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	dc:title "HTML Summary of #90781 \n\nA Cognitive Measurement Model for Pre-Service Teachers’ Higher Order of Thinking Skills in Digital Literacy.\n\n";
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	bibo:abstract "This study aims to; (1) Develop a HOTS digital literacy skills measurement \r\nmodel for prospective teachers at KazNPU, hereinafter referred to as the DLMCI; \r\n(2) Evaluate the quality of the digital literacy skills measurement instrument; and \r\n(3) Provide empirical evidence regarding the feasibility of measuring pre-service \r\nteachers' digital literacy skills, and (4) Analyse the pre-service teachers’ digital \r\nliteracy HOTS profiles.\r\nThis study employed a quantitative research method in the context of R&D. \r\nThe subjects were 151 prospective teachers (n = 151) at KazNPU. The data \r\ncollection instrument consisted of a two-part test: a Tier-Two Item Test and a \r\nSituational Judgment (SJ) in the form of an anti-cyberbullying video. Data analysis \r\nwas conducted using RStudio version R 4.4.3 to examine the parameters of the \r\ndeveloped items.\r\nThe results showed that (1) the Cognitive Measurement Model, the DLMCI, \r\nwas successfully developed to assess pre-service teachers’ HOTS digital literacy. \r\nThe (2) DLMCI has very high content validity, with an Aiken V value of 0.94 and \r\na composite reliability (McDonald's Omega) of α = 0.803. In classical test theory \r\n(CTT), Two-tier choice items showed an average a = 0.510, indicating moderate \r\ndiscrimination, and an average difficulty level of b = 0.643. In IRT, the instrument \r\nis multidimensional: MDIFF ranges from -1.27 to +1.29, and MDISC between 0.78 \r\nand 3.92. The residual correlation r_res. ≈0 supports local independence; the odd￾even theta coefficient (r = 0.925) confirms parameter invariance. Most of the \r\ndistractors in the items functioned well, indicated by a selection rate above 5%, \r\nexcept for one case with a percentage of 1.3%. The measurement model that best \r\nfits the data is the Generalised Partial Credit Model (GPCM). In a logistic scale [-3 \r\nto +3], Theta estimates for measuring higher-order thinking skills (HOTS) of digital \r\nliteracy of prospective teachers at KazNPU are in the range of -3.01 ≤ θ ≤ +2.4. The \r\n(3) DMCI demonstrated feasibility when implemented in a real-world setting \r\nwithout hindrances; it is both efficient and environmentally friendly. The (4) HOTS \r\nprofile of digital literacy among prospective teachers at KazNPU is divided into \r\nfour categories: Low (-1.93 ≤ θ < -0.85), Medium (-0.85 ≤ θ < 0.23), High (0.23 ≤ \r\nθ < 1.31), and Very High (1.31 ≤ θ ≤ 2.4). The minimum and maximum Theta values \r\nare -3.00 and +2.4, respectively, with an average Theta of -0.3, which falls into the \r\n“Low” category. The Low, Medium, High, and Very High categories are represented \r\nby 30 (19.86%), 67 (44.37%), 40 (26.50%), and 14 (9.27%) pre-service teachers, \r\nrespectively. Therefore, this study recommends that the Ministry of Education in \r\nKazakhstan utilise the DLMCI for data-driven decision-making."^^xsd:string;
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	dct:date "2026-01-07";
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