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Direct linkWen, Cai-Ting; Chang, Chia-Jung; Chang, Ming-Hua; Fan Chiang, Shih-Hsun; Liu, Chen-Chung; Hwang, Fu-Kwun; Tsai, Chin-Chung – Instructional Science: An International Journal of the Learning Sciences, 2018
This study investigated students' modeling progress and strategies in a problem-solving simulation game through content analysis, and through supervised and unsupervised lag sequential analysis (LSA). Multiple data sources, including self-report models and activity logs, were collected from 25 senior high school students. The results of the…
Descriptors: Educational Games, Simulation, Problem Solving, Models
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
Hafidi, Mohamed; Bensebaa, Taher – International Journal of Distance Education Technologies, 2015
The majority of adaptive and intelligent tutoring systems (AITS) are dedicated to a specific domain, allowing them to offer accurate models of the domain and the learner. The analysis produced from traces left by the users is didactically very precise and specific to the domain in question. It allows one to guide the learner in case of difficulty…
Descriptors: Intelligent Tutoring Systems, Foreign Countries, Interdisciplinary Approach, Universities
Shukor, Nurbiha A.; Tasir, Zaidatun; Van der Meijden, Henny; Harun, Jamalludin – Educational Technology & Society, 2014
Online collaborative learning allows discussion to occur at greater depth where knowledge can be constructed remotely. However students were found to construct knowledge at low-level where they discussed by sharing and comparing opinions; those are inadequate for new knowledge creation. As such, this research attempted to investigate the students'…
Descriptors: Learning Strategies, Cognitive Style, Cooperative Learning, Electronic Learning
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
Download full textBarnes, 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
