Factors of E-Learning Influencing Student Knowledge Research Proposal

Published: 2021-06-22 00:49:00
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Category: Education, Knowledge, Students, Students, Learning, Management

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Research question
What are Factors of E-learning influencing Students Knowledge?
Aims and objectives
The major aim of this study will be to determine E-Learning factors that influence the knowledge of students as far as management information systems and information technology is concerned. In order to realize this aim, the study will be aimed at achieving the following specific objectives:

To determine E-Learning factors that affects students
To establish the connection between student knowledge and E-Learning
To determine how E-Learning factors affect student knowledge.
To determine how negative E-Learning factors could be improved to facilitate student knowledge.
To determine how positive E-Learning factors could be promoted to enhance student knowledge.

In order to realize the above outlined specific objectives, the study will be seeking to answer the following questions.

What are the E-Learning factors that are influential on students in achieving knowledge in management information systems and information technology?
How is student knowledge in management information systems and information technology and E-Learning connected?
How do the E-Learning factors affect the knowledge of student?
How could negative E-Learning factors be improved to so as to facilitate the knowledge of students?
How could positive E-Learning factors be promoted so as to enhance the knowledge of students?

Scope of study
This research will be limited to the study of the factors of E-Learning that have influence on the knowledge of students. Arguably, lately, management information systems and information technology widely involves application of internet activities. Students under this field are taught on how they can apply their class knowledge with the internet at the workplace. Therefore, the basis of this study will be student knowledge and e-learning in general.
Literature review
Undeniably, various studies have been undertaken in the field of management information systems (MIS) and information technology. According to Venkatesh, Morris, Davis, & Davis, F. (2003), “management information system” is a term that is used to refer to a system that offers the knowledge that is required for effective management of organizations. On the other hand, (Sadagopan, 2004) defines this term as a discipline that aims at integrating computer systems with the objectives as well as goals of an organization. He further argues that advancement as well as management of the tools of information technology plays a significant role in assisting the workforce and executives in undertaking any work that is connected to processing of information.
According to (Mahmood, Hall, & Swanberg, 2001), MIS encompasses three most important resources: people, information, as well as technology. Although most scholars assert that the three are the key machineries when tackling issues in management information systems, a good number of them agree that the most crucial of the three is people. Notably, management information systems are taken to be a part of internal controls within any business organization. Taylor, & Todd (2005) argue that, it is important to demarcate between management information systems and ordinary information systems. From the academic point of view, MIS is widely used to imply the categories of methods of information management that are connected to the support or rather automation of human decision making.
Studies indicate that, utilization of communication and modern information technology purposely for learning has an impact on the knowledge of students, (Alexander & McKenzie, 2008). This explains why this issue has become a major issue in almost all the educational institutions as well as work life in the entire globe. According to Williams (2002), E-learning broadly refers to any king of learning that enabled electronically. In a narrower sense, it is the use of digital technologies in learning. To be more precise, it refers to any kind of learning that is enabled by internet or rather Web-based. Research indicates that, one of the significant breakthroughs in learning and teaching is the application of the internet educational activities. This is one of the reasons why most institutions of higher education have prioritized internet-enabled learning systems for their courses in e-learning, (Morss, 1999).
Nevertheless, it has been observed that there are various factors in e-learning that influences the knowledge that students acquire. Arguably, development of technology is taken to be tantamount with an improvement in efficiency of education, (Selim, 2003). Moreover, e-learning is advantageous in using information technology and the major aim of education lately is enhance the knowledge of students by introducing them to and taking advantage of contemporary technologies; which are usually used by businesses to acquire a competitive advantage. Therefore, based on the claim that factors of e-learning have an impact on the knowledge of students, it has become crucial to advance management of knowledge for e-learning, (Soong, Chan, Chua, & Loh, 2001)
Importance of the study
As mentioned above, a good number of studies have been undertaken in this field. However, it is expected that at the end of this study, knowledge about the issue in question will be improved. Precisely, E-Learning being a recent area of technology which is being widely used lately, the study will add to the existing knowledge by determining factors of E-leaning that have an impact of the knowledge of students and how the positive factors will be promoted as well as how to reduce the limitation the negative factors on improving the knowledge of students in the area of information systems as well as information technology.
Methodology
E-learning and student knowledge is a very sensitive subject. Therefore, the success of this study will be attributed to the kind methods that would be used. As such, both quantitative as well as qualitative methods will be applied in this study. Nevertheless, in comparison with qualitative methods, quantitative methods will be widely used. It is evident that there are several methods which are usually used in undertaking a research work, depending on the nature of study that is to be undertaken, (Patton, 2000). Some of the methods mostly employed in a research study include; questionnaires, sample survey as well as a census. Sample survey involves an analysis of a small population from which an inference about the entire population is made.
Conceptual Model
