Data-Driven Decision Making in Education

Mandinach, Ellen B.

doi:10.4324/9781138609877-ree3-1

Cited by 21 publications

(37 citation statements)

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“…As such, data-driven cultures influence how the individuals in the organization use data to create decisions and choose strategies to pursue organizational goals (Rexhepi et al, 2020). Hence, pursuing data-driven to gain benefits from data and analytics requires a wellmanaged implementation of organizational change (Storm and Borgman, 2020) in which leadership plays crucial roles (Mandinach et al, 2006;Kennedy, 2009;Gil et al, 2014;van Oijen et al, 2019). Strong leadership is significant in increasing the possibility of data usage by communicating a clear vision and plan for data-driven.…”

Section: Challenges and Critical Factors Of Data-driven Decision-makingmentioning

confidence: 99%

“…Rational decision-making might be constrained by, among others, the resources as the basis to infer the decision, such as time, data and information, as well as personal and organizational constraints in terms of analytic capacity, capability and culture (S ahin and Zaitoon, 2021). Data must be analyzed and transformed into information and knowledge to facilitate decision-making (Mandinach et al, 2006). Even having the correct information, making a decision based on information requires the ability to process the information (van Oijen et al, 2019).…”

Section: Challenges and Critical Factors Of Data-driven Decision-makingmentioning

confidence: 99%

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Data-driven decision-making challenges of local government in Indonesia

Sayogo,

Yuli,

Amalia

2023

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Purpose This study aims to identify and outline the critical challenges affecting the inclination of executives to use data as the basis for making decisions at a local government level. Design/methodology/approach The study conducted in-depth interviews with 21 public officials comprising middle- and top-level executives from 18 agencies and offices at the Bojonegoro Regency, one of Indonesia’s most progressive regencies in pursuing open government and smart cities. Findings The findings demonstrate that ensuring a good quality data architecture, nurturing data culture and developing analytics capability are essential in the case of a developing country such as Indonesia. However, insufficient policies and regulations, a nonexistent evaluative framework for data quality, disruptive local tradition and the ingrained autocratic administration represent significant and unique challenges to implementing data-driven decision-making in the local government in Indonesia. Research limitations/implications The chosen research approach may result in a need for more generalizability beyond Indonesia, accentuating the necessity for the geographical objects to include other developing countries in future research. Practical implications The findings showcase that lack of awareness and acceptance from public officials and the general public of the importance of a data-driven approach; as such, a better understanding of the change in attitudes and mindsets of public officials is invariably one of the critical practical determinants. Originality/value The findings signify the importance of creating robust accountability systems and evaluative frameworks that consider the many variables influencing decisions that capture the significance of organizational and local culture.

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Section: Challenges and Critical Factors Of Data-driven Decision-makingmentioning

confidence: 99%

Section: Challenges and Critical Factors Of Data-driven Decision-makingmentioning

confidence: 99%

Data-driven decision-making challenges of local government in Indonesia

Sayogo,

Yuli,

Amalia

2023

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“…They do so by making a broad distinction between data analysis on the one hand and interpretation on the other hand, that is, being able to read and understand the data, and being able to make valid inferences based on the data (Mandinach & Schildkamp, 2021; Schildkamp, 2019; Vanlommel & Schildkamp, 2019). Authors following this line of thought (e.g., Schildkamp, 2019) explicitly apply the global label of sensemaking to operations unravelled in more detail in data use frameworks put forward by authors such as Marsh et al (2006), Mandinach et al (2008), Marsh (2012) and Schildkamp and Poortman (2015). Those models tend to be rooted in a waterfall logic of turning data into information into actionable knowledge, through micro‐operations, such as data organisation, analysis and synthesis.…”

Section: Teachers’ and School Leaders’ Sensemaking Of Formal Achievem...mentioning

confidence: 99%

Teachers' and school leaders' sensemaking of formal achievement data: A conceptual review

Goffin

Janssen

Vanhoof

2022

Review of Education

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Formal achievement data such as test scores and school performance feedback from standardised assessments can be a powerful tool for data‐based decision making and school improvement. However, teachers’ and school leaders’ usage of these data is not necessarily straightforward or predictable. In order to illuminate how educational professionals engage with data in their daily practice, from their own subjective backgrounds and within their own contexts, data use researchers increasingly adopt a sensemaking perspective. Sensemaking, a theoretical construct grounded in psychological and organisational scholarship, offers a framework and a vocabulary to explain how cues such as educational output data are processed in real‐life educational settings. As such, sensemaking research sheds light on reasons why educational professionals’ use of these formal achievement data may deviate from normative expectations. The present study is a conceptual review of how sensemaking is conceived and applied in literature on educational professionals’ use of formal achievement data. In total, 25 empirical and theoretical studies were selected and subjected to thematic analysis. Findings include that sensemaking is used as a lens to study data use, as well as a label for interpretive micro‐processes of data analysis and interpretation, and that formal achievement data can be regarded as sensemaking resources. An integrated conceptual framework on educational professionals’ sensemaking of formal achievement data is presented, including a discussion of critical insights that may inspire future research on data‐based decision making in education.

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“…There is further scope to fine-tune standard canned reports and dashboards for various HR functions and study the consumption of these reports. Also, instead of covering all HR domains, future researchers can study one problem area in HR and apply the research methodology similar to Mandinach et al (2006) to identify a framework to make decision-making more data-enabled.…”

Section: Limitations and Future Scopementioning

confidence: 99%

Empowering human resource functions with data-driven decision-making in start-ups: a narrative inquiry approach

Varma

Dutta

2021

IJOA

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Purpose Across industries, firms want to adopt data-driven decision-making (DDDM) in various organizational functions. Although DDDM is not a new paradigm, little is known about how to effectively implement DDDM and which problem areas to focus on in these functions. This study aims to enable start-ups to use DDDM in human resources (HR) by studying five HR domains using a narrative inquiry technique and aims to guide managers and HR practitioners in start-ups to enable data-driven decisions in HR. Design/methodology/approach This study adopts the narrative inquiry technique by conducting semi-structured interviews with HR practitioners and senior members handling HR functions in start-ups. Interview memos are thematically analyzed to identify repeated ideas, concepts or elements that become apparent. Findings The study findings indicate that start-ups need to have canned operational reports with right attributes in each of these HR domains, which members should use when performing HR tasks. Few metrics, like cost-to-hire in recruitment, distinctly surfaced relatively higher in importance that each start-up, should compute and use in decision-making. Practical implications Managers, HR practitioners and information technology implementation teams will be able to consume the findings to effectively design or evaluate HR processes or systems that empower decision-making in a start-up. Originality/value Start-ups have a fast-paced culture where creativity, relationships and nimbleness are valued. Prevalent decision models of larger organizations are not suitable in start-ups’ environments. This study, being cognizant of these nuances, takes a fresh approach to guide start-ups adopt DDDM in HR and identify key problem areas where decision-making should be enabled through data.

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Data-Driven Decision Making in Education

Cited by 21 publications

References 0 publications

Data-driven decision-making challenges of local government in Indonesia

Data-driven decision-making challenges of local government in Indonesia

Teachers' and school leaders' sensemaking of formal achievement data: A conceptual review

Empowering human resource functions with data-driven decision-making in start-ups: a narrative inquiry approach

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