This may be the author’s version of a work that was submitted/acceptedfor publication in the following source:

White, Sonia, Graham, Linda, & Blaas, Sabrina(2018)Why do we know so little about the factors associated with gifted under-achievement? A systematic literature review.Educational Research Review, 24, pp. 55-66.

This file was downloaded from: https://eprints.qut.edu.au/116773/

c© Consult author(s) regarding copyright matters

This work is covered by copyright. Unless the document is being made available under aCreative Commons Licence, you must assume that re-use is limited to personal use andthat permission from the copyright owner must be obtained for all other uses. If the docu-ment is available under a Creative Commons License (or other specified license) then referto the Licence for details of permitted re-use. It is a condition of access that users recog-nise and abide by the legal requirements associated with these rights. If you believe thatthis work infringes copyright please provide details by email to qut.copyright@qut.edu.au

Notice: Please note that this document may not be the Version of Record(i.e. published version) of the work. Author manuscript versions (as Sub-mitted for peer review or as Accepted for publication after peer review) canbe identified by an absence of publisher branding and/or typeset appear-ance. If there is any doubt, please refer to the published source.

https://doi.org/10.1016/j.edurev.2018.03.001

1

Why do we know so little about factors associated with gifted underachievement?

A systematic literature review

2

Abstract

International comparisons of student achievement are generating renewed interest in the academic

underperformance of intellectually gifted students, however, government responses to this problem are

seldom grounded in empirical research evidence. This may be due to the quantity, type and quality of

available research, which can make it difficult to distinguish factors that are associated with gifted

underachievement. In this systematic review, we examine the methods used to identify both giftedness

and gifted underachievement in empirical research investigating factors associated with gifted

underachievement, and identify the factors this research associates with gifted underachievement.

Findings reveal that most studies investigating factors associated with gifted underachievement do not

employ research designs capable of distinguishing differences between gifted achievers and

underachievers. Of the studies that did employ appropriate research designs, the methods used to

identify giftedness and gifted underachievement differed widely and most focused on individual factors

with much less focus on school-related factors.

Keywords: identification, methods, factors, gifted underachievement.

3

1. Introduction

Interest in gifted underachievement has increased over the last decade, due to a number of

converging influences. These include shifts in the nature of the global economy and rapid advances in

technology, which have led to major changes in the type and availability of work in many developed

countries (Manyika, Chui, Bughin, Dobbs, Bisson, & Marrs, 2013). These changes have significant

implications for international competitive advantage and future prosperity (Wood, 2003), with 75% of

the fastest growing occupations now requiring skills and knowledge from the science, technology,

engineering and mathematics (STEM) disciplines (Office of the Chief Scientist, 2014). Reports that up

to 40% of current jobs will be lost to automation within the next two decades (Florence & Partland,

2015), and that students in the United States, England and Australia lag behind their Asian peers in

subjects critical to technological innovation (Sellar & Lingard, 2013), have fueled anxiety in nations

still experiencing the after-effects of the Global Financial Crisis (GFC).

Australia, for example, has witnessed decline across cycles of the OECD’s Programme for

International Student Assessment (PISA), both in terms of mean scores1 and in the percentage2 of “top

performers” in scientific, reading and mathematical literacy (Thomson, De Bortoli, & Buckley, 2013;

Thomson, De Bortoli, & Underwood, 2016). This decline in higher achievement levels is considered

partly responsible for Australia’s fall in the international PISA rankings (Bita, 2016). This fall has

occurred alongside stagnating achievement in Australia’s National Assessment Program in Literacy

and Numeracy (NAPLAN) and despite significant additional investment in school education (Browne

& Cook, 2016). Together, these events have prompted calls from government and business for schools

to “stretch the gifted” (Parkinson, 2016) by increasing academic demand, mandating the study of

science and mathematics through to the end of senior secondary school, recruiting and training more

specialist teachers, and requiring universities to reinstate prerequisites, particularly in mathematics,

physics and chemistry (Aubusson, 2016; Office of the Chief Scientist, 2014).

4

This is not the first time that the pressures of globalization and economic competitiveness have

led to increased focus on the academic achievement of students of high intellectual ability. Reis and

McCoach (2000), for example, described how the Soviet launching of Sputnik in 1967 unleashed

significant anxiety in the United States concerning the ability of young Americans to remain leaders in

technological innovation and to therefore maintain that nation’s economic dominance and future

prosperity. That anxiety has increased in recent years due to the rapid rise of China and the rebalancing

of global economic and military power since the 2008 GFC (Kell & Kell, 2016). The view that

academic achievement is the key to future competitiveness – and that American preeminence is under

threat – is reflected in the rhetoric infusing federal education policy reports, acts and funding

initiatives, such as “Race to the Top” (U.S. Department of Education, 2009). Indeed, on the release of

the PISA 2009 results – in which Shanghai’s students topped the world – President Obama drew a

parallel to America’s first educational achievement “wake-up call”, stating: “Fifty years later, our

generation’s Sputnik moment is back” (Dillon, 2010, np.).

Anxiety over future competitiveness and prosperity may have succeeded in focusing greater

media attention on the performance of highly able students in international student assessments,

however, the issue of gifted underachievement remains under-researched and poorly understood.

Factors contributing to the underachievement of intellectually gifted students – particularly the factors

that have been identified through the type of empirical research necessary to find differences between

achieving and underachieving gifted students – are seldom examined in the discussions around

declining results. This leaves a large margin for error in the development of policy solutions, allowing

room for populist or ideological responses that may have little to do with associated factors and which

may even exacerbate gifted underachievement. For this reason, it is critical to review which factors

have been identified as associated with gifted underachievement in recent empirical research literature,

especially given the scale and speed of changes in school education since, for example, the

5

development and uptake of smart technologies, such as iPads, beginning in the mid-2000s. We begin

this systematic review by defining giftedness and gifted underachievement, followed by a consideration

of the methodological challenges faced by researchers seeking to investigate this problem. We then

outline our three research questions and the method underpinning this study.

2. Defining Giftedness and Gifted Underachievement

Giftedness, as defined by Subotnik, Olszewski-Kubilius and Worrell (2012) is “performance

that is clearly at the upper end of the distribution in a specific talent domain even relative to other high-

functioning individuals in that domain” (p. 176). It is developmental (Reis & Renzulli, 2009), in that

potential is the earliest indicator of giftedness and achievement is its expression (Plucker & Callahan,

2014). Gifted underachievement is said to occur when there is “severe discrepancy between expected

achievement (as measured by standardized achievement test scores or cognitive or intellectual ability

assessments) and actual achievement (as measured by class grades and teacher evaluations)” (McCoach

& Siegle, 2003, p. 4), and where there are no diagnosed learning disabilities to account for those

discrepancies (McGee, 2013). Defining giftedness and gifted underachievement is a relatively

straightforward exercise (Reis & McCoach, 2000). However, empirically determining their existence

in a research population is far more challenging.