The proposed conceptual model to be used in this case is The Technology Acceptance Model (TAM). Notably, this is an edition of reasoned action theory which is customized for modeling acceptance of information systems by users. Therefore, it can be argued that it is some kind of intention-based model. Based on the reasoned action theory, attitudes influence beliefs, which in turn would lead to intentions, which the breeds behavior. According to TAM, the factors that are relevant in influencing the acceptance of IT behaviors are perceived ease of use and perceived usefulness, (Williams, 2002). The two factors are the result of various variables which falls outside TAM. Diagrammatically, Tam can be represented as follows.
In this case, the perceived ease of use represents the extent to which students believe use of technology in learning requires little effort; and on the other hand, perceived usefulness implies the degree to which the student believes that use of e-learning will contribute to improvement of his/her knowledge. TAM forms the basis of future research in computer and information technology. Originally, it was developed mainly to examine the use of IT in the work place. However, in the recent times, it has been used in e-learning domain, (Williams, 2002).
Research design
Based on the nature of this study, the best research design that will be applied is the sample design. It should be noted that the main parties to be involved in this study are both students and instructors probably in higher educational institutions where e-learning is common. Therefore, the sample that will be analyzed will be comprised of both the students and instructors from almost all the major higher institutions of learning throughout the country. For reliable conclusions as well as recommendations to be reached, the sample under investigation should be representative, (Chapman, & McNeill, 2005). Therefore, this will call for a decisive sample design which will ensure the representativeness of the sample.
Undeniably, there are various techniques of sample designs. However, the best technique in this case will be the random sampling, based on its simplicity. Before choosing the sample units, the all higher learning institutions will be listed. Thereafter, a certain number of participants will be chosen from each institution depending on the required number of the total sample. Based on the fact that is a large population of students in institutions of higher learning, the sample size is expected to be also large. Precisely, a sample size of approximately four thousand from all these institutions is projected to be relatively big enough to make inference on the entire population, (Creswell, 2001).
However, an equal number of student and instructors will be selected from each institution. Although not a major require, it will be better if the participants that will be involved in this study to be comprised of student who are taking a course in basic computer literacy as well as their teachers. The main reason for this proposition is that these are the people who widely use internet services in this course. However, other students can be involved as they also use internet services in tackling as well as submitting their assignments and research work.
It is important to note that, there are several advantages that will be associated with sample design in this study. To begin with, it is economical both in terms of time as well as cost. Based on the fact that the sample to be analyzed is small, time and costs involved will be relatively small. Secondly, this design is reliable. This can be explained by the fact that there are high chances that the information gathered from the sample will be true; therefore, the probability of reaching the correct conclusion and recommendations are high, (Chapman, & McNeill, 2005). Thirdly, the data obtained from this sample could be vital in checking the accuracy of the data of a census study under the same field. Lastly, the populations under investigation in this case are partly accessible. Therefore, sampling will take care of this problem. Precisely, some of the attributes of a good sampling design are; truly representative, viable economically, adequately large, easy to apply results to the general population, similar to the population, and it should have all the characteristics of the population.
Data collection
As mentioned above, this study will be undertaken through the application of both the quantitative and qualitative methods. The most practically viable method that will be used to gather information in this case will be a sample survey. Before embarking on the actual data collection, a questionnaire that is aimed on answering the research question will be developed, (Salant, and Dillman, 2004). Due to sensitiveness of the study, a closed questionnaire will be required so as to avoid any biasness during data collection. After designing the research questionnaire, enumerators will be selected and trained before being sent into the field to collect data. The major objective of training enumerators is to ensure to create awareness on how they will be handling the respondents so as to ensure that full information is obtained from these respondents and also to avoid any biasness resulting from the acts of the interviewers.
After collecting data from the field, it will be compiled and made ready for further analysis. The first step in analyzing this data will be a descriptive. This will be use in grouping the data into different sets to ensure better results, (Chapman, & McNeill, 2005). This will be followed by a statistical analysis which will be aimed at analyzing the data in detail using the various statistical tools. Notably, some of the statistical analysis to undertaken in this case will be; the mean, mode, and the various percentages. Moreover, the results of the study could also be illustrated in terms of diagrams such as graphs and histograms. Finally, conclusions and recommendations on the entire population will be made based on the results that are obtained from the sample survey.
Like in the case of sample design, there are various advantages of using a survey in this case. Some of these advantages are; it makes it easier to collect similar data from different individuals based on standardized questions, it is easy to avoid biasness, it offers flexibility at the creation stage in making decisions on how the questions will be controlled to ensure the intended information is obtained, and lastly, it can be managed from anywhere using different means.
Limitations/ challenges of study design
Several challenges are expected to be encountered in this study. To begin with, are the challenges which are associated with the research design as well as the research methods that will be used. Arguably, it is very difficult to obtain a representative sample in the study of this nature. This is based on the fact that there are some errors connected with sampling. These are usually referred to as the sampling, which encompasses the difference between the population and the sample, (Creswell, 2001). Another problem which is associated with sampling is biasness. Biasness in this case refers to the tendency of preferring certain individuals while choosing the sample. It can also happen when the enumerators directly or indirectly influences the respondents during the data collection process. However, in most cases, sampling bias is mostly associated with application of a poor sampling plan.
