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Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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Davis Krumins; Sandra Schumann; Veiko Vunder; Rauno Põlluäär; Kristjan Laht; Renno Raudmäe; Alvo Aabloo; Karl Kruusamäe – IEEE Transactions on Learning Technologies, 2024
Teaching robotics with the robot operating system (ROS) is valuable for instating good programming practices but requires significant setup steps from the learner. Providing a ready-made ROS learning environment over the web can make robotics more accessible; however, most of the previous remote labs have abstracted the authentic ROS developer…
Descriptors: Teaching Methods, Robotics, Programming, Computer Science Education
Sequeira Cesar de Oliveira, Juliana – ProQuest LLC, 2023
The present study sought to evaluate trial designs and training designs that are commonly used in popular commercially available computer-assisted language-learning (CALL) programs. The first two experiments (Experiment 1a and 1b) compared the effects of passive viewing and active student response methods in vocabulary learning. Contingencies on…
Descriptors: Computer Assisted Instruction, Teaching Methods, Computer Software, Vocabulary Development
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Shari Cavicchi; Abdulaziz Abubshait; Giulia Siri; Magda Mustile; Francesca Ciardo – Cognitive Research: Principles and Implications, 2025
Cognitive load occurs when the demands of a task surpass the available processing capacity, straining mental resources and potentially impairing performance efficiency, such as increasing the number of errors in a task. Owing to its ubiquity in real-world scenarios, the existence of offloading strategies to reduce cognitive load is not new to…
Descriptors: Robotics, Psychological Patterns, Cognitive Processes, Computer Software
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Rebecca J. Collie; Andrew J. Martin – Social Psychology of Education: An International Journal, 2025
Educational bodies are weighing up the extent to which generative artificial intelligence (genAI) is embedded within educational settings. Although researchers have examined how (generative) AI can be used for effective teaching and learning, less is known about how genAI was being integrated within teachers' practice shortly after the wide-scale…
Descriptors: Teaching Methods, Learning Processes, Artificial Intelligence, Computer Software
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Guoyang Liu; Yueyuan Zheng; Michelle Hei Lam Tsang; Zhao Yazhou; Janet H. Hsiao – npj Science of Learning, 2025
Eye movement patterns and consistency during face recognition are both associated with recognition performance. We examined whether they reflect different mechanisms through EEG decoding. Eighty-four participants performed an old-new face recognition task with eye movement pattern and consistency quantified using eye movement analysis with hidden…
Descriptors: Eye Movements, Human Body, Recognition (Psychology), Diagnostic Tests
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Venus Ho; Emily Stonehouse; Ori Friedman – Developmental Psychology, 2024
Although stories for children often feature supernatural and fantastical events, children themselves often prefer realistic events when choosing what should happen in a story. In two experiments, we investigated whether 3- to 5-year-olds (total N = 240 from diverse backgrounds) might be more likely to include fantastical events in stories about…
Descriptors: Fiction, Fantasy, Child Development, Preferences
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Václav Dobiáš; Václav Šimandl; Jirí Vanícek – Informatics in Education, 2024
The paper discusses an alternative method of assessing the difficulty of pupils' programming tasks to determine their age appropriateness. Building a program takes the form of its successive iterations. Thus, it is possible to monitor the number of times such a program was built by the solver. The variance of the number of program builds can be…
Descriptors: Difficulty Level, Computer Science Education, Programming, Task Analysis
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Nicolas Loiseau; Adrien Bruni; Pierre Puigpinos; Jean-Christophe Sakdavong – International Association for Development of the Information Society, 2024
This paper explores the concept of self-efficacy and its impact on individual performance on a mobile learning application. Self-efficacy refers to one's belief in their ability to achieve their goals and is a key factor in everyday life. To investigate the relationship between self-efficacy and performance, we conducted an experiment with 104…
Descriptors: Self Efficacy, Telecommunications, Handheld Devices, Computer Software
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Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
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Xavier Ochoa; Xiaomeng Huang; Yuli Shao – Journal of Learning Analytics, 2025
Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…
Descriptors: Learning Analytics, Artificial Intelligence, Computer Software, Scores
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Allison L. Gantt; Teo Paoletti; Srujana V. Acharya; Claudine Margolis – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
Emergent graphical shape thinking (EGST) entails conceiving a graph as being dynamically generated via the trace of a moving point constrained by two changing quantities. As such, Paoletti et al. (2023) argue that meanings for quantities within a situation and meanings for graphical representations must be connected, or bridged, to engage in EGST.…
Descriptors: Graphs, Mathematics Instruction, Task Analysis, Thinking Skills
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Paul Meara; Imma Miralpeix – Vocabulary Learning and Instruction, 2025
This paper is part 5 of a series of workshops that examines the properties of some simple models of vocabulary networks. While previous workshops dealt with activating words in the network, this workshop focuses on vocabulary loss. We will simulate two possible ways of modelling attrition: (a) explicitly turning active words OFF, and (b) raising…
Descriptors: Vocabulary Development, Workshops, Models, Networks
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Laurie-Anne Sapey-Triomphe; Gaëtan Sanchez; Marie-Anne Hénaff; Sandrine Sonié; Christina Schmitz; Jérémie Mattout – npj Science of Learning, 2023
Predictive coding theories suggest that core symptoms in autism spectrum disorders (ASD) may stem from atypical mechanisms of perceptual inference (i.e., inferring the hidden causes of sensations). Specifically, there would be an imbalance in the precision or weight ascribed to sensory inputs relative to prior expectations. Using three tactile…
Descriptors: Autism Spectrum Disorders, Tactual Perception, Sensory Integration, Comparative Analysis
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Sümeyra Tosun – Cognitive Research: Principles and Implications, 2024
Machine translation (MT) is the automated process of translating text between different languages, encompassing a wide range of language pairs. This study focuses on non-professional bilingual speakers of Turkish and English, aiming to assess their ability to discern accuracy in machine translations and their preferences regarding MT. A particular…
Descriptors: Bilingualism, Turkish, English (Second Language), Second Language Learning
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