16. ICT in Education and Training
Paper
ICT in Learning: Can It Be Used as Differentiation Tool?
Oleg Tyo, Shyryn Mulkibayeva, Kuralay Akhmadiyeva
International School of Astana, Kazakhstan
Presenting Author: Tyo, Oleg;
Mulkibayeva, Shyryn
Whether with concern or excitement, we, as educators, venture into the current millennium guided by a conceptual paradigm shift of changing student needs. Generation change and subsequent renewing of secondary education standards present the need for schools to expand their practices of differentiation and individualization of educational process. Traditional methodologies and traditional classroom settings are transforming, expanding beyond the four-walled cubes into the "virtual" amorphous cyberspace classrooms and reality sites outside of the typical ivy-covered towers of higher education. Because of technology-driven telecommunications and growing student diversity, we have a responsibility to be more innovative in our pedagogical approaches. Designing creative virtual classrooms developed within a theoretical framework while considering differentiation and individualization needs is the only answer. Research has attributed difficulties in doing so largely to problems and difficulties of differential approach in teaching, and has recently pinpointed the essential role of using of modern ICT tools in implementing that approach. An ethos of knowledge transfer, implementation and learning are needed for educational success.
Interactive electronic platforms are new and significant phenomena and are newly internationalizing. This study will employ longitudinal educational research to identify if and how these platforms reconcile with the problem of differentiation in education, and to advance understanding concerning the link between ICT and international education development.
Methodology, Methods, Research Instruments or Sources UsedThe research covers the period of one academic year, starting from August 2022 and ending up in May 2023. The object of study was the Republic of Kazakhstan’s education system and, in particular, state and private schools of such cities as Astana and Karaganda. The subject of study was to estimate the value of use of the ICT tools as innovative and individualizing teaching approach in Kazakhstan’s and Central Asia’s educational and cultural context. Additional subject was to study a foreign (predominantly Western European and Eastern Asian countries’) experience in the particular sphere and to analyze values and limitations of hypothetical knowledge transfer.
To start the research, relevance of the topic should have been affirmed. To indicate this, the survey was conducted on the initial stages of the study. The study itself has being started from August 2022, in accordance with the survey data received.
Variety of methods had been used during the research, including:
- Comparative analysis made to figure out the differences of education cultures of Central Asia and other regions, such as Eastern Asia or Western Europe;
- Secondary Data Analysis used to consider methods and results of previous studies on the particular topic, and to evaluate successes and flaws of similar methods when used in other countries;
- Experiments of implementing ICT tools as instruments for differential learning;
- Observation of the research progress by keeping records in a reflective journal and conducting one-on-one interviews with the students participating;
- Open lessons for receiving a feedback from the educators of various profiles;
- Focus Groups used as a method of organizing discussions and collecting opinions about the products (tools), and receiving the teachers' and students' feedback on research.
The final part of the research contained a qualitative observation of the particular results, such as quality of students’ knowledge dynamics, individual progress of specified groups of students, students’ and teachers’ opinion polls on ICT tools use, teachers’ progress in implementing ICT tools and diversifying education methods, limitations of the research process.
Conclusions, Expected Outcomes or FindingsThe first expected outcome is to find out whether the use of ICT can be justified as part of differential learning approach, and to consider existing and hypothetical limitations of implementing it in secondary education system. The second expected outcome is to estimate the possibility of knowledge transfer of the particular topic from other countries and regions, such as Eastern Asia and Western Europe. Conclusion on the latter aspect should include consideration of difference in education cultures and mentalities of Kazakhstan and indicated regions.The third expected outcome is to evaluate the possibility of integrating the particular system of ICT-based differential education in the context of region's educational culture.
