Psychological security in the digital classroom CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 Psychological security in the digital classroom Larysa P. Zhuravlova1, Liubov V. Pomytkina2, Alla I. Lytvynchuk1 and Tetiana V. Mozharovska1 1Polissia National University, 7 Staryi Blvd., Zhytomyr, 10008, Ukraine 2State University “Kyiv Aviation Institute”, 1 Liubomyra Huzara Ave., Kyiv, 03058, Ukraine Abstract. The rapid digitalization of education, accelerated by the COVID-19 pan- demic, has transformed how teachers engage with information and communication technologies (ICT). This study empirically investigates the psychological security of higher education teachers (N = 59) as they navigate between traditional (classroom, offline) and distance (online) learning environments. Using a mixed-methods ap- proach combining associative techniques, semantic field analysis, and statistical evaluations, we examined teachers’ emotional perceptions and subjective safety assessments across learning modalities. Results revealed significant differences in how teachers associate with distance versus traditional learning, with the former evoking primarily ICT-related and negative emotional associations, while the latter elicited communication-focused and positive associations. Notably, our analysis uncovered a complex relationship between emotional perception and psychological security that varied based on the time spent engaged in online teaching. Teach- ers with moderate online engagement (6-18 hours weekly) demonstrated the most positive associations with distance learning but paradoxically reported feeling less secure in this environment. Conversely, those with extensive online teaching loads (>18 hours) developed increasingly neutral emotional responses while reporting similar security levels across both modalities. The findings suggest that psycho- logical security in digital learning environments is shaped by complex interactions between technological engagement, interpersonal communication opportunities, and individual differences among educators. These insights have important implications for developing institutional support systems, balanced teaching schedules, and targeted psychological interventions for educators navigating increasingly digital educational spaces. Keywords: psychological security, distance education, information and communi- cation technologies, technostress, higher education, digital learning environments, teacher perceptions, COVID-19 1. Introduction Scientific and technological progress is rapidly gaining momentum and covers all areas of personality’s life activity. Today, no sphere of public life, including educational, is effective without the involvement and implementation of scientific and technical means. The involvement of developments of scientific and technological progress in the educational process is particularly rapid now – in a global pandemic caused by the spread of viral infection COVID-19 [16, 17]. One of the ways to implement information and communication technologies is the introduction of distance learning. Distance learning is defined as an individualized process of acquiring knowledge, skills, abilities and ways of human cognitive activity, which occurs mainly through the indirect interaction of distant participants of the educational process in a specialized environment that operates on the basis of psychological, pedagogical, information and � 0000-0003-4020-7279 (L. P. Zhuravlova); 0000-0002-2148-9728 (L. V. Pomytkina); 0000-0001-9805-7416 (A. I. Lytvynchuk); 0000-0001-9628-2994 (T. V. Mozharovska) # lpz2008@ukr.net (L. P. Zhuravlova); Lyubvit@ukr.net (L. V. Pomytkina); lytvynchukalla@gmail.com (A. I. Lytvynchuk); mozharovska.t@gmail.com (T. V. Mozharovska) ~ https://apsx.nau.edu.ua/pomytkina-liubov-vitaliivna-2/ (L. V. Pomytkina) CTE Workshop Proceedings © Copyright for this article by its authors, published by the Academy of Cognitive and Natural Sciences. This is an Open Access article distributed under the terms of the Creative Commons License Attribution 4.0 International (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 442 https://doi.org/10.55056/cte.918 https://orcid.org/0000-0003-4020-7279 https://orcid.org/0000-0002-2148-9728 https://orcid.org/0000-0001-9805-7416 https://orcid.org/0000-0001-9628-2994 mailto:lpz2008@ukr.net mailto:Lyubvit@ukr.net mailto:lytvynchukalla@gmail.com mailto:mozharovska.t@gmail.com https://apsx.nau.edu.ua/pomytkina-liubov-vitaliivna-2/ https://acnsci.org/cte https://creativecommons.org/licenses/by/4.0/deed.en https://acnsci.org CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 communication technologies [15]. We can say that distance learning is implemented using a set of modern technologies that ensure the process of providing and receiving information in an interactive mode with the use of information and communication technologies by all participants in the educational process. It is obvious that the main role in the implementation of distance (online) education, as well as, in fact, traditional (classroom, offline), is played by information and communication technologies. The latter, in turn, are defined as technologies for creating, accumulating, storing and accessing electronic resources of educational programs and training materials, providing and supporting the educational process using specialized software and means of information and communication, including the Internet [15]. It is the Internet that reveals the possibilities of virtual connection and communications. 