The Use of ICT for Communication between Teachers and Students in the Context of Higher Education Institutions
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Higher Institute of Accounting and Administration, University of Aveiro, 3810-193 Aveiro, Portugal
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Communication, Image and Public Relations Services, University of Aveiro, 3810-193 Aveiro, Portugal
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Author to whom correspondence should be addressed.
Information 2021, 12(11), 479; https://doi.org/10.3390/info12110479
Submission received: 1 October 2021
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Revised: 10 November 2021
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Accepted: 15 November 2021
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Published: 19 November 2021
(This article belongs to the Section Information Applications)
Abstract
:Recently, the communication paradigm has been changing in society in the higher education context because of the ease of access to the Internet and the high number of mobile devices. Thus, universities have increased their interest in accepting different and sophisticated communication technologies to improve student participation in the educational process. This study aimed to assess how students and teachers use communication technologies to communicate with each other and what their expectations, satisfaction, and attitudes regarding the results of this use are. An analysis model was used in a case study at the University of Aveiro to support the study. Data were obtained through an online questionnaire, which collected 570 responses from students and 172 responses from teachers. These data were processed through descriptive statistics techniques and inference tests (t-tests). The primary outcomes are that publishing and sharing technologies and electronic mail are the most commonly used communication technologies by students and teachers, suggesting that their use will not decline soon. However, other communication technologies were also revealed to be widely used and accepted, with excellent levels of confirmation of expectation.
1. Introduction
The use of information and communication technologies in higher education institutions has grown significantly in recent years. With the use of online communication networks and the widespread use of smartphones, communication practices have significantly evolved.
The general objective of this study is to contribute to our understanding of how communication technologies are currently used in higher education institutions, with special attention given to the comparison between the students’ and teachers’ respective perceptions on their use of these technologies in communication with each other. This paper focuses on a case study carried out in one of the largest Portuguese universities, the University of Aveiro, in 2018, prior to the COVID-19 pandemic. First, we present the context and the research questions of the study and offer a review of the relevant literature. An analysis model designed with specific indicators is presented in Section 2, systematizing the main dimensions of our research and analysis. Here, we describe the materials and methods carried out, with a particular focus on the questionnaire used to collect data. Section 3 contains a detailed analysis of the results of descriptive statistics, as well as the results of the inference tests. In Section 4, we discuss the results, including answers to the research questions. The final section of this paper presents our conclusions and suggestions for future research directions.
1.1. Context and Research Questions
The use of information and communication technologies in higher education institutions has grown significantly in recent years and continues to be recognized as a technological and educational trend [1]. In particular, the extensive use of online communication networks and mobile devices has contributed to changing students’ academic paths [2], thus creating new communication opportunities in the relationship between students and teachers. Traditionally, communication between students and teachers took place almost exclusively in the classroom or other physical spaces, such as teachers’ offices. However, the nature of this relationship seems to be changing, becoming broader, more varied, and physically more distant [3].
Higher education institutions have shown a real concern in connecting and communicating with their audiences, and for that reason, they have sought to implement and make available adequate communication technology infrastructure [4]. This effort is of great importance for students whose success in the digital age depends, partly, on the availability and use of communication technologies in carrying out of the various activities in which they are involved.
The innovation and development of technology in higher education must meet the needs of the rapidly changing world [5]. Communication technologies have expanded significantly, altering students’ learning processes; they are now using mobile devices to become more efficient in their daily tasks, and with information now more available and accessible, they have become more autonomous.
In “Teach Thought We Grow Teachers”, Sabo discusses examples of teachers who have adopted technologies in their classes and how technology is helping students and teachers interact [6]. For Sabo, technology is changing education and providing greater accessibility for teachers. One teacher pointed out that, currently, teachers are available 24 h a day to interact with their students, unlike in the past, when communication occurred by scheduling meetings in the office or through improvised debates at the end of classes. This teacher stated that “a student can now send a text, email, or social media message via Facebook, Twitter, or Tumblr at any time”.
The use of technology as a means of communication between students and teachers has now become common. However, there are some considerations that both parties need to take into account for their interaction to be efficient and effective. In particular, communication through email, social media, blog posts, or podcasts will only be successful if both students and teachers agree to use these platforms and are available to respond to the communication interactions to which they are involved.
Al-Adwan and Smedley [7] indicate that the rapid change in the world highlights the impact of technology on all aspects of learning. Higher education institutions in developed countries recognize that these advances can offer enriching opportunities to integrate technological innovation in the learning environment. Although many universities worldwide have incorporated internet-based learning systems, successful implementation requires an understanding of the end-user acceptance system. In fact, learning to use technology has become a popular approach in higher education due to technological innovation and the continued growth of internet technologies.
It is equally important to bear in mind that teachers need to keep up with the development and the evolution that has taken place in society over time, especially in education. Their monitoring and adherence to the use of new communication technologies can lead to more effective and efficient communication with their students [8]. It is therefore vital to understand what communication technologies are available to be used in the context of higher education institutions, how students and teachers use them to communicate with each other, and what their expectations are concerning the result of this use. In this context, the research questions of this study are as follows:
Research question 1: For what purposes and functions do students and teachers use communication technologies to communicate with each other?
Research question 2: What are the expectations of students and teachers when using communication technologies to communicate with each other?
1.2. Literature Review
The published literature on the use of information and communication technologies in the context of higher education institutions is quite extensive; some studies that refer to different aspects of this use are highlighted below. Some of these studies are about information and communication technologies and are not specifically focused on communication technologies.
In a study on the integration of information and communication technologies in the teaching process, Gebremedhin and Fenta [9] investigated teachers’ use of software, training tools and materials, preferences for professional development and information support. Factors that encouraged teachers’ use of technology, the perception of self-efficacy and the impediments of teachers during the use of technology in the teaching and learning process were also considered. Seventy-two teachers were questioned, and the authors concluded that most were unable to use the hardware in the teaching–learning process due to the scarcity of resources. Regarding perceptions of the use of information and communication technologies, they concluded that teachers have a strong and positive perception of the use of information and communication technologies in the teaching–learning process, with a significant relationship between the perception of teachers and the integration of information and communication technologies in the learning context, as well as the factors that encouraged the use of information and communication technologies. Finally, the relationship between the perception that the use of information and communication technologies increases the quality of the courses they taught and productivity due to the use of information and communication technologies was also classified as significant, concluding, then, that the productivity of teachers is a function of the integration of information and communication technologies in the course they teach.
According to King et al. [10], motivation is at the heart of learning, and few studies have been carried out from the perspective of teachers with good knowledge of information and communication technologies. In King’s study, a total of 114 teachers that students considered to be excellent users of information and communication technologies in an educational context were interviewed. In addition, 337 university students were interviewed about their preferences, suggestions, and their opinions about teachers in relation to information and communication technologies. The main results showed that the majority approved of the use of information and communication technologies by teachers in an educational context, presenting some suggestions. When comparing the two perspectives, it was noticed that students preferred to use their own technology in the classroom, but that many teachers did not allow it; only the most exemplary teachers did.
