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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
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – International Educational Data Mining Society, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Intelligent Tutoring Systems, Sequential Approach, Problem Solving, Learning Processes
Chen, Bodong; Resendes, Monica; Chai, Ching Sing; Hong, Huang-Yao – Interactive Learning Environments, 2017
As collaborative learning is actualized through evolving dialogues, temporality inevitably matters for the analysis of collaborative learning. This study attempts to uncover sequential patterns that distinguish "productive" threads of knowledge-building discourse. A database of Grade 1-6 knowledge-building discourse was first coded for…
Descriptors: Elementary Education, Knowledge Level, Databases, Coding
Duncan, Ravit Golan; Choi, Jinnie; Castro-Faix, Moraima; Cavera, Veronica L. – Science & Education, 2017
Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus…
Descriptors: Genetics, Learning Processes, Sequential Learning, Sequential Approach
Frey, Renato; Rieskamp, Jörg; Hertwig, Ralph – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
In nonmonotonic decision problems, the magnitude of outcomes can both increase and decrease over time depending on the state of the decision problem. These increases and decreases may occur repeatedly and result in a variety of possible outcome distributions. In many previously investigated sequential decision problems, in contrast, outcomes (or…
Descriptors: Risk, Learning Processes, Reinforcement, Decision Making
Xiong, Xiaolu; Zhao, Siyuan; Van Inwegen, Eric G.; Beck, Joseph E. – International Educational Data Mining Society, 2016
Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…
Descriptors: Intelligent Tutoring Systems, Computer Software, Bayesian Statistics, Knowledge Level
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
Glaser-Opitz, Henrich; Budajová, Kristina – Acta Didactica Napocensia, 2016
The article introduces a software application (MATH) supporting an education of Applied Mathematics, with focus on Numerical Mathematics. The MATH is an easy to use tool supporting various numerical methods calculations with graphical user interface and integrated plotting tool for graphical representation written in Qt with extensive use of Qwt…
Descriptors: Mathematics Education, Computer Software, Computer Assisted Instruction, College Mathematics
Min, Wookhee; Wiggins, Joseph B.; Pezzullo, Lydia G.; Vail, Alexandria K.; Boyer, Kristy Elizabeth; Mott, Bradford W.; Frankosky, Megan H.; Wiebe, Eric N.; Lester, James C. – International Educational Data Mining Society, 2016
Recent years have seen a growing interest in intelligent game-based learning environments featuring virtual agents. A key challenge posed by incorporating virtual agents in game-based learning environments is dynamically determining the dialogue moves they should make in order to best support students' problem solving. This paper presents a…
Descriptors: Prediction, Models, Intelligent Tutoring Systems, Computer Simulation
Bong, Hyeon-Cheol; Cho, Yonjoo; Kim, Hyung-Sook – Action Learning: Research and Practice, 2014
As the number of organizations implementing action learning increases, both successful and failed cases also increase in action learning practice in South Korea. Existing studies on action learning have listed key success factors of action learning at the program level or at the team level but have not paid sufficient attention to the program…
Descriptors: Experiential Learning, Instructional Design, Design Preferences, Models
Cheng, Kun-Hung; Hou, Huei-Tse – Technology, Pedagogy and Education, 2015
Previous research regarding peer assessment has investigated the relationships between peer feedback and learners' performance. However, few studies investigate in-depth learning processes during technology-assisted peer assessment activities, particularly from affective, cognitive, and metacognitive perspectives. This study conducts a series of…
Descriptors: Behavior Patterns, Student Behavior, Metacognition, Peer Evaluation
Bussey, Thomas J. – ProQuest LLC, 2013
Biochemistry education relies heavily on students' ability to visualize abstract cellular and molecular processes, mechanisms, and components. As such, biochemistry educators often turn to external representations to provide tangible, working models from which students' internal representations (mental models) can be constructed, evaluated, and…
Descriptors: Biochemistry, Science Instruction, Science Teachers, Teacher Attitudes
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
Sabo, Kent – ProQuest LLC, 2013
Concerted efforts have been made within teacher preparation programs to integrate teaching with technology into the curriculum. Unfortunately, these efforts continue to fall short as teachers' application of educational technology is unsophisticated and not well integrated. The most prevalent approaches to integrating technology tend to ignore…
Descriptors: Technological Literacy, Pedagogical Content Knowledge, Graduate Students, Teacher Education
Mühlfelder, Manfred; Konermann, Tobias; Borchard, Linda-Marie – Journal of Problem Based Learning in Higher Education, 2015
In this paper we describe a "Train the Tutor" programme (TtT) for developing the metacognitive skills, facilitator skills, and tutor skills of students in a problem based learning (PBL) context. The purpose of the programme was to train 2nd and 3rd year undergraduate students in psychology to become effective PBL tutors for…
Descriptors: Undergraduate Students, Problem Based Learning, Tutor Training, Program Design