2. Literature review Empirical research on educational technologies used in distance learning has be- come widely known. In particular, Anderson and Rivera-Vargas [2] identified and critically substantiated the main dimensions of using digital technologies in distance education, which led to significant changes, namely: reducing the quality of education; restriction of application of new knowledge development methods; copyright infringe- ment; excessive idealization of information and communication technologies; violation of private information due to the widespread use of social media in distance education [2]. At the same time, Anderson [1] notes that social media, as a tool of information and communication technologies, is a major component of commercial, entertainment and, of course, educational activities. Education has a unique opportunity to control and improve their own practices through the dissemination of social media, which are effective for all participants of the educational process. In particular, teachers, educators and mentors have additional opportunities to communicate with students. An important aspect of this connection is the control and intervention in the learning process in order to increase the effectiveness of both teaching and learning. New ways of finding, receiving and exchanging educational information are becoming available for learners (pupils, students) [1]. Pomytkin, Pomytkina and Ivanova [18], Sancho-Gil, Rivera-Vargas and Miño-Puigcercós [19] point out that the development of ICT has caused excessive concern about its ability to solve educational problems and improve the quality of learning. Such a situation requires the development and implementation of new digital technologies in education for effective digital inclusion in order to expand public knowledge about the possibilities of using information technology in the educational environment. The urgent need for the implementation and implementation of distance learning creates excessive excitement and uncertainty among all participants of the educational process. Thus, Anderson [1] notes that the main difference between distance learning and traditional is the exhaustion of its participants. Distance learning, accompanied by the intensive use of information and communica- tion technology tools, in particular, the inclusion in the digital information environment of participants of the educational process, leads to a deterioration in psychological well-being and information stress. The latter, in turn, is associated with the long-term use of information and communication technologies, in particular, the Internet [11]. Social networks, watching news, consuming information, etc. lead to increased information stress and reduce the level of psychological security of the personality. The problem of information and psychological security is related to such psychological aspects as the perception, preservation, processing and use by participants in the 443 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 educational process of a certain information array [12]. The concept of psychological security can be described as a state of psychological safety and the ability of the personality to withstand unpleasant external and internal influences. Psychological security is an important factor of interpersonal interaction [4, 5]. The latter is significantly reduced in terms of distance learning, which is confirmed by scientific research. A study conducted by Hu et al. [8] reported that the lower the level of psychological security of the personality, the higher the level of distance interaction. The dependence of a sense of psychological security in terms of distance or traditional learning is evidenced by the results of several studies. In particular, the relationship between psychological security and social networks is revealed [21], which is one of the main tools of interaction between participants in the educational process in distance learning. Recent research has expanded our understanding of psychological security in digital contexts. Stewart and Lacey [22] criticize the technocratic approach to information security awareness, highlighting that simply providing facts about security does not adequately change behavior. They argue that understanding bounded rationality, mental models, and psychological factors is essential for effective security commu- nications. Similarly, Enrici, Ancilli and Lioy [6] identify psychological dimensions relevant to information technology security, including cognitive hacking, hacker profil- ing, and human errors, emphasizing that purely technical approaches to security are insufficient. The paradigm of information-psychological confrontation has evolved significantly in recent years. Karayani and Karayani [10] describe how strategic communications now employ both “hard power” (coercion) and “soft power” (attraction) methods, with trends moving from overt to covert forms of influence and from immediate to long-term strategic impacts. This evolution has particular relevance in educational contexts, where participants may experience subtle information-psychological pressures. The concept of technostress, as explored by Setyadi, Widagdo and Susanto [20], describes mental stress employees experience due to information and communication technologies in the workplace. Their research revealed that age perceptions, both cognitive age (feeling young) and chronological age (actual age), affect how individ- uals experience technostress. This framework provides valuable insight into why educators might experience varying levels of psychological security when using digital technologies. Velki and Šolić [24] developed and validated the Behavioral-Cognitive Internet Security Questionnaire (BCISQ) to measure information security awareness among users. Their work illustrates the growing recognition that behavioral and cognitive factors are central to understanding security in digital environments, rather than merely technical controls. Given the significant amount of research on the study of psychological security and information and communication technologies, the aspect of psychological safety of teachers of higher education institutions in the conditions of using ICT remains insufficiently studied. The purpose of the research is an empirical study of the psychological safety of teachers of higher education institutions in the conditions of using information and communication technologies. In our study, we made assumptions that the teachers of higher education institutions evaluate traditional (classroom, offline) learning safer than distance (online) learning. 