Gifted education research is currently complicated by the lack of universally accepted protocols

guiding the identification of both intellectual giftedness and gifted underachievement (Stoeger, Ziegler,

& Martzog, 2008). As there are no consistent identification methods, researchers currently include and

exclude participants using a variety of criteria and measures (Francis, Hawes, & Abbott, 2016). These

measures may include tests of cognitive ability, such as the Wechsler Intelligence Scale for Children

(WISC) and Raven’s Standard Progressive Matrices (Raven’s SPM), and/or tests of academic

achievement, such as the Scholastic Aptitude Test (SAT; Lohman, 2012). However, each of these

assessments measure different aspects of intelligence. For instance, cognitive ability tests range from

6

exclusively non-verbal tasks to a mix of both verbal and non-verbal tasks (Worrell, 2013), while

academic achievement tests may include verbal tasks (e.g., reading) to measure content knowledge or

skills in an academic domain (Missett & Brunner, 2013). Measurement inconsistencies, however, lead

to variation in the number and type of students participating in gifted education research, which affects

the comparability, validity and applicability of research findings (Francis et al., 2016). The resultant

diversity in study criteria, participants and findings weakens the evidence base upon which the

development of appropriate policies and support for gifted underachievers depends.

To reliably identify factors associated with gifted underachievement, researchers must

understand how intellectually gifted underachievers differ from intellectually gifted achievers

(McCoach & Siegle, 2003). If these groups are not compared, then researchers have no way of

knowing whether the variables they are assessing are common to gifted underachievers or common to

gifted students overall. Test anxiety is a good example of a variable that can be easily misunderstood,

if the two groups are not carefully compared. For example, gifted achievers may experience test

anxiety as a positive form of motivation, leading them to increase effort, whereas gifted underachievers

may experience test anxiety negatively, leading them to decrease effort (Pekrun, 2006). Empirical

studies that examine the differences between groups of intellectually gifted students – those achieving

at their estimated potential and those underachieving relative to their potential – are therefore necessary

to reliably identify factors associated with gifted underachievement.

The aim of this review is to contribute to the research literature by investigating the methods

used to identify intellectual giftedness and gifted underachievement in empirical research investigating

factors associated with gifted underachievement, and to learn which factors this research associates

with gifted underachievement. Specifically, this review addresses the following three research

questions:

7

• Which methods are used to identify giftedness in empirical research investigating factors

associated with gifted underachievement?

• Which methods are used to identify gifted underachievers in empirical research investigating

factors associated with gifted underachievement?

• Which factors do these studies find associated with gifted underachievement?

3. Method

This literature review follows the Preferred Reporting Items for Systematic Reviews and Meta-

Analyses (PRISMA) guidelines to systematically and explicitly screen studies in a rigorous and

unbiased manner (Moher, Liberati, Tetzlaff, & Altman, 2009). The PRISMA flow diagram (Figure 1)

conveys the different phases of this systematic literature review from the number of records identified

through to those included and excluded (with reasons). Data were collected from empirical articles

involving two groups attending either elementary or secondary school: high-achieving intellectually

gifted students and underachieving intellectually gifted students. Articles published in peer-reviewed

academic journals between January 2005 and August 2015 were examined to capture the most recent

empirical research relating to gifted underachievement.

With the support of a university research librarian, databases were selected to capture empirical

research on gifted underachievement. A keyword search was conducted in eight databases including

A+ Education, Academic Search Elite, Education Source, ERIC, ProQuest – Education (Education

Journals), ProQuest – Social Science Journals, PsycINFO, and Primary Search. The search terms

were discussed and agreed upon by all authors to ensure relevant empirical research articles were

located. For the purposes of this systematic review, the important search terms were: gifted (and

related), underachievement (and related), and school (and related) (see Table 1 for exact terms). These

search terms were applied for each of the eight databases separately.

8

Table 1 Search Terms used for Systematic Search Search terms with Boolean Operators (in Abstract) gifted* OR talent* OR “high abilit*” OR bright OR “high achiev*” AND underachiev* OR “fail*” OR “poor performance” OR “academic fail*” OR “school difficult*” AND student* OR child* OR adolescen* OR “primary school” OR “elementary school” OR “high school” OR “middle school” OR “secondary school”

3.1. Inclusion and Exclusion Criteria

The initial search of eight databases identified 957 records (Figure 1). Duplicates were

removed and the remaining 490 records were screened by reading the title and abstract. At this

screening stage, records were excluded if they were (a) not in English, or (b) not about gifted students,

or (c) were not reporting an empirical study (e.g. review, commentary, editorial, or discussion of

policy). Following this initial screen, 113 records remained. An additional empirical article was

identified during the screening process (Figg, Rogers, McCormick, & Low, 2012). This article was

cited in the abstract of three records identified during the database search (Figg, 2012; Flint &

Ritchotte, 2012; Peters, 2012) and the original article was included for full-text assessment. All 114

full-text articles (113 + 1) were then assessed for eligibility (Figure 1). More detailed

inclusion/exclusion criteria were then applied to these articles. Articles were excluded if: (a) the full

text was not in English, (b) the article was a non-peer reviewed conference proceeding, commentary, or

thesis not resulting in or linked to a peer-reviewed empirical article, (c) the article did not report on

empirical research, or (d) participants were not gifted students in elementary or secondary school; e.g.,

studies that focused on adult learners or teacher perspectives were discarded. Further articles were

excluded if: (e) the article did not report specific criteria guiding gifted identification, (f) the article did

not specifically identify gifted students and gifted underachieving participants and compare these

groups in analyses, (g) the article was evaluating a test or program for gifted students, (h) participants

were twice exceptional, or (i) the article did not investigate/report on factors related to gifted

9

underachievement. After assessing the 114 full text articles, only nine articles fitting the eligibility

criteria remained and these were analyzed in the review.

Figure 1 PRISMA flow diagram demonstrating identification and screening stages and included articles

4. Results

The nine articles analyzed in this systematic review represent samples of intellectually gifted

students from four different countries (Australia, Germany, New Zealand and the United States). Eight

of the nine articles reported quantitative research with only one article (Reis, Colbert & Hébert, 2005)

adopting a qualitative approach in the form of a comparative case study. The articles using quantitative

analysis often combined multiple techniques, however, analysis of variance and correlations were the

10

dominant statistical approaches. A minority used regression analyses, confirmatory factor or path

analysis. In all articles, at least one analysis distinguished gifted achievers from gifted underachievers

to enable group comparison and investigation of factors associated with gifted underachievement.

