Why Isn't This Being Studied?

2017 ◽  
pp. 90-108
Keyword(s):  
Decision Making ◽  
Professional Practice ◽  
Information Seeking ◽  
Data Driven ◽  
Information Seeking Behavior ◽  
Data Driven Decision Making ◽  
Academic Librarianship ◽  
Seeking Behavior ◽  
Significant Question

This chapter poses and attempts to answer a significant question regarding emotions research within academic librarianship – namely, why isn't this topic being researched more? Given how emotionally-laden the work is and how emotionally-laden information-seeking behavior can be, it seems surprising that there is a dearth of research on emotion-related issues. Other people-oriented professions like healthcare and hospitality seem very focused on understanding the qualitative experiences of their professionals; in comparison, academic librarianship seems reluctant to tackle the topic. The chapter examines what does exist in the academic librarianship literature regarding emotions and branches out into other disciplines to see how they examine the issue of emotion and its impact on professional practice. The chapter also posits answers for why this topic isn't studied more within academic librarianship, focusing on issues of objectivity and data-driven decision making.

Confirmation of the Data-Driven Decision-Making Efficacy and Anxiety Inventory’s Score Factor Structure Among Teachers

2016 ◽  
Vol 36 (5) ◽  
pp. 477-491 ◽  
Author(s):  
David A. Walker ◽  
Todd D. Reeves ◽  
Thomas J. Smith
Keyword(s):  
Decision Making ◽  
Pacific Northwest ◽  
Factor Structure ◽  
Professional Practice ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Future Directions ◽  
The Pacific ◽  
Confirmatory Factor ◽  
Teacher Needs

The implementation of data-driven decision-making practices (DDDM) is a key component of contemporary teachers’ professional practice. As such, the measurement of DDDM and related constructs is important for multiple purposes in both research and practice (e.g., identifying teacher needs around DDDM, and monitoring teacher change in response to DDDM interventions). With the present study, we examined the score factor structure and reliability of the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA), an existing measure of data-driven decision-making–related self-efficacy and anxiety. Prior work with this instrument has provided some internal structure and reliability evidence in the context of teachers from the Pacific Northwest. Confirmatory factor analysis of 3D-MEA scores from a sample of Midwestern teachers replicates the initially hypothesized five-factor internal score structure. Our study also affords evidence of high score reliability within this population. Limitations, implications, and future directions are discussed.

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