An Empirical Analysis of Learners’ Perception of Online Learning Platform
Dr. Shilpi Saxena
Assistant Professor,
Department of Commerce,
IIS (deemed to be university), Jaipur
E-mail address- shilpi.saxena@iisuniv.ac.in
Abstract
Problem- COVID pandemic is a situation which affected every individual as well as every sector of the economy and Educational sector is not an exception. Due to pandemic the years old traditional class room teaching learning system has changed to teaching and learning through online platforms like MS Teams, Zoom and so on. As a result of this drastic change in traditional system, perception of learners has undergone huge changes which is required to be explored. Most of the studies conducted in the field of learners’ perception are general study with very few focusing on finding learners’ perception towards one specific online learning platform.
Purpose of the Study- This study aims to find out the perception and preference of learners for an online learning platform MS Teams.
Methodology–For exploring the factors associated with MS Teams as a platform for online learning, Exploratory Factor Analysis was used. Variation in perception of learners was measured by applying one- way ANOVA test. Descriptive statistics is used to study the preference of learners in the present study.
Findings- The findings of study are derived from a sample of 147 online learners from a University in Rajasthan. The findings showcased the fact that there exist differences in perception of learners when they accessed online classes through tablet device and on the basis of frequency of attending the online classes. Findings of work also highlighted the fact that MS Teams can be used along with traditional teaching system as a platform for sharing contents with learners.
Implication– The findings of the study will be useful for educational sector as well as online learning platform developing companies.
Keywords- COVID pandemic ,MS Teams , Online platform, Perception, Preferences, etc.
Introduction
The Educational sector is considered a foundation sector for all the other sectors of an economy. In India the traditional teaching system include class room teaching and one on one interaction between teachers and students. In last few years under digital India movement of Indian government, an innovative element of learning through online mode is being promoted to innovate the education system in the country. One of the government’s flagship program to promote E-Learning is learning through Swayam, an E-Learning portal (Bast, F., 2021). Soon after government’s initiative of promoting the E –Learning concept, the outbreak of COVID pandemic took place across the country. As a result, the educational institutions nationwide were closed down and education cannot be provided to the students in its usual offline class room manner. As an implication, learning through online platforms other than Swayam portal has become the trend during the covid pandemic in the country. Like other sectors, the educational sector too provided its services to learners by making use of different online learning platforms like Zoom, Google meet, MS Teams, Cisco Webex, and many more(Muthuprasad et al., 2021). Over a period two years from March 2019 to March 2022, this new way of providing education got acceptance not only by the students but by teachers too. The reasons behind the acceptance of teaching through online platforms includes ease of use , flexible learning , ease of controlling the platform(Khan et al., 2021) and an easy way of assessment and evaluation(Rani & Beutlin, 2020). Along with merits, this new system has some demerits as well like social isolation, lack of face to face interaction between teacher and students , connectivity issues(Khan et al., 2021) and a few more.