References1. Aceto, S., Borotis, S., Devine, J., & Fischer, T. (2013). Mapping and Analysing Prospective Technologies for Learning: Results from a consultation with European stakeholders and roadmaps for policy action. JRC Scientific and Policy Report JRC81935. Luxemburg: Publications Office of the European Union. Retrieved 11 August 2013, from http://ipts.jrc.ec.europa.eu/publications/pub.cfm?id=6360
2. Bocconi, S., Kampylis, P., & Punie, Y. (2012). Innovating Learning: Key Elements for Developing Creative Classrooms in Europe. EUR 25446 EN. Luxembourg: Publications Office of the European Union. Retrieved 9 April 2013, from http://ipts.jrc.ec.europa.eu/publications/pub.cfm?id=5181
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16. ICT in Education and Training
Paper
Inequalities in Participation in Online Courses Across Europe: The Heuristic Potential of Bourdieu’s Cultural Capital Theory
Svetlomir Zdravkov, Petya Ilieva-Trichkova
Bulgarian Academy of Sciences, Bulgaria
Presenting Author: Zdravkov, Svetlomir
Online courses are the latest technologically mediated form of distance asynchronous learning and today they are among the most popular non-formal education practices. The online courses use the internet (and all related technologies) to provide educational recourses to a wide audience whenever and however is convenient for them, breaking all institutional barriers to knowledge and information. Due to their user-friendly interface and user-oriented content, it is theorized that the online courses would play a key tool for lowering the educational inequalities and increasing inclusivity (Germain-Rutherford and Kerr, 2008). Judging from studies on inequalities in MOOCs, however, online courses appear to be less inclusive as expected.
Unfortunately, the literature on inequalities in participation and inclusivity in the online courses, outside of the MOOCs research, is poorly developed, mostly due to the lack of appropriate data.
Our study seeks to contribute to the literature on inequalities in participation in online courses in three main ways. First, we use unexplored data from the EU Information and Communications Technologies (ICT) usage by Households and Individuals for 2021. Second, our analysis provides a cross-national comparative perspective, using two-level regression analysis taking into account the level of the country's innovation. Third, we theorized the inequalities and the role of technologies in participation inequalities from the perspective of Bourdieu’s theory of cultural capital (Beckman et al., 2018).
Our analytical framework is based on Bourdieu's cultural capital theory but adapted to the online courses and digital context. We interpret the three states of cultural capital - embodied , objectified, and institutionalized statе (Bourdieu, 1986) - using them to create statistically analyzed variables.
We start with objectified cultural capital, arguing that technologies like laptops, internet access and smartphones have a major role in the inequalities in the online courses. Cultural capitals are noticeable through the device used by the students, which is recognised by pre-established algorithms, acting on behalf of their owners. These devices are not equally distributed among the learners, giving them unequal access to the educational content. Laptops and PCs are more adaptable to users’ educational needs but require more cultural capital in contrast to mobile devices, which are hard to adapt due to their original purposes but require less cultural capital.
Embodied cultural capitals are needed not only to use a device but also to navigate the web and to be able to find and recognise exactly what you need (van Dijk and van Deursen, 2014). Digital skills, linked to information seeking, are also distributed unevenly among the different social classes and especially with regard to the individual level of formal education, as studies of the social divide have shown (Hargittai, 2002).
The cultural capitals have ‘efficacy’ in relation to a specific field (Bourideu, 1984). How valuable the skills and knowledge learned in online courses are depends on the everyday struggles over price-forming locked around the strategies in the different fields. Comparing manual with non-manual occupation we study the effects of field efficacy. We also compute the differences between the countries, which Bourdieu considered as meta-fields (Bourdieu and Wacquant, 1992), taking their level of innovation.
Against this background research questions (RQs):
1) Which state (embodied, objectified, institutionalised) of cultural capital is a better predictor for participation in online courses?
2) Does the ‘efficacy’ of cultural capital on participation in online courses differ between specific fields?
3) Are there country differences in the influences of cultural capital in online courses?
4) Can a lack of cultural capital be mitigated by the country’s level of innovation in regard to participation in online courses?
Methodology, Methods, Research Instruments or Sources UsedWe use data from the EU Information and Communications Technologies (ICT) Usage by Households and Individuals for 2021. This is an annual survey which collects harmonised and comparable information on the use of ICT in households and by individuals. It covers a wide range of characteristics related to access to and use of ICTs, the use of the internet and other electronic networks for different purposes, ICT competences and skills, etc., as well as for various sociodemographic characteristics such as gender, age, level of education, occupation and main status on the labour market.
