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In an ideal world researchers and educators could collaborate to compile a definitive and exhaustive list of characteristics of gifted learners, which then could be used to guide identification, teaching strategies, and curriculum selection for this population. Unfortunately, no such list can or should be created, for one of the unifying themes in research on characteristics of gifted learners is, in fact, the great diversity among them. Gifted and talented learners are not a homogeneous group; to the contrary, they are varied and unique. Despite this diversity, research suggests that there are a handful of traits that may occur with greater frequency in gifted learners than in the general population. In this chapter, some of these characteristics are discussed, with the caveat that it is not the intention to provide a checklist by which students may be identified as either "gifted" or "not gifted." Rather, the intent is to provide educators with an overview of characteristics that may be present in some gifted and high-ability students, and to illustrate how these characteristics may vary based on a variety of factors, including gender, sociocultural group, the presence of a hidden or overt disability, age, and whether a student is achieving or underachieving. By discussing the heterogeneity associated with gifted and talented learners, this chapter may be useful to educators attempting to look beyond rigid stereotypes to more diverse and flexible conceptions of giftedness in a broad spectrum of children and young adults. To begin, the following illustrative case studies are presented. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

It had been said by many educators of the gifted that it is easier to define what differentiation of the curriculum is not than it is to define what differentiation of the curriculum is. Over the years, the concept of differentiating the curriculum for gifted students has changed commensurate to the changes in the definition of giftedness, the contemporary emphasis in general education, and the political and parental responses to general and gifted education. The many definitions of differentiation have resulted in the term becoming a referent for any learning experience that attends to individual differences. In reality, differentiation can be defined by the who—the learner and his or her needs, interest, and abilities; the what—the content and skills of the subject matter to be taught; the how—the pedagogy to be used to teach the content, skills, or both; and the where—the setting, grouping, or both needed to effectively implement the curriculum (the what) to the learner (the who). The original need to differentiate the curriculum for gifted students was based on the recognized strengths of these learners and the acknowledged inadequacy of the regular or core curriculum to meet these needs. The discrepancy theory assesses the core curriculum against the traits of gifted students in order to determine the missing curricular elements that would be responsive to the needs of students. This comparative analysis between the needs, interests, and abilities of gifted students and the content, processes, and product components of the core curriculum traditionally justified the purpose for a differentiated curriculum. To the degree that the core curriculum correlates with the defined attributes of gifted students, it is perceived as either appropriately or inappropriately differentiated. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

The affective characteristics of gifted individuals, as well as the social and emotional needs related to those characteristics, have been well documented by researchers in the field of gifted education (Clark, 2002; Cohen & Frydenberg, 1996; Cross, 2001; Delisle,1987; Roeper, 1995; Silverman, 1993). However, despite the evidence and support provided by the literature, proactive attention to the affective domain is still overlooked in many schools unless that attention is in reaction to some overt problem identified by teachers or the administration (Peterson, 2003). Addressing the affective domain within the curricula is appropriate for all students, but it is essential for gifted students whose affective traits may include divergent thinking, overexcitabilities, sensitivities, perceptiveness, and entelechy (Lovecky, 1992). In order to meet the program standards set forth by NAGC, gifted programs must incorporate the affective domain. Specific strategies to meet students' affective needs can be integrated into any subject area through individual activities, lessons, curricular units, or separate units. It is essential, however, that teachers who endeavor to address the affective aspects of giftedness be willing to follow up on issues that are inadvertently revealed. Whenever classroom activities touch upon the affective realm, it is important to remember that most teachers are not trained counselors. Teachers may not be prepared for all that is disclosed. A support system must be in place in the form of school counselors, school psychologists, and/or therapists. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

My perspective on an affective curriculum in education for gifted students is colored by my clinical experiences as a counselor, including those as a counselor of gifted children, adolescents, and adults. During my last 5 years as a teacher in K-12 education, I directed a complex program for gifted high school students, which included an emphasis on affective concerns (Peterson, 1990). Ten discussion groups per week, geared almost entirely to social and emotional development and involving 115 students per year, taught me a great deal about nonacademic concerns of highly able students. The program actively sought out gifted underachievers, who became approximately 30% of total participants and were articulate contributors in the groups as well. Later, I facilitated several similar groups for diverse gifted middle school students, counseled gifted children and adolescents and their families in a clinic geared to giftedness, and also worked with medical students and others with high ability in private practice. The individuals I met while doing ethnographic research on perceptions of giftedness in nonmainstream cultures educated me further. I also sometimes encountered gifted individuals as a counselor in two substance-abuse treatment centers, in an alternative school for expelled high school students, and as a substance-use evaluator in a K-12 school district. Currently I prepare counselors for work in K-12 schools and advise and supervise many highly capable graduate students. These varied clinical experiences with gifted individuals inform this chapter. (PsycInfo Database Record (c) 2025 APA, all rights reserved) (Source: chapter)

This chapter focuses on the influence of multiple intelligences (MI) theory in special and gifted education in Australia. In both contexts, the MI impact is evident in changes of teachers' attitudes and practices toward these students. In gifted education, MI has provided a means to more broadly define and identify giftedness in students across all economic and cultural groups. It has also influenced the design of curriculum materials for gifted students. In special education, MI teachers have transcended a deficit approach; they have become more positive toward students and recognize a wider range of learning potentials. Through the framework provided by MI theory, teachers have learned to genuinely value and appropriately respond to the diversity of learners in integrated Australian classrooms. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

Research shows that gifted girls, in general, are underserved and their talents underidentified. This insightful resource helps educators discover and strengthen, gifted female students' potential and promote their healthy intellectual, psychological, and emotional growth. Each chapter examines a different aspect of female development, provides a reflective exercise for applying the material to professional practice, and presents helpful strategies for teachers, counselors, and parents. This vital guide includes appendices of mentoring programs, curriculum enhancers, Web resources, and research on the importance of fostering female gifted education, giving voice to gifted females and their unique developmental needs. (PsycINFO Database Record (c) 2016 APA, all rights reserved) (Source: cover)

Gifted students often develop faster intellectually then socially and emotionally, resulting in feelings of isolation or inadequacy. This book provides educators with a window into the world of the gifted child, discusses how to develop the talents of gifted children with consideration for their unique needs, and suggests ways to help great kids become greater. Written by gifted education expert Dorothy A. Sisk, this practical resource offers techniques, strategies, and lessons to help gifted students bridge the gap between their cognitive and social-emotional development. (PsycINFO Database Record (c) 2016 APA, all rights reserved) (Source: cover)

Although the concept of leadership is often studied, researched, and discussed. The art of leadership is still misunderstood, debated, and often neglected. It is known, however, that leadership skills can be developed and more intentional endeavors must be made to cultivate bright, young leaders for the future. Developing Leadership Potential in Gifted Students offers insight into developing leadership skills in gifted students and provides definitions and theories of leadership, looks at trends and changing paradigms, and suggests screening and identification tools for leadership, as well as instructional programs and materials to incorporate into the regular curriculum. (PsycINFO Database Record (c) 2016 APA, all rights reserved) (Source: cover)

The editors envision this volume as a handbook for researchers in psychology and education who target exceptional populations in their work, and particularly individuals exhibiting gifts and talents. The research tools described here can help to move the scholarship on giftedness and talent development to a new level of rigor and encourage the testing of program models, as well as predictive validity of theoretical or conceptual frameworks (see for example Sternberg & Davidson, 2005). Of course, the methods described in these chapters can also be usefully applied in general populations or in studies dealing with specialized subpopulations other than gifted and talented. The scholars who contributed to the first nine chapters of this volume are pioneers in the field of measurement and statistics, and they show us most elegantly how the methodologies they have mastered or developed can apply to samples that, by their nature, make statistical analysis more challenging. We tasked our contributors to address the following four barriers, and one facilitator, associated with gifted education research: Definitions of giftedness and talent are not standardized; Test ceilings can be too low to measure progress or growth; Comparison groups are difficult to find for extraordinary individuals; Participant attrition in longitudinal studies may compromise tests of hypothesized effects; and, Qualitative research conducted with gifted populations can be enhanced due to highly articulate study participants. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: introduction)

Especially gifted and creative people are in relatively short supply, but are also very interesting. Because Q-technique factor analysis is especially suited for the intensive study of a small number of especially interesting people, Q-technique factor analysis is especially suitable for inquiry about giftedness and creativity. The purpose of the present chapter is to provide a primer on using Q-technique factor analysis in the intensive study of gifted or creative people, or other especially interesting people. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

Asher (1986) identified two factors that limit theory development and validation in gifted education research: imprecise measurement and small numbers of participants. He made this important point: “These two factors...combine to insure (sic) that results are obscure and that statistical significance is difficult to obtain” (p. 7). Asher was right about statistical significance being difficult to obtain: In fact, it may well be an unnecessarily difficult hurdle. The fact that p < .05 is difficult to obtain is only really a problem if statistical significance is considered the only acceptable evidence of result noteworthiness. In this chapter, I argue that it should not be and that falsely equating statistical significance with result noteworthiness has serious consequences. To demonstrate this, I draw lessons from other disciplines. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

Factor analysis is often used to summarize relationships among many variables into a manageable, smaller set of factors. The methodology is frequently employed in instrument development and assessment of score validity, but it has other applications as well. This chapter reviews some common applications of factor analysis, provides an accessible treatment of how to conduct and interpret the analysis with a heuristic example, and discusses some potential benefits and problems that may be faced when conducting factor analysis in the study of giftedness. Factor analysis has enjoyed a long history of use across the social sciences. With most approaches, factor analysis is employed when researchers seek to reduce many variables to a smaller set of factors. The factors can then be thought of as a synthesis, or representation, of the many variables from which the factors were created. There are other uses of the methodology, such as Q-technique factor analysis, which can be used to identify types of people (see chap. 2, this volume), but most often variables are the subject of the analysis and therefore are the focus of this chapter. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

Bias attributable to missing data conditions is often ignored by applied researchers. In response, journal editors (e.g., von Elm et al., 2007) and governing bodies (e.g., Wilkinson & APA Task Force, 1999) are increasingly calling for missing data analysis as routine assessment. The term missing data is traditionally used in reference to the condition of a study participant missing one or more, but not all, survey responses, test items, or other data points. In addition, methods to control the bias resulting from nonequivalent comparison groups could be viewed as a “missing data” scenario (Dates & King, 2009), though in this chapter we emphasize the former. Consideration of the effects of missing data is critically needed in studies of giftedness. Frequent causes of missing data include study dropouts in longitudinal studies of children through adolescence and adulthood and incomplete data records due to oversight on the part of respondents, refusal to answer certain questions, or a host of other reasons. Missing values can sometimes be safely ignored if observed for only a very small percentage of items. Yet even a few omitted responses can significantly bias results if the data are missing systematically. For example, consider a hypothetical study of 10,000 children in which 5% are categorized as gifted. Observing a modest missing data rate of 2% may nonetheless be of concern should the absent values all fall within the gifted population (i.e., 40% of gifted children would have missing data). In such an instance, ignoring missing values or applying ineffective adjustments may drastically alter study outcomes and lead to invalid conclusions. It is therefore imperative that giftedness researchers carefully examine the consequences of even modest amounts of missing data and familiarize themselves with best practices for handling these conditions. This chapter proceeds by briefly describing a typology for categorizing missing data. We then provide a review of the strengths and weaknesses of a number of traditional and contemporary methodologies for handling missing data, followed by discussion and detailed application of a new, “hybrid” approach that is capable of adjusting for both item-level missing data and missing cases in a nonequivalent groups design, a scenario frequently faced by the applied researcher. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

This chapter focuses on students with a unique profile of being strong in nonverbal areas but much lower in verbal abilities, a group that is surfacing with some regularity now that nonverbal tests are being used more frequently in schools. This particular group is included in the discussion of low-income gifted because of the prevailing view that strong nonverbal aptitudes are found in culturally different youngsters (e.g., Native Americans, African Americans, English language learners). We know that culturally different children often are found in poverty at higher rates, so discussion of this subset of gifted learners offers the opportunity to learn more about how to recognize and nurture giftedness in underserved groups. A literature review exploring aspects relevant to this special population opens the chapter. Aspects of the review include a working definition of high nonverbal, low verbal giftedness; identification route influences; student performance; and learning needs and supports, styles, and preferences. Drawing on case study findings of special needs gifted learners, this chapter discusses unique characteristics, educational needs, learning opportunities, and similarities/differences in student, parent, and teacher perspectives found in this special needs group. Examples and quotations from student vignettes illustrate these perspectives. Through integration of the literature and the case study findings, this chapter then provides ideas for school-based practitioners and gifted coordinators in the development of gifted high nonverbal, low verbal children. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

To understand and better serve the needs of the gifted, the field must produce quality research to inform practice. Far too often, recommendations in the field of gifted education are based on conventional wisdom or anecdotes instead of data-driven research. This book provides accessible introductory treatments of several modern analytic methods that can be used to advance our knowledge within the field of gifted education. It also alerts researchers about potential pitfalls of inferential statistics in general as well as analytical areas of particular concern within the field of giftedness. As someone who is passionate about both gifted education and research methodology, I am honored to be able to provide some comments about the techniques contained in this volume and to provide thoughts about future methodological directions for our field. This chapter contains three sections. First, I describe some of my own research within the field of gifted education. Then, I briefly describe studies that I am planning or contemplating that utilize some of the methodologies described in this book. Finally, I offer some thoughts on methodological issues that researchers in the field of gifted education should consider as they are planning their studies. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

