On the promise of personalized learning for educational equity

Abstract

Students enter school with a vast range of individual differences, resulting from the complex interplay between genetic dispositions and unequal environmental conditions. Schools thus face the challenge of organizing instruction and providing equal opportunities for students with diverse needs. Schools have traditionally managed student heterogeneity by sorting students both within and between schools according to their academic ability. However, empirical evidence suggests that such tracking approaches increase inequalities. In more recent years, driven largely by technological advances, there have been calls to embrace students’ individual differences in the classroom and to personalize students’ learning experiences. A central justification for personalized learning is its potential to improve educational equity. In this paper, we discuss whether and under which conditions personalized learning can indeed increase equity in K-12 education by bringing together empirical and theoretical insights from different fields, including the learning sciences, philosophy, psychology, and sociology. We distinguish between different conceptions of equity and argue that personalized learning is unlikely to result in “equality of outcomes” and, by definition, does not provide “equality of inputs”. However, if implemented in a high-quality way, personalized learning is in line with “adequacy” notions of equity, which aim to equip all students with the basic competencies to participate in society as active members and to live meaningful lives.

Do school grades matter for growing up? Testing the predictive validity of school performance for outcomes in emerging adulthood.

“…Such interventions may also help disrupting the transmission of family background inequality in education and help closing the attainment gap between children from high and low-SES backgrounds (Paulus et al, 2021; von Stumm et al, 2020). If greater equity in students’ school performance was achieved, with students obtaining more similar school-leaving grades, their subsequent educational trajectories would also likely be less differentiated (Dumont & Ready, 2023; Hanushek & Wößmann, 2006). In putatively meritocratic societies, maximizing homogeneity in educational attainment is likely to magnify equality in adulthood outcomes, ranging from income and health to social relationships.…”

Four Scenarios of Personalized Learning Integration Mediated by a Digital Platform

“…Besides, the concepts vary in learning design, in which tools, instruments, and instructions are distributed for groups, e.g., ''strong'' and ''weak'' students (differentiation), or are addressed at individual students (individualization). Regarding differentiation, Dumont and Ready (2023) argue that schools have a tendency to treat academic differences as obstacles and group students with similar abilities together; therefore, differentiation may result in reducing student heterogeneity. PL, being purely SCL, proposes a learner who chooses the tool and method to receive the content.…”

Research on the Disruptive Transformation and Future Development of American Teaching Models in the Context of Intelligent Transformation

“…▪ Personalized Learning: AI technology has shown promise in personalizing learning experiences based on individual students' strengths, weaknesses, engagement patterns, and performance data, thereby creating a tailored learning path for each student [23]. A significant rationale behind personalized learning is its potential to enhance educational equity, aiming to provide all students with the essential competencies to engage actively in society and lead meaningful lives [24]. ▪ Emotional Cognition: Advances in AI have also permeated the emotional dimension of learning.…”