Digital competence of special education teachers: an analysis from the voices of members of school management teams

Citation: Montenegro-Rueda, M.; Fernández-Cerero, J. Digital Competence of Special Education Teachers: An Analysis from the Voices of Members of School Management Teams. Societies 2023, 13, 84. https://doi.org/10.3390/ soc13040084 Academic Editor: Sandro Serpa Received: 4 March 2023 Revised: 22 March 2023 Accepted: 27 March 2023 Published: 29 March 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). societie s Article Digital Competence of Special Education Teachers: An Analysis from the Voices of Members of School Management Teams Marta Montenegro-Rueda * and JoséFernández-Cerero Department of Teaching and Educational Organization, University of Seville, 41013 Seville, Spain *Correspondence: [email protected] Abstract: The use of digital technologies is one of the fundamental resources to favour the inclusion of students with special educational needs. However, recent studies continue to show a lack of use by teachers during the development of their teaching practices, especially in the field of special education. This article aims to analyse the level of digital competence of special education teachers through the perceptions of the school management team in Andalusia (Spain). The information is obtained through interviews with 62 members of school management teams. The results suggest that the low level of training and digital competence of special education teachers is the reason why they do not make use of digital tools in their teaching practice, due to a lack of teacher awareness, as well as the non-existent or insufficient development of training activities that hinder such training. In conclusion, there is a need to improve the professional development of special education teachers in digital competencies, as well as greater institutional involvement through strategic plans that promote such training. Keywords: digital competence; special education; teacher training; school management team 1. Introduction The teaching profession is in a constant state of flux, where teachers require new competencies to perform their work in a dynamic and complex context. We all know that the qualities of teachers are key to achieving educational goals. At present, international organisations and education systems around the world are designing so-called competence frameworks in response to the new competencies required by teachers in the so-called knowledge and information society. In this context, digital competence is a requirement of the professional profile of teachers, especially if we consider that the application of technologies requires constant training of teachers. Furthermore, digital competence is key in the design, implementation and evaluation of actions aimed at understanding and improving the education of a generation of students who are digital natives [ 1 ]. Likewise, the improvement of digital competencies is identified as a guarantee for the success of teaching quality. To promote the development of digital competence and educational innovation, at European level, the European Commission has created the European Framework for Digitally Competent Educational Organisations (DigCompOrg) and the European Framework for Digital Competences of Teachers commonly known as DigCompEdu [ 2 ]. In the Andalusian context, teacher training is a fundamental element in responding to the new educational challenges posed by society, being the key factor for the development of quality and equity in education. In this sense, the importance of the regulations governing initial and in-service teacher training in the Autonomous Community of Andalusia is clear [ 3 ]. Likewise, the Andalusian System of Ongoing Teacher Training highlights that, among the priority lines, training actions and strategies that promote the level of digital competence of teachers in accordance with the European Framework for Digitally Competent Educational Societies 2023,13, 84. https://doi.org/10.3390/soc13040084 https://www.mdpi.com/journal/societies Societies 2023,13, 84 2 of 15 Organisations (DigCompOrg), through advice and support to educational centres, should be carried out [4]. On the other hand, the literature shows that the digital proficiency of university teachers fluctuates between “low” [ 5 ], “acceptable” [ 6 ] or “medium/medium-high” [ 7 ]. This contrasts with most of the teachers’ recognition of the potential of information and communication technologies (hereinafter referred to as ICT) and their positive effect on teaching [ 8 ]. Studies such as those by García-Ruiz et al. [ 9 ] show that the level of digital competence perceived by teachers is lower than that which they possess. On the other hand, in a review of the literature on digital competence, Fernández-Batanero et al. [ 10 ] note teachers’ use of ICT for basic activities such as the presentation of visual resources or word processing programmes, followed by Internet access and, to a lesser extent, other more advanced applications such as the creation and editing of digital resources. However, when it comes to the development of digital competence to support learners with special educational needs (SEN), the literature is more limited. Internationally, many studies highlight the importance of integrating technology to improve the learning of “all” students [ 11 , 12 ], but there are fewer studies that place