning have highlighted the need for information and communication technologies, increasing access to computers at higher levels of education, and universities facing challenges such as increasing demand for education, the need for economic activities to provide new resources, and the use of information technology to provide education services in the global market has caused universities to revise their traditional roles, and create new organizational structures (Panda & Mishra, 2007).
E-learning is one of the flourishing advances in educational technology (Shahzad et al., 2021). Along with the growth of technology and its manifestation in learning, experts in this field thought that they should respond to the educational needs of learners by starting e-learning education (Ayu, 2020). Information and communication technologies have changed life in many dimensions and led to new teaching and learning methods in the higher education system (Syed et al., 2021). The development of information technology in education has increased the flexibility of learner levels and lecturers and led to the expansion of new teaching and learning methods in educational institutions (Abbasi et al., 2021; Syakur & Sabat, 2020). E-learning has been recognized as ideal training, such as learning in any place and time, participatory learning, self-assessment, and self-strategy. It is believed that many e-learning providers have failed to achieve the primary goal of learning, so evaluating the quality, review, and promotion of e-learning is one of their tasks (Radha et al., 2020; Sajedi et al., 2021). Today, the impact of e-learning technology in the field of humanities is very significant and has led to the use of e-learning. It is suggested to hold training workshops to improve the readiness and attitude of lecturers and students, especially for lecturers who have the academic rank of instructor and undergraduate students. This research aims to evaluate English language student students' e-learning readiness and the attitude of English language lecturers at Ambo University Woliso Campus. Due to technological improvements, e-learning has grown in popularity in the field of education and has been incorporated into curricula at both universities and colleges. However, its success depends on how willingly students participate in it and how teachers view it. E-learning can help students with their language abilities when they are studying the English language, but how effective it is depends on the instructors. By examining the variables influencing students' willingness to participate in e-learning and their impressions of it, this study seeks to close this knowledge gap. The study will also examine the advantages and disadvantages of online education for both students and teachers. The research on the desire of Ambo University Woliso Campus students to participate in e-learning and the opinions of English language lecturers toward e-learning is lacking, which is a problem in this study. By examining the variables that affect students' willingness to participate in e-learning and the attitudes of English language lecturers about e-learning, this study seeks to close this gap. The study will also examine the advantages and disadvantages of e-learning for instructors and students alike. The study addresses the opinions of English language teachers, factors influencing students' willingness to participate in e-learning for English language learning, and possible advantages and difficulties for both students and instructors. It contributes to the body of literature by addressing the vacuum in research on English language instructors' opinions of e-learning and its effect on student involvement. It offers ideas for enhancing e-learning efficacy in English language education.
Review of Literature
How to prepare students for the complexity of the digital age and the world's changing societies is one of the biggest difficulties facing education in the 21st century (Bond et al., 2020). The quick inefficiency of earlier discoveries and knowledge, combined with significant advancements in science and technology, necessitate a type of schooling. While appreciating the challenges, students are actively learning and solving problems all the time (Anderson & Rivera-Vargas, 2020). According to several educational psychologists, learning environments should be set up such that each student works and learns according to their ability (Spector, 2020).
