@phdthesis{UNY90781,
           title = {A Cognitive Measurement Model for Pre-Service Teachers? Higher Order of Thinking Skills in Digital Literacy.},
          author = {Begimbetova Guldana Atymtaevna and Heri Retnawati},
          school = {Sekolah Pascasarjana},
           month = {January},
            year = {2026},
             url = {http://eprints.uny.ac.id/90781/},
        abstract = {This study aims to; (1) Develop a HOTS digital literacy skills measurement 
model for prospective teachers at KazNPU, hereinafter referred to as the DLMCI; 
(2) Evaluate the quality of the digital literacy skills measurement instrument; and 
(3) Provide empirical evidence regarding the feasibility of measuring pre-service 
teachers' digital literacy skills, and (4) Analyse the pre-service teachers? digital 
literacy HOTS profiles.
This study employed a quantitative research method in the context of R\&D. 
The subjects were 151 prospective teachers (n = 151) at KazNPU. The data 
collection instrument consisted of a two-part test: a Tier-Two Item Test and a 
Situational Judgment (SJ) in the form of an anti-cyberbullying video. Data analysis 
was conducted using RStudio version R 4.4.3 to examine the parameters of the 
developed items.
The results showed that (1) the Cognitive Measurement Model, the DLMCI, 
was successfully developed to assess pre-service teachers? HOTS digital literacy. 
The (2) DLMCI has very high content validity, with an Aiken V value of 0.94 and 
a composite reliability (McDonald's Omega) of {\ensuremath{\alpha}} = 0.803. In classical test theory 
(CTT), Two-tier choice items showed an average a = 0.510, indicating moderate 
discrimination, and an average difficulty level of b = 0.643. In IRT, the instrument 
is multidimensional: MDIFF ranges from -1.27 to +1.29, and MDISC between 0.78 
and 3.92. The residual correlation r\_res. {$\approx$}0 supports local independence; the odd?even theta coefficient (r = 0.925) confirms parameter invariance. Most of the 
distractors in the items functioned well, indicated by a selection rate above 5\%, 
except for one case with a percentage of 1.3\%. The measurement model that best 
fits the data is the Generalised Partial Credit Model (GPCM). In a logistic scale [-3 
to +3], Theta estimates for measuring higher-order thinking skills (HOTS) of digital 
literacy of prospective teachers at KazNPU are in the range of -3.01 {$\leq$} {\ensuremath{\theta}} {$\leq$} +2.4. The 
(3) DMCI demonstrated feasibility when implemented in a real-world setting 
without hindrances; it is both efficient and environmentally friendly. The (4) HOTS 
profile of digital literacy among prospective teachers at KazNPU is divided into 
four categories: Low (-1.93 {$\leq$} {\ensuremath{\theta}} {\ensuremath{<}} -0.85), Medium (-0.85 {$\leq$} {\ensuremath{\theta}} {\ensuremath{<}} 0.23), High (0.23 {$\leq$} 
{\ensuremath{\theta}} {\ensuremath{<}} 1.31), and Very High (1.31 {$\leq$} {\ensuremath{\theta}} {$\leq$} 2.4). The minimum and maximum Theta values 
are -3.00 and +2.4, respectively, with an average Theta of -0.3, which falls into the 
?Low? category. The Low, Medium, High, and Very High categories are represented 
by 30 (19.86\%), 67 (44.37\%), 40 (26.50\%), and 14 (9.27\%) pre-service teachers, 
respectively. Therefore, this study recommends that the Ministry of Education in 
Kazakhstan utilise the DLMCI for data-driven decision-making.},
        keywords = {digital literacy HOTS, pre-service teachers, measurement, Two-tier 
MCQ, TPACK}
}