Technology-Enhanced Mathematics and Statistics Education Ivo D. Dinov & Nicolas Christou www.SOCR.ucla.edu Ivo D. Dinov & Nicolas Christou www.SOCR.ucla.edu.

Slides:

Advertisements

Similar presentations

Happiness comes not from material wealth but less desire. 1.

Advertisements

Implications of Big Data for Statistics Instruction Mark L. Berenson Montclair State University MSMESB Mini-Conference DSI - Baltimore November 17, 2013.

INTRODUCTION TO NON-PARAMETRIC ANALYSES CHI SQUARE ANALYSIS.

Interactive, Data-Driven and Technology-Enhanced Approach for Probability and Statistics Education Ivo D. Dinov & Nicolas Christou Ivo.

ANOVA: ANalysis Of VAriance. In the general linear model x = μ + σ 2 (Age) + σ 2 (Genotype) + σ 2 (Measurement) + σ 2 (Condition) + σ 2 (ε) Each of the.

Improvements in Graphics from present at Hope College, Prepared by Elliot A. Tanis August, 2009.

Programme in Statistics (Courses and Contents). Elementary Probability and Statistics (I) 3(2+1)Stat. 101 College of Science, Computer Science, Education.

Integrated, Multidisciplinary & Technology-Enhanced Science Education: The Next Frontier Ivo D. Dinov Ivo D. Dinov It’s Online,

1 Review “Conducted a review of C&IT in learning and teaching and shown an understanding of the educational processes” u Review a type of learning technology.

Practical Meta-Analysis -- D. B. Wilson

1 BA 555 Practical Business Analysis Review of Statistics Confidence Interval Estimation Hypothesis Testing Linear Regression Analysis Introduction Case.

Statistical Theory; Why is the Gaussian Distribution so popular? Rob Nicholls MRC LMB Statistics Course 2014.

1 Service Learning Group D Mentors  Dr. M. N. Kaumal  Dr. H. R. Perera Cooperate Partner.

Lecture II-2: Probability Review

Robert delMas (Univ. of Minnesota, USA) Ann Ooms (Kingston College, UK) Joan Garfield (Univ. of Minnesota, USA) Beth Chance (Cal Poly State Univ., USA)

Teaching Statistics Methods for Biology 1. Outline About stat 503 Students Course set up – Lecture – Project Challenges Teaching approach – Project design.

Statistics 501 Methods of Applies Statistics Using MINITAB Fall 2012 TuTh 11:15AM-12:30PM Rm219 Professor H. K. Hsieh (“Shay”)

Herding CATS: the Community of Academic Technology Staff Lou Zweier, Director CSU Center for Distributed Learning The California State University NLII,

Linear Algebra and Image Processing

LEMMA: Learning Environment in Multilevel Modelling and Applications Fiona Steele London School of Economics & Political Science Director NCRM LEMMA node,

1. An Overview of the Data Analysis and Probability Standard for School Mathematics? 2.

Workshop on Teaching Introductory Statistics Session 2b: Planning the Use of Activities Roger Woodard, North Carolina State University Ginger Holmes Rowell,

Contributed Paper C312 ( July 4th 10:30-12:30) ICOTS-7,Salvador,Brazil, July Assessment of the Pedagogical Utilization of the Statistics Online Computational.

Finding Internet Resources for Teaching Statistics Using CAUSEweb Ginger Holmes Rowell, Ph. D. Middle Tennessee State University Roundtable Luncheon August.

Delivering your blended course Richard Walker E-Learning Development Team University of York Preparing, supporting & evaluating student learning.

1 An Application of the Action Research Model for Assessment Preliminary Report JSM, San Francisco August 5, 2003 Tracy Goodson-Espy, University of AL,

Sample an AIMS activity: What Makes the Standard Deviation Larger or Smaller (NSF DUE ) Bob delMas, Joan Garfield, and Andy Zieffler University.

Review of Econ424 Fall –open book –understand the concepts –use them in real examples –Dec. 14, 8am-12pm, Plant Sciences 1129 –Vote Option 1(2)

Using a Digital Library to Teach Statistics ICTCM, March 2006.

