during the covid-19 pandemic lockdown, Schemes and Mind Maps of Engineering

Download during the covid-19 pandemic lockdown and more Schemes and Mind Maps Engineering in PDF only on Docsity! STUDENT LIFE DURING THE COVID-19 PANDEMIC LOCKDOWN EUROPE-WIDE INSIGHTS The COVID-19 pandemic which has swept across Europe has made changes to many facets of life from working conditions to freedom of movement. Education has been one of the sectors disrupted by the crisis with educational provision both in Europe and globally having gone on-line. In higher education, on the one hand, this new moment has highlighted certain advantages to on-line studying including lower living costs for students who would otherwise study away from their family home. On the other, it has underlined inequalities between students particularly in relation to differences in terms of digital skills, support networks and home environment resources. This report presents insights on student experiences during lockdown due to the COVID-19 pandemic based on questionnaire responses given by students studying in Europe in April 2020. The research focused on the capacity of students, understood as a diverse group, to have reasonably positive academic outcomes in a disaster context such as the COVID-19 pandemic, as well as the role of their academic environment, social networks, emotional make-up, knowledge and skills and material resources in enabling such experiences. At the very end of the report, we provide insights on students’ responses to open questions which covered the advantages and disadvantages of on-line studying during the pandemic, problems students encountered and suggestions for improvement. STUDENT LIFE DURING THE COVID-19 PANDEMIC LOCKDOWN EUROPE-WIDE INSIGHTS Main findings | 3 For around two thirds of students who accessed the questionnaire (72,61%) on-site classes were cancelled due to the COVID-19 pandemic. LECTURES Students were exposed to a variety of formats replacing on-site lectures: online with the lecturer lecturing in real time (74,61%), lecturers sending their presentations to students (44,51%), online with a video recording of the lecturer lecturing (32,10%) and online with an audio recording of the lecturer lecturing (20,58%). For a small minority of students (3,75%) no online lectures had been organized as part of their course. The dominant method of online lectures was with the lecturer lecturing in real time (59,73%). For the majority of students, the preferred method of online lectures is with the lecturer lecturing in real time (57,43%), which suggests that most students like to have face-to-face lecturer-student interaction. SEMINARS Students were exposed to a variety of formats replacing on-site seminars: online with the lecturer lecturing in real time (45,09%), through written communication with the lecturer (26,76%), online with a video recording of the lecturer lecturing (12,51%) and online with an audio recording of the lecturer lecturing (7,9%). The dominant method of seminar provi- sion was online with the lecturer involved in real time (38,03%). In comparison to lectures, a higher proportion of students (15%) reported that there was no online provision of their seminars. Just as with lectures, students’ preferred method of online seminars is with the lecturer involved in real time. PRACTICAL CLASSES Students were exposed to a variety of formats replacing on-site practical classes: online with the lecturer lecturing in real time (41,77%), through written communication with the lecturer (23,01%), online with a video recording of the lecturer lecturing (12,56%) and online with an audio recording of the lecturer lecturing (6,18%). The dominant format was online with the lecturer involved in real time (37,9%). For 20,23%, of students i.e. a fifth of students there was no online provision of practical classes. Again, just as with lectures and semi- nars, the preferred method is with the lecturer involved in real time. In all teaching forms, the preferred method of content delivery is with the lecturer in- volved in real time. Challenges related to holding practical classes online were particularly highlighted by students. Whereas only 3,75% of students reported that no replacement lectures had been organized as part of their course, a higher proportion of students re- ported the same for seminars (15%) and practical classes (20,23%). SUPERVISIONS For a third of students there were no planned supervisions for this term. When supervisions had been organized they took on different forms: via e-mail (52,9%), via video-call (36,87%), via voice call (13,74%). Students’ preferred format for supervisions is via video-call which fur- ther confirms that students prefer face-to-face interaction with academic staff. ASSESSMENT On average, students agreed that their lecturers had provided course assignments on a regular basis, responded to their questions in a timely manner and were open to MAIN FINDINGS 2 Main findings | 54 | Main findings students’ suggestions and adjustments of online classes. To a lesser extent, however, they agreed that lecturers had provided feedback on their performance on the assignments and informed students what their exams will look like in the new situation. WORKLOAD Most of the students indicated that their study workload was larger than before on-site classes were cancelled (50,74%). Only 19,04% said that their workload was smaller than before whereas 25,46% reported no changes in their perceived study workload. Students indicated that their workload had increased because teachers compensated the lack of on-site classes with additional assignments. SUPPORT NETWORK Students are more likely to talk to a close family member about the COVID-19 crisis, fol- lowed by a close friend. A very small proportion of students would turn to institutional sources of support such as administrative staff (1,5%). During the COVID-19 pandemic, students had daily communication with their close family members and close friends. They also had weekly communication with colleagues from their course and lecturers. Communication with administrative staff was much less frequent. 9,1% of students indicated that they do not have several people they can trust to help solve their problems. Students who were living in their family homes reported higher levels of bonding social capital in comparison to students who were living in rented accommodation or student hall/dorm. Also, students who suffered from health impairments reported lower bonding social capital. An overall conclusion for this section is that for many problems students may have, they do not rely on institutional provision for solutions. EMOTIONAL WELLBEING Students have frequently felt frustrated, anxious and bored in relation to their academic activities since on-site classes were cancelled. The results indicate that students’ well-be- ing during the COVID-19 pandemic might have been negatively affected. Lower levels of general well-being were reported by female students, those who have difficulties paying their study costs, students with mental health problems and students who do not have a quiet place to study. In particular lower levels of general well-being were reported by students who do not have a supportive social network. SKILLS AND INFRASTRUCTURE FOR STUDYING FROM HOME The majority of students (80,7%) feel confident in using online teaching platforms such as MsTeams, Zoom and similar. However, 7,9% indicated their lack of confidence in using online teaching platforms. As one might expect, students in the field of Engineering, manufacturing and construc- tion reported higher levels of digital capital compared to all other groups of students. Students who suffered from any type of health impairment had lower digital capital. The majority of students have their own computer (89,3%), however only 41% reported they always have a good Internet connection. 0,5% do not have their own computer. The majority of students often or always have a quiet place to study, whereas 3,3% of students do not have a quiet place to study. The ma- jority also have a desk (79,2%), however 3,2% of students do not have a desk to work on. Only a third of students reported that they always have access to course study material. LIFE CIRCUMSTANCES More than a quarter of students indicated they were worried about their health most or all of the time. Balancing care responsibilities with studying as well as the costs of living was indicated as a concern most or all of the time by around a fifth of students. Students who lived in rented accommodation and a student hall/dorm reported a higher frequency of worrying about costs of studying and living in comparison to students who lived in their family homes or some other accommodation. Older and part-time students, students who do not pay tuition fees as well as students who reported having health impairments worried to a greater extent about their costs of studying and living. WORKING WHILE STUDYING Out of the students who have been working or were planning to work this term, 28,9% lost the job temporarily, while 12,2% lost their job permanently. For students for whom working is a necessity to cover costs of studying this is a risk factor. Indeed, students who lost their job permanently had lower levels of capability to cover the costs of studying and living compared to all other groups of students. TUITION FEES For students paying tuition fees, the majority (75,3%) answered that their fee payment has remained the same at their institution. For some students, flexible ways of paying fees was introduced (13,8%) and 1,8% reported their institution had cancelled fee payment for this term. SCHOLARSHIPS For students who receive scholarships, the majority (87,4%) answered the amount of their scholarship had remained the same. However, for almost one tenth of students the crisis has had an adverse effect on their scholarship status and their scholarship payment had either been postponed (4,10%), cancelled (2,9%) or reduced (2,6%). SATISFACTION WITH TEACHING AND ADMINISTRATION Students were mostly satisfied with how supportive lecturers have been since on-site classes were cancelled. They were less satisfied when it comes to the organization of their seminars and practical classes. On average, students who were older, who had greater capability to cover costs of stud- ying and living, those who were not paying tuition fees as well as part-time students re- ported greater levels of satisfaction. In addition, higher levels of satisfaction with teaching and administration were reported by students who did not suffer from any chronic illness, mental health problems or other health problems, as well as by students who had better access to home facilities for studying. Finally, students with greater digital and bonding social capitals and those who worried less about costs, health or balancing between care responsibilities and studying were also more satisfied. STUDENT ADJUSTMENT 47,43% of students indicated their performance as a student had changed for the worse since on-site classes were cancelled. In general, after all other predictors are statistically controlled for, younger students, stu- dents who do not have a quiet place to study, a good Internet connection and material for studying at their disposal, as well as students with lower levels of digital and social bonding capital, consistently reported lower adjustment during the COVID-19 pandemic lockdown. In addition, students who reported having mental health problems consist- ently had lower scores on all indicators of adjustment. 