4.1. Methods Used to Identify Giftedness

The majority of the nine articles (n=6) meeting our inclusion criteria relied on only one measure

to identify intellectually gifted students (e.g., WISC-R, Raven’s SPM, BIS-HB, CFT, OLSAT). The

remaining three articles identified gifted students using multiple measures or multiple sources of

information (see Table 2). Abu-Hamour and Al-Hmouz (2013), for example, used non-standardized

measures of academic achievement and general ability, whereas Ritchotte et al. (2014) used multiple

standardized measures to assess both cognitive ability and academic achievement. Reis et al. (2005)

used multiple qualitative criteria, including participation in a gifted program, teacher/counsellor

nomination, prior achievement at a superior level, and awards for academic achievement. After this

initial selection, performance in standardized intelligence tests or standardized achievement tests were

used as the primary identifier of giftedness.

Table 2 Overview of Measures and Criteria for Identifying Gifted Students # Study Measure Criteria 1 Abelman (2007) WISC-R

Above average IQ

2 Abu-Hamour and Al-Hmouz (2013)

State Selective High Schools Test: English Mathematics General ability Elementary School Achievement: English Mathematics

Total score must be above 160 (not standardized) Elementary school's assessment performance in English, Mathematics

3 Dixon et al. (2006)

WISC-R ≥ 125

4

Figg et al. (2012) OLSAT ≥ 130

11

Note.Weschler Intelligence Scale for Children – Revised (WISC-R); Raven’s Standard Progressive Matrices (Raven’s SPM); Otis-Lennon School Ability Test (OLSAT); Academically or intellectually gifted (AIG); Berliner Intelligenzstrukturtest für Jegendliche: Begabungs- und Hochbegabungsdiagnostik (BIS-HB); Culture Fair Intelligence Test (CFT)

Seven of the nine articles identified gifted students using both verbal and non-verbal tasks,

whereas the remaining two articles identified gifted students purely on their non-verbal cognitive

abilities (Obergriesser & Stoeger, 2015; Stoeger et al., 2008). Of the articles that reported the use of

standardized measures, five identified gifted students with a criterion that was between one and two

standard deviations above the mean (Table 2). In general, studies that combined both verbal and non-

verbal measures employed higher cut-off criteria (closer to two standard deviations above the mean)

than those using only non-verbal measures.

4.2. Methods used to Identify Gifted Underachievement

The percentage of gifted students identified as underachieving in the nine articles meeting our

inclusion criteria was also variable. In the six articles reporting secondary school samples, between 9%

and 23% of gifted students were identified as underachieving, compared to 16% and 28% in the four

5 Obergriesser and Stoeger (2015)

Raven’s SPM ≥ 90th percentile

6 Reis et al. (2005) Intelligence or achievement tests (various)

> 90th percentile at some stage during school career

7

Ritchotte et al. (2014)

Intelligence test (various) National aptitude test K-2 National achievement test

Must meet one of the three following criteria: (a) ≥ 95th percentile on IQ test (b) Nationally normed IQ/aptitude and achievement tests (sum of percentiles ≥ 180). (c) Aptitude test ≥ 93rd percentile AND achievement test ≥ 93rd percentile AND at least one year above grade level

8

Schick and Phillipson (2009)

BIS-HB ≥ 115

9 Stoeger et al. (2008) CFT ≥ 85th percentile

12

articles reporting elementary school samples (see Table 3). Although the study by Reis et al. (2005)

reports an underachievement identification rate of 49%, this was due to the use of a purposive sample

to enable a comparative case study with two even groups.

Table 3 Overview of Identified Articles on Gifted Underachievement. NR = Not reported.

# Study

Total number identified as gifted

[Females, Males]

Number of gifted underachievers

(% of Total gifted)

[Females, Males]

Grades represented in

sample Country

1 Abelman (2007)

402 [NR]

105 (26%) [NR]

Grades 2, 5, 8 United States

2 Abu-Hamour and

AlHmouz (2013)

197 [96, 101]

39 (20%) [NR]

Grades 10, 11 Australia

3 Dixon et al. (2006) 41 [NR]

7 (17%) [NR]

Grade 7 New Zealand

4 Figg et al. (2012) 93

[0, 93] 21 (23%)

[0, 21] Grades 8, 9, 10 Australia

5 Obergriesser and Stoeger (2015)

85 [54, 31]

24 (28%) [13, 11]

Grade 4 Germany

6 Reis et al. (2005) 35 [14, 21]

17 (49%) [5, 12]

Grades 9, 10 United States

7 Ritchotte et al. (2014) 156

[85, 71] 25 (16%)

[NR] Grades 6, 7 United

States

8 Schick and Phillipson (2009)

1366 [NR]

127 (9%) [NR]

Grade 9 Germany

9

Stoeger et al. (2008) 128 [57, 71]

31 (24%) [NR]

Grade 4 Germany

13

All nine articles meeting our inclusion criteria conceptualized gifted underachievement using a

discrepancy model, where students who are identified as gifted demonstrate lower than expected

achievement relative to cognitive ability. To identify gifted underachievers, all nine articles reported

on measures of achievement (Table 4) with most assessing multiple subject areas. Only one study

restricted assessment of underachievement to a single domain: mathematics. The type of achievement

measure (e.g., GPA, standardized achievement tests, student or teacher rankings), as well as the

discrepancy metric (e.g., above or below a specific percentile, rank, score, standard deviation or GPA),

varied between studies.

Achievement discrepancies were applied using either individual benchmarks or researcher

determined benchmarks (Table 4). Three articles used individual benchmarks and identified gifted

underachievement when a student’s standardized achievement was one or more standard deviations

below their standardized score on a test of cognitive ability. The remaining six articles identified gifted

underachievement using a researcher determined achievement benchmark, which is an arbitrary cut off

that is applied and makes no allocation for a student’s prior achievement or cognitive ability. This

approach was highly variable, however, and captured students who were ranked as the lowest achievers

in their class or students who received a grade below that deemed satisfactory by the researcher (Table

4).

The use of either one or two achievement indicators was another point of difference between

the nine articles. Five used only one indicator to identify gifted underachievement (Table 4), while the

remaining four articles used two or more indicators. Of the four articles using two or more indicators,

Abelman (2007), Figg et al. (2012) and Reis et al. (2005) used two direct measures of achievement

(e.g., GPA or test scores or class enrolment), while Abu-Hamour and Al-Hmouz (2013) relied on two

indirect measures of achievement (e.g., student and teacher ratings).

