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	<title>augmented reality language learning &#8211; Science</title>
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	<title>augmented reality language learning &#8211; Science</title>
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		<title>Why veteran language teachers beat the digital native myth on augmented reality</title>
		<link>https://scienmag.com/why-veteran-language-teachers-beat-the-digital-native-myth-on-augmented-reality/</link>
		
		<dc:creator><![CDATA[Courtney Benton]]></dc:creator>
		<pubDate>Sat, 17 Oct 2026 16:45:31 +0000</pubDate>
				<category><![CDATA[Social Science]]></category>
		<category><![CDATA[AR for vocabulary acquisition]]></category>
		<category><![CDATA[AR implementation in K-12 schools]]></category>
		<category><![CDATA[AR versus virtual reality in education]]></category>
		<category><![CDATA[augmented]]></category>
		<category><![CDATA[augmented reality]]></category>
		<category><![CDATA[augmented reality language learning]]></category>
		<category><![CDATA[authentic contextualized language learning]]></category>
		<category><![CDATA[barriers]]></category>
		<category><![CDATA[challenges of integrating augmented reality]]></category>
		<category><![CDATA[digital native myth in language teaching]]></category>
		<category><![CDATA[digital overlays in classroom]]></category>
		<category><![CDATA[educational technology]]></category>
		<category><![CDATA[EFL teachers]]></category>
		<category><![CDATA[Examining]]></category>
		<category><![CDATA[immersive language education]]></category>
		<category><![CDATA[language education]]></category>
		<category><![CDATA[mixed-methods research]]></category>
		<category><![CDATA[mobile-based AR language applications]]></category>
		<category><![CDATA[multimodal feedback in language learning]]></category>
		<category><![CDATA[shaping]]></category>
		<category><![CDATA[teacher attitudes toward AR]]></category>
		<category><![CDATA[teacher professional development]]></category>
		<category><![CDATA[technology adoption]]></category>
		<category><![CDATA[TPACK]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=299844</guid>

					<description><![CDATA[A mixed-methods study of 266 Greek English as a Foreign Language teachers finds that infrastructure barriers dominate augmented reality adoption, that AR knowledge reduces attitudinal but not material barriers, and that experienced teachers report the strongest technology self-efficacy, challenging the digital immigrant myth.]]></description>
										<content:encoded><![CDATA[<p>Augmented reality promises to transform the way students learn English, overlaying digital labels, images and three-dimensional objects onto the visible classroom through a tablet or smartphone. Unlike virtual reality, which replaces the user&#8217;s surroundings with a fully simulated environment via a headset, AR leaves the real classroom in view and enriches it. For language education, the distinction matters enormously: vocabulary acquisition is most effective when target items are encountered within authentic, contextualised settings rather than in isolation, and AR delivers exactly that kind of immediate multimodal feedback and interactive practice. Meta-analytic evidence documents measurable gains in student achievement, and a systematic review of studies between 2016 and 2023 found that 70 percent of AR language-learning research focused on lexical development, with a clear trend toward mobile-based, marker-triggered applications.</p>
<p>Yet a striking disconnect persists between this pedagogical promise and actual classroom implementation. In a recent international survey, 93 percent of teachers expressed the belief that immersive technologies would be helpful for instruction, but only just over 40 percent of K-12 schools had actually incorporated AR or VR technologies at some point in their practices. Fewer than 20 percent of language teachers feel confident integrating emerging technologies despite positive attitudes toward innovation in principle. Researchers have termed this gap the second-level digital divide, referring to teachers&#8217; capacity to integrate technology meaningfully into instruction beyond mere access to it. Understanding which barriers prove most binding, however, has remained underexplored, and the answer carries direct implications for where limited resources should be directed.</p>
<p>A new mixed-methods study published in SN Social Sciences by Eirini Maria Paraskevioti, Athanasios Christopoulos, Mikko-Jussi Laakso of the University of Turku and Stylianos Mystakidis of the University of Patras examined the barrier hierarchy among Greek English as a Foreign Language teachers and the relationship between AR knowledge and barrier perceptions. Following Ertmer&#8217;s classic barrier model, the team distinguished first-order, external and systemic barriers, such as infrastructure, training, time and support, from second-order, internal and attitudinal barriers, such as perceived relevance and self-efficacy concerns. The two differ fundamentally in tractability: infrastructure limitations require systemic investment, whereas attitudinal concerns may respond to awareness-raising and professional development.</p>
<p>The study surveyed 266 Greek EFL teachers, 208 female and 58 male, recruited across twelve regions with the highest participation from Attica and Central Macedonia. Participants spanned four institutional types, including public schools at 68.8 percent, private language institutes, private schools and experimental schools, and five teaching levels from primary through vocational education. Approximately one-third reported having used AR in some capacity, while the majority had no prior AR experience. Subsets of the sample participated in five focus groups totalling 35 teachers, organised by institutional context, and 18 purposively sampled individual interviews spanning the range of experience levels and school types. All qualitative sessions were conducted in Greek, audio-recorded and transcribed verbatim.</p>
<p>The quantitative results revealed a decisive barrier hierarchy. Infrastructure barriers, with a mean of 3.95 on a five-point scale, were rated significantly higher than all other barrier types, exceeding the scale midpoint and indicating that teachers endorsed them as genuine obstacles. Time barriers at 3.58 and training barriers at 3.50 occupied intermediate positions, while attitudinal barriers, especially perceived relevance at 2.53, fell below the midpoint, with most teachers not perceiving AR as irrelevant to language instruction. The contrast between infrastructure and perceived relevance returned a large effect size of 2.04. The repeated-measures ANOVA revealed a significant main effect across the six barrier domains with a partial eta squared of 0.40, and exploratory analyses showed that barrier profiles varied by teaching level, with secondary teachers reporting higher training barriers than primary teachers and multi-level teachers reporting substantially lower support barriers than all single-level groups.</p>
