Next Article in Journal
Students’ Workplace Readiness: Assessment and Skill-Building for Graduate Employability
Previous Article in Journal
Improvement of the Crude Glycerol Purification Process Derived from Biodiesel Production Waste Sources through Computational Modeling
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 14
Issue 3
10.3390/su14031748
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Modeling the Sustainable Educational Process for Pupils from Vulnerable Groups in Critical Situations: COVID-19 Context in Lithuania, Latvia, and Estonia

by
Alvyra Galkienė
1,*,
Ona Monkevičienė
1,2,
Lina Kaminskienė
1,
Ričardas Krikštolaitis
1,
Maile Käsper
2 and
Ilze Ivanova
3
1
Education Academy, Vytautas Magnus University, 44248 Kaunas, Lithuania
2
School of Educational Sciences, Tallinn University, 10120 Tallinn, Estonia
3
Faculty of Education, Psychology and Art, University of Latvia, LV-1586 Rīga, Latvia
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(3), 1748; https://doi.org/10.3390/su14031748
Submission received: 31 December 2021 / Revised: 23 January 2022 / Accepted: 29 January 2022 / Published: 3 February 2022
Browse Figures
Versions Notes

Abstract

:
The critical situation in education caused by COVID-19 has significantly reduced the involvement of pupils from vulnerable groups, particularly those with low learning achievements. The aim of this study is to reveal the modeling of the sustainable educational process and the factors that ensure optimal learning achievements of pupils from vulnerable groups in general education schools in critical educational transformation situations. To reveal the factors ensuring the sustainability of educational processes, this study was conducted in three Baltic countries (Lithuania, Latvia, and Estonia) involving 1432 subject teachers from public education schools. The results of the study highlight that self-regulatory collaborative learning has a sustainable, strong impact on the achievements of pupils with emotional and learning difficulties in various (stable and unstable) educational environments in all three countries. The development of digital skills, digital scaffolding, and technological provision for pupils with special educational needs enabled their teachers to have a sustainable positive impact on pupils’ learning achievements in Lithuania.

1. Introduction

COVID-19 has disrupted educational institutions worldwide, and this critical situation revealed that education systems must search for sustainable practices that ensure smoother transitions from one learning environment to another with or without a minimal negative impact on learners. In addition, COVID-19 has affected the educational systems of 190 countries worldwide. It has also disrupted learning in about 1.6 billion (94%) of the global learners’ population and about 99% of pupils in low- and lower-middle-income countries. Educational transformation processes during the COVID-19 pandemic have particularly affected the most vulnerable pupils living in deprived areas, villages, and pupils experiencing other difficulties [1] (p. 2).
The urgent need to organize teaching from a physical distance forced teachers and students to transfer educational activities to their homes without prior preparation, often lacking the proper tools, methods, and ideas on how to create not only academic but also socio-emotional capital [2]. After schools were closed and learning became remote, pupils’ wellbeing and quality of learning largely depended on the extent of how teachers and parents managed to master remote learning technologies [3].
Studies indicate that the difficulties experienced by pupils are related to the peculiarities of the technologies used, different possibilities of access to education, differences in contact and remote learning, lack of interpersonal communication, and experiences of uncertainty [4]. Unfortunately, the critical situation caused by COVID-19 has significantly reduced pupils’ involvement in the educational processes, and this situation became particularly acute for pupils from vulnerable groups and pupils with low learning achievements [5]. In many cases, remote learning approaches applied by teachers did not meet the needs of pupils with special educational needs. Only a few such approaches could be effectively used to teach these pupils. Moreover, the lockdown situation revealed a very high need for parental support when pupils with learning difficulties are learning at home [6]. However, families experiencing economic, social, or cultural difficulties could not fully master digital devices and, thus, could not professionally help their children [7]. Usually, under normal conditions, specialist support for such pupils is provided individually. However, the coordination of these services even under normal circumstances is sufficiently complicated. After the unexpected educational transformation caused by the COVID-19 pandemic, this support became a hard to overcome system barrier [8].
Studies have shown that, in the context of the COVID-19 pandemic, pupils with special educational needs and pupils from disadvantaged social backgrounds were placed in a situation of double disadvantage in education because they faced much more significant challenges than their peers. They were characterized by worse mental wellbeing, loss of learning skills and lack of progress, increased social isolation, and anxiety about the future [9]. The peculiarities of education systems, local communities, and online communication in different countries of the world have encouraged the search for a wide range of measures for the organization of education, including teleconferencing using cellphones, and other forms, reducing the level of marginalization and drop-outs from the educational processes [10]. Transformations in educational systems highlighted the need to reassess how educational processes are organized in schools and what are the main sustainability factors that positively impact learners’ participation and allow the achievement of learning goals based on the individual potentials of every learner [1] (p. 23).
The overview of the results of the first pandemic period studies [11] highlights the need for further research of remote teaching skills development, closer co-operation between teachers and parents, deeper education processes in uncertain conditions, pupils’ engagement and participation in learning processes, and the development of fundamental recommendations adapted to different educational, social, and cultural contexts. This actualized the problem of looking for factors that ensure the sustainability of the educational process and achievements of pupils with learning difficulties.
The aim of this study is to reveal the modeling of the sustainable educational process and the factors that ensure optimal learning achievements of pupils from vulnerable groups in general education schools in critical educational transformation situations.
Studies from different countries on educational challenges, specifically on children experiencing learning difficulties [7,12,13,14,15,16], have shown that the problems encountered are quite universal; however, some specific characteristics may emerge due to national contexts.
To reveal the factors ensuring the sustainability of educational processes, this study was conducted in three Baltic countries: Lithuania, Latvia, and Estonia. All three Baltic countries went through the same political and economic transformation, restoring their independence in 1991. The education systems of these countries were affected by the same processes as the economic transition from centralized planning to a neoliberal free market [17].
Lithuania, Latvia, and Estonia, three Baltic countries, had similar starting positions after the restoration of their independence in 1990, yet their education systems have gained distinct and specific developmental trends [18]. Comparing the results of PISA, Estonia demonstrates the highest achievements, whereas Latvia and Lithuania are around the OECD average [19]. The population of teachers in these countries is rather old, the majority is around 50 years and older. It is worth mentioning that Latvia in recent years managed to recruit more younger teachers as compared to Estonia and Lithuania.
During the pandemic in 2020 and spring 2021, the countries applied slightly different strategies in their educational systems. While Lithuania moved to a full school lockdown, Latvia has implemented a mixed approach to ensure school-based, remote, and blended learning. Pupils with special learning needs had a minimal remote learning experience in Latvia as the government aimed to ensure contact learning for the most vulnerable groups.
In Estonia, to address the COVID-19 risks, a school-based local approach was adopted in March 2020. The state has taken an approach that while general guidelines are provided by the ministry, school owners (mainly municipalities) and leaders must make decisions based on the local needs. The study performed in 2021 by Tammets et al. [20] in Estonia highlighted that the number of students with learning difficulties increased by 10%, namely, students who did not have learning difficulties gained them during remote learning. According to teachers, the number of students with learning difficulties almost doubled, about a quarter of the students at that time had permanent and temporary learning difficulties. These results are troubling because the increase of learning difficulties could affect further results in students’ academic achievements. To relieve that situation, 40% of the teachers supported these students by offering daily and weekly individual support, as needed [20].
In Latvia during the pandemic, The Ministry of Education allocated an additional 5 million to disadvantaged children, schools in the countryside, and for teachers to buy computers. Big telecommunication companies provided schools with computers and other technologies necessary to guarantee normal remote learning. Special attention was paid to cooperation with parents as they became teachers’ assistants and agents in teaching and learning at home especially for very young students [21].
In Lithuania, the sudden transition of schools to remote learning consolidated the efforts of the national government, schools, and voluntary society to provide all the pupils with computers and internet access [22], but there was not enough time to coordinate the procedures for the organization of remote learning at national and school level. The study by Daukšienė et al. [23] showed that a lack of criteria for choosing specific learning platforms and tools led to the choice of tools based on criteria of simplicity and notoriety rather than efficiency and sustainability. Merfeldaitė [24] and Kaminskienė et al. [25] identified links between teacher competencies and the development of remote education processes with particularly strengthened cooperation relations in school communities in extreme conditions.
In order to reveal sustainable education factors in unstable conditions, we focused on the three Baltic states—Lithuania, Latvia, and Estonia—due to their similar historical and economic contexts and at the same time growing differences in educational achievements.