Literature Review
Since 2019 till March 2022, the learners have seen two waves of covid pandemic and during this tenure different educational institutions have used different online platforms to minimize the learning gap(Khan et al., 2021).During this tenure some researchers have conducted studies on assessing perception and satisfaction of learners about online learning systems. Among the few studies on the theme of students’ perception, one of the study is conducted by T. Muthuprasad et. al (2021)on agricultural students to know about their perception and preferences about online learning. Their findings showed positive perception of agricultural students for online learning but for practical papers a need for hybrid mode is identified in this study. In another study by Rani. V & Bethi. M (2021) it was found that medical and dental students have differences in their perception for E- learning during pandemic. The findings of study showed that students prefer offline teaching over E- Learning as there is lack of interaction in online classes. Khan M.A. et.al.(2021)had undertaken a study on benefits of E-Learning and students’ perception of E-Learning. The findings of the study highlighted the fact that students have positive perception towards E-Learning system as it provides the learners a freedom of connectivity with all concerned parties and ease of accessing the study material as well. Zakaryia Almahasees, Khaled Mohsen and Mohammad Omar Amin (2021)conducted a study on teachers and students to know about their perception about learning during pandemic. They have also explored advantages, challenges, effectiveness of online learning system. Findings of the study highlighted that online learning is less effective than face to face learning. Various challenges identified include a lack of interaction and motivation, technical and internet issues, data privacy, and security. Advantages found were benefits mainly of self-learning, low costs, convenience, and flexibility. Bast F (2021) explored in a study that receptiveness for learning is more among the techno-savvy, school and college going urban students who accessed online classes through desktops during COVID. Students in the same study reported flexitime and break from loneliness during covid as two advantages of online learning system. Kulal A., Nayak A. (2020) performed a study to know about perception of teachers and students in a district of Karnataka state. The findings of the study showed that students have position perception towards online classes but don’t think that online classes can replace the traditional class room teaching system. In the study it was highlighted that teachers are not able to conduct online classes properly due to lack of training support and technical issues faced by them. P. Kalyanasundaram and C. Madhavi.(2019) conducted a study to explore graduate students’ perception for the value added certificate courses offered to them through online mode. Their findings show that the students have a positive perception towards online learning. Thus it could be concluded that in most of the past studies focus area is to study the perception of learners and users towards E-Learning system in general. Most of these studies focused on studying the overall perception of learners about online way of learning and none or very few studies have focused on finding perception of learners towards one specific online learning platform. So the research question addressed in this study is whether there is any difference in perception of learners for different online learning platforms as well as for one specific platform i.e MS Teams, as every online learning platform is different from another in some of its features. Another research question addressed in the study is exploring the perception of learners regarding imbedding the online learning platform or some of its features in the traditional teaching system to make learning more interesting for learners.
Rationale of the Study
Many studies were undertaken over the last two years to investigate the perception of learners about online learning or learning through online classes, but very few out of those focused on exploring the perception of learners about online classes taken through one specific online platform like MS Teams. Apart from this, the present study also focused on a comparison of MS Teams as a learning platform with other similar type of platforms used during the pandemic by different educational institutions and its future usability along with traditional offline teaching system.
Objectives of the Study
Hypotheses of the Study
H01: There is no significant difference in the perception of students towards the factors associated with MS Team as a platform for online learning based on demographic variables of learners.
H02: There is no significant difference in the perception of students towards the factors associated with MS Team as a platform for online learning based on features of online classes.
Research Methodology
The study is an exploratory study with reference to exploring the perception of learners towards MS Teams as a platform for online learning. It is also descriptive in nature with reference to the study of preference of learners.
The Sample
The data for present work was collected from 147 respondents pursuing education at the University level. Initially, the questionnaire was distributed to 200 learners but after data cleaning 147 responses were found to be useful for the study. The sample is composed of specifically those learners who have attended the online classes in last semester of their degree course. Also, purposely, only those respondents are included in the study who have taken online classes through MS Teams, Google meet, Zoom and Cisco Webex platform in the past one and half year. Detailed profile of respondents is given in table 1 in appendix.
Tools for Data Collection
The data for the study was collected by means of a questionnaire consisting of three sections. The first section is related to personal information of learners, the second segment carries questions related to features of online classes and the third section is having questions related to features of MS Teams as a platform for online learning and two questions related to preference for MS Teams and its features. The questions relating to MS Teams as a platform for online learning was designed on 5 point Likert Scale where 5 represented Strongly Agree and 1 represented Strongly Disagree.
Tools for Data Analysis
Exploratory Factor Analysis was used to find out the factors associated with the features of MS Teams as a platform for online learning. For examining the differences in perception of learners one -way ANOVA was applied. The preference of learners was identified based on descriptive statistics. All the statistical tools were applied on primary data collected by using SPSS.For the first hypothesis, factors associated with features of MS Teams are taken as dependent variables and demographic variables (years of study and faculty of study) of students as independent variables. In case of second hypothesis, dependent variable is same as taken for the first hypothesis and features of online classes (duration of online classes , frequency of attending the classes, device use to access the online classes and mode of accessing the internet connection) are taken as independent variables.