E-learning is a sort of individual education in which students can attain educational goals based on their talents (Sweller, 2020). They are taught how to learn, which is one of the educational aims. Students can learn at their own pace, location, and time thanks to advancements in information and communication technologies (Reinhold et al., 2020). The learner can pursue their studies despite work, family, disability, and geographical distance and have enough time to read, understand, and respond, encouraging and motivating them (Kloos et al., 2020). Of course, computer-assisted learning has its limitations, including the lack of accurate understanding of the Internet lack of full knowledge of its capabilities and functions, and the dependence of the learner's success on her technical skills in using the computer (Bedenlier et al., 2020). The advancement of information technology in education has boosted learners' and lecturers’' mental flexibility, resulting in the spread of novel teaching and learning methods in universities and educational institutions (Nurzhanov et al., 2021). From a systemic standpoint, it is required to offer conditions from many perspectives, which is referred to as electronic ready. It covers preparation for training policies, management, standards, content, law, finances, human resources, culture, security, hardware, networks, and support. Recently, technology has had a huge impact on e-learning in the humanities, which has encouraged its adoption. Students, lecturers, the field of education, teaching techniques, and e-learning are some of the other factors and variables that have an impact on the process of teaching English. A virtual learning environment's design and planning are quite intricate processes. To construct an educational environment over the network, appropriate infrastructure must be provided in addition to educational content (Bond et al., 2020; Vahedi, 2020). This infrastructure consists of educators, learning resources, and communication tools. However, to implement this learning system, each university must follow a set of guidelines that include the overall program goals and the learners' goals, assess the level of acceptance of e-learning, and compile a list of potential advantages and disadvantages based on the configuration of the current situation (Reinhold et al., 2020). The efforts of universities to improve students' technical abilities and acquaint them with the frameworks, legal guidelines, and models for teaching courses won't be successful, in other phrases, until people attain a certain level of cultural and skill preparation. Lecturers of English are one of the other key components of university e-learning. However, numerous studies have noted that a significant barrier to the development of e-learning programs is English language lecturers' reluctance to adopt new educational technologies. English language lecturers frequently voice worries and issues regarding taking part in e-learning, including a lack of free time, a lack of institutional support, and a lack of practical evaluation of their efforts. The success of the e-learning system, the continuation of the immediate process, and the faculty members' positive attitudes towards the creation of e-content can all be attributed to one of the most significant factors influencing intrinsic motivation in people (Alizadeh & Rezaei, 2020). To promote e-learning in universities and avoid bankruptcy, it is, therefore, crucial to look at students' and lecturers' attitudes as well as the appropriate design and technological infrastructure, promote the culture of using e-learning in educational affairs, develop e-learning skills among faculty members and students, and plan for electronic interaction between lecturers and students (Lund, 2020).
The term "e-learning" was first used to describe training methods that make use of the Internet and intranet technology Cross; quoted by Web-based learning, computer-based learning, network learning, virtual classrooms, and e-collaboration are just a few examples of the broad range of applications, procedures, and words that fall under this umbrella notion. The constructivist and participatory philosophies underpin e-learning. However, other experts believe that technology is the most crucial component because it can use the viewpoints of all methods to increase its efficacy. In the teaching and learning process, interaction is crucial. Using evolving technologies, e-learning offers enormous interactions for access to a wealth of information and communication, a potential that is severely constrained in traditional learning.
Cross who is widely regarded as the person who first coined the term "e-learning," identified the following six indicators of e-learning: The Internet is used for e-learning, which also includes the most recent information and a variety of teaching techniques (such as virtual classes, digital collaboration, simulation, etc.). New technologies that enable e-learning to execute administrative and managerial tasks including registration, tuition payment, monitoring the implementation of student activities, teaching and monitoring, and conducting remote evaluations are the foundation of this method of learning. E-learning, by definition, comprises leveraging web and Internet technology to produce educational experiences (Galvis & Carvajal, 2022). Since one of the major policies of Ambo University Woliso Campus is the use of modern teaching methods and recognizing that human resources, especially students and English lecturers’, are one of the most important components in the successful implementation of e-learning programs, assessing student readiness and the attitude of English language lecturers’ towards e-learning before the implementation of the plan allows university officials and policymakers to plan developmental plans in such a way as to create a harmonious and balanced environment for the realization of e-learning (Tayyib et al., 2020).
Vandana, 2021 in today's society, technology has had a huge impact on teaching methodology, resulting in the creation of "E-Learning" or "Technology in Education." This technique is critical because it meets the needs of today's students, who are not satisfied with traditional classroom methods that rely on lecturing and rote learning. Student involvement and participation in the classroom have improved dramatically as a result of technological innovation, notably in the study of English as a second language. The paper emphasizes the relevance and value of e-learning in English language teaching. Technology in education is critical for fulfilling the needs of today's pupils and developing English as a talent among students.