Stats for Engineers Lecture 9. Summary From Last Time Confidence Intervals for the mean t-tables Q Student t-distribution.

STAT 203 Elementary Statistical Methods. Review of Basic Concepts Population and Samples Variables and Data Data Representation (Frequency Distn Tables,

Institute for Statistics and Econometrics Economics Department Humboldt University of Berlin Spandauer Straße Berlin Germany CONNECTED TEACHING.

Probability and Statistics Required!. 2 Review Outline  Connection to simulation.  Concepts to review.  Assess your understanding.  Addressing knowledge.

Using Activity- and Web-Based Materials in Post-Calculus Probability and Statistics Courses Allan Rossman (and Beth Chance) Cal Poly – San Luis Obispo.

Some On-Line Applets and How They Can Be Used Dr. Bruce Dunham Department of Statistics.

NSF DUE /15/2002 Collaborative Research: Adaptation & Implementation of Activity & Web-Based Materials Into Post-Calculus Introductory Probability.

Overview of the LEMMA VLE Jon Rasbash, 2008 Centre for Multilevel Modelling.

Copyright © 2005, SAS Institute Inc. All rights reserved. Interactive Demonstrations of Statistical Concepts Using JMP TM Mark Bailey Statistical Services.

Seattle, Washington July6-10 Session Joint Statistical Meetings 1 Pedagogical Utilization and Assessment of the Statistics Online Computational.

Utilizing a Digital Library to Teach Introductory Statistics Joint Fall Conference, TMTA and MTMT.

Introduction to Correlation and Regression Introduction to Correlation and Regression Rahul Jain.

Lecture 2 Basics of probability in statistical simulation and stochastic programming Leonidas Sakalauskas Institute of Mathematics and Informatics Vilnius,

STATISTICAL ANALYSIS FOR THE MATHEMATICALLY-CHALLENGED Associate Professor Phua Kai Lit School of Medicine & Health Sciences Monash University (Sunway.

Experimental Research Methods in Language Learning Chapter 10 Inferential Statistics.

RESEARCH – DOING AND ANALYSING Gavin Coney Thomson Reuters May 2009.

Course Outline Presentation Reference Course Outline for MTS-202 (Statistical Inference) Fall-2009 Dated: 27 th August 2009 Course Supervisor(s): Mr. Ahmed.

Remember You just invented a “magic math pill” that will increase test scores. On the day of the first test you give the pill to 4 subjects. When these.

ReCap Part II (Chapters 5,6,7) Data equations summarize pattern in data as a series of parameters (means, slopes). Frequency distributions, a key concept.

Beginning Statistics Table of Contents HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems, Inc.

Stats Term Test 4 Solutions. c) d) An alternative solution is to use the probability mass function and.

Jump to first page Inferring Sample Findings to the Population and Testing for Differences.

Green Belt – SIX SIGMA OPERATIONAL Central Limit Theorem.

Workshop on Teaching Introductory Statistics Sessions 6 & 7: Using Technology in the Classroom, Parts I & II Roger Woodard, North Carolina State University.

Data Summary Data Analyses Air Ozone Pollution (Smog) SOCR Activity: A Case Study of California Ozone Pollution The aims of this activity are to:  Describe.

Statistics and probability Dr. Khaled Ismael Almghari Phone No:

Covariance/ Correlation

Why is this important? Requirement Understand research articles

Chapter 13 Nonlinear and Multiple Regression

Review This template can be used as a starter file for presenting training materials in a group setting. Sections Right-click on a slide to add sections.

ISSCM 491 Managerial Statistics

Evidence-based Best Practices for Blended Course Design

Covariance/ Correlation

Covariance/ Correlation

Distance Learning Statistics (e-learning)

Centre for Multilevel Modelling, University of Bristol

Central Limit Theorem A Demonstration of SOCR

Addressing the Assessing Challenge with the ASSISTment System

ON TEACHING STATISTICS IN E-LEARNING ENVIRONMENTS

Covariance/ Correlation

Erwin van Vliet, Natasa Brouwer

Presentation transcript:

Technology-Enhanced Mathematics and Statistics Education Ivo D. Dinov & Nicolas Christou Ivo D. Dinov & Nicolas Christou It’s Online, Therefore It Exists!

