The impact of cognitive characteristics and image-based semantic embeddings on item difficulty

Scientific Conference (2023, April 14)

Today’s educational field has a tremendous hunger for valid and psychometrically sound items to reliably track and model students’ learning processes. Educational large-scale assessments, formative ... [more ▼]

Today’s educational field has a tremendous hunger for valid and psychometrically sound items to reliably track and model students’ learning processes. Educational large-scale assessments, formative classroom assessment, and lately, digital learning platforms require a constant stream of high-quality, and unbiased items. However, traditional development of test items ties up a significant amount of time from subject matter experts, pedagogues and psychometricians and might not be suited anymore to nowadays demands. Salvation is sought in automatic item generation (AIG) which provides the possibility of generating multiple items within a short period of time based on the development of cognitively sound item templates by using algorithms (Gierl, Lay & Tanygin, 2021). Using images or other pictorial elements in math assessment – e.g. TIMSS (Trends in International Mathematics and Science (TIMSS, Mullis et al 2009) and Programme for International Student Assessment (PISA, OECD 2013) – is a prominent way to present mathematical tasks. Research on using images in text items show ambiguous results depending on their function and perception (Hoogland et al., 2018; Lindner et al. 2018; Lindner 2020). Thus, despite the high importance, effects of image-based semantic embeddings and their potential interplay with cognitive characteristics of items are hardly studied. The use of image-based semantic embeddings instead of mainly text-based items will increase though, especially in contexts with highly heterogeneous student language backgrounds. The present study psychometrically analyses cognitive item models that were developed by a team of national subject matter experts and psychometricians and then used for algorithmically producing items for the mathematical domain of numbers & operations for Grades 1, 3, and 5 of the Luxembourgish school system. Each item model was administered in 6 experimentally varied versions to investigate the impact of a) the context the mathematical problem was presented in, and b) problem characteristics which cognitive psychology identified to influence the problem solving process. Based on samples from Grade 1 (n = 5963), Grade 3 (n = 5527), and Grade 5 (n = 5291) collected within the annual Épreuves standardisées, this design allows for evaluating whether psychometric characteristics of produced items per model are a) stable, b) can be predicted by problem characteristics, and c) are unbiased towards subgroups of students (known to be disadvantaged in the Luxembourgish school system). The developed cognitive models worked flawlessly as base for generating item instances. Out of 348 generated items, all passed ÉpStan quality criteria which correspond to standard IRT quality criteria (rit > .25; outfit >1.2). All 24 cognitive models could be fully identified either by cognitive aspects alone, or a mixture of cognitive aspects and semantic embeddings. One model could be fully described by different embeddings used. Approximately half of the cognitive models could fully explain all generated and administered items from these models, i.e. no outliers were identified. This remained constant over all grades. With the exemption of one cognitive model, we could identify those cognitive factors that determined item difficulty. These factors included well known aspects, such as, inverse ordering, tie or order effects in additions, number range, odd or even numbers, borrowing/ carry over effects or number of elements to be added. Especially in Grade 1, the chosen semantic embedding the problem was presented in impacted item difficulty in most models (80%). This clearly decreased in Grades 3, and 5 pointing to older students’ higher ability to focus on the content of mathematical problems. Each identified factor was analyzed in terms of subgroup differences and about half of the models were affected by such effects. Gender had the most impact, followed by self-concept and socioeconomic status. Interestingly those differences were mostly found for cognitive factors (23) and less for factors related to the embedding (6). In sum, results are truly promising and show that item development based on cognitive models not only provides the opportunity to apply automatic item generation but to also create item pools with at least approximately known item difficulty. Thus, the majority of developed cognitive models in this study could be used to generate a huge number of items (> 10.000.000) for the domain of numbers & operations without the need for expensive field-trials. A necessary precondition for this is the consideration of the semantic embedding the problems are presented in, especially in lower Grades. It also has to be stated that modeling in Grade 1 was more challenging due to unforeseen interactions and transfer effects between items. We will end our presentation by discussing lessons learned from models where prediction was less successful and highlighting differences between the Grades. [less ▲]

Fairness as seen by students - a differentiated look at perceived assessment fairness by 7th and 9th graders in Luxembourg

Scientific Conference (2022, November 10)

Assessment is probably the central factor in every educational biography: On the one hand, through direct consequences for school career decisions, on the other hand, through repercussions on each ... [more ▼]