Methods
Design of the Study
The study's design is essential for determining the attitudes of English language lecturers and students at Ambo University Woliso Campus toward e-learning. It establishes the structure and methods of the research, ensuring a methodical and exacting process, accurate data collecting, and the accomplishment of goals. The research's success and impact are ultimately ensured by the chosen design, which also guarantees the findings' applicability and relevance.
The current study is a cross-sectional descriptive study that aims to look at how prepared students are for e-learning and how English lecturers feel about it in Ambo University Woliso Campus in 2020 after receiving written consent from all samples based on their informed and voluntary participation in the study, in Ambo University Woliso Campus made up the longitudinal and chronological scope of the study. They were chosen as instructors, lecturers, and assistant professors, respectively.
Participants
The study population included all English language students and lecturers at universities in Ambo University Woliso Campus, of which 402 students were selected as a sample.
Sampling
Convenience sampling was used as the sampling technique for students and lectures. The overall sample size was calculated at 402 students, taking into account the acceptable percentage of the willingness of 49% (based on Mousavi, 2014), statistical error of 5%, acceptable accuracy of 5%, and a 10% attrition rate. The ultimate sample size was determined to be 51 participants after taking into account the acceptable attitude percentage of 97% (based on Malaki et al., 2015), statistical error of 5%, acceptable accuracy of 5%, and a 10% attrition rate.
Data Collection Tool
The study will utilize both quantitative and qualitative data analysis methods. Qualitative data will be collected through interviews with English language professors, while quantitative data will be collected through a survey questionnaire given to students. Inferential statistics, such as correlation and regression analysis, will examine relationships between variables and factors affecting e-learning desire. Descriptive statistics will evaluate survey results, while thematic analysis will reveal patterns and themes in the qualitative data. This approach will provide a comprehensive understanding of the study problem and draw useful conclusions. Questionnaires demanding demographic data (5 questions total), faculty members' computer and Internet skills, and other subjects (17 questions) were used.
Moreover, a 20-item standard e-learning attitude questionnaire was employed in the study to assess the attitudes of the lecturers. The questions were scored on a 5-point Likert scale that rated 1 to 5. To establish the attitude, the total scores were first computed. Scores below 50% of the total score were considered low attitudes, and those between 50% and 75% of the whole score were considered moderate attitudes. Whereas, scores above 75% were considered good attitudes.
To analyze computer skills, the total scores were first calculated. Scores below 50% were deemed undesirable, scores between 50% and 75% were deemed favorable, and scores above 75% were deemed to be highly desirable. Thus, in the 17-question category of computer abilities, a score of 35 or less indicates a poor scenario, a score of 35 to 55 indicates a good situation, and a score of 56 indicates a very good situation. The relationship between attitudes and environmental factors including the computer and internet savvy of lecturers was also Examined. By computing Cronbach's alpha coefficient of 0.91 and the reliability of the Mishra attitude questionnaire with a coefficient of 0.90, the reliability of the Watkins questionnaire in the current study was confirmed.
The Watkins et al. (2004) and Trimer e-learning standard questionnaire, which has 24 questions in 8 categories (access to technology, skills, online communication, motivation, ability to learn through media, online group discussions, and important issues for success in learning electronically), was used in this study to assess students' readiness. A 5-point Likert scale that rates 1 to 5 was used to grade students’ readiness. score below 50% of the entire result was seen as low readiness, and those between 50% and 75% were regarded as average readiness. While results above 75% of the total score were regarded as good preparation. When measuring one's capacity to learn through media, Scores below six are indicative of little access to technology, seven to twelve are indicative of moderate access, and eleven or more are indicative of high access. And, scores below 21 indicate low skill, between 22 and 35 indicate average skill, and above 34 indicate good skill. Also, scores below 6 indicate low motivation, between 7 and 12 indicate average motivation, and above 11 indicate good motivation. Besides, Scores below 6 indicate low ability, between 8 and 11 indicate average ability, and above 12 indicate good ability. On the other hand, scores below 10 were considered low ability, scores between 11 and 15 were average ability and scores above 15 were good ability. Scores below 10 were considered low attention, scores between 11 and 15 average attention, and scores above 15 were considered good attention when measuring Internet group conversations with 4 questions.