Some error could also occur during the analysis process. These kinds of errors are usually referred to as non sampling errors. In most cases, this errors are made when incorrect information is put into record by the enumerators; either intentionally or unintentionally. For instance, due to various reasons, the enumerator may decide to fill the questionnaire on behalf of the respondents. In this case, incorrect information is recorded based on the fact that high chances are that this could not be the kind of information that the respondent intended to give. Besides, recording errors could also occur when erroneous figures are recorded during calculations, (Creswell, 2001). For instance, if a certain figure is omitted unknowingly when calculating the mean, the resulting figure will not be the right figure and it might lead to huge variations. Unquestionably, statistical analysis is a very technical area. Hence, special tools as well as personnel will be needed to assist in handling this segment of the study, which could be an added cost.
As mentioned above, there are chances that accessing the participants will not be easier. It is expected that some of the selected individuals to form part of the sample won’t be available during the material day when data will be collected from the field. This is a big challenge in the sense missing sample units will lead to a reduction of the sample size which might in turn cause the sample to be unrepresentative of the population. This could also be one of the causes of the biasness in the sample, (Patton, 2000). Besides the challenges that are associated with the research design, there are also other challenges which might be faced in this study. Some of these challenges include: time factor, in that they study could probably produce a better result if undertaken over a long duration; finances, based on the fact that personal funds will be employed in this study, offering attractive pay for the enumerators to motivate them to do a good work will be challenging. If all the above mentioned challenges are not handled carefully, wrong conclusions as well as recommendations may be made as far as the population under investigation is concerned, (Creswell, 2001).
Ways of handling these limitations
In order to deal with the above expected challenges, various mechanisms will be used. To begin with, the sample design and sampling plan will be made as easy as possible while taking into consideration not to compromise with the attributes of the sample in comparison with those of the population under investigation. Secondly, as mentioned, enumerators will be trained on how to handle the data collection process besides being informed on the importance of the study. Lastly, other sources of funds other than personal funds should be considered to avoid financial problems during the study.
Plan of work
Based on the nature of the study and the sample size to be analyzed, more time is expected to be spent on this study. Notably, enumerator will be moving from one institution to another throughout the country to gather information from the sampled individuals. Compiling and analyzing the collected data is not an easy task; therefore, it requires a lot of time to do it successfully. As such, it is expected that that approximately 21 weeks will be spent from the start to the end of the study. It is of importance to note that the projected time frame of the study is based on the assumption that all factors that have been taken into consideration will remain constant in the entire period of the study. The following is a schedule showing how this time will be spent.
Week 1-2
gathering all the needed resources for undertaking the study
Week 3-4
determining the institutions from which the sample will be selected from
Week 5-8
making the sample design and the sample frame, selecting the sample and finalizing all issues to do with sampling and the sample
Week 9-10
designing the questionnaires
Week 11-12
recruiting and training enumerators as well as supervisors; during this period, a pilot study could also be carried out as part of the training of supervisors and enumerators
Week 13-15
data collection
Week 16-19
compiling and analysis of the gathered data
Week 20-21
making conclusions and recommendations, and also releasing the results of the study.
Time allocation on the various activities has been based on the nature and technicality of the work to be undertaken. As an example, data collection and compiling as well as analyzing have been allotted more time in comparison to other activities mainly because relatively, a lot is needed to be tackled in the two activities as compared to others.
Bibliography
Alexander, S. & McKenzie, J., 2008. An evaluation of information technology projects in
university learning. Department of Employment, Education and Training and Youth Affairs,Canberra: Australian Government Publishing Services.
Chapman, S. & McNeill., 2005. Research Methods. New York: Routledge.
Creswell, W. J., 2001. Research Design: Qualitative & Quantitative Approaches. New York:
Sage Publisher
Mahmood, M. A., Hall, L., & Swanberg, D. L., 2001. Factors affecting information technology
usage: A meta-analysis of the empirical literature. Journal of Organizational Computing and Electronic Commerce, 11(2), 107-130.
Morss, D.A., 1999. A study of student perspectives on Web-based learning: WebCT in the
classroom. Internet Research, 9(5), 393–408.
Patton, M.Q., 2000). Qualitative evaluation and research methods. Newbury Park London New
Delhi SAGE Publications.
Sadagopan, S., 2004. Management Information Systems. Boston: PHI Learning Pvt. Ltd.
Salant, P. and Dillman D. A., 2004., How to conduct your own survey. New York: John Wiley &
Sons, Inc
Selim, H.M., 2003. An empirical investigation of student acceptance of a course websites.
Computers & Education, 40(4), 343-360.
Soong, M.H.B., Chan H.C., Chua, B.C. & Loh, K.F., 2001. Critical success factors for on-line
course resources. Computers & Education, 36(2), 101-120.
Taylor, S. & Todd, P.A., 2005. Understanding information technology usage: a test of competing
models. Information Systems Research, 6(2), 144-176.
Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F. D., 2003. User acceptance of information
technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 426-478
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Internet-based undergraduate materials for the teaching of key skills. Active Learning in Higher Education, 3(1), 40-53.

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