We limited our analysis to people aged 25–64. Our methodological consideration is to cover most of the economically active individuals, having either manual or non-manual jobs, which we use as a proxy to an economic field. After doing some list-wise deletion of the cases with missing values on one or more of the individual variables, we ended up with an analytical sample consisting of 95,345 adults nested in 28 countries.
The dependent variable is a dummy variable which distinguishes whether a person had completed an online course in the last 3 months or not. For the embodied state of cultural capital, we have used the level of overall digital skills. For institutionalised cultural capital, we have used the level of formal education. As a proxy for objectified cultural capital, we have combined the usage of laptops and desktop computers to connect to the internet compared to smartphones, tablets and other devices. For the respective social field, we have determined whether the individual is working a manual job or one in the service sector. One independent variable has been included at country (as a meta-field) level: the Innovation Index. We have controlled the results for gender and age
Given that our dependent variable is a dichotomous one, we have employed logistic regressions (Long and Freese, 2006), as well as a series of logit models with random effects. These models were considered appropriate because our dependent variable is binary and individuals (level 1) may be nested within countries (level 2). This multilevel modelling technique (Rabe-Hesketh and Skrondal, 2012) allows us to explore not only the associations between variables at individual and macro-level, but also whether there are cross-level interactions between variables at different levels.
Conclusions, Expected Outcomes or FindingsThis study has revealed that the lack of cultural capital in all three studied dimensions constrains participation in online courses, even after controlling for gender and economic field. The effects of the capitals are measured by classical indicators such as formal level of education but they are also more closely linked to sub-fields of online education such as digital skills and access to devices like laptops. However, it seems that institutionalised cultural capital measured by level of education is the strongest predictor.
The results indicate that being a manual worker is associated with lower odds of participating in online courses in comparison to a non-manual worker, given the other covariates. From the perspective of our framework, since manual work is less educationally intensive and values different skills (Lehmann and Taylor, 2015), the knowledge gained through courses is less valued, discouraging manual workers to participate.
Our analysis has shown that there are considerable country differences in participation in online courses. These findings suggest that cultural capital interacts in a different way with the national meta-field and could follow different patterns of inequalities. These implications are aligned with other studies suggesting that social class and status have different effects on online activities in different countries (Lindblom and Räsänen, 2017).
Our results suggest that the lack of cultural capital in participation in online courses could be mitigated by the country’s level of innovation. Yet, we have only found evidence of this for two of the three studied dimensions of cultural capital: level of education and having a device, not digital skills. As the social classes are stratified in every country, so are nation-states in the global field (Buchholz, 2016), and adult and higher education is playing an especially crucial role as a structuring institution (Marginson, 2008).
ReferencesBeckman К, Apps T, Bennett S and Lockyer L (2018) Conceptualizing technology practice in education using Bourdieu's sociology. Learning, Media and Technology 43(2): 197–210.
Bourdieu P (1986) The forms of capital. In: Richardson J (ed), Handbook of Theory and Research for the Sociology of Education. Westport, CT: Greenwood, 241–258.
Bourdieu P (1984) Distinction: A Social Critique of the Judgement of Taste. Harvard: Harvard University Press.
Bourdieu P and Wacquant LJ D (1992) An Invitation to Reflexive Sociology. Chicago: University of Chicago Press; Cambridge: Polity Press.
Buchholz L (2016) What is a global field? Theorizing fields beyond the nation-state. The Sociological Review Monographs 64(2): 31–60.
van Dijk, J. A. and van Deursen, A. J., 2014. Digital Skills Unlocking the Information Society. New York: Palgrave Macmillan.
van Deursen A J and van Dijk J A (2019) The first-level digital divide shifts from inequalities in physical access to inequalities in material access. New Media & Society, 21(2), 354–375.
Germain-Rutherford A and Kerr B (2008) An inclusive approach to online learning environments:Models and resources. Turkish Online Journal of Distance Education 9(2): 64–85.