2. Literature Review

The sustainability of the educational system may be defined in various ways, and this paper aims to highlight the need for a sustainable educational process following the principles of inclusive education. Furthermore, the characteristics of inclusive education may be better revealed by juxtaposing traditional versus inclusive education.
Transformation processes of traditional and inclusive education. The results of the research show that education is a system of social cohesion that is intensively influenced by political, economic, and social changes [26]. However, at the same time, it is most needed for the sustainability of educational processes that ensure the quality of results. Khalaf and Zin [27] stated that many theories explaining the educational process associate learning goals and the quality of results with the acquisition of knowledge and skills that are important in solving future problems. This idea is also present in the oldest, most widespread, behaviorism-based theory of traditional education. This approach to education is based on the transfer of knowledge to pupils, and the content of education is usually related to the learning of traditional, predetermined subjects [28]. The possibilities of pupils’ equal participation in the educational process are limited. Some pupils are marginalized by the monolithic educational content and process based on established norms focusing on homogeneous groups of pupils [29,30]. Meanwhile, the fourth goal of the 2030 Agenda for Sustainable Development [31] actualizes socio-educational justice in education, highlighting quality, universally accessible education as the basis for the sustainable development of an inclusive society. The Global Education Monitoring Report 2020 [32] conceptualizes inclusive education with two criteria: full participation of all persons—regardless of health, cultural, or social differences—in the educational process and the removal of barriers to participation and optimal results. However, the sustainability of inclusive education is subject to significant conditions, which are determined by direct, intra-school, and indirect, external processes based on agreed values and concepts. As a result, the use of traditional and inclusive education approaches in European educational practices is unevenly established [33]. In cases where the concept of inclusive education is linked solely to solving the learning problems of pupils with special needs, special and traditional inclusive education processes intertwine in the education system, and individual assistance or training in individual groups is most often used to overcome learning barriers [34,35].
Inclusion processes based on the approach of Universal Design for Learning (UDL) acknowledge the differences of all pupils and emphasize the variety of the ways of learning. When the teacher preventively foresees learning barriers and proposes scaffolding to every pupil, it results in education accessibility and the possibility of joint learning and allows successful achievement of optimal personal results. Sustainable participation of the pupils in education processes is enhanced by UDL components that encourage the pupils’ engagement and self-regulatory learning [29,35].
Overcoming barriers in the inclusive education process based on the UDL approach. The education processes of heterogeneous groups always presuppose the need for educational support [35]. It is, therefore, important to promote teachers’ confidence in the abilities of self-regulatory learning of all pupils, recognizing their uniqueness, while treating difficulties as barriers that are overcome by the universal modeling of educational processes [36,37]. In this manner, support for pupils with special educational needs is transferred from specialized classrooms to general classrooms, strengthening the role of teacher support through the modeling of the educational process and cooperation with specialists [38]. Teachers, by preventively anticipating possible barriers to pupils’ learning in the educational process, make planned adaptations to the educational process and implement them not through individual intervention but by treating these adaptations as an integral part of the lesson plan [39]. They achieve successful learning for all through the variety of methods offered, the modeling of the goal of flexible education, cultural relationality, and meaningful content. All this forms the basis for the differentiation of education [40,41]. By modeling a barrier-free learning environment, they create interdisciplinary links of professional cooperation and, by acting together, enable the participation of pupils with special educational needs in joint learning activities [42,43,44,45]. Studies have shown that the focused efforts of educators to create an engaging environment through academic, emotional, and social learning lead to greater social concentration, emotional openness, class climate awareness, satisfaction, and academic aperture. In addition, engaging students with disabilities in joint learning activities increases their self-regulatory learning abilities. As a result, the quality and achievements of pupils’ participation in the educational process are improving, regardless of whether they have special educational needs [46,47]. Creating a barrier-free educational environment for the pupils from vulnerable groups increases the sustainability of the education process, which manifests itself through the optimal learning achievements of pupils.
Self-regulating learning as a means of overcoming learning difficulties. Schunk [48] (p. 125) mentioned that learners actively construct and manage self-regulatory learning, systematically focused on achieving learning goals. It is integral learning, with high motivation, active behavior, and metacognition [49]. A learner with self-regulating learning skills sets personal learning goals, monitors one’s progress toward those goals, and reflects on his/her learning to understand whether his/her strategies used to achieve a particular goal have actually been effective [50]. Approaches to self-regulatory learning are divided into three groups: reflection-oriented, adaptive, and controlled self-regulating behavior [50,51]. In addition, self-regulatory learning is seen as a lifelong learning competence [52]. Thus, self-regulated learning components are self-knowledge, efficiency, and self-assessment [48,53]. If these qualities are not present, learners are less motivated and can show poor academic performance. Other studies, like Lim et al. [49], follow a slightly different logic when distinguishing components of self-regulating learning. According to Lim et al. [49] (p. 114), the components of self-regulatory learning are goal setting, time management, task strategies, help-seeking, environment structuring, and self-evaluation.
Research has shown that self-regulated learning is a vital element of remote and blended learning, as learners take greater responsibility for their learning and have greater autonomy [49,54]. Self-regulatory learning is a significant predictor of achievements in the English language [55] and other subjects. Lim et al. [49] revealed other results—the relationship between self-regulating learning and academic achievement in mixed learning environments has not been established. However, significant positive impacts of learning with others or others on self-regulatory learning in mixed learning environments (blended learning) have been identified.
Self-regulatory skills are acquired through social modeling, scaffolding, collaboration, and feedback [56]. Studies have shown that if teachers apply pedagogical strategies to promote the self-regulation of pupils, the sustainability of the educational process tends to grow and the self-efficacy of pupils increases [56].
Collaborative learning as a component of sustainable inclusion. Sencibaugh and Sencibaugh [57] summarized data from studies that show that collaborative learning is more effective than other strategies and affects students’ learning of languages, science, social sciences, mathematics, and other subjects. The authors also highlighted the lack of research investigating the impact of collaborative learning on the achievements of pupils with learning difficulties. Some studies have shown that collaborative learning for pupils with learning difficulties can be empowering and can increase their achievement: learners can take over effective learning strategies from peers [58] and develop self-regulatory learning abilities [49]. However, it is important to identify appropriate collaborative learning approaches [57], interactive learning pathways, and social mediation [59]. According to Sencibaugh and Sencibaugh [57], well-structured collaborative learning in groups is more beneficial for students with learning difficulties than unstructured learning.
Studies conducted by Gratton [59] (p. 262) and Moore et al. [60] showed that collaborative learning for pupils with learning difficulties is useful if heterogeneous (rather than homogeneous) groups are formed, the principles of equal participation in the work of the group are discussed, the members of the group have a clear common purpose and clear assigned roles (or permission to divide into intended roles), all pupils are taught social (collaboration, supporting each other in the ideas, critical, and support for each other) abilities, and monitoring and self-monitoring in working groups (e.g., by making videos and reflecting on the work of members of the group). Peer tutoring is also useful for pupils with learning difficulties [57].
When analyzing the impact of collaborative learning in a contact and remote learning approach, it was found that collaborative learning in contact learning leads to better academic achievements than collaborative remote learning. However, blended collaborative learning can lead to better academic achievements. In addition, different ways of learning collaboratively lead to different academic achievements [61]. It is important to explore effective ways of collaborative remote learning, especially for pupils with learning difficulties.
Creative ICT scaffolding as a factor of an educational process that supports pupils’ learning. During remote learning, teachers had the need to use different ICT tools, and even well-experienced teachers felt that they had to learn what and how to teach [62]. The most widely suggested ICT tools enabled real-time videoconferencing, prerecorded seminars, collaboration, sharing materials, learning management systems, and live broadcasting features of social networking sites [63]. Nevertheless, according to the teachers, they created the tasks for the students themselves and mainly used word processing software. The problem lies in the fact that few teachers use digital solutions [20]; they lack awareness of the possibilities of digital learning resources [64]. Therefore, ICT technologies are not capitalized purposefully to a full extent [65].
During remote learning, teachers in general education schools used different methods in their teaching. Tammets et al. [20] identified three teaching methods teachers preferred to use. The first method is based on individual tasks, such as digital learning materials, to perform individual tasks and the numerical evaluation of students’ performance. The second method focused on multidisciplinary learning activities, such as project-based learning, research and creative assignments, written work, group work, finding additional learning materials by students and creating assignments themselves, integrated learning activities, and special learning for learners. The third method—synchronous teaching, where the teacher continued to teach regularly—conducted lesson-based video lessons [20].
ICT technologies can positively impact students’ learning when teachers are digitally literate and understand how to use this technology. However, studies have indicated that during the lockdown, there was a lack of inclusive teaching practices in remote learning [66]. For this reason, students with learning difficulties had insufficient support to be actively engaged in remote learning environments. They lacked guided exercises and prompt feedback, collaborative learning, and support, which is at the core of digital scaffolding [67]. Jumaat and Tasir [68] identified four types of digital scaffolding: procedural, conceptual, strategic, and metacognitive. During the COVID-19 lockdown, when SEN pupils stayed at home to learn, distant scaffolding chains started to emerge—teachers helped the parents of their pupils to master necessary technologies and parents assisted their children to participate in the learning process [6]. Teacher professional collaboration creates e-inclusive practices by scaffolding pupils with severe disabilities during their participation in common classroom activities together with other pupils [7].
These different types of scaffolding might be successfully explored for developing the self-regulatory learning of pupils, as they build on the development of reflection abilities, structural guidance, personalized assignments, and peer learning.

