NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 7 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Wynton, Sarah K. A.; Anglim, Jeromy – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
While researchers have often sought to understand the learning curve in terms of multiple component processes, few studies have measured and mathematically modeled these processes on a complex task. In particular, there remains a need to reconcile how abrupt changes in strategy use can co-occur with gradual changes in task completion time. Thus,…
Descriptors: Learning Strategies, Learning Processes, Bayesian Statistics, Computer Assisted Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus – International Journal of Artificial Intelligence in Education, 2013
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Descriptors: Mathematics Instruction, Children, Computer Assisted Instruction, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Ting, Choo-Yee; Sam, Yok-Cheng; Wong, Chee-Onn – Computers & Education, 2013
Constructing a computational model of conceptual change for a computer-based scientific inquiry learning environment is difficult due to two challenges: (i) externalizing the variables of conceptual change and its related variables is difficult. In addition, defining the causal dependencies among the variables is also not trivial. Such difficulty…
Descriptors: Concept Formation, Bayesian Statistics, Inquiry, Science Instruction
Vos, Hans J. – 1988
The application of the Minnesota Adaptive Instructional System (MAIS) decision procedure by R. D. Tennyson et al. (1975, 1977) is examined. The MAIS is a computer-based adaptive instructional system. The problems of determining the optimal number of interrogatory examples in the MAIS can be formalized as a problem of Bayesian decision making. Two…
Descriptors: Academic Achievement, Bayesian Statistics, Computer Assisted Instruction, Decision Making
Peer reviewed Peer reviewed
Swaminathan, H.; And Others – Journal of Educational Measurement, 1975
A decision-theoretic procedure is outlined which provides a framework within which Bayesian statistical methods can be employed with criterion-referenced tests to improve the quality of decision making in objectives based instructional programs. (Author/DEP)
Descriptors: Bayesian Statistics, Computer Assisted Instruction, Criterion Referenced Tests, Decision Making
Novick, Melvin R.; And Others – 1980
The Computer-Assisted Data Analysis (CADA) Monitor is a set of conversational-language interactive computer programs that permit relatively inexperienced persons to perform relatively complex statistical data analysis. The Monitor leads the user through an analysis on a step-by-step basis providing the necessary direction, information, and…
Descriptors: Bayesian Statistics, Computer Assisted Instruction, Computer Programs, Data Analysis
Tennyson, Robert – 1978
Presented are variables and conditions for design of a computer-based adaptive instructional system. The design strategy uses Bayes' theory of conditional probability to determine an instructional sequence according to individual student characteristics and needs. The adaptive strategy uses prior estimates based on student pretask and on-task…
Descriptors: Aptitude Treatment Interaction, Bayesian Statistics, Computer Assisted Instruction, Computer Managed Instruction