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The Impact of Personalized Learning, Redbird Mathematics, on Student Achievement and their Attitudes towards Mathematical ContentKristen EvansKennesaw State University – ECE 7531AbstractEducation is continually evolving through each generation. Technology is becoming more enhanced and used more consistently in classrooms today. With this being said, our students cannot learn the same way they did 50 years ago. Personalized learning is one approach that is attracting more educators due to its positive impacts on student achievement. This mixed-method study was designed to assess the effects of a personalized learning technology program, Redbird Mathematics, has on student achievement levels and attitudes towards mathematical content. The participants of this study consisted of twenty-four first grade students in a public elementary school. After six weeks of collecting quantitative and qualitative data, the analysis of data proved a defined impact on students’ achievement levels and attitudes in mathematics. TABLE OF CONTENTSChapter 1: Introduction……………………………………………………………………………4 Chapter 2: Review of Literature………………………………………………………….……….6 Chapter 3: Methodology………………………………………………………………………... 18 Chapter 4: Results………………………………………………………………………………..21 Chapter 5: Conclusion……………………………………………………………………………27Appendix…………………………………………………………………………………………29References………………………………………………………………………………………..30CHAPTER 1IntroductionWhat is personalized learning? Many researchers have pondered this same question, and Cavanagh (2014) inserts Susan Pack’s, an executive director of the International Association of K-12 Online Learning, definition as, “Personalized learning in today's schools essentially amounts to the "differentiation" of lessons for students of different skill levels, or efforts to help students move at their own pace” (p.1). Personalized learning is focused on student-centered learning rather than teacher-centered learning, and is becoming more prominently developed in the United States School System. Hanover research (2012) states, “A recent (and presumably ongoing) Department of Education spotlight on personalized learning has firmly established the approach as a pillar of high-quality 21st century learning” (p.4). Why do we need personalized learning in the educational system? Grant and Basye (2014) stated, “Personalized learning is the key to engaging students, as teachers are leading the way toward making learning as relevant, rigorous, and meaningful inside school and outside” (p.1). If our students are engaged in their learning, then they are more likely to succeed in their educational pursuits. Technology is one of the many tools that will enhance our students’ learning opportunities through personalized learning. Many researchers have studied numerous computer-based software programs that will enrich our students learning, and provide them with instruction that can be individually set to their specific academic levels and pace their learning. Personalized learning is said to have a major impact on our classroom. This initiative helps support those academic strategies to address the specific learning needs, interests, or cultural backgrounds of individual learners. As teachers, it is imperative that all of the students in our classroom are receiving instruction that is customized to their distinct learning needs, and the way to do this is through personalized learning. How can I use personalized learning in the classroom? Redbird Advanced Learning offers web-based curriculum in several content areas. One of the content areas is Mathematics, and it was primarily developed for the elementary level. Redbird Mathematics, the focus of this study, is a digital curriculum that was created by Stanford University (2015), and the curriculum “features the latest in adaptive instruction, gamification, and digital project-based learning” and “is designed to meet the requirements of Common Core (Focus, Coherence, and Rigor) and other standards” (p.1).Personalized learning will contribute to my students’ success. Using the technology component will enhance student learning by creating a personalized learning experience. My role as the teacher is to provide instruction to my students through a small group setting, such as guided Math. When they leave the teacher station, my students will use their current knowledge to engage in curriculum on Redbird Mathematics software. Students will also participate in other differentiated activities on a specific math concept or skill. The differentiated activities that the students will take part in will include: math games, flash cards, independent practice in their math journals, and smart board activities. All of the strategies I use to personalize my students learning will assist them with their academic success.The purpose of the study is to determine the impact of individually personalized computer-based instruction, using Redbird Mathematics, on student achievement and their attitudes towards mathematical content. The county has divided its schools up into different cohorts in delivering this successful initiative, and it will be the first year my school will be implementing this way of learning for our students. Research has shown how it can improve the school’s learning as a whole. It is my goal to improve the practice of my teaching and the way I deliver instruction to my students. Personalized learning is very important to student’s learning and is a contributing factor to student success. The following research questions will be addressed in this study:Does personalized learning of computer-based instruction increase student achievement in mathematics?Does personalized learning of computer-based instruction have an effect on the performance of advanced