Another study focused on the use that students and teachers make of different communication technologies, concluding that almost all teachers used a virtual institutional learning environment, having also used other communication technologies in their curricular units, with lower levels of use [11]. Students also proved to be regular users of communication technologies in their curricular units. The authors also highlighted advantages, identified by the students, of the use of communication technologies, namely permanent access to information and educational resources; improvement in their learning; saving time; and improving the performance of its teachers. Regarding the perception of the use of communication technologies outside the context of curricular units, the authors mentioned that the most used mobile devices were mobile phones without internet access and android smartphones. Regarding social networks, the results indicated that more than 70% of students used social networks every day and 7% did not use them, while 29% of teachers used them every day and 23% never used them.
E-learning environments have also been the subject of several studies. In one of these studies, the authors highlighted problems regarding this type of environment, with a special focus on the perspective of teachers and the quality of learning outcomes [12]. In this study, an e-learning system was evaluated by 3636 users from two higher education institutions in Croatia. The students revealed that most teachers did not provide the expected level of information skills related to the needs of the course content and that their motivation depended on the teacher’s motivation and contribution to the e-learning class. The observations showed that more than 2/3 of the teachers did not update the material given in class and showed no interest in knowing whether the students are interested in the e-learning process.
Other studies also identified problems with e-learning platforms, such as the lack of direct interactivity between teachers and students and among students themselves [13]. Based on this, a virtual classroom model structure via the Internet was proposed. The proposed model linked the advantages of the offline approach, such as a whiteboard, with the advantages of online systems. The model was based on four technologies, namely the flash media server architecture; the real-time messaging protocol; the connection of users; and shared objects. The results showed that students were able to communicate as if they were in a real classroom. Participants shared streaming audio, video, and other messages and interacted and navigated the learning environment using streaming media. The researchers concluded that their virtual classroom proposal was a pleasant place for the academic community to come together, generating a more complete and attractive e-learning system.
The use of social networks in educational contexts has also been studied. One investigation studied the effectiveness of using a Facebook group to increase faculty knowledge about student participation in a forum for sharing issues related to the content of a technology course [14]. All participants already had previous experience in participating in similar groups, performing tasks such as organizing, communicating in events and classes, among others. Although the students who participated received a rating, most had a very low level of responses to the questions and few students commented. Prospects for using Facebook for academic purposes were weak but indicated significant changes in the perception that the functions of this social network are an invasion of privacy and, despite understanding the context, student participation was low.
In another study, Facebook groups were used in a university [15], and the reasons for the selection of this type of group were presented. Facebook groups were evaluated by the authors during the years 2012 to 2014 in 12 courses at a university in Israel. The data showed that the use of groups for academic purposes was positively evaluated by students. From the teachers’ perspective, communication with students was quick and simple, and the fact that there were email notifications allowed communication with students without having to resort to Facebook. In conclusion, the authors reported that the students’ experience was positive.
Some studies explored other factors such as usage expectations, satisfaction, or perceived usefulness. These are some of the factors on which some theoretical models used in some studies are based, namely the Technology Acceptance Model, (often referred as TAM) [16] and the Expectation Confirmation Model (often referred as ECM) [17]. For example, considering that students’ success in e-learning programs depends on how they accept and integrate technology into their learning activities, Moreno et al. [18] developed a study in which 251 students participated. A framework was designed to exemplify the students’ intentions regarding the effective use of e-learning platforms, that is, their intention to fully exploit the system’s functionalities in facilitating processes. The observed results demonstrated that students’ perceptions of usefulness and ease of use positively influenced their intention to effectively use e-learning systems. These effects were in line with their attitudes towards the Learning Management System (often referred to as the LMS). The perceived usefulness and ease of use of the system were influenced by the cognitive absorption and self-efficacy of students, as well as by the system’s interactivity and facilitating conditions.
In another study [19], the relationships between factors that presuppose the actual online use of university students of a mobile learning management system were observed through a structural model. In total, 222 students from a Korean university participated in the study, and data were collected to investigate integrated relationships between ease of use, perceived usefulness, confirmation of expectations, satisfaction, intention to continue using, and actual use of the mobile learning management system. The results show that the perceived ease of use predicted the perceived usefulness, but the confirmation of the expectations was not related to the perceived usefulness. Perceived usefulness and confirmation of expectations predicted satisfaction. Perceived usefulness and satisfaction predicted intent to continue, but perceived ease of use was not related to intent to continue use. The continuation intention predicted the actual use of the mobile learning management system.
Kurkovsky and Syta [20] carried out an investigation involving university students on perceptions, attitudes, opinions, and expectations of privacy and trust in relation to electronic communications, such as email, web browsing, the use of social networks, and other online activities. The authors considered characteristics of electronic communications, such as: being a facilitator of communication; the perceived impact on privacy; effects of institutional policies regarding monitoring; and possible loss of privacy and trust. The results showed that, in addition to awareness of institutional policies, students expected their electronic communications within the university to be private.
For Bozanta [21], the use of social media was shown to be present in many areas of a student’s daily life and, therefore, it can be an efficient tool to support communication with other students and with teachers. Thus, in this study, the effects of social networks on collaborative learning were examined with the help of a theoretical model, based on a literature review. An online questionnaire was used to collect data from students at a Turkish university. The results indicated that perceived ease of use is a predictor of perceived usefulness and both have an impact on students’ use of social media for educational purposes. The use of social media enhances interaction between students, student interaction with the faculty, and student engagement.
1.3. Model of Analysis
To systematize the literature review and prepare the creation of an appropriate instrument for data collection, an analysis model was created (Table 1), whose indicators helped to elaborate the answers to the research questions mentioned previously [22].
This analysis model was structured in two concepts. The first concept referred to the agents of the studied context, namely students and teachers, which are the two dimensions of this concept. For students, the indicators of sex, age, cycle of studies, and department were considered, and for the teachers, the indicators of sex, age, scientific area, and department were considered.
The second concept referred to communication technology, and three dimensions were considered. The first dimension was characterization, which corresponded to the need to know which communication technologies are used by agents, students, and teachers, categorizing the communication technologies. The results of these indicators contributed to the elaboration of the answer to research question 1.
The second dimension related to use acceptance and was based on the technology acceptance model. This model was developed to study the relationship between five items, as well as some external variables, aiming to understand the acceptance and behavior of users in the use of technologies. In our model analysis, five items were the indicators of this dimension: usefulness, which refers to the perception that someone has that the use of technology improves one’s performance; ease of use, which refers to the perception of the effort that someone has to exert using technology; attitude, which refers to the combination of increased performance and the reward that can result from the use of technology; intention of future use, which relates to the intention that someone has to continue to use technology they already use; and actual system usage, which refers to the frequency with which someone uses certain technology.
The third dimension referred to use expectation, and it was based on the confirmation of expectations model, which has been used to examine users’ intentions to continue using technology, as well as their satisfaction when using it. Four indicators were selected for this dimension: usefulness and intention of future use, which are two indicators similar to those already mentioned in the second dimension; confirmation, which refers to the relation between the actual use of communication technology and the expectation a user has regarding that use; and satisfaction, which refers to the degree of satisfaction that a user has using communication technologies.