6 | Methodological notes | 7 3.1. ABOUT THE STUDY An online questionnaire, launched on SurveyMonkey, was filled in by undergraduate and Master’s, full-time and part-time students studying at European higher education institu- tions in April 2020. The questionnaire was launched by the European Students Union on April 21 and was accessible until May 3 2020. Participation in the study was voluntary and anonymous. The questionnaire was constructed by a team of researchers from the University of Zadar in Croatia. It consisted of 7 parts which included 31 closed-type questions and 5 open questions. Part 1: Students’ socio-demographic and academic characteristics (e.g. gender, age, educational level of parents, student status, field of study) Part 2: Academic life (experiences with teaching, workload and assessment) Part 3: Infrastructure and skills for studying from home (e.g. access to a desk, a computer, a quiet place to study, confidence in using online teaching platforms) Part 4: Networks of support Part 5: Emotional life (general well-being and experienced emotions) Part 6: Life circumstances (e.g. employment, care responsibilities, tuition fees, scholarships) Part 7: General reflections on studying from home In total, 17,116 respondents from 41 European countries accessed the questionnaire. Coun- tries which had a higher number of respondents include Portugal (6,652), Romania (3,110), Croatia (2,029) and the Czech Republic (1,768). Out of the initial sample, 12,336 (or 72,61%) of them reported that their on-site classes were cancelled due to COVID-19 pandemic. However, after filling out the socio-demographic and academic characteristics block of questions, 9,196 students continued with the survey. The total number of students who responded to a particular question varied between different questions, which resulted in variation in the total number of responses, meaning that a certain amount of missing val- ues is present. This fluctuation in the total amount of responses is common in research like this. It is important to note that although some of the analysed factors (e.g. socio-demo- graphic characteristics, academic characteristics, health impairment etc.) were relat- ed to indicators of students’ academic adjustment and well-being during lockdown, many of the identified effects were rather small in size and and therefore conclusions are tentative. 3.2. PROFILE OF THE SAMPLE 3.2.1 Gender Table 1 presents the distribution of the gender of the respondents showing that a higher number of female (66,4%) compared to male (32,1%) and non-binary (0,4%) students filled in the questionnaire. METHODOLOGICAL NOTES 3 12 | Empirical findings and interpretation | 13 4 EMPIRICAL FINDINGS AND INTERPRETATION 4.1. ACADEMIC LIFE This part of the questionnaire assessed how the COVID-19 pandemic lockdown affected students’ experiences with teaching (lectures, seminars, practical classes and supervi- sions/mentorship), workload and assessment, their satisfaction with different aspects of their course, as well as evaluations of their own performance and their beliefs about their academic success. Out of the total number of students who accessed this part of the questionnaire (N=16,989), the majority of them (N=12,336 or 72,61%) reported that their on-site classes (those taking place in the location/campus of their study institution) had been cancelled, while 3,585 (21,10%) reported that their on-site classes had not been cancelled. The rest of the sample either did not respond to this question or responded as “not applicable” (N=1195 or 6,29%). Among those students whose on-site classes were cancelled, at the time of filling in the questionnaire, the majority of them (70,78%) reported that their on-site classes had been cancelled 5 to 7 weeks ago (i.e. in March 2020). 0,83% 0,74% 1,61% 9,68% 21,87% 33,09% 15,82% 7,43% N/A (my on-site classes have not been cancelled) (weeks ago) 1 2 3 4 5 6 8 8,94% 7 4.1.1. Organization of lectures The COVID-19 pandemic has caused lectures to be organized in diverse ways. Most of the students reported that they had experience of lectures held online with the lecturer lec- turing in real time (N=6849 or 74,61%), which was followed in frequency by lecturers send- ing presentations of lectures to students (N=4086 or 44,51%). A third of the students also had the experience of online lectures with a video recording of a lecturer lecturing and a fifth reported having had online lectures with an audio recording of a lecturer lecturing. 941 students (10,25%) reported that some of their on-site lectures had not been replaced by a different format. Next, students reported that online lectures with the lecturer lecturing in real-time was the dominant form of online lectures (N=5476 or 59,73%) which was followed by lecturers Figure 1 Time of cancellation of on-site classes Empirical findings and interpretation | 1514 | Empirical findings and interpretation sending presentations of lectures to students (N=1804 or 19,68%). 344 students (3,75%) noted that none of their lectures had been replaced by any kind of online method. The dominant forms of lectures did not always overlap with the preferred ways of lectures. Most of the students reported that they prefer online lectures with the lecturers lecturing in real time (N=5257 or 57,43%). Only 974 (or 10,64%) students reported that sending pres- entations of lectures is the preferred form of online lectures. In other words, students pre- fer to have face-to-face teacher-student interaction. For more details, please see Table 11. Variety of lectures* Dominant method of online lectures Preferred method of online lectures N % N % N % Online with the lecturer lecturing in real time 6849 74,61 5476 59,73 5257 57,43 Online with a video recording of the lecturer lecturing 2947 32,10 676 7,37 1946 21,26 Online with an audio recording of the lecturer lecturing 1889 20,58 327 3,57 368 4,02 Lectures replaced by lecturers sending their presentations to students 4086 44,51 1804 19,68 974 10,64 No online lectures have been organized 941 10,25 344 3,75 - - Not applicable (e.g. I do not have lectures this term) 569 6,20 456 4,97 480 5,24 Other 393 4,28 85 0,93 128 1,40 Total 9180 - 9168 100 9153 100 4.1.2. Organization of seminars With regard to the organization of seminars, most of the students had the experience of their seminars being held online with the lecturer lecturing in real time (N=4124 or 45,09%) which was followed by written communication with the lecturer (N=2448 or 26,76%). Im- portantly, 1369 students (15%) reported that their seminars had not been replaced with any online format. Again, students reported that online seminars with the lecturer in- volved in real-time was the dominant method (N=3472 or 38,03%) which was followed by written communication with the lecturer (N=1401 or 15,35%). Finally, most of the students reported that their preferred method is online seminars with the lecturer involved in re- al-time (N=4150 or 45,51%). In other words, just as with lectures, they prefer face-to-face teacher-student interaction. For more details, please see Table 12. N – number of students who chose particular answer category; % - percentage of students who chose particular answer category * Students were allowed to choose multiple answer categories Variety of seminars* Dominant method of online seminars Preferred method of online seminars N % N % N % Online with the lecturer involved in real time 4124 45,09 3472 38,03 4150 45.51 Online with a video recording of the lecturer 1144 12,51 364 3,99 1077 11,81 Online with an audio recording of the lecturer 731 7,99 189 2,07 262 2,87 Through written communication with the lecturer 2448 26,76 1401 15,35 1031 11,31 No online seminars have been organized 1758 19,22 1369 15 - - Not applicable (e.g. I do not have seminars this term) 2236 24,45 2259 24,75 2506 27,48 Other 162 1,77 75 0,82 93 1,02 Total 9147 - 9129 100 9119 100 4.1.3. Organization of practical classes Similar to the organization of online lectures and seminars, most students reported that they had the experience of online practical classes with the lecturer involved in real time (N=3825 or 41,77%). This method was followed in frequency of responses by the organ- ization of practical classes through written communication with the lecturer (N=2107 or 23,01%). However, 1851 students (20,23%) reported that they had the experience of practical classes not being replaced by an online version. Again, dominant methods were online practical class- es with the lecturer involved in real time (N=3468 or 37,90%) followed by written communication with the lecturer (N=1129 or 12,34%). For 20,23% of students, no online practical classes had been organized. As with the lectures and seminars, the students’ preferred method is online practical classes with the lecturer involved in real time (N=4255 or 46,63%). For more details, please see Table 13. Table 11 Lectures since on-site classes were cancelled Table 12 Seminars since on-site classes were cancelled N – number of students who chose particular answer category; % - percentage of students who chose particular answer category * Students were allowed to choose multiple answer categories Empirical findings and interpretation | 1716 | Empirical findings and interpretation Actual method of online practical classes* Dominant method of online practical classes Preferred method of online practical classes N % N % N % Online with the lecturer involved in real time 3825 41,77 3468 37,90 4255 46,63 Online with a video recording of the lecturer 1150 12,56 450 4,92 1227 13,45 Online with an audio recording of the lecturer 566 6,18 131 1,43 186 2,04 Through written communication with the lecturer 2107 23,01 1129 12,34 831 9,11 No online practical classes have been organized 2255 24,62 1851 20,23 - - Not applicable (e.g. I do not have seminars this term) 2065 22,55 2018 22,05 2365 25,91 Other 266 2,90 104 1,14 262 2,87 Total 9158 - 9151 100 9126 100 4.1.4. Organization of supervisions/mentorship Most of the students reported that they communicated with their supervisor or mentor via e-mail (N=3375 or 36,87%), while their preferred way of communicating with their su- pervisor or mentor is via video-call (N=3120 or 34,11%). For more details, please see Table 14. Actual organization of supervisions/ mentorship* Preferred organization of supervisions/ mentorship N % N % Via video-call 3375 36,87 3120 34,11 Via voice-call 1258 13,74 792 8,66 Via e-mail communication 4842 52,90 2524 27,60 Not applicable (e.g. I do not have supervisions/mentorship this term) 2826 30,88 2622 28,67 Other 223 2,44 88 0,96 Total 9153 - 9146 100 N – number of students who chose