444 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 3. Research methods The study of psychological safety in the use of ICT was implemented during the autumn semester of 2020. Teachers of higher education institutions (𝑁 = 59) took part in the study, including 48 women (81%) and 11 men (11%). The age of respondents varies between 25–75 years, the largest share are teachers aged 25–44 years (75%), 11 teachers aged 45–60 years (19%) and 4 teachers aged 61–75 years (7%). To study the features of psychological safety in traditional (classroom, offline) and distance (implemented as a measure to combat the spread of coronavirus disease (COVID-19)) forms of studying was developed and implemented author’s questionnaire “Psychological security in conditions of using ICT”. Its validity and reliability were ensured by using the method of independent expert evaluations. The questionnaire contained three components that assess both the conditions of distance learning and its psychological component: determining the intensity of involvement in distance learning (time spent), the study of associations on different forms of learning and the subjective level of psychological security (on a five-point scale) during distance and full-time forms of education. The method of frames (schemes) was used for qualitative and quantitative analysis of associations. This method allows you to group associations by certain descriptive characteristics that can be applied to abstract concepts: 1) actions, states and charac- teristics of the word-stimulus, 2) actions, states, characteristics of other subjects, 3) feelings and emotions [13] and the method of expert assessments. Methods of math- ematical statistics were used for statistical processing of the obtained quantitative data (descriptive statistics, comparison of dependent samples (Student’s t-criterion), Spearman’s rank correlation analysis). Automated data processing was performed using the IBM SPSS Statistics 26 and the ArcGIS software packages. Distance learning Traditional learning 0 10 20 30 40 50 60 70 Type of learning A ss oc ia ti on ty p es (% ) Negative Neutral Positive Figure 1: Emotional perception of distance and traditional learning by teachers of higher education institutions (percentage). 4. Results and discussions According to the results of empirical research, the frequency hierarchy of asso- ciations for the phrases “distance learning” and “full-time learning” was revealed. Analysis of the results shows that teachers of higher education institutions associate the phrase “distance learning” primarily with ICT: “computer” (6%), “Internet” (6%), 445 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 “Moodle, Classroom, Viber” (4%); with an evaluative attitude: “fast” (4%), “imperfect” (4%), also significant is the affective component, which has a negative emotional color: “stress” (4%). The hierarchy of associations for the phrase “full-time education” differs significantly from the previous one. The main associations are aimed at interaction, and interper- sonal connection - “communication” (17%); identification of specific characteristics of direct interaction - “live communication” (13%), “communication” (6%), “knowledge” (6%). Qualitative analysis of reactions (associations) based on the method of frames [13] allowed to make their qualitative characteristics. Field 1. Actions, states and characteristics of the word-stimulus. The phrase-stimulus “distance learning” is expressed through actions, states and characteristics that de- scribe the effectiveness of distance learning, its impact on the physical and mental state of the respondent: for example, “inappropriate”, “undesirable”, “low efficiency”, “exhausting”, “long”, “simple“, etc. The characteristics of the phrase-stimulus “full-time learning” mostly reflect its focus on the communicative process, such as “communica- tion”, “live communication”, “energy of live communication”, “simple”, “fast”. Field 2. Actions, states, characteristics of other subjects. In the associative chain of the phrase-stimulus “distance learning”, the interiorization is traced: the “other subject” is the respondent (for example, “insomnia”, “control”, “day mode”, “sleep”). At the same time, in the associative chain for the phrase-stimulus “full-time study”, respectively – exteriorization (for example, “students”, “I know where the child is”, “friends”, “noise”, “fun”, “long time to get to”, “waste of time”). Field 3. Feelings and emotions. The associative chain of the phrase-stimulus “distance learning” is characterized by the narrowness and uniformity of emotional characteristics, such as “sadness”, “worrying”, and so on. The associative chain of the phrase-stimulus “full-time learning” is dominated by concepts that characterize feelings and emotions. They differ in variety and bright emotional color, such as “fun”, “contact”, “attentive”, “emotions”. With the help of expert assessments, the associations were grouped into three groups: “negative”, “positive” and “neutral”. Negative associations include those that have an expressed negative evaluation attitude or emotional coloring, such as “sadness”, “horror”, “forced step”, “low efficiency”, and so on. Neutral associations include those that reflect events, objects, phenomena, objective reality, such as the “Internet”, “audience”, “Zoom”, etc. Positive associations include those that have a positive emotional color or evaluation, such as “fun”, “live communication”, “good feedback”, and so on. By assigning a numerical value to each group of associations (”0” = “negative”, “1” = “neutral”, “2” = “positive”) and using methods of statistical data processing, it was found that associations of teachers of higher education institutions regarding distance and traditional education differ significantly (𝑡 = −4.801, 𝑝 ≤ 0.012) (table 1). It should be noted that in each of the three fields, respondents focused on the concept of time spent on distance and full-time study and their characteristics, such as “more time for themselves”, “fast”, “slow”, “waste of time”, “all day”, “round-the-clock access”, “work after work”, “no waste of time”, etc. Peculiarities of the perception of distance learning by employees of higher education institutions depending on how much time they spent on average during the working week on distance learning are presented in table 2. The most negative perception of distance learning is perceived by respondents who have been involved in it for less than 6 hours (58.3%). Respondents who spend more than 18 hours a week on distance learning also rate it rather negatively. The smallest number (32.0%) of negative associations regarding distance learning have respondents 446 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 Table 1 Differences in associations of employees of higher education institutions about full-time and distance learning. Paired samples test Distance Paired differences t df Sig. 2-tailed / Mean Std. Std. 95% Confidence full devia- error Interval of the difference time tion mean Lower Upper -.593 .949 .123 -.840 -.345 -4.801 58 .012 Table 2 Emotional perception of distance learning by teachers with different times of using ICT. Crosstabulation Associations to the phrase-stimulus Total“distance learning” Negative Neutral Positive Term of online Less than 6 Count 7 3 2 12 % within 58.3 25.0 16.7 100.0 6-18 Count 8 11 6 25 study (hours) % within 32.0 44.0 24.0 100.0 More than 18 Count 10 11 1 22 % within 45.5 50.0 4.5 100.0 Total Count 25 25 9 59 % within 42.4 42.4 15.3 100.0 who are involved in it for 6–18 hours. It should be noted that the more respondents were involved in distance learning, the less positive (4.5%) and more neutral (50.0%) associations they have with it. Those who spend an average of 6 to 18 hours a week on distance learning tend to describe it most positively. The results of the analysis of associations for the phrase-stimulus “full-time learning” are fundamentally different from the previous ones (table 3). Most positive associations (40.9%) regarding full-time education occur in teachers who spend the most time (more than 18 hours) on distance learning, and the least – in those who worked distantly the least (6 hours per week). The vast majority (61%) of respondents generally have a neutral perception of traditional (classroom, offline) learning. It is worth noting much lower rates of negative associations with the phrase-stimulus “full-time learning”, compared with distance (respectively, 3.4% and 42.4%). For a more detailed interpretation of the peculiarities of the perception of distance and full-time learning, the subjective level of psychological security feeling of teachers of higher education institutions during the implementation of both forms of education was determined (table 4). In general, respondents rate their level of psychological security as equally mediocre in distance and full-time learning (�̄� = 2.808 and �̄� = 2.900, respectively). However, we observe contradictions between the emotional perception of online/offline learning and the assessment of their own psychological security in their implementa- tion depending on the time of using ICT. Thus, full-time learning is assessed as the 447 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 Table 3 Emotional perception of full-time learning by teachers with different time of using ICT. Crosstabulation Associations to the phrase-stimulus Total“full-time learning” Negative Neutral Positive Term of online Less than 6 Count 1 7 4 12 % within 8.3 58.3 33.3 100.0 6-18 Count 1 16 8 25 study (hours) % within 4.0 64.0 32.0 100.0 More than 18 Count 0 13 9 22 % within 0.0 59.1 40.9 100.0 Total Count 2 36 21 59 % within 3.4 61.0 35.6 100.0 Table 4 Level of psychological safety of teachers of higher education institutions (�̄�). Term of online learning (hours) Online (distance) learning Offline (full-time) learning Less than 6 2.820 3.307 6-18 3.305 2.694 More than 18 2.576 2.423 Total 2.900 2.808 Less than 6 6-18 More than 18 2 2.2 2.4 2.6 2.8 3 3.2 3.4 Hours spent on online learning per week P sy ch ol og ic al sa fe ty le ve l (s ca le 1 -5 ) Online learning Traditional learning Figure 2: Comparative psychological safety levels in online and traditional learning based on weekly engagement hours. most dangerous (�̄� = 3.307) by teachers who are most positive about it, and who spend more than 18 hours a week on distance learning. The least dangerous (�̄� = 2.423) full-time learning is for teachers who are involved in distance learning for less than 6 hours. The most