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Tunga, Yeliz; Cagiltay, Kursat – Education and Information Technologies, 2023
Eye movement modeling examples (EMME) are novel types of video modeling examples that contain additional eye-movement recordings of the model to provide attentional guidance. Increasing demand in using instructional videos and interest in using eye-tracking in education makes EMME an appealing research subject. Hence, this study aims to…
Descriptors: Models, Eye Movements, Video Technology, Attention
Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing
Luo, Zhenzhen; Zheng, Chaoyu; Gong, Jun; Chen, Shaolong; Luo, Yong; Yi, Yugen – Education and Information Technologies, 2023
Learning interest affects the way of learning and its process, which is an important factor that affects the learning effect. At present, students' learning interest in a teaching environment is mainly based on a traditional questionnaire or case analysis, which is not conducive for teachers to promptly access students' interest in class to…
Descriptors: Student Interests, Artificial Intelligence, Attention, Psychological Patterns
Duta, Mihaela; Plunkett, Kim – Child Development, 2023
We present a neural network model of referent identification in a visual world task. Inputs are visual representations of item pairs unfolding with sequences of phonemes identifying the target item. The model is trained to output the semantic representation of the target and to suppress the distractor. The training set uses a 200-word lexicon…
Descriptors: Networks, Models, Brain, Child Language
Nika Jurov – ProQuest LLC, 2024
Speech is a complex, redundant and variable signal happening in a noisy and ever changing world. How do listeners navigate these complex auditory scenes and continuously and effortlessly understand most of the speakers around them? Studies show that listeners can quickly adapt to new situations, accents and even to distorted speech. Although prior…
Descriptors: Models, Auditory Perception, Speech Communication, Cognitive Processes
Peterson, Jean; Jen, Enyi – Gifted and Talented International, 2023
The Peterson Proactive Developmental Attention model (PPDA) offers a framework for understanding and addressing social and emotional concerns of high-ability students. This manuscript focuses on the developmental component, with emphasis on academic underachievement, with explanations and guidance for applying the developmental aspect of the PPDA…
Descriptors: Attention, Student Development, Low Achievement, Models
Mary Girgis; Josephine Paparo; Ian Kneebone – Journal of Intellectual & Developmental Disability, 2025
Background: Compared to their typically developing peers, children and adolescents with intellectual disabilities are at an increased risk of developing emotion regulation difficulties, this is especially the case for autistic individuals with intellectual disabilities. To better understand the emotion regulation experiences of children and…
Descriptors: Children, Adolescents, Intellectual Disability, Emotional Response
Luo, Zhenzhen; Jingying, Chen; Guangshuai, Wang; Mengyi, Liao – Interactive Learning Environments, 2022
A student's interest level can strongly affect the learning process, and thus, can be considered an important factor in the effort to improve learning. Presently, student interest is primarily assessed by administering questionnaires or conducting case analyses. However, this method cannot provide timely feedback in the learning environment to…
Descriptors: Student Interests, Technology Uses in Education, Models, Attention
Jinnie Shin; Bowen Wang; Wallace N. Pinto Junior; Mark J. Gierl – Large-scale Assessments in Education, 2024
The benefits of incorporating process information in a large-scale assessment with the complex micro-level evidence from the examinees (i.e., process log data) are well documented in the research across large-scale assessments and learning analytics. This study introduces a deep-learning-based approach to predictive modeling of the examinee's…
Descriptors: Prediction, Models, Problem Solving, Performance
Xiaoxuan Fang; Davy Tsz Kit Ng; Jac Ka Lok Leung; Huixuan Xu – Interactive Learning Environments, 2024
The Attention, Relevance, Confidence, and Satisfaction or ARCS model is an effective motivational model that has been widely accepted by education practitioners. Literature on the ARCS model has focused primarily on aspects of educational settings, research methods, and outcomes. However, few studies have addressed the applications of the ARCS…
Descriptors: Attention, Relevance (Education), Self Esteem, Student Satisfaction
Xiong, Jiawei; Li, Feiming – Educational Measurement: Issues and Practice, 2023
Multidimensional scoring evaluates each constructed-response answer from more than one rating dimension and/or trait such as lexicon, organization, and supporting ideas instead of only one holistic score, to help students distinguish between various dimensions of writing quality. In this work, we present a bilevel learning model for combining two…
Descriptors: Scoring, Models, Task Analysis, Learning Processes
Jennings, Jay; Muldner, Kasia – Instructional Science: An International Journal of the Learning Sciences, 2020
When students are solving problems they often turn to examples when they need assistance. Examples are helpful because they illustrate how a problem can be solved. However, when examples are very similar to the problems, students default to copying the example solutions, which hinders learning. To address this, prior work has investigated the…
Descriptors: Problem Solving, Models, Teaching Methods, Attention
Wang, Peipei; Li, Lin; Wang, Ru; Xie, Yifan; Zhang, Jianwei – Education and Information Technologies, 2022
Planning course study is critical to facilitate strategic intervention in education. As a significant basis of planning course study, student performance prediction aims to utilize students existing relevant information to predict their future learning performance including course grades, course failure, grade point average, etc. We target course…
Descriptors: Planning, Prediction, Academic Achievement, Grades (Scholastic)
Jin, Kuan-Yu; Siu, Wai-Lok; Huang, Xiaoting – Journal of Educational Measurement, 2022
Multiple-choice (MC) items are widely used in educational tests. Distractor analysis, an important procedure for checking the utility of response options within an MC item, can be readily implemented in the framework of item response theory (IRT). Although random guessing is a popular behavior of test-takers when answering MC items, none of the…
Descriptors: Guessing (Tests), Multiple Choice Tests, Item Response Theory, Attention
Ovando-Tellez, Marcela; Kenett, Yoed N.; Benedek, Mathias; Bernard, Matthieu; Belo, Joan; Beranger, Benoit; Bieth, Theophile; Volle, Emmanuelle – Creativity Research Journal, 2023
Associative thinking plays a major role in creativity, as it involves the ability to link distant concepts. Yet, the neural mechanisms allowing to combine distant associates in creative thinking tasks remain poorly understood. We investigated the whole-brain functional connectivity patterns related to combining remote associations for creative…
Descriptors: Brain, Associative Learning, Cognitive Processes, Creative Thinking