3. Materials and Methods

3.1. The Research Design

A quantitative research approach was chosen to attain the aim of the study [69], survey design [70] (p. 35) was chosen because it helps disclose the attitude of teachers toward whether the pupils from vulnerable groups achieve optimal learning outcomes that match their abilities under conditions of contact and remote learning. It also allows one to identify how often teachers apply different educational practices of inclusive education that are relevant to modeling the sustainable educational process as well as distinguishing latent factors of modeling the educational process; as well as allowing one to establish the impact of distinguishing factors on the achievements of the vulnerable group of pupils and its strength (Figure 1).
The first stage of the research focused on analyzing the views of 5th–12th-grade subject teachers from Lithuania, Latvia, and Estonia on whether the learning achievements of the vulnerable groups of pupils (encountering learning failures due to SEN; emotional reasons; social reasons) are optimal according to their abilities under the unstable conditions of contact and remote learning in the context of the COVID-19 pandemic.
The second stage of the research focused on distinguishing the latent factors of the educational process by conducting Exploratory Factor Analysis (EFA) of the teachers‘ responses. Three statements regarding the evaluation of whether pupils from vulnerable groups achieve optimal learning outcomes according to their abilities were withdrawn. The following six latent factors were distinguished: F1: Modeling education for engagement and participation by eliminating barriers; F2: Promotion of self-regulatory and collaborative learning; F3: Use of digital technologies for education; F4: Use of digital technologies for engagement; F5: Development of digital skills and digital scaffolding; F6: Identification of learning barriers. Confirmatory Factor Analysis (CFA) of these identified latent factors was also conducted.
During the third stage of research, Structural Equation Modeling Analysis (SEM) was carried out with the aim of identifying the impact of latent factors of the educational process on the learning achievements of pupils from vulnerable groups (encountering learning failures due to SEN; emotional reasons; social reasons) in contact and remote learning. The following hypotheses were tested separately for Lithuania, Latvia, and Estonia, and also for forms of contact and remote learning:
Hypothesis 1 (H1).
Modeling education for engagement and participation by eliminating barriers has a positive influence on the optimal learning achievements of pupils who face learning difficulties due to SEN, emotional reasons, and social reasons.
Hypothesis 2 (H2).
Promotion of self-regulatory and collaborative learning has a positive impact on the optimal learning achievements of pupils who face learning difficulties due to SEN, emotional reasons, and social reasons.
Hypothesis 3 (H3).
Use of digital technologies for education has a positive impact on the optimal learning achievements of pupils who face learning difficulties due to SEN, emotional reasons, and social reasons.
Hypothesis 4 (H4).
Use of digital technologies for engagement has a positive impact on the optimal learning achievements of pupils who face learning difficulties due to SEN, emotional reasons, and social reasons.
Hypothesis 5 (H5).
Development of digital skills and digital scaffolding has a positive impact on the optimal learning achievements of pupils who face learning difficulties due to SEN, emotional reasons, and social reasons.
Hypothesis 6 (H6).
Identification of learning barriers has a positive impact on the optimal learning achievements of pupils who face learning difficulties due to SEN, emotional reasons, and social reasons.

3.2. Sample

The research respondents were subject teachers of 5th–12th grades from Lithuania, Latvia, and Estonia. The teachers were sampled using the random probability sample strategy. The Raosoft software suggested the minimum sample size needed in this study as 377 in Lithuania, 376 in Latvia, and 376 in Estonia with a 5% margin of error and 95% confidence level. The internet questionnaire was filled in by 645 Lithuanian teachers (3.79% margin of error), 410 Latvian teachers (4.78% margin of error), and 377 Estonian teachers (5.00% margin of error). Table 1 presents data on the teachers‘ work experience and the location of the school, whether it is in a town or rural area. The sample characteristics are in line with the characteristics of the teacher population in the respective countries.

3.3. Instrument for Data Collection

The online self-reported questionnaire was designed by Lithuanian, Latvian, and Estonian researchers by following a theoretical construct and the results of other pieces of research were also used in the presented study. The questionnaire consists of 46 items, which includes two questions to obtain demographic data.
Three statements aimed at evaluating whether the vulnerable group of pupils (with SEN, emotional difficulties, and social difficulties) achieve optimal learning outcomes that match their abilities (the questions: “My students with learning difficulties due to disorders and disabilities achieve results that match their abilities”, “My students with emotional difficulties achieve results that match their abilities”, “My students with social difficulties achieve results that match their abilities”). While evaluating the statements, the teachers were recommended to reflect on their pupils’ abilities and learning achievements.
A total of 21 statements aimed at revealing the inclusive education practices of teachers by focusing on full engagement and participation of every pupil, eliminating educational process barriers, promoting self-regulatory and collaborative learning, modeling a flexible educational goal, developing educational content that is meaningful to pupils, the variety of methods and their choice (e.g., “I create opportunities for students to plan their learning activities, search for and organize information, manage learning time and evaluate outcome”).
A total of 15 statements focused on developing digital technologies skills, disclosing practices of digital engagement and digital scaffolding (e.g., “Seeking for diversity of educational ways and aids, I use technology to supplement the teaching material provided in the textbook”, “For students with emotional and learning difficulties, I use ICT tools as scaffolding to involve them in classroom activities together”).
Seven statements were used to reveal the reasons for the pupils’ learning difficulties that the teachers identify in their class: barriers of education process modeling, pupil’s personal barriers or external barriers (e.g., “Children with learning difficulties fail to experience learning success if a lesson is organized by applying one method for the whole class”; “Cognitive and/or other developmental disorders hinder successful learning”, “Children find it difficult to learn due to a lack of family support and care”).
The statements were not divided into subscales because the Exploratory Factor Analysis was planned to be used to distinguish the latent factors of educational process modeling. The Likert scale was employed to rank the responses. The teachers in the research were requested to mark if they agreed with the statements: 1—strongly disagree, 2—disagree, 3—hard to tell, 4—agree, 5—strongly agree.
The internal consistency of the questionnaire statements is high as the Cronbach alpha equals 0.941. The internal consistency of separate parts of the questionnaire is higher than 0.70 (See Table 2).

3.4. Procedure and Ethics

All the teachers participated in the questionnaire survey voluntarily. The questionnaire forms in the Lithuanian, Latvian, and Estonian languages were hosted on the online platform: https://apklausa.lt/ (accessed on 1 October 2021). The Lithuanian, Latvian, and Estonian researchers sent an e-access to the questionnaire to responsible municipality specialists and school principals together with an e-mail that presented the aim of the survey in a more detailed way than in the questionnaire form. The school principals were requested to send the e-access of the questionnaire to the teachers working in the 5th–12th grades. The questionnaire was anonymous and full confidentiality was ensured.

3.5. Data Analysis Techniques

Statistical data processing methods were applied for the analysis of the quantitative research results. The obtained research data were processed using IBM SPSS Statistics 22.0 and MS Excel programs adapted to Windows. Descriptive statistics were used for quantitative and percentage analysis.
EFA was used for identifying the latent factors of educational practices used by teachers [71]. The Maximum Likelihood (ML) method of the Common Factor Model (CFM) was also applied. Oblique Rotation (Promax) was used when the factors were interrelated and demonstrated correlation [72,73,74,75]. SEM analysis was employed for developing a model of impact paths [76,77]. Attempts were made to identify which factors ensured the sustainability of the educational process, that is, have a positive influence on the learning achievements of vulnerable groups of pupils in the critical context of the COVID-19 pandemic. Version 24.0 of the statistical program SPSS AMOS was used in the analysis.

4. Results

4.1. The Attitude of Teachers towards Achievements of Vulnerable Groups of Pupils during Contact and Remote Learning in the Context of COVID-19

Seeking to identify if a sudden transition from contact to remote learning under the COVID-19 pandemic conditions disturbed the sustainability of the educational process, which is of paramount importance to vulnerable groups pupils, the opinions of the subject teachers working with 5th-12th graders in Lithuania, Latvia, and Estonia on whether the learning achievements of pupils from vulnerable groups in their classes are optimal and comply with their abilities were obtained. The figure below presents the percentage values of teachers who agreed or strongly agreed with the statement that their pupils with learning difficulties due to SEN and emotional difficulties (ED)/social difficulties (SD) in contact as well as remote learning were able to achieve learning outcomes that matched their abilities (Figure 2).
The obtained data shows that the number of teachers from Lithuania, Latvia, and Estonia, who agree that their vulnerable group of pupils achieve learning outcomes that match their abilities in the critical COVID-19 situation is 2–4 times lower as compared to contact learning. This encourages the search for the factors of the educational process that ensure the sustainability of the educational process in critical situations of educational transformations and create favorable conditions for vulnerable groups of pupils to achieve learning outcomes that match their abilities.

4.2. Latent Factors of the Inclusive Education Process

Distinguishing the latent factors of the educational process is an obligatory process aiming to identify the factors that can ensure the sustainability of the educational process. Exploratory Factor Analysis (EFA) was conducted in an attempt to distinguish the latent factors of inclusive education practiced by the teachers in contact and remote learning in the context of COVID-19. Since the criterion of Kruskal-Wallis (comparison of three samples) revealed statistically significant differences in the data on Lithuania, Latvia, and Estonia in contact as well as remote learning, EFA was carried out with six data blocks: Lithuania_contact, Lithuania_remote, Latvia_contact, Latvia_remote, Estonia_contact, Estonia_remote.
Six latent factors were singled out: Section B The “Inclusive education practices“ in all the three countries and in contact and remote learning situations were split into two latent factors—F1: “Modeling education for engagement and participation by eliminating barriers” and F2: “Promotion of self-regulatory and collaborative learning” (two statements were withdrawn due to the low values of Communalities in some countries, none of the statements were redistributed into other factors); the data on Section C “Use of digital technologies“ in all the countries and in contact and remote learning allowed distinguishing three factors—F3: “Use of digital technologies for education”, F4: “Use of digital technologies for engagement” and F5: “Development of digital skills and digital scaffolding” (due to the low value of Communalities in all the countries, one statement was rejected; none of the statements were redistributed into other factors); Section D “Identification of learning barriers“ remained as a separate factor—F6: “Identification of learning barriers” but only in the contact and remote learning context in Lithuania. The values of Communalities of some statements in the Latvian and Estonian contact and remote learning were lower, so the engagement of these statements into the model could have resulted in the lower values of KMO or Total Variance. The results of the exploratory factor analysis satisfy the following conditions: the values of Kaiser–Meyer–Olkin test (KMO) ranged from 0.925, p < 0.0001 to 0.951, p < 0.0001; the values of Cronbach’s alpha of the distinguished factors ranged from 0.766 to 0.939 with a few of them lower than 0.8; the values of Total Variance Explained fluctuated from 51.826 to 54.749.
Confirmatory Factor Analysis (CFA) of the distinguished latent factors was performed, and the results were in line with the minimum requirements of contact and remote education of all the countries (Table 3). According to the researchers, to confirm the consistency of the model, at least three indicators of model consistency and their values have to meet the minimum requirements, however, the minimum values indicated are slightly different in the different sources (Brown, 2015; Schreiber et al., 2006). The researchers in this study used the Goodness of Fit Indices suggested by a group of authors (Hair, Black, Babim, Anderson, 2010) for confirmatory factor analysis and fit of SEM model: Relative Chi-Sq < 5.0; CFI ≥ 0.9; GFI ≥ 0.9; AGFI ≥ 0.9; IFI ≥ 0.9; NFI ≥ 0.9; TLI ≥ 0.9; RMSEA ≤ 0.08.

4.3. The Impact of Latent Factors of Inclusive Education Modeling on Vulnerable Groups of Pupils’ Achievements That Match Their Abilities during Contact and Remote Learning in the Baltic States

The third stage of research focused on the Structural Equation Modeling analysis (SEM) and aimed to identify the paths of latent factors and the regression weights of achievements of vulnerable groups of pupils that match their abilities. Figure 3 presents the impact of latent factors of the Lithuanian contact learning process on the optimal achievements of the vulnerable groups of pupils.
Six hypotheses were tested. The dotted arrows in Figure 3 mark the tested hypotheses with the level of statistical significance equal to p > 0.05, which were withdrawn from the model. Hypothesis H2 was confirmed: “Promotion of self-regulatory and collaborative” learning (F2) has a positive influence on the achievements of pupils encountering learning difficulties due to SEN (Q1, Estimate = 0.376, SE = 0.095, CR = 3.973, p < 0.0001), emotional reasons (Q2, Estimate = 0.363, SE = 0.099, CR = 3.646, p < 0.0001), and social reasons (Q3, Estimate = 0.506, SE = 0.054, CR = 9.447, p < 0.0001). H1 was partially confirmed: “Modeling education for engagement and participation by eliminating barriers” (F1) has a positive impact on the learning achievements of pupils with learning difficulties due to SEN (Q1, Estimate = 0.209, SE = 0.097, CR = 2.162, p < 0.05) and emotional reasons (Q2, Estimate = 0.226, SE = 0.104, CR = 2.182, p < 0.05). Hypotheses H3, H4, H5, H6 were not confirmed and other factors do not have a statistically significant positive or negative impact on the vulnerable groups of pupils’ achievements during contact learning in Lithuania.
Figure 3 also shows the influence of latent factors of the Lithuanian remote learning process on the optimal achievements of the vulnerable groups of pupils. H2 was fully confirmed in remote learning just as in contact one: “Promotion of self-regulatory and collaborative learning” (F2) has a positive impact on the achievements of pupils facing learning difficulties due to SEN (Q1, Estimate = 0.422, SE = 0.069, CR = 6.104, p < 0.0001), emotional reasons (Q2, Estimate = 0.425, SE = 0.051, CR = 8.400, p < 0.0001), and social reasons (Q3, Estimate = 0.489, SE = 0.052, CR = 9.439, p < 0.0001). Thus, the “Promotion of self-regulatory and collaborative learning” is a stable factor having a positive impact both in the usual and critical COVID-19 situation after the pupils started remote learning. H5 was partially confirmed under conditions of remote learning: “Development of digital skills and digital scaffolding” (F5) has a positive influence on the achievements of pupils encountering learning difficulties due to SEN (Q1, Estimate = 0.205, SE = 0.069, CR = 2.989, p < 0.0005). Neither a positive nor negative impact was identified on the pupils from other vulnerable groups. H1, which was partially confirmed in contact learning, was not confirmed in the remote learning situation: “Modeling education for engagement and participation by eliminating barriers” (F1) showed a weak negative impact on the achievements of pupils who face learning difficulties due to SEN (Q1, Estimate = −0.141, SE = 0.065, CR = −2.162, p < 0.05). The other groups were not influenced at all. Under conditions of remote learning, factor F6 showed a negative impact. Hypothesis H6 was not confirmed: “Identification of learning barriers” (F6) has a negative impact on the achievements of pupils with learning difficulties due to SEN (Q1, Estimate = −0.354, SE = 0.052, CR = −3.828, p < 0.0001), emotional reasons (Q2, Estimate = −0.176, SE = 0.063, CR = −1.886, p < 0.05), and social reasons (Q3, Estimate = −0.336, SE = 0.066, CR = −3.517, p < 0.0001). H3: “Use of digital technologies for education” and F4: “Use of digital technologies for engagement” were not confirmed in remote learning. These factors had no impact on the vulnerable groups of pupils‘ achievements.
The models fit as all the indicators presented in Table 4 fully comply with the minimal requirements for fit indices.
Figure 4 presents the impact of latent factors of the Latvian contact learning process on the optimal achievements of the vulnerable groups of pupils.
Five hypotheses were tested because F6 was not distinguished as a latent factor. Only H2 was confirmed in Latvian contact learning: “Promotion of self-regulatory and collaborative learning” (F2) has a positive influence on the achievements of pupils encountering learning difficulties due to SEN (Q1, Estimate = 0.480, SE = 0.068, CR = 7.057, p < 0.0001), emotional reasons (Q2, Estimate = 0.437, SE = 0.068, CR = 6.422, p < 0.0001), and social reasons (Q3, Estimate = 0.607, SE = 0.068, CR = 7.075, p < 0.0001). Other hypotheses H1, H3, H4, H5 were rejected, that is, none of the latent factors had an impact on the learning achievements of pupils from vulnerable groups.
Figure 4 also shows the influence of latent factors of the Latvian remote learning process on the optimal achievements of pupils from vulnerable groups. In Latvia, just as in Lithuania, H2 was fully confirmed in remote learning as well as in contact learning: “Promotion of self-regulatory and collaborative learning” (F2) has a positive effect on the learning achievements of pupils from all the three vulnerable groups (Q1, Estimate = 0.350, SE = 0.064, CR = 3.359, p < 0.0001; Q2, Estimate = 0.436, SE = 0.064, CR = 5.581, p < 0.0001; Q3, Estimate = 0.554, SE = 0.063, CR = 5.377, p < 0.0001). The assumption that the “Promotion of self-regulatory and collaborative learning” is a stable positive factor in the usual and critical education situation in the educational systems of different countries was approved. Under conditions of remote learning in Latvia, H4 was partially confirmed: “Use of digital technologies for engagement” (F4) has a positive impact on the learning achievements of pupils who experience learning difficulties due to SEN (Q1, Estimate = 0.106, SE = 0.053, CR = 2.016, p < 0.05) and social reasons (Q3, Estimate = 0.113, SE = 0.060, CR = 1.900, p < 0.05). H3 was not confirmed in the context of Latvian remote learning: “Use of digital technologies for education” (F3) showed a weak negative impact on the learning results of pupils with learning difficulties due to SEN (Q1, Estimate = −0.175, SE = 0.064, CR = −1.899, p < 0.05); H4 was not confirmed: “Development of digital skills and digital scaffolding” (F4) had a weak negative effect on the achievements of pupils facing learning difficulties due to social reasons (Q3, Estimate = −0.158, SE = 0.077, CR = −2.057, p < 0.05); H1 too was not confirmed: “Modeling education for engagement and participation by eliminating barriers” had neither a positive nor a negative impact on the learning achievements of pupils from vulnerable groups.
The models fit as all the indicators presented in Table 5 fully comply with the minimal requirements for fit indices.
Figure 5 presents the impact of latent factors of the Estonian contact learning process on the optimal achievements of the vulnerable groups of pupils. Five hypotheses were tested because F6 was not distinguished as a latent factor just as in Latvia. Only H1 was confirmed in the situation of Estonian contact learning: “Modeling education for engagement and participation by eliminating barriers” (F1) has a positive influence on the learning achievements of pupils experiencing learning difficulties due to SEN (Q1, Estimate = 0.374, SE = 0.070, CR = 5.341, p < 0.0001), emotional reasons (Q2, Estimate = 0.357, SE = 0.065, CR = 5.468, p < 0.0001), and social reasons (Q3, Estimate = 0.244, SE = 0.072, CR = 3.379, p < 0.0001). This hypothesis was partially confirmed in the case of Lithuania and rejected in the case of Latvia. The other hypotheses H3, H4, H5 were not confirmed and other factors do not have a statistically significant positive or negative impact on the vulnerable groups of pupils’ achievements. H2, which was fully confirmed during contact learning in Lithuania and Latvia, was rejected in Estonia.
Figure 5 also shows the influence of latent factors of the Estonian remote learning process on the optimal achievements of pupils from the vulnerable groups. In the remote learning of Estonia, just as in Lithuania and Latvia, H2 was fully confirmed: “Promotion of self-regulatory and collaborative learning” (F2) has a positive influence on the learning achievements of pupils from all the three vulnerable groups (Q1, Estimate = 0.488, SE = 0.069, CR = 7.068, p < 0.0001; Q2, Estimate = 0.370, SE = 0.069, CR = 5.354, p < 0.0001; Q3, Estimate = 0.399, SE = 0.072, CR = 5.582, p < 0.0001). This only strengthens the assumption that the “Promotion of self-regulatory and collaborative learning” is a stable positive factor in the critical educational situations in the education systems of different countries. The other hypotheses H1, H3, H4, H5 were not confirmed, that is, none of the latent factors, with the exception of “Promotion of self-regulatory and collaborative learning”, had either a positive or negative impact on the achievements of pupils from vulnerable groups.
The models fit as all the indicators presented in Table 6 comply with the minimal requirements for fit indices.