14

Table 4 Overview of Measures and Criteria for Identifying Gifted Underachievers # Study Measure Criteria 1 Abelman (2007) Teacher ratings

Classroom observation Standard Assessment Test (SAT) Course grades

No specific criteria

2 Abu-Hamour and Al-Hmouz (2013)

Teacher ranking – low (bottom 5%), moderate, high (top 5%) Student ranking – low (bottom 5%), moderate, high (top 5%)

Ranked low achiever (bottom 5% of class) Ranked low achiever (bottom 5% of class)

3 Dixon et al. (2006)

Progressive achievement test (PAT) – four tests.

Score ≥1 standard deviation BELOW expected PAT score on three tests.

4 Figg et al. (2012) General achievement test (GAT) Academic ranking within the grade

Score ≤ 85th percentile

Consistent ranking BELOW the top 15% of the grade

5 Obergriesser and Stoeger (2015)

z-standardized grade point average (GPA) in main subjects

z-standardized GPA ≥ 1 standard deviation BELOW z-standardized cognitive ability (Raven’s SPM) score.

6 Reis et al. (2005) Grade point average (GPA) Class enrolment

Previously with strong academic grades of B or better. Current grade point average of 2.0 or lower. Consistently enrolled in non-college-bound or general classes. No longer in school, having dropped out or become truant.

7 Ritchotte et al. (2014)

Teacher reported mathematics grade point average (GPA) as a percentage - based on at least 10 graded assessment items.

GPA ≤ 84%

8 Schick and Phillipson (2009)

Student reported grade point average (GPA) – 1 outstanding, 3 average/satisfactory, 5 unsatisfactory/fail

GPA of 4 or 5

9 Stoeger et al. (2008)

Grade point average (GPA) in Mathematics, German and Science

Average GPA in 3 subjects ≥ 1 standard deviation BELOW cognitive ability (CFT) score.

15

4.3. Factors Associated with Gifted Underachievement

Only two of the nine articles that met our inclusion criteria investigated factors related to the

home environment (see Table 5), such as child rearing practices and family background/involvement.

Five of the nine articles examined school-related factors, such as students’ perceptions of

school/classroom climate and teacher support. However, structural factors – such as participation in

special programs and appropriately advanced classes – featured in only one of these studies. The

majority of studies (n=8) focused mainly on individual factors. The most common factors investigated

across the nine studies were motivation, emotion, and students’ perceptions of school.

Table 5 Factors Explored in the Nine Articles # Study Home Factors School Factors Individual Factors 1 Abelman

(2007) Parenting practices, children’s electronic media consumption

2 Abu-Hamour and Al- Hmouz (2013)

Attitudes towards school and teachers

Motivation, self-regulation, goal valuation, academic self-perception.

3 Dixon et al., (2006)

Academic self-concept

4 Figg et al., (2012)

Attitudes towards school and teachers

Motivation, self-regulation, goal valuation, academic self-perception.

5 Obergriesser and Stoeger (2015)

Motivation, learning goal orientation, emotions

6 Reis et al., (2005)

Family background and involvement

Structural aspects of schooling, such as support availability and specialist programs.

Resilience

16

# Study Home Factors School Factors Individual Factors 7 Ritchotte et

al., (2014) Negative environmental

perceptions, negative attitudes towards school and teachers

Self-efficacy, task meaningfulness, self-regulation, negative self-concept

8 Schick and Phillipson (2009)

Classroom climate Learning motivation,

self-efficacy, personal identity

9 Stoeger et al., (2008)

Fine motor skill

4.3.1. Motivation

All four articles investigating motivation reported gifted underachievers scoring lower in self-

reported measures of different aspects of motivation in comparison to gifted achievers. Using both the

Motivated Strategies for Learning Questionnaire (Pintrich, Smith, Garcia, & McKeachie, 1993) and the

motivation/self-regulation subscales from School Attitudes Assessment Survey – Revised (SAAS-R)

(McCoach & Siegle, 2003), Abu-Hamour and Al-Hmouz (2013) reported that gifted underachievers

scored significantly lower in intrinsic and extrinsic motivation when compared to their gifted achieving

peers. Figg et al., (2012) also used the motivation/self-regulation subscales from the SAAS-R and

found that gifted underachievers scored significantly lower than their gifted achieving peers in

motivation and self-regulation. Using a six-item scale adapted from the Manual for the Patterns of

Adaptive Learning Scales (Midgley et al., 1998), Obergriesser and Stoeger (2015) found that gifted

underachievers scored significantly lower in self-efficacy, although there were no significant

differences between groups in terms of learning goal orientation. Schick and Phillipson (2009)

captured learning motivation using three German language instruments: achievement ambition

(Schmidt-Denter & Schick, 2005), cognitive motive (Burrmann, 1996), and joy for thinking (Bless,

Wänke, Bohner, Fellhauer, & Schwarz, 1994), and found that underachieving students scored

17

significantly lower in learning motivation than achieving students, irrespective of their level of

intellectual giftedness.

4.3.2. Emotion

The three articles that investigated emotional factors associated with gifted underachievement

were less consistent in their findings, which appear dependent on the specific aspect of emotion that is

being investigated. Obergriesser and Stoeger (2015) used the Academic Emotions Questionnaire

(Pekrun, Goetz, Frenzel, Barchfeld, & Perry, 2011) and found that gifted underachievers scored

significantly higher on the academic anxiety items. Using two of the four subscales from the

Engagement versus Disaffection scale (Skinner, Kindermann, & Furrer, 2009), Ritchotte et al. (2014)

found that gifted underachievers were less emotionally engaged and more disengaged than gifted

achievers. Conversely, Schick and Phillipson (2009) reported no significant difference in emotional

control between gifted achievers and gifted underachievers.

4.3.3. Perceptions of school

The four articles that investigated students’ perceptions of school focused predominately on

attitudes towards school and teachers and rating of the environment (e.g., class climate). According to

Abu-Hamour and Al-Hmouz (2013), gifted underachievers scored significantly lower than gifted

achievers on both attitudes towards school and attitudes towards teachers. This is consistent with

Ritchotte et al. (2014) who reported that gifted underachievers scored lower on environmental

perceptions (e.g., perceptions of available support) than gifted achievers. These findings suggest that

gifted underachievers may feel less supported in the classroom environment than their gifted achieving

peers, although it should be noted that Figg et al. (2012) found no significant differences between

groups on the same measures. Each of these studies employed scales drawn from the SAAS-R

(McCoach & Siegle, 2003), which include items that assess students’ attachment to school and to their

teachers.