students and on-grade level students?Does personalized learning have an effect on student attitudes toward computer-based instruction in mathematics?CHAPTER 2 Literature ReviewThe Definitions of Personalized LearningPersonalized Learning is custom-made instruction that is adapted to each individual learner and their needs. The US Department of Education (2010) defines personalized learning as, “instruction that is paced to learning needs, tailored to learning preferences, and tailored to the specific interests of different learners. In an environment that is fully personalized, the learning objectives and content as well as the method and pace may all vary” (p. 1). However, many individuals feel there are several beliefs as to what personalized learning truly is. Cavanagh (2014) states, “Over the past few years, a number of education and technology organizations have sought to move beyond generalities to forge a clearer definition of what personalized learning really means” (p. 2). In the article, there are many references to conclude that personalized learning is meeting the academic and language needs of diverse student learners, accommodating the student’s interests to help motivate them, and giving more richer and meaningful experiences to their learning.Personalized learning is an approach to prepare students for their everyday learning and help them to become successful with their learning. Childress and Benson (2014) both state that, “Personalized learning can meet all students where they are, motivate them based on their interests and academic level, accelerate their learning, and prepare them to become true lifelong learners” (p. 34). This type of learning is different from the traditional method, but has proven to be successful. One school system that piloted personalized learning was Summit Public Schools located in San Jose, California. The teachers noticed that their students were able to advance in their math curricula at their own pace and were able to focus their attention where it was needed. Another school who went with the personalized learning approach was Whittemore Park Middle School located in Conway, South Carolina. The teachers were able to carefully plan instruction to meet their students’ needs and make it meaningful. Even though this school was considered a low-performing school, the staff was excited to redesign their way of learning and do what was best for their students, which was personalize learning.Personalized Learning in the ClassroomLearning how to balance personalized learning at both the district level and school level can be a daunting, but a rewarding task. This idea was looked at by two researchers, Donsky and Witherow (2015) to see how it could be successfully implemented. They both came up with the “70:20:10 model for learning and development” (p.36). Personalized learning encompasses just-in-time instruction, which educators will spend 70% of their time learning the experience and inserting it into their daily jobs. The 20% is provided to the mentors and coaches who will interact with educators on a regular basis. The final 10% will be the workshops and conferences the teachers will attend. The goal is personalization by the district to assist in improving student’s academics and well-being, as well as providing support to its staff. Educational leader, Bellavance (2014) believes “Putting students in charge of their own learning is the best way to prepare them for the future” (p. 62). Maine recently passed legislation which states, “Beginning in 2018, high school diplomas must be awarded on the basis of student proficiency” (p. 62). With that being said, teachers must give students multiple opportunities to show their level of proficiency in all subject areas. Many of the teachers worked together and were able to begin reshaping their instruction and assessments to cater to their students’ needs and focus on a “personalized, proficiency based education system” (p. 63). Headden (2013) examined Alliance Tennenbaum Family Technology High School and their approach to learning. The school uses a hybrid model to teach, which simply means both online and traditional instruction, the same as personalized learning. The students were able to work at their own pace, and the teachers were able to guide and inspire students in their learning. In the article, it provided clear evidence on effective personalized learning, which was that the “Department of Education's survey found that success with online learning depended on time spent on instruction, as well as the quality of the curriculum and pedagogy. In other words, it's not just the technology that counts: it's what teachers do with it” (p. 17). Molyneux and Godinho (2012) developed a pilot study that would research the functionality and appropriateness of a scientific literacy web-based program, known as The Venom Patrol, developed for middle years’ students. They also wanted to determine if it engaged students enough to support their learning. Their participants included 114 students (grades five and six) and 5 teachers, which were from three different co-educational schools in Melbourne, Australia. This qualitative case study involved collecting data in the following areas: classroom observations, teacher interviews, online student survey, and student focus group interviews. The researchers observed in all the classroom settings that there was a high degree of interest with the digital resource, students were engaged in higher order thinking activities (e.g. text-to-self connections, identifying main idea and details, and producing presentations) that were involved with the digital resource, and they created extended responses to the digital program’s information. In addition, the teachers were all in agreement during their interviews that there