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TransMath® Third Edition is a comprehensive math intervention curriculum that targets middle and high school students who lack the foundational skills necessary for entry into algebra and/or who are two or more years below grade level in math.
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Developed by renowned literacy experts Dr. Louisa Moats and Dr. Carol Tolman, LETRS® is a flexible literacy professional development solution for preK–5 educators. LETRS earned the International Dyslexia Association's Accreditation and provides teachers with the skills they need to master the fundamentals of reading instruction—phonological awareness, phonics, fluency, vocabulary, comprehension, writing, and language.
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Look to ClearSight to measure student mastery of state standards with items previously used on state high-stakes assessments. ClearSight Interim and Checkpoint Assessments include multiple forms of tests for grades K–high school.
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A new, online touch-enabled test administration and data system that allows educators to assess students and immediately see results, providing robust reporting at the student, class, school, and district levels.
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We Can
by Sandi Everlove on Feb 22, 2017
When most of us hear the word brilliant, we think of rare individuals who are exceptional in ways that set them apart. But what if that kind of thinking has held us and our children back? What if we reframed our focus in education to discovering, cultivating, and nurturing the brilliance in every child?
In the 1800s, medicine and education were somewhat on par. In medicine, bloodletting by barber surgeons and traveling medicine show nostrums were favored treatments. In education, schools were often overcrowded, and caning and the dunce cap were the norm for controlling behavior.
When Johns Hopkins University (JHU) opened its medical school in 1893, it ushered in a new era, changing medicine’s trajectory and enabling life-saving breakthroughs. Rigid entrance requirements, a vastly upgraded curriculum with an emphasis on the scientific method, and laboratory research that included bedside teaching as a core part of the instruction, made JHU a pioneer. Its standards for rigor, use of scientific data to guide practice, and sharing of key findings, transformed the field of medicine and created the conditions for extraordinary and explosive advancements felt worldwide.
While caning and dunce cap are thankfully long gone, the approach to general education has been slower to change. We’ve moved from blackboards to smart boards, and desktop computers to mobile devices. But the underlying structure has endured since the days of Horace Mann. The results on student learning are well documented and often discouraging, particularly for poor children and minorities. However, it is important to note that American schools are not worse than they were in previous generations. Most students, according to long-term NAEP assessments, master foundational skills as defined 40 years ago (e.g., reading well enough to follow directions). The problem is that our education system has not kept pace with the changing world around it. Today’s education challenges stem from the increased complexity of foundational skills needed to thrive in our ever-changing global society.
The good news is we are in the middle of an exciting revolution in education. Medical research is providing new information about the brain, sociological and psychological studies are providing new information about how children learn, and new technologies are transforming teaching and learning.
The field of neuroscience or brain research is playing an increasingly important role in education. There are key things we now know about the human brain that are relevant to educators:
We also know a lot more about conditions that facilitate and inhibit learning. The ability to learn, retain, and use information is not just based on raw IQ. Our overall emotional state impacts how well we can learn new things. When the limbic system (the emotional part of the brain) is under stress, higher processing is blocked, new connections stop forming, and learning is impeded. Claude Steele’s groundbreaking research on “stereotype threat” illustrates the powerful role emotions can play in both learning and academic performance. In numerous experiments, Steele and others have found that fear of confirming a negative stereotype causes stress and distracts individuals from completing a task to the best of their ability. For example, there’s a stereotype that females cannot do high-level math. When females were in high-threat situations, they performed significantly worse than their male peers on math tests. When the threat was eliminated, the performance gap disappeared.
Thirty-two years ago, a psychologist named Benjamin Bloom discovered that students who learned a topic through 1:1 tutoring performed two standard deviations better than students who received conventional classroom instruction. In other words, the average tutored student performed better than 98 percent of the students in the traditional classroom. What Bloom uncovered is that when learning is personalized, students do better. There was one big problem: his technique wasn’t scalable. So Bloom posed a challenge: devise teaching-learning conditions that will enable the majority of students under group instruction to achieve at levels that can only be reached under good tutoring conditions. More than 30 years later we may finally be close to solving Bloom’s challenge by taking what we know about the brain and learning, and coupling that with advances in adaptive learning technology.
Adaptive learning is simply an approach to creating a personalized learning experience for students. There’s nothing new about personalization. Good teachers will tell you they have been doing it for years. What is new, is that we can now employ technology and create an engine that gets “smarter” over time, enabling it to present problems and concepts in sequences that experts might never have considered. The engine can anticipate what content and resources a student needs at a specific point in time to make progress based on their previous interactions and demonstrated performance level, as well as inferred proficiencies drawn from data about thousands of previous students’ learning interactions with similar content.
Adaptive engines can also integrate non-cognitive factors that influence learning and motivation, such as persistence and time on task, and even help students develop these critical skills. Most importantly, adaptive engines can be designed with the understanding that learning is inherently contextual and social. In other words, there is a clear and important role for the computer, but there is also a critical role for the teacher and peers. The best systems know when and how to involve a teacher and peer groups by providing actionable, real-time data.
In 2013, the Rand Corporation published the results of a seven-year, controlled study comparing middle and high students’ performance in traditional algebra classrooms with those in classrooms using an adaptive learning technology. In the first year of implementation there were no significant differences in results. But students who took the adaptive learning course for a second year improved their scores twice as much between the beginning and end of the year compared to those who remained in traditional classrooms.
Imagine a future where teachers have unprecedented insights into how different students learn and where students are engaged in learning that supports their weaknesses, exploits their strengths, and enables their unique talents to flourish. Do we have it all figured out? No. But the potential is there and the results could be a breakthrough in education for teachers and students.
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