The results of the use acceptance and use expectation dimension indicators support the answer to research question 2.
2. Materials and Methods
This investigation was implemented with the aim of obtaining answers to the above-mentioned research questions. For this purpose, a survey approach was adopted, with the data obtained being of a quantitative nature. Based on the model of analysis already described, an original questionnaire was designed to be answered by students and teachers at the University of Aveiro (Portugal). The structure and questions were similar for students and teachers and were directly aligned with the indicators of the model of analysis.
The answers to the first 4 questions of the questionnaire collected data about the participants regarding the indicators of students and teachers: gender, age, cycle of studies (in the case of students), or the main scientific area of teaching (in the case of teachers), and their department of affiliation.
The other 8 questions (questions 5 to question 12) referred to the purposes, functions, and expectations of students and teachers in the use of communication technologies to communicate. These questions aligned with the dimensions and indicators of the model of analysis, and the responses obtained from students and teachers allowed us to characterize the indicators of which communication technologies were used (question 5); the usefulness of their use (question 6); the ease of use (question 7); the attitudes towards their use, in terms of performance (question 8); intentions to continue use (question 9); current use of the system, in terms of the frequency of use (question 10); confirmation of usage expectations (question 11); and satisfaction in usage (question 12). The questions were originally written in Portuguese, but for better understanding, they are presented here in English (Section 3 Results). A dichotomous yes/no scale was used to answer question 5. Five-level Likert scales were used for questions 6–12. For each of these questions, a specific scale was used, and each of these scales is presented in detail in the tables where the results of each question are presented in the Results section.
The questionnaire was implemented online, and pre-tests were carried out with students and teachers to identify possible aspects of improvement, namely in the writing and presentation of the questions. The final version was available for participation between 22 March and 9 May 2018, and all students and teachers were invited to answer the questionnaire.
For the elaboration of questions 5 to 12, the communication technologies taxonomy presented in Table 2 was adopted. This taxonomy is an adaptation of previous versions elaborated by the same authors and used in other investigations [23,24] and consists of six categories of communication technology. The first category is publishing and sharing technologies (PS), whose main function in the context of this study is the provision of pedagogical content and includes several examples of public platforms such as Youtube or Twitter, blogs in general, as well as institutionally available educational platforms such as Moodle or the Institutional platform (the name comes after the article review). The second category is collaborative technologies (CoT), designed to perform collaborative tasks involving students and/or teachers, and examples include Google Drive, Slack, or Wikis in general.
The next three categories refer to interpersonal communication; however, they have different purposes. One category is electronic mail (EM), used for asynchronous one-to-one and one-to-many communication; it is provided to all students and teachers by their institution. In addition to the institutional email system, examples also include Gmail and Hotmail. Another category of interpersonal communication category is instant messaging (IM), mainly associated with a quick and often more informal communication tool, such as Messenger, WhatsApp, and SMS. The third category of interpersonal communication is videoconferencing and voice systems (VCS), such as Skype or Google Hangouts. At the time of this research, which predated the COVID-19 pandemic, Zoom did not appear as an especially relevant example. Finally, the last category is social networks (SN), and examples include Sapo Campus, Facebook, Twitter, and LinkedIn. The institutional platform includes features of social networks and is provided by the university.
Data were processed using descriptive statistical techniques. In addition, inference tests (t-tests) were performed to test the independence of the data samples of students and teachers, that is, to verify whether the differences found between the two samples were statistically significant. A significance level of α = 0.05 was adopted.
3. Results
The results are presented in this section. Firstly, the data are characterized, and the two data samples obtained are described (Section 3.1). Next, the results of questions 5 to 12 are also described (Section 3.2).
3.1. Data
The data include two samples, one from students and one from teachers (Table 3). The University of Aveiro has 14,703 students and 1044 teachers. The validated sample includes n = 570 responses from students (3.9%) and n = 172 responses from teachers (16.5%).
Questions 1 to 4 of the questionnaire were used to collect the data necessary to characterize the participants who responded. The distribution of data samples by sex (Table 4 and Figure 1) shows that more female students (78.8%) than male students (21.2%) responded to the questionnaire. In the case of teachers, the distribution by sex is more balanced, with 50.6% male teachers and 49.4% female teachers.
In terms of age (Table 5), most students who participated were under 25 years of age (68.3%), with the other age groups being less significant. On the contrary, few teachers were under 40 years old (23.8%), and more than half (52.8%) were between 40 and 54 years old.
Most students attended bachelor’s or master’s studies (86.5%). The most represented departments of students are biological sciences (14.7%) and health sciences (12.8%).
In the case of teachers, the most represented areas of teaching are health sciences (11.6%) and mathematical sciences (9.9%), and the most represented departments are those of health sciences (12.2%) and communication and art (10.5%).
3.2. Main Results
In this section, the descriptive and inferential statistical results of the answers to questions 5 to 12 of the questionnaire are described, corresponding to the indicators belonging to the concept of communication technology in the analysis model.
The results of questions 5 to 12 are described below. The answer to question 5, which asked participants to indicate which communication technologies they use to communicate, created conditions for the answers to the remaining questions. That is, in questions 6 to 12, only the communication technologies that each participant indicated they used in question 5 were presented.
Question 5 was as follows: From the following categories of communication technologies, which ones do you use to communicate with your teachers/students?
The results of the answers to this question (Table 6 and Figure 2) show that students and teachers use all communication technologies indicated to communicate with each other, to greater or lesser degrees. Students and teachers have similar usage levels, which are especially high in the case of electronic mail (96.5%). This result can be explained by the fact that the use of email is widespread at the University of Aveiro. There, all students and teachers have an institutional email address. There are higher proportions of teachers than students who use the remaining communication technologies. These differences are relevant in all the communication technologies.
It is surprising that only 38.1% of students indicated that they use publishing and sharing technologies, namely because this category of communication technologies includes the platform used institutionally to provide educational content (Moodle). For this reason, it also seems interesting that only 72.7% of teachers use publishing and sharing technologies, which indicates that at least part of the educational content delivered to students is shared by other means.
Question 6 was as follows: How do you assess the usefulness of the following options in communicating with your teachers/students?
The results in Table 7 and Table 8 show that, in general, students and teachers found the use of communication technologies useful or very useful to communicate. Answers that show the opposite (not useful or little useful) are scarce from both students and teachers. The most expressive answer is the case of students using collaborative technologies, with 4.8% of students considering it little useful. The answers of neither useful nor useless are more expressive, reaching 10% or more of the answers in some cases. This refers to the case of students regarding the use of videoconferencing and voice systems (18.1%) and social networks (15.7%) and the case of teachers regarding the use of instant messaging (10.0%) and social networks (15.9%).
As mentioned above, students and teachers both expressed positive opinions about the usefulness of using communication technologies to communicate. Summing up their useful and very useful answers, was shown that in all cases, the results are above 80%. The case of electronic mail use stands out positively, with 65.1% of students and 77.7% of teachers considering its use very useful. Some cases show very useful around the response level of 30%, such as the responses of students in relation to the use of social networks (30.3%) and of the teachers in relation to the use of instant messaging (32.0%) and social networks (31.8%).
