AUGUST 2015
JONES SOFTWARE AND “ILIKEMATH” YIELD SIGNIFICANT RESULTS
Executive Summary
Dr. Dana Dodson Mathematics Education Indiana University, Northwest Dr. Rochelle Brock Executive Director, Urban Teacher Education Program Indiana University, Northwest
ESSA: AN OPPORTUNITY FOR AMERICAN EDUCATION THE PASSAGE OF THE EVERY STUDENT SUCCEEDS ACT (ESSA)...
2017 iLikeMath Press Compiled by Dr. Rochelle Brock | Reproducible
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Every Student Succeed Act (ESSA) is the law that guides schools requirements for scholars’ success perimeters. The law requires: movement toward equity for disadvantaged and high-need scholars, all scholars to be taught with high academic standards as preparation for college and career success, education and support communities receive important information from annual assessments that measure scholars’ progress toward high standards, assistance to support and grow local innovations developed by local leaders, and action for positive change and accountability in lowest-performing school and students not making progress (cite ESSA website).
COMMON CORE STANDARDS THE COMMON CORE STATE STANDARDS (CCSS) EXPECT STUDENTS TO FLUENTLY KNOW THE SUMS OF SINGLE DIGIT NUMBERS BY THE END OF GRADE 2 AND THE PRODUCTS OF SINGLE DIGIT NUMBERS BY THE END OF GRADE 3. BY THE END OF FOURTH GRADE, STUDENTS ARE EXPECTED TO FLUENTLY ADD AND SUBTRACT MULTI-DIGIT WHOLE NUMBERS AND BY THE END OF FIFTH GRADE STUDENTS ARE EXPECTED TO MULTIPLY MULTI-DIGIT WHOLE NUMBERS. YET STUDENTS CONTINUE TO STRUGGLE THROUGH MIDDLE SCHOOL, HIGH SCHOOL AND COLLEGE COURSES BECAUSE THEY HAVE FAILED TO FLUENTLY LEARN THEIR ADDITION, SUBTRACTION, AND MULTIPLICATION AND DIVISION FACTS. THIS IS NOT AN EASY TASK. AFTER THE FACTS HAVE BEEN DISCOVERED, CONCEPTUALIZED AND APPLIED, THEY MUST BE MEMORIZED AND RETAINED FOR FLUENT AND IMMEDIATE USE. MANY STUDENTS FALL SHORT OF THE “FLUENCY” GOAL (CARON, 2007). ROBERT GAGNE (1983) RECOGNIZED THE NEED FOR FLUENCY AND EMPHASIZED THAT THE PROCESSES OF COMPUTATION THAT UNDERLIE ALL PROBLEM SOLVING MUST BE “NOT JUST LEARNED, NOT JUST MASTERED, BUT AUTOMATIZED.” (PG. 18) IN THIS STUDY AND IN AGREEMENT WITH THE WORK OF R. OLDRIEVE (N.D.), “FLUENCY” IS DEFINED AS THE COMBINATION OF COMPUTATIONAL RATE AND ACCURACY. STUDENTS WITHOUT MULTIPLICATIONFACT FLUENCY SPEND MORE TIME DETERMINING ROUTINE ANSWERS AND LESS TIME ON MORE MEANINGFUL APPLICATIONS. STUDENTS WHO KNOW THEIR FACTS BUILD ON THESE FUNDAMENTAL CONCEPTS, ULTIMATELY BENEFITING THEIR SUBSEQUENT MATHEMATICAL DEVELOPMENT (WALLACE AND GURGANUS, 2005)..
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FLUENCY IN THE MATHEMATICS STANDARDS CONT Students with learning disabilities (LD) struggle developing number sense (Robinson, Menchetti, & Torgesen, 2002), have poor long-term memory, and are often tactile learners (Learning Disabilities Association of America, 2004). To compensate for their weaknesses, teachers provide helpful multi-sensory aids and strategies to compute answers, including finger counting, foot tapping, number lines, or picture drawing. Although these supports are helpful, additional instructional strategies are needed to help students with LD become fluent with basic computation.
Predicators of Success Richard Oldrieve (n.d.) studied the mathematical computational fluency on urban and suburban 2nd and 3rd grade students with a 42 two-digit by two-digit addition problems worksheet. The urban students were from an economically depressed section of a city whose school district was comprised of 71% African Americans. The suburban students were 96% European Americans. Highly significant results appeared in the completion rates of these groups. Urban students mean average time of completion on their worksheet was ~24 minutes which was significantly slower than the suburban students whose mean average completion time was ~8 minutes. The results suggest the urban students had a focus on accuracy with ~30 seconds spent to count out 7+8 in the ones and/or tens column for each and every problem. The suburban students spent ~10 seconds on each problem with no time allotted for counting. Oldrieve concluded in his study that it was possible to teach students accuracy without speed, but students who achieved the combination of speed and accuracy were able to continue improvements in accuracy. An overall correlation was shown that indicated speed accounts for 32% of the variance in accuracy. Oldrieve also found the results of this computational fluency study in the second grade to mirror the 10th grade state mathematics proficiency exams and graduation rates in both the urban and suburban school districts.
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RESEARCH DESCRIPTION
This study employed a quasi-experimental, two group comparison design to evaluate the effects of a computer mathematics facts program. Pre and post-test data were collected from two groups of 18 elementary students over a 12-week period. Setting This study was conducted in an urban elementary school in Northwest Indiana where 97% of students were Black, 1% Multiracial and the remaining 2% White, Hispanic, and Asian. The socioeconomic status of the elementary school was reported by the Indiana Department of Education (2010) as 46% paid lunch, 4% reduced lunch, and 50% free lunch. All data collection took place in the participants’ elementary classroom.
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Research Findings All students scored similarly on the pretest, with a range of scores from 0 to 17 out of a possible 50 in the general education class, with an average score of 4.6 (9.1% correct) and a standard deviation of 5.4. In the special education class, the pretest scores ranged from 0 to 6 with an average score of 2.3 (4.6% correct) and a standard deviation of 1.7. Since the two groups were selected for convenience, at-test was performed on the pretest scores of the two groups. The pretest scores of the two groups were compared using SPSS, which indicated that the variances are not significantly different from each other, supporting the fact that the two groups came from similar populations. Sixteen weeks after treatment, students were administered the same test. Student scores in the general education class post test scores ranged from 5 to 27 and had increased from an average of 4.5 to 14.8 (29.8% correct) with a standard deviation of 7.4. Students in the special education class who received the daily treatment had post test scores range from 13 to 25 and a greater increase in their class average from 2.3 to 18.9 (37.8% correct) with a standard deviation of 3.9. The variances in the two groups remained similar, with the general education students displaying a wider box and whisker plot as compared to the smaller variance and tighter clustered scores in the special education class. By the end of the study, the general education class had improved by an average of 20.7% correct and the special education class had improved by an average of 33.1% correct. 2017 iLikeMath Press Compiled by Dr. Rochelle Brock | Reproducible
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Research FindingsÂ
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