Quality of Social Media in Higher Education Essay

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Updated: Feb 1st, 2024

Introduction

In the Western world, the use of the internet is ubiquitous. Majorly, it is popular among all groups of the population regardless of their age and background. However, the group that seems to demonstrate the highest level of interest in digital technology, the internet, and social media are the younger people – children, adolescents, and young adults. Since these groups of the population are the most likely receivers of education, it is logical that the technologies tend to produce a rather heavy impact on the way they study, receive and pass information, and communicate with one another. In that way, for the higher educational institutions and their representatives to be able to communicate successfully with the students’ many universities and colleges start to create their own campus websites with libraries and helpful resources, their individual blogs related only to the internal and external matters of each specific institution, and their personal pages on the social network platform such a Facebook.

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This is done for the purpose to establish a productive and effective communication with the students and to help them handle some of the challenges they tend to face during their years of education. It sometimes happens that the university webpages or social network pages are not as helpful and interactive as the students would like them to be. In some cases, they are poorly designed, not managed well, and lack active supervision. At times, they are only designed to provide one-sided communication from the institutions to the students and do not provide space for the students’ self-expression, responses, complaints, and notifications. Qualitative research using the Servqual quality model and WEBQUAL tools was conducted in order to evaluate different aspects of the Facebook page of the University of Wollongong in Dubai and detect its strengths and weaknesses.

Overview

Social media technology is rapidly growing as a major web-space for exchanging crucial communication and data (Oswaldo 2015). The academic use of social media in higher learning institutions has grown by leaps and bounds in the past decade or so. When referring to social media, it basically refers to a channel for social interaction. It may also be used to imply all forms of applications that utilize either mobile or web platforms in facilitating the exchange of vital information. This may take place by creating, engaging, and sharing data on specific areas of interest.

The widespread use of social media through mobile or computer gadgets is real. As it stands now, Facebook and Twitter are among the most popular interfaces of social media platforms that engage tens of millions of users across the globe.

The profiles created on Facebook are allowed to engage and socialize with each other. Besides, Facebook users can discover commonalities among them alongside permitting the individual profile users to be connected as well as welcoming others outside the Facebook community to join it.

Current statistics indicate that there are over 750 million active Facebook profiles (Yeona 2014). The Facebook profile accounts comprise of both individuals and institutions. However, there has been growing concern regarding service quality in social media used by higher learning institutions. This literature review seeks to delve into the quality of social media and particularly Facebook in higher learning entities.

There is adequate literature documentation on social media use in higher education (Silius, Kailanto & Kailanto 2013). Stand-alone departments in tertiary colleges and universities use Facebook as a la carte tool for sending and receiving information. The same mode of using Facebook applies to administrative offices. The latter is a vivid indication that Facebook is not utilized as a wider and systemic commitment tool in higher learning institutions. For example, student blogs are being used by a number of admission offices in higher learning institutions to market departments of interest. Current student experiences are also highlighted in such blogs. Student volunteers and current students are also hired by higher learning institutions to spread positive news about their respective learning entities. Hence, there is a growing need to personalize students’ experiences so that higher learning institutions can attract more admissions. Needless to say, the millennial generation is highly receptive to such messages, and therefore, it is a relatively effective public relations approach.

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According to a recent study, the blogs created by these institutions have also been found to be quite effective in engaging both the current and prospective students (Kurkela 2011). However, some institutional blogs do not allow comments from readers or provide email subscriptions. According to WEBQUAL tool, lack of comments in blogs or email subscriptions hinders two-way engagement.

Blogs have been utilized as a pedagogical approach by institutions of higher learning. After creating blog articles, readers are given the opportunity to share their opinions using personal Facebook profiles (Sharda, Anita & Pragya 2013). They can also share the same stories on Facebook walls. Recent studies have dwelt much on the effectiveness of such blogs especially in teacher education, language learning, and sciences.

On a positive note, Facebook profiles created by faculties have been instrumental in bridging the formal space between faculty staff and students (Silius, Kailanto & Tervakari 2011). Members of staff can now relate more personally with students than it was in the past. Consequently, Facebook communities such as groups taking particular courses have been developed on Facebook (Wilson 2013).

The past two decades witnessed extensive study of conventional aspects of service quality (Scott & Stanway 2015). As a matter of fact, website service quality is a recent area of study. Websites can indeed assist in executing an effective and efficient learning process. Nonetheless, it is crucial to mention that service experience or expected outcomes should be evaluated before and after it has been used in order to determine its effectiveness. That is one of the core functions of WEBQUAL (Sancho & de Vries 2013).

Just as it is in the real world, it is possible to obtain the metrics or standards of a social media platform used by a higher learning institution. In this regard, WEBQUAL measures can be categorized into two broad areas. These include attitudinal and behavioral measures (Kivunja 2015). When the commercial effectiveness of a social media site is observed, it is referred to as a behavioral measure. It may entail but is not limited to the following metrics: new visitors, conversion rates, unique visitors, or number, and frequency of clicks. When it comes to attitudinal measure, it refers to conventional metric scales that assess client perceptions (Loiacono, Watson & Goodhue 2007). Learning institutions may also hire the services of experts to obtain metrics of the perceptions. Generally, WEBQUAL seeks to explore the effectiveness of social media sites in the following ways.

First, the quality of web material in any given social media site (or information quality) is obtained from an information system that handles all issues related to research (Pomerantz, Hank & Sugimoto 2015). Quality paradigms considered here include information relevance, format, accuracy, and appropriateness. Second, the quality injected in the research information system determines interaction quality. In other words, users are in a position to interact effectively and comfortably. In other words, social media sites such as Facebook and Twitter should be tailored in such a way that users in higher learning institutions can comfortably and securely interact. Third, ease of navigation, site appearance, and design account for overall usability (Boyko 2016).

Based on WEQUAL assessment, most social media sites for higher learning institutions lack email subscriptions and comments section. However, other attributes of web quality metrics are up to the mark.

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Methodology

In our research, we decided to use a tool called the Servqual quality model. Which is a quantitated tool that measures quality in the service sector. Servqual tools have been successfully used in other research which can be found in our literature review. The Servqual model helps us to understand and highlight the gap between the customer expectation and perception of the service they had received before according to several main diminutions. Above that, it will clear the path for us to meet customer expectations.

We conducted a questionnaire in personnel with a sample size of 121 undergraduate students (UOWD). Regardless, of their gender, nationality, major and other factors. In order for us to understand their expectation regarding the Facebook page of UOWD according to their perception of other colleges Facebook page.

The survey question in each dimidiation includes two parts which must be rated from 1 (strongly disagree) to 7 (strongly agree). And we concentrated on seven diminutions that are important to satisfy and fulfill the requirement needed.

The First primary diminution is the functionality and design of the page which creates the first impression of our users that can lead to the failure of the page if it’s not prepared carefully. Reliability and trustworthiness are the second diminutions, which pulls the customer toward visiting the page more often knowing that he can rely on the information on the page. Third, is responsiveness which is an important element for the users nowadays since time is critical and any delay can create an unpleasant customer. Next, is assurance, or as we can say building trust between the user and our page. Then, empathy help in creating a connection with the university and students. We also focused on content or information availability. Finally, we put in our consideration the importance of security of the user information in that page.

After conducting the survey we use SPSS software to analyze and make sure of the validity of the data.

Analysis

An analysis of data collected through WEBQUAL questionnaires is represented in this section. Two ways of analysis were conducted; SPSS software and finding the difference between perception and expectation using excel.

SPSS is a statistical analysis and reporting software to find the reliability of the data to a degree of stability and consistent results, reliability of the data in measuring what is purported to measure, and factor analysis in which redundancy and duplication variables are removed.

SPSS analysis

Reliability

Cronbach’s alpha is a measure of reliability in SPSS. It is used to determine the reliability of questions in the questionnaire.

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Table 1.0: Actual reliability statistics.

Reliability Statistics
Cronbach’s AlphaCronbach’s Alpha Based on Standardized ItemsN of Items
.955.95666

The Cronbach’s alpha is our survey data is 0.955, which indicates a high level of reliability.

Table 1.1: Item-total statistics.