was a high level engagement among the students with this digital resource. The researchers also concluded that the majority of students viewed the program as a positive one. Further research is determined to be conducted on this web-based program to develop its impact on student learning through scientific literacy. Blackwell, Lauricella, and Wartella (2015) studied the factors that contribute to early childhood educators’ technology use within the classroom. They hypothesized that teachers who have increased support, a predetermined technology policy, teach lower socioeconomic status students, and have less teaching experience will have better attitudes and motivation towards using technology. Their participants included experienced teachers who taught children from age 0-4 years from three different childcare centers. The researchers conducted a survey with the early childhood educators, which developed their responses to the following categories: access to and use of technologies, attitude towards technology, and their supposed levels of support. They were able to direct a path analysis to conclude the relationship barriers between technology integration with early childhood teachers. The single order barriers, support, technology policy, student SES, and teaching experience, they hypothesized did have both positive direct and negative indirect effects on their influence with technology. Inclusive, early childhood teachers say that they still need heavy support with new technology inventions, which is believed to increase attitudes and motivations towards the use of technology.Currently, there are teachers who still believe in the traditional approach to teaching instead of newly developed models. For example, some educators are set in their ways and provide Direct Instruction all day to their students. Skarr, Zielinski, Ruwe, Sharp, Williams, & McLaughlin (2014) researched the use of Direct Instruction through flash cards to teach math facts. The study was to see if this approach would increase their levels of accuracy and fluency on multiplication facts. The researchers examined the effects of Direct Instruction on the following participants: a third-grade boy, fifth-grade girl and a boy with learning disabilities. By the end of the study, the participants did master their multiplication facts and their levels of confidence did increase. The Benefits of Personalized LearningResearch is continually being conducted, and with that being said many theorists have a differing view on Direct Instruction compared to the previous article. The implementation of personalized learning has been the discussion amongst many researchers because they have found significant gains made by students within their test scores, motivational levels, and knowledge of skill. Ku, Harter, Liu, Thompson, and Cheng (2007) researched the effects of an individual personalized computer-based instructional program on solving mathematical problems. They conducted the experiment in a middle school with 104 students in sixth through eighth grades. Ku, Harter, Liu, Thompson, and Cheng used a survey to determine the students’ likes, and a pre-test to define their knowledge on multiplication math facts and multi-step word problems. The students were separated into two groups: personalized computer-based instructional program and non-personalized computer-based instructional program. Results revealed there were significant gains for the personalized group in both math facts and solving word problems. A second set of theorists researched the impact of personalized learning with a computer-based program, but with elementary school math. Kiriakidis and Geer (2014) researched the computer-based program, Success Maker, and its effect on student achievement in math. The researchers stated, “Success Maker is used to help (a) students improve their math skills and (b) math teachers with standard-based assessments of students’ computational fluency” (p. 131). Data was collected from two elementary schools. Cohort 1 School used Success Maker in their classroom and Cohort 2 School did not use Success Maker in their classroom. Findings did reveal that by using this software student proficiency levels in math did increase per state tests.Schaaf (2012) examined digital game-based learning in regards to students’ on task behavior and engagement. He wanted to understand if students were more engaged with digital game-based learning or alternative instructional strategies. The participants included students in grades 3 through 5 from Clarkesville Elementary School located in Clarkesville, Maryland. Schaff (2012) chose this set of participants because he states they are more mature at this age and will understand the vocabulary presented to them through data collection. The researcher created an experimental groups which received digital game-based learning strategies and a control group that received alternative learning strategies. Both the experimental and control groups had onsite observations that would witness time-on-task behavior and student groups were chosen at random by the observers to participate in attitudinal surveys. As data was collected from both groups and analyzed, results prove that student engagement is much higher with digital game-based learning in comparison to alternative learning strategies.The Challenges of Personalized LearningWith successes, there are also challenges that can be faced with the implementation of a new strategy. Faculty researchers from Australia completed a study on personalized learning and its improvement on students’ academic performance. They completed this study in a low socio-economic area of Australia in secondary schools. It was determined by a survey that these secondary schools did see “…some or considerable impact on student