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This article presents the findings of a systematic review of perceived usability of educational technology systems. The research was conducted after studying, organizing, and analyzing the results of 104 research papers evaluating perceived usability of educational technologies using the System Usability Scale (SUS). The results were organized on the basis of (a) the usability score obtained when using the SUS, (b) the type of educational technology used, (c) the subject being learned, (d) the level of education, (e) the type of participant, (f) the age, and (g) the number of participants in each survey. Statistical analysis in all surveys (N = 170) demonstrated a good level of usability but with some issues (M = 70.09, SD = 12.98). The categories of Internet platforms (M = 66.25, SD = 12.42), university websites (M = 63.82, SD = 16.52) and affective tutoring systems (ATS) (M = 68.87, SD = 7.30) seem to have a good usability level according to SUS, preceded by mobile applications (M = 73.62, SD = 13.49) and multimedia (M = 76.43, SD = 9.45). Moreover, SUS scores were not found to be significantly related with participants' age (r = 0.017, p = 0.931, ns), stage of education (p = 0.539, ns), or the type of participants (p = 0.639, ns). Furthermore, the subject being learned (p = 0.038, s) and the number of participants in each survey (r = -0.259, p = 0.001, s) seem to relate to the obtained SUS scores. ? slight, statistically insignificant improvement is noted in the perceived usability over the years (p = 0.182, ns). The findings of this review will serve as a useful reference guide for educational technology designers, practitioners, and teachers.

Purpose: The purpose of this study was to determine the impact of perceived usability and students' personality traits on their learning gain in an e-learning context at the university level. Design/methodology/approach: The factors examined are related to individual characteristics such as students' personality traits, as well as to perceptual characteristics such as the perceived usability of the platform used. A total of 110 undergraduate students participated in the study. A one-group pretest-posttest research design was adopted. Big 5 personality test, System Usability Scale (SUS) and a general knowledge assessment questionnaire were used. Findings: Perceived usability of Zoom platform is statistically significantly correlated with students' learning gain (r = 0.294, p = 0.002, s). Concerning learning effectiveness in the current e-learning scenario, students' final performance was found to be statistically significantly higher than the initial (p = 0.000, s). A hierarchical regression analysis (R[superscript 2] = 0.146) unveiled that Zoom's perceived usability and personality traits are significant predictors for learning gain (p = 0.011, s). Research limitations/implications: The findings of this research provide important implications regarding the design of lessons in an e-learning context. Social implications: A substantial fraction of the educational process is going online, especially in higher education. Thus, a thorough understanding of the factors which influence learning gain in an e-learning context is of significance. Originality/value: The main contribution of this study is that it quantifies the variance of the learning gain explained by two factors, namely, SUS and personality.

Purpose: The purpose of this paper is to investigate the impact of personality traits on the perceived usability evaluation of e-learning platforms. In specific, perceived usability levels of the educational platforms and tools used in primary and secondary education in Greece are demonstrated. The impact which personality traits and other individual-related factors have on the perceived usability were also examined. Design/methodology/approach: In total, 2,239 Greek primary and secondary education teachers participated in the study through an online survey. The system usability scale (SUS) and Big 5 personality test questionnaires were adopted, as well as a demographics questionnaire and nine platforms were examined: e-me, eclass, Google Classroom, Microsoft Teams, Cisco Webex, Edmodo, Padlet, Skype and Zoom. Findings: Most platforms were rated as satisfactory in terms of perceived usability as measured by SUS. SUS scores were not found to be significantly related with participants' age, gender, private/public school, working relationship. Furthermore, openness to new experience and extraversion demonstrated the strongest positive correlation with perceived usability evaluation. Research limitations/implications: The current study used a sample of Greek teachers as participants, so the generalizability of results without considering cultural or organizational issues is of questionable validity. The Big 5 personality test is widely adopted; however, it seems that it does not capture comprehensively all possible dimensions of personality. Practical implications: Acknowledging the correlations between personality traits and perceived usability for each platform, teachers may now choose the most user-friendly one depending on the personality traits. Designers can adapt their systems to meet users' needs accordingly. Moreover, the reported results provide a frame of reference for the respective organizations and companies to compare the quality of user experience of their products and services. Thus, development costs of an e-learning platform/tool can be reduced accordingly. Social implications: Text. Originality/value: Perceived usability of a technological system affects the way users interact with it and consequently the whole learning experience. Thus, factors which may affect perceived usability and, in turn, the learning outcomes are of paramount importance and should be exhaustively examined. Giving that personality affects or is related to, other parameters related with technology (technology adoption, perceived and actual use, acceptance, interaction, perceived ease of use), this study addresses a significant research gap and sheds light to the before-mentioned issues.

This study investigated undergraduate students' intention to use wiki technology. An extension of the Technology Acceptance Model (TAM) has been used by taking into account not only students' wiki perceived utility and usability, but also Big Five personality characteristics and two other variables, social norms, and facilitating conditions, as proposed in the Unified Theory of Acceptance and Use of Technology (UTAUT). Students' beliefs before (pre-wiki scenario) and after (post-wiki scenario) the actual use of the wiki system were investigated, with 85 and 86 participants respectively. The hypotheses were tested using partial least squares analysis. For the pre-wiki scenario, 8/15 hypotheses were confirmed and 11/15 for the post-wiki scenario. The relationship between perceived ease of use and perceived usefulness was found to be of the highest magnitude. The most notable difference across the two scenarios was that the relation between perceived ease of use and attitudes towards use was significant only in the first scenario. The results demonstrate that the proposed TAM-extended model could predict students' wiki acceptance.

Perceived usability affects greatly student's learning effectiveness and overall learning experience, and thus is an important requirement of educational software. The System Usability Scale (SUS) is a well-researched and widely used questionnaire for perceived usability evaluation. However, surprisingly few studies have used SUS to evaluate the perceived usability of learning management systems (LMSs). This paper presents an empirical evaluation of the SUS questionnaire in the context of LMSs' perceived usability evaluation. Eleven studies involving 769 students were conducted, in which participants evaluated the usability of two LMSs (eClass and Moodle) used within courses of their curriculum. It was found that the perceived usability of the evaluated LMSs is at a satisfactory level (mean SUS score 76.27). Analysis of the results also demonstrated the validity and reliability of SUS for LMSs' evaluation, and that it remains robust even for small sample sizes. Moreover, the following SUS attributes were investigated in the context of LMSs evaluation: gender, age, prior experience with the LMS, Internet self-efficacy, attitude towards the Internet and usage frequency of the LMS.

This study examines the acceptance of technology and behavioral intention to use learning management systems (LMS). In specific, the aim of the research reported in this paper is to examine whether students ultimately accept LMSs such as eClass and the impact of behavioral intention on their decision to use them. An extended version of technology acceptance model has been proposed and used by employing one of the most reliable measures of perceived eased of use, the System Usability Scale. 345 university students participated in the study. The data analysis was based on partial least squares method. The majority of the research hypotheses were confirmed. In particular, social norm, system access and self-efficacy were found to significantly affect behavioral intention to use. As a result, it is suggested that e-learning developers and stakeholders should focus on these factors to increase acceptance and effectiveness of learning management systems.

The present article examines the relationship between student personality, use of social media and their academic performance and engagement. Specifically, this article examines the relationship of students' Facebook (FB) use and personality characteristics using the Big Five Personality Test. This is focused on (a) student engagement; (b) time spent preparing for class; (c) time spent in co-curricular activities; and (d) academic performance. 204 higher education students participated in the study. Results illustrate that FB time was significantly positively correlated to student engagement and time spent preparing for class. Sharing links activity was positively correlated with student engagement and playing FB games with time spent preparing for class. However, sending private messages and status updates were significantly negatively correlated with student engagement and time spent preparing for class. Also, viewing videos was negatively correlated with time spent in co-curricular activities. Chatting on FB and viewing photos found to be the most popular activities. Moreover, students' extraversion, conscientiousness, openness to experience were positively correlated to student engagement. In addition, extraversion had a positive relationship with time spent in co-curricular activities, although agreeableness had a negative relationship. Implications of the study for the instructors and the students are also discussed.

This study examines the relationship of the Twitter's use with the students' learning outcome in a series of well-organised educational activities. Three studies were conducted in the context of two academic courses. In all three studies, the students who participated in the process received a higher laboratory grade than the students who did not participate. Students' conscientiousness and openness to experience were related to their activity in one study. However, no relationship between the students' personality traits and their grade was unveiled. Moreover, the students' interventions in the activities are examined, as well as the differentiation in their attitudes towards social media use in learning. The implications of the results are discussed and a comparison with other studies is presented.

The influence of students' non-cognitive characteristics on their learning performance constitutes a significant but rather unexplored topic. The goal of the research presented in this article, is to examine the relation between the students' personality characteristics (as measured using the Big Five Personality Test) and their learning outcome in the context of four framed wiki-based learning activities. 368 university students participated in the studies. Meta-analysis of results indicates that learning gain was significant negatively correlated with one of the five basic personality dimensions, namely Extraversion. Also, agreeableness was significant positively correlated with learning gain. Moreover, conscientiousness and emotionally stability were significant positively correlated with logged wiki edits that students made in this activity. It is argued, and discussed, that results from such studies can lead to useful conclusions regarding the design of appropriate activities and the creation of more effective collaborative teams in the context of wiki-based web activities.

A considerable interest in using Web 2.0 technologies such as wikis in education has been observed recently. Despite the advantages of the wiki technology, a number of questions concerning design of appropriate activities and their learning effectiveness remain open. In this paper, we present the results of three activities involving first-year university students using wikis to learn basic concepts related to information technology. Three activities of different classes were designed and delivered to the students using the framework proposed by West and West (2009). In all studies, a one-group pretest-posttest design was adopted. Results illustrated significant improvement in learning outcomes, particularly for students with low initial performance. The average students' questionnaire score jumped from 39.0/100 to 57.3/100. No significant effect of both students' role in the activity and their school stream on learning gain was observed. Finally, regardless of the activity's class and learning goal, a persistent pattern of high learning gain was observed.

Given that educational technology has increased tremendously, usability testing is a necessity to maximize the efficiency of technological tools in education. The findings of a systematic review including 42 research papers that evaluated the educational technologies' perceived usability with the Post-Study System Usability Questionnaire (PSSUQ) and the Computer System Usability Questionnaire (CSUQ) are presented in this article. The results were categorized according to the following factors: (a) score derived from evaluating usability with PSSUQ/CSUQ, (b) type of educational technology employed, (c) subject studied, (d) educational stage, (e) participant type, (f) age, and (g) participant count in each survey. The usability levels were found to be satisfactory (M = 72.75, SD = 15.12) from the statistical analysis of all surveys (N = 58). The mobile applications category showed a very good mean PSSUQ/CSUQ score (M = 81.53, SD = 12.61) followed by the multimedia category with 73.89 (SD = 19.69) and internet platforms (M = 73.23, SD = 7.74). The educational stage (p = 0.01) and the participant type (p = 0.005) seem to relate to the obtained PSSUQ/CSUQ scores. However, the participants' age, the subject being studied, or the participant count in each study did not exhibit any significant correlation with the PSSUQ/CSUQ scores. Over the course of time, a marginal non-statistically significant improvement was noted in terms of perceived usability (p = 0.136). [ABSTRACT FROM AUTHOR]

Usefulness and ease of use proved to be key determinants of the acceptance and usage of e-learning. On the contrary, little is known about students' perceptions in a blended learning setting. In this paper, the Technology Acceptance Model (TAM) was utilised, in order to investigate Greek university students' attitudes toward blended learning. The goal of the study was twofold. First, to investigate whether the students' perceptions in a blended learning setting were comparable with other studies reporting perceptions in the context of distant learning. Second, to investigate variation in students' perceptions before and after actual system use. A sample of 130 students before actual system use and 102 students after the end of the semester was used. As derived from the model analysis using partial least squares, the e-learning system was well accepted and the majority of our hypotheses were confirmed. The most notable difference between pre- and post- use scenario was that perceived usefulness did not prove to have a significant effect on behavioral intention before system use, whereas, in the end, it appeared to be significant. The results are compared with similar studies focused on e-learning acceptance. The implications, both for the designer of a blended learning course as well as for the educational community, are also discussed. (Contains 8 tables and 2 figures.)

Purpose: The purpose of this paper is to compare the effect of different representations while teaching basic algorithmic concepts to novice programmers. Design/methodology/approach: A learning activity was designed and mediated with two conceptually different learning environments, each one used by a different group. The first group used the learning environment "Visual Flowchart", which enables the students to construct and examine an algorithm using visual representation based on actual flowchart objects. The second group used the software "Language Interpreter", which allows the students to express an algorithms using pseudocode. Findings: Analysis of results among the two groups showed no statistically significant differences in the students' performance with respect to the tool they used to solve the activity, the school stream they followed in high school and their gender. Research limitations/implications: The lack of difference among the two groups could be attributed to the non-complicated nature of the given activity. In addition, longitudinal studies of the effect of the different representation in the frame of an introductory first semester academic course in computer science could further validate the results. Practical implications: Two alternative learning environments aimed to support learning of basic programming skills. Originality/value: Two alternative learning environments were presented and discussed in detail, aimed to support learning of basic programming skills. The conclusions of the present study are in contrast to the research that has taken place in the past which compared usage of flowcharts and pseudocode to educate novice programmers, and wider adoption of "flowcharts" was depicted.

During the last years, development of open learning environments that support effectively their users has been a challenge for the research community of educational technologies. The open interactive nature of these environments results in users experiencing difficulties in coping with the plethora of available functions, especially during their initial efforts to use the system. In addition,--from the tutors' perspective--the problem solving strategies of the students are often particularly difficult to identify. In this paper, we argue that such problems could be tackled using machine learning techniques such as Bayesian Networks. We show how we can take advantage of log files obtained during field studies to build an adaptive help system providing the most useful support to the student, according to the state of interaction. On the other hand, we attempt to support the tutor, by automating the process of diagnosing students' problem solving strategies using Bayesian Networks. The presented approaches are discussed through examples of two prototypes that have been developed and corresponding evaluation studies. These studies have shown that the proposed approach can effectively support the tasks of students and tutors in such open learning environments. (Contains 7 figures and 2 tables.)