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Xiangyi Liao; Daniel M. Bolt; Jee-Seon Kim – Journal of Educational Measurement, 2024
Item difficulty and dimensionality often correlate, implying that unidimensional IRT approximations to multidimensional data (i.e., reference composites) can take a curvilinear form in the multidimensional space. Although this issue has been previously discussed in the context of vertical scaling applications, we illustrate how such a phenomenon…
Descriptors: Difficulty Level, Simulation, Multidimensional Scaling, Graphs
Yafit Gabay; Lana Jacob; Atil Mansour; Uri Hertz – npj Science of Learning, 2025
The current study examined how individuals with neurodevelopmental disorders navigate the complexities of learning within multidimensional environments marked by uncertain dimension values and without explicit guidance. Participants engaged in a game-like complex reinforcement learning task in which the stimuli dimension determining reward…
Descriptors: Dyslexia, Attention Deficit Hyperactivity Disorder, Difficulty Level, Reinforcement
Aiman Mohammad Freihat; Omar Saleh Bani Yassin – Educational Process: International Journal, 2025
Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…
Descriptors: Accuracy, Computation, Multiple Choice Tests, Test Items
Julie E. Owen; Derrick R. Pacheco; Aoi Yamanaka – New Directions for Student Leadership, 2024
Leadership knowledge is viewed as an essential aspect of overall leadership learning, yet questions abound as to who decides what forms of knowledge are recognized as legitimate. This article reviews existing frames of leadership knowledge along with prior attempts to codify leadership knowledge. We then examine the function of leadership…
Descriptors: Decolonization, Codification, Models, Cultural Influences
C. Rashaad Shabab – Teaching Mathematics and Its Applications, 2024
This paper applies the well-known cognitive bias of loss aversion from behavioural economics to student decisions over engagement with mathematically demanding coursework. This bias is shown to predict behaviour that is consistent with mathematics anxiety in a dynamic model of student engagement. It is shown that these forces can imply…
Descriptors: Mathematics Anxiety, Mathematics Instruction, Difficulty Level, Student Behavior
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
Wuji Lin; Chenxi Lv; Jiejie Liao; Yuan Hu; Yutong Liu; Jingyuan Lin – npj Science of Learning, 2024
The debate about whether the capacity of working memory (WM) varies with the complexity of memory items continues. This study employed novel experimental materials to investigate the role of complexity in WM capacity. Across seven experiments, we explored the relationship between complexity and WM capacity. The results indicated that the…
Descriptors: Short Term Memory, Difficulty Level, Retention (Psychology), Test Items
Bephyer Parey; Elisabeth Kutscher – Journal of Mixed Methods Research, 2024
Rigor evaluation in mixed methods research is a growing need. Linking rigor to Hong and Pluye's (2019) concepts of methodological and reporting quality, the purpose of this article is to operationalize and expand Harrison et al.'s (2020) Rigorous Mixed Methods Framework. Drawing from a systematic methodological review of 66 inclusive education…
Descriptors: Mixed Methods Research, Difficulty Level, Evaluation Methods, Research Design
Gerit Wagner; Laureen Thurner – Journal of Information Systems Education, 2025
Git, as the leading version-control system, is frequently employed by software developers, digital product managers, and knowledge workers. Information systems (IS) students aspiring to fill software engineering, management, or research positions would therefore benefit from familiarity with Git. However, teaching Git effectively can be…
Descriptors: Computer Science Education, Information Systems, Teaching Methods, Computer Software
Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
Julius Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Instructional Science: An International Journal of the Learning Sciences, 2024
Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…
Descriptors: Problem Based Learning, Problem Solving, Prompting, Models
Jenna Starck; Oleg A. Sinelnikov; Kevin Andrew Richards – Journal of Teaching in Physical Education, 2024
Purpose: Using the assessment literacy framework, the purpose of this study was to explore preservice teachers understanding and enactment of the message system during an early field experience. Method: Six PTs employed SE seasons totaling 540 min. Seven qualitative data methods were utilized. Data analysis included deductive and inductive…
Descriptors: Preservice Teachers, Assessment Literacy, Preservice Teacher Education, Physical Education
Xiaodong Wei; Lei Wang; Lap-Kei Lee; Ruixue Liu – Journal of Educational Computing Research, 2025
Notwithstanding the growing advantages of incorporating Augmented Reality (AR) in science education, the pedagogical use of AR combined with Pedagogical Agents (PAs) remains underexplored. Additionally, few studies have examined the integration of Generative Artificial Intelligence (GAI) into science education to create GAI-enhanced PAs (GPAs)…
Descriptors: Artificial Intelligence, Technology Uses in Education, Models, Science Education
Stefan Vermeent; Ethan S. Young; Meriah L. DeJoseph; Anna-Lena Schubert; Willem E. Frankenhuis – Developmental Science, 2024
Childhood adversity can lead to cognitive deficits or enhancements, depending on many factors. Though progress has been made, two challenges prevent us from integrating and better understanding these patterns. First, studies commonly use and interpret raw performance differences, such as response times, which conflate different stages of cognitive…
Descriptors: Early Experience, Trauma, Cognitive Processes, Children
Heidi L. Morton; David Moran; Mary Amanda Graham; Paige Wakamatsu; Chloe Kimiai – Journal of Educational Leadership and Policy Studies, 2024
Counselors and educators must re-imagine social-emotional wellness as an essential part of the academic curriculum. The authors present a collaborative, sustainable model that focuses both on academic rigor and emotional wellness. The authors outline how this model can be integrated in any academic content area and how school counselors and…
Descriptors: School Counselors, High School Teachers, Social Emotional Learning, Academic Standards