In two cases (publishing and sharing technologies and electronic mail), the differences between the students and teachers are statistically significant (Table 9, t-test results). In the case of publishing and sharing technologies (p = 0.003), the teachers’ answers are significantly more positive than the students’ answers, as the teachers’ values are much higher, especially with regard to the responses of useful and very useful. The same happens with electronic mail (p = 0.004): although the sum of useful and very useful responses is quite similar for students (97.8%) and teachers (97.6%), the level of very useful responses is higher for teachers (77.7% against 65.1%) and the level of useful responses is higher for students (32.7% against 19.9%).
Question 7 was as follows: How do you assess the degree of ease of use of the following options in communicating with your teachers/students?
Table 10 and Table 11 present the results of the answers to this question and show that, in general, students and teachers consider the use of communication technologies to be easy or very easy. Only the case of the use of collaborative technologies by students does not reach a value of 50% of very easy responses, only registering 37.1% in this case. Additionally, in this communication technology, 40.0% of students responded with easy and 19.0% responded with neither difficult nor easy. This is the least positive case of all the answers to this question either by students or teachers.
Electronic mail and instant messaging were proven to be the easiest communication technologies to use. In the case of electronic mail, 96.3% of students and 93.4% of teachers indicated that the use of this communication technology is easy or very easy, with 69.9% of teachers responding very easy; also, 92.9% of students and 96.0% of teachers indicated that the use of instant messaging is easy or very easy; 72.0% of teachers considered using it very easy.
Few students and teachers consider the use of communication technologies to be difficult or very difficult, with the most expressive case being the use of collaborative technologies by teachers, with 4.9% responding that this use is difficult.
The t-test results (Table 12) showed that the differences in the responses of students and teachers in relation to the ease of use of social networks are statistically significant (p = 0.015), being more positive for teachers than for students. In fact, the response level of very easy is much higher for teachers than for students (68.2% against 52.8%), being higher for students than for teachers in all other response options.
Question 8 was as follows: How do you assess your performance using the following options in communication with your teachers/students?
The results of the answers to this question (Table 13 and Table 14) show that, in general, students and teachers consider their performance in the use of communication technologies to be good or very good. However, in general, the values of good are greater than those of very good. The most significant exception is the use of electronic mail by teachers, in which 36.1% responded with good and 54.2% responded with very good (with 90.3% being good or very good), being the only case with a value above a 50% in the very good option. Students also present important values of good (48.7%) or very good (43.5%) answers, making up 92.2% of these two types of answers. Thus, electronic mail stands out in both students and teachers as the communication technology in which they consider to present better user performance.
The use of social networks by teachers is a category that presents a less positive answer, with 75.0% of teachers responding with good (38.6%) or very good (36.4%) and with 22.7% responding with neither bad nor good.
The bad or very bad responses have very low levels, not seeming to have any important meaning. However, neither bad nor good answers present relevant values, and only in the case of electronic mail are the values lower than 10%: 7.1% in the case of students and 9.6% in the case of teachers.
The t-test results (Table 15) show that there are no statistically significant differences between the responses of students and teachers in any of the communication technologies considered. Thus, although the relative frequencies of their responses show different results, the t-test results do not show, with at least 95% certainty, that these differences are not due to chance.
Question 9 was as follows: Which of the following communication technologies do you intend to continue to use to communicate with your teachers/students?
From the data presented in Table 16 and Table 17, the results clearly show that both students and teachers have a positive opinion on the intention of future use of communication technologies to communicate. Summarizing the answers of probably yes and yes, it is shown that this intention is stronger for teachers than for students. Future use intentions are especially high in the case of electronic mail for students (98.4%) and for teachers (99.4%). There are also cases above 90.0% in the teachers’ answers regarding the future use of publishing and sharing technologies (98.4%), collaborative technologies (97.6%), instant messaging (98.0%) and videoconferencing and voice systems (96.4%). In other words, in the case of teachers, only in the future use of NS is there a response level of less than 90% (86.3%) when the answers of probably yes and yes are considered together. The future use of this same technology by students also presents values lower than the values for other communication technologies, with 13.5% of students responding with neither yes nor no and 14.6% of students responding negatively (no and probably no). Response rates of neither yes nor no is higher for students than for teachers across all communication technologies considered.
There are three cases where the t-test (Table 18) shows statistically significant differences between students’ responses and teachers’ responses: publishing and sharing technologies (p < 0.001), collaborative technologies (p < 0.001), and instant messaging (p = 0.035). In all of these cases, the teachers’ responses show a more favorable opinion about the intended future use than the students’ responses. The cases of publishing and sharing technologies and collaborative technologies are particularly significant, with p < 0.001.
Question 10 was as follows: How often do you use the following options when communicating with your teachers/students?
From the data shown in Table 19 and Table 20, the frequencies of use of communication technologies are higher in teachers than in students, which occurs in all categories of communication technologies. The communication technologies most frequently used are publishing and sharing technologies and electronic mail, with these frequencies being higher in teachers than in students: 59.5% of students use publishing and sharing technologies often or always, with 92.0% being the corresponding value for teachers. The same occurs in the case of electronic mail, where 76.6% of the students indicate using it often or always, and 91.6% of the teachers indicate using it often or always.
The least used communication technologies are the videoconferencing and voice systems, especially in students (only 25.0% use it often or always), but also in teachers (only 41.1% use it often or always). The frequency of use of social networks in students is also very low: only 33.7% use them often or always.
The results of the t-test (Table 21) show that teachers use all categories of communication technology more frequently than students, with these differences being statistically significant. In four out of six communication technology categories, the results are particularly significant (p < 0.001). Additionally, the results regarding collaborative technologies and instant messaging are also statistically significant. Thus, the main result regarding the frequency is that teachers use communication technologies to communicate more frequently than students.
Question 11 was as follows: The result of using the following options to communicate with teachers/students is according to my expectation.
Data in Table 22 and Table 23 show that, in general, the result of using communication technologies to communicate are in accordance with their expectations for students and teachers alike. Interestingly, the most frequent answer is that of agree in both students and teachers. In one case, it is even above 60%, as 61.0% of teachers confirm that the result of using collaborative technologies is as they expected. Only in two cases is this number under 50%, which are the cases of using videoconferencing and voice systems in students (44.4%) and of using social networks in teachers (45.5%). Very small numbers of answers show levels of no confirmation, as answers such as totally disagree and disagree are in small numbers.
Teachers show higher levels of expectation confirmation than students, and in four cases, these differences are statistically significant (Table 24, t-test results). The cases refer to using publishing and sharing technologies (p < 0.001), electronic mail (p < 0.001), videoconferencing and voice systems (p = 0.037), and social networks (p = 0.007).
Question 12 was as follows: How satisfied are you with using the following options to communicate with your teachers/students?
