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Budgett, Stephanie; Pfannkuch, Maxine – Teaching and Learning Research Initiative, 2016
This report summarises the research activities and findings from the TLRI-funded project entitled "Visualising Chance: Learning Probability Through Modelling." This exploratory study was a 2-year collaboration among two researchers, two conceptual software developers/interactive graphics experts, three university lecturers/practitioners,…
Descriptors: Statistics, Probability, Mathematical Models, Computer Software
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
Improving Students' Problem Solving in a Virtual Chemistry Simulation through Metacognitive Messages
Beal, Carole R.; Stevens, Ronald H. – Society for Research on Educational Effectiveness, 2011
Recent assessments indicate that American students do not score well on tests of scientific problem solving, relative to students in other nations. IMMEX is a web-based virtual environment that provides students with opportunities to solve science problems by viewing information resources through a suite of menu options, developing a hypothesis…
Descriptors: Feedback (Response), Chemistry, Problem Solving, Educational Technology
Briggs, Derek C.; Wilson, Mark – Journal of Educational Measurement, 2007
An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random…
Descriptors: Markov Processes, Generalizability Theory, Item Response Theory, Computation
Dewdney, A. K. – Scientific American, 1989
Reviews the performance of computer programs for writing poetry and prose, including MARK V. SHANEY, MELL, POETRY GENERATOR, THUNDER THOUGHT, and ORPHEUS. Discusses the writing principles of the programs. Provides additional information on computer magnification techniques. (YP)
Descriptors: Computer Simulation, Computer Software, Computer Software Reviews, Computers