5. Discussion

The processes observed in the education system during the COVID-19 pandemic confirm the fact that the situation of pupils’ learning is particularly susceptible to the transformations in society. This necessitates the search for factors that ensure the sustainability of the education system. The results of our research, which embraces the teachers’ experiences in all the three Baltic countries, demonstrate the same perspective of societal development. Hilmarsson [17] substantiated the existence of factors that can ensure the sustainability of the educational system in critical situations.
The results of the research on the teachers’ experience under COVID-19 conditions show that modeling of the inclusive education process, based on the promotion of self-regulatory, collaborative learning, ensures the sustainability of the educational process in the critical COVID-19 situation, that is, there is a positive impact on the optimal learning achievements of pupils from all the three vulnerable groups in all the Baltic countries in the context of both remote learning and contact learning in Lithuania and Latvia. Another factor contributing to the sustainability of the educational process is modeling education for engagement and participation by eliminating barriers. Such modeling of the educational process based on the principles of UDL had a positive influence on the learning achievements of pupils from all the three vulnerable groups in Estonia and also on the pupils experiencing learning difficulties due to SEN and social reasons in contact learning in Lithuania. Modeling of the educational process based on UDL principles and the promotion of self-regulatory and collaborative learning make up the essential principles in the structure of the Universal Design for Learning. The research that analyzes the efficiency of the UDL approach indicates the influence of learning based on this approach, on the development of strategies and goal-directed abilities of pupils under usual conditions of learning [47,78,79]. Our research discloses that the application of self-regulatory and collaborative principles ensures the sustainability of the impact of the educational process on the pupils’ achievements under unfavorable environmental factors. In the situation when the educational systems were forced to transfer from contact to remote learning, the influence of this educational principle on the learning achievements remains significant in all the three countries and for pupils from all the three vulnerable groups, that is, students encountering learning barriers due to SEN, emotional, and social difficulties. However, the results of other studies [5,8] show that in the context of the sudden transformation from contact to remote learning, the educational processes lost their efficiency in terms of pupils’ participation and achievements.
Other factors of education organization in different educational contexts had a different impact on the pupils’ achievements. It was identified that the use of digital technologies for engagement in the learning process positively influences the learning outcomes of pupils facing learning difficulties due to SEN and social reasons in Latvia during remote learning. Developing digital skills and digital scaffolding has a positive impact on pupils who experience learning difficulties due to SEN in remote learning in Lithuania; however, it has a negative influence on pupils with learning difficulties due to social reasons in the context of remote learning in Latvia. Research conducted by other authors allows the assumption of the possible reasons for the inefficiency of applying digital technologies and digital scaffolding: insufficient diversity of aids for remote learning [63,64], insufficient variety of methods for organizing remote learning [20], absence of targeted adaptation of teaching aids for remote learning [65]. The digital skills of teachers and learners became crucial during the school lockdown; however, our study re-confirms the results of other studies [66], which indicate that during remote learning there was a lack of inclusive digital learning practices. Our study revealed that the use of digital technologies and trying out various engaging digital resources without a clear didactic direction does not affect the achievements of pupils with learning difficulties. Our research is also in line with studies that highlight the need for digital scaffolding [67], which supports learners’ interaction, essential not only to ensure school connectedness but also to develop the self-regulatory learning skills of pupils with learning difficulties. The study highlights that the development of digital skills, digital scaffolding, and technological provision for pupils with SEN, their teachers and parents have a sustainable positive impact on the pupils’ learning achievements. The study implies that it is important to provide general education in schools not only with standards but also with specialized technological equipment to help teachers implement effective inclusive education.
Identification of learning barriers, which following the UDL approach should help the teachers to eliminate the identified learning barriers, had a negative influence on the achievements of pupils experiencing learning difficulties due to SEN and social reasons in the context of remote learning in Lithuania. Modeling education for involvement and participation by eliminating learning barriers, which had a positive impact on the achievement of pupils in the process of contact learning in Lithuania, negatively influences the achievements of pupils during remote learning. The Lithuanian educational system is in the process of active transformation towards inclusive education [80], therefore, the teachers lacked the experience to transform successful practices of contact learning into efficient practices of e-inclusive education [7,81].
The sustainability of remote learning processes during the critical transformations in the educational systems of the Baltic States in the context of COVID-19 was ensured by the promotion of self-regulatory and collaborative learning. It can be assumed that the educational systems, where the process of education is modeled on the basis of self-regulatory and collaborative practices, will create conditions for ensuring optimal achievements of the vulnerable groups of pupils that match their abilities.
The study has certain limitations. First of all, it focused on the situation of three Baltic Sea Region countries which are very similar in their size of population, the structure of education systems, teachers’ age, ICT and technological infrastructure, and other characteristics. Further studies could address gaps and differences during remote learning which were caused by unequal technological resources in different countries and particularly rural areas. The second limitation is associated with the participants of the study. Our research is based on teachers’ views, while other stakeholders like parents and pupils were not involved. This study has clear implications for further research to analyze remote learning models which could be successfully transferred and adapted to daily educational practices in post-pandemic contexts. More studies are needed to investigate how the universal design for learning approach aligned with the principles of self-regulated learning could help develop sustainable inclusive practices, which would be rather flexible and transferrable to different learning environments.

6. Conclusions

Self-regulatory collaborative learning has a sustainable, strong impact on the achievements of pupils with emotional and learning difficulties in various (stable and unstable) educational environments in all three countries. In Estonia, self-regulating collaborative learning has become evident as a leading factor of the education system in remote learning conditions.
Modeling of education for involvement and participation by eliminating barriers has a positive impact on the achievement of pupils with emotional and learning difficulties in normal learning conditions, but the available inclusive educational practices in conditions of critical changes in the education system were not sustainable. The application of UDL principles in remote learning would ensure the sustainability of the remote learning process as well.
The development of digital skills, digital scaffolding, trying out various engaging digital resources, and technological provision for pupils with special educational needs, and their teachers and parents have a sustainable positive impact on the pupils’ learning achievements. To guarantee the sustainability of digital scaffolding, specialized resources and teacher preparation are to be flexibly modeled to the general process of pupils’ education by increasing parents’ engagement.
In the cases when teachers are able to identify the learning barriers of pupils with learning difficulties due to SEN, emotional, and social reasons but do not remodel the process of education, a negative impact was observed on the achievements of such pupils.

Author Contributions

Conceptualization, A.G., L.K., O.M., I.I. and M.K.; methodology, O.M., A.G. and R.K.; software, O.M. and R.K.; validation, O.M., R.K. and A.G.; formal analysis, A.G., O.M. and L.K.; investigation, A.G., O.M., M.K., I.I. and L.K.; writing—original draft preparation, A.G., O.M. and L.K.; final editing, O.M., A.G., L.K., M.K., R.K. and I.I. All authors have read and agreed to the published version of the manuscript.

Funding

The research was funded by the Research Council of Lithuania project, Emotional and Educational Difficulties Pupils Encounter under the Conditions of Inclusive Education, and Coping with Them: Context of COVID-19 (Agreement No. S-DNR-20-09), co-financed by the European Union under the measure‚ Implementation of Analysis and Diagnostics of Short-Term (Necessary) Research (in Health, Social and Other Fields) related to COVID-19.

Institutional Review Board Statement

The research was carried out following the provisions which underline the basic principles of professionalism and ethics of research, approved by the Resolution No. SEN-N-17 of the Senate of Vytautas Magnus University of 24 March 2021. The study was conducted in accordance with the principles of reliability, integrity, respect, and accountability and with the provisions of point 23, which define the cases in which the investigator is required to submit to the evaluation committee his/her research plan for the validation of compliance with the professionalism and ethics of the research.