18

Schick and Phillipson (2009), however, used the Linzer Questionnaire for School and

Classroom Climate for Grades 8-13 (LSFK 8-13), which assesses students’ perception of general

learning motivation in the class and conducted regression analyses to determine the relative

contribution to students’ individual learning motivation. They found a significant difference between

groups with general learning motivation (or classroom climate) making six times the contribution to

individual motivation in underachieving gifted students than achieving gifted students. However, this

effect was moderated by the addition of personality variables in the final step of the regression,

suggesting that the learning motivation of underachieving students may be more vulnerable to

environmental factors but also that this vulnerability is moderated by individual factors, such as

personality.

5. Discussion

This systematic review sought to address key questions relating to the identification of

giftedness and gifted underachievement, as well as the factors that the nine empirical research articles

meeting our inclusion criteria found associated with gifted underachievement. Our first research

question focused on the methods used to identify intellectually gifted students in empirical research

and, although the nine articles in this review adopted different measures (non-verbal and/or verbal;

cognitive tests and/or achievement tests), we found that the majority (n = 7) adopted standardized tests

with both verbal and non-verbal tasks (e.g. WISC-R and BIS-HB). A minority (n = 2) focused

explicitly on non-verbal tests such as the Raven’s SPM and CFT to determine cognitive ability (see

Table 3). As academic achievement measures inherently require students to engage with language to

complete the assessment, they are also considered verbal. This is an important finding because the

differential use of verbal and non-verbal tasks has the potential to affect some students’ performance

and may result in identification discrepancies between studies (Worrell, 2013). Six of the nine studies

19

also used only one measure, despite attempts by leading researchers in the field of gifted and talented

education to “dispel the myth that a single score is sufficient for determining giftedness” (Worrell,

2009, p. 242).

In addition to using different measures to identify giftedness, our review also detected

variability in the cut-offs employed. Indeed, each study was different resulting in a diverse range of

cut-offs, even when different studies used the same type of measure. In relation to standardized scores

on tests of cognitive ability, for example, three different studies employed three different composite

scores as identification cut-offs (Dixon et al., 2006; Schick & Phillipson, 2009; Figg et al., 2012). Such

variability may result in a research sample that comprises both intellectually gifted students and

students of average intelligence, which may impact research findings when compared to other studies

with higher cut-off criteria. It may also result in much larger estimations of the prevalence of gifted

underachievement, which has implications for policy development and models of support.

Finally, it is important to note that the inclusion/ exclusion criteria informing this review did not

specify which gifted identification approaches should be employed, only that articles must have

reported the approaches used. Further, although we were principally interested in intellectual

giftedness, we included all studies that reported an approach to identifying giftedness, regardless of

domain. All nine articles that met our criteria by first reporting approaches to identify gifted and gifted

underachieving groups, and then using these groups in analyses to determine factors associated with

gifted underachievement, focused on academic achievement and intellectual giftedness. However, as

shown in Table 3, even the nine articles that reported sufficient detail for inclusion in this systematic

review did not consistently report other key variables, such as gender composition in full and group

samples.

Our second research question focused specifically on the methods used to identify gifted

underachievement and, while a discrepancy model was used in all nine studies, there was considerable

20

diversity in the number and type of achievement measures, as well as the cut-off metric used to identify

underachievement. Abu-Hamour and Al-Hmouz (2013) was the only study that utilized solely indirect

measures to determine underachievement (e.g., student and teacher self-reported class rankings). Most

included at least one direct measure of achievement to determine underachievement (e.g., achievement

test score or GPA), but again, no two studies were the same and each employed different cut-offs.

Moreover, only a few of the cut-offs in these nine studies were individually referenced (Dixon et al.,

2006; Obergriesser & Stoeger, 2015; Stoeger et al., 2008) (Table 4), as per the discrepancy model

(McGee, 2013). All three studies identified gifted underachievers based on individual academic

achievement being more than one standard deviation below that student’s expected achievement, which

is determined by an individual’s own cognitive ability score.

The remaining six studies used researcher determined cut-offs, however, this approach is

conceptually inconsistent with the discrepancy model and risks incorrectly identifying some students as

under/achieving. For example, the use of a researcher determined benchmark, such as a GPA of 2.0 or

lower (Reis et al., 2005), may fail to identify individual underachievement in a student with a GPA of

4.0 who is capable of a GPA of 5.0. Ideally, research designs should adopt individually referenced

benchmarks as opposed to researcher determined benchmarks because the characteristics of a gifted

student can vary across domains (Reis & Renzulli, 2009). Such an approach would be more consistent

with the discrepancy model which, as we described in our introduction, provides the conceptual

underpinning for the definition of gifted underachievement.

Our third research question aimed to examine which factors the studies meeting our inclusion

criteria found associated with gifted underachievement. The review revealed that the majority focused

on individual student factors, as opposed to factors relating to the home or school environment. Across

the nine studies, the most commonly investigated factors were motivation, emotion, and perceptions of

school (Table 5). Motivation, in four of the reviewed articles (Abu-Hamour & Al-Hmouz, 2013; Figg

21

et al., 2012; Obergriesser & Stoeger, 2015; Schick & Phillipson, 2009), was consistently reported as

being lower in gifted underachievers when compared to gifted achievers, despite the use of different

self-reported indicators of motivation (e.g., motivation/self-regulation, learning goal orientation,

cognitive motive, achievement ambition and joy for learning). Emotion, in three of the reviewed

articles, reported findings that were less consistent and variable depending on what aspect of emotion

was investigated. For example, Obergriesser and Stoeger (2015) reported gifted underachievers

scoring higher on academic anxiety items in the Academic Emotions Questionnaire (Pekrun et al.,

2011). Alternatively, Schick and Phillipson (2009) found gifted achievers and gifted underachievers

had similar levels of emotional control. Arguably, levels of academic anxiety are associated with an

individual’s ability to control or regulate emotion (e.g., Bertrams, Englert, Dickhauser, & Baumeister,

2013), so the contrasting findings of Obergriesser and Stoeger (2015) and Schick and Phillipson (2009)

are interesting. However, these contrasting findings may also be related to the diversity in research

samples; for example, Obergriesser and Stoeger (2015) focused on elementary school students, while

Schick and Phillipson (2009) focused on secondary school students. Alternatively, the contrasting

findings may indicate a more complex interplay of factors that have not been captured in the research

designs of the reviewed articles.

Perceptions of school (e.g., perceived teacher support and classroom climate), in four of the

reviewed articles, were reported as typically lower in gifted underachievers when compared to gifted

achievers. Interestingly, however, only one study included any variables relating to structural aspects

of schooling, such as participation in gifted programs (Reis et al., 2005). The three remaining studies

used scales aimed at assessing students’ attitudes towards school or student perceptions of classroom

climate. While these methods may provide a window into how a student feels about their learning

environment, they cannot – on their own – provide any insights as to why students’ feel the way they

do or what school-related factors are at play.