Findings of the Study
Exploratory Factor Analysis
For the first objective of the study, Exploratory Factor Analysis was applied on the question related to features of MS Teams as a platform for online learning and as a result two factors have been extracted namely “Features” and “Assessment”. Both these factors with the different variables and their loading values have been shown below in Table 2. Simultaneously factor scores have also been calculated for these two factors. Detailed result of Exploratory Factor Analysis has been shown in Table 4 to Table 7 in appendix.
Table 2 - Factor 1- Features
Variables |
Factor Loading Value |
I am comfortable using Microsoft Teams to learn theory paper |
.597 |
I am comfortable using Microsoft Teams to learn lab paper |
.703 |
Microsoft Teams works well even if the internet speed is low |
.742 |
Chat with the faculty is easy |
.803 |
Voice calling faculty or individual registered members is simple and easy |
.805 |
Using Chat (conversation) option for discussion during class is easy |
.707 |
Giving attendance during the class is simple and easy |
.555 |
Class notebook is found useful |
.614 |
Additional app which are embedded in Microsoft Teams will be useful |
.614 |
Source – Primary Data
Table 3- Factor 2- Assessment
Variables |
Factor Loading Value |
Submitting multiple choice in quiz is simple and easy |
.639 |
Submitting assignment is simple and easy |
.869 |
Uploading assignment is simple and easy |
.860 |
Viewing grades in quiz and assessment is simple and easy |
.745 |
Using forms giving a quick response during class easy |
.786 |
Uploading * doc, pdf, jpeg as attachment or in the file is easy |
.675 |
Source – Primary Data
Result of ANOVA Test for Factor 1 i.e. “Features”
For testing the hypothesis based on differences in perception,one way ANOVA test was applied. Initially One way ANOVA was first applied to test the differences in perception of respondents for first factor identified,i.e.,features based on demographic variables (hypothesis 1) as well as based on features of online classes (hypothesis 2). In case of hypothesis 2, for the first factor, i.e., features, the null hypothesis is rejected in two cases at 0.1 level of significance.The two cases are “frequency of attending online classes” and “frequency of attending online classes through the device tablet”. The result can be interpreted as there exists a significant difference in the perception of learners for MS Teams as a learning platform when learners belong to different categories based on frequency of attending online classes and when learners belong to different categories while accessing the online classes through a Tablet device.In rest of the cases based on features of online classes as well as in case of hypothesis based on demographic variable, null hypothesis for the first factor i.e. featuresis accepted.
Table 8- Result of ANOVA for Factor 1- Features
ANOVA |
||||||
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Average duration of theory classes |
Between Groups |
6.521 |
26 |
.251 |
1.092 |
.361 |
Within Groups |
27.560 |
120 |
.230 |
|
|
|
Total |
34.082 |
146 |
|
|
|
|
Average duration practical classes |
Between Groups |
13.650 |
26 |
.525 |
1.051 |
.409 |
Within Groups |
59.915 |
120 |
.499 |
|
|
|
Total |
73.565 |
146 |
|
|
|
|
Frequency of attending the online classes |
Between Groups |
32.047 |
26 |
1.233 |
1.659 |
.036 |
Within Groups |
89.178 |
120 |
.743 |
|
|
|
Total |
121.224 |
146 |
|
|
|
|
Attending online classes through laptop device |
Between Groups |
8.988 |
26 |
.346 |
.673 |
.879 |
Within Groups |
61.665 |
120 |
.514 |
|
|
|
Total |
70.653 |
146 |
|
|
|
|
Attending online classes through Desktop |
Between Groups |
20.082 |
26 |
.772 |
.928 |
.570 |
Within Groups |
99.918 |
120 |
.833 |
|
|
|
Total |
120.000 |
146 |
|
|
|
|
Attending online classes through Smatphone |
Between Groups |
30.657 |
26 |
1.179 |
.871 |
.647 |
Within Groups |
162.459 |
120 |
1.354 |
|
|
|
Total |
193.116 |
146 |
|
|
|
|
Attending online classes through Tablet device |
Between Groups |
42.447 |
26 |
1.633 |
1.469 |
.086 |
Within Groups |
133.404 |