Results and Findings
The data were analyzed from 402 students and university instructors to produce the results Table 1.
| Table 1 Distribution of Academics' Descriptive Statistics | |||||||
| Variables | Frequency (%) | Unstandardized Coefficients | Standardized Coefficients (Beta) | Lower Bound | Upper Bound | P-Value | |
| Sex | Male | 35(70) | 4.73 | 0.11 | -4.58 | 14.04 | 0.312 |
| Female | 15(30) | ||||||
| Age Group (Year) | <30 | 7(14) | -9.44 | -0.46 | -16.22 | -2.66 | 0.007 |
| 30-40 | 15(30) | ||||||
| 40-50 | 20(40) | ||||||
| >50 | 8(16) | ||||||
| Work Experience | <5 | 17(34) | 1.66 | 0.13 | -2.68 | 6.01 | 0.444 |
| (Year) | 05-Oct | 9(18) | |||||
| Oct-15 | 7(14) | ||||||
| 15-20 | 10(20) | ||||||
| >20 | 7(14) | ||||||
| Academic Degree | Instructor | 11(22) | -12.16 | -0.29 | -21.41 | -2.92 | 0.011 |
| Lecturers | 38(76) | ||||||
| Assist Professor | 1(2) | ||||||
Group1: Academics' Views on Online Learning
According to the results of the demographic features of faculty members, the biggest percentage of participants in the study was male (70%), age group 41-50 years (40%), and the work experience of faculty members was 14-21 years. Age and academic degree were found to be predictors of faculty member attitudes toward e-learning in a linear regression analysis. With increasing age and work experience, the negative attitude increased by 45% and 30%, respectively Table 2.
| Table 2 Distribution of Academics' Computer, Internet Access, and Mindset Capabilities (N=50) | |||||
| Variables | Mean (Sd) | Low | Moderate | Good | Correlation* |
| Frequency % | Frequency % | Frequency % | |||
| Attitude | 80.44(18.83) | 5(10) | 34(68) | 11(22) | P value=0.001 r=0.48 |
| Computer And Internet Connection Skills | 48.68(9.67) | 6(12) | 16(32) | 28(56) | |
| Palmer coefficient | |||||
The results showed that the range of attitude scores was 50 to 110, with an average (SD) of 80.44 (18.83). Only 10% of faculty members have a low attitude toward e-learning, while the majority of them have a moderate attitude. The majority of them possessed a high degree of computer and Internet connectivity proficiency, and there was a strong positive association (r=0.48) between their attitude and these abilities Table 3.
| Table 3 Frequency Distribution of Demographic Characteristics and Predictive Variables of Student E-Learning Willingness | |||||||
| Variables | Frequency % | Unstandardized Coefficients | Standardized Coefficients (Beta) | Lower Bound | Upper Bound | P-Value | |
| Sex | Male | 125(30.6) | 3.72 | 0.12 | 0.81 | 6.64 | 0.012 |
| Female | 283(69.4) | ||||||
| Age Group (Year) | 19-24 | 377(92.4) | 1.56 | 0.16 | 0.71 | 2.42 | 0.001 |
| 25-30 | 31(7.6) | ||||||
| Term | 2 | 21(5.1) | -2.35 | -0.25 | 3.26 | 1.45 | 0.001 |
| 3 | 18(4.4) | ||||||
| 4 | 48(11.8) | ||||||
| 5 | 38(9.3) | ||||||
| 6 | 150(36.8) | ||||||
| 7 | 98(24) | ||||||
| 8 | 35(8.6) | ||||||
The results of Table 3 show that the highest percentage of participating students were female (69.4%), the age group of 19 to 24 years (92.4%). The linear regression model showed that age, gender, and semester predicted e-learning readiness. Therefore, in females, it was 12% more than in males. Also, readiness significantly increased with increasing age by 16% and decreasing semester by 25%.
