Introduction
Teaching and learning processes have continuously evolved with technological advances. Correspondingly, the rapid development of information and communication technologies has shaped traditional classrooms into smart learning environments. For instance, sharing learning materials online has enabled the learners to study whenever and wherever they want. Online attendance marking systems have also dramatically reduced the amount of time spent by the instructors to check their students’ attendance and thus increased the actual teaching and learning time. Moreover, the assignments or examinations can also be delivered online with appropriate instructions and feedback to support learning outside of scheduled classes. Likewise, there are many other ubiquitous combinations of pedagogical practices supported or facilitated with recent technologies.
Due to increasing number of available smart learning features, it has become indispensable to manage these features for effective and organized instructional processes. Currently, it is commonly seen that educational institutes operate their own Learning Management Systems (LMS) and provide various online smart learning features for a diverse group of students. An LMS is known as a web-based system that possesses an extensive range of pedagogical and course administration tools (Yakubu,
2019). Through these educational tools, LMS can facilitate group chats, discussions, document sharing, assignment submission, quizzes, grading and course evaluations (Bove, & A.,, & Conklin, S.,
2020). Moreover, LMS has a potential to serve students with diverse backgrounds including culture, age or gender.
Previous studies have focused on identifying various learning features of LMS that can influence students’ learning outcomes. However, it seems that the results of previous studies were controversial with inconsistent learning outcomes of the students. One possible reason can be due to the lack of thorough understanding on students’ learning preferences, needs and diverse backgrounds. As the essence of an LMS is to facilitate self-regulated learning (Douglas & Alemanne,
2007), there is a need for analyzing and understanding users’ preferences when applying LMS in educational contexts which will serve various learning needs of the students.
As such, this study aims to analyze key factors that can influence users’ preferences on LMS use and gain a deeper understanding of how to maximize the learning outcomes through LMS by considering four essential independent variables; culture, gender, age and school years. The results of this study will contribute to a successful implementation of smart learning in class.
Results
The total mean scores and standard deviations of each of the twenty design items were presented in Table
4 (
n = 166). Additionally, the mean scores and standard deviations were calculated separately for German students (
n = 83) and Spanish students (n = 83) and tabulated in Table
4. Within the ‘content management’ dimension, the highest means were observed for private storage (M = 3.82) and online whiteboard (M = 3.59). Integrated offline mode (M = 3.66) and calendar integration (M = 3.59) were revealed as the most valued items of ‘ease of use’ dimension. The dimension ‘communication within the LMS’ was calculated over 3.00 for each of its items; respectively chat system (M = 3.54), notifications (M = 3.42), discussion forum (M = 3.33) and survey feature (M = 3.24). For the last dimension of screen ‘design’, the participants mostly valued marking files/courses as their favorites (M = 3.82) and choosing a personal layout (M = 3.78).
Table 4
The mean scores and standard deviations of each of twenty items
When the mean scores of each country were considered, it is easy to see that many design items were valued differently. Thirteen items were more valued by Spanish students and seven items were more valued by German students. The higher mean score for each item was highlighted grey in Table
4. The simple mean score differences may not show the real statistically differentiating items. Therefore, the comparison tests of Mann-Whitney U tests and Kruskal Wallis H tests were run for better understanding.
First Mann-Whitney U tests were conducted for gender variable (male versus female) on twenty items of learning management system design. The only significantly differentiating item was appeared on the first item of ‘ease of use’ dimension; ‘allowing downloading multiple files’ (U = 2811.500, p = 0.037). The mean rank demonstrated that male students (mean rank = 90.55, n = 88) valued the downloading multiple files feature more than female students do (mean rank = 75.54, n = 78).
Other Mann-Whitney U tests were implemented for age variable (18–25 versus above 25) on twenty learning management system design items. The results yielded only one single significantly differentiating item which belongs to ‘communication within the LMS’ dimension; ‘survey feature’ (U = 2450.000, p = 0.023). The mean rank for ‘above 25’ group (n = 56) is higher than ‘18–25’ age group (n = 110); 94.75 and 77.77 respectively.
The last Mann-Whitney U tests were run for the country variable (Germany versus Spanish). As Table
5 demonstrates, sixteen items were significantly differentiated around country variable. Among these sixteen significantly differentiating items, only four design items’ mean ranks were higher for German students; ‘uploading assignments’, ‘accessing learning materials’, ‘learning materials are available before lectures’ and ‘simple navigation structure’. The Spanish students’ mean ranks were higher than German students for the other twelve design items; ‘comment feature’, ‘online whiteboard’, ‘private storage’, ‘easy enrollment of subject’, ‘integrated offline mod’, ‘calendar integration’, ‘chat system’, ‘discussion forum’, ‘survey feature’, ‘notifications’, ‘choose a personal design/layout’, and ‘mark files/courses as favorite’.