120 |
1.112 |
|
|
|
Total |
175.850 |
146 |
|
|
|
|
Accessing internet using LAN connection |
Between Groups |
10.961 |
26 |
.422 |
1.094 |
.359 |
Within Groups |
46.223 |
120 |
.385 |
|
|
|
Total |
57.184 |
146 |
|
|
|
|
Accessing internet using mobile datapack |
Between Groups |
22.335 |
26 |
.859 |
1.312 |
.165 |
Within Groups |
78.563 |
120 |
.655 |
|
|
|
Total |
100.898 |
146 |
|
|
|
|
Accessing internet using Wifi |
Between Groups |
10.292 |
26 |
.396 |
.843 |
.685 |
Within Groups |
56.375 |
120 |
.470 |
|
|
|
Total |
66.667 |
146 |
|
|
|
|
Faculty of study |
Between Groups |
13.188 |
26 |
.507 |
.883 |
.630 |
Within Groups |
68.894 |
120 |
.574 |
|
|
|
Total |
82.082 |
146 |
|
|
|
|
Study year |
Between Groups |
12.113 |
26 |
.466 |
1.426 |
.103 |
Within Groups |
39.193 |
120 |
.327 |
|
|
|
Total |
51.306 |
146 |
|
|
|
Source – Primary Data
Result of ANOVA for Factor 2- Assessment
Secondly, one- way ANOVA is applied to test the differences in perception of respondents for the second factor identified, i.e., assessment. For the second factor the null hypothesis is accepted in all the cases at0.1 level of significance for both the hypotheses. It can be interpreted, as there exists no significant differences in the perception of learners for MS Teams as learning platform based on features of online classes taken through MS Teams as a learning platform, as well as on the basis of demographic features of learners.
Table 9- Result of ANOVA for Factor 2- Assessment
ANOVA |
||||||
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Average duration of theory classes |
Between Groups |
3.357 |
15 |
.224 |
.954 |
.507 |
Within Groups |
30.724 |
131 |
.235 |
|
|
|
Total |
34.082 |
146 |
|
|
|
|
Average duration of practical classes |
Between Groups |
9.230 |
15 |
.615 |
1.253 |
.241 |
Within Groups |
64.335 |
131 |
.491 |
|
|
|
Total |
73.565 |
146 |
|
|
|
|
Frequency of attending the online classes |
Between Groups |
6.779 |
15 |
.452 |
.517 |
.927 |
Within Groups |
114.445 |
131 |
.874 |
|
|
|
Total |
121.224 |
146 |
|
|
|
|
Attending online classes through laptop device |
Between Groups |
4.299 |
15 |
.287 |
.566 |
.896 |
Within Groups |
66.354 |
131 |
.507 |
|
|
|
Total |
70.653 |
146 |
|
|
|
|
Attending online classes through Desktop |
Between Groups |
12.658 |
15 |
.844 |
1.030 |
.429 |
Within Groups |
107.342 |
131 |
.819 |
|
|
|
Total |
120.000 |
146 |
|
|
|
|
Attending online classes through Smatphone |
Between Groups |
28.413 |
15 |
1.894 |
1.507 |
.112 |
Within Groups |
164.703 |
131 |
1.257 |
|
|
|
Total |
193.116 |
146 |
|
|
|
|
Attending online classes through Tablet device |
Between Groups |
14.565 |
15 |
.971 |
.789 |
.688 |
Within Groups |
161.285 |
131 |
1.231 |
|
|
|
Total |
175.850 |
146 |
|
|
|
|
Accessing internet using LAN connection |
Between Groups |
4.243 |
15 |
.283 |
.700 |
.781 |
Within Groups |
52.940 |
131 |
.404 |
|
|
|
Total |
57.184 |
146 |
|
|
|
|
Accessing internet using mobile datapack |
Between Groups |
8.129 |
15 |
.542 |
.765 |
.713 |
Within Groups |
92.769 |
131 |
.708 |
|
|
|
Total |
100.898 |
146 |
|
|
|
|
Accessing internet using Wifi |
Between Groups |
2.755 |
15 |
.184 |
.377 |
.983 |
Within Groups |
63.911 |
131 |
.488 |
|
|
|
Total |
66.667 |
146 |
|
|
|
|
Faculty for study |
Between Groups |
3.531 |
15 |
.235 |
.393 |
.979 |
Within Groups |
78.551 |
131 |
.600 |
|
|
|
Total |
82.082 |
146 |
|
|
|
|
Study year |
Between Groups |
7.854 |
15 |
.524 |
1.579 |
.088 |
Within Groups |
43.452 |
131 |
.332 |
|
|
|
Total |
51.306 |
146 |
|
|
|
Source – Primary Data
Preference of Online Learning Platform
For knowing about the preference of learners, two questions have been included in the questionnaire. One of the question was related to a preference of MS Teams as a platform for online learning over other similar online learning platforms. In response to this question it was found that 51% of learners preferred MS Teams over other similar online learning platforms, followed by 38% respondents reporting MS Teams as a learning platform to be good as compared to other similar platforms. Another question was related to identifying the feature of MS Teams which can be embedded in traditional offline teaching systems to make learning more effective for the students. In response to this question 51 % responded that MS Teams can be used as a platform for sharing the contents on regular basis in traditional teaching system followed by 23.8 % supporting the fact that its feature of being a platform for solving doubts and assessments can be embedded in traditional offline teaching systems. Detailed result is shown in table 8.
