AI Case Study
Dreambox offers students larger and faster gains in achievement through AI adaptive learning according to a Harvard report
Harvard conducted a study on the use of DreamBox Learning software in the Howard County Public School System (HCPSS) and the Rocketship Education charter school network. The study aimed to measure the impact of the AI adaptive learning system on student achievement. The key founding highlighted that the majority of students did not engage with the software as much as it was recommended, the software's use was driven by teachers and schools rather than student preferences, while students spending more time on the software and following its recommendations saw larger and faster gains in achievement. Although results for causal impact on student achievement is positive, the evidence is mixed.
Public And Social Sector
Education And Academia
"The IAL System are Designed to:
1) Serve as a personal tutor to the student
2) Adapt the sequencing of the curriculum and associated learning experiences
3) Individualize the pace of learning
4) Regulate cognitive load for the student
5) Engage students in learning through gaming
Intelligent adaptive learning (IAL) optimizes learning by establishing a digital learning environment that keeps students in their optimized learning zone. It captures every decision a student makes and adjusts the student’s learning trajectory both within lessons and across lessons. The key attribute of the IAL system is not the immediate correction of every student error, but rather that it attempts to “identify the psychological cause of mistakes,” provides intelligent feedback and prompts for re ection and rethinking by the student, and “thereby lower(s) the probability that such mistakes will occur again.”
Imagine a personal tutor who constantly checks for understanding in real-time by analyzing large datasets of a student’s actions
and interactions, often comparing them to a knowledge base of known misconceptions or errors commonly committed by other students studying the same topic. This tutor provides multiple pathways to learning with real-time intelligent feedback and access to progress reports for students, teachers, and parents. IAL systems often include feature sets that students and engaging. Examples include gaming, or providing students a modicum of choice as to which activities they pursue—within set parameters of their current level of expertise and their targeted goals.
Inherent in the design of IAL systems are five critical factors: 1) the content in the form of lessons or activities in which the learner engages in a sequence unique to his needs, 2) the instructional strategies that teach and guide the learner, 3) measurements of the a ect of the student toward the learning, 4) mechanisms for measuring and understanding what the student does or does not know, and 5) a feedback mechanism whereby the data acquired about the learner informs the next round of content, instruction, and motivation the student encounters." (static.dreambox.com)
"One of today’s next generation technology innovations now available to schools is intelligent adaptive learning (IAL), which serves to individualize and, to some extent, personalize learning for each student.
Intelligent adaptive learning is de ned as digital learning that immerses students in modular learning environments where every decision a student makes is captured, considered in the context of sound learning theory, and then used to guide the student’s learning experiences, to adjust the student’s path and pace within and between lessons, and to provide formative and summative data to the student’s teacher.
This type of learning tailors instruction to each student’s unique needs, current understandings, and interests, while ensuring that all responses subscribe to sound pedagogy."
"An impact study on the use of DreamBox Learning software on student achievement in the Howard County Public School System (HCPSS) and the Rocketship Education charter school network showed the following key findings:
1. Most students did not reach the recommended levels of usage of the DreamBox software.
2. Some schools used DreamBox software to target low-achieving students and after-school learning, while others did not.
3. The variation in DreamBox software use was driven largely teacher- and school-level practices, as opposed to student preferences.
4. Students who spent more time on the DreamBox software saw larger gains in achievement.
5. Students who followed the DreamBox lesson recommendations, as opposed to going back and repeating content, saw faster gains.
6. The DreamBox progress measure was positively associated with achievement gains on state tests and interim assessments.
7. The evidence for the causal impact of DreamBox on student achievement is encouraging but mixed." (cepr.harvard.edu)