dangerous (�̄� = 3.305) feel in the online environment those who spend from 6 to 18 hours on it. To find significant differences between the indicators of experiencing a sense of security in the implementation of online/offline learning by teachers of higher ed- 448 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 ucation institutions we used calculations of the Student’s t-criterion (table 5). No statistically significant differences were found, but some trends were indicated: teach- ers who are involved in distance learning for less than 6 hours tend to perceive the online environment as safer (𝑡 = 1.442, 𝑝 ≤ 0.175), those who work from 6 to 18 hours, on the contrary, as more dangerous (𝑡 = −1.51, 𝑝 ≤ 0.144). Those who spent more than 18 hours distantly mediocrely assessed their own safety both offline and online (𝑡 = −0.731, 𝑝 ≤ 0.473). Table 5 The sense of security features of higher education institutions teachers with different time of using ICT in the conditions of online/offline learning. Paired samples test Term of Paired differences t df Sig. 2-tailed online Mean Std. Std. 95% Confidence training devia- error Interval of the difference (hours) tion mean Lower Upper Total -.084 1.734 .225 -.536 .367 -.375 58 .709 More than 18 -.272 1.750 .373 -1.048 .503 -.731 21 .473 6-18 -.416 1.348 .275 -.986 .152 -1.51 23 .144 Less than 6 .846 2.115 .586 -.432 2.124 1.442 12 .175 Spearman’s correlation analysis was used for a more detailed interpretation (table 6). It was found that there is a statistically significant relationship between indicators of psychological safety in distance and offline learning for both respondents of the general sample (𝑟 = 0.358, 𝜌 ≤ 0.001) and teachers who are involved distantly for 6-18 hours (𝑟 = 0.528, 𝜌 ≤ 0.001). We do not observe such correlations in respondents who are engaged in online learning for a small or extremely large amount of time. Table 6 Relationships between psychological safety indicators in online/offline learning. Sample/term of online training (hours) Offline/Online Spearman’s rho Total sample Correlation coefficient .358** Sig. (2-tailed) .005 𝑁 59 More than 18 Correlation coefficient .241 Sig. (2-tailed) .280 𝑁 22 6-18 Correlation coefficient .528** Sig. (2-tailed) .008 𝑁 24 Less than 6 Correlation coefficient .327 Sig. (2-tailed) .276 𝑁 13 ** Correlation is significant at the 0.01 level (2-tailed). The findings of our study reveal several interesting patterns regarding psychological security in online and offline learning environments that align with and extend previous research. 449 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 Our results regarding the association of distance learning with ICT tools (“computer,” “Internet,” “Moodle, Classroom, Viber”) reinforce findings by Anderson [1] who noted that digital tools have become inseparable components of the educational process. However, while Anderson [1] emphasized the opportunities these tools provide, our research highlights the emotional complexity they introduce. The emotional perception of distance learning revealed in our study supports findings by Kislyakov [11] about information stress associated with prolonged ICT use. The negative emotional coloring (“stress”) associated with distance learning in our study exemplifies this relationship. Furthermore, our finding that teachers who spend more than 18 hours weekly on distance learning develop increasingly neutral rather than positive associations aligns with concept of emotional fatigue among educators during massive shifts to online teaching [3]. The strong association of traditional learning with interpersonal interaction (“com- munication,” “live communication”) supports assertion by Edmondson [5] that psy- chological security is fundamentally linked to interpersonal interactions. Our finding that full-time learning has significantly fewer negative associations (3.4%) compared to distance learning (42.4%) indicates that the reduction in interpersonal interaction may indeed compromise psychological security, as suggested by Hu et al. [8]. Intriguingly, our data revealed a complex relationship between actual security feelings and emotional perceptions. While distance learning evoked more negative associations, the subjective ratings of psychological security were similar for both modalities (�̄� = 2.808 for distance and �̄� = 2.900 for traditional learning). This discrepancy suggests that emotional responses to learning modalities may not directly translate to conscious security assessments, a nuance not previously highlighted in the literature. The correlation between psychological safety perceptions in online and offline en- vironments among those with moderate online teaching loads (6-18 hours) suggests that adaptability to teaching context may be optimized at this level of engagement. This supports position by Traxler [23] that balanced integration of technology, rather than minimal or excessive use, best serves educational objectives while maintaining psychological well-being. Our findings also connect with the technostress literature. Setyadi, Widagdo and Susanto [20] found that cognitive age (feeling young) helps reduce the influence of technostress, which may explain why different age groups in our sample reported varying levels of psychological security. Similarly, Moustafa, Bello and Maurushat [14] identified that psychological traits and individual differences among computer system users determine their ability to counter information security threats, which aligns with our observation that teachers’ responses to ICT environments are highly individualized. The relationship between hours spent in online teaching and perceived