Conclusion and Discussion
COVID 19 phase I and II represented such a time which no one had imagined. Due to the pandemic, the educational sector had to switch from the years old class room teaching pattern to an online mode of teaching and learning. Such a switch is one of the major reasons behind conducting this study. There were two focus areas of this study, namely perception and preference of learners. The result of the study showed that there exist no major differences in perception of learners for MS Teams as a platform for learning irrespective of features of online classes as well as demographic features of learners. The findings for preference showed that out of several features of MS Teams as learning platform, the firstfeature which a majority of respondents suggested to be embedded in the traditional class room teaching system is,“it can be used as a platform for sharing contents with learners” followed by “platform for solving doubts and for assessment”.
The findings of the present study with reference to preferences are found to be similar to the findings of the study conducted by Khan M.A. et.al.(2021). In the study conducted by Khan M.A. et.al. one of the reason found for students’ positive perception towards E –Learning was easy access of study material in E-Learning systems. Likewise, in the present study, when respondents were asked which features of MS Teams can be embedded into traditional teaching system, the majority responded that it can be used as a platform for sharing contents with learners.
The next feature of MS Teams which students preferred after the one mentioned above is–“a platform for solving doubts and assessments”. This finding is in contrast of findings of the research work conducted by Rani. V &Bethi. M (2021). Both these authors in their study found lack of interaction in E- Learning system as one of the factors because of which E- Learning systems cannot be properly implemented in the educational sector.
Implications
The study has implications for educational sector as well as for software companies. The findings of the present study will help the educational institutions in taking decisions regarding the adoption of MS Teams along with traditional teaching systems for making learning more interesting for learners. This study will also help educational institutions in designing their curriculum in order to be ready for situations like covid, if any, in the future.By referring to preferred features of MS Teams, institutes can design their curriculum in a such manner that assessment of students can be conducted smoothly through online mode even if they are taught in through offline mode. The findings regarding preference will help software companies to modify online learning platforms so as to increase their acceptability in the educational sector in the future.
Scope for Further Study
In the present work, only female respondents are considered for the sample. Thus, the study can be conducted with male respondents as well. Also a comparative study of a similar nature can be conducted for male and female respondents. The present work can also be conducted on teachers who have used MS Teams as a platform for teaching to know about their perception and preference about the platform. This study is conducted on students pursuing graduation and post graduation programs at the University level. Learning through MOOC’s platform and online learning apps like Biju’s, Vedantu, etc are not part of this study. Similar types of studies can be conducted in the future for Learning through MOOC’s platform and online learning apps like Biju’s, Vedantu, etc.
