Data for “Reading as Resemiotization: Pre-service English Teachers’ Evolving Conceptions of Literacy in a Virtual Reality-Mediated Multiliteracies Practice”
Description
Research context and guiding proposition. This dataset documents an embedded convergent mixed-methods case study of how the conceptions of literacy held by 53 first-year pre-service English language teachers evolved over a semester-long multiliteracies intervention, the “Literography Project.” In the project, each participant read a work of literature set for their course, transposed a chosen scene into an original photographic narrative, and curated the resulting composition in a low-immersion, browser-based virtual reality exhibition (Artsteps). Data were collected at a single state university in Türkiye from participants who held a B2–C1 level of English proficiency. Because the design is an interpretive case study, the research was guided by research questions rather than by a hypothetico-deductive hypothesis. The guiding proposition that motivated data collection was that positioning pre-service teachers as designers of multimodal texts—rather than as receivers of print—would shift their conception of literacy away from an autonomous, language-centred decoding skill and toward a multimodal, design-oriented, and socially situated practice. A more specific expectation, which the data allow a reuser to test rather than merely accept, is that the driver of any such conceptual shift is the compositional constraint of working in a non-linguistic mode, not the technological richness or degree of immersion of the delivery medium. The two research questions were: ● RQ1. How do pre-service English teachers’ conceptions of literacy evolve through participation in a virtual reality-mediated multiliteracies practice? ● RQ2. What affordances and challenges do the participants perceive in that practice? What the data contain and how they were gathered. The dataset assembles the anonymized primary and derived data from four instruments, together with the full analytic apparatus used to code and interpret them. (1) A rating-scale survey with two open-ended definitional items in which participants stated, in their own words, what “literacy” and “being literate” mean; one survey response is missing, giving 52 complete returns of a possible 53. (2) Individually authored reflective essays on the experience of designing and exhibiting the photo-narrative. (3) Focus-group interviews conducted after the exhibition. (4) The participants’ own digital multimodal compositions—the photo-narratives and their accompanying written rationales—as curated in the virtual exhibition.
Files
Steps to reproduce
1. Recruit a cohort of first-year pre-service English teachers (here, n = 53; B2–C1 proficiency) and obtain informed consent and ethics clearance (this study: institutional ethics approval, Form 2025/274, dated 08 April 2025). 2. Deliver the Literography Project: each participant reads a set literary text, selects a scene, and transposes it into an original photographic narrative supported by a written rationale; a field professional delivers supporting photography workshops. 3. Curate the compositions in a low-immersion, browser-based virtual reality exhibition (Artsteps) and hold a viewing session. 4. Collect data through (a) a rating-scale survey containing two open-ended definitional items on literacy; (b) individual reflective essays; (c) post-exhibition focus-group interviews; and (d) the compositions and rationales themselves. 5. Define the coding unit as one participant’s combined response to the two definitional items. Code every unit independently with two raters against the four-construct multiliteracies scheme and its descriptive subcodes (provided in the coding-frame file). 6. Compute Cohen’s κ per construct and pooled, with 95% confidence intervals and percentage agreement, on all paired decisions before consensus; benchmark against Landis and Koch (1977). 7. Resolve disagreements by consensus discussion arbitrated against the descriptive subcode inventory; record the direction of each resolution. Derive affordance/challenge themes from the essays and focus groups. Score VR-related adjectives with the VADER sentiment lexicon.
Institutions
- Istanbul University-CerrahpaşaIstanbul, Istanbul