The purpose of this study was to explore the data-driven decision making process within the context of K-12 physical education. Although the topic has received extraordinary attention in other areas of education, it has yet to be investigated directly in physical education settings. A conceptual framework proposed by Mandinach, Honey, Light, and Brunner (2008) guided the investigation. Using a multi-site case study design, one school district previously awarded a Carol M. White Physical Education Program Grant served as the overarching case and eight schools within the district served as embedded cases. Eight physical education teachers, three district coordinators, one principal, and one school counselor participated in the study. Evidence was gathered through interviews, observations, documents, archival records, and artifacts. Analytic strategies such as pattern matching, examining rival explanations, and drawing diagrams were utilized to generate common themes within the data. Overall, findings indicated that physical education teachers collected substantial amounts of physical activity and fitness data aligned with policy requirements, often at the expense of data related to other important teaching domains. Evidence also indicated that teachers rarely transformed collected data into actionable knowledge. It seemed as though teachers were only collecting data because they were required to and held little value in the data once they were collected. Teachers reported that the data collection process was time-consuming and challenges associated with pedometers and information management systems served as barriers to the collection/organization process. In addition, professional development was not utilized to help teachers use data for effective teaching as district coordinators had limited access to teachers on designated professional development days. It is important to note that teachers had substantial concerns surrounding the validity and reliability of the data that were collected. This likely contributed to the low value that was placed upon data. Based upon the findings, ten recommendations for the enhancement of the DDDM process in physical education were generated. One of the most important recommendations is to provide physical education teachers with support in developing data literacy skills so they can take full advantage of the data they collect for the benefit of student learning.
By Lisa Roepe
More companies are relying on data to help them identify challenges, capitalize on opportunities and make timely decisions that could affect their bottom line.
A recent Harvard Business Review study, “The Evolution of Decision Making: How Leading Organizations Are Adopting a Data-Driven Culture,” found companies that rely on data expect a better financial performance. The study, which surveyed 646 executives, managers and professionals from all industries around the global, found many corporations are integrating data capture and analysis into their decision-making processes. In fact, many business executives are enhancing their skills to allow them to integrate analytical tools into their business decision-making practices.
As more companies rely on data to make their most important decisions, earning a Master of Business Administration degree can be a game changer for your career. Utica College offers an online MBA program that features core courses such as data-driven decision making. Designed to be integrated and applied, these courses establish critical thinking and problem analysis for executive decision-making and data-context relevance. The program can be completed in two years of part-time study and many requirements can be completed online, and/or on campus, due to its blended learning format.
Here are examples of how three companies – Google, Amazon and Southwest Airlines – are using data to make decisions that increase their success and profitability.
Google’s name is synonymous with data-driven decision making. The company’s goal is to ensure all decisions are based on data and analytics. In fact, part of the company’s culture is to discuss questions, not pithy answers, at meetings.
Google created the People Analytics Department to help the company make HR decisions using data, including deciding if managers make a difference in their teams’ performance. The department used performance reviews and employee surveys to answer this question. Initially, it appeared managers were perceived as having a positive impact. However, a closer look at the data revealed teams with better managers performed best, are happier and work at Google longer.
The next question Google tackled was what makes a good manager. Google created the “Great Managers Award” to encourage employees to nominate managers they felt made a difference. Employees were required to provide examples of good manager behavior in the nomination application. Google also interviewed managers about their practices.
Using this data, Google established eight behaviors for good managers, as well as the top three reasons managers might struggle in their roles. Google then used this data to measure managers against these behaviors, enact a twice-yearly feedback survey and revise its management-training program.
Ecommerce sites typically use data to drive profits and sales. If you’ve ever shopped at Amazon you have probably received a product recommendation while visiting the Amazon website or through email. This is an example of a data-driven business decision.
Amazon bases its recommendations on what customers have bought in the past, the items in their virtual shopping cart, what items the customer has ranked or reviewed after purchase and what products the customer has viewed when visiting the site. Amazon also uses key engagement metrics such as click-through rates, open rates and opt-out rates to further decide what recommendations to push to which customers.
By integrating recommendations into nearly every aspect of Amazon’s purchasing process, from product browsing to checkout, the company has found that product recommendations, in fact, do drive sales and increase the bottom line.
It’s no secret airlines use data to track customers’ luggage, personalize customer offers, boost customer loyalty and optimize their operations. At Southwest Airlines, executives are using customer data to determine what new services will be most popular with customers and the most profitable. Southwest has found that by observing and analyzing customers’ online behaviors and actions, the airline can offer the best rates and customer experiences. As a result, Southwest has seen its customer and loyalty segments grow year after year.
So make a data-driven decision to see how an online MBA from Utica College can help you advance your career.