References
Almahasees, Z., Mohsen, K., & Amin, M. O. (2021). Faculty’s and Students’ Perceptions of Online Learning During COVID-19. Frontiers in Education, 6(May), 1–10. https://doi.org/10.3389/feduc.2021.638470
Bast, F. (2021, August). Perception of Online Learning Among Students From India Set Against the Pandemic. In Frontiers in Education (Vol. 6, p. 705013). Frontiers Media SA.
Khan, M. A., Vivek, Nabi, M. K., Khojah, M., & Tahir, M. (2021). Students’ perception towards e-learning during covid-19 pandemic in India: An empirical study. Sustainability (Switzerland), 13(1), 1–14. https://doi.org/10.3390/su13010057
Kulal, A., & Nayak, A. (2020). A study on perception of teachers and students toward online classes in Dakshina Kannada and Udupi District. Asian Association of Open Universities Journal, 15(3), 285–296. https://doi.org/10.1108/aaouj-07-2020-0047
Muthuprasad, T., Aiswarya, S., Aditya, K. S., & Jha, G. K. (2021). Students’ perception and preference for online education in India during COVID -19 pandemic. Social Sciences & Humanities Open, 3(1), 100101. https://doi.org/10.1016/j.ssaho.2020.100101
Rani, V., & Bethi, M. (2021). Perception of E-learning among undergraduate medical and dental students during COVID-19 pandemic - A cross-sectional study. National Journal of Physiology, Pharmacy and Pharmacology, 11(0), 1. https://doi.org/10.5455/njppp.2021.11.01040202103022021
Appendix
Table1 – Respondents Profile
Online Class related Features |
|||
|
Count |
Column N % |
|
Average duration of online theory classes |
30 min |
7 |
4.8% |
45 min |
109 |
74.1% |
|
more than 45 min |
31 |
21.1% |
|
Total |
147 |
100.0% |
|
Average duration of online practical classes |
30 min |
22 |
15.0% |
45 min |
62 |
42.2% |
|
more than 45 min |
63 |
42.9% |
|
Total |
147 |
100.0% |
|
Frequency of attending online classes |
Daily |
76 |
51.7% |
most of the days in a week |
54 |
36.7% |
|
hardly 1 or 2 days in a week |
3 |
2.0% |
|
as per my willingness |
14 |
9.5% |
|
Total |
147 |
100.0% |
|
Attending online classes through Laptop device |
Always |
5 |
3.4% |
Mostly |
6 |
4.1% |
|
Rarely |
12 |
8.2% |
|
Never |
124 |
84.4% |
|
Total |
147 |
100.0% |
|
Attending online classes through Desktop device |
always |
68 |
46.3% |
Mostly |
36 |
24.5% |
|
Rarely |
39 |
26.5% |
|
Never |
4 |
2.7% |
|
Total |
147 |
100.0% |
|
Attending online classes through Smatphone device |
Always |
51 |
34.7% |
Mostly |
36 |
24.5% |
|
Rarely |
29 |
19.7% |
|
Never |
31 |
21.1% |
|
Total |
147 |
100.0% |
|
Attending online classes through Tablet device |
Always |
34 |
23.1% |
Mostly |
30 |
20.4% |
|
Rarely |
47 |
32.0% |
|
Never |
36 |
24.5% |
|
Total |
147 |
100.0% |
|
Accessing internet using LAN connection |
Always |
3 |
2.0% |
Mostly |
6 |
4.1% |
|
Rarely |
15 |
10.2% |
|
Never |
123 |
83.7% |
|
Total |
147 |
100.0% |
|
Accessing internet using mobile datapack |
Always |
85 |
57.8% |
Mostly |
39 |
26.5% |
|
Rarely |
18 |
12.2% |
|
Never |
5 |
3.4% |
|
Total |
147 |
100.0% |
|
Accessing internet using WIFI |
Always |
5 |
3.4% |
Mostly |
5 |
3.4% |
|
Rarely |
10 |
6.8% |
|
Never |
127 |
86.4% |
|
Total |
147 |
100.0% |
|
Study related Personal features of learners |
|||
Study year |
first year |
9 |
6.1% |
second year |
78 |
53.1% |
|
third year |
60 |
40.8% |
|
Total |
147 |
100.0% |
|
Program level |
post graduation |
29 |
19.7% |
Graduation |
118 |
80.3% |
|
Total |
147 |
100.0% |
|
Faculty for study |
Science |
55 |
37.4% |
commerce and management |
61 |
41.5% |
|
Humanities |
31 |
21.1% |
|
Total |
147 |
100.0% |
Source – Primary Data
Table 4 – KMO and Bartlett's Test
KMO and Bartlett's Test |
||
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.909 |
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
1466.440 |
Df |
105 |
|
Sig. |
.000 |
Source – Primary Data
The KMO value of 0.909 and significance value of 0.00 of Bartlett’s test of Sphericity shows that the sample taken is adequate for application of exploratory factor analysis.