Item-Total Statistics
Scale Mean if Item DeletedScale Variance if Item DeletedCorrected Item-Total CorrelationCronbach’s Alpha if Item Deleted
PQ1360.421862.4610.1990.956
PQ2359.861839.1940.4350.955
PQ3359.961845.3020.3480.955
PQ4359.811827.8490.5510.955
PQ5360.051825.4970.4980.955
PQ6360.561861.2130.1760.956
PQ7360.31845.230.3910.955
PQ8359.991837.670.5040.955
PQ9359.861831.8190.4630.955
PQ10360.041857.5960.2490.956
PQ11359.961830.1950.490.955
PQ123601853.50.2890.955
PQ13359.871844.5090.3860.955
PQ14360.381832.1660.4250.955
PQ15360.041829.5880.4710.955
PQ16360.421862.6920.1790.956
PQ17359.971829.740.5210.955
PQ18360.271823.0180.5120.955
PQ19360.111831.3810.5010.955
PQ20360.021835.6430.4740.955
PQ21360.311843.0190.340.955
PQ22360.451879.6780.0080.957
PQ23360.581857.0490.1610.956
PQ24359.751849.0090.3340.955
PQ25359.881835.9670.4970.955
PQ26359.891860.3280.2570.956
PQ27359.881853.8350.2930.955
PQ28360.121846.6630.3530.955
PQ29360.071852.5660.3470.955
PQ30360.241857.3620.2340.956
PQ31359.841830.7070.4790.955
PQ32359.441849.9990.2890.956
PQ33360.11857.7490.1820.956

The Item-Total Statistics table presents the Cronbach’s Alpha if Item Deleted in the column. This column presents the value of Cronbach’s alpha if the question was deleted. Removal of questions 1, 6, 16, 22, 23, and 33 will lead to a small improvement in Cronbach’s alpha, were their Corrected Item-Total Correlation value is also low.

Validity

The validity test is done using Pearson by correlating each question of the questionnaire score with the total score. Two hypotheses are tested; whether the significance value <0.05 or less than >0.05.

Based on the significant values obtained from SPSS, all the questions result in less than 0.05, most of them with 0.00, which means that all data are valid.

Factor analysis

The factor analysis in SPSS reduces the redundancy and or the duplication of questions.

Table 3.0: Factor analysis.

Case Processing Summary
N%
CasesValid11393.4
Excluded86.6
Total121100.0

As shown from the table, a total of eight questions was removed from 121 questions. Question 1, 2, 5, 9, 12, 23, 27, and 31.

The perception and expectation

The tables and figures in the analysis are related to the average score of participants’ perception (P), expectation (E), and the gap between the perception and expectation (P-E) per question in each dimension.

Functionality and Design

Table 1.0: Functionality and Design score.

F & DAverage PAverage EGap ( P – E)
Q14.905.69-0.79
Q25.475.86-0.39
Q35.395.80-0.41
Q45.485.95-0.47
Q55.325.67-0.35
Total26.5629.0-2.41

The table represents the Functionality and Design dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q1 about the appearance of the Facebook page of any university and the visually appealing, comparing to the lowest gap in Q5 about University user’s interaction with Facebook page. Q4 has the highest expectations among all the dimensions which are about the links posted on the Facebook page should work and lead to the correct path.

Functionality and Design score.
Table 1.0: Functionality and Design score.

The figure above is assessing the highest gap in Q1 and the lowest in Q5, which tells us to improve in the lowest gap and maintain the highest gap.

Reliability and Trustworthiness

The table represents the Reliability and Trustworthiness dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q10 about the pictures and videos on the Facebook page that should reflect the reality of the university, comparing to the lowest gap in Q8 about Facebook pages that deliver the information promised to users.

Reliability and Trustworthiness score.
Table 2.0: Reliability and Trustworthiness score.

The figure above is assessing the highest gap in Q10 and the lowest in Q8, which tells us to improve in the lowest gap and maintain the highest gap.

Responsiveness

Table 3.0: Responsiveness score.

RAverage PAverage EGap ( P – E)
Q125.315.91-0.60
Q135.395.76-0.37
Q144.945.70-0.76
Q155.295.71-0.42
Q164.935.59-0.66
Total25.8628.7-2.81

The table represents the Responsiveness dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q14 about the reviews (positive/negative) posted on the Facebook page by the administrator, comparing to the lowest gap in Q13 about events and news reporting on the Facebook page close to the actual event.

Responsiveness score.
Table 3.0: Responsiveness score.

The figure above is assessing the highest gap in Q14 and the lowest in Q13, which tells us to improve in the lowest gap and maintain the highest gap.

Assurance

Table 4.0: Assurance score.

