Dreambox Learning: Intelligent Adaptive Computer-based mathematics instruction
Dreambox claims that its advanced adaptive learning technology produces “millions of personalized learning paths” that are “tailored to students’ unique needs.” Further, the Dreambox adaptive learning engine “ensures that students work in their optimal learning zone” and “can adapt the level of difficulty, scaffolding, sequencing, and the number of hints, the pacing—all in real-time—allowing students of all levels to progress at a pace that suits them” (http://www.dreambox.com/adaptive-learning). This is described as student-directed learning that makes students feel empowered. The question that needs to be answered is whether or not students will challenge themselves in areas where they struggle, or if they will rely on hints and scaffolding to meet academic standards.
The fundamental claim made by proponents of computer-based adaptive learning tools is presented by Dreambox in their information material – “Researchers are finding that the results from computer-based systems using adaptive technology approximate those from human tutoring.” (http://www.dreambox.com/adaptive-learning – learn more). Can this be supported?
Case Study: Rocketship Charter Schools, USA
In 2007, Rocketship charter schools launched a hybrid education program in collaboration with Dreambox Learning. The term hybrid is differentiated from blended learning in that a hybrid model does not embed online learning in a traditional classroom setting, but rather separates online and traditional learning into separate locations and during different time-blocks in a student’s day (Schorr and McGriff, 2011, p.11). Dreambox software was integrated into their online learning programs for their math curriculum; DreamBox is used as part of a daily two-hour learning lab session where students receive personalized instruction.
In 2009, the strength of their model was proven as a new site that opened that year was the number-one first-year school in the state of California in the high-poverty category (Schorr and McGriff, 2011, p.11).
By 2011, the fact that Rocketship’s model provided substantial measurable learning gains was indicated as it climbed to into the 15 top-performing high poverty schools (Schorr and McGriff, 2011, p.11). However, also in 2011, the limitations of using software like Dreambox to meet the goals of the model being pursued by Rocketship began to become apparent. Dreambox prescribes lessons for students based on their performance, whereas Rocketship’s vision is to receive assessment data from the online learning software so that teachers can provide lesson prescriptions. Charlie Bufalino manages the data collected from Rocketship’s online learning labs, and expressed disappointment that adaptive learning software vendors had not invested sufficient research and development into their products to make a standardized data stream that would inform teacher prescriptions possible (Schorr and McGriff, 2011, p.12) .
By 2013, this problem had led to some teachers and members of the administration at Rocketship schools becoming vocal critiques of intelligent adaptive learning software like Dreambox. In a case study written about the success of their school programs, they describe the use of online programs “that are adaptive and intended to be run without any teacher intervention” as being “at odds with their current model,” suggesting instead that they prefer online tools that provide data for teachers to use in their own personalized instruction (Opportunityculture.org, 2013, p.4). They elaborate that adaptive online learning tools were creating a disconnect between their technology driven learning labs and the classroom environment, and have taken on a new model to bring students’ “online work closer to the teacher” (p.3).
By the end of the 2012-2013 school year, Rocketship schools had shifted the focus of their online learning labs away from completely intelligent adaptive learning software like Dreambox to software that allow teachers more control of assigning content and accessing student data (Opportunityculture.org, 2013, p.4).