particular answer category; % - percentage of students who chose particular answer category * Students were allowed to choose multiple answer categories Table 13 Practical classes since on-site classes were cancelled N – number of students who chose particular answer category; % - percentage of students who chose particular answer category * Students were allowed to choose multiple answer categories Table 14 Supervisions/ mentorship since on-site classes were cancelled 4.1.5. Assessment and responsiveness To evaluate issues of assessment and lecturer responsiveness during the COVID-19 pan- demic and online classes, students were asked to rate their agreement with several state- ments that describe different assessment modalities by using a Likert-type scale with five points (1=strongly disagree, 2=disagree, 3=neither agree nor disagree, 4=agree, 5=strongly agree). As can be seen in Table 15, students gave relatively high rates to all of the questions regarding assessment: on average they agree that their lecturers have provided course assignments on a regular basis, responded to their questions in a timely manner and were open to students’ suggestions and adjustments of online classes. However, their rat- ings on questions regarding feedback on their performance on a given assignment and information about what exams will look like were lower (M=3.32 and M=3.11, respectively). N Mean Median Mode Range Have provided course assignments (e.g. readings, homework, quizzes) on a regular basis 8672 3.91 4 4 1-5 Have provided feedback on my performance on given assignments 8639 3.32 4 4 1-5 Have responded to my questions in a timely manner 8618 3.77 4 4 1-5 Have been open to students’ suggestions and adjustments of online classes 8521 3.60 4 4 1-5 Have informed me on what exams will look like in this new situation 8589 3.11 3 4 1-5 4.1.6. Workload Students were asked to evaluate the amount of their study workload during the COVID- 19 pandemic. Out of 9132 students who answered this question, the majority of them reported that their study workload was larger than before on-site classes were cancelled (N=4609 or 50,47%). Only 1739 students (19,04%) said that their study workload was smaller than before while 2325 students (25,46%) reported no changes in their perceived study workload. These results are depicted in Figure 2. Table 15 Students’ ratings of assessment modalities since on-site classes were cancelled 5,03% 25,46% 50,47% 19,04% Figure 2 Study workload on online classes compared to on-site classes Empirical findings and interpretation | 2322 | Empirical findings and interpretation with their close family members and close friends, while colleagues from the course are in third place. A more detailed analysis is presented in Table 19. N Median Range Close family members 9096 1.58 1-6 Close friends 9037 2.41 1-6 Colleagues from my course 9058 3.17 1-6 Lecturers 9033 3.97 1-6 More distant family members 9075 4.16 1-6 Acquaintances 8858 4.61 1-6 Administrative staff 8980 5.49 1-6 Voluntary organizations offering support during the Pandemic 9056 5.76 1-6 Several times a day Once a day Several times a week Once a week Two or three times a month Not at all Close family members 70.2 11.6 11.6 4.1 1.5 1.5 More distant family members 2.6 7.2 24.0 23.3 24.0 19.0 Close friends 37.1 16.9 26.9 10.0 5.4 3.6 Acquantainces 3.0 3.5 15.5 19.2 25.5 33.4 Colleagues 17.8 12.9 33.0 16.1 11.2 9.0 Lecturers 3.9 8.2 27.9 25.3 16.2 18.5 Administrative staff 0.8 0.9 3.6 6.5 18.9 69.2 Voluntary organizations 0.9 0.7 2.0 2.5 5.5 88.4 Overall, it seems that since the COVID-19 pandemic started, many students have turned to their families: they have returned to their parents’ homes and are getting support from their immediate family circle. * the larger value of median indicates lower frequency of contact Table 18 Frequency of contact with different people in students’ academic and social life: descriptive statistics* Table 19 Frequency of contact with different people in students’ academic and social life: frequency tables 4.2.3. Perceived social support The last instrument used in this part of the questionnaire was the shortened scale of bonding social capital (Ellison et. al., 2007). The scale included five items and students were asked to give their answers on a Likert-type scale with five points (1 = strongly dis- agree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree). As can be seen in Table 20, students gave relatively high rates to the majority of items, with the exception of the last item which is the only reversed item in the scale. More specifically, 9,1% of students answered that they disagree or strongly disagree with the first item in the scale (there are several people I can trust to help solve my problems), while 68,9% of them answered positively to this question. Similarly, 7,3% of students disa- greed with the second item in the scale, while 83,3% answered positively, indicating that for the majority there is someone they can turn to for advice about making important decision. When it comes to the third item, 21,9% of respondents disagreed, indicating that they do not have someone if they needed an emergency loan of 500 euros, while 63,1% agreed. More than half of our respondents (51,4%) think the people they interact with would be good job reference for them, while 14,4% disagreed. Finally, 15,2% of students think they do not know people well enough to get them to do anything important, while 58,6% disagreed. N Mean SD Range There are several people I trust to help solve my problems 9084 3.74 1.16 1-5 There is someone I can turn to for advice about making very important decisions 9074 4.12 0.96 1-5 If I needed an emergency loan of 500 euros, I know someone I can turn to 9069 3.59 1.31 1-5 The people I interact with would be good job references for me 9056 3.46 1.00 1-5 I do not know people well enough to get them to do anything important 9034 2.36 1.08 1-5 To identify certain characteristics of students who had lower levels of bonding social capital during the COVID-19 crisis lockdown, differences in students’ bonding social cap- ital were examined according to their field of study (i.e. Education, Arts and Humanities, Social Sciences, Business and Law, Natural and Life Sciences, Engineering, Manufacturing and construction, Agriculture and veterinary medicine, Health and welfare, Services and Other), year of study (i.e. undergraduate years 1, 2, 3, and 4, master’s years 1 and 2) and ac- commodation (i.e. family home, rented accommodation, student hall/dorm and other) by means of one-way ANOVAs. Post hoc multiple comparisons were performed using LSD test (in the following text, only statistically significant differences will be commented). In addition, Pearson correlation coefficients were calculated between bonding social capital and students’ age, gender (i.e. male vs. female), student status (i.e. full time vs. part time), paying tuition fees (i.e. yes vs. no), receiving scholarship (yes vs. no), parental edu- cational level (i.e. primary schooling, secondary schooling, tertiary education), capability to cover study and living costs (i.e., six-points scale ranging from “with great difficulty” to “very easily”) and presence of health issues (i.e., chronic illness, mental health problems, physical disabilities and other health problems; present vs. absent). Table 20 Bonding social capital Empirical findings and interpretation | 2524 | Empirical findings and interpretation Prior to conducting these analyses, a composite score on bonding social capital was cal- culated as a mean value of ratings on individual items divided by its total number. Internal consistency of this scale was satisfactory (Cronbach a=0.74). The ANOVA results showed that students differed in their level of bonding social capital according to their field of study (F [8, 7152] = 8.78, p<0.01). Students in the field of Engi- neering, manufacturing and construction reported lower levels of bonding social capital than any other group of students. Next, students differed in their bonding social capital depending on their year of study (F [6, 7152] = 6.38, p<0.01). Undergraduate students at second and fourth year of study had greater bonding social capital compared to under- graduate students in their first year of study. In addition, first year master studies students reported greater bonding social capital compared to all other groups of students except undergraduates at year four. Finally, students differed in their ratings of bonding social capital based on their accommodation since the onset of the COVID-19 pandemic (F [3, 7165] = 12.49, p<0.01). Students who were living in their family homes reported higher levels of bonding social capital in comparison to students who were living in rented accommo- dation or student hall/dorm. However, students who were living in rented accommoda- tion had higher social bonding capital then those who were living in student halls/dorm. The results of correlation analyses are shown in Table 21. Bonding Social Capital Socio-demographic characteristics Age -0.01 Gender1 0.09** Capability to pay study costs 0.23** Parental educational level 12 0.08** Parental educational level 22 0.10** Academic characteristics Student status1 -0.01 Paying tuition fees1 0.03* Receiving scholarship1 -0.01 Presence of health issues Chronic illness1 -0.04** Mental health problems1 -0.18** Physical disabilities1 -0.05** Other health problems1 -0.07** 1 Dummy variables: gender (0=male, 1=female), health issues (0=absent, 1=present), student status (1=full- time, 2=part-time), paying tuition fees (1=yes, 2=no), receiving scholarship (1=yes, 2=no); 2 Due to ordinal scale of the variable, Spearman Rho coefficient was calculated; *p<0.05 **p<0.01; Correlations were calculated on a sample of students whose on-site classes were cancelled As can been seen in Table 21, female students, students with a greater capability to cover study and living costs, students whose parents were more highly educated as well as students who were not paying tuition fees reported higher levels of bonding social capi- tal. In contrast, students who suffered from health impairments reported lower bonding social capital. 