Student Background Information – Digital Promise

Student Background Information

Sections

Hearing

The ability to hear speech sounds is essential for oral language development. Children who experience hearing loss often experience difficulty in acquiring oral language skills, which are important precursors to learning to read. The main constructs for understanding Hearing are:

  • Hearing is the ability to hear sounds in the typical human range of approximately 20 – 20,000 Hz.
  • Even mild-to-moderate hearing loss can impact oral language development because children receive degraded auditory language input which results in distortion of speech sounds.
    • More severe hearing loss is associated with more language development difficulties.
  • Hearing loss typically impacts high frequency speech sounds (e.g., /sh/, /s/, /f/, /th/) more than sounds at other frequencies. This makes common words difficult to understand.
  • Early detection of hearing loss is essential for children to receive the necessary supports to allow them to achieve the same language and cognitive milestones as their peers with typical Hearing.
    • Mild-to-moderate hearing loss is often not identified until a child is 4 to 5 years old, and this late identification can have a negative impact on their ability to achieve academic milestones in both oral language and literacy skills.
  • Hearing aids and cochlear implants do not always completely restore Hearing.

Assessment

  • Pure-Tone Audiometry: Assesses how well an individual can hear sounds at different pitches (frequencies). The student is asked to wear headphones and indicate when they hear a sound.

Learner Factor Connections

  • Auditory Processing: The process of detecting sound and interpreting it as meaningful input
    • Hearing allows auditory information to enter the brain and be interpreted as meaningful input via Auditory Processing.
  • Emotion: A complex psychological state that involves a subjective experience and can result in a physiological and behavioral response. Depression is a mood disorder causing feelings of sadness and hopelessness that have a significant negative impact on a student’s ability to participate in daily activities and succeed in school.
    • Children with hearing loss experience depression at higher rates than their peers with typical hearing. This is likely due to the social isolation that can occur when hearing loss causes communication difficulties, as well as exclusion and discrimination that these students frequently face.
  • Morphological Awareness: Sensitivity to linguistic units (morphemes) including root words, prefixes, suffixes, intonations, and stress, which all convey meaning
    • Even mild-to-moderate hearing loss can impact the quality of speech signal a child hears, which can impact Morphological Awareness. For example, children who cannot hear the /s/ (a high frequency sound) in speech will have less exposure to the morpheme “-s” which can change a word to plural (“dogs”) or possessive (“dog’s”).
  • Phonological Awareness: The knowledge of and ability to manipulate and detect sounds in words
    • Hearing loss can impact the ability to distinguish between different speech sounds. This can result in reduced Phonological Awareness and reduced production of certain speech sounds when speaking.
  • Vocabulary: Includes both the lexical representations of stored sounds (word forms) and the semantic meaning associated with each of those stored sounds. Receptive Vocabulary refers to words that a student understands and expressive Vocabulary refers to words a student can successfully produce during speech.
    • The sound distortion caused by hearing loss can make it difficult for students to learn new Vocabulary, often resulting in smaller receptive and expressive Vocabularies than peers with normal Hearing.