Informed Consent Statement

In the case of this study, written informed consent is not necessary, since the teachers’ survey was conducted remotely without identifying the data of the study participant and his/her institution, as well as respondents from sensitive groups did not directly participate in the study.

Data Availability Statement

The datasets generated and analysed during the current study are not publicly available due to privacy and ethical concerns but are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. United Nations. Policy Brief: Education during COVID-19 and Beyond, 2020, August. Available online: https://www.un.org/sites/un2.un.org/files/sg_policy_brief_covid-19_and_education_august_2020.pdf (accessed on 14 December 2021).
  2. Bozkurt, A.; Sharma, R.C. Emergency remote teaching in a time of global crisis due to Corona Virus pandemic. Asian J. Distance Educ. 2020, 15, i–vi. Available online: http://www.asianjde.com/ojs/index.php/AsianJDE/article/view/447/297 (accessed on 4 November 2021).
  3. Morgan, H. Best Practices for Implementing Remote Learning during a Pandemic. Clear. House J. Educ. Strateg. Issues Ideas 2020, 93, 135–141. [Google Scholar] [CrossRef]
  4. Doyumgaç, I.; Tanhan, A.; Kiymaz, M.S. Understanding the most important facilitators and barriers for online education during COVID-19 through online photovoice methodology. Int. J. High. Educ. 2021, 10, 166–190. [Google Scholar] [CrossRef]
  5. Reimers, F.M. Conclusions and Implications. In Primary and Secondary Education during COVID-19. Disruptions to Educational Opportunity during a Pandemic; Reimers, F.M., Ed.; Springer: Cambridge, MA, USA, 2021; pp. 461–475. [Google Scholar] [CrossRef]
  6. Karasel, N.; Bastas, M.; Altinay, F.; Altinay, Z.; Dagli, G. Distance Education for Students with Special Needs in Primary Schools in the Period of COVID-19 Epidemic. Propósitos Represent. 2020, 8, e587. [Google Scholar] [CrossRef]
  7. Parmigiani, D.; Benigno, V.; Giusto, M.; Silvaggio, C.; Sperandio, S. E-inclusion: Online special education in Italy during the COVID-19 pandemic. Technol. Pedagog. Educ. 2020, 1, 1–14. [Google Scholar] [CrossRef]
  8. Basham, J.D.; Blackorby, J.T.; Marino, M.T. Opportunity in Crisis: The Role of Universal Design for Learning in Educational Redesign. Learn. Disabil. Contemp. J. 2020, 18, 71–91. [Google Scholar]
  9. Skipp, A.; Smith, S.; Wall, D. Learning from the COVID crisis for educating children and young people with SEN/disabilities. J. Res. Spec. Educ. Needs 2021, 21, 168–184. [Google Scholar] [CrossRef]
  10. Essel, H.B.; Vlachopoulos, D.; Adom, D.; Tachie-Menson, A. Transforming higher education in Ghana in times of disruption: Flexible learning in rural communities with high latency internet connectivity. J. Enterprising Communities People Places Glob. Econ. 2021, 15, 296–312. [Google Scholar] [CrossRef]
  11. Bond, M. Schools and emergency remote education during the COVID-19 pandemic: A living rapid systematic review. Asian J. Distance Educ. 2020, 15, 191–247. Available online: https://eric.ed.gov/?id=EJ1285336 (accessed on 6 November 2021).
  12. Aloizou, V.; Chasiotou, T.; Retalis, S.; Daviotis, T.; Koulouvaris, P. Remote learning for children with Special Education Needs in the era of COVID-19: Beyond tele-conferencing sessions. Educ. Media Int. 2021, 58, 181–201. [Google Scholar] [CrossRef]
  13. Nusser, L. Learning at home during COVID-19 school closures–How do German students with and without special educational needs manage? Eur. J. Spec. Needs Educ. 2021, 36, 51–64. [Google Scholar] [CrossRef]
  14. Page, A.; Charteris, J.; Anderson, J.; Boyle, C. Fostering school connectedness online for students with diverse learning needs: Inclusive education in Australia during the COVID-19 pandemic. Eur. J. Spec. Needs Educ. 2021, 36, 142–156. [Google Scholar] [CrossRef]
  15. Brom, C.; Lukavský, J.; Greger, D.; Hannemann, T.; Straková, J.; Švaříček, R. Mandatory Home Education During the COVID-19 Lockdown in the Czech Republic: A Rapid Survey of 1st-9th Graders’ Parents. Front. Educ. 2020, 5, 103. [Google Scholar] [CrossRef]
  16. Kruszewska, A.; Nazaruk, S.; Szewczyk, K. Polish teachers of early education in the face of distance learning during the COVID-19 pandemic–the difficulties experienced and suggestions for the future. Education 2020, 3–13, 1–12. [Google Scholar] [CrossRef]
  17. Hilmarsson, H.P. Nordic Welfare, Baltics Austerity and COVID-19. Rev. Manag. Comp. Int. 2021, 22, 542–554. [Google Scholar] [CrossRef]
  18. Želvys, R. Lietuvos švietimo raida: Praeitis, dabartis ir ateities perspektyvos. Educ. Psychol. Ugdym. Psichol. 2018, 29, 88–96. [Google Scholar] [CrossRef]
  19. OECD. PISA 2018 Results (Volume I): What Students Know and Can Do 2019; OECD Publishing: Paris, France, 2019. [Google Scholar] [CrossRef]
  20. Tammets, K.; Ley, T.; Eisenschmidt, E.; Soodla, P.; Sillat, P.-J.; Kollom, K.; Väljataga, T.; Loogma, K.; Sirk, M. Eriolukorrast Tingitud Distantsõppe Kogemused ja mõju Eesti Üldharidussüsteemile. Vahearuanne. [Experiences of Distance Learning due to an Emergency Situation and Its Impact on the Estonian General Education System. Interim Report.]; Tallinn University: Tallinn, Estonia, 2021. [Google Scholar]
  21. IZM [Ministry of Education] EMU: Skola kopsavilkums [School Summary] 2021. Available online: https://www.izm.gov.lv/lv/petijumi-0 (accessed on 6 November 2021).
  22. Švietimo Naujienos. Mokiniams Iš Socialiai Remtinų Šeimų–20 Tūkst. Interneto Kortelių [Education News. For Pupils from Socially Supported Families–20 Thous. Internet Cards] 2020-04-08. Available online: https://www.svietimonaujienos.lt/mokiniams-is-socialiai-remtinu-seimu-20-tukst-interneto-korteliu/ (accessed on 3 November 2021).
  23. Daukšienė, E.; Trepulė, E.; Naujokaitienė, J. Kokybiško nuotolinio ugdymo link: Mokyklų pirmosios išmoktos pamokos COVID-19 pandemijos metu. Pedagogika 2021, 142, 5–23. [Google Scholar] [CrossRef]
  24. Merfeldaitė, O.; Prakapas, R.; Railienė, A. Nuotolinio mokymo organizavimas COVID-19 metu: Bendrojo ugdymo mokyklų patirtis. Pedagogika 2020, 140, 5–17. [Google Scholar] [CrossRef]
  25. Kaminskienė, L.; Galkienė, A.; Navaitienė, J.; Ignatova, N.; Kasperiūnienė, J.; Rutkienė, A.; Monkevičienė, O.; Miltenienė, L.; Melienė, R. The power of the school community in increasing inclusion. In Proceedings of the ICERI 2021: 14th Annual International Conference of Education, Research and Innovation, Online Conference, 8–9 November 2021; IATED Academy: Valencia, Spain. Available online: https://portalcris.vdu.lt/cris/bitstream/20.500.12259/145916/2/ISBN9788409345496.PG_9865-9873.pdf (accessed on 24 November 2021).
  26. Wolhuter, C.; Nel, M.; Želvys, R.; Alisauskiene, S. Thirty Years since the Fall of the Berlin Wall: Educational Reforms Worldwide. Glocal Education in Practice: Teaching, Researching, and Citizenship. In BCES Conference Books; Bulgarian Comparative Education Society: Sofia, Bulgaria, 2019; Volume 17, pp. 216–222. [Google Scholar]
  27. Khalaf, B.K.; Zin, Z.B.M. Traditional and Inquiry-Based Learning Pedagogy: A Systematic Critical Review. Int. J. Instr. 2018, 11, 545–564. [Google Scholar] [CrossRef]
  28. Wyse, D.; Hayward, L.; Higgins, S.; Livingston, K. Traditional school subjects versus progressive pedagogy. Curric. J. 2018, 29, 295–297. [Google Scholar] [CrossRef]
  29. Meyer, A.; Rose, D.H.; Gordon, D. Universal Design for Learning: Theory and Practice; CAST Professional Publishing: Wakefield, MA, USA, 2014. [Google Scholar]
  30. Smith, A.; Chestnutt, C. Differentiation for Equity. J. High. Educ. Theory Pract. 2021, 21, 232–241. [Google Scholar] [CrossRef]
  31. UNESCO. Transforming Our World: The 2030 Agenda for Sustainable Development 2015. Available online: https://sdgs.un.org/2030agenda (accessed on 14 December 2021).
