Integration and Management of Technologies Through Practicum Experiences: A Review in Preservice Teacher Education (2010-2020)

OPEN ACCESS CONTEMPORARY EDUCATIONAL TECHNOLOGY ISSN: 1309-517X (Online) 2022, 14(2), ep352, https://doi.org/10.30935/cedtech/11540 Research Article Copyright © 2022 by the authors; licensee CEDTECH by Bastas. This article is published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). Integration and Management of Technologies Through Practicum Experiences: A Review in Preservice Teacher Education (2010-2020) Irene García-Lázaro Department of Communication and Education, Faculty of Social and Human Sciences, Universidad Loyola Andalucía, Seville, Spain Department of Research Methods and Diagnosis in Education, Faculty of Education Sciences, University of Seville, Seville, Spain ORCID: 0000-0001-9818-6170 Jesús Conde-Jiménez Department of Educational Theory and History and Social Pedagogy, Faculty of Education Sciences, University of Seville, Seville, Spain ORCID: 0000-0002-4471-5089 María Pilar Colás-Bravo Department of Research Methods and Diagnosis in Education, Faculty of Education Sciences, University of Seville, Seville, Spain ORCID: 0000-0003-3000-075X Received: 11 Nov 2021 Accepted: 29 Dec 2021 Abstract The presence and use of technologies in educational settings is constantly increasing. Therefore, initial teacher education needs to prepare future teachers to deal with this technological implementation from both practical and pedagogical perspectives. This paper examines the treatment of technologies that initial teacher education offers to early childhood education and primary education preservice teachers facing their practicum experiences. A bibliometric and thematic review during the 2010-2020 period is conducted in WoS, Scopus, PsycInfo, and ERIC databases. An analysis of co-occurrence of terms and the creation of bibliometric maps are considered. The thematic analysis follows an inductive approach. Three big areas are addressed through this approximation: consideration of technologies before practicum, the use of technologies at the schools, and the study of preservice teacher’s personal variables. Findings show the importance of working with technological preparation of university supervisors and cooperating teachers when teacher candidates do their practicum. In this proposal, to consider the self-efficacy and technological, pedagogical and content knowledge model of preservice teachers is encouraged. Conclusions underline the importance of teaching and strengthening pedagogical and reflective experiences during the practicum. Limitations are considered. Keywords: initial teacher education, bibliometric review, practicum, TPACK, educational technologies, teaching practices INTRODUCTION The presence of technologies in the teacher training continues being an essential topic as they have become subjects into the university curriculum; it is also an axis in teacher competency frameworks such as the European DIGCOMPEDU (Caena & Redecker, 2019; Reisoglu & Cebi, 2020). During the initial teacher García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 2 / 19 education (ITE), teacher candidates interact with technological tools created to help their professional performance. However, technologies are not only objects; future teachers must develop abilities, attitudes and Technological, Pedagogical and Content Knowledge (TPACK) through their academic training to create successful learning paths for their students (Cabero-Almenara & Martínez, 2019; Mishra & Koehler, 2006; Starkey, 2020). We need to consider children’ interactions with technology in their daily routine to teach preservice teachers (PTs) pedagogical uses of technologies. Regarding practicum experiences, the increase of technologies in early childhood and primary education classrooms allows PTs to manage devices and tools while helping children to reach learning outcomes (Area-Moreira et al., 2016). Technologies are transversal components for the ITE (United Nations Educational, Scientific and Cultural Organization, 2016), thus, the responsibility toward learning about technologies’ management in practicum settings starts from university supervisors (USs) and cooperating teachers (CTs). They become pivotal agents to confront a possible blended learning and to guide and encourage teacher candidates to use technologies in their teaching (Sola‐Martínez et al., 2020). Recently, COVID-19 has forced the ITE to transform the way PTs learn, for instance, supervising and planning the teaching strategies to fulfil new challenges that face-to-face education confronts. Although practicum is part of this transformation due to the strong on-site character