AAverage PAverage EGap ( P – E)
Q175.385.87-0.49
Q185.075.97-0.90
Q195.175.71-0.54
Q205.295.79-0.50
Total20.923.3-2.43

The table represents the Assurance dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q18 about the Facebook page administrator having the ability to answer all questions and possess accurate information, comparing to the lowest gap in Q20 about the content on a university Facebook page makes the student feel more confident about attending the institution in the future.

Assurance score.
Table 4.0: Assurance score.

The figure above is assessing the highest gap in Q14 and the lowest in Q13, which tells us to improve in the lowest gap and maintain the highest gap.

Empathy

Table 5.0: Empathy score.

EAverage PAverage EGap ( P – E)
Q215.005.68-0.68
Q224.885.69-0.81
Q234.775.81-1.04
Total14.6517.18-2.53

The table represents the Empathy dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q23 about Facebook pages to allow students to connect with Alumni of the university, comparing to the lowest gap in Q21 about University Facebook pages to make students familiar with the institution before you ever physically enter the campus.

Empathy score.
Table 5.0: Empathy score.

The figure above is assessing the highest gap in Q23 and the lowest in Q21, which tells us to improve in the lowest gap and maintain the highest gap.

Content

Table 6.0: Content score.

CAverage PAverage EGap ( P – E)
Q245.576.05-0.48
Q255.445.78-0.34
Q265.435.88-0.45
Q275.385.77-0.39
Q285.195.77-0.58
Q295.285.67-0.39
Q305.115.74-0.63
Total37.440.7-3.26

The table represents the Content dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q30 about Facebook page and posts of a university to be distinctive and unique when compared to other university pages on Facebook, comparing to the lowest gap in Q27 & Q29 about posts on Facebook pages to include regular news updates, events coverage, and other relevant information about the university and a balance between posting promotional content and information-based content.

Content score.
Table 6.0: Content score.

The figure above is assessing the highest gap in Q30 and the lowest in Q27 & Q29, which tells us to improve in the lowest gap and maintain the highest gap.

Security / Privacy

Table 7.0: Security/Privacy score.

S/PAverage PAverage EGap ( P – E)
Q315.525.98-0.46
Q325.876.02-0.15
Q335.265.93-0.67
Total16.717.9-1.28

The table represents the Security/Privacy dimensions. All the gaps in the table are in negatives, that represent the expectations of students exceeded perceptions.

The highest gap was in Q33 about how easy to contact the Facebook administrator privately, comparing to the lowest gap in Q32 about not posting any material on the Facebook page that violates student’s privacy for example pictures, names, exam results, etc.

Security/Privacy score.
Figure 7.0: Security/Privacy score.

The figure above is assessing the highest gap in Q33 and the lowest in Q32, which tells us to improve in the lowest gap and maintain the highest gap.

WEBQUAL importance of weight

WEBQUAL dimensions.
Figure 1: WEBQUAL dimensions.

The chart illustrates the importance of each dimension. There are only slight differences between all the dimensions, which means that all of them have the same importance. The highest dimension is Content with 17%, and the lowest in the Empathy. Functionality & Design, and Security/Privacy are the second-highest dimensions with 16%, following are Reliability & Trustworthiness, and Responsiveness with 14%. The assurance dimension comes in the second-lowest dimension with 12%.

WEBQUAL weight scores

SERVQUAL DimensionA Average: weighted WEBQUAL score (P-E)B % Average important of each dimension(AxB)
Weighted score
Average Functionality & Design
  • 2.41
16%(0.39)
Average Reliability & Trustworthiness
  • 2.78
14%(0.39)
Average Responsiveness
  • 2.81
14%(0.39)
Average Assurance
  • 2.43
12%(0.29)
Average Empathy
  • 2.53
11%(0.28)
Average Content
  • 3.26
17%(0.55)
Average Security/Privacy
  • 1.28
16%(0.20)
Total(17.5)100%(2.49)
AVERAGE (= Total / 7)(0.36)

Figure 2.

Gender vs. weighted dimensions

Figure 3.

DimensionsFM
Functionality & Design14.217.8
Reliability & trustworthiness15.1114.8
Responsiveness14.114.6
Assurance13.912.2
Empathy10.611.5
Content18.417.7
Security/Privacy16.016.3
Gender vs. weighted dimensions
Figure 4.

Both tables and figures show that males are the highest in a weighted average of four dimensions out of seven.