psychological security shows an interesting inverted U-shaped pattern (figure 2). This non-linear relationship suggests that moderate engagement with distance learning technologies (6-18 hours) might represent an optimal balance point where teachers have enough exposure to develop comfort with the technology without experiencing the negative effects of digital overexposure noted by Pomytkin, Pomytkina and Ivanova [18]. Based on our findings and the integration of existing literature, we propose a conceptual model (figure 3) that illustrates how personal factors, contextual factors, and psychological mediators interact to influence perceived psychological security in ICT learning environments. This model provides a framework for understanding the complex interplay of factors that determine how educators experience security in digital teaching contexts. 450 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 Personal factors Age and experience ICT competence Digital adaptability Prior security beliefs Contextual factors Time demands Institutional support Communication quality Technical infrastructure Psychological mediators Technostress Emotional fatigue Perceived control Communication satisfaction Perceived psychological security Figure 3: Conceptual model of factors influencing perceived psychological security in ICT learning environments. 5. Practical implications The findings of this study have several important practical implications for higher education institutions implementing distance learning: First, our research suggests that teachers who spend moderate amounts of time (6-18 hours weekly) on distance learning report the most positive associations and adaptability. Institutions should consider this when designing teaching loads for online instruction to avoid both insufficient engagement and excessive screen time. The finding aligns with criticism by Stewart and Lacey [22] of technocratic approaches to information security, suggesting that optimal engagement with technology requires consideration of human factors rather than merely technical solutions. Second, given the higher negative emotional associations with distance learning, institutions should develop targeted psychological support programs for teachers engaged in online education. These might include emotional regulation workshops, digital well-being seminars, and regular check-ins focused on psychological security. As Gamble, Boyle and Morris [7] note in their research on ethical practice in telepsy- chology, psychological support in digital contexts requires specific attention to the unique stressors of the online environment. Third, since full-time learning is strongly associated with interpersonal communica- tion, distance learning platforms should prioritize features that enhance synchronous communication and social presence. This might include greater use of video confer- encing with social interaction components rather than asynchronous content delivery. This recommendation is supported by Soares and Lopes [21] highlighting the relation- ship between psychological security and social networks. Fourth, the similar levels of psychological security reported in both modalities suggest that a hybrid model combining elements of both traditional and distance 451 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 learning might optimize both pedagogical effectiveness and psychological well-being. Framework of integrating cybersecurity with psychological defense by Juurvee and Arold [9] provides a model for how technical and psychological aspects can be blended effectively. Finally, the contradictory relationship between emotional perception and security assessment indicates that teachers’ experiences are highly individualized. Institutions should offer personalized digital adaptation training that accounts for individual differences in technological comfort, teaching style, and psychological needs. This aligns with findings by Moustafa, Bello and Maurushat [14] on the importance of individual differences in determining responses to digital security threats. Implementation of these recommendations may help mitigate the negative psycho- logical impacts of rapid transitions to distance learning while preserving the benefits of technological integration in higher education. 6. Limitations and future research directions While this study provides valuable insights into the psychological security of higher education teachers in ICT environments, several limitations should be acknowledged. The study was conducted with a relatively modest sample size (𝑁 = 59) from Ukrainian higher education institutions during the early period of pandemic-induced distance learning (autumn 2020). Generalizability to other educational contexts and later stages of the pandemic may be limited. The assessment of psychological security relied on self-report measures and associations, which may be subject to social desirability bias and may not fully capture unconscious aspects of security experiences. The study’s cross-sectional nature limits our ability to track how perceptions of psychological security evolved as teachers gained more experience with distance learn- ing technologies. Additionally, the research occurred during a period of rapid, forced transition to online learning due to COVID-19, which may have influenced perceptions differently than planned, gradual implementations of distance learning would. The study also did not control for variations in technological infrastructure, platforms used, or institutional support, which may have influenced teachers’ experiences of psychological security. Future research should address these limitations through longitudinal