In general, students and teachers were shown to be satisfied using communication technologies to communicate (Table 25 and Table 26). The results are not very different between students and teachers, especially when the answers of satisfied and very satisfied are added together, as it happens in the cases of using collaborative technologies (75.2% of students and 78.1% of teachers) and of using videoconferencing and voice systems (75.0% of students and 75.0% of teachers). Larger differences were found in the other cases. Teachers are especially satisfied in the cases of using publishing and sharing technologies (92.0% of satisfied or very satisfied) and electronic mail (92.2% of satisfied or very satisfied), with very low numbers of any type of dissatisfaction or indifference. Higher numbers of indifference (neither satisfied nor satisfied) were found in other cases, with some of them even being above 20%: students on the use of collaborative technologies (21.0%) and social networks (22.5%), as well as teachers on the use of videoconferencing and voice systems (21.4%) and social networks (34.1%).
There are two cases where the students’ and the teachers’ answers are significantly different (Table 27, t-test results). Those are the cases of publishing and sharing technologies (p = 0.001) and of electronic mail (p = 0.032), both with higher levels of satisfaction from teachers than from students.
4. Discussion
This study was guided by two research questions and its implementation was based on a model of analysis (Section 1.3). This model of analysis allowed the design of a questionnaire survey whose application to students and teachers of the University of Aveiro enabled the collection of data that, after descriptive and inferential statistical treatment, produced results corresponding to the indicators of the analysis model.
This section presents the answers to the two research questions (Section 4.1 and Section 4.2) and presents an overall discussion of the results (Section 4.3).
4.1. First Research Question
The first research question was the following: For what purposes and functions of students and teachers use communication technologies to communicate with each other? The indicators that allow an answer to this question to be obtained are those of the characterization of communication technology dimension of the model of analysis, corresponding to question 5 of the questionnaire. In this question, each student indicated, from a list of communication technology categories (Table 1), which ones they used to communicate with their teachers, and each teacher indicated which, from a list of communication technologies categories, they used to communicate with their students. The results show that the communication technologies most used by students and teachers are publishing and sharing technologies and electronic mail. In the case of electronic mail, usage is especially high, which corresponds to what would be expected, and which corresponds to the most used communication technologies for interpersonal communication. In fact, the use of electronic mail to carry out asynchronous and interpersonal communication is extremely widespread in higher education institutions and in society in general.
Other communication technologies that allow for interpersonal communication show relevant levels of use by students and teachers, such as instant messaging and videoconferencing and voice systems, but significantly less than the use of electronic mail. It is expected that during the COVID-19 pandemic period, the instant messaging and videoconferencing and voice systems will have been used by more students and teachers than before that period. In fact, applications such as Zoom (videoconferencing and voice systems) or Microsoft Teams (videoconferencing and voice systems and other functions) were systematically used during this period to teach classes and to carry out other activities that were previously carried out in person. It will be interesting to compare the levels of instant messaging and videoconferencing and voice systems utilization before and after the COVID-19 pandemic period.
Publishing and sharing technologies are also used by large numbers of students and teachers. These communication technologies allow the publication and sharing of content, which corresponds to a role that teachers usually play in higher education institutions. It is interesting to see that the level of use of this category of communication technology is much higher by teachers than by students. In fact, one of the most common concerns of teachers is the provision and sharing of pedagogical content, which is normally obtained and consumed by their students. Apparently, it would make sense that the level of use of publishing and sharing technologies was not very different for teachers and students, so we propose, as a possible explanatory hypothesis, that at least some portion of students understood this dimension to refer to sharing content and not to refer to its consumption. Another hypothesis is that teachers also publish and share content through other categories of communication technology, but it is not possible to formulate an answer with the available data. The remaining communication technologies also show relevant levels of use, being systematically higher by teachers than by students.
In general, it is found that students and teachers make significant use of communication technologies, with this use being especially evident in applications that allow interpersonal communication, emphasizing the use of email and applications that allow one to publish and share pedagogical content. This is in accordance with previous results, confirming that older forms of communication between students and teachers are being replaced. For example, pedagogical content traditionally available on paper in copy centers or bookshops are being replaced by digital content published and available on digital platforms, and personal communication with teachers, for example in teacher’s offices, is being replaced with more direct and immediate digital applications [23].
4.2. Second Research Question
The second research question was the following: What are the expectations of students and teachers when using communication technologies to communicate? The indicators that allow an answer to this question to be obtained are those related to the dimensions of use acceptance and of use expectation of the analysis model, corresponding to questions 6 to 12 of the questionnaire. These questions asked about various items that were taken from theories such as the technology acceptance model and the confirmation of expectations model (Section 1.3 and Table 1). The collected data are processed and described in the results section (Section 3).
Before answering the second research question, it is important to emphasize that only the communication technologies that each participant indicated they used in question 5 were listed when they answered questions 6 to 12.
Some main ideas emerge from the analysis of the results. First, publishing and sharing technologies and electronic mail are the two communication technologies that show higher rates in several indicators, which is in accordance with the answer to the first research question, i.e., publishing and sharing technologies and electronic mail are clearly the two most used communication technologies by both students and teachers. The results give further credence to that, adding very positive indicators about the use of both of these communication technologies in terms of perceived usefulness, perceived ease of use, perceived performance due to their use, intentions to continue use, and frequency of use. All of these indicators are from the use acceptance dimension of the model of analysis and so they suggest a good level of acceptance of publishing and sharing technologies and electronic mail.
The results are not so high with regard to the other communication technologies; however, in general, they are positive. There are just a few cases with negative results, often regarding the use of social networks, which seemed to be confirmed when participants asked about continuing using it to communicate, as 14.6% of students and 4.6% of teachers answered that they did not intend to continue to use it. This agrees with the frequency of use, with 33.7% of students and 17.5% of teachers answering that they never or rarely used this communication technology to communicate with their students/teachers.
Second, two other indicators are specific of the use expectation dimension, namely confirmation (of expectations) and satisfaction. The results regarding the use of publishing and sharing technologies and electronic mail are not as positive as they were on the previous indicators. In the case regarding the confirmation of expectations (question 11), the most frequent answer was “agree” and not “fully agree” by large margins, both in the case of students and in the case of teachers. This suggests that for a significant group of students and teachers, the expectations of using publishing and sharing technologies and electronic mail were not completely fulfilled, suggesting that something more was expected. This is similar to the last indicator regarding satisfaction. In fact, the most frequent answer was “satisfied”, and not “very satisfied” by large margins, both in the case of students and in the case of teachers. This suggests that a significant group of students and teachers were not very satisfied using publishing and sharing technologies and electronic mail.
Interestingly, these results regarding expectations and satisfaction in the use of publishing and sharing technologies and electronic mail are similar to the other communication technologies considered, which means that, in general, students and teachers could feel more convinced about their expectations and more satisfied with using of communication technologies to communicate.
Third, analyzing the results of the inference tests, it is observed that, with few exceptions, the students’ responses and the teachers’ responses are significantly different in relation to the use of two communication technologies, namely the publishing and sharing technologies and electronic mail. These significant differences are observable in several items analyzed, with more favorable values being systematically obtained by the teachers than by the students:
- Teachers have a significantly more favorable opinion than students regarding the usefulness of publishing and sharing technologies and electronic mail (question 6);
- Teachers have a significantly more favorable opinion than students regarding the intention of future use with regard to publishing and sharing technologies and electronic mail, with a similar trend for collaborative technologies (question 9);
- Teachers have a significantly more favorable opinion than students in relation to the current use (frequency) of publishing and sharing technologies and electronic mail, with a similar trend for all communication technologies considered (question 10);
- Teachers have a significantly more favorable opinion than students in relation to expectations, that is, in relation to the fact that the result of using publishing and sharing technologies and electronic mail is in accordance with their expectations, with a trend similar for videoconferencing and voice systems and social networks (question 11);
- Teachers have a significantly more favorable opinion than students regarding the satisfaction of using publishing and sharing technologies and electronic mail (question 12).
What do these results suggest? In the specific case of frequency of use, this result seems to be natural, given that in general, each teacher has a high number of students with whom they communicate and, on the contrary, in general, each student has a reduced number of teachers. Consequently, it seems natural that teachers use these communication technologies significantly more often than students. In relation to the other aspects, it is rather difficult to formulate an objective answer, although this could eventually be obtained by conducting in-depth interviews with students and teachers. Still, some hypotheses can be suggested, such as:
- These differences are due to the generational differences between students and teachers, who have different perspectives on the academic use of publishing and sharing technologies and electronic mail, namely in aspects such as the usefulness or intention of future use, among others;
- These differences are due to the fact that the study was about the use of communication technologies in an academic environment and not in an informal and more personal environment.
Fourth, regarding the ease of use (question 7) and the performance of the use (question 8) of publishing and sharing technologies and electronic mail, there are no statistically significant differences between the students’ answers and the teachers’ answers, which occurs in all categories of communication technologies considered, with the exception being the ease of use social networks. This is not surprising, because students and teachers are generally expected to be frequent and literate users of communication technologies, both in academic and in non-academic contexts.
4.3. Concluding Remarks
To conclude this article, some limitations are presented, as well as the main implications of the results and some directions for future research.
4.3.1. Limitations
This study has some limitations, namely the fact that it was only carried out at one university and, therefore, its results cannot be generalized. However, these results have some relevance, as data samples of good sizes were obtained, and some trends were confirmed through inference tests.
Another limitation arises from the fact that the data are only quantitative and, therefore, it is difficult to carry out a deeper discussion, namely by exploring the reasons or motivations that justify the results.
4.3.2. Implications and Future Research
The main implications of these results are that publishing and sharing technologies and electronic mail continue to be the most used communication technologies by students and teachers, suggesting that this use will not decline soon. However, other communication technologies were also revealed to be widely used and accepted with good levels of confirmation of expectations and satisfaction, which also indicates the continuation or even the increase in their use.
The COVID-19 pandemic period did, however, bring some changes, as communication technologies were used even more frequently during this period in order for students and teachers to communicate with each other. Some applications, such as Zoom or Microsoft Teams, were used systematically to teach classes, and other technologies, such as social networks or instant messaging, were also used more frequently. Thus, the question that seems to arise is whether in the post-pandemic period, the communication technologies used, their acceptance of use, and their expected use will be similar to as they were at the pre-pandemic period, or if they will evolve to account for the uses that were made during the pandemic period; in other words, the question is whether the pandemic period caused significant changes in these indicators that will extended beyond that period.
Thus, it seems important to replicate this study (completely carried out in the pre-pandemic period) in the post-pandemic period, at the same university and directed equally at students and professors. This study will thus produce comparable results, although this comparison cannot be isolated from other contextual factors, namely social, technological, and educational factors, that also influence the evolution of the use of communication technologies. These results may be advantageously complemented with other qualitative data, as previously recognized in Section 4.3.1.
Author Contributions
Conceptualization, J.B., H.S. and R.P.M.; methodology, J.B., H.S. and R.P.M.; formal analysis, J.B., H.S. and R.P.M.; writing—original draft preparation, J.B.; writing—review and editing, J.B., H.S. and R.P.M.; supervision, J.B. and R.P.M. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
This paper summarizes the main results from a thesis, the full text of which can be accessed on https://ria.ua.pt/handle/10773/25472 (accessed on 13 November 2021).
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Students and teachers, by sex.
Figure 2.
Communication technologies used by students and teachers.
Table 1.
Model of analysis.
| Concept | Dimension | Indicators |
|---|---|---|
| Agent | Student | Sex; age; cycle of studies; department |
| Teacher | Sex; age; scientific area; department | |
| Communication technology | Characterization | Categories used by objective or function |
| Use acceptance (technology acceptance model) | Usefulness; ease of use; attitude; intention of future use; actual system usage | |
| Use expectation (expectations confirmation model) | Usefulness; confirmation; satisfaction; intention of future use |
Table 2.
Taxonomy of communication technologies.
| Category | Examples |
|---|---|
| PS—Publishing and sharing technologies | Youtube, Moodle, Flickr, Sapo Campus, Blogs, etc. |
| CoT—Collaborative technologies | Google Drive, Slack, Wiki, etc. |
| EM—Electronic mail | Gmail, Institutional electronic mail, Hotmail, etc. |
| IM—Instant messaging | Messenger, WhatsApp, SMS, etc. |
| VCS—Videoconferencing and voice systems | Skype, Google Hangouts, etc. |
| SN—Social networks | Sapo Campus (institutional SN), Facebook, Twitter, LinkedIn, etc. |
Table 3.
Population and data samples, from students and teachers.
| Students | Teachers | |
|---|---|---|
| Population (academic year 2017–2018) | 14,703 | 1044 |
| Validated answers | 570 | 172 |
| Sample (% of population) | 3.9% | 16.5% |
Table 4.
Students and teachers, by sex.
| Sex | Students (n = 570) | Teachers (n = 172) |
|---|---|---|
| Male | 120 (21.2%) | 87 (50.6%) |
| Female | 449 (78.8%) | 85 (49.4%) |
Table 5.
Students and teachers, by age.
| Age Intervals | Students (n = 570) | Teachers (n = 172) |
|---|---|---|
| <20 years | 136 (23.9%) | 0 (0.0%) |
| 20–24 years | 253 (44.4%) | 2 (1.2%) |
| 25–29 years | 83 (14.6%) | 9 (5.2%) |
| 30–34 years | 38 (6.7%) | 9 (5.2%) |
| 35–39 years | 19 (3.3%) | 21 (12.2%) |
| 40–44 years | 14 (2.5%) | 30 (17.4%) |
| 45–49 years | 15 (2.6%) | 36 (20.9%) |
| 50–54 years | 8 (1.4%) | 25 (14.5%) |
| 55–59 years | 3 (0.5%) | 22 (12.8%) |
| 60–64 years | 1 (0.2%) | 15 (8.7%) |
| 65–69 years 1 | 0 (0.0%) | 3 (1.7%) |
1 In the Portuguese public higher education system, teachers cannot teach after reaching 70 years old.
Table 6.
Communication technologies used by students and teachers.
| Communication Technologies | Students | Teachers |
|---|---|---|
| PS | 38.1% | 72.7% |
| CoT | 18.4% | 23.8% |
| EM | 96.5% | 96.5% |
| IM | 17.4% | 29.1% |
| VCS | 12.6% | 32.6% |
| SN | 15.6% | 25.6% |
Table 7.