4.3. EMOTIONAL WELL-BEING In order to assess students’ emotional well-being during the COVID-19 pandemic, stu- dents were asked to rate the frequency at which they were experiencing particular emo- tions related to attending classes and studying and preparing for them (i.e., joyful, hopeful, proud, frustrated, angry, anxious, ashamed, relieved, hopeless and bored). They gave their answers on a Likert-type scale with 5 points (1=never, 2=rarely, 3=sometimes, 4=often, 5=al- ways). In addition to such emotions, students’ well-being during the COVID-19 pandemic was assessed by 6 items extracted from the revised version of the Psychological General Well-Being Index (PGWB-R; Revicki, Leidy, & Howland, 1996). Students rated how often they felt in the described way during the last several weeks on a 5-point Likert-type scale (1=none of the time, 2=a little of the time, 3=some of the time, 4=a good bit of the time, 5=all of the time). Sample item is: “I have had or felt a lot of energy and vitality”. Results presented in Table 22 show that, with respect to the theoretical range of possible values, students most frequently felt frustrated, anxious and bored in relation to their academic activities. They reported average frequency of joy and slightly above average frequency of pride, and they also reported quite a low frequency of undesirable emotions of hopelessness and shame. Interestingly, their average levels of general well-being were located somewhat below the middle point of the scale indicating that students’ well-be- ing during the COVID-19 pandemic might have worsened. Emotion N Mean Median Mode Range Joyful 7229 2.99 3 3 1-5 Hopeful 7229 3.16 3 3 1-5 Proud 7207 2.81 3 3 1-5 Frustrated 7228 3.54 4 4 1-5 Angry 7222 2.93 3 3 1-5 Anxious 7213 3.39 4 4 1-5 Ashamed 7202 2.04 2 1 1-5 Relieved 7201 2.56 3 3 1-5 Hopeless 7215 2.64 3 3 1-5 Bored 7231 3.31 4 4 1-5 General well-being 7151 2.91 2.83 3 1-5 Table 21 Correlates of students’ bonding social capital during the COVID-19 pandemic * General well-being score was calculated as a mean value of students’ ratings on six items. Cronbach a for this scale was 0.85. Table 22 Frequency of experienced emotions and evaluation of general well- being Empirical findings and interpretation | 2726 | Empirical findings and interpretation 4.4 SKILLS AND INFRASTRUCTURE FOR STUDYING FROM HOME 4.4.1. Digital skills Digital skills can be crucial in getting the most out of online classes and seminars which is why respondents’ perception of their own skills in the digital environment is important for understanding where potential differences between students may lie. In order to evaluate these skills, a scale was used (Ragnedda, Ruiu and Addeo 2020) that measured how students manage various information and situations online. A five-point Likert-type scale was used (1= strongly disagree, 2= disagree, 3= neither agree nor disagree, 4= agree, 5= strongly agree) and Table 23 shows that on most of the statements provided, respondents on average perceive themselves as skilled and confident when various el- ements of digital literacy is involved. However, it is also clear that this confidence is lower when more complex usage of software and programs are taken into consideration. For example, values for applying advanced formatting functions (M=3,68, SD= 1,05), ability to select safe and suitable digital media (M=3,58, SD= 1,03) and applying advanced settings in software and programmes (M=3,18, SD= 1,2) are lower than basic digital skills. It is worth pointing out that these three skills are less relevant for online lectures and classes as access to these requires basic digital knowledge and skills, but it can be argued that respondents who are more competent in advanced areas of digital literacy are simultaneously also more likely to cope better with unforeseen challenges when presented with an environment of online lectures and seminars. Online teaching platforms have been of particular importance during the COVID-19 pandemic. Our results show that the majority of students feel confident in using these platforms. However, for some students the use of such platforms is more of a challenge. N Mean SD Range I am confident in browsing, searching and filtering data, information and digital content 7259 4,27 0,82 1-5 I am confident in using online teaching platforms such as MS Teams, Zoom and similar 7264 4,09 0,94 1-5 I can produce complex digital content in different formats (e.g. images, audio files, text, and tables) 7260 3,93 0,98 1-5 I can apply advanced formatting functions of different tools (e.g. mail merge, and merging documents of different formats) to the content I or others have produced 7259 3,68 1,05 1-5 I am able to select safe and suitable digital media, which are efficient and cost-effective in comparison with others 7259 3,58 1,03 1-5 I am able to apply advanced settings to some software and programmes 7252 3,18 1,2 1-5 A closer look at the responses in percentages when it comes to confidence in using online teaching platforms shows that the majority of students (80.7%) feel confident in using online teaching platforms such as MsTeams, Zoom and similar. However, 7.9% indicated their lack of confidence in using online teaching platforms. Table 23 Digital skills of the respondents: mean values Strongly disagree Disagree Neither agree nor disagree Agree Strongly agree I am confident in browsing, searching and filtering data, information and digital content 0,9% 3,1% 8,9% 41,3% 45,8% I am confident in using online teaching platforms such as MS Teams, Zoom and similar 1,8% 6,1% 11,4% 41,9% 38,8% I can produce complex digital content in different formats (e.g. images, audio files, text, and tables) 2,0% 7,7% 16,9% 41,7% 31,7% I can apply advanced format- ting functions of different tools (e.g. mail merge, and merging documents of different formats) to the content I or others have produced 3,1% 11,7% 22,8% 38,4% 24,0% I am able to apply advanced settings to some software and programmes 8,4% 23,3% 25,6% 26,3% 16,4% I am able to select safe and suitable digital media, which are efficient and cost-effective in comparison with others 3,7% 10,5% 28,8% 37,2% 19,8% To explore the characteristics of students with different levels of digital capital, a series of one-way ANOVAs was conducted with the following factors: field of study, year of study and accommodation since the onset of the COVID-19 pandemic. Again, post hoc multiple comparisons were performed using LSD test and only statistically significant differences will be discussed in the following sections. Furthermore, Pearson correlation coefficients were calculated between digital capital and students’ age, gender, student status, paying tuition fees, receiving scholarship, parental educational level, capability to cover study and living costs and presence of health issues. Prior to conducting these anal- yses, a composite score on digital capital was calculated as a mean value of ratings on individual items divided by its total number. Internal consistency of this scale was very good (Cronbach a=0.87). The results of ANOVAs showed that students differed in the level of dig- ital capital according to their field of study (F [8, 7191] = 34.25, p<0.01). Students in the field of Engineering, manufacturing and construction reported higher levels of digital capital compared to all other groups of students. Next, differences in digital capital according to the year of study were only marginally statistically significant (F [6, 7190] = 2.17, p=0.043). Master students in both years of study reported somewhat greater digital capital in comparison to undergraduate students in their first two years of study. Lastly, there were no differences in digital Table 24 Digital skills of the respondents: percentages Empirical findings and interpretation | 3332 | Empirical findings and interpretation To explore whether groups of students whose job was affected by the COVID-19 pandem- ic differed in their capability to cover costs of studying and living, a one-way ANOVA was conducted with LSD post hoc tests. The results showed that different groups of students indeed differed in their economic status (F [5, 4358] = 28.18, p=0.01). In particular, students who lost their job permanently had statistically significant lower levels of capability to cover the costs of studying and living compared to all other groups of students. In con- trast, students who reported still working rated their capability to cover the costs of stud- ying and living as more positive in comparison to their colleagues whose job was affected by the COVID-19 crisis. 4.5.3. Tuition fees Students were asked whether they pay tuition fees and if so whether the fees had been affected by the COVID-19 pandemic. Out of 9117 respondents who answered this question, 47,8% pay tuition fees. In this group of respondents who pay tuition fees, 75,3% answered that fee payment has remained the same at their institution. However, some institutions have provided flexible ways of paying for the fees (13,8% of students indicated this) and 1,8% of students reported that their institution had cancelled the payment of fees for this term. The distribution of answers is presented in Figure 12. 4.5.4. Scholarships Students were asked whether they receive a scholarship and whether this had been af- fected by the COVID-19 crisis. Out of 8179 respondents who answered this question, 64,2% do not and 35,8% do receive a scholarship. Among this group of respondents who receive a scholarship, the majority of them (87,4%) had answered that the amount of scholarship has remained the same. However, for almost one tenth of students the crisis has had an adverse effect on their scholarship status and their scholarship payment had either been postponed (4,10%), cancelled (2,9%) or reduced (2,6%). 32,1% 28,9% 12,4% 9% 5,3% Yes, I have lost the job permanently Yes, I have lost the job temporarily Yes, I have had a salary cut No, the job ended before the Covid-19 crisis No, I’m still working None of the above 12,2% Fee payment has remained the same 75.30% My institution has introduced exible ways of paying fees this term 13.80% None of the above 6.70% My institution has reduced the amount of fees which need to be paid this term 2.40% My i stitution has cancelled he paymen of fees for this term 1.80% 75,3% 13,8% 6,7% 1,8% Fee payment has remained the same 2,4% My institution has introduced exible way of paying fees this term None of the above My institution has reduced the amount of fees to be paid this term My institution has cancelled payment of fees this term 87,4% 4,1% 3% 2,6% The amount of my scholarship has remained the same 2,9% Payment of the scholarship has been postponed None of the above My scholarship has been cancelled The amount of my scholarship has been reduced No, I have not worked this academic year and was not planning to 37.2 No, I have not worked this academic year but was planning to 24 Yes, I worked regularly this academic year 21.5 Yes, I worked occasionally this academic year 14.7 None of the above 2.5 37,2% 24% 21,5% 14,7% 2,5% No, I have not worked this academic year and was not planning to No, I have not worked this academic year but was planning to Yes, I worked regularly this academic year Yes, I worked occasionally this academic year None of the above Figure 10 Have you had a paid job during the current academic year or were you planning on having a paid job during the current academic year? Figure 11 If you have been working or were planning to work, has this paid job been affected by the COVID-19 pandemic Figure 12 If you do pay tuition fees, in the context of the COVID-19 pandemic please indicate whether… Figure 13 Change in scholarship payment Empirical findings and interpretation | 3534 | Empirical findings and interpretation 4.6 CORRELATES OF STUDENTS’ SATISFACTION AND ADJUSTMENT DURING THE COVID-19 PANDEMIC LOCKDOWN We used four indicators of students’ adjustment2 during the COVID-19 pandemic: 1. Satisfaction with teaching and administration 2. Perceived drop in performance since on-site classes were