Using Data Analytics to Drive Performance and Instructional Decision-Making

2016 ◽  
pp. 21-30
Author(s):  
Tristan E. Johnson
Keyword(s):  
Decision Making ◽  
Data Analytics ◽  
Instructional Decision Making ◽  
Using Data ◽  
Instructional Decision

scholarly journals New dilemmas, old problems: advances in data analysis and its geoethical implications in groundwater management

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
César de Oliveira Ferreira Silva ◽  
Mariana Matulovic ◽  
Rodrigo Lilla Manzione
Keyword(s):  
Decision Making ◽  
Data Analytics ◽  
Data Science ◽  
Final Decision ◽  
Aquifer Recharge ◽  
Groundwater Governance ◽  
Ethical Attitude ◽  
New Information ◽  
Modeling Experiment ◽  
Using Data

Abstract Groundwater governance uses modeling to support decision making. Therefore, data science techniques are essential. Specific difficulties arise because variables must be used that cannot be directly measured, such as aquifer recharge and groundwater flow. However, such techniques involve dealing with (often not very explicitly stated) ethical questions. To support groundwater governance, these ethical questions cannot be solved straightforward. In this study, we propose an approach called “open-minded roadmap” to guide data analytics and modeling for groundwater governance decision making. To frame the ethical questions, we use the concept of geoethical thinking, a method to combine geoscience-expertise and societal responsibility of the geoscientist. We present a case study in groundwater monitoring modeling experiment using data analytics methods in southeast Brazil. A model based on fuzzy logic (with high expert intervention) and three data-driven models (with low expert intervention) are tested and evaluated for aquifer recharge in watersheds. The roadmap approach consists of three issues: (a) data acquisition, (b) modeling and (c) the open-minded (geo)ethical attitude. The level of expert intervention in the modeling stage and model validation are discussed. A search for gaps in the model use is made, anticipating issues through the development of application scenarios, to reach a final decision. When the model is validated in one watershed and then extrapolated to neighboring watersheds, we found large asymmetries in the recharge estimatives. Hence, we can show that more information (data, expertise etc.) is needed to improve the models’ predictability-skill. In the resulting iterative approach, new questions will arise (as new information comes available), and therefore, steady recourse to the open-minded roadmap is recommended. Graphic abstract

scholarly journals International Perspectives on Understanding and Improving Teachers’ Data-Based Instruction and Decision Making: Introduction to the Special Series

2021 ◽  
Vol 54 (4) ◽  
pp. 239-242
Author(s):  
Christine A. Espin ◽  
Natalie Förster ◽  
Suzanne E. Mol
Keyword(s):  
Decision Making ◽  
General Education ◽  
International Perspective ◽  
Series Data ◽  
Instructional Decision Making ◽  
Special Series ◽  
Use Of Data ◽  
International Perspectives ◽  
Based Instruction ◽  
Instructional Decision

This article serves as an introduction to the special series, Data-Based Instruction and Decision-Making: An International Perspective. In this series, we bring together international researchers from both special and general education to address teachers’ use (or non-use) of data for instructional decision making. Via this special series, we aim to increase understanding of the challenges involved in teachers’ data-based instructional decision making for students with or at-risk for learning disabilities, and to further the development of approaches for improving teachers’ ability to plan, adjust, and adapt instruction in response to data.

scholarly journals Teaching with Analytics: Towards a Situated Model of Instructional Decision-Making

2019 ◽  
Vol 6 (2) ◽  
Author(s):  
Alyssa Friend Wise ◽  
Yeonji Jung
Keyword(s):  
Decision Making ◽  
Learning Analytics ◽  
Course Design ◽  
Data Interpretation ◽  
Contextual Knowledge ◽  
Instructional Decision Making ◽  
University Instructors ◽  
Wait And See ◽  
Instructional Decision ◽  
Data Reading

The process of using analytic data to inform instructional decision-making is acknowledged to be complex; however, details of how it occurs in authentic teaching contexts have not been fully unpacked. This study investigated five university instructors’ use of a learning analytics dashboard to inform their teaching. The existing literature was synthesized to create a template for inquiry that guided interviews, and inductive qualitative analysis was used to identify salient emergent themes in how instructors 1) asked questions, 2) interpreted data, 3) took action, and 4) checked impact. Findings showed that instructors did not always come to analytics use with specific questions, but rather with general areas of curiosity. Questions additionally emerged and were refined through interaction with the analytics. Data interpretation involved two distinct activities, often along with affective reactions to data: reading data toidentify noteworthy patterns and explaining their importance in the course using contextual knowledge. Pedagogical responses to the analytics included whole-class scaffolding, targeted scaffolding, and revising course design, as well two new non-action responses: adopting a wait-and-see posture and engaging in deep reflection on pedagogy. Findings were synthesized into a model of instructor analytics use that offers useful categories of activities for future study and support

Improving the use of analytics and big data by changing the decision-making culture

2017 ◽  
Vol 55 (10) ◽  
pp. 2074-2088 ◽  
Author(s):  
Jane Elisabeth Frisk ◽  
Frank Bannister
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Design Approach ◽  
Action Research Project ◽  
Content Type ◽  
Use Of Data ◽  
Support Organizations ◽  
Novel Approach ◽  
Using Data

Purpose Evolving digital technologies continue to enable new ways to collect and analyze data and this has led some researchers to claim that skillful use of data analytics and big data can radically improve a company’s performance, but that in order to achieve such improvements managers need to change their decision-making culture and to increase the degree of collaboration in the decision-making process. The purpose of this paper is to create an increased understanding of how a decision-making culture can be changed by using a design approach. Design/methodology/approach The paper presents an action research project in which the authors use a design approach. Findings By adopting a design approach organizations can change their decision-making culture, increase the degree of collaboration and also reduce the influence of power and politics on their decision-making. Research limitations/implications This paper proposes a new approach to changing a decision-making culture. Practical implications Using data analytics and big data, a design approach can support organizations change their decision-making culture resulting in better and more effective decisions. Originality/value This paper bridges design and decision-making theory in a novel approach to an old problem.

Call for Manuscripts: Assessment

2014 ◽  
Vol 107 (8) ◽  
pp. 639
Keyword(s):  
Decision Making ◽  
Teaching And Learning ◽  
Mathematics Instruction ◽  
Instructional Decision Making ◽  
Curriculum Instruction ◽  
Instructional Decision

Assessment is an integrated part of mathematics instruction that guides and enhances teaching and learning. A key aspect of instructional decision making is the alignment of standards, curriculum, instruction, and assessment. The MT Editorial Panel is interested in manuscripts that address one or more of the following themes related to assessment.

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