22

Schools and classrooms are complex social environments and the interplay of a multitude of

factors – including curricular choice, instructional quality, classroom composition and climate, school

composition (e.g., elementary/secondary), culture and competitiveness, streaming and selectivity, and

support availability – may differentially influence individual students. Liem, Marsh, Martin,

McInernery and Yeung (2013), for example, found that the national policy of academic streaming in

Singapore had a negative ‘big-fish-little-pond’ effect on the academic self-concepts of students, such

that students in the higher ability streams had lower English and Math self-concepts than students in the

lower ability streams. Their findings suggest that the processes and practices adopted within school

contexts could influence gifted underachievement. Our systematic review indicates that the potential

contribution made by structural aspects of the school context remains an under-researched topic in

gifted underachievement research.

5.1. Implications for Future Research

Reis and McCoach (2000) identified more than a decade and a half ago that most of the

empirical evidence about gifted underachievement in schools has focused on individual factors, and has

not captured the complexity of an individual in context. This same gap was noted in Dai et al.’s (2011)

review of the state of research on giftedness and gifted education just over a decade later. The focus of

the nine articles in this systematic literature review investigating factors associated with gifted

underachievement – another half decade since Dai et al.’s review of gifted research – suggests that

individual factors still dominate empirical research in this field. This is despite acknowledgement of

the importance of context in some of the reviewed articles (e.g., Abu-Hamour & Al-Hmouz, 2013;

Ritchotte et al., 2014; Schick & Phillipson, 2009), and other recent literature in the field (e.g. Matthews

& McBee, 2007; McCormick & Plucker, 2013). Although it has been acknowledged that the school

environment is “the variable most readily modifiable by school personnel”, making “its effects on the

achievement or underachievement of gifted children seem particularly worth studying” (Matthews &

23

McBee, 2007, p. 169), the findings of this review suggest that this knowledge has not yet translated

into greater research focus on the contribution that school contexts might make to gifted

underachievement. In the absence of robust research evidence, potential contributing factors – such as

instructional quality and support availability – cannot be identified or addressed.

This is a critically important finding because policy responses to educational problems typically

focus on structural “fixes” like those noted in our introduction; e.g., mandating the study of science and

mathematics through to the end of senior secondary school, and recruiting and training more specialist

teachers. If those fixes are not informed by rigorous research evidence this could lead to the

misdirection of precious funding and resources, as well as the wasted investment of teachers’ time and

energy, not to mention continued failure to address potentially important factors associated with gifted

underachievement. To that end, however, the field must place greater research emphasis on the school

environment to understand which practices, programs, policies and/or people have the greatest impact

on underachieving gifted students’ educational experiences and outcomes.

Finally, it is of great concern that so few articles met our inclusion criteria (Figure 1). Of the

377 records excluded from our sample in the record screening phase, approximately 42% of these

records did not report on an empirical study. These records represented a range of publication types,

including reviews (scholarly or otherwise), feature articles, book reviews and editorials. A further 37%

of excluded records did not indicate research involving gifted individuals in either the title or abstract.

At the full-text assessment phase (n=114), 50 articles were excluded because the participants were

either gifted college/university students or high school students who were high achieving, but not

formally identified as gifted. A further 21 articles were excluded because they did not compare gifted

and gifted underachieving groups in analyses. These articles typically reported explicit criteria to

identify gifted students and had a heterogeneous sample that included both achievers and

underachievers, but the researchers did not try to disentangle the factors that might be associated with

24

(under)achievement by looking for differences between groups. This systematic review suggests that

the goal for future research in this area is to have clearly defined methods for identifying gifted

students and gifted underachievers, as well as rigorous research designs that can reliably isolate factors

associated with gifted underachievement, particularly those most amenable to change by school

personnel. Education policy and practice should be driven by this empirical evidence-base.

5.2. Limitations

This systematic literature review has presented nine articles representing research from a small

number of developed countries. It used specific inclusion and exclusion criteria to identify empirical

articles for analysis, so may not represent all empirical research on the broader topic of giftedness,

across different cultures. The review focused on recent research investigating intellectually gifted

school students and the factors associated with gifted underachievement. As such, the review was

based on empirical articles published between 2005 and 2015, and did not include articles published

prior to 2005. Keyword searches in each of the eight databases (Table 1) were applied to Abstract, so

articles without the designated keywords in the Abstract were not reviewed. Aligned with the research

questions of this systematic review, to be included in the final analysis the articles must have reported

how gifted students and gifted underachievers were identified, and must also have used these groups in

relevant data analyses. Again, this may have resulted in the exclusion of empirical research which

reported on some aspects of gifted underachievement in elementary or secondary school settings, but

did not satisfy all inclusion criteria. For example, there were some articles (n = 6) that were excluded

at the full text stage because they did not report on the methods used to identify the intellectually gifted

participants. This limitation in our sample, however, reflects a broader limitation of research in the

field of gifted underachievement.

25

5.3. Conclusion

This systematic literature review explored the identification methods used to identify gifted

students and gifted underachievers in empirical articles published between 2005 and 2015, which met

explicit inclusion/exclusion criteria. The review also explored the factors that these articles reported as

associated with gifted underachievement. The findings of the review revealed that there is variability

in identification methods when identifying giftedness and gifted underachievement, largely due to

differential use of verbal and non-verbal subtests, and the use of inconsistent identification cut-offs.

Although students’ perceptions of school was an area explored in four of the nine articles, only one

study had explored structural school-related factors, such as enrolment in a gifted program. Curricular

choice, quality of teaching, the use of differentiation and acceleration, support availability, streaming

practices, and school culture and competitiveness may also contribute to gifted underachievement, but

these school related factors were not captured in any of the articles that met our inclusion criteria.

This systematic review also indicated that very few studies (nine from 957 across an 11-year

period) are employing the methodologies needed to isolate factors associated with gifted

underachievement, which include: rigorous criteria for the identification of both giftedness and gifted

underachievement, and the comparison of these groups in analyses to understand how gifted

underachievers differ from gifted achievers. Further, the variability in identification methods and cut-

offs revealed in this review also suggests that researchers might not be basing critical measurement

decisions on relevant published research, which could be the first step towards improving the quality

and rigor of gifted education research. Development of more rigorous identification protocols and

research methods will ensure greater consistency and comparability in research findings, enabling

researchers to speak with confidence about the estimated prevalence of gifted underachievement, as

well as the factors that would most likely benefit from intervention.