Table 5- Communalities
Communalities |
||
|
Initial |
Extraction |
I am comfortable using Microsoft Teams to learn theory paper |
1.000 |
.501 |
I am comfortable using Microsoft Teams to learn lab paper |
1.000 |
.558 |
Microsoft Teams works well even if the internet speed is low |
1.000 |
.551 |
Chat with the faculty is easy |
1.000 |
.693 |
Voice calling faculty or individual registered members is simple and easy |
1.000 |
.719 |
Using Chat (conversation) option for discussion during class is easy |
1.000 |
.635 |
Submitting multiple choice in quiz is simple and easy |
1.000 |
.478 |
Submitting assignment is simple and easy |
1.000 |
.789 |
Uploading assignment is simple and easy |
1.000 |
.781 |
Viewing grades in quiz and assessment is simple and easy |
1.000 |
.599 |
Class notebook is found useful |
1.000 |
.503 |
Giving attendance during the class is simple and easy |
1.000 |
.620 |
Using forms giving a quick response during class easy |
1.000 |
.743 |
Uploading * doc, pdf, jpeg as attachment or in the file is easy |
1.000 |
.762 |
Additional app which are embedded in Microsoft Teams will be useful |
1.000 |
.517 |
Extraction Method: Principal Component Analysis. |
Source – Primary Data
The survey has been started with 18 variables / statements related to MS Teams as a platform for learning. Based on communalities values after extraction 3 statements have been dropped as their communalities value after extraction is found to be less than 0.5. Finally, EFA have been applied on remaining 15 variables / statements only.
Table 6 - Total Variance Explained
Total Variance Explained |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1 |
7.867 |
52.449 |
52.449 |
7.867 |
52.449 |
52.449 |
4.876 |
32.507 |
32.507 |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2 |
1.579 |
10.525 |
62.974 |
1.579 |
10.525 |
62.974 |
4.570 |
30.467 |
62.974 |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3 |
.833 |
5.552 |
68.526 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
4 |
.787 |
5.248 |
73.774 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
5 |
.701 |
4.674 |
78.448 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
6 |
.539 |
3.594 |
82.042 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
7 |
.492 |
3.282 |
85.324 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
8 |
.440 |
2.932 |
88.256 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
9 |
.343 |
2.284 |
90.540 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
10 |
.337 |
2.244 |
92.785 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
11 |
.306 |
2.041 |
94.825 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
12 |
.256 |
1.710 |
96.535 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
13 |
.224 |
1.493 |
98.028 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
14 |
.175 |
1.164 |
99.192 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
15 |
.121 |
.808 |
100.000 |
|
|
|
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Extraction Method: Principal Component Analysis. Source – Primary Data Table 7- Rotated Component Matrix
|
Source – Primary Data
Table 8- Result of Preference objective
Featureto be embedded |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
platform for sharing course contents |
76 |
51.7 |
51.7 |
51.7 |
additional app |
23 |
15.6 |
15.6 |
67.3 |
|
platform for doubt solving |
13 |
8.8 |
8.8 |
76.2 |
|
assessment |
35 |
23.8 |
23.8 |
100.0 |
|
Total |
147 |
100.0 |
100.0 |
|
Source – Primary Data