special emphasis on students with special educational needs due to disabilities [ 13 ], even though the United Nations Convention on the Rights of Persons with Disabilities [ 14 ] considers ICT as a key tool to promote equity and equal opportunities. The lack of training and knowledge that teachers have regarding the types of technologies that can be used with this group, the possibilities they offer and the function for which they can be used [ 15 – 17 ] is also highlighted. This aspect hurts the use of ICTs, hindering access to information and the empowerment of people’s capabilities and, in the case of people with disabilities, helping to alleviate their difficulties or minimising them [18]. In recent years, the study of digital competence and disability reveals that the research topics studied contain three main trends: the interaction of technology with people with disabilities; the relationship of technology with communication in people with disabilities; and the observation of the relationship between e-inclusion and digital competence [ 19 ]. In this sense, due to the importance of the integration of technologies to favour the learning of all students in the framework of an inclusive school, and the preceding problematizing context of the scarce use of technologies in special education classrooms, it is necessary to identify how special education teachers are developing their digital teaching competence. The aim of the study is to transform the development of the digital competence of special education teachers, as well as the teachers’ perception of the use of technologies in special education classrooms. 2. Purpose and Research Questions Starting from the previous context, the aim of the research carried out was to analyse the level of digital competence of special education teachers in the Autonomous Community of Andalusia, considering the perceptions of the members of the management team of the educational centres. Based on this objective, the following research questions (RQ) are explored: RQ1. What are the perspectives of the school management team on the level of digital competence of special education teachers in Andalusia? RQ2. Does the ownership of the school condition the level of digital competence of special education teachers as perceived by the school management team? RQ3. What are the perspectives of school management teams on the challenges of promoting the digital competence of special education teachers (i.e., what actions and strategies are associated with the promotion and development of digital literacy experiences)? By answering these research questions, we aim to provide a deeper analysis of the digital competence of special education teachers, as well as to provide empirical evidence on digital teacher training experiences for special education teachers. Societies 2023,13, 84 3 of 15 3. Method 3.1. Design To respond to the research objective, a descriptive and comprehensive qualitative methodology was adopted to understand the research problem. Specifically, data were collected through semi-structured interviews. The qualitative content analysis presented is based on Glaser and Strauss’ Grounded Theory of group and individual opinions [ 20 ]. This methodology, used in multiple research projects in the educational context [ 21 , 22 ], follows a coding process according to Charmaz [ 23 ] based on a systematic collection and analysis of the data to build a grounded theory on the digital competence of special education teachers. 3.2. Participants The pool of informants consisted of 62 professionals in the education sector. Their gender distribution was 35 (60%) men and 27 (40%) women. Non-random purposive sampling was used to select the sample [ 24 ]. Table 1provides information on the university teachers interviewed. Table 1. Distribution of participants by province and ownership of the school. Province Public Private-Concerted Private Total N◦. % N◦. % N◦. % N◦. % Almeria 4 6.45 - - - - 4 6.45 Cadiz 3 4.84 1 1.61 - - 4 6.45 Cordoba 4 6.45 1 1.61 1 1.61 6 9.68 Granada 8 12.90 3 4.84 3 4.84 14 22.58 Huelva 5 8.06 - - 1 1.61 6 9.68 Jaen 3 4.84 1 1.61 - - 4 6.45 Malaga 5 8.06 1 1.61 2 3.23 8 12.9 Seville 9 14.52 3 4.84 4 6.45 16 25.81 Total 41 66.12 10 16.12 11 17.74 62 100 Source: own elaboration. As can be seen, it is the school heads from Seville (f= 16, 25.81%) who participated most in the interviews, followed by those from Granada (f= 14, 22.58%) and Malaga (f= 8, 12.9%). 3.3. Instrument The instrument used for data collection was the structured interview. These were conducted during the months of June–September 2022. The designed interview is semistructured, combining open, closed, and multiple-choice questions, since, as Grande and Abascal [ 25 ] state, we cannot provide the answers of the participants in all the questions. The interview design aims to respond to the purpose of the study, which is to find out the level of digital competence of special education teachers. After reviewing the specialised scientific literature on the field of study, an interview script was designed and validated through the expert judgement strategy, applying the Delphi method. Two mechanisms were established for the selection of the experts. Firstly, they had to meet two or more of the following criteria: (a) Teaching related to “special education”, (b) Teaching related to “educational technology”, (c) Having experience in digital teacher training in the framework of an inclusive school, and (d) Having made a scientific publication related to “technology”, “special education” and “teacher training”. Secondly, the “Expert Competence Coefficient” (K-Coefficient) procedure was used for their selection, obtained from the formula: K = 1/2 (Experience Coefficient “Kc” + Argumentation Coefficient “Ka”) [ 26 ]. The value of the Coefficient K was higher than 0.8 in the 16 selected, which indicates an excellent degree of acceptance [27]. The experts’ evaluations were carried out anonymously and in successive rounds, to reach a consensus, but with the greatest possible autonomy of the participants (Delphi method). Societies 2023,13, 84 4 of 15 To facilitate the experts’ analysis, a four-point Likert scale has been applied to each question, where 1 is “strongly disagree” and 4 is “strongly agree” regarding the content, importance, and appropriateness of each question. There was also a section for comments at the end of the interview in case the expert wished to make any remarks. Finally, the semi-structured interview script (Table 2), consisting of 13 questions, was as follows: Table 2. Interview script. Interview Script Questions Preliminary questions 1. Let’s start, what is your name and age? 2. What is your current position in the school? 3. How many years of experience have you had in that position (length of service)? 4. What type of school do you work in (ownership of the school)? 5. Where is your school located (province of the school)? Background knowledge 6. When we talk about students with special educational needs, what is the first thing that comes to mind? What does this concept mean to you? Profile of special education teachers 7. In general, do you consider that special education teachers are aware and prepared to help students with special educational needs using technology? 8. What are the main barriers or limitations you encounter in your training in digital competences? 9. What are the strengths of an education teacher trained in digital competences? Strategies of the school 10. Does your educational centre develop training experiences for the educational application of technologies for students with special educational needs? 11. Does the management of the educational centre promote these initiatives and is the teaching staff given incentives? In what way are they promoted? 12. Of the following six options, select the three which you consider to be priorities in special education teacher training courses. (a) To learn about specific technological tools, devices, and software for students with special educational needs. (b) To learn didactic strategies to carry out curricular adaptations supported by technology for students with special educational needs. (c) Identify the appropriate type of technological tool according to the educational needs of the students. (d) Locate websites with educational resources for students with special educational needs. (e) Know in a practical way digital tools that enhance accessibility. (f) To learn about good inclusive practices from technology. Acknowledgements and farewell 13. Finally, any questions or comments you would like to add? Source: own elaboration. 3.4. Data Collection and Analysis Procedure An exploratory study was carried out between September and December 2022. To select the sample, the official website of the “Junta de Andalucía” was consulted in order to obtain the database of all the schools in the Autonomous Community of Andalusia. Societies 2023,13, 84 5 of 15 With this database, contact was attempted by telephone calls with 135 eligible schools, of which only 96 responded to the call, and finally 62 participants completed the telephone interview. Using an interview script designed by the researchers, the call explained the purpose of the study and the voluntary nature of participation in the study, informing participants that they and their school would not be identified in any future communication. All interviews were conducted with the verbal informed consent of the participants and were audio-recorded for transcription to ensure anonymity and confidentiality, for subsequent qualitative analysis using the computer tool Atlas.Ti version 9.1 [ 28 ]. This allowed us to extract representative textual quotes from the participants. For the analysis of the data, the technique of content analysis was used from a qualitative perspective [ 29 ]. The phases followed by the researchers were pre-analysis (by reading the interview transcripts to identify and code common themes); formation of the categorical system; coding; analysis and identification of quotes or fragments linked to the categories (evidence); and interpretation of the data using the computer tool that facilitates qualitative data analysis, Atlas.Ti. The research process must be governed by criteria of rigour and precision that ensure the reliability and validity of the results. The credibility of the results is based on prior work on the concordance between coders (category system). To this end, we calculated the Fleiss Kappa to determine the value of the concordance between coders (reliability). We obtained a Fleiss Kappa of 0.857 for overall concordance strength. This index, according to the interpretation of Fleiss [ 30 ], can be interpreted as excellent, as it is above 0.75. Being at the highest level of agreement, we can conclude that the results are reliable and significant. The categories selected for the study (Table 3) revolved around: professional profile (sex, province, position, length of service; ownership of the school); concept of special educational needs; digital awareness and training of special education teachers; barriers to digital training; development of training experiences and initiatives with the use of ICT; promotion of training and initiatives with the use of ICT; and priority in training. Table 3. Categories, subcategories, codes, and indicators resulting from the interpretative analysis of the interviews. Category Subcategory Code Indicator Professional profile: contextualisation of the interviewees. Sex PPS Male; female Province PPP Almeria, Cadiz, Cordoba, Granada, Huelva, Jaen, Malaga, Seville Position PPPO Headmaster, head of studies, ICT coordinator Length of service PPLS 0 to 2 years, 3 to 5 years, 6 to 10 years, 11 years and more Ownership of the school PPO Public, private, private-concerted Concept of special educational needs: understood as students who require, for a period of their schooling or throughout it, certain support and specific educational attention derived from disability or serious behavioural disorders. Knows the concept CC Correct answer Not familiar with it CI Incorrect answer Awareness and digital training of special education teachers: Awareness: respondents’ perception of whether special education teachers are aware of the importance of carrying out digital training activities. Training: respondents’ perception of the level of digital training and preparation of special education teachers. Aware and trained AT Manifests the existence of both aspects Aware yes, trained no ATN Manifests only one aspect Neither aware, nor trained ATNN Manifests the non-existence of the two aspects Societies 2023,13, 84 6 of 15 Table 3. Cont. Category Subcategory Code Indicator Barriers to digital literacy: obstacle that prevents or hinders the implementation of training activities. Attitude of teachers BAT It expresses the willingness and attitude of the teaching staff Age BAG State aspects related to the years Financial BF Financial aspects Lack of training opportunities BTO Lack of training courses Lack of school equipment BSE Availability of digital tools Lack of time BT Time-related aspects Lack of recognition BR The need to incentivise innovative teachers Rapid technological updating BRTU Expressing the rapid advances in technology Strengths of a digitally trained teacher: benefits of digitally trained teachers Use of digital devices and tools SDD Mentions the implementation of technologies Communication and information SCI Mentions communication channels Interaction and collaboration SIC Mentions student participation and the flexibility of teaching Content creation SCC Mentions the development and adaptation of resources and materials Development of training experiences and initiatives with the use of ICT: training actions designed and developed for special education teachers. Development of training experiences DTE Affirmative answer No training experiences are developed DNTE Negative answer Promotion of training and initiatives with the use of ICTs: to encourage in some way an action to develop or to increase a positive aspect towards it. Promotion of training PT Answer in the affirmative (courses, seminars, congresses or conferences, research projects, working groups). No promotion of training PNT Negative answer Priority in training: respondents’ preference for the content of training experiences (multiple choice answer). (a) To learn about specific technological tools, devices, and software for students with special educational needs. PA Same as subcategory (b) To learn didactic strategies to carry out curricular adaptations supported by technology for students with special educational needs. PB Same as subcategory (c) Identify the appropriate type of technological tool according to the educational needs of the student. PC Same as subcategory (d) Locate websites with educational resources for students with special educational needs. PD Same as subcategory (e) Know in a practical way digital tools that enhance accessibility. PE Same as subcategory (f) To learn about good inclusive practices from technology. PF Same as subcategory Source: own elaboration. 4. Results Based on the empirical basis of the informants’ perceptions, the semantic network of the categories and subcategories is presented below (Figure 1). Societies 2023,13, 84 7 of 15 Figure 1. Semantic network of categories and subcategories. 4.1. Characteristics of the Participants The interview was conducted with a representative sample of 62 education professionals who hold the position of school head in Andalusia. Table 4shows the demographics and characteristics of the participants. The participants were mostly male (60%), holding a position as headmaster (46.77%) and with a length of service of 3 to 5 years (46.77%). Table 4. Interview script. Subcategory Indicator N◦. Percentage Sex Male 35 60% Female 27 40% Position Headmaster 29 46.77% Head of studies 25 40.33% ICT coordinator 8 12.9% Length of service 0 to 2 years 17 27.42% 3 to 5 years 29 46.77% 6 to 10 years 10 16.13% 11 and over 6 9.68% Source: own elaboration. 4.2. Responses to the Interview Topics All interview participants were asked about the definition of the concept of students with special educational needs. Among the main results, we found that only 37.1% of the interviewees defined the concept correctly, and 62.9% defined it incorrectly. The incorrect definition of the concept SEN was generalised by the participants in all provinces. If we analyse the response according to the variable “Ownership of the school”, 80% of those interviewed in public schools know the meaning of the SEN concept. On the other hand, participants from privately owned schools (100%) provided the highest percentage of incorrect answers, as can be seen in Figure 2. Societies 2023,13, 84 8 of 15 53,66% 46,34% 10% 90% 0% 100% 0,00% 20,00% 40,00% 60,00% 80,00% 100,00% 120,00% Yes No Yes No Yes No Public Private-concerted Private Figure 2. Ownership of the school and concept of SEN. Considering the results, the participants were asked whether they believed that the special education teachers in their schools were aware of and trained in the use of technologies for working with students with special educational needs. In this sense, 54.84% of the respondents acknowledged that special education teachers are aware of, but not trained in the use of technologies for students with special educational needs, compared to 32.26% who stated that teachers are neither trained nor prepared for their implementation. Only 12.9% of the participants consider that special education teachers are trained in digital competences. The results are similar if we analyse the responses according to the province in which the participants’ schools are located. However, if we analyse the responses according to the school ownership variable (Figure 3), the schools with the highest percentage of responses in the category “neither aware nor prepared” were private schools (72.73%), while public schools had the highest percentage of positive responses in the category “aware and prepared” (12.19%). 12.19% 68.29% 19.51% 10% 40% 60% 9.09% 18.18% 72.73% 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% Aware and trained Aware yes, but not trained Neither aware nor trained Aware and trained Aware yes, but not trained Neither aware nor trained Aware and trained Aware yes, but not trained Neither aware nor trained Public Private-concerted Private Figure 3. Level of teacher awareness and training according to school ownership. Societies 2023,13, 84 9 of 15 On the other hand, regardless of the conceptual notions held by the interviewees, the participants had the opportunity to argue the factors or barriers that underpin the low level of awareness and training in digital competences among special education teachers in Andalusia, as shown in Table 5. Among the main reasons mentioned by key informants, the following stand out: the scarce training offered (25%), teachers’ attitude (22%) and economic factors (16%). Table 5. Barriers to digital competence. Category Subcategory Percentage Barriers to digital training Age 8% Attitude of teachers 22% Financial 16% Lack of training opportunities 25% Lack of school equipment 10% Lack of time 12% Lack of recognition 4% Rapid technological updating 3% Source: own elaboration. “In my opinion, teachers are interested in training courses, but I think that there is insufcient training on specic aspects of the use of technology with learners with educational needs.” (INT.32) “Honestly, I think that teachers are getting more and more tired and stressed, and they don’t have the time or the desire to train.” (INT.53) “I imagine that one of the barriers is nancial, as the development of such specic courses is usually offered by private institutions, and not all teachers are willing to invest in so many courses.” (INT.04) After finding out the level of awareness and digital training, as well as the barriers to their training, that special education teachers have, it is considered essential to check the degree of development of training experiences on technologies applied to students with special educational needs that are being carried out according to the opinion of those interviewed. In this sense, 72.58% of those interviewed recognise that training experiences focused on the use of technologies for students with educational needs are scarce or nonexistent, or that they focus on the general use of technologies without considering the diversity of students, compared to 27.42% who consider the opposite to be true. With regard to the development of training experiences depending on the provinces of Andalusia, the data do not vary considerably, since in the provinces of Granada, Malaga and Seville, the participants indicated that no training experiences are developed (75%, 70% and 68.75%, respectively). Likewise, as shown in Figure 4, the interviewees showed that the digital competence of special education teachers presents numerous strengths in educational quality, highlighting, mainly, that the use of technologies as didactic resources in the teaching-learning process depends on their level of digital training (43%) or for the creation of specific materials and contents for students (35%). To a lesser extent, but no less important, their digital training improves communication with students (13%), as well as their interaction and flexibility of teaching students (9%). “Teachers feel insecure about using technology in their teaching practice; if they had this acquired competence, technology would be an essential resource in the classroom.”(INT.33) “Knowing how to use technology appropriately allows teachers to adapt their materials and resources to students with educational needs.”(INT.57)