MindPlay Math helps students improve their math skills through an adaptive learning platform that adjusts to each student’s needs as they progress. With MindPlay Math, educators can easily track progress and trust that all grade-level objectives are met, and students will confidently and easily navigate higher levels of math knowledge, building their skills (and confidence!) as they progress through school, year after year.
Support for Struggling Math Students
In fall 2022, almost half of all students (49%) started school performing below grade level in one or more subjects, most commonly in math, according to a recent report from the National Center for Education Statistics (National Center for Education Statistics, 2022).
In order to combat this very pressing problem, educators and parents must consider adopting math intervention programs that are creative, engaging, effective, and that supplement the existing curriculum at all levels of mathematics. Using programs that offer adaptive technology can help students advance through math levels according to their individual skill mastery (Jagušt et al., 2018). This means that programs will adapt as students make progress through various topics and concepts in real time. MindPlay Math reassigns lessons that students did not pass in order to reinforce learning and adapt to the level of the learner. The goal is to keep students engaged without them feeling overwhelmed by the material they’ve already mastered while stimulating growth and improvement.
How Does MindPlay Math Improve Math Skills?
MindPlay Math helps students improve their math skills through an adaptive learning platform that adjusts to each student’s needs so they have the opportunity to master every skill. The supplemental practice also benefits teachers by consistently providing assessments and reporting so they can appropriately adjust instruction based on individual student needs.
MindPlay Math Benefits Include:
- Adaptive technology that understands student responses to align scaffolded support to meet individual needs.
- Standards-aligned lessons that are educator-designed to ensure students are achieving mastery and fluency in the subject.
- Engaged learning in the form of animated videos that draw students’ attention to math vocabulary and allow students to work according to their individual learning needs so they aren’t overwhelmed or bored.
- Achievements and awards to motivate students as they level up and earn coins for rewards upon mastering lessons.
- Instant reporting provides targeted feedback for each student to let teachers view progress in real-time and increase the ability to identify skill gaps and understand precisely where a student might be struggling.
- Functional dashboard to let students personalize their profile through avatars, themes, and more, making learning and getting on the platform fun.
Differentiated Instruction
The same instruction does not always work for every student. Differentiated instruction recognizes and values the diverse needs, abilities, and interests of students (Watts-Taffe et al., 2012; Dietrichson et al., 2021). Tuning in to learners’ preferences and skill levels allows for more equitable learning that supports and challenges each student at their individual level. Differentiated instruction also leads to more engagement and motivation by offering choice and flexibility in how students learn and demonstrate their understanding.
MindPlay Math, at its core, was designed to identify and target specific gaps of each individual learner. The MindPlay Math learning experience is individualized to meet the specific needs of each student, meaning they complete lessons at a level and pace that suits them best (Morgan, 2014). For example, if a student struggles to answer a specific question, the program will provide them with a reminder of the skill they’ve already learned and how to apply it. If the student continues to give an incorrect answer, the program will provide the student with the correct answer as well as an explanation. To determine each student’s current skill level, students complete the Math Screener to help teachers identify where students require more support and then complete only the lessons that target specific skills each student needs. MindPlay Math incorporates guided practice that is individualized and adaptable, providing models, opportunities for error correction, and reinforcement of learning (Rosenshine, 2012). The aim is to meet learners in their zone of proximal development, working through lessons that challenge them appropriately and providing the support they need to master each new skill (Morgan, 2014). Students complete lessons in phases to pace instruction which is designed to reduce frustration and focus on their individual growth. Furthermore, teachers are able to assign lessons to students based on skills previously learned, and students realize success by retrieving and incorporating those skills into new learning (Rohrer et al., 2015; Karpicke et al., 2016).
Repeated, Multisensory Practice
Learners are encouraged to use the program regularly, engaging in daily review and repeated practice to develop mastery. This repetition of content helps learners deepen their knowledge and use their new skills more automatically. Students only repeat lessons that they uniquely need in order to fill gaps. MindPlay Math takes a data-driven approach by using pre- and post-testing to assign an individualized learning path for students and allow for practice opportunities, which spiral and interleave practice to bring in skills from earlier lessons into new ones. This form of spaced practice improves long-term retention as well as student’s ability to determine the appropriate strategy to apply to a specific problem (Rohrer, 2009). Students receive instruction that meets their specific needs to close gaps in knowledge and allow students to build on their strengths (Dietrichson et al., 2021). In addition, during instruction, students are presented with multiple representations of a skill or strategy. This multi-representational, personalized approach, rooted in the Orton-Gillingham Approach to learning, is designed to prevent students from falling behind or feeling frustrated (Lomibao & Tabor, 2023). For instance, when students learn about simplifying fractions, they see it demonstrated visually in a real-world context as a pizza, then as a fraction model, and at the same time receive an auditory explanation to reinforce the models. Furthermore, research indicates that this approach, in keeping with the concrete-representational-abstract approach to teaching mathematics, greatly improves students’ accuracy and fluency in mathematics skills (Milton et al., 2019)
Mastery-based Learning
Mastery-based learning approaches focus on helping students learn math skills and strategies deeply and not at a predetermined pace (Guskey, 2007). Students are able to fully understand each concept before moving on to the next one because they have agency and autonomy over their progress, receiving targeted feedback that helps them tackle challenges without just giving them the answers. When problems are not answered correctly, students are presented with the information again and targeted specifically toward what they struggled with. When learners focus on mastering concepts, they gain lifelong learning skills. This fosters self-motivation, confidence, and engagement, and students feel a sense of ownership of their learning (Essa & Laster, 2017).
In conclusion, MindPlay believes mastery-based learning provides students with the foundational skills to grasp more complex concepts. MindPlay Math incorporates pre- and post-testing for each concept to ensure students have mastered concepts before moving on to more complex concepts. Students have multiple opportunities to achieve mastery of a concept in MindPlay Math by completing multiple different activities related to the same concept in order to ensure mastery.
References
Dietrichson, J., Filges, T., Seerup, J. K., Klokker, R. H., Viinholt, B. C., Bøg, M., & Eiberg, M. (2021). Targeted school‐based interventions for improving reading and mathematics for students with or at risk of academic difficulties in Grades K‐6: A systematic review. Campbell Systematic Reviews, 17(2), e1152.
Essa, A., & Laster, S. (2017). Bloom’s 2 Sigma problem and data-driven approaches for improving student success. The first year of college: Research, theory, and practice on improving the student experience and increasing retention, 212-246.
Guskey, T. R. (2007). Closing achievement gaps: revisiting Benjamin S. Bloom’s “Learning for Mastery”. Journal of Advanced Academics, 19(1), 8-31.
Jagušt, T., Botički, I., & So, H. J. (2018). Examining competitive, collaborative, and adaptive gamification in young learners’ math learning. Computers & Education, 125, 444-457.
Karpicke, J. D., Blunt, J. R., & Smith, M. A. (2016). Retrieval-based learning: Positive effects of retrieval practice in elementary school children. Frontiers in Psychology, 7, 350.
Lomibao, L. S., & Tabor, H. R. (2023). Orton-Gillingham Approach as an Online Intervention for Learners Diagnosed with Attention Deficit Hyperactivity Disorder (ADHD)-Specific Learning Disorder (SLD) in Mathematics: A Descriptive Case Study. Canadian Journal of Family and Youth/Le Journal Canadien de Famille et de La Jeunesse, 15(1), 141-151.
Milton, J. H., Flores, M. M., Moore, A. J., Taylor, J. L. J., & Burton, M. E. (2019). Using the concrete–representational–abstract sequence to teach conceptual understanding of basic multiplication and division. Learning Disability Quarterly, 42(1), 32-45.
Morgan, H. (2014). Maximizing student success with differentiated learning. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 87(1), 34-38.
National Center for Education Statistics. (2022, February 9). Administrators Report Roughly Half of Public School Students Began 2022-23 School Year Behind Grade Level in At Least One Academic Subject [Press Release]. Retrieved August 16, 2023, from https://nces.ed.gov/whatsnew/press_releases/2_09_2023.asp#:~:text=WASHINGTON%20(February%209%2C%202023),statistical%20center%20within%20the%20U.S.
Rohrer, D. (2009). Research commentary: The effects of spacing and mixing practice problems. Journal for Research in Mathematics Education, 40(1), 4-17.
Rohrer, D., Dedrick, R. F., & Stershic, S. (2015). Interleaved practice improves mathematics learning. Journal of Educational Psychology, 107(3), 900.
Rosenshine, B. (2012). Principles of instruction: Research-based strategies that all teachers should know. American educator, 36(1), 12.
Watts‐Taffe, S., Laster, B. P., Broach, L., Marinak, B., McDonald Connor, C., & Walker‐Dalhouse, D. (2012). Differentiated instruction: Making informed teacher decisions. The Reading Teacher, 66(4), 303-314.