cancelled 3. Self-efficacy beliefs 4. General well-being Differences in indicators of students’ academic adjustment were explored according to their socio-demographic and academic characteristics (i.e. gender, age, economic status, parental educational level, accommodation, student status, year of study, field of study, tuition fee payment, receiving scholarship), health impairment (i.e. presence of chronic illness, mental health problems, physical disabilities and other health problems), digital capital, bonding social capital, everyday worries (i.e. about health, taking care of others and covering the costs of studying and living) and home facilities for studying (i.e. a quiet place to study, a desk, a computer, a good Internet connection, access to course study material)2. To examine the differences in indicators of students’ adjustment according to their field of study, year of study and accommodation since the onset of the COVID-19 pandemic, a series of one-way ANOVAs were calculated. Post hoc multiple comparisons were per- formed using LSD test and can be found in the Appendix. In the following sections, only statistically significant differences will be commented. Concerning students’ satisfaction with teaching and administration, statistically signifi- cant differences emerged in relation to the field of study (F [8, 7171] = 11.37, p<0.01), year of study (F [6, 7170] = 7.53, p<0.01) and accommodation (F [3, 7183] = 3.84, p<0.01). The obtained results suggest that students in the fields of Arts and Humanities and Social Sciences, Business and Law were the most satisfied since their overall satisfaction ratings were higher than ratings of students in all other fields. Students in Agriculture and veter- inary medicine and Health and welfare fields were the least satisfied with teaching and administration during the pandemic, possibly because their course consists of practical work which was difficult to organize during lockdown. Regarding the year of study, results showed that students at master level studies were more satisfied with teaching and administration when compared to undergraduate stu- dents. Students at different years of study within the undergraduate and graduate levels did not differ in their levels of satisfaction. Lastly, students who lived in their family home during the COVID-19 pandemic reported to have greater satisfaction than students who lived in rented accommodation. Next, differences in the perceived drop of academic performance were found only in rela- tion to the year of study (F [6, 7162] = 4.95, p<0.01), but not in relation to field of study (F [8, 7162] = 1.89, p>0.05) or accommodation (F [3, 7174] = 0.34, p>0.05). Undergraduate students in year 1 reported a greater drop in performance when compared to undergraduate students in year 2 and all graduate students. Similarly, undergraduate students in year 2 reported a greater drop in performance in comparison to all graduate students, while undergraduates in years 3 and 4 reported a greater drop in performance only when compared to graduate students in year 1. The results suggest that students in earlier stages of their courses tended to experience a greater decline in academic performance during the COVID-19 pandemic. Statistically significant differences in students’ self-efficacy emerged in relation to the field of study (F [8, 7098] = 4.36, p<0.01) and year of study (F [6, 7098] = 18.48, p<0.01) but not in re- 2 Overall student satisfaction with teaching and administration was calculated as a composite score of 7 items (see Table 31 for their content). This newly created scale had a unidimensional latent structure and satisfactory level of internal consistency (a=0.84). Perceived drop in performance was calculated as a mean of ratings on two items assessing perceived changes in academic performance during the pandemic (a=0.81). Self-efficacy and general well-being were calculated as composite scores of items on these two scales. lation to accommodation (F [3, 7110] = 0.58 p>0.05). Students in the fields of Education, Arts and Humanities, Social Sciences, Business and Law, Health and welfare, as well as Services, reported higher levels of self-efficacy than students in the field of Engineering, Manufac- turing and construction. Additionally, students in the field of Social Sciences, Business and Law and Health and welfare reported greater self-efficacy than those in the field of Natural and Life sciences. These results suggest that students of Engineering, Manufacturing and construction might have been the most adversely affected when it comes to their per- ceived academic self-efficacy. Students studying at in more senior years of study tended to report greater self-efficacy than those studying in lower years of study. More specifically, undergraduate students in year 3 had higher self-efficacy in comparison to undergraduate students in year 2. Similarly, undergraduate students in year 4 had higher self-efficacy when compared to undergraduate students in year 1. Finally, all students at master level reported greater self-efficacy in comparison to their undergraduate colleagues. Finally, concerning students’ general well-being, statistically significant differences emerged in relation to the field of study (F [8, 70130] = 8.63, p<0.01) and year of study (F [6, 7130] = 7.83, p<0.01), but not in relation to accommodation (F [3, 7149] = 1.18, p>0.05). Post hoc comparisons showed that students in the field of Arts and Humanities reported the lowest levels of general well-being when compared to all other groups of students. In addition, students studying in the field of Engineering, Manufacturing and construction reported greater general well-being in comparison to students in Education and Social Sciences, Business and Law fields. Finally, students in the field of Services had greater self-reported well-being in comparison to all other groups of students except students in the fields of Engineering, Manufacturing and construction and Agriculture and veterinary medicine. In the next step, the correlation coefficients between the four indicators of students’ ad- justment and socio-demographic and academic characteristics, presence of health issues, the availability of needed home facilities for studying, digital capital, bonding social capital and everyday worries were calculated. Satisfaction with teaching and administration Perceived drop in performance Self-efficacy General well-being Socio-demographic characteristics Age .07** -0.06** 0.09** 0.11** Gender1 -0.02 -0.03* -0.01 -0.16** Capability to pay study costs 0.16** -0.08** 0.15** 0.17** Parental educational level 12 -0.02 -0.01 0.04** 0.01 Parental educational level 22 -0.02 -0.01 0.05** 0.02 Academic characteristics Student status1 0.06** -0.05** 0.03* 0.05** Paying tuition fees1 -0.06** 0.01 0.01 0.06** Receiving scholarship1 -0.01 -0.02 -0.03* 0.00 Table 28 Correlates of students’ adjustment during the COVID-19 pandemic Empirical findings and interpretation | 3736 | Empirical findings and interpretation Satisfaction with teaching and administration Perceived drop in performance Self-efficacy General well-being Presence of health issues Chronic illness1 -0.06** 0.02 -0.04** -0.09** Mental health problems1 -0.10** 0.11** -0.14** -0.34** Physical disabilities1 -0.02 0.01 -0.04** -0.04** Other health problems1 -0.05** 0.04** -0.05** -0.09** Home facilities for studying Quiet place to study .25** -0.22** 0.27** 0.29** Desk .14** -0.10** 0.13** 0.14** Computer .16** -0.06** 0.15** 0.08** Good Internet connection .20** -0.16** 0.24** 0.22** Course study material .34** -0.19** 0.31** 0.22** Digital Capital .23** -0.19** 0.32** 0.18** Social bonding .23** -0.16** 0.18** 0.32** Worries Covering the costs of study -0.16** 0.04** -0.12** -0.15** Covering the costs of living -0.15** 0.05** -0.12** -0.16** Balancing care responsibilities with studying -0.13** 0.06** -0.10** -0.18** Health -0.06** 0.02 -0.06** -0.17** 1 Dummy variables: gender (0=male, 1=female), health issues (0=absent, 1=present), student status (1=full- time, 2=part-time), paying tuition fees (1=yes, 2=no), receiving scholarship (1=yes, 2=no) 2 Due to ordinal scale of the variable, Spearman Rho coefficient was calculated * p<0.05 ** p<0.0001 Correlations were calculated on a sample of students whose on-site classes were cancelled Concerning satisfaction with teaching and administration, correlational analysis indicat- ed that students who were older, who had greater capability to cover costs of studying and living, those who were not paying tuition fee as well as part-time students reported greater levels of satisfaction. In addition, higher levels of satisfaction with teaching and administration were reported by students who did not suffer from any chronic illness, mental health problems or other health problems, as well as by students who had better access to home facilities for studying (including a quiet place to study, desk, computer, good Internet connection and course study material). In addition, students with greater digital and bonding social capitals were more satisfied with teaching and administration. Finally, those who worried less about costs of studying and living, their health or balancing care responsibilities with studying were also more satisfied. Similar results were found for perceived drop in performance. Younger and male stu- dents, those who are less able to cover study costs and full-time students reported greater perceived drop in academic performance. Next, this drop was more pronounced among students who suffered from mental health problems and other health problems as well as among those who worried more about costs of study and living, their health and bal- ancing between care responsibilities and studying. In addition, students who reported having poorer access to home facilities needed for studying (including a quiet place to study, desk, computer, good Internet connection and course study material), lower levels of digital and social bonding capitals were also more likely to report they had experienced a drop in their academic performance during lockdown. Older students, students of more educated parents, part-time students, students who were receiving a scholarship and those who had greater capability to cover their costs, reported higher levels of self-efficacy. In addition, students who did not suffer from any health con- dition, who had better access to home facilities needed for studying and those with greater levels of digital and social bonding capitals, had higher levels of self-efficacy. In contrast, reporting greater worries about covering study and living costs, their health or balancing between care responsibilities and studying was related to lower self-efficacy levels. Lastly, older and male students, part-time students and students who were paying tuition fees as well as students who reported a greater capability to cover costs of studying and living had higher levels of general well-being. Greater general well-being was related to the absence of any health problems and lower levels of worries about costs, health or bal- ancing between care responsibilities and studying. Furthermore, having better access to home facilities for studying and higher levels of digital and social bonding capitals were related to greater well-being. In contrast, lower levels of general well-being were reported by women, those with any health issue, those who are worried about covering their study and living costs, their health and balancing care responsibilities with studying. Finally, to identify which of the examined factors are the most important ones in an attempt to explain the variability in different indicators of students’ adjustment, a series of hierarchical regression analyses were conducted. Hi- erarchical regression analysis enables exploring the unique contribution of specific predictor variables (or set of predictor variables) in explaining the variance in criterion variables after other predic- tor variables (or set of predictor variables) have been statistically controlled for. In particular, four hierarchical regression analyses were con- ducted with each of the examined indicators of students’ adjustment as criterion variables. 