Hargittai E (2002) Second-level digital divide: Differences in people’s online skills. First Monday 7 (4). https://doi.org/10.5210/fm.v7i4.942.
Long J S and Freese J (2006) Regression Models for Categorical Dependent Variables Using Stata. College Station, Texas: Stata Press.
Marginson S (2008) Global field and global imagining: Bourdieu and worldwide higher education. British Journal of Sociology of Education 29(3): 303–315.
Mittal O, Nilsen T and Björnsson J K (2020) Measuring equity across the Nordic education systems—Conceptual and methodological choices as implications for educational policies. In: Frønes F S, Pettersen A, Radišić J and Buchholtz N (eds), Equity, Equality and Diversity in the Nordic Model of Education. Cham: Springer, 43–71.
Lehmann W and Taylor A (2015) On the role of habitus and field in apprenticeships. Work, Employment and Society 29(4): 607–623.
Lindblom T and Räsänen P (2017) Between class and status? Examining the digital divide in Finland, the United Kingdom, and Greece. The Information Society 33(3): 147–158.
Rabe-Hesketh S and Skrondal A (2012) Multilevel and Longitudinal Modeling using Stata (3rd Edition). College Station, TX: Stata Press.
16. ICT in Education and Training
Paper
Same Digital Infrastructures for All? How Teachers in China Perceive the (In)equality in the Digitalization of Schooling
Kaiyi Li
Leibniz Institute for Educational Media, Germany
Presenting Author: Li, Kaiyi
The discourse that digitalization could fix educational problems, notably boosting educational opportunity equality and inclusion underpins many national and international policies and drives many initatives to integrating digitalization into schooling. Numerous research have been conducted on this topic, including policy analysis, case studies, and the factors that determine the consequences of employing digital tools, particularly on the Covid-19 pandemic, in addition to the political concerns behind incorporating digital technologies into education. However, there have not been many in-depth qualitative research on how various individuals view the (in)equality brought about by educational digitalization based on their daily usage experiences. In this study, we attempt to bridge the gap by using China as an example. In recent years, with the central government-oriented “new basic infrastructure construction”, and the "internet+" program, providing the same digital infrastructures for all within a province has been viewed as a fundamental responsibility of local government and articulated as the most effective tool for addressing long-standing concerns about educational inequality in China. China is stimultaneously presenting itself and being acknowledged by international organizations such as UNESCO as a country that excels in utilizing digitalization to ensure educational inclusion and equal access to high quality education for disadvantaged individuals.
This paper investigates, on the one hand, the visible and invisible digital infrastructure differences between rural and urban schools within a province and between provinces, and, on the other, how teachers, the individuals who use digital technologies for teaching on a daily basis, perceive the (in)equality against the backdrop of educational digitalization.
We ask following three questions:
- What are the differences between each school's digital infrastructures and how did they arise?
- Do teachers with access to the same digital infrastructures have access to the same teaching resources?
- How does digitalization affect educators' perceptions of educational equality, and what does educational equality mean for teachers in the context of digitalization?
The concept equality contains different levels of meaning. This study begins by defining equality as varying access to sophisticated technology, in light of the Chinese government's emphasis in policy papers and government-oriented practice, which are asserted, on providing everyone with the same infrastructures and high-quality educational materials. This article seeks to discover, by continual study of the data, what additional layers of (in)equality are generated by teachers.
Methodology, Methods, Research Instruments or Sources UsedMethodologically, we conduct in-depth semi-interviews with teachers from seven primary school from different regions of China. We selected three economic significantly different provinces: Zhejiang Province in Eastern China and Anhui Province in Central China, and in Yunnan Province in Southwestern China. In each of the three provinces, public rural and urban schools from economically distinct cities were chosen. In each school, we conduct interviews with teachers from various subject areas (Chinese, mathematics, Music/Arts, English, and technology) and generations (born in 1960s, 1970s, 1980s, 1990s). We conduct 105 interviews in total. Each interview lasts between 30 and 70 minutes. All collected data are analyzed by the methodology of grounded theory with the support of the software MAXQDA. We firstly categorize the data collceted according to the above-mentioned research questions and then derive concepts and ideas from the analysis of this data.