  32. UNESCO. Global Education Monitoring Report 2020: Inclusion and Education: All Means All 2020. Available online: https://unesdoc.unesco.org/ark:/48223/pf0000373721/PDF/373721eng.pdf.multi (accessed on 10 December 2021).
  33. Haug, P. ‘It is impossible to avoid policy’ comment on Mel Ainscow: Promoting inclusion and equity in education: Lessons from international experiences. Nord. J. Stud. Educ. Policy 2020, 6, 17–20. [Google Scholar] [CrossRef]
  34. Ramberg, J.; Watkins, A. Exploring Inclusive Education across Europe: Some Insights from the European Agency Statistics on Inclusive Education. FIRE Forum Int. Res. Educ. 2020, 6, 85–101. [Google Scholar] [CrossRef]
  35. Magnússon, G. Inclusive education and school choice lessons from Sweden. Eur. J. Spec. Needs Educ. 2020, 35, 25–39. [Google Scholar] [CrossRef] [Green Version]
  36. Louick, R.; Daley, S.G.; Robinson, K.H. Using an Autonomy-oriented Learning Environment for Struggling Readers: Variations in Teacher Sensemaking and Instructional Approach. Elem. Sch. J. 2019, 120, 176–196. [Google Scholar] [CrossRef]
  37. Kieran, L.; Anderson, C. Connecting Universal Design for Learning with Culturally Responsive Teaching. Educ. Urban Soc. 2019, 51, 1202–1216. [Google Scholar] [CrossRef]
  38. Sanahuja-Gavalda, J.M.; Olmos-Rueda, P.; Mar Morón-Velasco, M. Collaborative Support for Inclusion. J. Res. Spec. Educ. Needs 2016, 16, 303–307. [Google Scholar] [CrossRef]
  39. Aas, H.K. Teachers talk on student needs: Exploring how teacher beliefs challenge inclusive education in a Norwegian context. Int. J. Incl. Educ. 2019, 1, 1–15. [Google Scholar] [CrossRef] [Green Version]
  40. Swanson, J.A.; Ficarra, L.R.; Chapin, D. Strategies to strengthen differentiation within the common core era: Drawing on the expertise from those in the field. Prev. Sch. Fail. Altern. Educ. Child. Youth 2020, 64, 116–127. [Google Scholar] [CrossRef]
  41. Hansen, J.H.; Carrington, S.; Jensen, C.R.; Molbæk, M.; Secher Schmidt, M.C. The collaborative practice of inclusion and exclusion. Nord. J. Stud. Educ. Policy 2020, 6, 47–57. [Google Scholar] [CrossRef] [Green Version]
  42. King-Sears, M.E. Facts and Fallacies: Differentiation and the General Education Curriculum for Students with Special Educational Needs. Support Learn. 2008, 23, 55–62. [Google Scholar] [CrossRef]
  43. Florian, L.; Black-Hawkins, K. Exploring inclusive pedagogy. Br. Educ. Res. J. 2011, 37, 813–828. [Google Scholar] [CrossRef]
  44. Rapp, W. Universal Design for Learning in Action; Brooks: Baltimore, MD, USA, 2014. [Google Scholar]
  45. García-Campos, M.D.; Canabal, C.; Alba-Pastor, C. Executive functions in universal design for learning: Moving towards inclusive education. Int. J. Incl. Educ. 2020, 24, 660–674. [Google Scholar] [CrossRef]
  46. Al-Azawei, A.; Serenelli, F.; Lundqvist, K. Universal design for learning (UDL): A content analysis of peer-reviewed journal papers from 2012 to 2015. J. Scholarsh. Teach. Learn. 2016, 16, 39–56. [Google Scholar] [CrossRef] [Green Version]
  47. Capp, M.J. The effectiveness of universal design for learning: A meta-analysis of literature between 2013 and 2016. Int. J. Incl. Educ. 2017, 21, 791–807. [Google Scholar] [CrossRef]
  48. Schunk, D.H. Social cognitive theory and self-regulated learning. In Self-Regulated Learning and Academic Achievement: Theoretical Perspectives; Zimmerman, B.J., Schunk, D.H., Eds.; Lawrence Erlbaum Associates Publishers: Mahwah, NJ, USA, 2001; pp. 125–151. [Google Scholar]
  49. Lim, C.; Ab Jalil, H.; Ma’rof, A.; Saad, W. Peer Learning, Self-Regulated Learning and Academic Achievement in Blended Learning Courses: A Structural Equation Modeling Approach. Int. J. Emerg. Technol. Learn. 2020, 15, 110–125. [Google Scholar] [CrossRef] [Green Version]
  50. Hong, J.C.; Lee, Y.F.; Ye, J.H. Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown. Personal. Individ. Differ. 2021, 174, 110673. [Google Scholar] [CrossRef]
  51. Bai, B.; Wang, J. The role of growth mindset, self-efficacy and intrinsic value in self-regulated learning and English language learning achievements. Lang. Teach. Res. 2020, 1–22. [Google Scholar] [CrossRef]
  52. Gan, Z.; Liu, F.; Yang, C.C.R. Student-teachers’ self-efficacy for instructing self-regulated learning in the classroom. J. Educ. Teach. 2020, 46, 120–123. [Google Scholar] [CrossRef]
  53. Kim, D.H.; Wang, C.; Ahn, H.S.; Bong, M. English language learners’ self-efficacy profiles and relationship with self-regulated learning strategies. Learn. Individ. Differ. 2015, 38, 136–142. [Google Scholar] [CrossRef]
  54. Cho, M.H.; Heron, M.L. Self-regulated learning: The role of motivation, emotion, and use of learning strategies in students’ learning experiences in a self-paced online mathematics course. Distance Educ. 2015, 36, 80–99. [Google Scholar] [CrossRef]
  55. Shing, L.S.; Rameli, M.R.M. The influence of self-regulation towards academic achievement in English among Malaysian upper primary students. Univers. J. Educ. Res. 2020, 8, 1–11. [Google Scholar] [CrossRef]
  56. Ozer, O.; Akçayoğlu, D.I. Examining the Roles of Self-Efficacy Beliefs, Self-Regulated Learning and Foreign Language Anxiety in the Academic Achievement of Tertiary EFL Learners. Particip. Educ. Res. 2021, 8, 357–372. [Google Scholar] [CrossRef]
  57. Sencibaugh, J.M.; Sencibaugh, A.M. An Analysis of Cooperative Learning Approaches for Students with Learning Disabilities. Education 2016, 136, 356–364. [Google Scholar]
  58. Morocco, C.C.; Hindin, A.; Mata-Aguilar, C.; Clark-chiarelli, N. Building a Deep Understanding of Literature with Middle-Grade Students with Learning Disabilities. Learn. Disabil. Q. 2001, 24, 47–58. [Google Scholar] [CrossRef]
  59. Gratton, R. Collaboration in students’ learning: The student experience. Support Learn. 2019, 34, 224–276. [Google Scholar] [CrossRef]
  60. Moore, B.; Smith, C.; Boardman, A.; Ferrell, A. Using Video Self Reflection to Support Collaborative Learning for Students With Learning Disabilities. Teach. Except. Child. 2020, 53, 52–59. [Google Scholar] [CrossRef]
  61. Chen, F.S.; Ke, H.S.; Chen, Y.C. Online Learning as a Panacea? An Empirical Study to Discuss Problem-Based Cooperative Learning in Taiwan. Int. J. Emerg. Technol. Learn. 2020, 15, 251–259. [Google Scholar] [CrossRef]
  62. Bergdahl, N.; Nouri, J. COVID-19 and crisis-prompted distance education in Sweden. Technol. Knowl. Learn. 2020, 26, 443–459. [Google Scholar] [CrossRef]
  63. Bozkurt, A.; Jung, I.; Xiao, J.; Vladimirschi, V.; Schuwer, R.; Egorov, G.; Lambert, S.; Al-Freih, M.; Pete, J.; Olcott, D., Jr.; et al. A global outlook to the interruption of education due to COVID-19 Pandemic: Navigating in a time of uncertainty and crisis. Asian J. Distance Educ. 2020, 15, 1–126. [Google Scholar] [CrossRef]
  64. Erss, M.; Lauristin, M.; Loogma, K.; Sarv, E.-S.; Sirp, L. The Second COVID-19 Spring from the Perspectives of Students, Teachers and Parents: The Follow-Up Study of Estonian Distance Learning by Estonian Education Forum; Estonian Education Forum: Tallinn, Estonia, 2021. [Google Scholar]
  65. European Commission; Joint Research Centre; Mägi, E. The School Year 2020–2021 in Estonia during the Pandemic: Country Report, Publications Office. 2021. Available online: https://data.europa.eu/doi/10.2760/52883 (accessed on 12 November 2021).
  66. Letzel, V.; Pozas, M.; Schneider, C. Energetic Students, Stressed Parents, and Nervous Teachers: A Comprehensive Exploration of Inclusive Homeschooling during the COVID-19 Crisis. Open Educ. Stud. 2020, 2, 159–170. [Google Scholar] [CrossRef]
  67. Cho, M.H.; Cho, Y. Online instructors’ use of scaffolding strategies to promote interactions: A scale development study. Int. Rev. Res. Open Distrib. Learn. 2016, 17, 108–120. [Google Scholar] [CrossRef] [Green Version]
  68. Jumaat, N.F.; Tasir, Z. Instructional Scaffolding in Online Learning Environment: A Meta-analysis. In Proceedings of the 2014 International Conference on Teaching and Learning in Computing and Engineering, Kuching, Malaysia, 11–13 April 2014; pp. 74–77. [Google Scholar] [CrossRef]