26

References

Abelman, R. (2007). Fighting the war on indecency: Mediating TV, internet, and videogame usage

among achieving and underachieving gifted children. Roeper Review, 29, 100-112.

doi:10.1080/02783190709554393

Abu-Hamour, B., & Al-Hmouz, H. (2013). A study of gifted high, moderate, and low achievers in their

personal characteristics and attitudes toward school and teachers. International Journal of

Special Education, 28, 5-15. Retrieved from

http://www.internationaljournalofspecialeducation.com

Aubusson, K. (2016, March 17). Push for Year 12 maths prerequisites for STEM degrees. The Sydney

Morning Herald. Retrieved from http://www.smh.com.au/national/education/push-for-year-12-

maths-prerequisites-for-stem-degrees-20160316-gnkmct.html

Bertrams, A., Englert, C., Dickhauser, O., & Baumeister, R. F. (2013). Role of self-control strength in

the relation between anxiety and cognitive performance. Emotion, 13, 668-680.

doi:10.1037/a0031921

Bita, N. (2016, February 6). Our students up to three years behind Asian teens. The Australian.

Retrieved from http://www.theaustralian.com.au/national-affairs/education/our-students-up-to-

three-years-behind-asian-teens/news-story/d93d32274661460ed92e29034cf6a470

Bless, H., Wänke, M., Bohner, G., Fellhauer, R.F., & Schwarz, N. (1994). Need for cognition: Eine

Skala zur Erfassung von Engagement und Freude bei Denkaufgaben. Zeitschrift für

Sozialpsychologie, 25, 147–154.

Browne, R., & Cook, H. (2016, August 3). 2016 NAPLAN results not good enough, says federal

education minister Simon Birmingham. The Age. Retrieved from

http://www.theage.com.au/victoria/2016-naplan-results-not-good-enough-says-federal-

education-minister-simon-birmingham-20160802-gqjd8e.html

27

Burrmann, U. (1996). Lernstrategien und Lernmotive von Schülerinnen und Schülern - erste

Ergebnisse einer empirischen Studie. (LLF-Berichte Nr. 16). Universität Potsdam: Lehr-Lern-

Forschung.

Dai, D. Y., Swanson, J. A., & Cheng, H. (2011). State of research on giftedness and gifted education: A

survey of empirical studies published during 1998 – 2010. Gifted Child Quarterly, 55, 126-138.

doi:10.1177/0016986210397831

Dillon, S. (2010, December 7). Top test scores from Shanghai stun educators. The New York Times.

Retrieved from http://www.nytimes.com/2010/12/07/education/07education.html

Dixon, R. M., Craven, R. G., & Martin, A. J. (2006). Underachievement in a whole city cohort of

academically gifted children: What does it look like? Australasian Journal of Gifted Education,

15(2), 9-14. Retrieved from http://www.aaegt.net.au

Fannema, E., & Sherman, J. (1976). Fennema-Sherman Mathematics Attitude Scales: Instruments

designed to measure attitudes toward the learning of mathematics by females and males.

Journal for Research in Mathematics Education, 7, 324-326. Retrieved from

http://www.nctm.org/publications/journal-for-research-in-mathematics-education

Figg, S. (2012). Author’s Response to Commentaries on “Differentiating Low Performance of the

Gifted Leaner: Achieving, Underachieving, and Selective Consuming Students. Journal of

Advanced Academics, 23(2), 180-184. doi:10.1177/1932202X12439705

Figg, S. D., Rogers, K. B., McCormick, J., & Low, R. (2012). Differentiating low performance of the

gifted learner: Achieving, underachieving, and selective consuming students. Journal of

Advanced Academics, 23, 53-81. doi:10.1177/1932202X11430000

Flint, L. J., & Ritchotte, J. A. (2012). A commentary on “Differentiating low performance of the gifted

learner: Achieving, underachieving, and selective consuming students”. Journal of Advanced

Academics, 23(2), 168-175. doi:10.1177/1932202X11434641

28

Florence, L., & Partland, L. (2015, June 16). Almost 40 per cent of Australian jobs could be replaced

by technology by 2025, report finds. ABC News. Retrieved from

http://www.abc.net.au/news/2015-06-16/technology-could-make-almost-40pc-of-jobs-

redundant-report/6548560

Francis, R., Hawes, D. J., & Abbott, M. (2016). Intellectual giftedness and psychopathology in children

and adolescents: A systematic literature review. Exceptional Children, 82, 279-303.

doi:10.1177/0014402915598779

Kell, P., & Kell, M. (2016). The Sputnik moment in the twenty-first century. In R. C. Mizzi, T. S.

Rocco, & S. Shore (Eds.), Disrupting adult and community education: Teaching, learning, and

working in the periphery (pp. 243-255). Albany, NY: SUNY Press.

Liem, G., Marsh, H., Martin, A., McInerney, D., & Yeung, A. (2013). The big-fish-little-pond effect

and a national policy of within-school ability streaming: Alternative frames of reference.

American Educational Research Journal, 50, 326-370. doi:10.3102/0002831212464511

Lohman, D. F. (2012). Identifying gifted students. In C. M. Callahan & H. L. Hertberg-Davis (Eds.),

Fundamentals of gifted education: Considering multiple perspectives (pp. 112-126). New York,

NY: Routledge.

Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P., & Marrs, A. (2013, May 13). Disruptive

technologies: Advances that will transform life, business, and the global economy. McKinsey

Global Institute. Retrieved from http://www.mckinsey.com/business-functions/business-

technology/our-insights/disruptive-technologies

Matthews, M. S., & McBee, M. T. (2007). School factors and the underachievement of gifted students

in a talent search summer program. Gifted Child Quarterly, 51, 167-181.

doi:10.1177/0016986207299473

29

McCoach, D. B., & Siegle, D. (2003). The school attitude assessment survey-revised: A new

instrument to identify academically able students who underachieve. Educational and

Psychological Measurement, 63, 414-429. doi:10.1177/0013164403063003005

McCormick, K. M., & Plucker, J. A. (2013). Connecting student engagement to the academic and

social needs of gifted and talented students. In K. Kim, J. Kaufman, J. Baer, & B. Sriraman

(Eds.), Creatively gifted students are not like other gifted students (pp. 121-136) [ProQuest

eBook Central]. Retrieved from

http://ebookcentral.proquest.com.ezp01.library.qut.edu.au/lib/qut/reader.action?docID=303484

0

McGee, C. (2013). Motivation, gifted children, and underachievement. Parenting for High Potential,

2(7), 12. Retrieved from http://www.nagc.org/parenting-high-potential-1

Midgley, C., Kaplan, A., Middleton, M., Maehr, M., Urdan, T., Anderman, L., & Anderman, E. (1998).

The development and validation of scales assessing students’ achievement goal orientations.