42 | Student voices | 43 STUDENT VOICES ON STUDYING DURING COVID-19 LOCKDOWN5 Students were asked four open-ended questions in the final part of the questionnaire: what they liked and disliked about studying from home, what problems they have encountered in the process and recommendations for improving their study experience. The answers to these open questions were coded openly using descriptive codes. The coding process ended once saturation in responses was reached. The codes were grouped into deductive themes: advantages of studying from home, disadvantages, problems and recommendations. For a summary of the main points raised please see Table 39 in the Appendix. A prominent answer to the question of what they liked about studying from home during lockdown was the autonomy to plan their own time. The following responses illustrate this: “studying at my own pace”, “paced to my liking”, “I can control my time”, “I like the fact that I can organize my study”, “manage my own schedule”, “plan the day as I like. Wake up when I want, study when I want, take a break when I want, go outside for a walk then I want. Study what subject I want”. The phrase “my own pace” particularly stood out in the answers. In general, many students when responding to the question of what they liked about stud- ying from home indicated that it opened up “more time to study” (not having to get ready to go to their higher education institution, not having to travel to and from the institution). A frequent answer to what students liked about studying at home can be summarized as being with one’s family. Illustrative responses include: “Could spend more time with my parents”, “being surrounded with family”, “be with my partner and my dogs during the day”, “more time with my family”. Students also singled out not having to travel as a benefit of studying from home. On the one hand, not having to travel was described as time saving (“not losing time on commute”, “not losing time on transport”, “time saved by not travelling”, “less time spent in traffic”), on the other as cost saving (“save bus fare”, “saving petrol”). Lower costs were also mentioned by students with regard to food (“saving money I would spend on lunch at café”) and socializing. Additionally, in relation to food, certain students noted that their diet was better when studying from home: “I eat more healthy”. The comfort of following lectures from home and being able to sleep more were also fre- quent responses. For example, “can participate in class in the comfort of my home”, “more re- laxed environment”, “it’s more comfortable to follow the lectures”, “have a bit more sleep”, “get- ting enough sleep”, “not waking up early” and “more hours of sleep” are selected illustrations of these mentioned benefits. On the other hand, the home can also be a source of frustration for certain students, particularly those who do not have adequate infrastructure for studying from home, i.e. who do not have a quiet place to study or have a poor Internet connection or poor access to study materials: “I am not alone in the house so it’s not always easy to find a quiet place to study”, “I don’t have a separate study room or living room so I am constantly fighting the urge to just stay in bed and be depressed all day”, “Sometimes the Internet is very bad”, Not all people have the same conditions at home, the lack of Internet or devices is a con- cern to some”, “study material is not always available”, “the most important thing is that I can’t have all the additional material I could get from the university library”. For certain students, not having to go to their higher education institutions is less stress- ful: “I also don’t feel nervous”, “I do not feel I am constantly drowning”. One response prob- lematically indicated that a benefit of studying from home is that “cheating is an option”. It is important to note that for some of our respondents there are no benefits to studying at home (“I don’t like this way of studying”, “basically none, apart from listening to boring Student voices | 4544 | Student voices lectures now from home”, “I cannot find any benefits of studying from home”), as well as that for some this is not a new experience: “I was already studying from home so it doesn’t change anything”, “This is how it was done before COVID-19 so nothing really changed”. For those who wrote critically of their study experiences at home, the most prominent critique was that they are not able to have practical classes which are integral to their course of study, as well as that they missed face-to-face interaction with their teachers and colleagues. The following responses illustrate this: “the quality of education has been significantly reduced, especially since my field of study (veterinary medicine) is a highly practical education”, “not being able to go to the laboratory or the field (I’m a biology student)”, “no proper interaction with teacher”, “there is no immediate response from the lecturers”, “we could have more video-calls with teachers, where they can talk about the lessons instead of sending work to do for the next weeks”, “having no close contact with friends or colleagues”, “stuck with no one your own age”, “not seeing colleagues for a long time”, “I can’t enjoy the academic life without my friends and social contact”. Other disadvantages of studying from home which were mentioned include: having to be in front of the computer all day, the monotony of everyday life (repetitive days) as well as blurred boundaries between one’s work and free time. Problems students mentioned they had encountered during their lockdown study experience overlapped in many ways with what they reported as the disadvantages of studying from home. The biggest problem that students faced was lack of motivation and increased procrastination because of the unstructured schedule that prolongs studying to the whole day. Or in their own words: “Lack of motivation, difficulty distinguishing between free time from study time, less ability to concentrate, stress due to quizzes and tests, uncer- tainties about the future and method of evaluation“. Indeed, many students responded that it was difficult for them to concentrate at home: “hard to concentrate”, “hard to concentrate at home”, “I can’t focus. I get distracted very easily” are some of the answers illustrating this. Indeed, getting distracted was a frequent response when it came to students listing disadvan- tages of studying at home. Reasons for this were usually related to one’s family: “It is difficult studying at home with family and kids moving around all the time”, but also other distractions. For example, one student responded: “studying in private at home means it’s very easy to get distracted and procrastinate. TV, computer, smartphone etc.”. In their experience, online classes cannot compensate for the practical elements of their studies. Moreover, they find it hard to study on their own, without the possibility to imme- diately clarify open questions with teachers, or to interact and discuss in and outside of classroom with their co-students. More complex subject matter is especially hard to learn in an online environment. As they say: “It takes way more time and energy to study by your- self, than to listen attentively in a lecture while taking notes. I also used to ask a lot of ques- tions to understand the subject matter more, but I can’t really do that anymore.”; “I miss going to Uni and meeting everybody there and talk to them. In our Uni it’s like a big family and we always help each other and rate the work of the others or have tipps. It isn’t easy to do that online.”; “Time just disappear somewhere and the midnight is come, and nothing is done. Don’t have motivation to do it all on my own in home alone. The video call is not enough to get motivation. The feeling is like it’s not real. Everything is online and everything is worthless. Don’t have real person feedback for my work, just emails.” A paradox therefore emerges: a flexible schedule and living at home can on the one hand be less stressful and less financially demanding, but on the other hand can make it harder for the students to focus on studying and can also alienate them from their co-students. Combined with these problems, not having clear and sufficient information about exams, creates additional problems to the online study experience. Students feel that their workload has increased because teachers compensated the lack of on-site classes by additional assignments. So, students spend a lot of time in front of the computer, indoors and sitting down, and some in unsuitable conditions for studying (they do not have their own rooms, no desks, they share a computer and internet connection or are dis- tracted by family). Although being with family provides support, it can also be challenging to maintain one’s focus on studying in a home setting, especially for students who live in big families or have children themselves: “Eye tiredness, more homework (projects, works), the necessity to do several things around the house while studying, which distracts from the work that I am doing”; “I am not alone in the house so it’s not always easy to find a quiet place to study and the most important thing is that I can’t have all the additional material I could get from university’s library.”; “(…) Family expecting me to do housework even though I say I have schoolwork to do.”; “I have struggled finding my quite place in the house and focusing on a daily basis. There are days where I feel very focused, and days where I feel very useless and effortless. Going from living with 1 friend, to living every day in contact with 4 family members has been a huge change that has really impacted my learning and focus.” Rounding up problems that students encountered while studying from home, poor internet connections were often mentioned. Whether their connection was breaking off, or was in- sufficiently fast since the whole of their household was either working or studying from home, this seems to be