Usefulness of the use of communication technologies by students.
| Communication Technologies | Not Useful | Little Useful | Neither Useful Nor Useless | Useful | Very Useful |
|---|---|---|---|---|---|
| PS | 0.9% | 3.2% | 6.0% | 38.2% | 51.6% |
| CoT | 0.0% | 4.8% | 9.5% | 44.8% | 41.0% |
| EM | 0.0% | 0.4% | 1.8% | 32.7% | 65.1% |
| IM | 0.0% | 2.0% | 5.1% | 46.5% | 46.5% |
| VCS | 0.0% | 0.0% | 18.1% | 27.8% | 54.2% |
| SN | 1.1% | 2.2% | 15.7% | 50.6% | 30.3% |
Table 8.
Usefulness of the use of communication technologies by teachers.
| Communication Technology | Not Useful | Little Useful | Neither Useful Nor Useless | Useful | Very Useful |
|---|---|---|---|---|---|
| PS | 0.0% | 0.8% | 4.0% | 29.6% | 65.6% |
| CoT | 0.0% | 2.4% | 4.9% | 43.9% | 48.8% |
| EM | 0.0% | 0.0% | 2.4% | 19.9% | 77.7% |
| IM | 0.0% | 2.0% | 10.0% | 56.0% | 32.0% |
| VCS | 0.0% | 1.8% | 5.4% | 51.8% | 41.1% |
| SN | 2.3% | 0.0% | 15.9% | 50.0% | 31.8% |
Table 9.
Results of statistical inference t test to verify the independence of students’ and teachers’ responses to question 6, about the usefulness of using communication technologies (p ≤ 0.05).
Table 9.
Results of statistical inference t test to verify the independence of students’ and teachers’ responses to question 6, about the usefulness of using communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | 0.003 |
| CoT | 0.236 |
| EM | 0.004 |
| IM | 0.104 |
| VCS | 0.756 |
| SN | 0.876 |
Table 10.
Ease of use communication technologies by students.
| Communication Technologies | Very Difficult | Difficult | Neither Difficult Nor Easy | Easy | Very Easy |
|---|---|---|---|---|---|
| PS | 0.5% | 1.8% | 14.3% | 43.3% | 40.1% |
| CoT | 0.0% | 3.8% | 19.0% | 40.0% | 37.1% |
| EM | 0.2% | 0.7% | 2.7% | 35.8% | 60.5% |
| IM | 2.0% | 2.0% | 3.0% | 28.3% | 64.6% |
| VCS | 0.0% | 4.2% | 18.1% | 33.3% | 44.4% |
| SN | 2.2% | 2.2% | 18.0% | 24.7% | 52.8% |
Table 11.
Ease of use communication technologies by teachers.
| Communication Technologies | Very Difficult | Difficult | Neither Difficult Nor Easy | Easy | Very Easy |
|---|---|---|---|---|---|
| PS | 0.0% | 2.4% | 16.0% | 40.8% | 40.8% |
| CoT | 0.0% | 4.9% | 9.8% | 43.9% | 41.5% |
| EM | 0.0% | 0.0% | 6.6% | 23.5% | 69.9% |
| IM | 0.0% | 0.0% | 4.0% | 24.0% | 72.0% |
| VCS | 0.0% | 1.8% | 7.1% | 41.1% | 50.0% |
| SN | 0.0% | 0.0% | 9.1% | 22.7% | 68.2% |
Table 12.
Results of statistical inference t-test to verify the independence of students’ and teachers’ answers to question 7 about the ease of use of the communication technologies (p ≤ 0.05).
Table 12.
Results of statistical inference t-test to verify the independence of students’ and teachers’ answers to question 7 about the ease of use of the communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | 0.934 |
| CoT | 0.458 |
| EM | 0.166 |
| IM | 0.150 |
| VCS | 0.142 |
| SN | 0.015 |
Table 13.
Performance (attitude) in the use of communication technologies by students.
| Communication Technologies | Very Bad | Bad | Neither Bad Nor Good | Good | Very Good |
|---|---|---|---|---|---|
| PS | 0.5% | 1.4% | 14.3% | 54.8% | 29.0% |
| CoT | 0.0% | 2.9% | 19.0% | 45.7% | 32.4% |
| EM | 0.0% | 0.7% | 7.1% | 48.7% | 43.5% |
| IM | 2.0% | 0.0% | 12.1% | 43.4% | 42.4% |
| VCS | 0.0% | 1.4% | 16.7% | 40.3% | 41.7% |
| SN | 2.2% | 1.1% | 14.6% | 50.6% | 31.5% |
Table 14.
Performance (attitude) in the use of communication technologies by teachers.
| Communication Technologies | Very Bad | Bad | Neither Bad Nor Good | Good | Very Good |
|---|---|---|---|---|---|
| PS | 0.0% | 0.8% | 15.2% | 53.6% | 30.4% |
| CoT | 0.0% | 0.0% | 14.6% | 41.5% | 43.9% |
| EM | 0.0% | 0.0% | 9.6% | 36.1% | 54.2% |
| IM | 0.0% | 0.0% | 12.0% | 54.0% | 34.0% |
| VCS | 0.0% | 0.0% | 16.1% | 50.0% | 33.9% |
| SN | 0.0% | 2.3% | 22.7% | 38.6% | 36.4% |
Table 15.
Results of statistical inference t-test to verify the independence of student and teacher responses to question 8 about the performance (attitude) using communication technologies (p ≤ 0.05).
Table 15.
Results of statistical inference t-test to verify the independence of student and teacher responses to question 8 about the performance (attitude) using communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | 0.707 |
| CoT | 0.130 |
| EM | 0.093 |
| IM | 0.867 |
| VCS | 0.741 |
| SN | 0.937 |
Table 16.
Intention of future use of communication technologies by students.
| Communication Technologies | No | Probably No | Neither Yes Nor No | Probably Yes | Yes |
|---|---|---|---|---|---|
| PS | 0.5% | 4.1% | 5.5% | 25.3% | 64.5% |
| CoT | 2.9% | 7.6% | 5.7% | 31.4% | 52.4% |
| EM | 0.0% | 0.5% | 1.1% | 20.2% | 78.2% |
| IM | 5.1% | 2.0% | 8.1% | 27.3% | 57.6% |
| VCS | 1.4% | 2.8% | 9.7% | 25.0% | 61.1% |
| SN | 5.6% | 9.0% | 13.5% | 21.3% | 50.6% |
Table 17.
Intention of future use of communication technologies by teachers.
| Communication Technologies | No | Probably No | Neither Yes Nor No | Probably Yes | Yes |
|---|---|---|---|---|---|
| PS | 0.0% | 0.0% | 1.6% | 17.6% | 80.8% |
| CoT | 0.0% | 0.0% | 2.4% | 24.4% | 73.2% |
| EM | 0.0% | 0.0% | 0.6% | 16.3% | 83.1% |
| IM | 0.0% | 0.0% | 2.0% | 38.0% | 60.0% |
| VCS | 0.0% | 1.8% | 1.8% | 33.9% | 62.5% |
| SN | 2.3% | 2.3% | 9.1% | 29.5% | 56.8% |
Table 18.