Contemporary Educational Psychology, 23, 113–131. doi: 10.1006/ceps.1998.0965

Missett, T. C., & Brunner, M. C. (2013). The use of traditional assessment tools for identifying gifted

students. In C. M. Callahan & H. L. Hertberg-Davis (Eds.), Fundamentals of gifted education:

Considering multiple perspectives (pp. 105-111). New York, NY: Routledge.

Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. (2009). Preferred reporting items for systematic

reviews and meta-analyses: The PRISMA statement. BMJ: British Medical Journal, 339(7716),

332-336. doi:10.1136/bmj.b2535

Office of the Chief Scientist. (2014). Science, Technology, Engineering and Mathematics: Australia’s

Future. Retrieved from the Office of the Chief Scientist website:

http://www.chiefscientist.gov.au/wp-

content/uploads/STEM_AustraliasFuture_Sept2014_Web.pdf

30

Obergriesser, S., & Stoeger, H. (2015). The role of emotions, motivation and learning behavior in

underachievement and results of an intervention. High Ability Studies, 26, 167-190.

doi:10.1080/13598139.2015.1043003

Parkinson, E. (2016, August 16). Stretching the gifted. Financial Review. Retrieved from

http://www.afr.com/news/special-reports/stretching-the-gifted-20150814-giyzgz

Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and

implications for educational research and practice. Educational Psychology Review, 18, 315-

341. doi:10.1007/s10648-006-9029-9

Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011). Measuring emotions in

students' learning and performance: The Achievement Emotions Questionnaire (AEQ).

Contemporary Educational Psychology, 36, 36-48. Retrieved from

http://www.journals.elsevier.com/contemporary-educational-psychology

Peters, S. J. (2012). Underachievers: From Whose Perspective? A Commentary on “Differentiating

Low Performance of the Gifted Learner: Achieving, Underachieving, and Selective Consuming

Students”. Journal of Advanced Academics, 23(2), 176-180. doi:10.1177/1932202X12438718

Pintrich, P. R., Smith, D., Garcia, T., & McKeachie, W. (1991). A manual for the use of the Motivated

Strategies for Learning Questionnaire (MSLQ). Ann Arbor, MI: NCRIPTAL, School of

Education, The University of Michigan.

Plucker, J., & Callahan, C. (2014). Research on giftedness and gifted education: Status of the field and

considerations for the future. Exceptional Children, 80, 390-406.

doi:10.1177/0014402914527244

Reis, S. M., Colbert, R. D., & Hébert, T. P. (2005). Understanding resilience in diverse, talented

students in an urban high school. Roeper Review, 27, 110-120.

doi:10.1080/02783190509554299

31

Reis, S. M., & McCoach, D. B. (2000). The underachievement of gifted students: What do we know

and where do we go? Gifted Child Quarterly, 44, 152-170. doi:10.1177/001698620004400302

Reis, S. M., & Renzulli, J. S. (2009). Myth 1: The gifted and talented constitute one single

homogeneous group and giftedness is a way of being that stays in the person over time and

experiences. Gifted Child Quarterly, 53(4), 233-235. doi:10.1177/0016986209346824

Ritchotte, J., Matthews, M., & Flowers, C. (2014). The validity of the achievement-orientation model

for gifted middle school students: An exploratory study. Gifted Child Quarterly, 58, 183-198.

doi:10.1177/0016986214534890

Schmidt-Denter, U., & Schick, H. (2005). Kurzform des Fragebogens zur personalen und sozialen

Identität von Jugendlichen und Erwachsenen (FPSI-K) (Forschungsbericht Nr. 17 zum Projekt

“Personale und soziale Identität im Kontext von Globalisierung und nationaler Abgrenzung”).

Köln: Universität zu Köln.

Schick, H., & Phillipson, S. N. (2009). Learning motivation and performance excellence in adolescents

with high intellectual potential: What really matters? High Ability Studies, 20, 15-37.

doi:10.1080/13598130902879366

Sellar, S., & Lingard, B. (2013). Looking east: Shanghai, PISA 2009 and the reconstitution of reference

societies in the global education policy field. Comparative Education, 49, 464-485.

doi:10.1080/03050068.2013.770943

Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009). A motivational perspective on engagement

and disaffection: Conceptualization and assessment of children's behavioral and emotional

participation in academic activities in the classroom. Educational and Psychological

Measurement, 69, 493-525. doi:10.1177/0013164408323233

32

Stoeger, H., Ziegler, A., & Martzog, P. (2008). Deficits in fine motor skill as an important factor in the

identification of gifted underachievers in primary school. Psychology Science Quarterly, 50,

134-146. Retrieved from http://www.psychologie-aktuell.com/

Subotnik, R. F., Olszewski-Kubilius, P., & Worrell, F. C. (2012). A proposed direction forward for

gifted education based on psychological science. Gifted Child Quarterly, 56(4), 176-188.

doi:10.1177/0016986212456079

Thomson, S., De Bortoli, L., & Buckley, S. (2013). PISA in brief: Highlights from the full Australian

report: PISA 2012: How Australia measures up. Camberwell, VIC: Australian Council for

Educational Research (ACER). Retrieved from https://www.acer.org/files/PISA-2012-In-

Brief.pdf

Thomson, S., De Bortoli, L., & Underwood, C. (2016). PISA 2015: A first look at Australia’s results.

Camberwell, VIC: Australian Council for Educational Research (ACER). Retrieved from

http://research.acer.edu.au/cgi/viewcontent.cgi?article=1021&context=ozpisa

U.S. Department of Education. (2009). Race to the Top Program. Retrieved from the U.S Department

of Education website: http://www2.ed.gov/programs/racetothetop/index.html

Wood, J. (2003). Australia: An under performing knowledge nation? Journal of Intellectual Capital, 4,

144-164. doi:10.1108/14691930310472785

Worrell, Frank C. Myth 4: A single test score or indicator tells us all we need to know about

giftedness. Gifted Child Quarterly, 53, 242-244. doi:10.1177/0016986209346828

Worrell, F. C. (2013). Identifying gifted learners: Nonverbal assessment. In C. M. Callahan and H. L.

Hertberg-Davis (Eds.), Fundamentals of gifted education: Considering multiple perspectives

(pp. 135-147). New York, NY: Routledge.

33

1 Australia’s mean score in scientific literacy declined by 17 points between 2006 and 2015, reading literacy declined by 12 points between 2009 and 2015, and mathematical literacy declined by 10 points between 2012 and 2015. 2 The percentage of Australian students in the two highest achievement levels (Levels 5 & 6) declined between the 2006 and 2015 PISA cycles in both scientific (from 15% to 11%) and mathematical literacy (16% to 11%). In reading literacy, the percentage of students achieving in the two highest levels has fluctuated from 17% in 2000, 15% in 2003, 11% in 2006, 13% in 2009, 12% in 2012 and 11% in 2015.