Table 5
The Mann-Whitney U tests results for the country variable
Content Management | Uploading assignments | 2469.000 | .001 | Germany (n = 83) | 95.25 |
Spain (n = 83) | 71.75 |
Reviewing grade | 2928.500 | .085 | Not significant |
Accessing learning materials | 1759.000 | .000 | Germany (n = 83) | 103.81 |
Spain (n = 83) | 63.19 |
Comment feature | 2268.000 | .000 | Germany (n = 83) | 69.33 |
Spain (n = 83) | 97.67 |
Online whiteboard | 1608.000 | .000 | Germany (n = 83) | 61.37 |
Spain (n = 83) | 105.63 |
Private storage | 1799.500 | .000 | Germany (n = 83) | 63.68 |
Spain (n = 83) | 103.32 |
Ease of use | Allowing downloading multiple files | 3033.000 | .167 | Not significant |
Easy enrollment of subject | 2035.500 | .000 | Germany (n = 83) | 66.52 |
Spain (n = 83) | 100.48 |
Learning materials are available before lectures | 2662.500 | .009 | Germany (n = 83) | 92.92 |
Spain (n = 83) | 74.08 |
Integrated offline mod | 2265.000 | .000 | Germany (n = 83) | 69.29 |
Spain (n = 83) | 97.71 |
Calendar integration | 1876.000 | .000 | Germany (n = 83) | 64.60 |
Spain (n = 83) | 102.40 |
Communication within the LMS | Chat system | 2322.500 | .000 | Germany (n = 83) | 69.98 |
Spain (n = 83) | 97.02 |
Discussion forum | 2314.500 | .000 | Germany (n = 83) | 69.89 |
Spain (n = 83) | 97.11 |
Survey feature | 2629.500 | .005 | Germany (n = 83) | 73.68 |
Spain (n = 83) | 93.32 |
Notifications | 2180.000 | .000 | Germany (n = 83) | 68.27 |
Spain (n = 83) | 98.73 |
Design | Simple navigation structure | 2418.000 | .001 | Germany (n = 83) | 95.87 |
Spain (n = 83) | 71.13 |
Choose a personal design/layout | 2015.000 | .000 | Germany (n = 83) | 66.28 |
Spain (n = 83) | 100.72 |
Mark files/courses as favorite | 1888.000 | .000 | Germany (n = 83) | 64.75 |
Spain (n = 83) | 102.25 |
Language selection | 3157.500 | .342 | Not significant |
Allowing access through mobile application | 3426.500 | .953 | Not significant |
The last comparison tests were conducted on the school year variable for twenty design items separately. The Kruskal Wallis H tests results unfolded eleven significantly differentiating design items around the school year variable; ‘comment feature’, ‘online whiteboard’, ‘private storage’, ‘allowing downloading multiple files’, ‘learning materials are available before lectures’, ‘calendar integration’, ‘discussion forum’, ‘survey feature’, ‘notifications’, ‘choose a personal design/layout’ and ‘mark files/courses as favorite’. Although the number of students in each school level differs from each other, the mean ranks could still be used to get a deeper understanding for school years on each design item. Table
6 shows that except ‘learning materials are available before lectures’ design items where the master students had the highest mean rank, freshman students’ mean ranks were the highest for the other ten significantly differentiating design items.
