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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
Introduction
It is believed that increasing class attendance enhances class engagement and success (Moores,
Birdi and Higson, 2019; Wongtrakul and Dangprapai, 2020). Hence, minimum attendance requirement
to classes is mandatory in most universities. While some studies support this fact, some studies have
concluded that attendance does not affect course success (Gomis-Porqueras and Rodrigues-Neto,
2018; Kaushik, Kumar and Kumar, 2021). Even if the students physically attend the lessons, they may
not provide behavior engagement, emotional engagement, and cognitive engagement, which are three
dimensions of class engagement (Hu and Li, 2017; Qiping Kong, 2003). Compulsory attendance to the
course may lead the students to attend the course without listening to the course, such as surng the
internet, and so this does not contribute to their success (Nieuwoudt, 2020). Kaushik, Kumar and Kumar
(2021), stating that compulsory attendance may hinder academic success, dened the reasons for this as
students wasting the interval when the course intervals are long, spending too much time on their way to
and from school, and thinking that asynchronous courses would be sufcient for some courses. Some of
these reasons do not apply to distance education. Because in online education, time is not spent going to
school; the students can watch the lectures anywhere and anytime they want. So the effects of physical
attendance on success can be different for online courses.
So far, the comparison of live and recorded lecture viewing is mostly about students’ preferences,
and studies measuring their effects on academic achievement are limited (Islam, Kim and Kwon, 2020;
Howard, Meehan and Parnell, 2018; Trenholm, Alcock and Robinson, 2012; Nieuwoudt, 2020; Kahui et
al., 2022; Le, 2022). In addition, generally studies in literature are limited mostly with schools or lectures.
We want to evaluate student live and recorded course viewings, which are very important parts of the
distance education system, especially in the Covid-19 period. We hope that this study will be benecial
for policy makers, education system developers and educators interested in online lesson viewings in
Online Course Viewings and Their Effects on Performances in Covid-19
Distance Education Period
Erdem Demir
1
, Çağla Ediz
1*
, Aykut Hamit Turan
1
Management Information Systems, Sakarya University, Sakarya, Turkey,
e-mail: erdem.demir@skampus365.com, cediz@sakarya.edu.tr, ahturan@sakarya.edu.tr
Abstract: Despite numerous studies examining student preferences in terms of live and recorded lecture viewings,
the effects of lesson viewings on online platforms have been limitedly studied. In this study, the rates of attending live lectures
and viewing lecture recordings in the Covid-19 era were examined, and attendance and viewings effects on nal scores in
these courses were evaluated. For this purpose, data from online education systems of live and record viewings for Turkish
Literature, mathematics, and biostatistics classes in the spring semester of 2021-2022, belonging to 13 Turkish universities
and 2082 students, were utilized. We found that (1) Thirteen percent of the students did not view any live or recorded courses,
and approximately one-third did not enter the nal exam; (2) The students in state universities have signicantly higher record
viewing rates than those in private universities with medium effect size, (3) Females present signicantly higher live viewings and
record viewing rates than males with small effect sizes; (4) Biostatistics has moderate-high correlations between viewing rates
and nal scores. On the other hand, there are no or weak relationships between the viewing rates and nal scores for Turkish
literature and mathematics, in which study materials can be widely accessed from many sources different from biostatistics.
Keywords: distance education, nal scores, live lecture attendance, recorded lecture viewing.
Original scientic paper
Received: March, 12.2023.
Revised: May, 12.2023.
Accepted: May, 24.2023.
UDC:
37.018.43:159.953.072(560)”2021/2022”
10.23947/2334-8496-2023-11-2-247-255
© 2023 by the authors. This article is an open access article distributed under the terms and conditions of the
Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
*
Corresponding author: cediz@sakarya.edu.tr
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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
universities’ distance education. This study is important for the evaluation of selected three courses in
13 universities. First we have seen that in the literature (For example: Shahabadi and Uplane, 2015),
students have different perspectives for synchronized and recorded lectures. Hence, we classied our
viewed classes in two classes as synchronized and live lectures. Existing studies indicated that based on
gender, there would be some differences in distance education as well (Gupta and Saks, 2013; Kahui et
al., 2022). Hence, we created a category for gender. On the other hand, we have not come up with any
literature regarding the differences in public and private university students’ interests in viewing the online
lectures. In order to provide support to the literature, we also investigated public and private university
difference in our study. Finally, whether students attend the nal or not was the third category in our study.
We also investigated the participants online class participation in all these categories specically for Covid
19 period. Hence, we propose the following hypothesis.
RQ1- What are the rates of viewings (live & record) and entering nal exams of the students in the
Covid-19 in Turkey?
