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David Williamson Shaffer; Yeyu Wang; Andrew Ruis – Journal of Learning Analytics, 2025
Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…
Descriptors: Learning Processes, Learning Analytics, Models, Data
Li, Michael Y.; Callaway, Fred; Thompson, William D.; Adams, Ryan P.; Griffiths, Thomas L. – Cognitive Science, 2023
Humans can learn complex functional relationships between variables from small amounts of data. In doing so, they draw on prior expectations about the form of these relationships. In three experiments, we show that people learn to adjust these expectations through experience, learning about the likely forms of the functions they will encounter.…
Descriptors: Learning Processes, Expectation, Experience, Relationship
Ahmed A. Alsayer; Jonathan Templin; Chris Niileksela; Bruce B. Frey – Education and Information Technologies, 2025
Prior research on the "Community of Inquiry" (CoI) framework has a limited amount of work which uses structural techniques to confirm the factorial structure of the CoI. The current study investigates the structural relationships among the three elements of the CoI framework (cognitive presence, teaching presence, and social presence),…
Descriptors: Communities of Practice, Inquiry, Online Courses, Educational Experience
Fu Chen; Chang Lu; Ying Cui – Education and Information Technologies, 2024
Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…
Descriptors: Computer Assisted Testing, Problem Solving, Learning Analytics, Learning Processes
Il Do Ha – Measurement: Interdisciplinary Research and Perspectives, 2024
Recently, deep learning has become a pervasive tool in prediction problems for structured and/or unstructured big data in various areas including science and engineering. In particular, deep neural network models (i.e. a basic core model of deep learning) can be viewed as an extension of statistical models by going through the incorporation of…
Descriptors: Artificial Intelligence, Statistical Analysis, Models, Algorithms
Siripon Saenboonsong; Akarapon Poonsawad – Journal of Education and Learning, 2024
The aims of this study were to synthesize and evaluate the learning model in gamification environment together with cartoon animation media to promote students' creative problem-solving skills. This study was divided into three phases, (i) synthesized and evaluated the appropriateness of learning model (ii) developed cartoon animation and (iii)…
Descriptors: Problem Solving, Creative Thinking, Cartoons, Gamification
Sarah H. Solomon; Anna C. Schapiro – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Concepts contain rich structures that support flexible semantic cognition. These structures can be characterized by patterns of feature covariation: Certain features tend to cluster in the same items (e.g., "feathers," "wings," "can fly"). Existing computational models demonstrate how this kind of structure can be…
Descriptors: Concept Formation, Learning Processes, Verbal Stimuli, Visual Stimuli
Feng Hsu Wang – IEEE Transactions on Learning Technologies, 2024
Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…
Descriptors: Learning Processes, Models, Man Machine Systems, Cooperative Learning
Xinning Zheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
The integration of Internet technology and the collaborative development of smart classrooms is an essential step for colleges and universities to advance English instruction reform. This study utilized data mining (DM) technology to analyze the learning process in college English smart classrooms. The results indicate that the DM algorithm used…
Descriptors: English Instruction, Data Use, Learning Processes, Educational Technology
A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
Xia, Xiaona; Qi, Wanxue – Education and Information Technologies, 2023
MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to…
Descriptors: MOOCs, Learning Processes, Learning Analytics, Graphs
Chunking versus Transitional Probabilities: Differentiating between Theories of Statistical Learning
Emerson, Samantha N.; Conway, Christopher M. – Cognitive Science, 2023
There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks.…
Descriptors: Statistics Education, Learning Processes, Learning Theories, Pattern Recognition
Ia Williamsson; Linda Askenäs – Learning Organization, 2024
Purpose: This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations. Design/methodology/approach: This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in…
Descriptors: Organizational Learning, Computer Software, Business, Reflection
Eva Portelance; Michael C. Frank; Dan Jurafsky – Cognitive Science, 2024
Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question…
Descriptors: Vocabulary, Grammar, Visual Aids, Language Acquisition
Christiansen, Iben Maj; Corriveau, Claudia; Pettersson, Kerstin – Educational Studies in Mathematics, 2023
Within the commognitive perspective, ritual and explorative routines are used in a very particular way to distinguish students' routines according to whether they are driven by social reward or by generating a substantiated narrative. Explorative routines in this theorisation may refer not to inquiry-based activity but to the result of a student's…
Descriptors: Mathematics Instruction, Teaching Methods, Learning Processes, Discovery Learning