The first part of the survey intended on understanding the demographics and background details of the respondents. Therefore, they were asked to supply their age, gender, nationality, and attended course, among other demographic data. The demographics of the 185 respondents in this study indicate: a large majority were female (71.4%) students from Portugal (94.6%) within the age group of 18 to 25 years (78.8%). Besides Portuguese there were students of other nationalities, namely Brazil, Cabo Verde, Ecuador, Mozambique, Switzerland, and Ukraine. Some of these students can be long-term residents, ERASMUS students, or students who chose Portugal to pursue their studies.
The Polytechnic of Porto offers a variety of courses, thus, it was important to gather which courses the respondents were attending. 18.9% of the respondents expressed ‘Other’ as their course. The disciplines of Engineering (17.8%), Accounting (10.8%) and Information Systems & Technology (IS&T) (10.3%) were best represented, with 100% of respondents being full time students in Year 1 (29.7%), Year 2 (16.2%), Year 3 (30.3%) and Postgraduation (23.8%) (Table 1).
Table 1 Courses attended by the respondents and level of study
Course/Level of study
|
Postgraduate
|
Year 1
|
Year 2
|
Year 3
|
Total
|
Other
|
4,9%
|
7,0%
|
2,7%
|
4,3%
|
18,9%
|
Engineering
|
8,6%
|
2,2%
|
2,2%
|
4,9%
|
17,8%
|
Accounting
|
0,5%
|
6,5%
|
2,2%
|
1,6%
|
10,8%
|
Information Systems and Technology
|
1,1%
|
0,5%
|
0,0%
|
8,6%
|
10,3%
|
Marketing Management
|
0,5%
|
2,2%
|
3,2%
|
3,2%
|
9,2%
|
Health
|
0,5%
|
1,1%
|
1,1%
|
4,3%
|
7,0%
|
Arts and Music
|
1,1%
|
3,2%
|
0,5%
|
0,5%
|
5,4%
|
Education
|
2,2%
|
1,6%
|
1,6%
|
0,0%
|
5,4%
|
Design
|
1,1%
|
1,6%
|
0,5%
|
1,6%
|
4,9%
|
Management/Business Management
|
0,5%
|
1,1%
|
0,5%
|
0,5%
|
2,7%
|
Tourism
|
1,1%
|
1,1%
|
0,0%
|
0,0%
|
2,2%
|
Economics
|
0,0%
|
0,5%
|
0,5%
|
0,5%
|
1,6%
|
Entrepreneurship
|
1,1%
|
0,0%
|
0,0%
|
0,0%
|
1,1%
|
Finance
|
0,5%
|
0,0%
|
0,5%
|
0,0%
|
1,1%
|
Human Resource Management
|
0,0%
|
0,5%
|
0,5%
|
0,0%
|
1,1%
|
Public Governance
|
0,0%
|
0,5%
|
0,0%
|
0,0%
|
0,5%
|
Total
|
23,8%
|
29,7%
|
16,2%
|
30,3%
|
100,0%
|
The survey also showed that most respondents (60%) were not receiving any funding for their studies. When inquired on where the respondents currently live and study, 94.1% affirm that (at the time of the survey) they are based in their home country (p<.0005) (Table 2). When asked whether they were based in their home country during the lockdown period, there was a 0,9% reduction. Meaning that some respondents have returned to their home country during the lockdown period. During lockdown, a significant 95,1% were based at their home country. 2,16% of the respondents that are currently living in the country in which they are studying, opted to return in their home country during the COVID-19 lockdown.
Table 2 Area of living home country living during COVID-19 lockdown
Currently living…
|
Remote small city/village
|
Rural area
|
Urban area (Big city or suburbs)
|
Total
|
During COVID-19 lockdown
|
… in my home country
|
30,27%
|
13,51%
|
50,27%
|
94,05%
|
During COVID-19 lockdown
|
Not based at home country
|
0,00%
|
0,00%
|
1,08%
|
1,08%
|
Based at the home country
|
30,27%
|
13,51%
|
49,19%
|
92,97%
|
… in the country in which I am studying
|
1,08%
|
0,54%
|
4,32%
|
5,95%
|
During COVID-19 lockdown
|
Not based at home country
|
0,54%
|
0,54%
|
2,70%
|
3,78%
|
Based at the home country
|
0,54%
|
0,00%
|
1,62%
|
2,16%
|
Total
|
31,35%
|
14,05%
|
54,59%
|
100,00%
|
It was also important to understand in which areas the respondents lived, during COVID-19 lockdown, since the Internet capacity in different areas of the country may differ. 54,6% lived in urban areas (p=.1054), 31,4% lived in small cities/villages, and 14,1% lived in rural areas (Table 2).