attainment or engagement” (p. 659). Many staff members of the school, however, felt the student engagement piece of personalized learning was based on opinion rather than from quantitative measurement. Research also states, “…ongoing challenges in conceptualizing and implementing a personalized learning approach” (p. 660). Another negative association to personalized learning and its technology component is the effect of some online math games and its impact on student’s academic performance. Zhang (2015) researched the google search engine and its search volume for “…three search terms cool math, cool math games and math games” (p. 258) among the vast Internet users in the United States. He found that these math websites have an adverse impact on students’ academic performance, limited criteria in effective instruction, and its inability to match itself to the curriculum’s learning goals. Personalized Learning and its Impacts on Student LearningConversely, one district chose to incorporate a personalized learning program within their schools and notable findings were discussed. Davis (2014) completed his research on a sixth grade math teacher at Whittemore Park Middle School who noticed his students’ scores from the math software on the iPads and MacBooks were not showing levels of improvement because the lack of seriousness from his students. The teacher chose to publicly hang his students’ progress on the back wall of his classroom. This plan of action was going to hold the students accountable and help them to be motivated in making goals towards their progress within the program. Whittemore Park Middle School found that personalized learning has transformed their instruction, which in turn is “…boosting test scores, student engagement, and teacher attendance” (p.1). The school also made meaningful impacts with its teachers because they provided professional development on the electronic devices. One of the teachers interviewed expressed, "What has been a huge benefit is getting those devices in the hands of the teachers prior to issuing them to students and doing a lot of heavy professional development before teachers felt the stress of the kids having the devices in the classrooms, said Ms. Cox” (p.4). Personalized learning made a huge impact on Whittemore Park Middle School and they are now able to focus on the students’ needs first. A recent case study on personalized learning in a digital environment was examined by Districts’ administrators (2014) of Seattle’s Federal Way Public Schools. They wanted to incorporate as much technology into their instruction as possible. With district goals and Common Core State Standards, they understand that an initiative needs to be put into place to help their students become proficient in math. District administrators (2014) found a tool to help support personalized learning in their schools and it is DreamBox Learning. This software “…offers a personalized K8 math environment that combines a rigorous curriculum for deep conceptual understanding, a highly engaging game-like environment, and industry-leading Intelligent Adaptive Learning? technology which dynamically adapts in real time to create millions of personalized learning paths tailored to each student’s unique needs” (p.15). Teachers are able to use the results from the digital program and determine which students’ have mastered specific skills and the ones who need face-to-face instruction on a specific concept. The program also helps the teachers adapt their instruction based on the data they receive from DreamBox Learning. Additionally, the study explains that students are motivated and excited to learn with the use of this digital tool.Walkington, Sherman and Howell (2014) stated, “Research has shown that personalization makes key ideas in algebra more understandable” (p. 274). Through their research of personalized learning, the researchers determined that this approach to learning ensures two effects: “…personalized problems can elicit students’ interest…” (p. 275) and “…personalizing problems can provide a critical bridge between what students already know and understand and formal concepts of algebra” (p.275). Before instruction started, students’ interests were surveyed and results were conveyed to the teachers so the learning of algebraic problems could be personalized. The following topics were gathered from students’ out-of-school interests: sports, part-time jobs, after school activities, video games, social networking, cell phones, and other digital media. The high school teachers used their students’ interests to group the students, which began the process of implementing personalized learning in the classroom. In summary, personalized learning is to “…help students meet the Common Core Standards (2010) by allowing them to reason abstractly while contextualizing and decontextualizing mathematical ideas and to model situations with mathematics and by providing support for making sense of problems and persevering. Personalization can also provide scaffolding for students who struggle by making the content meaningful and allowing for differentiated instruction” (p. 279).Ramani and Eason (2015) both believe “Play and games can give young children opportunities to learn and develop foundational math skills that are aligned with Common Core standards” (p. 27). As stated in the article above, the more we, as teachers, use our students’ interests to plan our instruction, the more engaged our students will be in their learning. In order for teachers to personalize their students learning, several recommendations were given in this article and they include: “seeking out play curricula, thinking outside the (game) box, what happens in math class… does not have to stay in math class, peers are a valuable resource, engage parents, and make connections between home and school” (p. 32). Preschoolers from a Head Start program were examined through play using a linear number board game. The children were instructed how to play the game correctly. The experiment was conducted over a two-week period and the children played the game for four 15-20 minute sessions. The researchers made note that the children made significant improvements with their mathematical knowledge when the recommendations were put into action. Meluso, Zheng, Spires and Lester (2012) explored the study of science content and science self-efficacy through game-based learning. The article states that academic self-efficacy “…impacts students’ choice of learning activities and the amount of effort they attribute to learning both in the classroom and while playing educational video games” (Mikropolous & Natsis, 2011, p.498). The participants in this study included a final total of 66 fifth grade students from a magnet school located in Southeastern United States. First, the students were exposed to science curriculum on landforms based on their current science standards. Next, the students were given the opportunity to play an online, narrated computer game, known as Crystal Island, where they explored the islands’ features and communicated with other characters to learn about science related concepts. Students were randomly assigned in this study to either single player or collaborative playing conditions. They were assessed through pre and post-test assessments, which measured their science self-efficacy and content knowledge. After data was collected over a four day study and analyzed, it was determined that there were no differences in science self-efficacy between males and females. Additionally, the students’ results did not differ in science content knowledge based on the assessments. Whether students are playing independently or in a group, the research states that this online game is a huge benefit to any fifth grade classroom.Delacruz (2014) researched using the Nearpod application in guided reading groups, and its effectiveness and challenges within the guided reading group setting. She wanted to determine if students preferred using an iPad to read during guided reading or to read from a traditional book. The participants included 9 fourth grade students and 1 student teacher from a suburban school located in Southeastern United States. The school consists of a wide range of diverse learners, with the study representing 4 out of 9 of its participants being English Language Learners (ELL’s). The student teacher chose to select her lowest and highest guided reading groups to partake in this study. This study used qualitative research methods to collect data in the following areas: student video journal interviews, work samples from the Nearpod app, and a student teacher interview. All of the students noted that they preferred reading on an iPad rather than from a traditional book. The student teacher believed that the students were actively engaged in their learning, and her students felt comfortable in reading and participating in quizzes on the Nearpod app. She also noted another benefit of using the Nearpod app during guided reading, which was the collection and distribution of quiz results was time effective. However, there are some challenges that were prominent with the Nearpod app, which were the nonexistent text-to-speech option, no dictionary or highlighting tools, and the inconsistent closing of the application on a student’s iPad. Researchers felt that the benefits outweighed the challenges because the student teacher concluded that she would be integrating the app within other subject areas, such as Math Science, and Writing, and possibly sharing her lessons globally with everyone. Evans (2013), the CEO of The Speak Up National Research Project, conducted an online survey, and over 400,000 student responses were submitted. Using the results from the online survey, she determined, “They are the technology trendsetters in terms of how they want to use technology in and out of school” (p.14). Evans (2013) also asked administrators and parents of elementary schools to give their opinions on the use of technology during instruction. She confirmed that both of these groups feel the integration of technology is extremely important in the classroom. After interviewing several elementary school principals, she learned that they want “…adaptive learning software, e-textbooks, and digital content as means of increasing engagement and learning for their students” (p. 15). Lastly, she found many educators want “…to use games, most elementary instructors said they would use games as motivational and engagement tools, as well as for learning differentiation” (p. 15).In conclusion, personalized learning is increasingly being implemented across classrooms in grades elementary, middle and high school. This specific approach can be used across all curriculums, such as math, reading, science and social studies. Many researchers have agreed that personalized learning has resulted in students making significant gains in the content being taught. However, there are several challenges that have been discussed among educators on personalized learning, and they feel that there was limited professional development of this new strategy and student engagement was based on teachers’ opinions rather than specific measures. Attention to the following question has been thought out for possible research: What are the effects of personalized learning, using Redbird Software, on student achievement in math? As a newly developed initiative, surveys of students’ interests and pre-tests of beginning academic levels will be completed to examine the overall, beginning of the year data of my students and further assessments will be completed using the computer-based software. CHAPTER 3MethodologyResearch ContextThe elementary school is located in a residential suburb south of the central city in the southeastern United States. It is a public school open to students from grades Pre-Kindergarten through Fifth grade. The current total population of students is 738. The school enrollment consists of many ethnicities, with a majority of African-American students. The current ethnicities enrolled include 91% African-American, 1% Caucasian, 5% Hispanic, 1% Asian, and 2% Multi-Racial.In August 2002, the school opened its doors. Since this time, the school has had a high number of students receiving free and reduced lunch. The current approximation of students receiving free and reduced lunch is about 84%. Many students come from households earning a median income of $35,125. The 2011 Census report informed the school (?) that many, almost 25% of its residents, live below the poverty level. With that being said, the school has many students coming and leaving the school for various reasons, which gives it a high mobility rate of 39%. The teachers are divided into the following categories: 35 general education, 12 special education and 18 support. The administrative team involves the principal, assistant principal, curriculum support teacher (CST), data support specialist (DSS), instructional support team (IST), and guidance counselor. Last school year (2014-2015), there was a change in administration involving a new assistant principal, curriculum support specialist, instructional support team, and guidance counselor; as well as, a third of its teachers resigned, transferred, or retired.ParticipantsThe investigation directed a first grade class of twenty-four participants ranging from six to seven years old. The subjects in this classroom are classified as learning on grade level in mathematics. There are 12 students who were tested at the end of last school year, 2014-2015, and were deemed as Accelerated in both Reading and English Language Arts. These twelve students plus an additional two receive Talented and Gifted (TAG) services one day a week. However, one of the participants in this class is categorized under the Special Education spectrum and has an Individualized Educational Plan (IEP) for both Reading and Math. This student is pulled out for Interrelated Resource (IRR) services during Reading and Math instruction. The individual’s involvement remained absent in the study and did not affect the classroom community’s overall number. Additionally, one of the students is in transition mode from Tier 3 to Tier 4 of the Response to Intervention (RTI) process for behavior. Last school year, 2014-2015, the student was diagnosed with Attention-Deficit-Hyperactivity-Disorder (ADHD) and Obsessive Compulsive Disorder (OCD). The student is on an individual, weekly behavior contract and receives student support daily from the RTI coordinator. Fifteen of the students are male and nine of the students are female. The ethnicity of the subjects are 95% African-American and 5% Hispanic. This first grade class was composed by the administrative team based on their end of benchmark results from last school year. Even though this study is a combination of on grade level and accelerated subjects, it is a diverse and mixed abilities group. InterventionRedbird Mathematics is a computer-based instructional program that is an intervention to bring about favorable outcomes. The goal in mind is for students to have the opportunity to receive whole group math instruction, small group math instruction, and personalized learning through Redbird Mathematics. With the additional approach of personalized learning and the computer-based instructional program, desired results are anticipated to be attained in students’ achievement and attitudes. Data Collection Tools and ProceduresThe participants in this study were questioned for their input in a self-assessment survey (see Appendix A). Students were individually probed a multitude of questions, which were related to their personal attitudes towards mathematics. This process provides an understanding to the students’ outlooks on mathematics and their perceptions towards learning in school. There are two pre-assessment tools that will be used to understand the students’ knowledge of mathematical content. STAR Math is an assessment tool that was taken at the beginning of the school year to assess students’ achievement levels in mathematics. These benchmark scores provide educators with two imperative scores: grade equivalency scores and scale scores. Another assessment tool that was administered to the participants was the Redbird Mathematics pre-test. It is a ten question test that assesses students’ current ability level in mathematics. After the pre-test was completed, the students began their learning on the computer-based instructional program at their current academic level in math. Each day, students are instructed for 10-15 minutes in a whole group mini-lesson on mathematical concept(s). After the mini-lesson, the students transition into small group math rotations, which include: Math Facts, At Your Seat, Teacher Station, and Hands-On. The students visit two small group math rotations each day for two 20 minute segments. The mathematical concept(s) that was taught in the mini-lesson is supported in the Teacher Station. The students will be utilizing digital devices in the Hands-On station, which is where they will log into their Redbird Mathematics’ accounts to begin their personalized learning at their current independent academic levels in math. The other stations, Math Facts and At Your Seat, include independent work for students to complete during their math rotations. The students are rotating through the four rotations every two days, which means they will only rotate to two stations a day. Therefore, the intervention implemented with personalized learning on the Redbird Mathematics software will be conducted by all students twice a week for approximately 20 minutes per time. The students will be reassessed using the STAR Math benchmark assessment in the middle of the year, January, and the end of the year, May. The mid-year benchmark data results will be collected to understand the effect on student achievement using the technology component of personalized learning. The end of the year benchmark assessment will be considered as post-test data to students overall achievement levels. In addition, the participants will be surveyed again at the conclusion of the study to assess on their personal attitudes towards mathematics. CHAPTER 4ResultsAnalyzing and Interpreting DataThe research design conducted for this study was mixed methods. The qualitative data components included: individual interviews and existing test documents. The components used for quantitative data included: Redbird Mathematics pre-assessment, STAR Math benchmark assessments, and a survey. The purpose of collecting the qualitative data at the beginning of the study is to understand and analyze the students’ achievement levels before the intervention of personalized learning is put into action. Moreover, the effects of student achievement and attitude will be explained in further detail after quantitative data is collected and analyzed at the end of the study. Qualitative DataI interviewed all my students before the collection of data began to better understand my students’ attitudes towards mathematics. Most of the students seemed to like math; however, there opinions on math worksheets were negative. As I collected the data, I started journaling once a week to observe if my students’ attitudes towards the math software, Redbird Mathematics, were engaging or non-engaging. Below you will see a wordle document (Figure 1.1), which is a collection of words, that I journaled to describe my students as I observed them on the devices with the Redbird Mathematics program.Figure 1.1right1143000The words above show my students eagerness to learn mathematics with the use of Redbird Mathematics. I also displayed in a chart below (Figure 1.2) that shows my students who were engaged and not-engaged each week during my journaling. Within this chart, about 83% of my students were actively engaged each week with the Redbird software. However, there were about 4 students who were not engaged and did have difficulty with the Redbird software. These students’ challenges included: logging on to the program, understanding how to use the program, and using a device correctly. Figure 1.2WeekMath GroupEngaged in Redbird Mathematics (E)Not Engaged in Redbird Mathematics (NE)February 19, 2016Group 3E (6 students)Group 4E (6 students)February 26, 2016Group 1E (4 students)NE (2 students)Group 2E (5 students)NE (1 student)February 29, 2016Group 3E (6 students)Group 4E (5 students)NE (1 student)March 7, 2016Group 1E (6 students)Group 2E (6 students)March 15, 2016Group 3E (6 students)Group 4E (5 students)NE (1 student)March 21, 2016Group 1E (4 students)NE (2 students)Group 2E (6 students)Quantitative DataRedbird Mathematics had each student take a ten question pre-assessment to determine their current ability level in math. The chart below (Figure 1.3) displays each student’s ability level based on Redbird Mathematics from the beginning pre-assessment in comparison to their current level of learning. The ability levels are calculated by their grade equivalence. Each student has to receive 100 points before they are moved on to the next grade level of instruction. As you can see from the chart below, some students have only made small gains where some students have gained almost half of the points on their ability level. Student #3 is my Special Education student who receives pullout services during math instruction; however, he is able to access Redbird and complete lessons at a Kindergarten level. Student #23 surprised me by receiving a Kindergarten ability level due to her high scores on both STAR Math benchmark tests. Figure 1.3StudentBeginning Ability Level(Grade Equivalency)Current Ability Level(Grade Equivalency)122.07222.053*K--411.16511.23611.07722.09822.02922.051011.201111.521211.251322.431422.161522.271611.201711.3618KK1922.022011.092122.072222.0923K--2411.07I have also included my students’ test scores from the beginning of the year and middle of the year on the STAR Math test. My students took this test at the beginning of the year before they were introduced to the Redbird Mathematics program. In comparison, they took the STAR Math benchmark test again for midyear data collection, which the results are in line with the use of Redbird Mathematics. The graph (Figure 1.4) compares their scores at the beginning of the school year to current. As you can see, 21 of my students’ scale scores increased from the beginning to now. My student #23 was not here at the beginning of the school year, so she has no comparative data to show. My students #12 and #15 indicated a slight decline in their scale scores from the beginning of the year’s test to the current results. left28448000Figure 1.4In addition, I have comprised my students’ grade percentages on their Math Unit pre and post-tests into a graph (Figure 1.5). The Math Unit pre-test was taken prior to the collection of data for Redbird Mathematics. The post-test for this Math Unit was given last week, which was the end of my data collection and end of the unit. Student #3 is a Special Education student, which he is exempt from taking pre and post tests on his grade level. The remaining 23 students achieved high scores on their post-test. They scored an 80% or above on the Math Unit post test, which correlates to them meeting and exceeding the standards for this unit. Figure 1.5CHAPTER 5ConclusionThe purpose of the study was to determine the effect of student achievement and their attitudes towards mathematical content with personalized instruction, using Redbird Mathematics. After 6 weeks, I was able to analyze my collection of data and determine the influence that the technology component had on my students. My students’ achievement levels in mathematical content were significantly impacted on the STAR Math benchmark test and Math Unit Post Test. These students made meaningful strides from the pre assessment to the post assessment. Even though, two out of twenty-four students did not show gains on the benchmark test their Math Unit Post Test and ability level on Redbird proved differently. As well as, my Special Education child was able to show slight improvement on his benchmark results from the beginning of the year to current. As there are always negative effects to any research, the only limitations I noted were: the inconsistency of Wi-Fi connection and student difficulty with logging into the Redbird Mathematics website. Despite the fact that these restrictions were prominent they did not have any adverse effect on my students’ achievement levels. I feel that their attitudes towards mathematics were not affected due to the engaging mathematical instruction they were receiving through Redbird. Overall, I believe that Redbird Mathematics provided each of my students with both rigorous instruction and individualized pacing, which aided them in refining their ability levels and attitudes towards mathematical content. Appendix AReferencesBellavance, M. (2014). Personalized learning Maine style. Educational Leadership, 71, 62-65. Retrieved from , C.K., Lauricella, A.R., & Wartella, E. (2014). Factors influencing digital technology use in early childhood education. Computers & Education, 77, 82-90. doi:10.1016/pedu.2014.04.013Cavanagh, S. (2014). What?is personalized?learning? Educators seek clarity. Editorial Projects in Education, Inc., 34. Retrieved from , S. & Benson, S. (2014). Personalized learning for every student every day. Phi Delta Kappan, 95, 33-38. doi: 10.1177/003172171409500808Davis, M.R. (2014). District's ambitious personalized learning effort shows progress. Editorial Projects in Education, Inc., 34. Retrieved from , S. (2014). Using Nearpod in elementary guided reading groups. TechTrends, 58, 6370. doi: 10.1007/s11528-014-0787-9District Administration. (2014). Math instruction is personalized in a digital environment at Washington district. Professional Media Group LLC, 50, 56. Retrieved from Administration. (2013). The future of personalized learning in elementary schools. Professional Media Group LLC, 49. Retrieved from , D. & Witherow, K (2015). A sense of balance: district aligns?personalized?learning?with school and system goals. Journal of Staff Development, 36, 36-40. Retrieved from , P. & Basye, D. (2014). Personalized learning: a guide for engaging students with technology. International Society for Technology in Education, 1-179. Retrieved from HYPERLINK " oad" oadHanover Research. (2012). Best Practices in Personalized Learning Environments. Caveat, 2-43. Retrieved from HYPERLINK "" , S. (2013). The promise of?personalized?learning: blending the human touch with technological firepower. Education Next, 13, 14. Retrieved from , P. P. & Geer, B. T. (2014). The effect of success maker software on state scores in elementary school math. Romanian Journal of Multidimensional Education, 6, 127-138. Retrieved from , H. Y., Harter, C. A., Liu, P. L., Thompson, L., & Cheng, Y. C. (2007). The e?ects of individually personalized computer-based instructional program on solving mathematics problems. Elsevier Ltd., 23, 1195-1210. doi: 10.1016/j.chb.2004.11.017Meluso, A., Zheng, M., Spires, H.A., & Lester, J. (2012). Enhancing 5th graders’ science content knowledge and self-ef?cacy through game-based earning. Computers & Education, 59, 497-504. Retrieved from , P. & Godinho, S. (2012). This is my thing! Middle years students’ engagement and learning using digital resources. Australasian Journal of Educational Technology, 28, 1466-1486. Retrieved from , V., Cox, P., Deed, C., Dorman, J., Edwards, D., Farrelly, C., Keeffe, M., Lovejoy, V., Mow, L., Sellings, P., Waldrip, B., & Yager, Z. (2013). Personalized learning: lessons to be learnt. British Educational Research Journal, 39, 654-676. doi: 10.1080/01411926.2012.669747Ramani, G. B. & Eason, S. H. (2015). It all adds up: learning early math through play and games. Phi Delta Kappan, 96, 27-32. , R. (2012). Does digital game-based learning improve student time-on-task behavior and engagement in comparison to alternative instructional strategies. Canadian Journal of Action Research, 13, 50-64. Retrieved from , A., Zielinski, K., Ruwe, K., Sharp, H., Williams, R. L., & McLaughlin, T. F. (2014). The effects of direct instruction flashcard and math racetrack procedures on mastery of basic multiplication facts by three elementary school students. Education and Treatment of Young Children, 37, 77-93. Retrieved from University. (2015). Redbird mathematics. Redbird Advanced Learning. Retrieved from . Department of Education National Education Technology Plan. (2010). Learning: engage and empower. Office of Educational Technology. Received from , C., Sherman, M., & Howell, E. (2014). The mathematics teacher. National Council of Teachers of Mathematics, 108, 272-279. doi: 10.5951/mathteacher.108.4.0272Zhang, M. (2015). Understanding the relationships between interest in online math games and academic performance. Journal of Computer Assisted Learning, 31, 254-267. ................
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