Table 6
The Kruskal Wallis H tests results for the school year variable
Content Management | Uploading assignments | Not significant |
Reviewing grade | Not significant |
Accessing learning materials | Not significant |
Comment feature | 11.780 | .019 | freshman | 44 | 100.26 |
sophomore | 28 | 87.41 |
junior | 24 | 76.88 |
senior | 23 | 61.65 |
master | 47 | 79.55 |
Online whiteboard | 14.108 | .007 | freshman | 44 | 102.36 |
sophomore | 28 | 70.98 |
junior | 24 | 66.52 |
senior | 23 | 86.35 |
master | 47 | 80.57 |
Private storage | 10.341 | .035 | freshman | 44 | 100.61 |
sophomore | 28 | 77.20 |
junior | 24 | 71.48 |
senior | 23 | 79.33 |
master | 47 | 79.41 |
Ease of use | Allowing downloading multiple files | 17.738 | .001 | freshman | 44 | 104.56 |
sophomore | 28 | 83.59 |
junior | 24 | 57.52 |
senior | 23 | 73.96 |
master | 47 | 81.67 |
Easy enrollment of subject | Not significant |
Learning materials are available before lectures | 10.781 | .029 | freshman | 44 | 85.14 |
sophomore | 28 | 66.91 |
junior | 24 | 68.23 |
senior | 23 | 87.20 |
master | 47 | 97.84 |
Integrated offline mod | Not significant |
Calendar integration | 11.774 | .019 | freshman | 44 | 102.26 |
sophomore | 28 | 73.88 |
junior | 24 | 85.23 |
senior | 23 | 73.17 |
master | 47 | 75.84 |
Communication within the LMS | Chat system | Not significant |
Discussion forum | 15.135 | .004 | freshman | 44 | 103.95 |
sophomore | 28 | 73.18 |
junior | 24 | 83.67 |
senior | 23 | 86.57 |
master | 47 | 68.91 |
Survey feature | 11.756 | .019 | freshman | 44 | 101.22 |
sophomore | 28 | 80.14 |
junior | 24 | 66.65 |
senior | 23 | 71.39 |
master | 47 | 83.45 |
Notifications | 12.566 | .014 | freshman | 44 | 103.43 |
sophomore | 28 | 76.00 |
junior | 24 | 68.98 |
senior | 23 | 81.39 |
master | 47 | 77.76 |
Design | Simple navigation structure | Not significant |
Choose a personal design/layout | 17.027 | .002 | freshman | 44 | 105.68 |
sophomore | 28 | 77.57 |
junior | 24 | 81.33 |
senior | 23 | 72.30 |
master | 47 | 72.85 |
Mark files/courses as favorite | 22.935 | .000 | freshman | 44 | 108.78 |
sophomore | 28 | 75.13 |
junior | 24 | 84.46 |
senior | 23 | 77.57 |
master | 47 | 67.23 |
Language selection | Not significant |
Allowing access through mobile application | Not significant |
Discussion and conclusion
As LMS has become a crucial element of different instructional contexts, the efforts trying to unfold its successful design factors have been studied more than ever before. The previous studies enlisted four essential success factors for LMS implementations. Therefore, this study aims to understand LMS design from a cultural point of view in additional variables of gender, age and school year. The general results clearly demonstrated that one unique LMS design will not be useful and appreciated by the students all the time. In that sense, other than setting up a commonly designed LMS on their school smart systems, the managers/instructors should prefer a more user centered approach where the LMS will be tailored according to their students’ demographics (especially the variables discussed in this study).
When German and Spanish students were compared with non-parametric statistical tests, it seemed that Spanish students generally more valued various features of LMS. In particular, Spanish students claimed that ease of use and communication within the LMS are important features for their learning. In the content management section, Spanish students also valued comment feature and online whiteboard as evident in the mean scores and the Mann-Whitney U test results. This implies that Spanish students would prefer learning through communication. Hence, the instructional designers or practitioners should offer more interactive and communicative opportunities to Spanish students on their LMS.
On the other hand, German students have put a strong emphasis on LMS features such as ‘uploading assignments’, ‘accessing learning materials’, ‘learning materials are available before lectures’ and ‘simple navigation structure’. Most of these features are directly related to the final grade and individual learning. Such different characteristics of German and Spanish students could affect their learning behaviors in a way that German students would value goal-oriented individual learning and Spanish students would value process-oriented group learning with active communication. This gives clues to the instructors while designing their instructional activities on LMS. For instance, Spanish students should be directed toward more group assignments whereas German students would appreciate more individual self-studies and exercises.
