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Yang, Xiaotong; Rahimi, Seyedahmad; Fulwider, Curt; Smith, Ginny; Shute, Valerie – Educational Technology Research and Development, 2022
The current study investigated students' gameplay behavioral patterns as a function of in-game learning supports delivery timing when played a computer-based physics game. Our sample included 134 secondary students (M = 14.40, SD = .90) from all over the United States, who were randomly assigned into three conditions: receiving instructional…
Descriptors: Student Behavior, Educational Games, Game Based Learning, Problem Solving
Chen, Binglin; West, Matthew; Ziles, Craig – International Educational Data Mining Society, 2018
This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…
Descriptors: Accuracy, Probability, Student Behavior, Test Items
Shen, Shitian; Chi, Min – International Educational Data Mining Society, 2017
One of the most challenging tasks in the field of Educational Data Mining (EDM) is to cluster students directly based on system-student sequential moment-to-moment interactive trajectories. The objective of this study is to build a general temporal clustering framework that captures the distinct characteristics of students' sequential behaviors…
Descriptors: Sequential Approach, Cluster Grouping, Interaction, Student Behavior
Cheng, Ya-Wen; Wang, Yuping; Cheng, I-Ling; Chen, Nian-Shing – Interactive Learning Environments, 2019
Collaborative learning has long been proved to be a crucial agent for enhancing students' social skills, problem-solving abilities and individual learning performance. Understanding how students move from one phase to another in their collaboration process can inform educators of how best to facilitate such learning. However, this is still an area…
Descriptors: Interaction, Computer Simulation, Mathematics Activities, Computer Games
Codina, A.; Cañadas, M. C.; Castro, E. – Electronic Journal of Research in Educational Psychology, 2015
Introduction: The macroscopic perspective is one of the frameworks for research on problem solving in mathematics education. Coming from this perspective, our study addresses the stages of thought in mathematical problem solving, offering an innovative approach because we apply sequential relations and global interrelations between the different…
Descriptors: Problem Solving, Mathematics Instruction, Sequential Approach, Observation
Wu, Sheng-Yi; Hou, Huei-Tse – Journal of Educational Computing Research, 2015
Cognitive styles play an important role in influencing the learning process, but to date no relevant study has been conducted using lag sequential analysis to assess knowledge construction learning patterns based on different cognitive styles in computer-supported collaborative learning activities in online collaborative discussions. This study…
Descriptors: Cognitive Style, Student Behavior, Problem Solving, Discussion (Teaching Technique)
Wang, Shu-Ming; Hou, Huei-Tse; Wu, Sheng-Yi – Educational Technology Research and Development, 2017
Instructional strategies can be helpful in facilitating students' knowledge construction and developing advanced cognitive skills. In the context of collaborative learning, instructional strategies as scripts can guide learners to engage in more meaningful interaction. Previous studies have been investigated the benefits of different instructional…
Descriptors: Cognitive Processes, Electronic Journals, Student Journals, Web Based Instruction
Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2015
This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…
Descriptors: Learning Activities, Learning Processes, Data Collection, Student Behavior
Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse – Educational Technology & Society, 2015
Unlike most research, which has primarily examined the players' interest in or attitude toward game-based learning through questionnaires, the purpose of this empirical study is to explore students' engagement patterns by qualitative observation and sequential analysis to visualize and better understand their game-based learning process. We…
Descriptors: Elementary School Students, Learner Engagement, Educational Games, Teaching Methods
Wu, Sheng-Yi; Hou, Huei-Tse; Hwang, Wu-Yuin; Liu, Eric Zhi-Feng – Journal of Educational Computing Research, 2013
Both asynchronous and synchronous discussions have advantages and limitations for online learning. This study conducts an empirical analysis of these discussion activities while applying the proposed Seamless Online Learning Integrated Discussion (SOLID) system, which can instantly integrate Facebook's asynchronous discussion function with the MSN…
Descriptors: Problem Solving, Active Learning, Student Projects, Student Behavior
Lee, Woon Jee – ProQuest LLC, 2012
The purpose of this study was to explore the nature of students' mapping and discourse behaviors while constructing causal maps to articulate their understanding of a complex, ill-structured problem. In this study, six graduate-level students were assigned to one of three pair groups, and each pair used the causal mapping software program,…
Descriptors: Student Behavior, Graduate Students, Maps, Computer Uses in Education
Simonson, Michael, Ed.; Seepersaud, Deborah, Ed. – Association for Educational Communications and Technology, 2021
For the forty-fourth time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online and onsite during the annual AECT Convention. Volume 1 contains papers dealing primarily with research and development topics. Papers dealing with…
Descriptors: Educational Technology, Technology Uses in Education, Computer Mediated Communication, Video Technology
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection