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Teacher racial diversity has been widely considered important in education. However, it remains unclear to what extent and how teacher racial diversity has been addressed at the federal, state, and district levels. In this study, we employed text mining to collect and analyze over three million documents at the federal, state, and district levels. We found that while students of color had disproportionately less access to racially diverse teachers, the documents under our analysis insufficiently discussed the recruitment and retention of racially diverse teachers. Our findings also reveal that education agencies at the federal, state, and district levels paid scant attention to recruiting and retaining Hispanic teachers. For the states and districts that discussed the recruitment of racially diverse teachers, they primarily recruited teachers from institutions and organizations that primarily serve people of color, such as Historically Black Colleges and Universities, the Columbia Latino/a Law Student Association, the National Association of Asian American Professionals, and the National Black MBA Association. Given the findings and the projected growth of Black and Hispanic student enrollment in the United States, we provide five policy recommendations for policymakers and leaders to racially diversify the teacher workforce amid shifting student demographics, particularly Hispanic students.

School improvement plans are strategic documents most schools complete on an annual basis. Research on school improvement planning highlights that high-quality plans contribute to student achievement gains, but many plans are of poor quality. Principals serve in a critical role within the school improvement process. In this article, we review research on decision-making and biases to provide a set of recommendations to improve the school improvement planning process. Specifically, we highlight how a set of biases can contribute to flawed planning that reduces the likelihood that the school improvement plan will be comprehensive, strategic, and useful. We also include a set of definitions and "planning guardrails" principals can use when developing a school improvement team and facilitating the school improvement planning process.

The purpose of this study is to investigate policy coalitions of the Every Student Succeeds Act (ESSA) at U.S. congressional hearings. This study is grounded in the advocacy coalition framework, which argues that advocacy coalitions are forged by policy actors who have similar policy preferences. To identify the coalitions, according to the policy claims articulated by policy actors, discourse network analysis was performed to examine 30 testimonies in the congressional hearings on ESSA since its passage in 2015. The policy actors fall into eight categories: (1) federal administrative and executive offices, (2) state administrative and executive offices, (3) teachers unions, (4) interest groups, (5) superintendents, (6) teacher, (7) education professor, and (8) Congress members. The results of discourse network analysis suggest four coalitions based on the actors' policy claims on (1) equity, (2) assessment and accountability, (3) states have changed/passed legislation to align the state accountability systems with ESSA goals, and (4) the U.S. Department of Education's state plan approval was inconsistent with the ESSA statutory provisions. The findings provide timely insights into the ongoing process of ESSA implementation at the federal, state, and local levels

This article provides a critical review of school leaders' data-driven decision making (DDDM), drawing attention to the potential tension between DDDM and moral decision making. With mounting accountability in education, DDDM has been espoused as one of the core values in school leadership. Making a data-driven decision means that school leaders use data to set goals, identify problems, seek and evaluate options, and choose a course of action; whereas moral decision making is about deciding what is right, just, virtuous, and ethical. The two decision-making approaches could be on a collision course if school leaders are situated in an organizational context in which leaders, teachers, and students have competing interests. This article draws upon literature on decision making in multiple disciplines (e.g., psychology, behavioral economics, and cognitive neuroscience) to discuss the potential tension between DDDM and moral decision making. The article concludes with recommendations for school leaders' decision making.

This study examines destructive leadership and its relationship with instructional leadership. Destructive leadership refers to a leader's repeated behaviors that prioritize self-serving interests by undermining organizational interest and at the expense of harming subordinates. A total of 154 teachers completed a survey that measured their principals' destructive and instructional leadership. Results of multiple regression analyses indicate that destructive leadership predicted ineffective instructional leadership. This study called for attention to identifying destructive leaders in school leadership training, hiring, and evaluation.

Purpose: Emotions have a pervasive, predictable, sometimes deleterious but other times instrumental effect on decision making. Yet the influence of emotions on educational leaders' decision making has been largely underexplored. To optimize educational leaders' decision making, this article builds on the prevailing data-driven decision-making approach, and proposes an organizing framework of educational leaders' emotions in decision making by drawing on converging empirical evidence from multiple disciplines (e.g., administrative science, psychology, behavioral economics, cognitive neuroscience, and neuroeconomics) intersecting emotions, decision making, and organizational behavior. Proposed Framework: The proposed organizing framework of educational leaders' emotions in decision making includes four core propositions: (1) decisions are the outcomes of the interactions between emotions and cognition; (2) at the moment of decision making, emotions have a pervasive, predictable impact on decision making; (3) before making decisions, leaders' individual differences (e.g., trait affect and power) and organizational contexts (e.g., organizational justice and emotional contagion) have a bearing on leaders' emotions and decision making; and (4) postdecision behavioral responses trigger more emotions (e.g., regret, guilt, and shame) which, in turn, influence the next cycle of decision-making process. Implications: The proposed framework calls for not only an intensified scholarly inquiry into educational leaders' emotions and decision making but also an adequate training on emotions in school leadership preparation programs and professional development.

Despite abundant data and increasing data availability brought by technological advances, there has been very limited education policy studies that have capitalized on big data--characterized by large volume, wide variety, and high velocity. Drawing on the recent progress of using big data in public policy and computational social science research, this commentary discusses how to approach big data and how big data can be used in education policy research. First, I introduce big data that is potentially relevant to education policy research. I then present methodological frontiers by examining the assumptions, key concepts, merits, and caveats of three commonly used analytical approaches to mining massive amounts of text data: topic models, network text analysis, and sentiment analysis. Next, to ensure the veracity of using big data in education policy research, I debunk three methodological misconceptions. This commentary concludes with a discussion on developing interdisciplinary research capacity and addressing the privacy concerns and ethical conundrums as we explore a research agenda of using big data in education policy.

Opting out of state standardized tests has recently become a movement--a series of grassroots, organized efforts to refuse to take high-stakes state standardized tests. In particular, the opt-out rates in the state of New York reached 20% in 2015 and 21% in 2016. This study aims to illustrate the social networks and examine the paradoxes that have propelled the opt-out movement in New York--the movement's epicenter with the highest opt-out rate in the United States. Drawing on the conceptual frameworks of social movement theory, social network theory, and policy paradox, this study compiled the opt-out corpus by using the data from 221 press-coverage and 30 archival documents. Social network analysis was performed by examining the relational data that suggest coalition ties between movement actors. Further, to explicate how the movement actors forged coalition ties, all data in the corpus were then coded by Stone's framework of policy paradox regarding how the movement goals were articulated, how the movement was framed, and what policy solutions were mobilized. In addition to identifying the movement actors and two competing coalitions, it is found that to forge coalition ties, the movement actors in the opposing coalitions articulated contested goals of standardized testing, framed the movement via symbols, numbers, and interests, as well as mobilized policy solutions via inducements, rights, and power. The findings have important and timely implications for policymakers and movement actors as they seek and advance on common ground to make substantive changes in education policy.

Purpose: Artificial intelligence (AI) refers to a type of algorithms or computerized systems that resemble human mental processes of decision-making. This position paper looks beyond the sensational hyperbole of AI in teaching and learning. Instead, this paper aims to explore the role of AI in educational leadership. Design/methodology/approach: To explore the role of AI in educational leadership, I synthesized the literature that intersects AI, decision-making, and educational leadership from multiple disciplines such as computer science, educational leadership, administrative science, judgment and decision-making and neuroscience. Grounded in the intellectual interrelationships between AI and educational leadership since the 1950s, this paper starts with conceptualizing decision-making, including both individual decision-making and organizational decision-making, as the foundation of educational leadership. Next, I elaborated on the symbiotic role of human-AI decision-making. Findings: With its efficiency in collecting, processing, analyzing data and providing real-time or near real-time results, AI can bring in analytical efficiency to assist educational leaders in making data-driven, evidence-informed decisions. However, AI-assisted data-driven decision-making may run against value-based moral decision-making. Taken together, both leaders' individual decision-making and organizational decision-making are best handled by using a blend of data-driven, evidence-informed decision-making and value-based moral decision-making. AI can function as an extended brain in making data-driven, evidence-informed decisions. The shortcomings of AI-assisted data-driven decision-making can be overcome by human judgment guided by moral values. Practical implications: The paper concludes with two recommendations for educational leadership practitioners' decision-making and future scholarly inquiry: keeping a watchful eye on biases and minding ethically-compromised decisions. Originality/value: This paper brings together two fields of educational leadership and AI that have been growing up together since the 1950s and mostly growing apart till the late 2010s. To explore the role of AI in educational leadership, this paper starts with the foundation of leadership--decision-making, both leaders' individual decisions and collective organizational decisions. The paper then synthesizes the literature that intersects AI, decision-making and educational leadership from multiple disciplines to delineate the role of AI in educational leadership.

Background/Context: Since 2013, opting out of state standardized tests has become a movement--the grassroots, organized efforts to refuse to take high-stakes state standardized tests. In particular, opt-out rates in the state of New York have been consistently fluctuating around 20%. Purpose/Objective: This study aims to examine the actor coalitions and discourse coalitions that have propelled the opt-out movement in the state of New York--the movement's epicenter with the highest opt-out rate in the United States. Conceptual Framework: This study is conceptually grounded in the advocacy coalition framework (ACF), a prominent conceptual lens to investigate the formation of coalitions and their impact on policymaking. The ACF posits that advocacy coalitions are forged by policy actors who have similar policy preferences. By contrast, differences in policy preferences are manifested in the discourse that serves to defend or propose coherent arguments as justifications for policy preferences held by the opposition coalitions. Research Design: This study compiled the Opt-out Discourse Data Set by using data from 323 press articles and 52 archival documents from 2015 to 2018. Each news article or archival document was coded with three variables: movement actors, statements articulated by the actors, and the actors' sentiment toward the statements. An actor-statement bipartite network, an actor coalition network, and a discourse coalition network were created, respectively. Next, Freeman degree centrality was calculated to identify major actors and their statements. The network metrics of density and connectedness of the two competing coalitions were calculated to compare the coalitions' network structure. Findings: In the actor coalition network, the movement advocacy coalition is clearly more densely connected than the movement opposition coalition in terms of the number of actors, coalition density, and coalition connectedness. The discourse coalition network shows similar patterns: the movement advocacy coalition is densely connected, as evidenced by the numbers of nodes in each coalition and the network metrics of coalition density and connectedness. Conclusions/Recommendations: This study concludes with a discussion on how the future of the opt-out movement depends on (1) how the movement advocacy coalition continues to amass power and influence in education policymaking, and (2) how the New York State Education Department exercises its power over implementation of the Every Student Succeeds Act (ESSA). Moreover, this article demonstrates the application of discourse network analysis to examine qualitative data in education research. The discourse network approach is particularly instrumental in explaining a policy output by identifying coalitions and their interactions within and across the coalitions.

In this study, we examined the role of leadership styles and multi-dimensional learner engagement in how students emerge as learning leaders in asynchronous online discussions. Grounded in the conceptual framework of two dominant leadership styles of transformational and transactional leadership, this study applies the two leadership styles--transformational leadership and transactional leadership--to the Leader Identification Method (LIM) which defines three types of leader roles (i.e., full, transactional and attractive facilitator) in online learning. We collected data from 20 students enrolled in a graduate-level online course that required participation in 12-week discussion activities. Results of the longitudinal data analyses show that person-focused, transformational leadership and active participation in online discussions were significant factors that enabled students to emerge as learning leaders. Students are more likely to become leaders by exhibiting transformational leadership behaviour and productively interacting with one another in an online discussion community.

The purpose of this study is to examine the public opinion on the Common Core State Standards (CCSS) on Twitter. Using Twitter Application Program Interface (API), we collected the tweets containing the hashtags #CommonCore and #CCSS for 12 months from 2014 to 2015. A Common Core corpus was created by compiling all the collected 660,051 tweets. The results of sentiment analysis suggest Twitter users expressed overwhelmingly negative sentiment toward the CCSS in all 50 states. Five topic clusters were detected by cluster analysis of the hashtag co-occurrence network. We also found that most of the opinion leaders were those who expressed negative sentiment toward the CCSS on Twitter. This study for the first time demonstrates how text mining techniques can be applied to education policy research, laying the foundation for real-time analytics of public opinion on education policies, thereby informing policymaking and implementation.

Purpose: This review study aims to bridge neuroscience and educational leadership by exploring the neural mechanisms of the constructs relevant to educational leadership. Research Methods: The reviewed literature includes 69 neuroscience studies and 4 books on neuroscience. The brain activities and neurotransmitters associated with the constructs pertinent to educational leadership were coded to bridge the knowledge base of neuroscience and educational leadership. Findings: The neural mechanisms of the constructs related to educational leadership (e.g., vision, charisma, trust, and organizational justice) were organized by four different leadership approaches: charismatic, transformational, destructive, and culturally responsive school leadership. Emotions are the common thread weaving through all four leadership approaches. Implications: This study has salient theoretical, methodological, and practical implications for educational leadership. Theoretically, the findings not only accentuate the role of emotions in educational leadership, but also reveal the trade-off between emotions and analytical calculation in leaders' decision making. Methodologically, the neuroscience methods (e.g., functional magnetic resonance imaging, quantitative electroencephalography, and hormonal analysis) add to the methodological repertoire of educational leadership research. Practically, the findings warrant the emotion training and present the potential of using neurological measurements in school leadership preparation and professional development.

School leadership can be developed and strengthened from many approaches, including, but not limited to, transformational, instructional, distributed, and social justice leadership. This article presents an alternative perspective to develop school leadership from the social network perspectives. Drawing upon the growing body of research on social networks in school leadership, this article elucidates the evidence-based school leadership practices from four facets: social ties, network structure, social influence, and school culture. These four facets influence one another as the school leaders emerge, exercise leadership, and build a nurturing school culture through forging social ties, shaping network structure, and gaining social influence.

Purpose: Given the essential role of theories in research, this study aims to identify the theories and concepts undergirding educational leadership research, illuminate the interconnections among them, and examine the evolution of the theoretical groundings of the field from 2005 to 2014. Methods: This study constructed a concept co-occurrence network, in which the nodes represent all the framing concepts that theoretically framed the 1,328 articles published in four leading educational leadership research journals ("Educational Administration Quarterly," "Journal of Educational Administration," "Educational Management Administration & Leadership," and "Journal of School Leadership") over the past decade and the ties link the concepts that co-occur in an article. The reference frequency and centrality measures were used to identify the influential concepts. Next, the k-core analysis was performed to visualize the interconnections among the concepts. Moreover, a series of network cohesion measures were used to detect the changes in conceptual cohesion over the past decade. Findings: While 295 framing concepts guided the educational leadership empirical studies, a small number of concepts exerted a disproportionately large influence on the research. Furthermore, these influential concepts closely interplay with one another, and the strongest interconnection was seen between the concepts of leadership approaches and organizational perspectives. Last, the increasingly pluralistic theoretical foundation did not yield the growing conceptual cohesion in educational leadership. Implications: This study for the first time elucidates the structure and evolution of the theoretical groundings of educational leadership research, laying the foundation for further theory development and inviting researchers to bring conceptual cohesion to this field through integrating concepts, allowing random ideas to mutate, and developing new theories.

Purpose: The purpose of this study is to describe the underlying topics and the topic evolution in the 50-year history of educational leadership research literature. Method: We used automated text data mining with probabilistic latent topic models to examine the full text of the entire publication history of all 1,539 articles published in "Educational Administration Quarterly" (EAQ) from 1965 to 2014. Given the computationally intensive data analysis required by probabilistic topic models, relying on high-performance computing, we used a 10-fold cross-validation to estimate the model in which we categorized each article in each year into one of 19 latent topics and illustrated the rise and fall of topics over the "EAQ's" 50-year history. Findings: Our model identified a total of 19 topics from the 1965 to 2014 "EAQ" corpus. Among them, five topics--inequity and social justice, female leadership, school leadership preparation and development, trust, and teaching and instructional leadership--gained research attention over the 50-year time period, whereas the research interest appears to have declined for the topic of epistemology of educational leadership since the 2000s. Other topics waxed and waned over the past five decades. Implications: This study maps the temporal terrain of topics in the educational leadership field over the past 50 years and sheds new light on the development and current status of the central topics in educational leadership research literature. More important, the panoramic view of topical landscape provides a unique backdrop as scholars contemplate the future of educational leadership research.

The purpose of this study is to examine the Twitter communication between school districts, superintendents, and the public. Content analysis of the tweets posted by the 100 largest U.S. school districts and those district superintendents was performed to investigate how the districts and the superintendents communicated with the public on Twitter. Next, paired sample f-tests were performed to compare the differences between public sentiment toward the districts and the superintendents. The findings suggest that the districts and their superintendents primarily used Twitter for one-way information broadcasting, leaving Twitter's two-way communication functionality largely untapped. Further, the public expressed significantly less negative sentiment toward the superintendents than the districts, whereas no statistical difference existed in the public's positive or neutral sentiment toward the districts and the superintendents. The findings provide novel insights into educational institutions' and leaders' Twitter communication. More importantly, the findings offer research-based guidance on districts' and superintendents' Twitter communication. Recommendations were provided for districts and leaders to use social media effectively and thus engage the public and garner social support for education.

Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the concerns over data security, privacy protection, and ethical boundaries of accessing personal digital data are discussed. The article concludes with an invitation to education practitioners, policymakers, and researchers to advance our understanding of big data and better serve students in the digital era.

This study investigated the relationship between the leader's gender, leadership position. Twitter use, and influence on information diffusion in the communication network on Twitter. We collected the 30,200 latest tweets of 151 active Twitter users who held educational leadership positions. Results of social network analysis and multiple regression analyses suggest a gender inequality in the leader's influence on information diffusion in the network. Findings also indicate no significant relationship between leadership position (district vs. building) and a leader's influence in the network. Moreover, Twitter following was positively associated with the leader's influence in the network, whereas the number of followers, weekly tweets, and the time of Twitter account creation did not predict the leader's influence. Practical implications on how leaders use Twitter to disseminate information are discussed.

This study examined how Twitter was used by all U.S. state education agencies (SEAs) for public engagement in education. Drawing on the ecological model of communication, this study analyzed the latest 71,913 tweets from 40 SEAs that had official Twitter accounts. The results of correlation analysis indicate no significant relationship between the SEAs' presence on Twitter and the SEAs' targeted Twitter users, denoting that the SEAs' well-intentioned efforts in communicating with stakeholders and the public by using Twitter might fall short of the public's preferable medium for receiving information. In addition, the results of content analysis suggest that the SEAs primarily used Twitter for one-way asymmetrical information broadcasting, leaving Twitter's two-way symmetrical communication functionality largely untapped. Findings are discussed with respect to the implications for educational organizations' effective use of Twitter through the public's increased participation and collaboration.

Purpose: The purpose of this paper is to uncover how knowledge is exchanged and disseminated in the educational administration research literature through the journal citation network. Design/ Methodology/Approach: Drawing upon social network theory and citation network studies in other disciplines, the authors constructed an educational administration journal citation network by extracting all 157,372 citations from 5,359 journal articles in 30 educational administration journals from 2009 to 2013. The authors then performed social network analysis to visualize the network structure by journal clusters, and quantified journal prominence and interdisciplinarity by calculating Freeman indegree and betweenness, respectively. In addition to journal-to-journal citations, the authors examined the sources of non-journal citations by citation counts. Findings: The results of journal prominence, interdisciplinarity, and eight journal clusters in the citation network indicate that educational administration, as a porous field, intimately interacts with the sub-fields of education (e.g. urban education and teacher education), other disciplines (e.g. economics, human resources, sociology, and psychology), and the research internationally. In addition to journals as the knowledge source (45.29 percent), the authors also found books (31.08 percent) and reports (14.98 percent) are important citation sources in the educational administration research literature. The most cited books and reports shed light on the knowledge base in the theory, research, and practice of educational administration. Originality/Value: The results of this by far the largest-scale study of educational administration journals present abundant evidence that educational administration is a porous field. This study also presents social network analysis as an alternative method to evaluate journal influence in the educational administration field.