Discussions

In this section of the report, a discussion of the results will be highlighted, which have been obtained from the analysis of data collection to improve the quality of the services within the social media, especially Facebook.

The seven dimensions have been measured of the quality of the service by using the WEBQUAL tool, these seven dimensions are forming the core of the service’s performance. Functionality & Design; is the quality of being functional and the pattern, appearance of the attraction. Reliability & Trustworthiness; is the trust and credibility of both the university and student. Responsiveness; is the required level of the speed of responding to the students. Assurance; is the confidence provided by a university employee to students, their behaviors, and knowledge. Empathy; is understanding student’s needs and expectations and solving their problems. Content; is how well the information is presented, clearly, and accurate. Security/Privacy; is the degree of protecting student’s personal information on the analysis that of the male and female gender. Male has the highest weighted average over the female in four dimensions.

As illustrated in the WEBQUAL weight scores table in the analysis part, the average weighted gap for the 7 dimensions is (-0.36) which means that there is a significant gap between the overall students’ expectations and perception in the social media, especially Facebook. This indicates that the Facebook page of UOWD University still needs to be improved to ensure all required dimension is fit to the students.

Moreover, the highest gap among the seven dimensions was on Content (-0.55) and the lowest (-0.20) was on the Security/Privacy dimension. This indicates that the Content dimension needs to be improved by UOWD University to meet student’s expectations and perceptions. As it shows unsatisfactory quality since expectations exceeded perception.

By analyzing each perception and expectations separately for each dimension, we have noticed the gap in each which gives us a hint on what to improve and by how much.

References

Boyko, L 2016, ‘Postsecondary play: The role of games and social media in higher education’, Canadian Journal of Higher Education, vol. 46, no. 1, pp. 203-205.

Kivunja, C 2015, ‘Innovative Methodologies for 21st Century Learning, Teaching and Assessment: A Convenience Sampling Investigation into the Use of Social Media Technologies in Higher Education’, International Journal Of Higher Education, vol. 4, no. 2, pp. 1-26.

Kurkela, L 2011, ‘Systemic Approach to Learning Paradigms and the Use of Social Media in Higher Education’, International Journal of Emerging Technologies In Learning, vol. 6, no. 3, pp. 14-20.

Loiacono, E, Watson, R, & Goodhue, D 2007, ‘WebQual: An Instrument for Consumer Evaluation of Web Sites’, International Journal Of Electronic Commerce, vol. 11, no. 3, pp. 51-87.

Oswaldo, C 2015, ‘Social Media as Learning Tool in Higher Education: The case of Mexico and South Korea’,SinĂ©ctica, vol. 44, p. 1.

Pomerantz, J, Hank, C, & Sugimoto, C 2015, ‘The state of social media policies in higher education’, Plos One, vol. 10, no. 5, p. e0127485.

Sancho, T, & de Vries, F 2013, ‘Virtual learning environments, social media and MOOCs: key elements in the conceptualisation of new scenarios in higher education: EADTU conference 2013’, Open Learning, vol. 28, no. 3, pp. 166-170.

Scott, O, & Stanway, A 2015, ‘Tweeting the Lecture: How Social Media Can Increase Student Engagement in Higher Education’, Sport Management Education Journal (Human Kinetics), vol. 9, no. 2, pp. 91-101.

Sharda, G, Anita, D, & Pragya, G 2013, ‘Social Media in Quality Enhancement in Higher Education’, International Journal On Research And Development : A Management Review, vol. 1, p. 93.

Silius, K, Kailanto, A, & Kailanto, M 2013, ‘Visualizations of User Data in a Social Media Enhanced Web-based Environment in Higher Education’, International Journal of Emerging Technologies in Learning, vol. 8, pp. 13-19.

Silius, K, Kailanto, M, & Tervakari, A 2011, ‘Evaluating the Quality of Social Media in an Educational Context’, International Journal of Emerging Technologies in Learning, vol. 6, no. 3, pp. 21-27.

Wilson, CD 2013, ‘Making Connections: Higher Education Meets Social Media’, Change, vol. 45, no. 4, pp. 51-57.

Yeona, J 2014, ‘Convenience matters: A qualitative study on the impact of use of social media and collaboration technologies on learning experience and performance in higher education’, Education for Information, vol. 31, no. 1/2, pp. 73-98.

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