<p>Perhaps the most technically consequential finding concerns knowledge-barrier selectivity. The researchers administered a custom five-item factual AR quiz and correlated scores with barrier perceptions. AR knowledge was significantly and negatively correlated with perceived relevance at r = -0.45 and with training barriers at r = -0.38, both medium magnitudes. In contrast, the correlation between AR knowledge and infrastructure barriers was negligible and non-significant at r = -0.09. Steiger&#8217;s Z-test confirmed that the knowledge-relevance correlation was significantly stronger than the knowledge-infrastructure correlation. In other words, teachers with greater AR knowledge perceived the technology as more pedagogically relevant and felt less need for formal training, but technical knowledge could not create tablets or improve WiFi reliability. Awareness campaigns can reasonably be expected to reduce scepticism about pedagogical fit, yet such interventions will not address, and may even exacerbate frustration with, infrastructure limitations.</p>
<p>The study also measured teacher knowledge through the Technological Pedagogical Content Knowledge framework, which conceptualises effective technology integration as the intersection of technological, pedagogical and content knowledge. The results exposed a dramatic asymmetry. Pedagogical Knowledge averaged 6.14 on a seven-point scale while Technological Knowledge averaged 4.16, and Content Knowledge at 6.00 similarly exceeded Technological Content Knowledge at 4.14. All paired comparisons between technology-related and pedagogical domains returned effect sizes exceeding 2.0, indicating that Greek EFL teachers possess strong pedagogical and content expertise but cluster around the scale midpoint on technological competencies. The asymmetry likely reflects teacher education programmes that historically emphasised pedagogical and disciplinary preparation while treating technology as an optional supplementary skill.</p>
<p>Two further findings challenged popular assumptions. First, experienced teachers with 15 or more years in the classroom reported the fewest self-efficacy concerns, averaging 2.82, compared with mid-career teachers at 3.51, a significant contrast with an effect size of 1.22. This contradicts the digital immigrant narrative, which suggests veteran educators resist technological disruption, and instead supports the professional capital prediction: accumulated pedagogical confidence transfers to technology-related self-assessments. Second, when teachers rated conditions for adoption readiness, evidence of learning gains received the highest endorsement at 5.77 on a seven-point scale, significantly outranking free resources at 5.52 and intensive 40-hour training at 4.88. Teachers prioritised pedagogical justification over resource provision, consistent with Diffusion of Innovations theory in which perceived relative advantage is the strongest adoption driver. Notably, teachers viewed extensive training requirements as barriers rather than enablers.</p>
<p>A third counter-intuitive result concerned the mediation analysis. Public school teachers reported dramatically lower device availability, WiFi reliability and technical support than private school and language institute teachers, with public schools averaging 1.88 on a five-point contextual scale compared with 2.94 for private schools. Yet infrastructure barrier ratings were virtually identical across institutional types, and the indirect effect through contextual factors was not significant. Teachers appear to evaluate infrastructure adequacy relative to perceived implementation requirements rather than in absolute terms. Public school teachers lacked devices entirely, while private school teachers noted that sharing arrangements undermined the individual immersive experiences AR is designed to provide. Qualitative accounts clarified this pattern: an urban public-school teacher described one computer lab with 15 outdated desktops, calling AR science fiction for their school, while a language institute teacher explained that not having enough tablets for every student defeats the purpose of individual experiences.</p>
<p>The qualitative data broadly converged with the barrier hierarchy but exposed genuine heterogeneity that the quantitative aggregate obscured. Across the 18 interviews, stances were mixed, with seven sceptical, six positive and five cautiously open. Teachers expressed initiative fatigue toward top-down technology mandates lacking sustained support, and questioned the alignment between immersive tools and paper-based examinations. Taken together, the findings reveal a structure with its own internal logic: the binding constraint lies in infrastructure, awareness can move attitudes but not material conditions, and even willing, pedagogically expert teachers may lack the technology-specific competence that integration requires. Because awareness-raising, resource provision and TPACK-oriented training operate on different, non-substitutable obstacles, progress on any one lever is bounded by the others. In a first-order-dominant setting like the Greek EFL context, an awareness campaign without devices, or hardware without pedagogical preparation, is unlikely to shift adoption far. The authors conclude that coordinated investment across infrastructure, knowledge and pedagogy offers the more plausible path, positioning experienced teachers as potential early adopters and mentors rather than obstacles to innovation.</p>
<p><strong>Subject of Research:</strong> Educational technology and teacher adoption research</p>
<p><strong>Article Title:</strong> Examining the barriers shaping augmented reality adoption among English as a Foreign Language teachers: a mixed-methods study</p>
<p><strong>Article References:</strong> Paraskevioti, E. M., Christopoulos, A., Mystakidis, S., &amp; Laakso, M.-J. (2026). Examining the barriers shaping augmented reality adoption among English as a Foreign Language teachers: a mixed-methods study. <em>SN Social Sciences, 6</em>(9), Article 355. <a href="https://doi.org/10.1007/s43545-026-01634-y" rel="noopener noreferrer">https://doi.org/10.1007/s43545-026-01634-y</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s43545-026-01634-y" rel="noopener noreferrer">10.1007/s43545-026-01634-y</a></p>
<p><strong>Keywords:</strong> augmented reality, EFL teachers, technology adoption, TPACK, mixed-methods research, educational technology, language education, teacher professional development, Examining, barriers, shaping, augmented</p>
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