  69. Cohen, L.; Manion, L.; Morrison, K. Research Methods in Education, 8th ed.; Routledge: London, UK, 2018. [Google Scholar]
  70. Creswell, J.W. Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research, 4th ed.; Pearson: New York, NY, USA, 2014. [Google Scholar]
  71. Fabrigar, L.R.; Wegener, D.T. Exploratory Factor Analysis: Understanding Statistics; Oxford University Press Inc.: New York, NY, USA, 2011. [Google Scholar]
  72. Brown, T.A. Choosing the right type of rotation in PCA and EFA. JALT Test. Eval. SIG Newsl. 2009, 13, 20–25. Available online: https://hosted.jalt.org/test/PDF/Brown31.pdf (accessed on 8 October 2021).
  73. Costello, A.B.; Osborne, J.W. Best practices in Exploratory Factor Analysis: Four recommendations for getting the most from your analysis. Pract. Assess. Res. Educ. 2005, 10, 1–9. [Google Scholar] [CrossRef]
  74. Finch, H. Comparison of the performance of Varimax and Promax rotations: Factor structure recovery for dichotomous items. J. Educ. Meas. 2006, 43, 39–52. [Google Scholar] [CrossRef]
  75. Schreiber, J.B.; Nora, A.; Stage, F.K.; Barlow, E.A.; King, J.; Nora, A.; Barlow, E.A. Reporting structural equation modelling and confirmatory factor analysis results: A review. J. Educ. Res. 2006, 99, 232–338. [Google Scholar] [CrossRef]
  76. Fodikes, E. Pre-service teachers’ intention to use MUVEs as practitioners–A Structural Equation Modeling Approach. J. Inf. Technol. Educ. Res. 2017, 17, 47–68. [Google Scholar] [CrossRef] [Green Version]
  77. Henseler, J. Bridging design and behavioral research with variance-based structural equation modeling. J. Advert. 2017, 46, 178–192. [Google Scholar] [CrossRef]
  78. Finnegan, L.A.; Dieker, L.A. Universal design for learning-representation and science content: A pathway to expanding knowledge, understanding, and written explanations. Sci. Act. 2019, 56, 11–18. [Google Scholar] [CrossRef]
  79. Dalton, E.M. Beyond Universal Design for Learning: Guiding Principles to Reduce Barriers to Digital & Media Literacy Competence. J. Media Lit. Educ. 2017, 9, 17–29. Available online: https://eric.ed.gov/?id=EJ1160465 (accessed on 14 November 2021).
  80. Lietuvos Respublikos Švietimo Įstatymo Nr. I-1489 5, 14, 21, 29, 30, 34 ir 36 Straipsnių Pakeitimo ir Įstatymo Papildymo 451 Straipsniu Įstatymas, 2020 Nr. XIII-3268 [Law of the Republic of Lithuania on Education No. I-1489 Law Amending Articles 5, 14, 21, 29, 30, 34, 36 and Supplementing the Law with Article 451, 2020 No. XIII-3268], 2020, Vilnius. Available online: https://e-seimas.lrs.lt/portal/legalAct/lt/TAD/a396c630c07711eaae0db016672cba9c (accessed on 11 December 2021).
  81. Galkienė, A.; Monkevičienė, O. Improving Inclusive Education through Universal Design for Learning. Available online: https://link.springer.com/book/10.1007/978-3-030-80658-3 (accessed on 7 November 2021).
Sustainability 14 01748 g001 550
Figure 1. The research design.
Figure 1. The research design.
Sustainability 14 01748 g001
Sustainability 14 01748 g002 550
Figure 2. Optimal achievements of vulnerable groups of pupils in contact and remote learning: the teachers’ perspective.
Figure 2. Optimal achievements of vulnerable groups of pupils in contact and remote learning: the teachers’ perspective.
Sustainability 14 01748 g002
Sustainability 14 01748 g003 550
Figure 3. The Structural Models of “Lithuania_contact learning” and “Lithuania_remote learning”: Standardized estimates.
Figure 3. The Structural Models of “Lithuania_contact learning” and “Lithuania_remote learning”: Standardized estimates.
Sustainability 14 01748 g003
Sustainability 14 01748 g004 550
Figure 4. The Structural Models of “Latvia_contact learning” and “Latvia_remote learning”: Standardized estimates.
Figure 4. The Structural Models of “Latvia_contact learning” and “Latvia_remote learning”: Standardized estimates.
Sustainability 14 01748 g004
Sustainability 14 01748 g005 550
Figure 5. The Structural Models of “Estonia_contact learning” and “Estonia_remote learning”: Standardized estimates.
Figure 5. The Structural Models of “Estonia_contact learning” and “Estonia_remote learning”: Standardized estimates.
Sustainability 14 01748 g005
Table
Table 1. The distribution of Lithuanian, Latvian, and Estonian respondents according to their length of service and the location of their school.
Table 1. The distribution of Lithuanian, Latvian, and Estonian respondents according to their length of service and the location of their school.
CountryLithuaniaLatviaEstonia
Length of
Service		Frequency (n)%Frequency (n)%Frequency (n)%
1–5213.2610726.104411.67
6–10274.194410.734010.61
11–15375.74389.273810.08
16–20578.84358.544110.88
>2150377.9818645.3721456.76
City39861.7133481.4625667.90
Village24738.297618.5412132.10
Table
Table 2. Internal consistency of the questionnaire sections.
Table 2. Internal consistency of the questionnaire sections.
Groups of StatementsNumber of StatementsCronbach’s Alpha Coefficient
Section ACompliance of pupils’ achievements with their abilities30.857
Section BPractices of inclusive education210.927
Section CUse of digital technologies170.907
Section DIdentification of learning barriers 70.802
Table
Table 3. The values of Confirmatory Factor Analysis.
Table 3. The values of Confirmatory Factor Analysis.
Goodness of Fit IndexCMIN (χ2)χ2/dfCFIIFITLIGFIRMSEA
Value: Lithuania_contact1158.3482.0150.9460.9460.9410.9010.042
Value: Lithuania_remote962.7121.8910.9550.9560.9510.9060.040
Value: Latvia_contact707.8511.8430.9380.9390.9300.8990.047
Value: Latvia_remote624.7971.8710.9390.9400.9310.9000.048
Value: Estonia_contact516.0942.0080.9270.9280.9140.8980.054
Value: Estonia_remote616.3731.9950.9220.9230.9110.8970.054
Table
Table 4. Goodness of fit indices of the models “Lithuania_contact” and “Lithuania_remote”.
Table 4. Goodness of fit indices of the models “Lithuania_contact” and “Lithuania_remote”.
Goodness of Fit IndexCMIN (χ2)χ2/dfCFIIFITLIGFIRMSEA
Value: Lithuania_contact18.4511.4190.9980.9980.9960.9930.027
Value: Lithuania_remote12.2341.2230.9980.9990.9970.9950.020
Table
Table 5. Goodness of fit indices of the models “Latvia_contact” and “Latvia_remote”.
Table 5. Goodness of fit indices of the models “Latvia_contact” and “Latvia_remote”.
Goodness of Fit IndexCMIN (χ2)χ2/dfCFIIFITLIGFIRMSEA
Value: Latvia_contact59.4084.5700.9980.9980.9960.9930.086
Value: Latvia_remote9.0671.1330.9990.9990.9980.9940.019
Table
Table 6. Goodness of fit indices of the models “Estonia_contact” and “Estonia_remote”.
Table 6. Goodness of fit indices of the models “Estonia_contact” and “Estonia_remote”.
Goodness of Fit IndexCMIN (χ2)χ2/dfCFIIFITLIGFIRMSEA
Value: Estonia_contact53.2695.1050.9560.9570.9060.9480.084
Value: Estonia_remote66.3731.1950.9220.9230.9110.9030.054
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Galkienė, A.; Monkevičienė, O.; Kaminskienė, L.; Krikštolaitis, R.; Käsper, M.; Ivanova, I. Modeling the Sustainable Educational Process for Pupils from Vulnerable Groups in Critical Situations: COVID-19 Context in Lithuania, Latvia, and Estonia. Sustainability 2022, 14, 1748. https://doi.org/10.3390/su14031748

AMA Style

Galkienė A, Monkevičienė O, Kaminskienė L, Krikštolaitis R, Käsper M, Ivanova I. Modeling the Sustainable Educational Process for Pupils from Vulnerable Groups in Critical Situations: COVID-19 Context in Lithuania, Latvia, and Estonia. Sustainability. 2022; 14(3):1748. https://doi.org/10.3390/su14031748

Chicago/Turabian Style

Galkienė, Alvyra, Ona Monkevičienė, Lina Kaminskienė, Ričardas Krikštolaitis, Maile Käsper, and Ilze Ivanova. 2022. "Modeling the Sustainable Educational Process for Pupils from Vulnerable Groups in Critical Situations: COVID-19 Context in Lithuania, Latvia, and Estonia" Sustainability 14, no. 3: 1748. https://doi.org/10.3390/su14031748

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop