The intersection of school context and teachers’ data use practice: Implications for an integrated approach to capacity building

Abrams, Lisa; Varier, Divya; Mehdi, Tareque

doi:10.1016/j.stueduc.2020.100868

Cited by 18 publications

(27 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It measures several indicators which reflect educational inputs, processes, and outputs. This policy is in line with the studies of effective school development (10)(11)(12)(13)(14). There are two main menus view data of an education/ services unit and view public data.…”

Section: Rapor Pendidikanmentioning

confidence: 65%

Digitalization of Education in the Implementation of Kurikulum Merdeka

Novita

Saputro

Chauhan

et al. 2022

KSS

View full text Add to dashboard Cite

The Indonesian Ministry of Education, Culture, Research, and Technology (Kemendikbudristek) recently released several educational platforms like Merdeka Belajar, Rapor Pendidikan, Belajar.id, ARKAS, TanyaBOS, SiPLah and Kampus Merdeka to make a leap in educational progress. However, the user percentage is still low, which may be due to various reasons such as limited internet access and reluctance to learn new technology. Discussion on which priority technology platforms are and how they are used to support Kurikulum Merdeka’s implementation has been limited. Therefore, this paper will analyze the primary educational platforms useful for the implementation of Kurikulum Merdeka. We carried out a systematic review of the relevant databases on the digitalization of education in implementing Kurikulum Merdeka. Although the current educational platforms are still being developed, they provide unique features which facilitate students, teachers, administrators, and principals in the learningmanagement process at all levels of education. This work has the potential to become an essential reference that provides guidelines for using the educational platform to improve the number of users. Keywords: Kurikulum Merdeka; Merdeka Belajar; software; digital school; application

show abstract

Section: Rapor Pendidikanmentioning

confidence: 65%

Digitalization of Education in the Implementation of Kurikulum Merdeka

Novita

Saputro

Chauhan

et al. 2022

KSS

View full text Add to dashboard Cite

show abstract

“…The distinctions we make between intuitive and rational processes pertain to timing, pace, depth, thought processes, and options. These are always dependent on the context in which the teacher operates (Coburn & Tunner, 2011;Abrams et al, 2020). When the teachers in our study intuitively made sense of school performance feedback data, this happened immediately during the initial reading of the feedback reports.…”

Section: Discussionmentioning

confidence: 80%

Sensemaking unraveled: how teachers process school performance feedback data

Gutwirth¹,

Goffin²,

Vanhoof³

2022

Studia paedagogica

View full text Add to dashboard Cite

The present study investigates how Flemish middle school mathematics teachers make sense of schoolperformanfeedback data from low-stakes, external standardised tests. We take an in-depth look into the interpretive steps they take, based on a conceptual model that integrates intuitive and rational aspects of individual and collective sensemaking and empirical data collected in semi-structured interviews. We describe the nature of these sensemaking processes and consider the impact of influencing factors. Our findings demonstrate that the mere availability of school performance feedback data does not spontaneously spark sensemaking, nor does it necessarily lead to improvements in instructionalpractice. Teachers' sensemaking of schoolperformancefeedback data appears to be a largely intuitive process, grounded in external attributions and absent of triangulation. Challenges regarding expertise and lack of inquiry-based attitude and commitment result in superficial and often incorrect interpretations of the data that tend to remain uncorrected as teachers barely engage in collaborative professional dialogue about the data.

show abstract

“…Otra fuente de información altimétrica es el ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Glogal Digital Elevation Model), el cual posee información altimétrica de toda la superficie terrestre, mediante la correlación imágenes estereoscópicas individuales. Este último, fungió de auxiliar para complementar la información altimétrica de las zonas carentes de información LiDAR (Abrams et al 2020, Hawker et al 2022. Un modelo digital de elevación (MDE) es una representación digital rasterizada de la topografía de la superficie del suelo o del terreno, cada celda rasterizada (o píxel) tiene un valor correspondiente a su altitud sobre el nivel del mar en la topografía (Abrams et al 2020, Jeannin et al 2021, Hawker et al 2022.…”

Section: Introductionunclassified

“…Este último, fungió de auxiliar para complementar la información altimétrica de las zonas carentes de información LiDAR (Abrams et al 2020, Hawker et al 2022. Un modelo digital de elevación (MDE) es una representación digital rasterizada de la topografía de la superficie del suelo o del terreno, cada celda rasterizada (o píxel) tiene un valor correspondiente a su altitud sobre el nivel del mar en la topografía (Abrams et al 2020, Jeannin et al 2021, Hawker et al 2022. El relieve kárstico puede estudiarse a partir del moni- toreo 3D y la generación de MDE, estos modelos se originan a partir de la extracción de datos altimétricos de MDT o la digitalización de las curvas de nivel e interpolación de los datos altitudinales, a partir de herramientas de Sistemas de Información Geográfica (SIG) (Rodríguez-Castillo et al 2021, Hawker et al 2022.…”

Section: Introductionunclassified

Caracterización morfométrica de depresiones kársticas: zona costera nororiente de la Península de Yucatán, México

Rodríguez-Castillo

Martínez

Uhu-Yam

et al. 2022

Ecosist. Recur. Agropec.

View full text Add to dashboard Cite

Estudiar el relieve a través del análisis morfológico permite tipificar formas, elementos y estructuras del relieve kárstico que auxilia en la determinación de la génesis, evolución y dinámica geomorfológica. La implementación de herramientas con nuevos métodos y tecnologías ayuda a desarrollar estudios de mayor precisión en zonas con bajo contraste altitudinal. El objetivo del presente estudio es analizar y clasificar las depresiones kársticas en la región costera del nororiente de la península de Yucatán. El relieve kárstico se analizó a partir de dos fuentes de datos: a) un mosaico de datos LiDAR (light detection and ranging) y b) un mosaico de datos AsterGDEM (Advanced Spaceborne Thermal Emission and Reflection Radiomete Global Digital Elevation Model). Estos se acoplaron generando insumos altimétricos y modelos topográficos base. Posteriormente, se generaron curvas de nivel diferenciando depresiones con una profundidad mínima de 1m; después, se procesaron y clasificaron las depresiones aplicando un análisis de mediciones morfométricas, tipología morfológica del perfil e índice de elongación. Se identificaron 10 672 depresiones donde, el 67% corresponde a depresiones tipo V, 23% tipo U y 10% tipo caja; respecto al índice de elongación, 18% son dolinas, 42% dolinas-úvalas, 13% úvalas y el 27% poljes, siendo las úvalas y poljes las que poseen mayor complejidad, debido al control estructural del sistema de fallas Holbox y Tikul, con orientación principal de NE7°SW y secundario SE83°NW, que pone en evidencia en carácter disyuntivo estructural. Finalmente, se presenta un inventario de depresiones kársticas, sirviendo de base para la gestión del territorio kárstico costero.

show abstract

The intersection of school context and teachers’ data use practice: Implications for an integrated approach to capacity building

Cited by 18 publications

References 38 publications

Digitalization of Education in the Implementation of Kurikulum Merdeka

Digitalization of Education in the Implementation of Kurikulum Merdeka

Sensemaking unraveled: how teachers process school performance feedback data

Caracterización morfométrica de depresiones kársticas: zona costera nororiente de la Península de Yucatán, México

Contact Info

Product

Resources

About