RQ2- Are there any signicant differences between viewings (live & record) based on gender,
university type, and nal taking tendency?
RQ3- Are there signicant relations between viewings (live & record) and nal scores?
The remain of this study continues with literature review. In the third section of this study, download
and data preparation processes are explained. In the fourth section, analyzes and ndings are provided.
In this section, rst of all, descriptive statistics about lesson viewings, and the distribution of student
lecture viewings and entering the nal exam are given. Afterward, we investigated whether there were
signicant differences in lesson viewings according to gender, type of university, and entering the nal
exam. Later, it was investigated whether the lectures’ viewing rates had an effect on nal scores. In the
last section, the ndings were also elaborated.
Literature Review
With Covid-19, face-to-face teaching was suspended in schools to a large extent, and distance
education decisions were taken not to interrupt education during this period. Universities in Turkey also
followed this suit and carried out the 2020-2021 spring academic period with online courses to prevent
the risk of Covid-19 contamination in the classroom environment and to ensure the continuation of the
education. In distance education, teachers and students work on educational materials in different places
and sometimes at different times (Gunawardena and McIsaac, 2013). Distance education, which was
previously carried out through channels such as radio and television, continues with web-based training
widely with the development of information technology and the spread of the Internet. Web-based online
courses can be given as synchronously or asynchronously. While synchronous education offers the
opportunity to interact between the teacher and the student, asynchronous education offers the option
of using course records that can be watched at any time by adjusting the video speed and moving back
and forth. When these educations with different advantages are compared, students generally preferred
recorded video lectures to live lectures (Islam, Kim and Kwon, 2020; Howard, Meehan and Parnell, 2018;
Trenholm, Alcock and Robinson, 2012). However, students stated that they still attach importance to live
lectures for existence of sense of community and quick feedback (Trenholm, Alcock and Robinson, 2012).
Motivations and cognitive strategies affect students’ decision whether to attend the courses face-to-face
or online (Bassili, 2008; McKenna and Kopittke, 2018). Since most students consider the interaction in
face-to-face courses important, they continue to attend the lessons even though online accessible class
records are uploaded to the system (Yoon, Oates and Sneddon, 2014; Fei et al., 2013; Gysbers et al.,
2011; Alamer and Alharbi, 2021). For example, only 58 per cent of university students, who can take
distance or face-to-face education, preferred and participated in face-to-face education, and less than
15 per cent of those who did not take the any preference to downloaded courses, yet did not watch them
(McKenna and Kopittke, 2018).
At the beginning of the Covid-19 period in Turkey, students stated that both theoretical and
practical courses would be insufcient with distance education. They did not think of suspending study,
but thought that the school time would be extended (Kursuncu and Kurt, 2020). Although the students did
not encounter any technical problems in the distance exams, they stated that they were worried because
they would deal with power cuts and internet connection problems before the exam (Ilgaz and Afacan
Adanır, 2020). Different results were obtained to student satisfaction in the studies conducted during the
Covid period. In a survey evaluating the distance education of undergraduate dentistry students in Turkey
during pandemic, students complained that practical training could not be given online and the lectures
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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
were inefcient (Cirakoglu and Ozbay, 2022). On the other hand, Tayem et al. (2022) reported that most
of the students were satised with distance education and would prefer the theoretical courses to be
given remotely and the practical courses to be given face-to-face. With a similar inference, educators who
give anatomy education think that the loss of quality experienced in the distance teaching in theoretical
courses will be less than that of distance practical courses (Ozen, Erdoğan and Malas, 2022). For some
courses, distance education can be as effective as traditional education, if it is supported by simultaneous
education (Alamer and Alharbi, 2021). In the distance education system, it was observed that especially
male students were more satised and found the lectures more effective and exible (Buluk and Equalti,
2020; Turan, Kucuk and Cilligol Karabey, 2022). In another survey conducted with undergraduate
students, students stated that they were provided time exibility and course content exibility in distance
education. Yet, student satisfaction was generally low because of the complexity of teaching materials
(Turan, Kucuk and Cilligol Karabey, 2022). On the other hand, in Nieuwoudt’s study, it is found that
viewing live lectures or watching videos of course recordings can have the same effect as face-to-face
education. It is emphasized that there may be different reasons for students not attending the live courses
in distance education, therefore they should be given the right to attend the course by watching the lecture
records (Nieuwoudt, 2020).