Considering that online learning is done via the Internet, the data access of the respondents currently and during the COVID-19 lockdown needed to be attained. It is important to understand how the respondents had access to the Internet and the quality of it. During lockdown, a significant percentage (Figure 1) of the sample had access to Wi-Fi (98.4%, p<.0005). It is also evident that a significant percentage had no access to, at least, free Wi-Fi at the institution (96.3%, p<.0005). Currently (at the time of data collection), a significant percentage of the sample had access to Wi-Fi (97.8%, p<.0005). It is also evident that a significant percentage had no access to, at least, free Wi-Fi at the institution (77.3%, p<.0005).
Regarding the maximum Internet data access, no significant changes were perceived in both periods (Figure 2). Most respondents (40,5%) had uncapped data access before and during lockdown. During lockdown, the majority (53.5%) had access to >10Gb of data per month, p=.1705 and the significant majority (66.4%) has access to >5Gb of data per month, p<.0005. While currently (at the time of data collection), the majority (54.0%) had access to >10Gb of data per month, p<.1383 and the significant majority (65.4%) has access to >5Gb of data per month, p<.0005.
The quality of the Internet connection was another aspect asked in the survey. The intention of this question was to determine whether there were substantial changes in both periods. The Internet quality can compromise online learning, especially if classes are done synchronously. Therefore, Figure 3 and Figure 4 present the respondents' perception, currently and during the COVID-19 lockdown.
Either during the lockdown or currently, the overall quality of the Internet regarding quality, reliability, signal, and speed was found to be ‘non-existent’ by only a significant 0.5% of the sample (p<.0005), with more than 24% of the sample indicating either ‘always good’ or ‘good at times’ (p<.0005) in each case.
Another important dimension of the survey is Technology Usage for Online Learning since the students’ experience with online learning could vary depending on their access to technology. Table 3 presents the devices used by the students to continue their learning. A significant number of students own laptops (87.0%) and smartphones (63.2%), and in both instances these devices were the most significantly adopted by students to access their emails and learning content on the institution’s Learning Management System (LMS), p<.0005 in each case. A significant proportion of the sample (p<.0005) owned multiple devices such as laptops (82.7%) and/or smartphones (96.2%) to facilitate access to online learning.
Table 3 Devices used during the COVID-19 lockdown
Device(s) used during the COVID-19 lockdown to continue online learning
|
Total
|
Laptop
|
87,0%
|
Smart phone
|
74,1%
|
Desktop
|
24,9%
|
Tablet
|
17,3%
|
Smart TV
|
7,0%
|
Borrowed laptop
|
0,5%
|
Cellphone
|
0,5%
|
Total
|
100%
|
Email is an important tool that students use to keep in touch with the University staff and lecturers, and vice versa. During the COVID-19 lockdown, it would be expected that students increased their use of their institutional email. Figure 5 presents the respondents frequency in accessing their university emails.
Likewise, LMS is a valid source of information for students. Hence it was important to gathering the number of times that the respondents accessed the institution LMS during the COVID-19 lockdown. Figure 6 shows that 36.2% of the respondents checked the LMS at least once a day. Students were interacting with both emails and the LMS during the lockdown as a significant number (p<.0005 in each case) were accessing emails 1 (27.0%) or more times a day (30.3%) or when they received a notification for it (83.2%) and 1 or more times a day to LMS when the institution adopted it (63.2%). 11.9% did not adopt any LMS during the lockdown.
When transitioning to online learning, some students may not be at ease with new and/or different technologies and tools. When inquired on their ease in using online learning tools, there is significant agreement (75.7%) that it was easy (classifications of either 4 or 5 in the Likert scale) to navigate/use new online learning tools during COVID, p<.0005, without having used them previously.
When asked about the respondents’ literacy with digital areas, namely their network, digital and LMS literacy levels, the respondents were asked to choose from a 5-point Likert scale, where 1 stands for “not at all literate” and 5, for “extremely literate” (Figure 7).
The data shows that the respondents consider themselves extremely literate in all three aspects in this question. The average literacy scores (Figure 7) for general LMS (77.9%), digital (84.3%), and network literacy (87.1%) skills are all significantly greater than 3 (p<.0005 for each case), indicating that the sample is confident about being literate in all three areas. Using the same scale as the previous question, the respondents had to express their level of literacy on online platforms. From the online platforms listed in the survey, the respondents expressed less literacy with “Google Meet”. While “Zoom” was the platform in which the students felt more at ease with (Figure 8).
Regarding the Social capital, the students were asked to state the general support they had access to during the lockdown period. When inquired on whether the students had someone at home to assist in case of any technological issue, 47,6% of the respondents expressed having no one at home that could assist or support them when they experienced a technological problem (Figure 9).
While there were a number of ways students could get assistance with online learning during lockdown, the lecturer (93.0%), peers (89.2%), friends (85.4%) and family members (76.8%) were support providers for a significant proportion of the sample, p<.0005 (Table 4). However, it cannot go unnoticed that there were respondents (3.8%) whose support during the lockdown period was non-existent.
