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Jane Hubbard – Mathematics Education Research Group of Australasia, 2024
The current paper overviews a nine-month PhD study that investigated the impact of learning mathematics through sequences of challenging tasks on the mathematical competence and attitudes of Year 2 students (n = 59). Adopting a Self-Determination Theory lens, a pragmatist paradigm and a mixed-method design, the study found that at all levels of…
Descriptors: Self Determination, Learning Processes, Mathematics Education, Elementary School Students
Russo, James; Bobis, Janette; Downton, Ann; Livy, Sharyn; Sullivan, Peter – Mathematics Education Research Group of Australasia, 2022
The current study explores how teachers report using enabling and extending prompts when teaching with sequences of challenging mathematical tasks. Twenty-nine early years primary school teachers completed a questionnaire following their participation in a professional learning project. Findings suggest that teachers': view prompts as important…
Descriptors: Cues, Elementary School Students, Teaching Methods, Task Analysis
Zhou, Jianing; Bhat, Suma – Grantee Submission, 2021
Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…
Descriptors: Models, Online Courses, Learner Engagement, Learning Processes
Kang, Jina; An, Dongwook; Yan, Lili; Liu, Min – International Educational Data Mining Society, 2019
Collaborative problem-solving (CPS) as a key competency required in the 21st century. There has been an increasing need to understand CPS since it involves not only cognitive but also social processes, and thus its process is difficult to examine. Recent research has highlighted that computer-based learning environments provide an opportunity for…
Descriptors: Cooperative Learning, Problem Solving, Science Education, Educational Games
Cook, Joshua; Lynch, Collin F.; Hicks, Andrew G.; Mostafavi, Behrooz – International Educational Data Mining Society, 2017
BKT and other classical student models are designed for binary environments where actions are either correct or incorrect. These models face limitations in open-ended and data-driven environments where actions may be correct but non-ideal or where there may even be degrees of error. In this paper we present BKT-SR and RKT-SR: extensions of the…
Descriptors: Models, Bayesian Statistics, Data Use, Intelligent Tutoring Systems
Emond, Bruno; Buffett, Scott – International Educational Data Mining Society, 2015
This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…
Descriptors: Data Analysis, Classification, Learning Activities, Inquiry
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
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
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
Sullivan, Peter; Mousley, Judy; Zevenbergen, Robyn – International Group for the Psychology of Mathematics Education, 2004
We are researching actions that teachers can take to improve mathematics learning for all students. Structural elements of the lessons being trialled include making aspects of pedagogy explicit to seek to overcome differences in familiarity with schooling processes, and sequencing tasks with the potential to engage students. This article reports…
Descriptors: Familiarity, Mathematics Instruction, Mathematics Achievement, Teaching Methods
Carifio, James – 1976
This study compared two learning structures for an introductory course in tests and measurements in terms of their relative effects on attitudes and achievement. The first structure represented a functionally arranged instructional sequence (FAIS). The second represented a psychologically arranged instructional sequence (PAIS). The instructional…
Descriptors: Academic Achievement, Education Courses, Education Majors, Learning Processes
Partin, Ronald L. – 1976
The instructional effectiveness of learning programs derived from Gagne-type task analysis, ordering theory analysis, and random sequenced presentation of complex intellectual skills were investigated. Fifty-seven high school students completed a self-instructional program derived from one of the three sequences. No significant differences were…
Descriptors: Academic Achievement, Cognitive Processes, High School Students, Instructional Design
Douglass, Claudia B. – 1978
The primary purpose of the reported study was to identify a possible interaction between the cognitive style of the students and the instructional sequence of the materials and their combined effect on achievement. The subjects were 627 biology students from six midwestern high schools. The students were ranked and classified as field-dependent…
Descriptors: Biology, Cognitive Style, Deduction, Educational Research
Trimino, Andy – 1993
A basic principle of second language learning is the need to negotiate meaning in any language-learning situation. Once meaning is established, comprehension follows. Clusters of meaning result in schemata, which serve as the basis for sustained communication and ultimately, permanence of language learning. The comprehension approach to second…
Descriptors: Class Activities, Classroom Techniques, Comprehension, Educational Strategies