Effects of Data‐Based Individualization for Students with Intensive Learning Needs: A Meta‐Analysis

Jung, Pyung Gang; McMaster, Kristen L.; Kunkel, Amy K.; Shin, Jaehyun; Stecker, Pamela M.

doi:10.1111/ldrp.12172

Cited by 96 publications

(112 citation statements)

References 47 publications

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“…), they all incorporate some dynamic assessment of learning progress on an individual basis and they all seem to have at least some positive effects on learning, compared with a business-as-usual control group. This has been shown in several meta-analyses reporting effect sizes of d = 0.32 in regular classrooms (Kingston and Nash 2011), and higher ones for students with special educational needs (Jung et al 2018).…”

Section: Personalized Learning In the Classroommentioning

confidence: 72%

“…The benefits of personalization can not only be seen in digital environments, however. Even in a conventional classroom context, there is mounting evidence for increased learning gains through personalized instruction across a wide range of settings and subjects (Connor et al 2007;Connor et al 2009;Jung et al 2018;Slavin and Karweit 1985;Stecker et al 2005;Waxman et al 1985).…”

mentioning

confidence: 99%

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Developing Personalized Education: A Dynamic Framework

2020

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Personalized education—the systematic adaptation of instruction to individual learners—has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when relevant learner characteristics are measured repeatedly during the learning process and when these data are used to adapt instruction in a systematic way. Building on these observations, we propose a novel, dynamic framework of personalization that conceptualizes learners as dynamic entities that change during and in interaction with the instructional process. As these dynamics manifest on different timescales, so do the opportunities for instructional adaptations—ranging from setting appropriate learning goals at the macroscale to reacting to affective-motivational fluctuations at the microscale. We argue that instructional design needs to take these dynamics into account in order to adapt to a specific learner at a specific point in time. Finally, we provide some examples of successful, dynamic adaptations and discuss future directions that arise from a dynamic conceptualization of personalization.

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Section: Personalized Learning In the Classroommentioning

confidence: 72%

mentioning

confidence: 99%

Developing Personalized Education: A Dynamic Framework

2020

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“…DBI is a framework that can be used by teachers to take a scientific approach to modifying instruction effectively and efficiently based on individual student need through the use of data. While there is variation in the literature regarding the specific steps of the DBI process, generally, DBI consists of the following core components: (a) determine a student's present level of academic and functional performance, (b) set a long-term performance goal, (c) select and implement a researchbased instructional platform and frequently monitor progress, (d) apply decision rules to determine when instructional modifications are needed based on the data, (e) use data to create hypotheses regarding the student's needs and make instructional changes accordingly, (f) monitor student progress in response to the instructional changes, (g) repeat this process until the long-term goal is reached (Jung et al, 2018).…”

Section: Data-based Instructionmentioning

confidence: 99%

Exploring the Relation Between Teacher Factors and Student Growth in Early Writing

Bresina

McMaster

2020

J Learn Disabil

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Data from a small randomized control trial of teachers’ use of Data-Based Instruction (DBI) for early writing were analyzed to determine the influence of teacher knowledge, skills, and treatment fidelity on student Curriculum-Based Measurement (CBM) slope. Participants included 11 elementary grade teachers who delivered intensive intervention in early writing and their students ( n = 31), all identified as either at risk for or with disabilities that affect their writing. Teachers received professional development and ongoing coaching to support the implementation of DBI for improving their students’ early writing skills. Results from a multiple regression analysis suggest that teacher knowledge and skills in DBI was strongly related to student CBM slope in early writing ( p < .01) and a small but significant relation between fidelity of writing instruction and student CBM slope ( p < .01). Implications for instructional coaching and improving student writing progress are discussed.

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“…CBM are a tool to make educational decisions based on reliable and objective data (Jung et al, 2018;. In this way the instruction or intervention is evaluated, and a modification can be initiated if necessary (e.g.…”

Section: Suggestionsmentioning

confidence: 99%

Tablet or Paper and Pen? Examining Mode Effects on German Elementary School Students’ Computation Skills with Curriculum-Based Measurements

Blumenthal¹

2020

INT J EDUC METHODOL

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Progress monitoring of academic achievement is an essential element to prevent learning disorders. A prominent approach is curriculum-based measurement (CBM). Various studies have documented positive effects of CBM on students' achievement. Nevertheless, the use of CBM is associated with additional work for teachers. The use of tablets may be of help here. Yet, although many advantages of computer-or tablet-based assessments are being discussed in the literature (e. g. innovative item formats, adaptive testing, automated scoring and feedback), there are still concerns regarding the comparability of different assessment modes (paper-pencil vs. tablet). In the study presented, we analyze the CBM data of 98 fourth graders. They processed the exact same computation items once with paper and pen and once in a tablet application. The analyses point to comparable results in the test modes, although some significant deviations can be found at item level. In addition, the children report perceived benefits when working with the tablet.

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Effects of Data‐Based Individualization for Students with Intensive Learning Needs: A Meta‐Analysis

Cited by 96 publications

References 47 publications

Developing Personalized Education: A Dynamic Framework

Developing Personalized Education: A Dynamic Framework

Exploring the Relation Between Teacher Factors and Student Growth in Early Writing

Tablet or Paper and Pen? Examining Mode Effects on German Elementary School Students’ Computation Skills with Curriculum-Based Measurements

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