Table 4 Support providers in online learning, during the COVID-19 lockdown
Provided by
|
Support in online learning, during the COVID-19 lockdown
|
Excellent
|
Good
|
Average
|
Poor
|
Non-existent
|
Family Members
|
25.4%
|
26.5%
|
16.8%
|
8.1%
|
23.2%
|
76.8%
|
Friends
|
25.4%
|
39.5%
|
17.8%
|
2.7%
|
14.6%
|
85.4%
|
Lecturer
|
10.3%
|
36.2%
|
28.6%
|
17.8%
|
7.0%
|
93.0%
|
Peers
|
14.6%
|
41.6%
|
23.2%
|
9.7%
|
10.8%
|
89.2%
|
All providers
|
7.6%
|
8.1%
|
2.7%
|
0.5%
|
3.8%
|
Other aspects such as the cost of Internet of the respondents and whether they had a personal space to attend the online classes also needed to explore. The respondents indicated that the cost of Internet access during the lockdown was low-to-moderately expensive (73.0%, p<.0005). Another important aspect when studying online at home is the necessity of a personal space. 70% of the respondents affirmed having such personal space to attend online classes during the COVID-19 lockdown. 16,7% some of the time had a personal space, while 13,3% never had a designated space at home (Figure 10).
The Transition to online learning dimension aimed at understanding the students’ experience of the transition from face-to-face learning to online learning. To test for significant agreement or disagreement, the Wilcoxon Signed ranks test was used to test the agreement score against the central value (on the scale) of 2.5 (Table 5).
Table 5 Transition to online learning
Q
|
Online learning
|
Highest %
|
Mean
|
p-value
|
1
|
provides a more encouraging learning environment
|
39.5% : Disagree
|
2.23
|
.000
|
2
|
facilitates deeper learning
|
45.4% : Disagree
|
2.10
|
.000
|
3
|
facilitates easier completion of learning tasks
|
35.1% : Disagree
|
2.41
|
.018
|
4
|
provides more opportunities to participate in learning activities
|
35.1% : Disagree
|
2.41
|
.018
|
5
|
enhances collaboration with my peers
|
39.5% : Agree
|
2.37
|
.094
|
6
|
enhances communication with my lecturer
|
38.4% : Disagree
|
2.23
|
.000
|
7
|
encourages me to become an independent learner
|
39.5% : Agree
|
3.02
|
.000
|
8
|
forces me to be self-motivated
|
43.2% : Agree
|
2.94
|
.000
|
9
|
forces me to have a structures study routine
|
40.0% : Agree
|
2.83
|
.000
|
10
|
is easy to adapt to
|
38.9% : Agree
|
2.57
|
.280
|
Analysis shows that there is significant agreement to questions 7, 8 and 9, and significant disagreement to questions 1, 2 and 6. The overall perception is that online learning is easy to adapt to, forces students to have structured study routines and to be self-motivated, and it also encourages them in becoming independent learners. However, most respondents disagree on other aspects, mainly that online learning does not enhance the communication with their lecturers, nor facilitates deeper learning.
The final part of the study investigated the skills which a student needs develop to succeed as an online learner. The questions focused on the extent to which the respondents agreed with the statements presented (Table 6) in relation to the skills they have developed/are developing during online learning.
Table 6 Development of skills in the online environment
Q
|
The transition to online learning has helped me to…
|
Highest %
|
Mean
|
p-value
|
1
|
better communication skills
|
39.5% : Agree
|
2.32
|
.016
|
2
|
collaboration opportunities
|
42.2% : Agree
|
2.51
|
.722
|
3
|
more empathy for others
|
44.3% : Agree
|
2.53
|
.464
|
4
|
my own personal wellbeing
|
35.1% : Agree
|
2.41
|
.236
|
5
|
flexibility to changing circumstances
|
55.7% : Agree
|
2.96
|
.000
|
6
|
self-regulation to facilitate personal success
|
53.0% : Agree
|
2.73
|
.000
|
7
|
a growth mindset to facilitate holistic learning
|
53.0% : Agree
|
2.60
|
.038
|
8
|
independent learning management
|
58.4% : Agree
|
2.97
|
.000
|
9
|
critical thinking skills
|
54.1% : Agree
|
2.68
|
.001
|
Most respondents agree that the transition to online has helped them in developing and improving their skills. Independent learning management was the skill that most students felt was developed during online learning (58.4%). Also, flexibility to changing circumstances (55.7%), critical thinking skills (54.1%), and a growth mindset to facilitate holistic learning (53.0%) were other skills that respondents agreed were developed. The skills that the students felt that were not developed with online learning were communication skills (39.5%), collaboration opportunities (42.2.%), improving their own personal wellbeing (35.1%), and creating empathy for others (44.3%).