Outline 1)What is SOCR? 2)Webapps: Distributions, Experiments, Analyses, Games, Modeler, Graphs 3)Multilingual instructional resources: EBooks, Continuing Ed workshops 4)Learning activities: interactive, data-driven and technology-enhanced 5)Examples:  Central Limit Theorem  Hands-on California Ozone Data Activity  Polynomial Model Fitting  Stochastic estimation of transcendental numbers:  Natural number e and π  Hands-on Wavelet and Fourier representation and signal denoising 6)Data: Diverse publicly accessible datasets for copy-paste/download utilization – e.g., Latin Letters Frequency Distribution 7)Dissemination: papers, conferences, workshops, etc.

What is SOCR?

Core SOCR Resources Tools & Activities wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials Virtual Demos Concepts & Methods Data Infrastructure

Distributions FEATURES 70+ Distributions Graphs PDFs CDFs Inverse CDFs Moments FEATURES 70+ Distributions Graphs PDFs CDFs Inverse CDFs Moments

Experiments FEATURES 80+ Experiments Simulations Summary Stats Model vs. Sample FEATURES 80+ Experiments Simulations Summary Stats Model vs. Sample

Experiments - CLT Dinov, et al., JSE 2008

SOCR Charts FEATURES 70+ Dynamic Interactive Graphs Summary Stats GUIs Web Interface Based on JFreeCharts FEATURES 70+ Dynamic Interactive Graphs Summary Stats GUIs Web Interface Based on JFreeCharts

SOCR Analyses FEATURES Param+NonParam Graphs Summary Stats R Interface GUIs Web Interface FEATURES Param+NonParam Graphs Summary Stats R Interface GUIs Web Interface ANOVA - One Way ANOVA - Two Way  2 Model Goodness-of-Fit Test Multiple Regression Analysis One Sample T Test Simple Regression Analysis Two Independent Sample T Test Two Independent Sample Wilcoxon Rank Sum Test Two Paired Sample Sign-Test Two Paired Sample Signed-Rank Test (Wilcoxon) Two Paired Sample T Test … RESULT: Sample size=19 INDEPENDENT = Group DEPENDENT = Dependent DF Model = 2 DF Error = 16 DF Corrected Total = 18 RSS MODEL = RSS ERROR = RSS TOTAL = MSS MODEL = MSS ERROR = F-VALUE = P-VALUE = E-10

Central Limit Theorem

California Ozone Data Activity

Polynomial Model Fitting

Transcendental Number Estimation e and π

Wavelet & Fourier Representation & Signal Denoising

Data Example: Latin Letters Frequency Distribution

Future Research & Development New tools under development Additional SOCR Wiki activities Annual SOCR Workshops Evaluation SOCR usage:

SOCR Curricular Assessment Conducted several IRB-approved studies of SOCR- blended instruction, compared to controls, quantifying the efficacy of the applets, materials and IT-enhanced curricular training in undergrad courses. Christou, N and Dinov, ID (2010) A Study of Students’ Learning Styles, Discipline Attitudes and Knowledge Acquisition in Technology-Enhanced Probability and Statistics Education, JOLT, 6(3), Dinov, ID, Sanchez, J, and Christou, N (2008) Pedagogical Utilization and Assessment of the Statistic Online Computational Resource in Introductory Probability and Statistics Courses, JC&E, 50, 284–300. Christou, N, Sanchez, J and Dinov, I. (2007) Design and Evaluation of SOCR Tools for Simulation in Undergraduate Probability and Statistics Courses. Proceedings ISI, Lisbon, Portugal, August 2007.

Session Evaluation/Feedback Provide Anonymous Feedback Online

Acknowledgments Funded by NSF DUE Collaborators I. D. Dinov, N. Christou, R. Gould J. Cui, A. Che, R. Gidwani