the most common (technical) obstacle experienced. But, even when the In- ternet was working, students needed more free and online accessible resources for studying. In that respect, closing up of libraries made it even harder for students to study, since they lost access to study materials and were not able to use libraries as a place for studying. This seems to be especially hard for those students who do not have favourable home conditions (e.g. disagreements with parents or having children). This makes libraries a rather crucial resource for a full study experience. In naming what would make their studying from home experience better, students were slightly less elaborate. Their suggestions for improvement counterpart their naming of the problems they encountered. They would also either claim that they do not have any suggestions on how to improve their online studying experience, or they would express their wish to return to campus. As our questionnaire data shows, students suggested that more of the classes should be held live via video-calls. They emphasize the living experience of the lecture, since stud- ying from written materials provided by teachers is not sufficient. But, in order to help them study better, they would also like to have a recording of the lectures, so that they can return to them at their convenience: “If the lecturers had made movies of all lectures we would have normally, and we would have possibility to play it when we want.” In addition, a lighter workload, clearer teacher instructions and more understanding for the stressful living and studying situation both on the part of teachers but also university administration, would also be helpful. Overall better support of university administration is named as an important element of improvement of online studying: “I would upload online materials that we need to pass exams, make an open class where administration and professors can hear our problems and demands”. Of course, better internet connec- tions and (personal) computer resources were also seen as crucial. Students have noted that being able to study at one online platform in a similar manner for all the courses would also better their studying from home experience: “At present situation, every lector is working with students in a slightly different manner. Some unification would make situation easier.” This claim indicates that they would like the online experience to resemble the on-site studying experience as much as possible. If they cannot be on campus, at least they would like to emulate that structure and learning experience in a digital surrounding. A fuller picture of the challenges of studying from home can be rounded up by the fol- lowing statement that emphasizes all of the socio-economic complexities of students’ ex- perience during the COVID-19 crisis: “(…) better social conditions, equal PC for all students. Job loss is a heavy social burden, especially when it is not sure how to pay rent etc. Social backgrounds favor who studies well and who does not. The university cannot cope with the fact that someone has to do care-work on the side. There must not be any disadvan- tage for any students.” 46 | Policy implications | 47 6 POLICY IMPLICATIONS RECOMMENDATIONS FOR PUBLIC AUTHORITIES RESPONSIBLE FOR HIGHER EDUCATION LEARNING AND TEACHING Public authorities should support and provide the means to higher education institutions to improve initial and continuing professional training for academic and administrative staff on how to effectively replace on-site learning and teaching methods with online delivery. The COVID-19 pandemic forced higher education institutions to transform their methods of teaching and learning in a very short period. This transformation has required extensive use of technology and communication platforms by academic and administrative staff. Public authorities should help higher education institutions by creating cooperative na- tional structures, securing the exchange of good practices, and facilitating peer learning and inter-institutional staff development both in terms of the technical aspects of online delivery, but also pedagogic practices including assessment . STUDENT SERVICES Public authorities should have policies that enable higher education institutions to pro- vide effective, accessible, and user-friendly counselling and guidance for students in order to find adequate solutions for academic, health, and career challenges caused by the COVID-19 pandemic. Students (45,5%) prefer to talk about the COVID-19 crisis with close family members, fol- lowed by a close friend (32,8% of students). Only 1,5% of students would turn to institution- al sources of support such as administrative staff. On the other side, if they would like to talk about problems related to studying issues (lectures, seminars, practical work), 32,4% of respondents would first turn to their colleagues, while 31,6% of our respondents would first talk to a close friend, and 18,9% chose the answer “close family member”. Only 5,8% of students would turn to administrative staff at their institution. So students very often do not seek institutional support for problems they may have. FUNDING An emergency fund for helping students to ameliorate the negative consequences caused by the COVID-19 pandemic should be established by public authorities, and it should provide grants to underrepresented, disadvantaged, and vulnerable students. The Eurostudent VII survey (2020:14) shows that on average almost 60% of students in Eurostudent countries work along studies. The same survey finds that 49% of students would not have been able to study at all if they did not have a paid job to finance their studies. On the other side, this survey demonstrates that, out of the students who were working or had intended to work this term, 12,2% had lost their job permanently and 28,9% lost the job temporarily. These students are now significantly less capable of covering their cost of study and living, compared to all other groups of students. One of these costs is related to accommodation. In particular, a higher proportion of students who lived in rented accommodation and student dorms reported worrying about costs of studying Appendix | 5352 | Appendix Field of study Mean Difference Standard Error p Social Sciences, Business and Law Other (please specify) .10158* .03630 .005 Education .11283* .05419 .037 Arts and Humanities .00353 .03920 .928 Natural and Life Sciences .19274* .04671 .000 Engineering, Manufacturing and construction .10689* .03456 .002 Agriculture and veterinary medicine .31382* .05579 .000 Health and welfare .26459* .03480 .000 Services (tourism, sports, transport, security) .08716 .05646 .123 Natural and Life Sciences Other (please specify) -.09116 .04854 .060 Education -.07992 .06305 .205 Arts and Humanities -.18921* .05075 .000 Social Sciences, Business and Law -.19274* .04671 .000 Engineering, Manufacturing and construction -.08585 .04726 .069 Agriculture and veterinary medicine .12108 .06443 .060 Health and welfare .07185 .04743 .130 Services (tourism, sports, transport, security) -.10559 .06502 .104 Engineering, Manufacturing and Construction Other (please specify) -.00531 .03699 .886 Education .00594 .05466 .913 Arts and Humanities -.10335* .03985 .010 Social Sciences, Business and Law -.10689* .03456 .002 Natural and Life Sciences .08585 .04726 .069 Agriculture and veterinary medicine .20693* .05624 .000 Health and welfare .15771* .03552 .000 Services (tourism, sports, transport, security) -.01973 .05691 .729 Field of study Mean Difference Standard Error p Agriculture and Veterinary Medicine Other (please specify) -.21224* .05733 .000 Education -.20099* .07004 .004 Arts and Humanities -.31029* .05921 .000 Social Sciences, Business and Law -.31382* .05579 .000 Natural and Life Sciences -.12108 .06443 .060 Engineering, Manufacturing and construction -.20693* .05624 .000 Health and welfare -.04922 .05639 .383 Services (tourism, sports, transport, security) -.22666* .07181 .002 Health and Welfare Other (please specify) -.16301* .03722 .000 Education -.15177* .05481 .006 Arts and Humanities -.26106* .04006 .000 Social Sciences, Business and Law -.26459* .03480 .000 Natural and Life Sciences -.07185 .04743 .130 Engineering, Manufacturing and construction -.15771* .03552 .000 Agriculture and veterinary medicine .04922 .05639 .383 Services (tourism, sports, trans- port, security) -.17744* .05706 .002 Services (tourism, sports, transport, security) Other (please specify) .01442 .05799 .804 Education .02567 .07058 .716 Arts and Humanities -.08362 .05985 .162 Social Sciences, Business and Law -.08716 .05646 .123 Natural and Life Sciences .10559 .06502 .104 Engineering, Manufacturing and construction .01973 .05691 .729 Agriculture and veterinary medicine .22666* .07181 .002 Health and welfare .17744* .05706 .002 * The mean difference is statistically significant at p<0.05 Appendix | 5554 | Appendix Table 32. Differences in students’ satisfaction with teaching and administration in relation to the year of study Year of study Mean Difference Standard Error p Other (please specify) Undergraduate year 1 -.04714 .04886 .335 Undergraduate year 2 -.04331 .04955 .382 Undergraduate year 3 -.02433 .05032 .629 Undergraduate year 4 .03635 .05935 .540 Master’s year 1 -.23124* .05453 .000 Master’s year 2 -.16015* .06586 .015 Undergraduate year 1 Other (please specify) .04714 .04886 .335 Undergraduate year 2 .00383 .02948 .897 Undergraduate year 3 .02282 .03076 .458 Undergraduate year 4 .08349 .04401 .058 Master’s year 1 -.18409* .03725 .000 Master’s year 2 -.11301* .05246 .031 Other (please specify) .04331 .04955 .382 Undergraduate year 1 -.00383 .02948 .897 Undergraduate year 2 Undergraduate year 3 .01899 .03185 .551 Undergraduate year 4 .07966 .04477 .075 Master’s year 1 -.18792* .03815 .000 Master’s year 2 -.11684* .05311 .028 Undergraduate year 3 Other (please specify) .02433 .05032 .629 Undergraduate year 1 -.02282 .03076 .458 Undergraduate year 2 -.01899 .03185 .551 Undergraduate year 4 .06067 .04562 .184 Master’s year 1 -.20691* .03915 .000 Master’s year 2 -.13582* .05383 .012 Undergraduate year 4 Other (please specify) -.03635 .05935 .540 Undergraduate year 1 -.08349 .04401 .058 Undergraduate year 2 -.07966 .04477 .075 Undergraduate year 3 -.06067 .04562 .184 Master’s year 1 -.26758* .05023 .000 Master’s year 2 -.19650* .06235 .002 Year of study Mean Difference Standard Error p Master’s year 1 Other (please specify) .23124* .05453 .000 Undergraduate year 1 .18409* .03725 .000 Undergraduate year 2 .18792* .03815 .000 Undergraduate year 3 .20691* .03915 .000 Undergraduate year 4 .26758* .05023 .000 Master’s year 2 .07108 .05778 .219 Master’s year 2 Other (please specify) .16015* .06586 .015 Undergraduate year 1 .11301* .05246 .031 Undergraduate year 2 .11684* .05311 .028 Undergraduate year 3 .13582* .05383 .012 Undergraduate year 4 .19650* .06235 .002 Master’s year 1 -.07108 .05778 .219 Table 33. Differences in students’ satisfaction with teaching and administration in relation to their accommodation Accommodation Mean Difference Standard Error p Other (please specify) Family home .04585 .06400 .474 Rented accommodation .14705* .06914 .033 Student hall/dorm .06031 .07855 .443 Family home Other (please specify) -.04585 .06400 .474 Rented accommodation .10120* .03107 .001 Student hall/dorm .01446 .04853 .766 Rented accommodation Other (please specify) -.14705* .06914 .033 Family home -.10120* .03107 .001 Student hall/dorm -.08674 .05513 .116 Student hall/dorm Other (please specify) -.06031 .07855 .443 Family home -.01446 .04853 .766 Rented accommodation .08674 .05513 .116 * The mean difference is statistically significant at p<0.05 Appendix | 5756 | Appendix Table 34. Differences in students’ perceived drop in academic performance in relation to the year of study Year of study Mean Difference Standard Error p Other (please specify) Undergraduate year 1 -.13796* .05777 .017 Undergraduate year 2 -.12271* .05860 .036 Undergraduate year 3 -.06255 .05953 .293 Undergraduate year 4 -.06078 .07041 .388 Master’s year 1 .06704 .06457 .299 Master’s year 2 .01270 .07836 .871 Undergraduate year 1 Other (please specify) .13796* .05777 .017 Undergraduate year 2 .01525 .03482 .661 Undergraduate year 3 .07541* .03637 .038 Undergraduate year 4 .07718 .05231 .140 Master’s year 1 .20500* .04413 .000 Master’s year 2 .15066* .06260 .016 Undergraduate year 2 Other (please specify) .12271* .05860 .036 Undergraduate year 1 -.01525 .03482 .661 Undergraduate year 3 .06016 .03767 .110 Undergraduate year 4 .06193 .05323 .245 Master’s year 1 .18975* .04521 .000 Master’s year 2 .13541* .06336 .033 Undergraduate year 3 Other (please specify) .06255 .05953 .293 Undergraduate year 1 -.07541* .03637 .038 Undergraduate year 2 -.06016 .03767 .110 Undergraduate year 4 .00178 .05425 .974 Master’s year 1 .12960* .04642 .005 Master’s year 2 .07526 .06423 .241 Undergraduate year 4 Other (please specify) .06078 .07041 .388 Undergraduate year 1 -.07718 .05231 .140 Undergraduate year 2 -.06193 .05323 .245 Undergraduate year 3 -.00178 .05425 .974 Master’s year 1 .12782* .05974 .032 Master’s year 2 .07348 .07443 .324 Year of study Mean Difference Standard Error p Master’s year 1 Other (please specify) -.06704 .06457 .299 Undergraduate year 1 -.20500* .04413 .000 Undergraduate year 2 -.18975* .04521 .000 Undergraduate year 3 -.12960* .04642 .005 Undergraduate year 4 -.12782* .05974 .032 Master’s year 2 -.05434 .06892 .430 Master’s year 2 Other (please specify) -.01270 .07836 .871 Undergraduate year 1 -.15066* .06260 .016 Undergraduate year 2 -.13541* .06336 .033 Undergraduate year 3 -.07526 .06423 .241 Undergraduate year 4 -.07348 .07443 .324 Master’s year 1 .05434 .06892 .430 * The mean difference is statistically significant at p<0.05 Appendix | 6362 | Appendix Year of study Mean Difference Standard Error p Master’s year 1 Other (please specify) .07328 .05206 .159 Undergraduate year 1 .28485* .03551 .000 Undergraduate year 2 .25765* .03637 .000 Undergraduate year 3 .14558* .03738 .000 Undergraduate year 4 .19673* .04812 .000 Master’s year 2 -.03591 .05545 .517 Master’s year 2 Other (please specify) .10918 .06315 .084 Undergraduate year 1 .32076* .05038 .000 Undergraduate year 2 .29356* .05099 .000 Undergraduate year 3 .18149* .05172 .000 Undergraduate year 4 .23264* .05994 .000 Master’s year 1 .03591 .05545 .517 Table 37. Differences in students’ general well-being in relation to field of study Field of study Mean Difference Standard Error p Other (please specify) Education .04189 .05149 .416 Arts and Humanities .19346* .03816 .000 Social Sciences, Business and Law -.00123 .03344 .971 Natural and Life Sciences .00186 .04456 .967 Engineering, Manufacturing and construction -.07226* .03408 .034 Agriculture and veterinary medicine -.06174 .05281 .242 Health and welfare -.03022 .03427 .378 Services (tourism, sports, transport, security) -.14438* .05322 .007 Education Other (please specify) -.04189 .05149 .416 Arts and Humanities .15157* .05331 .004 Social Sciences, Business and Law -.04311 .05004 .389 Natural and Life Sciences -.04003 .05806 .491 Engineering, Manufacturing and construction -.11414* .05047 .024 Agriculture and veterinary medicine -.10363 .06461 .109 Health and welfare -.07211 .05059 .154 Services (tourism, sports, transport, security) -.18627* .06494 .004 Field of study Mean Difference Standard Error p Arts and Humanities Other (please specify) -.19346* .03816 .000 Education -.15157* .05331 .004 Social Sciences, Business and Law -.19469* .03617 .000 Natural and Life Sciences -.19160* .04664 .000 Engineering, Manufacturing and construction -.26571* .03676 .000 Agriculture and veterinary medicine -.25520* .05458 .000 Health and welfare -.22368* .03693 .000 Services (tourism, sports, transport, security) -.33784* .05497 .000 Social Sciences, Business and Law Other (please specify) .00123 .03344 .971 Education .04311 .05004 .389 Arts and Humanities .19469* .03617 .000 Natural and Life Sciences .00309 .04287 .943 Engineering, Manufacturing and construction -.07103* .03183 .026 Agriculture and veterinary medicine -.06052 .05139 .239 Health and welfare -.02900 .03204 .365 Services (tourism, sports, transport, security) -.14315* .05181 .006 Natural and Life Sciences Other (please specify) -.00186 .04456 .967 Education .04003 .05806 .491 Arts and Humanities .19160* .04664 .000 Social Sciences, Business and Law -.00309 .04287 .943 Engineering, Manufacturing and construction -.07412 .04337 .088 Agriculture and veterinary medicine -.06360 .05923 .283 Health and welfare -.03208 .04352 .461 Services (tourism, sports, transport, security) -.14624* .05960 .014 Appendix | 6564 | Appendix Field of study Mean Difference Standard Error p Engineering, Manufacturing and Construction Other (please specify) .07226* .03408 .034 Education .11414* .05047 .024 Arts and Humanities .26571* .03676 .000 Social Sciences, Business and Law .07103* .03183 .026 Natural and Life Sciences .07412 .04337 .088 Agriculture and veterinary medicine .01051 .05181 .839 Health and welfare .04203 .03270 .199 Services (tourism, sports, transport, security) -.07212 .05222 .167 Agriculture and Veterinary Medicine Other (please specify) .06174 .05281 .242 Education .10363 .06461 .109 Arts and Humanities .25520* .05458 .000 Social Sciences, Business and Law .06052 .05139 .239 Natural and Life Sciences .06360 .05923 .283 Engineering, Manufacturing and construction -.01051 .05181 .839 Health and welfare .03152 .05194 .544 Services (tourism, sports, transport, security) -.08263 .06599 .211 Health and Welfare Other (please specify) .03022 .03427 .378 Education .07211 .05059 .154 Arts and Humanities .22368* .03693 .000 Social Sciences, Business and Law .02900 .03204 .365 Natural and Life Sciences .03208 .04352 .461 Engineering, Manufacturing and construction -.04203 .03270 .199 Agriculture and veterinary medicine -.03152 .05194 .544 Services (tourism, sports, transport, security) -.11416* .05235 .029 * The mean difference is statistically significant at p<0.05 Field of study Mean Difference Standard Error p Services (tourism, sports, transport, security) Other (please specify) .14438* .05322 .007 Education .18627* .06494 .004 Arts and Humanities .33784* .05497 .000 Social Sciences, Business and Law .14315* .05181 .006 Natural and Life Sciences .14624* .05960 .014 Engineering, Manufacturing and construction .07212 .05222 .167 Agriculture and veterinary medicine .08263 .06599 .211 Health and welfare .11416* .05235 .029 Table 38. Differences in students’ self-efficacy in relation to the year of study Year of study Mean Difference Standard Error p Other (please specify) Undergraduate year 1 .10958* .04472 .014 Undergraduate year 2 .14735* .04536 .001 Undergraduate year 3 .03961 .04606 .390 Undergraduate year 4 -.00624 .05443 .909 Master’s year 1 -.03888 .05007 .437 Master’s year 2 -.01741 .06022 .772 Undergraduate year 1 Other (please specify) -.10958* .04472 .014 Undergraduate year 2 .03777 .02711 .164 Undergraduate year 3 -.06997* .02826 .013 Undergraduate year 4 -.11582* .04049 .004 Master’s year 1 -.14846* .03441 .000 Master’s year 2 -.12699* .04800 .008 Other (please specify) -.14735* .04536 .001 Undergraduate year 1 -.03777 .02711 .164 Undergraduate year 2 Undergraduate year 3 -.10774* .02927 .000 Undergraduate year 4 -.15358* .04120 .000 Master’s year 1 -.18623* .03524 .000 Master’s year 2 -.16476* .04860 .001 Appendix | 6766 | Appendix * The mean difference is statistically significant at p<0.05 Year of study Mean Difference Standard Error p Undergraduate year 3 Other (please specify) -.03961 .04606 .390 Undergraduate year 1 .06997* .02826 .013 Undergraduate year 2 .10774* .02927 .000 Undergraduate year 4 -.04585 .04197 .275 Master’s year 1 -.07849* .03613 .030 Master’s year 2 -.05702 .04925 .247 Undergraduate year 4 Other (please specify) .00624 .05443 .909 Undergraduate year 1 .11582* .04049 .004 Undergraduate year 2 .15358* .04120 .000 Undergraduate year 3 .04585 .04197 .275 Master’s year 1 -.03264 .04633 .481 Master’s year 2 -.01117 .05715 .845 Master’s year 1 Other (please specify) .03888 .05007 .437 Undergraduate year 1 .14846* .03441 .000 Undergraduate year 2 .18623* .03524 .000 Undergraduate year 3 .07849* .03613 .030 Undergraduate year 4 .03264 .04633 .481 Master’s year 2 .02147 .05302 .685 Master’s year 2 Other (please specify) .01741 .06022 .772 Undergraduate year 1 .12699* .04800 .008 Undergraduate year 2 .16476* .04860 .001 Undergraduate year 3 .05702 .04925 .247 Undergraduate year 4 .01117 .05715 .845 Master’s year 1 -.02147 .05302 .685 Table 39. Main points raised in answers to open questions Advantages to on-line studying Disadvantages to on-line studying Problems with on-line studying Recommendations Flexible schedule, autonomy to plan one’s own time Studying from home is not “real studying” Not feeling motivated, procrastination y Returning to campus, to studying on-site y If on-line, teaching resembling as much as possible on-site lectures (video calls in real-time) y Lighter workload y Clear lecturer instructions y Understanding and support shown by university staff (administrative and academic) with regard to new studying conditions y Good Internet connection y Good quality computers y One online platform for the course More time for studying; more time for sleeping Monotonous, repetitiveness of everyday life, having to be in front of the computer all day long Lower living costs Money and time is saved by not having to travel to one’s department Lack of practical classes Increase in workload (lecturers compensating for lack of on-site teaching) Lack of close interaction with colleagues and friends Independent learning more difficult Lack of close interaction with university staff Independent learning more difficult, less opportunity for clarification by lecturers Family time too intense Studying more difficult for those with parenting re- sponsibilities and from larger families (quiet time a challenge) Being at home with one’s family The comfort and safety of the family home Healthier diet Lack of infrastructure: not having one’s room, study materials not available Poor internet connec- tion, inability to access library resources Less stressful Lack of infrastructure: frustration with a poor Internet connection