This piece was co-authored with Jessie Woolley-Wilson, CEO of DreamBox Learning.
Gone are the days when the success of technology integration in classrooms was measured by whether or not every student had access to a device. Simply making hardware available so that students can access software that merely displays digitized versions of formerly print content– such as PDF versions of worksheets– used to be considered edtech innovation, but it wasn’t creative or novel. Rather, technology that gives teachers the ability to improve teaching and learning in ways that wouldn’t be possible without technology is what makes edtech innovative.
One of the ways technology can innovate in education is through changing the way that teachers use student performance data. However, not all student data is helpful to teachers. In a recent survey by the Bill & Melinda Gates Foundation, Teachers Know Best, teachers reported that most student data that is available is not useful to them. This is because most of the data provides “rear-view mirror” information about students’ performance on summative assessments that the students completed long ago, which provide information about the effectiveness of teachers’ former lessons but doesn’t serve teachers in their current lessons. What teachers instead need is real-time, formative data during the lessons themselves that provides relevant and meaningful feedback about student learning. Such data would enable teachers to tweak their instructional approaches while they are teaching a lesson.
Adaptive learning technology makes this kind of dynamic data available to teachers, but most adaptive learning technologies that are currently on the market are not designed for this purpose. These technologies adapt the pace at which students move through static content such as lectures and readings based on whether a student has correctly answered the assessment items. Such technologies don’t attempt to diagnose why a student is stuck on a problem or to analyze the specific moves a student makes in his or her attempt to solve it. In this way, they can be thought of as adaptive assessment platforms rather than adaptive learning platforms. While they may be able to approximate what a student knows about a topic, content does not get more difficult when a student is progressing well and slow down if a student needs further instructional support.
A specific type of adaptive learning technology, intelligent adaptive learning technology, is able to assess what students know and seeks to offer what they need to achieve content mastery. This technology “learns the learner” as the learner engages with it, which enables nuanced, personalized and relevant data collection and reporting that gives teachers insight into how the learner is solving problems and thinking. In addition to tracking achievement, the technology identifies trends in student motivation and engagement so that teachers can optimize learning efficiency, learning tenacity and ultimately learning outcomes. While students are working through lessons, the technology analyzes every click, hesitation and answer in order to direct students based on what they need in the moment to ensure deep understanding of key concepts, develop fluency with important skills, and cultivate critical thinking.
The results of intelligent adaptive learning technology use in classrooms are promising. Harvard University’s Personalized Learning Collaborative at the Center for Education Policy Research found that adaptive learning technology (specifically DreamBox Learning’s Intelligent Adaptive Learning™ math curriculum) can lead to gains in mathematics achievement. According to the study, students who used DreamBox Learning’s math program for an average of seven hours witnessed a two percentile point gain on the Northwest Evaluation Association’s (NWEA) MAP assessment when compared to similar students who did not use the software at all. Moreover, students who spent more time on the DreamBox Learning software saw larger gains in achievement.
The noted benefits and future possibilities of intelligent adaptive learning technology have encouraged dozens of companies to produce adaptive learning technology that addresses student learning needs in different ways. Fishtree allows teachers to prepare and assign differentiated adaptive lessons. Teachers can assign individual students or groups of students different lessons based on varying learning needs, and the technology adapts as the students move through the lessons. Smart Sparrow’s adaptive e-learning platform offers adaptive and interactive quizzes and simulations. A study in a mechanics course at the University of New South Wales found that use of Smart Sparrow technology platform reduced student failure rates from 31% to 7%. It is clear that advances in intelligent adaptive learning technology are changing the way we teach and analyze learning in the e-learning space.
Intelligent adaptive learning platforms make it possible to collect evidence of student thinking and learning in ways that are impossible with paper and pencil. By arming educators with rich, timely information about student growth and performance, future developments in intelligent adaptive learning platforms will likely encourage educators to re-imagine their instructional practices, resulting in increased classroom innovation and improved student outcomes.
This article was written by Barbara Kurshan from Forbes and was legally licensed through the NewsCred publisher network.