The history of hierarchical linear models generally traces its roots back to the work of Robinson (1950) in recognizing contextual effects. The discovery that Robinson made is sometimes thought of as the “frog pond” theory and is fairly simple to relate. Suppose that a researcher was conducting an analysis on environmental factors affecting the weight of frogs. And also suppose that two of the frogs being analyzed both weighed 500 grams. However, the first frog that weighed 500 grams was drawn from a pond where it was the largest frog in the pond. The second frog that weighed 500 grams was drawn from a lake where 500 grams was the weight of the average frog for that pond. In a typical ordinary least squares (OLS) analysis, the researcher would have no way of honoring the pond nesting structure for these two frogs and would then erroneously assume that the environmental factors affecting frog growth were the same regardless of which pond was home to the frog. This same problem often presents itself when researchers are analyzing data obtained from school research. For example, suppose that a researcher were to try to run a regression analysis in which student grade point average (GPA) scores were used to predict performance on the Stanford Achievement Test (SAT). It stands to reason that, within a given school, GPAs might be good predictors of SAT scores where higher GPAs correlate with higher scores on the SAT. However, across schools, the relationship between GPA and SAT may be dramatically different. Whereas in a low-performing school, a student with a 4.0 GPA might score only a 1,000 on the SAT, a student with a 4.0 GPA in an elite, high-performing private school might score a 1,600 on the SAT. This happens because GPA scores are not independent of the school from which they are drawn. This problem of independence of observations is often a factor when collecting data in schools, yet until the development of hierarchical linear modeling (HLM), no methods for dealing appropriately with such data existed. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

Given my interest in statistics and design, I was pleased to be able to read the chapters in Parts 1 and 2 of this book and think about applying the concepts within them to my own work. I am going to respond to the earlier chapters from two different perspectives—as a former editor of two of the major journals in the field of gifted education and as a current reviewer for several others, and as a researcher in the field of gifted education. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

In this chapter, I argue that researchers of giftedness should shift emphasis from null hypothesis significance testing (NHST) to confidence intervals (CIs) and other preferred techniques. I start with a brief summary of arguments put forward by statistical reformers and describe basic features of CIs. I then report a small survey of current statistical practices in giftedness research and a comparison with practices in psychology generally. The main part of the chapter is a discussion of p values and CIs in relation to replication; I focus on the Pearson’s r correlation, because r is so widely used in giftedness research. A simulation demonstrates the large variability in r, and even greater variability in p values, over replications of a simple experiment. Calculations confirm that a p value gives only very vague information about replication, and therefore any p value could easily have been very different, simply because of sampling variability (Cumming, 2008). The severe deficiencies of p values in relation to replication give an additional strong reason for giftedness researchers to turn from NHST and pursue statistical reform with vigor. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

The chapters in Parts 1 and 2 of this book provide considerable detail about myriad approaches to quantitative and mixed method research designs and important issues to consider when using those designs. The authors build a compelling case for the importance of using those designs in moving the research base in gifted studies toward greater sophistication. The first author’s awareness of the need to enhance the literature base by incorporating increasingly sophisticated research approaches crystallized in November 1997 at the National Association of Gifted Children conference just after a symposium on research methodology had ended, when Laurence J. Coleman, Michael Pyryt, and I stood talking about the session. I asked Michael if he thought the field of gifted studies was ready to move in a postpositivistic direction. As he was known to do, he thought about what I had asked him and carefully responded with his own question: “How can the field of gifted studies become postpositivistic when our research base is still prepositivistic?” That was Michael’s way of critiquing our field as being reliant on too many studies that were theoretically unsound and poorly conducted. The symposium had emphasized the epistemological and ontological assumptions of qualitative and quantitative approaches to research. Arguments were made during the session for the utility of both approaches, but with an emphasis being placed on the limitations of each in terms of the nature of the research questions that can and cannot be addressed by either. While few academics these days still question the usefulness of either quantitative or qualitative research (see Capraro & Thompson, 2008; Larabee, 2003), what Michael did in few words was summarize the research in the field of gifted studies circa 1997. This book is intended to be both a catalyst and a primer for future research in gifted studies to help us move from prepositivistic to positivistic and postpositivistic approaches. Michael would be pleased. In this chapter, we describe the various research approaches we have utilized over the years, including both qualitative and quantitative techniques. Other chapters in this volume have provided fodder for additional discussions about our research. As a result of the ideas generated by our fellow authors in this volume, we propose an enhancement to our existing research through the use of structural equation modeling (SEM) as described by Kline in chapter 7 of this volume. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)

Generating accurate and reliable data is critical to strong scientific inquiry and essential to furthering giftedness research yet is often neglected by even the most attentive researchers. From a measurement standpoint, much of the focus has been on the question of score validity (i.e., do assessments accurately identify gifted and talented students?) and test fairness (e.g., do assessments provide an unfair advantage based on socioeconomic status, race, ethnicity, culture, language, and other contextual factors that may affect assessment results?). Although valid and fair measurement is certainly a goal within the larger fields of both measurement and giftedness research, before score validity and test fairness can be addressed, instruments must first generate consistently repeatable and replicable scores. If a measure cannot generate reliable scores across the population for which the measure is intended, it will not be able to generate valid scores. The ability of a measure to generate repeatable, consistent scores is a psychometric concept known as reliability. This chapter’s purpose is to explain the integral role of score reliability and reliability generalization across studies in advancing both the science of giftedness and the practice of identifying and measuring the progress of students that are gifted. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: chapter)