Detali of sources:
Zhejiang Province: An educational digitalization pilot school and a rural complete school in a village from a city economically ranks above the average of the province. An urban and rural school from a city economically most disadvantage city.
Anhui Province: An educational digitalization pilot school from an economically leading city. An educational digitalization pilot school and a rural school in economic undisvantage village from previously poverty county.
Conclusions, Expected Outcomes or FindingsThis paper presents three interesting findings. First, based on school observations and descriptions provided by teachers, we find the accessible digital infrastructures for daily teaching are quite similar in each province. But there are huge gaps in digital tools for AI-oriented extra curriculum, such as Irobort. However, the majority of teachers in rural and urban schools agreed that digital equipment is nearly identical.
Second, "Seewo whiteboard" and PowerPoint are the most frequently mentioned digital tools by teachers, who claim that digital technologies are only supplementary tools. While teachers in urban schools are more likely to remark "Seewo whitebroad," rural and urban teachers utilize the free version. In addition, we discover that teachers in China rarely purchase digital resources, and that the sources through which they obtain access to digital resources are typically the same, whether subjects BBS or government-supported platforms. Teachers have varying opinions regarding the functionality and quality of government-supported platforms, but most of them tend to believe that digitalization provides them with equal access to educational resources.
Thirdly,most rural and urban teachers agree that with a smart phone, students have access to the same educational resources. However, they believe there are huge gaps between rural and urban students on digital literacy. While not specifically employing the term "cultural capital," the majority of teachers emphasize cultural backgrounds of parents in promoting children's use of digital learning tools. It implies that inequality, rather than resulting from school education, is determined by the type of family in which a child is born.
ReferencesLiu, Haimeng; Fang, Chuanglin; Sun, Siao (2017): Digital inequality in provincial China. In Environ Plan A 49 (10), pp. 2179–2182. DOI: 10.1177/0308518X17711946.
Kuhn, A., Schwabe, A., Boomgarden, H., Brandl, L., Stocker, G., Lauer, G., Brendel-Kepser, I., & Krause-Wolters, M. (2022). Who gets lost? How digital academic reading impacts equal opportunity in higher education. New Media & Society, 0(0). https://doi.org/10.1177/14614448211072306
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Abbey, Cody; Ma, Yue; Li, Guirong; Boswell, Matthew (2019.10.): EdTech for Equity in China: Can Technology Imrpove Teaching for Millions of Rural Students. Standford Freeman Spogli Institute for International Studies. Available online at https://fsi.stanford.edu/publication/edtech-equity-china-can-technology-improve-teaching-millions-rural-students.
Wilkin, S., Davies, H., & Eynon, R. (2017). Addressing digital inequalities amongst young people: conflicting
discourses and complex outcomes. Oxford Review of Education, 43(3), 332-347.
Jacob, Brian; Berger, Dan; Hart, Cassandra; Loeb, Susanna (2016): Can Technology Help Promote Equality of Educational Opportunities? In rsf 2 (5), pp. 242–271.
Lembani, Reuben; Gunter, Ashley; Breines, Markus; Dalu, Mwazvita Tapiwa Beatrice (2020): The same course, different access: the digital divide between urban and rural distance education students in South Africa. In Journal of Geography in Higher Education 44 (1), pp. 70–84. DOI: 10.1080/03098265.2019.1694876.
Lynch, Kathleen; Baker, John (2005): Equality in education. In Theory and Research in Education 3 (2), pp. 131–164. DOI: 10.1177/1477878505053298.
Di Mo; Swinnen, Johan; Zhang, Linxiu; Yi, Hongmei; Qu, Qinghe; Boswell, Matthew; Rozelle, Scott (2013): Can One-to-One Computing Narrow the Digital Divide and the Educational Gap in China? The Case of Beijing Migrant Schools. In World Development 46, pp. 14–29. DOI: 10.1016/j.worlddev.2012.12.019.
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