designs tracking changes in psychological security over extended periods of distance teaching, inclusion of diverse international samples, mixed-methods approaches incorporating observational data, and examination of specific technological and institutional factors that might moderate the relationship between teaching modality and psychological security. Additionally, investigating how the findings might apply to other educational stakeholders, particularly students and administrative staff, would provide a more comprehensive understanding of psychological security in contemporary educational environments. Exploring the implications of information-psychological impact frameworks proposed by Karayani and Karayani [10] in educational contexts could yield valuable insights into how subtle influences shape perceptions of security. Similarly, applying Velki and Šolić [24]’s Behavioral-Cognitive Internet Security Questionnaire to educational contexts might help institutions better assess and address the behavioral dimensions of information security in learning environments. 7. Conclusions 1. Psychological security is defined as a state of psychological protection from external and internal influences. In the conditions of distance learning the 452 https://doi.org/10.55056/cte.918 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 feeling of psychological safety of its participants decreases, in comparison with the conditions of traditional (classroom) learning. 2. There are differences in the perception of distance and traditional (full-time) learning among teachers of higher education institutions. Associations for the phrase “distance learning”, “full-time learning” are located in three semantic “fields”: teachers of higher education institutions associate distance learning with ICT and with feelings and emotions, full-time learning is associated with communication and interaction with others. There is a significant difference between distance and traditional learning associations: distance learning is perceived more negatively than full-time learning. 3. There is a statistically significant relationship between the feeling of psychological security of respondents in distance learning and the feeling of psychological security in offline learning. The subjective level of feeling of psychological security has average indicators, both in terms of distance and full-time learning. Teachers who spend a lot of time online tend to perceive more dangerous full-time learning. The least dangerous are those who are involved in distance learning for a short time. The most dangerous in the online environment feel those who spent on it an average of 6 to 18 hours. 4. Contradictions between the emotional perception of online/offline learning and the assessment of the level of their own psychological security in their implemen- tation depending on the time of using ICT were defined. 5. Integration of recent psychological security frameworks with our findings reveals that technostress, cognitive factors, and information-psychological impacts all contribute to how educators experience security in digital environments. Opti- mizing psychological security requires attention to both technological solutions and human factors. The research hypothesis was partially proved. We see prospects for further research in the study of the features of psychological security of all participants in the educational process in a wide sample, as well as exploration of how frameworks from informa- tion security psychology can enhance our understanding of educational technology implementations. References [1] Anderson, T., 2019. Challenges and Opportunities for use of Social Media in Higher Education. Journal of Learning for Development, 6(1). Available from: https://jl4d.org/index.php/ejl4d/article/view/327. [2] Anderson, T. and Rivera-Vargas, P., 2020. A critical look at educational technology from a distance education perspective. Digital Education Review, (37), pp.208–229. Available from: https://revistes.ub.edu/index.php/der/article/view/30917. [3] Chernyshov, S.A., 2021. Massive shift of schools towards distance learning in the estimates of a local pedagogical community. Obrazovanie i nauka, 23(3), pp.131– 155. Available from: https://doi.org/10.17853/1994-5639-2021-3-131-155. [4] Edmondson, A., 1999. Psychological Safety and Learning Behavior in Work Teams. Administrative Science Quarterly, 44(2), pp.350–383. Available from: https://doi.org/10.2307/2666999. [5] Edmondson, A.C., 2004. Psychological Safety, Trust, and Learning in Organi- zations: A Group-Level Lens. In: R.M. Kramer and K.S. Cook, eds. Trust and distrust in organizations: Dilemmas and approaches. New York: Russell Sage Foundation, pp.239–272. 453 https://doi.org/10.55056/cte.918 https://jl4d.org/index.php/ejl4d/article/view/327 https://revistes.ub.edu/index.php/der/article/view/30917 https://doi.org/10.17853/1994-5639-2021-3-131-155 https://doi.org/10.2307/2666999 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 [6] Enrici, I., Ancilli, M. and Lioy, A., 2010. A psychological approach to information technology security. 3rd International Conference on Human System Interaction, HSI’2010 - Conference Proceedings. pp.459–466. Available from: https://doi.org/ 10.1109/HSI.2010.5514528. [7] Gamble, N., Boyle, C. and Morris, Z.A., 2015. Ethical Practice in Telepsychology. Australian Psychologist, 50(4), pp.292–298. Available from: https://doi.org/10. 