Data Preprocessing
ALMS is one of the two most used learning management systems in Turkey (Durak, Çankaya and
İzmirli, 2020). The system records data of the students and teachers in order to measure the efciency of
their online activities. To examine the course viewing rates of students and their effects on their success
in the 2020-2021 spring semester of Covid period, we selected the courses that are commonly given in
different departments of universities. We preferred these courses to be in different categories: numerical,
verbal, and departmental. These courses were mathematics, Turkish literature and biostatistics. We
downloaded the records of these courses given in 13 different universities and 21 different departments.
We ltered the dataset in such a way that the names of the courses included as mathematics, Turkish
literature, biostatistics, or the words with the same meaning as them, such as calculus. In addition, we
have removed the courses that evaluate the nal of the courses as homework from the dataset. All
characters in the downloaded dataset texts are converted to lowercase. Since some of the gender data of
the users was missing from the database, the missing places were added manually.
Each lecture recorded by the teachers in the dataset is added to the system as a separate record
for each student. These records include student times of viewing live lectures. Viewing recorded lectures
are assigned as zero at rst. As viewing activities of students’ change, these values are altered. We
summed students’ live attendance times and also summed up their replay (record viewing) times for each
lecture and saved them in a new database. So in the new database, there was a single record for each
student-lecture. In addition, we summed the recording times of the teacher in the live lectures for each
lecture during 14-weeks and we found the total live time for each lecture. In some lectures, we observed
that the live lectures were not given, instead, the videos uploaded or recorded by the teacher to the system
were watched. We removed these course records from the prepared dataset. Afterward, we divided the
total live viewing time and the total record viewing time of the courses by the total recording time of the
live lectures and multiplied by 100 (1, 2). So we normalized the viewings by replacing them with their
percentages. These records were joined on the dataset containing the nal scores of the students where
student numbers and course numbers were equal, and the data set preparation process was completed.
Live Attendance (%)= ∑Live Viewing Time / ∑Live Lecture Time x 100 (1)
Record Viewing Rate= ∑Record Viewing Time/∑Live Lecture Time x 100 (2)
Analyzes and Findings
Descriptive Analyses with Student Rates of Viewing Lessons and Entering
Final
There are 2082 records in the prepared dataset. In this prepared dataset, the numbers of records
for mathematics, Turkish literature, and biostatistics are respectively; 251, 1277 and 604. While the
numbers of females and males are 1374 and 708, respectively, there are 1434 state, 648 private university
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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
students. At the end of the semester, 1410 of the 2082 students entered the nal exam, 672 of them did
not. All variables are not normally distributed. The average percentage of viewing for live lectures is 28.1
per cent and for viewing recorded lectures’ range is 46.4. The highest average viewings, belonging to
biostatistics, female, state schools’ courses and students entered the nal are presented below (Table 1).
Table 1
Descriptive Statistics
We want to investigate students’ attention to the online lectures. To evaluate this, we examined
viewing and entering nal rates. We observed that,13,4 per cent of the students did not attend any live
classes in the chosen courses and did not view any video lectures (Table 2). The percentage of students
in private universities not viewing any lectures is the highest with 32.25 per cent. In the Turkish literature
course, 19.8 per cent of the students did not view any lecture. On the other hand, biostatistics has the
lowest percentages of not to watch course with 2.48 per cent. One third of the students approximately
(32.28 per cent), did not enter the nal. 251 of 708 (35.45 per cent) male students, 421 of 1374 (30.64
per cent) female students, 326 of the 1434 (24.73 per cent) state university students, and 346 of the 648
(53.4 per cent) private university students did not take the nal exam (Table 2).
Table 2
Rates of students who didn’t watched any online classes and did not enter the nals
Differences Analyses
We want to analyze differences for viewing rates with different features. These features are male
and female, type of universities as state and private universities, entering nal exam and not entering nal
exam. Each student attends only one course in the dataset, so each record is independent from the other
courses and the data values in each group are nonparametric. Thus, we applied the Mann-Whitney U
Test for all to see if there was a signicant difference between two groups in live attendance rates (record
viewing rates).
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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
H1: There is a signicant difference between male and female students’ live attendances.
H2: There is a signicant difference between male and female students’ record viewings.
H3: There is a signicant difference between state and private university students’ live attendances.
H4: There is a signicant difference between state and private university students’ record viewings.
H5: There is a signicant difference between the students’ who taking nal and who the students’
not taking nal live attendances.
H6: There is a signicant difference between the students’ who taking nal and who the students’
not taking nal students’ record viewings.
