Item response theory: A basic concept

Mahmud, Jumailiyah

doi:10.5897/err2017.3147

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…Item response theory (IRT) is a measurement model based on attempts to explain the relationship between latent traits (e.g., level of stress) and their manifestations (derived from responses to items). A graded response model (because this fits best for a questionnaire that uses a Likert scale for the responses (Merino-Soto, Angulo-Ramos, Rovira-Millán, and Rosario-Hernández, 2023)) and a maximum likelihood approach (because it is commonly used and is effective for large sample sizes (Jumailiyah, 2017) were used to fit the IRT models.…”

Section: Item Response Theorymentioning

confidence: 99%

Fourteen‐item perceived stress scale assessment using item response theory among pregnant women

Pintro,

Sanchez,

Rondon

et al. 2023

Scandinavian J Psychology

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The current study aimed to assess the psychometric properties of the Spanish language version of the 14‐item Perceived Stress Scale (PSS‐S) in a population of pregnant women who speak Spanish in Peru using item response theory (IRT). Our study consisted of 5,435 pregnant women who participated in the Pregnancy Outcomes Maternal and Infant Study (PrOMIS) cohort in Peru. Exploratory and confirmatory factor analyses were conducted to determine dimensionality of the scale in this population, and item response theory was conducted to determine the applicability of the PSS. The PSS consisted of a 2‐factor questionnaire measuring perceived stress and coping capacity accounting for 77% of variability. The IRT analysis showed differences in item difficulty and discrimination. Item difficulty represents the level of the latent construct where 50% of respondents endorse a particular response, and item discrimination determines the rate of change of the probability of endorsing an item for differing ability levels. For the first factor, perceived stress, item 12 was the least difficult and item 2 was the most difficult. For the second factor, coping capacity, item 9 was the least difficult and item 6 was the most difficult. The Spanish version of the 14‐item PSS can be a useful assessment tool for perceived stress, but more IRT should be done to delve further into the psychometric properties of the questionnaire to inform clinicians and policy makers more appropriately.

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Section: Item Response Theorymentioning

confidence: 99%

Fourteen‐item perceived stress scale assessment using item response theory among pregnant women

Pintro,

Sanchez,

Rondon

et al. 2023

Scandinavian J Psychology

View full text Add to dashboard Cite

show abstract

“…The adaptation of activities, especially for closed-ended questions, has been discussed to some extent in the literature (Chrysafiadi, Troussas, & Virvou, 2018). In the case of closed-ended questions, such as those used in most MOOCs, IRT can be an interesting solution to adapt the questions to the level and skills of the students (Cui et al, 2019;Hambleton, Swaminathan, Rogers, 1991;Mahmud, 2017). IRT models can include up to three parameters (Reeve & Fayers, 2005): ( 1) difficulty (the ability a student needs to have to be able to answer correctly a question with a 50% probability); ( 2) discrimination (how good a question is to differentiate between students with an ability higher or lower than the needed to answer that question correctly); and ( 3) guessing (the probability to answer a question correctly by guessing).…”

Section: Adaptive Learningmentioning

confidence: 99%

Adaptive learning module for a conversational agent to support MOOC learners

González-Castro

Muñoz‐Merino

Alario-Hoyos

et al. 2021

AJET

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Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that complements a MOOC on Java programming, helping learners review the key concepts of the MOOC. This adaptive learning module adapts the difficulty of the questions provided to learners considering their level of knowledge using item response theory (IRT) and also provides recommendations of video fragments extracted from the MOOC for when learners fail questions. The adaptive learning module for JavaPAL has been evaluated showing good usability and learnability through the system usability scale (SUS), reasonably suitable video fragments recommendations for learners, and useful visualisations generated as part of the IRT-based adaptation of questions for instructors to better understand what is happening in the course, to design exams, and to redesign the course content.

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“…CTT approaches to measurement rely mainly on correlational techniques like Cronbach's alpha coefficients, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). Although CTT approaches have advantages (e.g., require smaller sample sizes, weaker assumptions) and can be effective at creating internally consistent scales, researchers are using IRT approaches to develop psychometrically optimized scales by increasing precision and minimizing measurement error (Foster et al, 2017;Mahmud, 2017).…”

Section: Studymentioning

confidence: 99%

School Burnout Inventory: Latent Profile and Item Response Theory Analyses in Undergraduate Samples

et al. 2020

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The current research reports both latent profile (person-oriented) and item response theory (IRT) analyses of the School Burnout Inventory (SBI) in United States undergraduate samples. Study 1 (n = 1,007) comprises a latent profile analysis (LPA) that identified four mutually exclusive subgroups based on patterns of school burnout responses. Covariate analyses of grade point average and negative affect suggested that school burnout profiles function similarly to variable-oriented approaches. Study 2 (n = 544) explored longitudinal patterns of school burnout among college students via use of a repeated measures LPA. Findings suggested that the profiles identified reflect a relatively stable school burnout trajectory over time. Covariate analysis of sleep quality and academic engagement demonstrated differences across profiles, but the patterns were similar to variable-oriented statistical approaches. Study 3 (n = 2,364) utilized an IRT analysis of the SBI to identify a short, efficient measure. Item information curves and graded response model item discrimination parameters identified a 4-item SBI scale (SBI-4) that offered reasonably high levels of information for assessing school burnout in comparison to the original nine-item SBI. Implications and future research are identified. Keywords: item response theory, latent profile analysis, person-oriented approach, repeated measures latent profile analysis, School Burnout Inventory with about 11.5 million females enrolled in the fall of 2017 as compared to 8.9 million males (U.S. Department of Education, 2017). Reflecting the importance of higher education, the number of American undergraduate students is increasing. Enrollment of traditional college-aged students (18-to 24-year-olds) is up more than 5.1 million in 2017 (20.4 million) from that of 2000 (U.S. Department of Education, 2017). Given the prevalence of college education and its resulting employment advantages, investigations into factors that may jeopardize retention in United States colleges are warranted. One such emerging factor is school burnout. Burnout is a well-researched, multidimensional, affective response to occupational stress. Although burnout has traditionally been investigated within the workplace, it is becoming more

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Item response theory: A basic concept

Cited by 6 publications

References 11 publications

Fourteen‐item perceived stress scale assessment using item response theory among pregnant women

Fourteen‐item perceived stress scale assessment using item response theory among pregnant women

Adaptive learning module for a conversational agent to support MOOC learners

School Burnout Inventory: Latent Profile and Item Response Theory Analyses in Undergraduate Samples

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