that it presents, teaching practices prepare PTs for their future profession so more technological experiences start to be considered to continue showing the characteristics that a school involves from an online perspective (i.e., simulation of practicum experiences) (Kim, 2020; Sasaki et al., 2020). However, there is a lack of information about how PTs, CTs and USs interact in practicum contexts considering the management of technologies. For instance, recent literature points to the relationship between internal variables of PTs and the TPACK model in the improvement of their practicum experiences as well as in personal perceptions toward their professional roles (Han et al., 2017; McGarr & Gallchóir, 2020; Polly et al., 2010). Thus, further research of this issue is needed to clarify two areas of interest from bibliometric and thematic points of view: the tendency of publication about this topic, and the consideration of variables related to technologies before and during practicum. PURPOSE The purpose of this study is to draw a visual and comprehensible examination of the perceptions and treatment of technologies made through ITE toward practicum experiences. This aim involves the training offered by USs, as well as the subsequent work from schools made by CTs. This general objective is explained through specific research questions related to each area of study: 1. First area: Bibliometric information. What countries and journals have the most articles published? What methodological designs are the most predominant in this area? 2. Second area: Thematic analysis. a. Before the practicum: Are technologies part of the previous training to the practicum? Are technologies presented as resources or as reflection mechanisms? b. During the practicum: How are technologies used at the schools? What is the role of CTs? What variables are involved in PTs’ management of technologies? METHODOLOGY Identification and Selection of Articles To conduct the review, this study replicates the methodological guidelines provided by Fernández-Batanero et al. (2019) and Starkey (2020). Thus, the focus of this contribution is the search of three cornerstones: a) technologies, b) practicum, and c) preservice teachers. The methodology pattern starts with the identification of the articles sample that follows these three cornerstones. The comparison of different García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 3 / 19 databases method was selected as the most suitable tool to measure trends in educational research (Levine- Clark & Gil, 2009). Thus, a quantified bibliographical search related to technologies in practicum settings was conducted in four educational data bases: ERIC, PsycInfo, Scopus, and Web of Science (WoS). It is a computer-assisted search developed from January 2020 to September 2020. A deductive approach is selected to do the exploration: some keywords from the research questions were selected to guide the first exploration, later, some replacement terms were selected, and finally, a search string was proposed through the combination of Boolean operators with keywords. The search within keywords allows to find the most relevant articles suggesting specific descriptors that would appear on the title, keywords and abstract. The descriptors were: ((ICT) OR (TIC)* OR (Technolog*) AND ((Practicum*) OR (Teaching Practice) OR (Student Teaching) OR (Field Experience)) AND ((preservice teacher) * OR (pre-service teacher) OR (student teacher*) OR (teacher candidate)). The first filtering is conducted through previous mentioned descriptors. If there were enough information in the summary to consider the article, it was exported to the information management platform (Mendeley). However, if any aspects were not clear after reading the summary of the articles (i.e., sample, PTs’ s bachelor’s degree, collection data process, etc.), it was decided to download and read the complete contribution to check the adequacy of a second reading. When the first filtering was successful, the article was imported to Mendeley. Mendeley allowed to classify papers in different folders for each data base; it also showed bibliometric details, such as the country and continent of origin, the date of publication, etc. It also allowed to create a workgroup where authors discussed together about readings and the final decisionmaking. It enabled highlighting and creating memos (notes) for a deep analysis of the information. Inclusion and Exclusion Criteria Table 1 and Table 2 show the followed criteria to include or exclude any studies. Table 1. Selection criteria Articles Area Period Review PTs courses Language Empirical Review Social sciences & education 2010-2020 Peerreview Early childhood Primary education Spanish English Table 2. Exclusion criterio Area of interest Type of manuscript Subjects or programs (methods course) Evaluations (eportfolios) Specific topics (Special Education Needs, EFL...) Incomplete text Dissertation Book Conference Proceedings FINDINGS The first filtering resulted in a sample of 172 articles. A complete reading excluded 135 articles. Finally, 37 articles were considered. Within the total number of studies, 12 studies were found in the four databases; thus, exclusively, 31 articles were selected from ERIC, 16 articles from PsycInfo, 33 articles from Scopus, and 27 from WoS. 35 articles were traditional empirical studies and 2 manuscripts were empirical research based on ongoing projects (4; 25). Table 3 summarises the identification data of the articles; authorship is numbered to facilitate the future reading in advance. The analysis in Mendeley was guided by the three main cornerstones and notes were taken in relation to the framed research questions. The latent topics were identified through collecting as much information as possible to make the thematic analysis. This examination identified the axis patterns used for the construction of each article. Constant readings were needed to understand these patterns and different ones that emerged. García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 4 / 19 First Part: Bibliometric Information The number of publications related to use of technologies, field experiences and preservice teachers from early childhood or primary education is limited. In Table 3, information related to the journal’s country of origin as well as the countries where research is most developed can be seen. The highest publication rate is found in 2011 and 2017, with 5 and 8 publications, respectively. The years 2014, 2015, and 2019 also present some publications (4 respectively). Six journals published more than one article from 2011 to 2020: Australasian Journal of Educational Technology (10; 12), Teaching and Teacher Education (20; 24; 34), Computers & Education (8; 27), Education and Information Technologies (29; 30), The Asia-Pacific Table 3. First author, journal, and database (DB) indexing information First author Country Journal ERIC PsycInfo Scopus WoS All DBs 1. Aslan and Zhu (2015) Turkey TOJET: The Turkish Online Journal of Educational Technology X X X 2. Aslan and Zhu (2016) Turkey International Journal of Research in Education and Science X X 3. Aslan and Zhu (2017) UK British Journal of Educational Technology X 4. Bladergroen and Chigona (2019) South Africa Africa Education Review X X X 5. Browne (2015) Australia Asia-Pacific Journal of Health, Sport and Physical Education X X 6. Cakir and Yildirim (2013) Philippines The Asia-Pacific Educational Research X X 7. Charbonneau-Gowdy (2015) UK The Electronic Journal of e-Learning X X X 8. Chen (2010) UK Computers & Education X 9. Dong and Mertala (2019) UK Early Years. An International Research Journal X 10. Figg and Jamani (2011) Australia Australasian Journal of Educational Technology X X X 11. Franklin et al. (2018) USA TechTrends X X 12. Gao et al. (2011) Australia Australasian Journal of Educational Technology X X X 13. Gill et al. (2014) Australia Australian Journal of Teacher Education X X X 14. Gill and Dalgarno (2017) UK Technology, Pedagogy and Education X 15. Goldstein and Tesler (2017) USA Interdisciplinary Journal of E-skills and Lifelong Learning X 16. Guillén-Gámez et al. (2018) Australia Technology, Knowledge and Learning X X X 17. Habibi (2020) USA The qualitative Report X 18. Hammond et al. (2011) UK Journal of Computer Assisted Learning X 19. Hu and Yelland (2017) USA Journal of Early Childhood Teacher Education X 20. Instefjord and Munthe (2017) UK Teaching and Teacher Education X X X 21. Jita (2016) South Africa Perspectives in Education X X 22. Kim (2020) Australia International Journal of Early Childhood X X X 23. Maestre et al. (2017) Spain Bordón. Revista de Pedagogía [Staff. Pedagogy Magazine] X X 24. Martinovic and Zhang (2012) UK Teaching and Teacher Education X 25. Melville et al. (2011) Spain Electronic Journal of Research in Educational Psychology X 26. Merc (2015) Turkey TOJET: The Turkish Online Journal of Educational Technology X X X 27. Mouza et al. (2014) UK Computers & Education X X X 28. Ntuli (2017) USA Open Journal for Educational Research X X 29. Olivares and Castillo (2018) USA Education and Information Technologies X X X 30. Rowston et al. (2019) USA Education and Information Technologies X X X 31. Sahin and Kabakci (2014) Turkey Education Sciences: Theory and Practice X 32. Szeto and Cheng (2014) Philippines The Asia-Pacific Educational Research X X X 33. Szeto and Cheng (2016) USA Journal of Educational Computing X 34. Vratulis et al. (2011) UK Teaching and Teacher Education X 35. Wake (2013) USA Contemporary Issues in Technology and Teacher Education X X 36. Walker et al. (2019) USA The New Educator X X X 37. Zipke (2017) Philippines The Asia Pacific Journal Of Education X X Total 31 17 33 27 10 García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 5 / 19 Educational Research (6; 32), TOJET: The Turkish Online Journal of Educational Technology (1; 26), and Education and Information Technologies (29; 30). The main research design is clearly qualitative in the last decade. The predominant methodological design is the case study through interviews, observations and field notes, analysis of documents (narratives, diaries, portfolios, etc.) and focus groups (see Figure 1, Figure 2, and Figure 3). Secondly, the mixed methodology combines surveys and questionnaires or scales with interviews and focus groups. Thirdly, exploratory studies, with non-experimental, cuasi-experimental, correlational designs and the design and validation of structural equation models were found (respectively). Scales, surveys, and questionnaires are the most used quantitative techniques. As Figure 1, Figure 2, and Figure 3 show, some of the articles appeared in more than one database, or in all databases. Scopus presents the highest rate of publication in relation to quantitative studies. In relation to qualitative research, ERIC and Scopus present the same rate of publications. ERIC is the database that publishes more mixed papers. The quantitative approach presents most of publications in 2017, the qualitative approach obtained the highest rate in 2015, and the mixed methodology presents the highest level of publications in 2014. As the figures show, databases with a greater influence internationally (WoS and Scopus) presented less articles about this issue. Figure 1. Quantitative approach by database and year of publication Figure 2. Qualitative approach by database and year of publication García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 6 / 19 According to the inclusion criteria, the number of articles is reduced from 2010 to 2020. Methodologically, some contributions created structural equation models to explain the relationships between specific variables that intervene in the topic of this issue (3; 8). Quantitative articles presented exploratory analysis, correlations, and regressions to show descriptive data (2; 6; 16; 12; 18; 19; 20; 21; 24; 26; 27; 31; 32; 36; 37). Qualitative findings present specific cases that are illustrative for future replications in similar contexts (1; 4; 5; 6; 7; 9; 10; 11; 12; 13; 14; 17; 18; 19; 21; 22; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 36; 37). VOSViewer software was used to build a visual interpretation of the co-occurrence of the cornerstones for the research. This analysis presents to what extent a term and a group of related terms appear in the search about the topics of our review. KW+ system was selected to obtain bibliometric results from WoS and Scopus databases since both are the most visited platforms internationally (Pranckutè, 2021). The search filters in WoS were KW+, co-occurrence and full counting; the filters in Scopus were co-occurrence and all keywords. Bibliometric analysis from Web of Science (WoS) The homogeneity of the search’s results in WoS was analysed and three thematic clusters were found through VOSViewer (see term map in Figure 4 and density map in Figure 5). The weight of each descriptor (term) corresponds to the size of the node. The node also represents the term’s links with other descriptors. These links (curves lines) describe the connections shared by the nodes. The proximity between two descriptors also represents the strength of the relationship. In Figure 4, the size represents the frequency of appearance of the descriptor; the intensity of the clusters come from the number of KW+, the frequency of occurrence of those KW+, etc. The red cluster (the most highlighted and the biggest one) implies a high correlation of KW+; however, clusters that appear in the margins of the image show a low correlation. The three clusters (red, green, and blue, in order of relevance) show our three cornerstones: • Red Cluster 1: It represents the findings related to the PTs’ training, that is, the role played by PTs and their USs. We find terms such as teacher educator, reflection, opportunity, teacher education program, knowledge, etc. This cluster involves 34 terms. Since the size of the descriptors determines the weight of the cluster, the terms with the highest weight are preservice teacher (links=59, occurrences=128, total link strength=697), knowledge (links=57, occurrences=96, total link strength=541), teacher education program (links=46, occurrences=30, total link strength=324) teacher educator (links=53, occurrences=39, total link strength=214). Figure 3. Mixed methodological approach by database and year of publication García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 7 / 19 • Green Cluster 2: It represents variables in practicum settings and their relationship with the use of technology. This cluster involves 19 terms. The heaviest descriptors are mode (links=58, occurrences=79, total link strength=528), data (links=59, occurrences=54, total link strength=483), factor (links=58, occurrence=59, total link strength=424), influence (links=47, occurrence=184, total link strength=27), attitude (links=50, occurrence=336, total link strength=38), and theory (links=56, occurrence=264, total link strength=37). • Blue Cluster 3: It involves everything related to technologies. This cluster includes 7 descriptors. The most highlighted terms are: TPACK (links=48, occurrences=295, total link strength=38), technological pedagogical content knowledge (links=43, occurrences=275, total link strength=65), content knowledge (links=45, occurrence=245, total link strength=27), ICT (links=56, occurrences=331, total link strength=48), and communication technology (links=54, occurrence=221, total link strength=28). In the density map (Figure 5), the KW+ circles and the colour indicate the relevance level of each descriptor. The KW+ related to the field of practicum and ITE is coloured in yellow and is located in the centre of the image, that is, a high relevance of its co-occurrence (preservice teacher, teacher education program, teacher educator, TPACK, data, model, factor, attitude). The colour green-blue represents less density of cooccurrences of KW+ (gender, discipline, access, effectiveness). Figure 4. Term map for WoS analysis García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 8 / 19 Bibliometric analysis from Scopus The search of information’s homogeneity was analysed. Four thematic clusters were obtained: red, blue, green, and yellow (Figure 6): • Red Cluster 1: It represents the bases of the ITE. It includes terms such as educator, reflection, instruction, lesson, pedagogy, etc. This cluster involves 12 terms. The heaviest terms are educator (links=35, occurrences=200 and total link strength=52), reflection (links=35, occurrences=117, total link strength=31), instruction (links=35, occurrences=120, total link strength=31) and pedagogy (links=33, occurrences=103, total link strength=27). • Green Cluster 2: It represents factors that intervene in the ITE through using technologies. It includes terms such as ability, effect, environment, etc. This cluster involves 11 descriptors. The heaviest items are teaching practice (links=34, occurrence=102, total link strength=28), university (links=33, occurrences=109, total link strength=35) environment (links=35, occurrences=113, total link strength=30), information (links=34, occurrences=108, total link strength=25), and attitude (links=29, occurrences=66, total link strength=20). • Blue Cluster 3: It involves factors that mediate the training and learning process through field experiences. This cluster includes 8 descriptors. There are terms such as interest, implementation, professional development, etc. The most highlighted items are interview (33 links, 114 occurrences and 32 total link strength), training (links=28, occurrences=81, total link strength=26), integration (links=31, occurrence=104, total link strength=26) and implementation (links=31, occurrences=72, total link strength=20). • Yellow Cluster 4: This cluster represents technologies shown and used through ITE by PTs. This cluster involves 5 items. The heaviest terms are TPACK (links=35, occurrences=99, total link strength=32), content knowledge (links=26, occurrences=6, total link strength=16), and technological pedagogical content knowledge (links=33, occurrences=90, total link strength=18). Figure 5. Density map for WoS analysis García-Lázaro et al. / Contemporary Educational Technology, 2022, 14(2), ep352 9 / 19 In the density map (Figure 7), the KW+ circles and their colour indicate the level of relevance of the terms. 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The New Educator, 14(4), 342-262. https://doi.org/10.1080/1547688X.2017. 1401191 Correspondence: Irene García-Lázaro, Department of Communication and Education, Faculty of Social and Human Sciences, Universidad Loyola Andalucía, Seville, Spain and Department of Research Methods and Diagnosis in Education, Faculty of Education Sciences, University of Seville, Seville, Spain. E-mail: [email protected]