We evaluated the signicance level at the 0.01 value and we calculated the effect sizes (r) of
through division of Z on N square (Corder and Foreman, 2009) for signicant tests. It was seen that the
group with the most different viewing rates, with a medium effect size (r=- 0.371), was between state
and private university students’ record viewings (Table 3). That is, the rate of record viewings of students
at state universities (15.70) is signicantly higher than those at private universities (0.13) (U=250635,
p=0.00). Also, the percentage of female students’ live attendance (24.23 per cent) is signicantly higher
than the percentage of male students’ live attendance (10.64 per cent) (U=403653, p=0.00). Likewise,
the rate of female students’ record viewing (11.945) is signicantly higher than the record viewing rates of
male students (3.195) (U=414842, p=0.00). However, the effect sizes of gender differences for both live
and record viewings are small (r=-0.141 and -0.121sequentially). While there is a signicant difference
between state university students (18.49) and private university students in the live viewing, the effect size
of this difference is also small (r=-0.06). On the other hand, there are no signicant differences between
the rates of those who took the nal and those did not take the nal in both live and record viewings.
Table 3
Evaluation of the differences in viewing percentages between Female-Male, State-Private, and
Taking Exam-Not Taking Exam
Correlations Between Final Scores and Viewings
For Turkish literature, biostatistics, and mathematics courses, we desired to examine the
relationships between online course viewings and students’ performances. For the evaluation of student
performance, the nal exam grades entered by the students at the end of the semester and were taken
as a basis, and the data of the students who did not participate the nal were excluded from the analysis.
H7: There is a relationship between the live viewing rates and Turkish Literature nal scores.
H8: There is a relationship between the record viewing rates and Turkish Literature nal scores.
H9: There is a relationship between the live viewing rates and biostatistics nal scores.
H10: There is a relationship between the record viewing rates and biostatistics nal scores.
H11: There is a relationship between the live viewing rates and mathematics nal scores.
H12: There is a relationship between the record viewing rates and mathematics nal scores.
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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
When the data of the students who took the nal exam were ltered, and the distributions of live
viewing and recording of the Turkish literature, biostatistics, and mathematics courses were examined,
we have seen that all distributions did not t with the normal distribution (Table 1). Hence, Spearman’s
Correlation method was run to see the relations. The highest correlation is found, as 0.665 at a 0.01
signicant level, between biostatistics live viewings and nal scores (Table 4). The second highest
correlation is 0.1962, also between the biostatistics course live viewings and the record viewing rates, at
a 0.01 signicant level. Mathematics’ nal scores have no signicant correlation with live viewings, but
a positive low correlation (r= 0.1885) with record viewings. For Turkish literature course, there are again
low, but positive (r=0.1164) correlations between nal scores and live attendance rates and negative
correlations (r=-0.1128) between nal scores and record viewing rates.
Table 4
The correlations between the rates of (live-record) viewing and nal scores for the students who
entered the nal
Discussion and Conclusion
The average live and record viewing rate values, which are found to be 28.1 per cent and 46.4
respectively. These values present that attendances to lectures in Turkish universities are low during the
pandemic period. A signicant number of students (13.4 per cent) have never attended any live lecture
and watched any recording lecture. A similar conclusion is also reached in the study belongs to the
beginning period of Covid19 for Turkey. Can (2020) concluded that the course data for ve courses
in the rst weeks of distance education due to the pandemic in Turkey (23 March 2020-07 April 2020)
and students’ participation in live virtual classrooms and record viewing rates are low. Students mainly
preferred access to written materials and course presentations during this period (Can, 2020). Before the
pandemic, universities in Turkey required attendance to classes based on the institutional requirements
and regulations, and students who did not achieve a certain attendance rate would fail the class. Since
the sudden transition to distance education during the Covid-19 period could cause problems on an
institutional and individual basis, this obligation was suspended in Turkey. However, in countries where
attendance is mandatory, during Covid 19 pandemic, the online class attendances are observed to be low
as well. For example, although dentistry students attending a prosthetics course in China must attend 95
per cent of the lectures to pass the course in Covid-19 period, about a third of the students did not attend
almost any lecture, and half of them attended only 10 per cent of the lectures (Yang et al., 2021). Similarly,
in New Zeland during 2020 lockdown period because of Covid 19, 34 per cent of students did not view
any live or recorded lectures (Kahui, 2022). This may indicate the existence of some technical, social, or
cultural difculties for countries in distance education. Lack of strong telecommunication infrastructure,
inability to abandon cultural habits, insufcient technical personnel, and nancial reasons can be seen as
the main problems encountered in distance education to be overcome (Mirza and Al-Abdulkareem, 2011;
Basha, Hussein and Maklad, 2021).