Assessment is probably the central factor in every educational biography: On the one hand, through direct consequences for school career decisions, on the other hand, through repercussions on each student’s self-concept in the respective subject, for one's own work behavior and the perception of institutional fairness in general. A crucial factor is the subjective, perceived fairness of assessment, which has been shown to influence students' satisfaction, motivation, and attitudes toward learning (Chory-Assad, 2002; Wendorf & Alexander, 2005). The current study examines how Luxembourgish students experience fairness of assessment on the basis of representative samples of the 7iéme (N > 700 students) and 9iéme/ 5iéme (N > 2200, 35% of the total cohort) and gives a first insight into the connection with school interest and self-concept. Special attention is given to the heterogeneity of the Luxembourgish student population: the extent to which language background, socioeconomic status, and gender are related to these perceptions of fairness will be analyzed. Data was collected as part of the nationwide Épreuves standardisées in fall 2021 using the Fairness Barometer (Sonnleitner & Kovacs, 2020) - a standardized instrument to measure informational and procedural fairness in student assessment. The analyses are theoretically based on Classroom Justice Theory and educational psychology (Chory-Assad and Paulsel, 2004; Chory, 2007; Duplaga & Astani, 2010) and utilize latent variable models (SEM) to study the complex interplay between perceived assessment practices and students’ school-related motivational factors. The insights offered by this study are internationally unique in their scope and provide a first glimpse on fairness perceptions of groups of Luxembourgish students in known disadvantaged situations. Results aim to sensitize especially active teachers and educators to the central importance of assessment in schools and offer some concrete advice how to improve it. References: Chory, R. M. (2007). Enhancing student perceptions of fairness: the relationship between instructor credibility and classroom justice. Commun. Educ. 56, 89–105. doi: 10.1080/03634520600994300 Chory-Assad, R. M., and Paulsel, M. L. (2004). Classroom justice: student aggression and resistance as reactions to perceived unfairness. Commun. Educ. 53, 253–273. doi: 10.1080/0363452042000265189 Chory-Assad, R. M. (2002). Classroom justice: perceptions of fairness as a predictor of student motivation, learning, and aggression. Commun. Q. 50, 58–77. doi: 10.1080/01463370209385646 Duplaga, E. A., and Astani, M. (2010). An exploratory study of student perceptions of which classroom policies are fairest. Decision Sci. J. Innov. Educ. 8, 9–33. doi: 10.1111/j.1540-4609.2009.00241.x Sonnleitner, P., & Kovacs, C. (2020, February). Differences between students’ and teachers’ fairness perceptions: Exploring the potential of a self-administered questionnaire to improve teachers’ assessment practices. In Frontiers in Education (Vol. 5, p. 17). Frontiers Media SA. Wendorf, C. A., and Alexander, S. (2005). The influence of individual- and class-level fairness-related perceptions on student satisfaction. Contemp. Educ. Psychol. 30, 190–206. doi: 10.1016/j.cedpsych.2004.07.003 [less ▲]

Using Automatic Item Generation in the context of the Épreuves Standardisées (Épstan): A pilot study on effects of altering item characteristics and semantic embeddings

Scientific Conference (2021, November 11)

Assessing mathematical skills in national school monitoring programs such as the Luxembourgish Épreuves Standardisées (ÉpStan) creates a constant demand of developing high-quality items that is both ... [more ▼]

Assessing mathematical skills in national school monitoring programs such as the Luxembourgish Épreuves Standardisées (ÉpStan) creates a constant demand of developing high-quality items that is both expensive and time-consuming. One approach to provide high-quality items in a more efficient way is Automatic Item Generation (AIG, Gierl, 2013). Instead of creating single items, cognitive item models form the base for an algorithmic generation of a large number of new items with supposedly identical item characteristics. The stability of item characteristics is questionable, however, when different semantic embeddings are used to present the mathematical problems (Dewolf, Van Dooren, & Verschaffel, 2017, Hoogland, et al., 2018). Given culture-specific knowledge differences in students, it is not guaranteed that illustrations showing everyday activities do not differentially impact item difficulty (Martin, et al., 2012). Moreover, the prediction of empirical item difficulties based on theoretical rationales has proved to be difficult (Leighton & Gierl, 2011). This paper presents a first attempt to better understand the impact of (a) different semantic embeddings, and (b) problem-related variations on mathematics items in grades 1 (n = 2338), 3 (n = 3835) and 5 (n = 3377) within the context of ÉpStan. In total, 30 mathematical problems were presented in up to 4 different versions, either using different but equally plausible semantic contexts or altering the problem’s content characteristics. Preliminary results of IRT-scaling and DIF-analysis reveal substantial effects of both, the embedding, as well as the problem characteristics on general item difficulties as well as on subgroup level. Further results and implications for developing mathematic items, and specifically, for using AIG in the course of Épstan will be discussed. [less ▲]