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Osipenko, Maria – Education and Information Technologies, 2022
A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…
Descriptors: Behavior Patterns, Models, Undergraduate Students, Preferences
Xiaona Xia; Wanxue Qi – Education and Information Technologies, 2024
The full implementation of MOOCs in online education offers new opportunities for integrating multidisciplinary and comprehensive STEM education. It facilitates the alignment between online learning content and learning behaviors. However, it also presents new challenges, such as a high rate of STEM dropouts. Many learners struggle to establish…
Descriptors: Graphs, MOOCs, STEM Education, Learning Processes
Aislinn Keogh; Simon Kirby; Jennifer Culbertson – Cognitive Science, 2024
General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory--the component of short-term memory used for temporary…
Descriptors: Language Variation, Learning Processes, Short Term Memory, Schemata (Cognition)
Mohammed Jebbari; Bouchaib Cherradi; Soufiane Hamida; Abdelhadi Raihani – Education and Information Technologies, 2024
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…
Descriptors: MOOCs, Algorithms, Computer Simulation, COVID-19
Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making
Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
Jennifer Hu – ProQuest LLC, 2023
Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…
Descriptors: Linguistic Theory, Computational Linguistics, Models, Language Research
Fiol, C. Marlena; O'Connor, Edward J. – Learning Organization, 2017
Purpose: The purpose of Part II of this two-part paper is to uncover important differences in the nature of the three unlearning subprocesses, which call for different leadership interventions to motivate people to move through them. Design/methodology/approach: The paper draws on research in behavioral medicine and psychology to demonstrate that…
Descriptors: Learning, Organizational Change, Models, Behavior Patterns
Sungjin Nam – ProQuest LLC, 2020
This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…
Descriptors: Vocabulary Development, Intelligent Tutoring Systems, Student Evaluation, Learning Analytics
Zonca, Joshua; Coricelli, Giorgio; Polonio, Luca – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
In our everyday life, we often need to anticipate the potential occurrence of events and their consequences. In this context, the way we represent contingencies can determine our ability to adapt to the environment. However, it is not clear how agents encode and organize available knowledge about the future to react to possible states of the…
Descriptors: Eye Movements, Individual Differences, Task Analysis, Futures (of Society)
Process Mining Techniques for Analysing Patterns and Strategies in Students' Self-Regulated Learning
Bannert, Maria; Reimann, Peter; Sonnenberg, Christoph – Metacognition and Learning, 2014
Referring to current research on self-regulated learning, we analyse individual regulation in terms of a set of specific sequences of regulatory activities. Successful students perform regulatory activities such as analysing, planning, monitoring and evaluating cognitive and motivational aspects during learning not only with a higher frequency…
Descriptors: Metacognition, Learning Strategies, Learning Processes, Verbal Communication
Zhou, Xiaokang; Chen, Jian; Wu, Bo; Jin, Qun – IEEE Transactions on Learning Technologies, 2014
With the high development of social networks, collaborations in a socialized web-based learning environment has become increasing important, which means people can learn through interactions and collaborations in communities across social networks. In this study, in order to support the enhanced collaborative learning, two important factors, user…
Descriptors: Cooperative Learning, Social Networks, Behavior Patterns, Correlation
Gerber, Bertram; Yarali, Ayse; Diegelmann, Sören; Wotjak, Carsten T.; Pauli, Paul; Fendt, Marcus – Learning & Memory, 2014
Memories relating to a painful, negative event are adaptive and can be stored for a lifetime to support preemptive avoidance, escape, or attack behavior. However, under unfavorable circumstances such memories can become overwhelmingly powerful. They may trigger excessively negative psychological states and uncontrollable avoidance of locations,…
Descriptors: Pain, Learning Processes, Memory, Emotional Disturbances
Salvucci, Dario D. – Cognitive Science, 2013
Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to…
Descriptors: Cognitive Ability, Skill Development, Transfer of Training, Task Analysis
Knudsen, Daniel P.; Gentner, Timothy Q. – Brain and Language, 2010
Songbirds share a number of parallels with humans that make them an attractive model system for studying the behavioral and neurobiological mechanisms that underlie the learning and processing of vocal communication signals. Here we review the perceptual and cognitive mechanisms of audition in birds, and emphasize the behavioral and neural basis…
Descriptors: Singing, Auditory Perception, Animals, Learning Processes
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