When females and males are compared in terms of both live and record viewing rates in Turkey
during the Covid 19 period, it is seen that females’ viewing rates are signicantly higher than those of
males. But these differences have low effect size (r=-0.141 and r=-0121 for live and record viewings
sequentially) and variables don’t explain each other very well (Table 3). In Kahui, Kumar and Kumar
(2020) study for Covid 19 lockdown, New Zealand’s students attended only 20 to 23 per cent of the live
lectures, and this gure is three times higher for females than males. On the other hand, in 2013 study
of medical students found that while females attended more live lectures than males, they viewed fewer
recorded lectures (Gupta and Saks, 2013). Yet, the widespread use of computers may have probably
increased women’s ability to access and use computers since then.
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Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
Our results also indicate that approximately one-third (32.28 per cent) of the students didn’t take
the nal in the spring semester of 2021-2022 semester (Table 2). More than half of the private university
students did not take their nal exams (53.4 per cent), and in state universities, we saw that this ratio is
somewhat lower (22.73 per cent),(Table 2). We couldn’t nd a signicant relationship between students’
live classes attendance and taking nal exams. Similarly, we couldn’t nd a signicant relationship either
between students taking their nal exams and recorded lecture viewings (Table 3). This is surprising and
why students do not take the exam is an issue that needs to be investigated. We may think that some
students did not intend to fail some classes, do their viewings normally like other students, and yet at
the end of the semester, prefer not to take their nal exams. Biostatistics is the class, the highest ratio of
students missed nal exam (53.4 per cent), at the same time has the highest ratio of live attendance (32.5
per cent) and recorded lecture viewings (54.3 per cent). We may conclude here that although students
largely viewed live and recorded classes, since some students did not understand the lectures, they
preferred not to take the nal exam.
Another remarkable result is that, in state and private universities, students’ lecture records viewing
have differentiated as middle effect (r = -0.371) in viewing class recordings (Table 3). The median value
of recorded lecture viewings in private universities is close to zero (0.13). The issue of why students
in private universities in Turkey do not watch recorded lectures despite their participation in live online
lectures also needs to be studied and understood.
In mathematics and Turkish literature classes, zero to low correlations were found between live/
recorded viewings and nal scores (Table 4). Similar results were obtained for 31 students, enrolling
in the “Volcanology and Geohazards” course at the University of Liverpool. In that study, no positive or
negative relationship was observed between live and recorded viewing rates and performances (Jones,
2022). Therefore, the authors think that instead of observing these statistics, it would be better to invest in
systems where students can monitor active participation, such as answering questions in live lessons. In
addition, the author also states that students who know that statistics such as clicks and page refreshes are
measured may be inclined to cheat the system. With new technologies such as the use of face recognition
systems may students’ entry into the system be controlled in the future (Ozdemir and Ugur, 2021),
but these technologies have not become widespread yet. On the other hand, in the bio-statistics course,
which has more limited learning resources, a moderate-high correlation was found between students’
viewings and nal scores. For the biostatistics course, live viewings have a much more signicant impact
on nal grades than recorded lecture viewings. Le (2022), in his study, compared the academic success
of those who watch only live lectures with those who watch only video lectures, and similarly, she found
that those who watch live lectures become more successful. We observed from the results that for the
Turkish literature course also, online live attendance has a higher effect on the nal score than the record
viewing rate. The low correlations in mathematics and Turkish literature courses could be because these
courses are taught as a repetition of the similar courses in high school, and the content of these courses
can be accessed from different sources easily.
When the survey studies between January 2000 and May 2021 were examined, teachers evaluated
their digital competence as low or medium-low and admitted that they did not have some competence
in educational practices (Basilotta-Gómez-Pablos, 2022). The highest negative factor among teachers
in distance education was evaluated as the difculty in preparing the lesson technically and attracting
the attention of the student (Sorochinsky, 2021). More frequent and effective use of distance educational
systems’ features such as polls, chats, breakout rooms, and giving extra time to gather their courage after
questions asked can enable students to participate more actively in the lesson (Nichols et al., 2022). It
will be also benecial for scientists, psychologists, game developers, teachers and software developers
to work together in order to increase students’ active participation in classes and teaching achievements
in future.
Acknowledgements
We thank Advancity Company for allowing their data to be used and shared in scientic studies.
Conict of interests
The authors declare no conict of interest.
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254
Demir, E., Ediz, Ç, & Turan, A. H. (2023). Online course viewings and their effects on performances in Covid-19 distance
education period, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 11(2), 247-
255.
Author Contributions
Conceptualization, E.D. and Ç.E.; resources, E.D.; methodology, E.D. and Ç.E.; software, E.D.;
formal analysis, E.D. and Ç.E; supervision, A.H.T.; writing—original draft preparation, E.D. and Ç.E;
writing—review and editing, Ç.E. and A.H.T. All authors have read and agreed to the published version of
the manuscript.
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