1111/ap.12133. [8] Hu, J., Erdogan, B., Jiang, K., Bauer, T.N. and Liu, S., 2018. Leader humility and team creativity: The role of team information sharing, psychological safety, and power distance. Journal of Applied Psychology, 103(3), pp.313–323. Available from: https://doi.org/10.1037/apl0000277. [9] Juurvee, I. and Arold, M.U., 2021. Psychological defence and cyber security: Two integral parts of Estonia’s comprehensive approach for countering hybrid threats. Icono14, 19(1), pp.70–94. Available from: https://doi.org/10.7195/RI14.V19I1. 1628. [10] Karayani, A.G. and Karayani, Y.M., 2021. Information and psychological impact in the context of strategic communications paradigm. National Psychological Journal, 14(1), pp.3–14. Available from: https://doi.org/10.11621/npj.2021.0101. [11] Kislyakov, P., 2020. Psikhologicheskaya ustojchivost’ studencheskoj molodezhi k informaczionnomu stressu v usloviyakh pandemii COVID-19. Perspectives of Science & Education, 47(5), pp.343–356. [12] Krasnyanskaya, T.M. and Tylets, V.G., 2019. Technological components for pro- viding the information and psychological safety of personality in the conditions of distance learning. Information Technologies and Learning Tools, 73(5), p.249–263. Available from: https://doi.org/10.33407/itlt.v73i5.2546. [13] Mironova, N.I., 2011. Associative experiment: methods of data analysis and analysis based on the universal scheme. Voprosy psikholingvistiki, (14), pp.108– 119. Available from: https://tinyurl.com/5bswdbmv. [14] Moustafa, A.A., Bello, A. and Maurushat, A., 2021. The Role of User Behaviour in Improving Cyber Security Management. Frontiers in Psychology, 12. Available from: https://doi.org/10.3389/fpsyg.2021.561011. [15] Polozhennia pro dystantsiine navchannia, 2013. Available from: https://zakon. rada.gov.ua/laws/show/z0703-13#Text. [16] Pomytkin, E.O., 2020. Strategy and Tactics of Conscious Psychologi- cal Counteraction of Humanity to Viral Diseases. In: V.H. Kremen, ed. Psychology and education infighting COVID-19: online manual. Yurka Lyubchenka, pp.17–30. Available from: https://drive.google.com/file/d/ 1yDw7bZfGo0Ny94KsbcBJWfDlcZ8wHXN9/view. [17] Pomytkin, E.O. and Pomytkina, L.V., 2020. Strategy and Tactics of Conscious Psychological Counteraction of Humanity to Viral Diseases. In: V. Rybalka, A. Samodryn, O. Voznyuk, V. Morgun, E. Pomytkin and N. Samodryna, eds. Philosophy, psychology and pedagogics against COVID-19. Zhytomyr: Oleksiy Yevenok, pp.119–133. Available from: http://emed.library.gov.ua/jspui/handle/ 123456789/160. [18] Pomytkin, E.O., Pomytkina, L.V. and Ivanova, O.V., 2020. Electronic resources for studying the emotional states of new Ukrainian school teachers during the COVID- 19 pandemic. Information Technologies and Learning Tools, 80(6), p.267–280. Available from: https://doi.org/10.33407/itlt.v80i6.4179. [19] Sancho-Gil, J.M., Rivera-Vargas, P. and Miño-Puigcercós, R., 2020. Moving beyond the predictable failure of Ed-Tech initiatives. Learning, Media and Tech- nology, 45(1), pp.61–75. Available from: https://doi.org/10.1080/17439884. 2019.1666873. 454 https://doi.org/10.55056/cte.918 https://doi.org/10.1109/HSI.2010.5514528 https://doi.org/10.1109/HSI.2010.5514528 https://doi.org/10.1111/ap.12133 https://doi.org/10.1111/ap.12133 https://doi.org/10.1037/apl0000277 https://doi.org/10.7195/RI14.V19I1.1628 https://doi.org/10.7195/RI14.V19I1.1628 https://doi.org/10.11621/npj.2021.0101 https://doi.org/10.33407/itlt.v73i5.2546 https://tinyurl.com/5bswdbmv https://doi.org/10.3389/fpsyg.2021.561011 https://zakon.rada.gov.ua/laws/show/z0703-13#Text https://zakon.rada.gov.ua/laws/show/z0703-13#Text https://drive.google.com/file/d/1yDw7bZfGo0Ny94KsbcBJWfDlcZ8wHXN9/view https://drive.google.com/file/d/1yDw7bZfGo0Ny94KsbcBJWfDlcZ8wHXN9/view http://emed.library.gov.ua/jspui/handle/123456789/160 http://emed.library.gov.ua/jspui/handle/123456789/160 https://doi.org/10.33407/itlt.v80i6.4179 https://doi.org/10.1080/17439884.2019.1666873 https://doi.org/10.1080/17439884.2019.1666873 CTE Workshop Proceedings, 2025, Vol. 12, pp. 442–455 https://doi.org/10.55056/cte.918 [20] Setyadi, H.J., Widagdo, P.P. and Susanto, T.D., 2017. Cognitive age and chrono- logical age of the technostress that effect on satisfaction, performance, and intention of continue the use of information technology in the university. Pro- ceeding - 2017 3rd International Conference on Science in Information Technol- ogy: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. vol. 2018-January, p.330 – 335. Available from: https://doi.org/10.1109/ICSITech.2017.8257134. [21] Soares, A. and Lopes, M.P., 2014. Social networks and psychological safety: A model of contagion. Journal of Industrial Engineering and Management, 7(5), pp.995–1012. Available from: https://doi.org/10.3926/jiem.1115. [22] Stewart, G. and Lacey, D., 2012. Death by a thousand facts: Criticis- ing the technocratic approach to information security awareness. Informa- tion Management and Computer Security, 20(1), pp.29–38. Available from: https://doi.org/10.1108/09685221211219182. [23] Traxler, J., 2018. Distance learning—predictions and possibilities. Education Sciences, 8(1), p.35. Available from: https://doi.org/10.3390/educsci8010035. [24] Velki, T. and Šolić, K., 2019. Development and Validation of a New Measurement Instrument: The Behavioral-Cognitive Internet Security Questionnaire (BCISQ). International Journal of Electrical and Computer Engineering Systems, 10(1), pp.19– 24. Available from: https://doi.org/10.32985/ijeces.10.1.3. 455 https://doi.org/10.55056/cte.918 https://doi.org/10.1109/ICSITech.2017.8257134 https://doi.org/10.3926/jiem.1115 https://doi.org/10.1108/09685221211219182 https://doi.org/10.3390/educsci8010035 https://doi.org/10.32985/ijeces.10.1.3 1 Introduction 2 Literature review 3 Research methods 4 Results and discussions 5 Practical implications 6 Limitations and future research directions 7 Conclusions