The results of Table 4 show that the e-learning readiness of the majority of participants was at a reasonable level (60%). Also, in terms of e-learning readiness areas were important issues in e-learning success (73.8%), online communication skills (71.1%), e-learning ability (46.6%), online chat (42.6%), and access to technology, respectively. (28.4%) and e-learning motivation (26.5%) was at a reasonable level Table 4.
| Table 4 Frequency Distribution and Percentage of E-Learning Readiness and Its Domains | ||||
| Variables | Low | Moderate | Good | |
| Frequency % | Frequency % | Frequency % | ||
| Components | Access to technology | 94(23) | 198(48) | 116(28.4) |
| Online communication skills | 17(4.2) | 101(24.8) | 290(71.1) | |
| Motivation of e-learning | 70(17.2) | 230(56.4) | 108(26.5) | |
| Ability to learn e-learning | 30(7.4) | 196(48) | 182(46.6) | |
| Online chat | 69(16.9) | 165(40.4) | 174(42.6) | |
| Success in e-learning | 14(3.4) | 93(22.8) | 301(73.8) | |
| Total | E-learning readiness | 9(2.2) | 154(37.7) | 245(60) |
Discussion
Discussions and interpretations of the research aims were included in this section. Four specific goals have been taken into consideration in this study to help reach the overall aim of "students' e-learning readiness and the attitude of English language lecturers in Ambo University Woliso Campus."
If researchers want technology to be successfully used in an organization, they should not only pay attention to the development of skills and personal knowledge of individuals but also improve their attitude towards the use of technology. The first goal of the study was to "determine the attitude of English language lecturers in Ambo University Woliso Campus on e-learning." In this regard, the findings of the current study indicated that most lecturers had favorable to extremely favorable attitudes about e-learning. In comparison, just 10% of people have a bad attitude.
According to Zolfaghari et al. (2010), 66% of lecturers had a positive attitude toward e-learning, and 34% of them had a completely good attitude toward it. No lecturers had a negative attitude toward e-learning, and their attitude was linked to a higher level of preparation.
In a different study, Sangwan et al. (2021) found that lecturers' attitudes were better than average and that these attitudes increased in direct proportion to the level of education and decreased in direct proportion to the level of work experience. These findings were in line with the findings of the current study. Sangwan et al. (2021) showed in a related study that most university lecturers had a favorable attitude about using e-learning as a teaching instrument. In this sense, lecturers' desire to employ e-learning was most strongly influenced by their perception of their usefulness and success.
In the studies, most lecturers had a favorable attitude toward e-learning and saw it as a tool to enhance students' learning (Radha et al., 2020; Sajedi et al., 2021; Shahzad et al., 2021; Syed et al., 2021). Age, education, teaching experience, and gender of lecturers were all related to their attitudes and views of e-learning; thus, female lecturers under the age of 42 and with less than 10 years of teaching experience had a positive attitude.
It has also been investigated how lecturers in some foreign nations feel about e-learning. According to Alsuelmi, the majority of Jordanian instructors had a generally positive attitude in this regard. 71.1% of instructors said that the Internet might be used for distance learning. They had the opinion that there is countless unexplored potential in this area. According to 70.2% of lecturers, this educational approach gives them more flexibility when teaching or learning. According to 64.5% of the lecturers, implementing this teaching strategy is very simple. More than half of the lecturers thought that this approach to instruction improved both teaching and learning. This approach increases students' motivation to study at a higher rate than other approaches due to better interaction and instructional efficiency.
The findings of the current study revealed that more than 88% of English language lecturers at Ambo University Woliso Campus had a moderate to positive attitude toward the level of computer skills of their lectures. This attitude was examined about some contextual variables, including demographics, computer and Internet skills, and perceived value. Their attitude and their knowledge of computers and the internet were significantly correlated (r=0.48). Age and academic standing were predicted, according to linear regression analysis. As a result, the unfavorable attitude increased by 46% and 29% with increasing age and work experience, respectively.