In fact, this study results are relevant to a four-dimensional model of cultural differences proposed by Hofstede (
1986). Based on Hofstede’s model, the individualism-collectivism dimension provides a possible explanation for different characteristics of German and Spanish students. As described by Mercado et al. (
2004), individualism values personal achievement or well-being of an individual, which suits with the characteristics observed from German students. On the other hand, collectivism highlights group achievement or group actions, which can match with the characteristics shown by Spanish students. These findings can also explain both countries’ different cultural dimension scores on individualism versus collectivism as mentioned in the literature review (Hofstede et al.,
2010). As German students highly valued two LMS features, ‘accessing learning materials’ and ‘learning materials are available before lectures’, it implies that German students want to be prepared for their classes. Such preparation might be related to uncertainty avoidance for what they will learn in class. If so, it will contradict the results obtained by Hofstede et al. (
2010) as Germany’s uncertainty avoidance score was lower than Spain. Therefore, the fundamental reason for accessing learning materials should be clarified to further explain such contradictory results. The remaining two cultural dimensions, power distance and masculinity, could not be related to our study results as students’ perspectives on hierarchical learning and competition-based learning were not assessed. Despite the cultural differences, it should be also noted that both groups of students similarly valued certain features of LMS such as reviewing grade, downloading multiple files, language selection, and access through mobile application. In both cultures, the LMS features related to users’ convenience seem equally important.
In this study, significant gender differences were not observed. The only difference observed was that male students valued downloading multiple files feature of LMS more than female students, which could mean male students favor efficiency when using LMS. As suggested by Astleitner and Steinberg (
2005), LMS features might actually reduce gender differences compared to the offline class environments or there were not enough accumulating effects to induce gender differences in our study. Another possible explanation could be that gender differences are created due to the learning materials or course contents rather than LMS itself. Further elucidation on gender effect is required in future studies.
In terms of the age variable, this study results indicated that higher age group students more valued communication within the LMS, in particular, survey feature. This result is also supported by McSporran and Young (
2001) as their study showed better communication skills from older students. As a learner’s age increases, it might also develop online/offline communication skills and thus learning through communication becomes a preferable option. However, it should be noted that communication features of LMS were not necessarily valued by students with the higher school year. In other words, the school year variable does not induce the same effect on the learning process or learning preference as the age variable does. Therefore, instructors should not assume similar learning behaviors between the higher age group and higher school year group when designing and implementing an LMS.
When the school year variable was examined, numerous features of LMS were highly valued by the freshman students. One of the possible reasons would be an exposure to new smart learning environments. As freshman students need to adapt in the university education system, they need to pay a particular attention to each element of an LMS. Once the adaptation period is over, the significance of LMS features might be reduced and students will gradually utilize specific LMS functions that are directly relevant to their learning process. Indeed, each feature of LMS was valued differently in each school year apart from the freshman period. It is interesting to note that the master students highly valued availability of the learning materials before lectures. This possibly indicates that postgraduate programs emphasize more on pre-class learning, which is often observed in learner-centered environments.
Our study explored various features of LMS valued by different groups of students based on their cultural background, gender, age, and school year. Out of the four hypotheses tested in our study, the first (cultural background) and the fourth (school year) hypotheses were validated whereas the second (gender) and the third (age) hypotheses were partially validated. Although not every hypothesis was fully validated, there are several important recommendations for instructors or education providers based on our study results. First of all, it is advised that future LMS design should consider the four-dimensional model of Hofstede (
1986), especially the individualism-collectivism dimension to cater for various learning needs of international students. Understanding the effect of culture on LMS design, delivery and implementation will provide more user satisfaction leading toward more success stories in education. Secondly, learning materials on LMS should be checked for possible inducing factors of gender differences. In that sense, the instructors should be informed about gender bias issues. Thirdly, more communication features of LMS will be effective in the courses with higher age groups. Lastly, LMS can provide more guidelines or assistance for freshman students and create a wide range of learner-centered environments for postgraduate programs.
Since this study was delimited to two specific cultures, prospective studies must focus on adding more variety to similar culture based design studies. In order to gain a further understanding of LMS and smart learning process, future studies should investigate more various cultural groups and their learning characteristics. Moreover, due to the sample limitation of this study, the researchers highly recommend to conduct prospective studies with larger sample size to analyze group with parametric techniques. If possible and available, students’ LMS logs (including the most commonly used tools) should be analyzed for a better understanding of LMS tools and their usage by different cultures. Similarly, different variables examined in this study could be compared with assessment or examination grades to identify which LMS features can maximize the learning outcomes for a particular group of students. Additionally, qualitative interview schedules should be integrated into culture based studies to understand its effects in depth.
Since this study implemented the convenience sampling which might have the disadvantage of bias, the similar studies should be replicated in different courses or universities to check if the observed results are due to onetime occurrence. Moreover, LMS has also been utilized in business world where different companies' training activities are supported by these smart systems. In that sense, the research in business world could assist us to understand the deeper influence of culture.
The instructional stakeholders must always remember that future studies on culturally sensitive LMS design will contribute to the achievement of better learning in the waves of upcoming digital revolution era.
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