Computer in Education Jiaying Zhao CSE 610 Western Oregon University.

Slides:



Advertisements
Similar presentations
Individual, Home, and Community Factors PISA/PIRLS Task Force International Reading Association January 2005.
Advertisements

Brief Overview of Qualitative & Quantitative Research.
Robin L. Donaldson May 5, 2010 Prospectus Defense Florida State University College of Communication and Information.
Latino Students in the Worcester Public Schools March 30, 2010 Miren Uriarte Mauricio Gaston Institute for Latino Community Development and Public Policy.
Figure 1. SAT-9 Reading Percentile Scores from Sample Schools with Mostly Native English-Speaking Students (
Post-Test Data Analysis Workshop. Agenda I. Analyze 2014 TerraNova Results II. Comparative Data Analysis: TerraNova & Explore Test Results III. Using.
Method IntroductionResults Discussion Effects of Plans and Workloads on Academic Performance Mark C. Schroeder University of Nebraska – Lincoln College.
Chapter18 Determining and Interpreting Associations Among Variables.
Faculty Salary Equity Study University of North Carolina at Chapel Hill Faculty Council Report November 1, 2002.
Science Achievement and Student Diversity Okhee Lee School of Education University of Miami National Science Foundation (Grant No. REC )
Chapter 7 Correlational Research Gay, Mills, and Airasian
Computer in Education Jiaying Zhao CSE 610 Western Oregon University.
Stats anxiety! CanCorr example. SA Background Stats Anxiety (SA) experienced by as much as 80% of grad students What is it? –“The apprehension which occurs.
Different Pathways To Offending and Violence: An Examination Of The Differences Among Youths With Varying Histories Of Contact With The Juvenile Justice.
March 2010 what the school readiness data mean for Harford County’s children ©
Implication of Gender and Perception of Self- Competence on Educational Aspiration among Graduates in Taiwan Wan-Chen Hsu and Chia- Hsun Chiang Presenter.
Effect of Incorporating Academic Vocabulary Instruction on Academic Achievement for General and Special Needs Students By Josh Lullmann.
SPSS Series 1: ANOVA and Factorial ANOVA
The Quality of Teacher-Student and Home-School Relationships in Black and White Students in West-Central Wisconsin Paula Hoffert, M.S.E. and Barbara Lozar,
Background RateMyProfessors.com (RMP.com) is a public forum where students rate instructors on several characteristics: Clarity Helpfulness Overall Quality.
Student Engagement Survey Results and Analysis June 2011.
Impact Analyses for VAM Scores The following slides show the relationship of the teacher VAM score with various classroom characteristics The observed.
By Hui Bian Office for Faculty Excellence 1. K-group between-subjects MANOVA with SPSS Factorial between-subjects MANOVA with SPSS How to interpret SPSS.
Growing Up In Ireland Research Conference The Education of 9-Year-Olds.
ACCESS for ELLs® Interpreting the Results Developed by the WIDA Consortium.
CRESST ONR/NETC Meetings, July 2003, v1 1 ONR Advanced Distributed Learning Language Factors in the Assessment of English Language Learners Jamal.
(Capps et al. 2005; Kindler 2002; Karathanos 2009)  The population of English Language Learner (ELL) students in the United States has steadily and markedly.
Ashley Comer Amy Doerfler Lyssa Fisher-Rogers Travis Morris Gloria Pagan EDFN 508 July 8, 2009.
C R E S S T / U C L A Impact of Linguistic Factors in Content-Based Assessment for ELL Students Jamal Abedi UCLA Graduate School of Education & Information.
MEASURES of CORRELATION. CORRELATION basically the test of measurement. Means that two variables tend to vary together The presence of one indicates the.
7th Annual SERU Symposium University of Texas, Austin May 2, 2013 GALE S. STUART, UNIVERSITY OF TEXAS, AUSTIN GREGG E. THOMSON, UNIVERSITY OF CALIFORNIA,
STUDENT AIMS PERFORMANCE IN A PREDOMINANTLY HISPANIC DISTRICT Lance Chebultz Arizona State University 2012.
Locus of Control & Children’s Performance in Schools Jennifer Elias, Don Ghrist, Negar Zivari California State University, Northridge.
How can giving ELL students access to learning games on a computer help them learn in the classroom? By: Lisa Cruz.
Nonparametric Survival Analysis of Undergraduate Engineering Student Dropout Young Kyoung Min 1,3, Guili Zhang 1,4, Russell A. Long 2, Timothy J. Anderson.
Effective Data Sharing Research Project Linking London; Newham Sixth form College.
1 Chen, S. Y., & Fu Y. C. (2009). Internet use and academic achievement: Gender differences in early adolescence. Adolescence, 44(176), _________________________________.
American Educational Research Association Annual Meeting AERA San Diego, CA - April 13-17, 2009 Denise Huang Examining the Relationship between LA's BEST.
The Nation’s Report Card 4th-Grade Reading SOURCE: National Center for Education Statistics, National Assessment of Educational Progress (NAEP),
An exploratory analysis of Latino risk and protective health factors in a community sample Julie Gast, PhD, MSCHES, Terry Peak, MSW, PhD, & Jason J. Leiker,
How can giving ELL students access to learning games on a computer help them learn in the classroom? By: Lisa Cruz.
Statistical Analysis Quantitative research is first and foremost a logical rather than a mathematical (i.e., statistical) operation Statistics represent.
The Correlational Research Strategy Chapter 12. Correlational Research The goal of correlational research is to describe the relationship between variables.
Freshmen On-Track Analysis: Summary of Findings and Implications for Leadership.
Helping ELL Learners Advance To the Next Level: Teaching Through Video Games By: Colleen Hart.
STATISTICS STATISTICS Numerical data. How Do We Make Sense of the Data? descriptively Researchers use statistics for two major purposes: (1) descriptively.
C R E S S T / U C L A Psychometric Issues in the Assessment of English Language Learners Presented at the: CRESST 2002 Annual Conference Research Goes.
Challenges and Opportunities in the First Year of a 1:1 iPad Initiative in a High Poverty, Highly Diverse Urban High School Gayle Y. Thieman, Ed.D. Portland.
Participation of and Accommodations for Students with Disabilities and English Language Learners NAEP State Analysis Project Jenifer Harr María Pérez CCSSO.
Tips and Guidelines. Chapter Four: Results Assessments Questionnaires/SurveysTest Scores/Report Card Data Rationale Why study is needed?What results will.
Evaluation Institute Qatar Comprehensive Educational Assessment (QCEA) 2008 Summary of Results.
Third Grade Vocabulary Instruction Using Repetition and Graphic Organizers Action Research Project Kristen Russell Fall 2008.
Center for Institutional Effectiveness LaMont Rouse, Ph.D. Fall 2015.
Bad Boys and Good Girls? Patterns of Interaction and Response in Whole Class Teaching Myhill, Debra. (2002) Bad Boys and Good Girls? Patterns of Interaction.
2009 Grade 3-8 Math Additional Slides 1. Math Percentage of Students Statewide Scoring at Levels 3 and 4, Grades The percentage of students.
C R E S S T / U C L A UCLA Graduate School of Education & Information Studies Center for the Study of Evaluation National Center for Research on Evaluation,
Method Introduction Results Discussion Mean Negative Cigarette Systoli Previous research has reported that across the nation 29% of college students engage.
LESSON 5 - STATISTICS & RESEARCH STATISTICS – USE OF MATH TO ORGANIZE, SUMMARIZE, AND INTERPRET DATA.
Chronic Absence in Oregon Attendance Works The Children’s Institute The Chalkboard Project ECONorthwest.
SEC–ELL Study Iowa Dept. of Ed. / CCSSO / WCER & Participating States Florida Iowa Minnesota Ohio Utah Virginia Wisconsin Bringing together diverse communities.
Florida Algebra I EOC Value-Added Model June 2013.
AZUREEN BINTI ABD AZIZ RESEARCH PROPOSAL. RESEARCH TITLE Information and communication technology (ICT) practises and skills for learning English The.
Lecture 7 Gender & Age.
Sexual Imagery & Thinking About Sex
2017 TUDA NAEP Results for Miami-Dade
2015 PARCC Results for R.I: Work to do, focus on teaching and learning
Linguistic Predictors of Cultural Identification in Bilinguals
Impact Analyses for VAM Scores
Research concerning intercultural issues
COMPARING VARIABLES OF ORDINAL OR DICHOTOMOUS SCALES: SPEARMAN RANK- ORDER, POINT-BISERIAL, AND BISERIAL CORRELATIONS.
Presentation transcript:

Computer in Education Jiaying Zhao CSE 610 Western Oregon University

Computer games for the math achievement of diverse students As a way to improve student academic performance, educators have begun paying special attention to computer games (Gee, 2005; Oblinger, 2006) This paper examined the effects of playing computer games on math achievement of 4th graders, with special focus on gender and language minority groups. To achieve greater generalizability of the study findings the study utilized a US nationally representative database — the 2005 National Assessment of Educational Progress (NAEP). Kim, S., & Chang, M. (2010). Computer Games for the Math Achievement of Diverse Students. Educational Technology & Society, 13 (3), 224– 232.

Research questions 1. Are computer games in math classes associated with the 4th-grade students’ math performance? 2. How does the relationship differ by linguistic group? 3. How does the association vary by gender? 4. Is there an interaction effect of computer games on linguistic and gender groups? In other words, how does the effect of computer games on linguistic groups vary by gender group?

Some Important finding

Methods The study used the 4th-grade math database of the NAEP 2005 for analyses. A computer game variable, the frequency of computer game use in math class, was the chief predictor variable The two math computer game variables were also used by creating interaction variables with gender and linguistic group variables.

Results It represents descriptive statistics and inter-correlations of all varibles. The correlation results showed all variables had significant relationship with math scores. The students who played computer games sometimes showed high math scores (r=0.031, p<.01), but those who played computer games everyday tended to have low math scores

Results It displays the association between computer game frequency and math achievement for non-ELL students. Overall, the effect of computer games was greater for males than for females.The pattern indicated that when students played math games sometimes, they displayed the highest math performance among the three groups.The second performance group was the students who did not play math games at all and the lowest performance group was the students who played math games everyday.The results highlight the finding indicating that daily math game for non-ELL students was negatively associated with math performance

Results Figure 2 shows the relation between computer game frequency and math achievement for ELL students. The association patterns for ELL students were quite different from those for non-ELL students. The male ELL students demonstrated high math performance when they played math games sometimes or daily, while male students displayed low performance when they never played math games. The female ELL students had the highest math performance when they played math games sometimes, the second highest when they did not play, and the lowest when they played every day

Discussion The study performed an analysis to examine the differential effect of computer games for students of two linguistic groups. Among native English- speaking students, the male students who played math computer games daily performed significantly worse than the students who never played. The study found a gender-based differential effect of computer games on math achievement: the computer game was significantly associated with males’ math achievement, but not with females’ achievement.

Discussion In the third model, English-speaking male students showed low math achievement scores with daily math games, ELL male students demonstrated high performance with daily math games in class. It was interpreted that daily games for English-speaking male students can be a distracting factor for their school engagement, but daily games for ELL male students can be an educational stimulator. The study confirmed the differential effects of math computer games on the academic achievement of diverse students from different linguistic and gender groups, and it suggests that various learner characteristics should be considered when attempting to explore the effects of computer games.