In a related study by Ahmadi Tehran University instructors were completely proficient in using the Internet and e-mail. However, 88% of them had no experience with computer programming. It was consistent with the findings of the current study that 78% of lecturers had access to a hand-held computer, 76% had high-speed Internet, and 76% had access to a professional database. Gender and clinical work experience were two criteria that affected lecturers' attitudes in the aforementioned study; in the case of males with clinical expertise, the attitude was more favorable than in other groups.
As per Obiero's study from 2021, faculty members felt that limited Internet access, a lack of student readiness, a lack of organizational support, a lack of personal interest in using technology, intellectual challenges, a lack of infrastructure, and technology were the most significant issues. These factors were examined in Shahzad's study from the year 2021, and they included a lack of tools and insufficient skills to execute e-learning. Indicators like reluctance to change, perceived value, computer self-efficacy, and a favorable attitude toward e-learning systems were demonstrated to be useful by Omoi et al. (2011). This hypothesis's conclusion is in line with those (Abbasi et al., 2021; Anderson & Rivera-Vargas, 2020; Ayu, 2020; Syakur & Sabat, 2020).
The third goal of the study revealed that the majority of students were moderate to well-prepared for e-learning, with only 2.2% of students showing low preparation. In this regard, Darab revealed that the average level of e-learning preparedness was 4.8 out of 10, and the lowest student readiness score was correlated to the equipment index, which was 9.58 out of 15. According to the current survey, 77% of students had access to equipment at a fair or reasonable level, indicating that students at Ambo University Woliso Campus were generally well-prepared in terms of equipment, which is inconsistent with the findings of the aforementioned study. Differences and inconsistencies may arise from different study periods. Students at Sistan and Baluchestan University were shown to be relatively prepared to participate in e-learning by Kamelian and Fazel when they looked at the prerequisites and viability of installing an e-learning system, which was similar to the findings of the current study. Examining pupils' readiness for e-learning in several international nations included (Anderson & Rivera-Vargas, 2020; Nurzhanov et al., 2021; Shraim & Zuheir, 2010; Spector, 2020; Sweller, 2020; Syakur & Sabat, 2020).
They looked at students' e-learning preparedness, usefulness, self-efficacy, desires, and obstacles. The stated findings indicated that although students were open to the value of e-learning, they were not yet ready to use it, which conflicts with the findings of the current study. The linear regression model revealed that age, gender, and semester predicted e-learning readiness in the fourth goal of "determining the association between e-learning readiness of students in Ambo University Woliso Campus with demographic characteristics." Women were more prepared than males by 12%. Furthermore, the level of readiness increased by 16% and 25% with rising age and decreasing semesters, respectively. Changiz et al. (2013) used the Walkins questionnaire to assess the e-learning readiness of 23 Isfahan University of Medical Sciences graduates. In the preceding study, scores greater than 3 in each category were considered adequate preparedness. In general, all students were well prepared. Motivation and online conversation had the lowest average preparedness scores. The level of preparation did not differ significantly by gender, but it did differ significantly by job status, with faculty members having higher levels of abilities and drive than other groups. In terms of the level of preparation, but not gender, the current study's findings were nearly identical to those of the previous study. This study's findings are compatible with those of (Bond et al., 2020; Kloos et al., 2020). For students at Fasa University of Medical Sciences, Bordbar investigated the conditions and viability of implementing an e-learning project in six areas: access to technology, skills, and online communication, motivation, ability to learn through media, Internet group discussions, and critical issues for success in e-learning. The findings indicated that students were less motivated and relatively well-prepared for e-learning. Additionally, the degree of student preparation rose steadily, which was nearly consistent with the findings of the current study.