Results of statistical inference t-test to verify the independence of students’ and teachers’ responses to question 9 about the intention of future use of communication technologies (p ≤ 0.05).
Table 18.
Results of statistical inference t-test to verify the independence of students’ and teachers’ responses to question 9 about the intention of future use of communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | <0.001 |
| CoT | <0.001 |
| EM | 0.080 |
| IM | 0.035 |
| VCS | 0.250 |
| SN | 0.076 |
Table 19.
Actual system usage of communication technologies by students.
| Communication Technologies | Never | Rarely | Sometimes | Often | Always |
|---|---|---|---|---|---|
| PS | 4.1% | 13.4% | 23.0% | 40.6% | 18.9% |
| CoT | 4.8% | 18.1% | 36.2% | 32.4% | 8.6% |
| EM | 0.4% | 2.9% | 20.2% | 41.1% | 35.5% |
| IM | 6.1% | 20.2% | 29.3% | 36.4% | 8.1% |
| VCS | 6.9% | 27.8% | 40.3% | 23.6% | 1.4% |
| SN | 13.5% | 20.2% | 32.6% | 30.3% | 3.4% |
Table 20.
Actual system usage of communication technologies by teachers.
| Communication Technologies | Never | Rarely | Sometimes | Often | Always |
|---|---|---|---|---|---|
| PS | 0.0% | 0.8% | 7.2% | 44.8% | 47.2% |
| CoT | 0.0% | 4.9% | 39.0% | 46.3% | 9.8% |
| EM | 0.0% | 0.6% | 7.8% | 47.6% | 44.0% |
| IM | 0.0% | 10.0% | 38.0% | 34.0% | 18.0% |
| VCS | 0.0% | 7.1% | 51.8% | 30.4% | 10.7% |
| SN | 4.1% | 13.4% | 23.0% | 40.6% | 18.9% |
Table 21.
Results of statistical inference t-test to verify the independence of the responses of students and teachers to question 10 about the actual usage of communication technologies (p ≤ 0.05).
Table 21.
Results of statistical inference t-test to verify the independence of the responses of students and teachers to question 10 about the actual usage of communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | <0.001 |
| CoT | 0.025 |
| EM | <0.001 |
| IM | 0.024 |
| VCS | <0.001 |
| SN | <0.001 |
Table 22.
Confirmation of expectations on the use of communication technologies by students.
| Communication Technologies | Totally Disagree | Disagree | Neither Agree Nor Disagree | Agree | Totally Agree |
|---|---|---|---|---|---|
| PS | 0.9% | 2.8% | 19.4% | 54.4% | 22.6% |
| CoT | 1.0% | 4.8% | 17.1% | 54.3% | 22.9% |
| EM | 0.4% | 1.1% | 10.2% | 56.4% | 32.0% |
| IM | 0.0% | 2.0% | 13.1% | 50.5% | 34.3% |
| VCS | 1.4% | 4.2% | 15.3% | 44.4% | 34.7% |
| SN | 1.1% | 5.6% | 23.6% | 52.8% | 16.9% |
Table 23.
Confirmation of expectations on the use of communication technologies by teachers.
| Communication Technologies | Totally Disagree | Disagree | Neither Agree Nor Disagree | Agree | Totally Agree |
|---|---|---|---|---|---|
| PS | 0.0% | 2.4% | 7.2% | 53.6% | 36.8% |
| CoT | 0.0% | 2.4% | 12.2% | 61.0% | 24.4% |
| EM | 0.0% | 0.0% | 4.8% | 51.8% | 43.4% |
| IM | 0.0% | 0.0% | 14.0% | 56.0% | 30.0% |
| VCS | 0.0% | 1.8% | 8.9% | 51.8% | 37.5% |
| SN | 0.0% | 2.3% | 27.3% | 45.5% | 25.0% |
Table 24.
Results of statistical inference t-test to verify the independence of the responses of students and teachers to question 11 about the confirmation of expectations on the use of communication technologies (p ≤ 0.05).
Table 24.
Results of statistical inference t-test to verify the independence of the responses of students and teachers to question 11 about the confirmation of expectations on the use of communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | <0.001 |
| CoT | 0.055 |
| EM | 0.000 |
| IM | 0.147 |
| VCS | 0.037 |
| SN | 0.007 |
Table 25.
Satisfaction on the use of communication technologies by students.
| Communication Technologies | Very Unsatisfied | Unsatisfied | Neither Satisfied Nor Unsatisfied | Satisfied | Very Satisfied |
|---|---|---|---|---|---|
| PS | 1.4% | 0.5% | 16.1% | 63.6% | 18.4% |
| CoT | 1.0% | 2.9% | 21.0% | 51.4% | 23.8% |
| EM | 0.0% | 1.5% | 9.3% | 57.1% | 32.2% |
| IM | 2.0% | 1.0% | 12.1% | 49.5% | 35.4% |
| VCS | 2.8% | 4.2% | 18.1% | 47.2% | 27.8% |
| SN | 2.2% | 4.5% | 22.5% | 50.6% | 20.2% |
Table 26.
Satisfaction on the use of communication technologies by teachers.
| Communication Technologies | Very Unsatisfied | Unsatisfied | Neither Satisfied Nor Unsatisfied | Satisfied | Very Satisfied |
|---|---|---|---|---|---|
| PS | 0.0% | 1.6% | 6.4% | 60.0% | 32.0% |
| CoT | 0.0% | 2.4% | 19.5% | 53.7% | 24.4% |
| EM | 0.0% | 1.2% | 6.6% | 50.6% | 41.6% |
| IM | 0.0% | 0.0% | 18.0% | 52.0% | 30.0% |
| VCS | 0.0% | 3.6% | 21.4% | 48.2% | 26.8% |
| SN | 2.3% | 0.0% | 34.1% | 34.1% | 29.5% |
Table 27.
Results of statistical inference t-test to verify the independence of the responses of students and teachers to question 12 on the satisfaction on the use of communication technologies (p ≤ 0.05).
Table 27.
Results of statistical inference t-test to verify the independence of the responses of students and teachers to question 12 on the satisfaction on the use of communication technologies (p ≤ 0.05).
| Communication Technology | p |
|---|---|
| PS | 0.001 |
| CoT | 0.695 |
| EM | 0.032 |
| IM | 0.817 |
| VCS | 0.743 |
| SN | 0.690 |
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Batista, J.; Santos, H.; Marques, R.P. The Use of ICT for Communication between Teachers and Students in the Context of Higher Education Institutions. Information 2021, 12, 479. https://doi.org/10.3390/info12110479
AMA Style
Batista J, Santos H, Marques RP. The Use of ICT for Communication between Teachers and Students in the Context of Higher Education Institutions. Information. 2021; 12(11):479. https://doi.org/10.3390/info12110479
Chicago/Turabian StyleBatista, João, Helena Santos, and Rui Pedro Marques. 2021. "The Use of ICT for Communication between Teachers and Students in the Context of Higher Education Institutions" Information 12, no. 11: 479. https://doi.org/10.3390/info12110479
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