Conclusion
The purpose of the study is to comprehend student attitudes about online learning and create efficient teaching and learning strategies for colleges. It also investigates the perspectives of English language professors and any potential effects on educational achievements. However, restrictions include the sample size and student self-reported data. For lecturers to successfully incorporate e-learning into their teaching practices, the study underlines the significance of comprehending students' willingness to engage in online learning. One of the most crucial factors in the successful execution of an e-learning program is the willingness and attitude of the human resources, particularly students and lecturers. The findings of the current study indicated that the majority of students were moderately well-equipped for e-learning. The majority of lecturers had a favorable to an extremely favorable opinion regarding online learning. To some extent, this shows that the institution, Ambo University Woliso Campus has the necessary human resources capacity to successfully implement e-learning programs. All were in good condition concerning access and skills. It is advised to improve both the attitude and readiness of lecturers and students, especially for lecturers with academic degrees and undergraduate students, given that lecturers' attitudes were significantly related to the level and status of students' "e-learning readiness with students' educational level."
Implication and Limitations
This study has important ramifications for the Woliso Campus of Ambo University's English language teaching and learning. It offers information about students' openness to participating in e-learning and the variables affecting their attitudes about this type of instruction. This knowledge can help create efficient e-learning strategies that cater to the needs and preferences of students. The study will also provide insight into how English language professors view e-learning and its potential influence on teaching and learning results. Using this understanding, professional development programs can be created to provide lecturers with the abilities they need to successfully incorporate e-learning into their classroom practices. The study is constrained by factors including a sample size that might not be representative of all students and an emphasis on English language learning. The study has certain drawbacks, though, including a sample size that might not be typical of the total student body, a concentration on English language teaching and learning, and a reliance on student self-reported data that might be prone to social desirability bias.
Competing Interests
A conflict of interest does not exist
Funding
Not applicable.
Availability of Data and Materials
Not applicable
Declarations
Ethics approval and consent to participate
Not applicable.
Consent of Publication
Not applicable
References
Abbasi Kesani, Hamed, Shams Morkani, Seraji, & Rezaeizadeh. (2021). Evaluation in e-learning: what, why, how. Development Strategies in Medical Education, 8 (1), 80-91.
Ahmadi, M., Rakhshanderou, S., Khodakarim, S., & Ghaffari, M. (2021). Internet addiction theory-based intervention among university students: A case of health belief model. Journal of education and health promotion, 10.
Indexed at, Google Scholar, Cross Ref
Alizadeh, N., & Rezaei, M. (2020). The mediating role of individual learning in the relationship between e learning and academic achievement (case study: students at Islamic Azad University of Mahmoodabad Branch). Journal of Cultural Management, 13(46), 97-114.
Anderson, T., & Rivera Vargas, P. (2020). A critical look at educational technology from a distance education perspective. Digital Education Review, 2020, num. 37, p. 208-229.
Ayu, M. (2020). Online learning: Leading e-learning at higher education. The Journal of English Literacy Education: The Teaching and Learning of English as a Foreign Language, 7(1), 47-54.
Indexed at, Google Scholar, Cross Ref
Bedenlier, S., Bond, M., Buntins, K., Zawacki-Richter, O., & Kerres, M. (2020). Learning by doing? Reflections on conducting a systematic review in the field of educational technology. Systematic reviews in educational research: Methodology, perspectives and application, 111-127.
Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2020). Mapping research in student engagement and educational technology in higher education: A systematic evidence map. International journal of educational technology in higher education, 17(1), 1-30.
Indexed at, Google Scholar, Cross Ref
Changiz, T., Haghani, F., & Nowroozi, N. (2013). Are postgraduate students in distance medical education program ready for e-learning? A survey in Iran. Journal of education and health promotion, 2.
Cross, J. (2004). An informal history of eLearning. On the Horizon, 12(3), 103-110.
Galvis, Á. H., & Carvajal, D. (2022). Learning from success stories when using eLearning and bLearning modalities in higher education: A meta-analysis and lessons towards digital educational transformation. International Journal of Educational Technology in Higher Education, 19(1), 1-31.
Indexed at, Google Scholar, Cross Ref
Kloos, C. D., Alario-Hoyos, C., Muñoz-Merino, P. J., Ibáñez, M. B., Estévez-Ayres, I., & Fernández-Panadero, C. (2020). Educational technology in the age of natural interfaces and deep learning. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 15(1), 26-33.
Lund, B. D. (2020). Do “interdisciplinary” disciplines have an interdisciplinary impact?: Examining citations between educational technology and library and information science journals. Education and Information Technologies, 25(6), 5103-5116.
Indexed at, Google Scholar, Cross Ref
Nurzhanov, C., Pidlisnyuk, V., Naizabayeva, L., & Satymbekov, M. (2021). Research and Trends in Computer Science and Educational Technology during 2016-2020: Results of a Content Analysis. World Journal on Educational Technology: Current Issues, 13(1), 115-128.
Indexed at, Google Scholar, Cross Ref
Panda, S., & Mishra, S. (2007). E‐Learning in a Mega Open University: Faculty attitude, barriers and motivators. Educational Media International, 44(4), 323-338.
Radha, R., Mahalakshmi, K., Kumar, V. S., & Saravanakumar, A. R. (2020). E-Learning during lockdown of Covid-19 pandemic: A global perspective. International journal of control and automation, 13(4), 1088-1099.
Reinhold, F., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. (2020). Learning fractions with and without educational technology: What matters for high-achieving and low-achieving students?. Learning and Instruction, 65, 101264.
Indexed at, Google Scholar, Cross Ref
Sajedi, R., Khorshidi, A., Hamidifar, F., Moghaddasi, H., & Mahmoodi, A. H. (2021). Designing and Validation of a Conceptual Model of E-learning in Iranian Universities of Medical Sciences.
Sangwan, A., Sangwan, A., & Punia, P. (2021). Development and validation of an attitude scale towards online teaching and learning for higher education teachers. TechTrends, 65, 187-195.
Indexed at, Google Scholar, Cross Ref
Shahzad, A., Hassan, R., Aremu, A. Y., Hussain, A., & Lodhi, R. N. (2021). Effects of COVID-19 in E-learning on higher education institution students: the group comparison between male and female. Quality & quantity, 55, 805-826.
Shraim, K., & Zuheir, K. (2010). Students' Readiness Towards E-learning. A case study of Virtual Classrooms for secondary education in Palestine. The 3rd Annual Forum on e-learning Excellence in the Middle East. Dubai.
Spector, J. M. (2020). Remarks on progress in educational technology. Educational Technology Research and Development, 68, 833-836.
Indexed at, Google Scholar, Cross Ref
Sweller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1-16.
Syakur, A., & Sabat, Y. (2020). The effectiveness of coopertative learning (STAD and PBL type) on E-learning sustainable development in higher education. Journal of Development Research, 4(1), 53-61.
Indexed at, Google Scholar, Cross Ref
Syed, A. M., Ahmad, S., Alaraifi, A., & Rafi, W. (2021). Identification of operational risks impeding the implementation of eLearning in higher education system. Education and Information Technologies, 26, 655-671.
Tayyib, N. A., Ramaiah, P., Alshmemri, M. S., Alsolami, F. J., Lind-say, G. M., Alsulami, S. A., & Asfour, H. I. (2020). Faculty members' readiness implementing e-learning in higher education Saudi Universities: A cross-sectional study. Indian Journal of Science and Technology, 13(25), 2558-2564.
Indexed at, Google Scholar, Cross Ref
Vahedi, M. (2020). The effect of E-learning readiness on self-regulated learning strategies and students’ behavioral tendency to web-based learning: The mediating role of motivational beliefs. Education Strategies in Medical Sciences, 13(2), 133-142.
Watkins, R., Leigh, D., & Triner, D. (2004). Assessing readiness for e‐learning. Performance Improvement Quarterly, 17(4), 66-79.
Indexed at, Google Scholar, Cross Ref
Zolfaghari, M., Negarandeh., R., Ahmadi., F. (2010). The effectiveness of a combined e-learning system in educating nursing and midwifery students of Tehran University of Medical Sciences. Iranian Journal of Medical Education 10(4), 398-409.
Received: 17-Jan -2024, Manuscript No. jmids-24-14388; Editor assigned: 20-Jan -2024, Pre QC No. jmids-24- 14388 (PQ); Reviewed: 27- Jan-2024, QC No. jmids-24-14388; Published: 29-Jan-2024