Research Findings

  • Even mild-to-moderate hearing loss can impact language input, as it results in lower Hearing thresholds as well as distortion of sounds (Moeller et al., 2007). Thus language input is partial and degraded. This type of hearing loss is often not detected until the age of 4 or 5 (Hansson et al., 2004; Stelmachowicz et al., 2004), meaning these children often experience degraded language input during the crucial years for language development. It should be noted that while hearing aids and cochlear implants improve Hearing, they do not restore Hearing to normal levels.
  • Delage and Tuller (2007) assessed language skills in a group of 19 French speaking adolescents (age range = 11 to 15 years) with mild to moderate sensorineural hearing loss compared to a group of typically developing students and a group of students with Specific Language Impairment (SLI). They assessed several different aspects of language including Phonological Awareness (assessed in a word repetition task), expressive Vocabulary (using a naming task), expressive grammar/morphosyntax (in a sentence completion task), reading fluency (reading a list of words quickly and accurately), and spelling (word identification task). They also included lexical judgement (whether a word corresponds with a picture) and grammatical judgment tasks (whether a sentence corresponding to a picture is grammatically correct). In students with hearing loss, they found disorders particularly in the areas of phonology and morphosyntax (related to Morphological Awareness) that were similar to the group of students with language disorders (e.g, SLI). However, the students with SLI performed worse on measures of written language (on a task that did not require morphosyntax), while the students with hearing loss performed similarly to the typically developing students on this task. They also found that the degree of hearing loss was associated with the severity of language impairment. Thus, hearing loss can have a long-term impact on language development that is apparent in adolescents. However, a large amount of intersubject variability was present, and only about 50% of students with hearing loss experienced language impairments.
  • Norbury, Bishop, and Briscoe (2001, 2002) and Briscoe, Bishop, and Norbury (2001) conducted a series of studies examining the impact of mild-to-moderate sensorineural hearing loss on language development in a group of children between ages 5 to 10. They found that 21-22% of students with hearing loss displayed difficulties in both the production and comprehension of morphosyntax, and 50% had significant phonological impairments (Phonological Awareness, expressive phonology).
  • Theunissen and colleagues (2011) examined Emotion regulation and depressive symptoms in a group of children living in the Netherlands and the Dutch speaking part of Belgium: 27 children with cochlear implants, 56 children with hearing aids, and 117 children with normal Hearing (age range = 8 to 16 years, mean age = 11 years 11 months). They measured depression using the Child Depression Inventory and also measured two aspects of Emotion regulation: (1) mood states (measured using a self-report Mood questionnaire) and (2) coping skills (using the self-report Coping Scale). They found that children with hearing impairments experienced significantly more symptoms of depression compared to children with normal Hearing, although the degree of hearing loss was not related to level of depression. The authors explain that higher levels of depression are probably due to difficulties communicating with people with normal Hearing and due to exclusion and discrimination against hearing impaired individuals. Also, the older students were more likely to experience depression. Moreover, depression rates were lower in children who attended mainstream schools and only used oral speech to communicate compared to those attending schools for the deaf and who supplemented their communication with sign language. The authors explained that students who attend schools for the deaf may experience more feelings of isolation than those attending mainstream schools.
  • Vohr and colleagues (2010) investigated the impact of early intervention on expressive Vocabulary. They examined expressive Vocabulary in infants who were identified in the Rhode Island newborn screening program as having hearing loss and, at the time of the study, were between the ages of 18 to 24 months. The children with hearing loss were divided into those who were enrolled in early intervention at or before 3 months of age and those who were enrolled after 3 months. Early intervention services included being enrolled in a specialty program for infants/toddlers with hearing loss that supports language acquisition and provides speech therapy, as well as occupational and physical therapy when needed. Overall, children with hearing loss had a smaller expressive Vocabulary than children with typical Hearing, and children who received early intervention services at/before 3 months of age had larger expressive Vocabularies than children who enrolled after 3 months. This demonstrates that early identification of hearing loss and subsequent early intervention services are both essential to language development outcomes in children with hearing loss.

References

Briscoe, J., Bishop, D. V., & Norbury, C. F. (2001). Phonological processing, language, and literacy: A comparison of children with mild-to-moderate sensorineural hearing loss and those with specific language impairment. Journal of Child Psychology and Psychiatry, 42(3), 329-340.

Ching, T.Y., Crowe, K., Martin, V., Day, J., Mahler, N., Youn, S., & Orsini, J. (2010). Language development and everyday functioning of children with hearing loss assessed at 3 years of age. International Journal of Speech-Language Pathology, 12(2), 124-131.

Delage, H., & Tuller, L. (2007). Language development and mild-to-moderate hearing loss: Does language normalize with age?Journal of Speech, Language, and Hearing Research, 50(5), 1300-1313.

Hansson, K., Forsberg, J., Löfqvist, A., Mäki-Torkko, E., & Sahlén, B. (2004). Working memory and novel word learning in children with hearing impairment and children with specific language impairment. International Journal of Language and Communication Disorders, 39(3), 401–422.

Moeller, M. P., Tomblin, J. B., Yoshinaga-Itano, C., Connor, C. M., & Jerger, S. (2007). Current state of knowledge: Language and literacy of children with hearing impairment. Ear and Hearing, 28(6), 740-753.

Norbury, C. F., Bishop, D. V. M., & Briscoe, J. (2001). Production of English finite verb morphology: A comparison of SLI and mild–moderate hearing impairment. Journal of Speech, Language, and Hearing Research, 44, 165-179.

Norbury, C. F., Bishop, D. V. M., & Briscoe, J. (2002). Does impaired grammatical comprehension provide evidence for an innate grammar module? Applied Psycholinguistics, 23, 247-268.

Stelmachowicz, P. G., Pittman, A. L., Hoover, B. M., & Lewis, D. E. (2004). Novel-word learning in children with normal hearing and hearing loss. Ear and Hearing, 25, 47–56.

Theunissen, S. C., Rieffe, C., Kouwenberg, M., Soede, W., Briaire, J. J., & Frijns, J. H. (2011). Depression in hearing-impaired children. International Journal of Pediatric Otorhinolaryngology, 75(10), 1313-1317.

Vohr, B., Jodoin-Krauzyk, J., Tucker, R., Topol, D., Johnson, M. J., Ahlgren, M., & Pierre, L. (2011). Expressive vocabulary of children with hearing loss in the first 2 years of life: Impact of early intervention. Journal of Perinatology, 31(4), 274-280.

 

Home Literacy Environment

The Home Literacy Environment (HLE) is the environment that parents and caregivers provide their children to help them gain early literacy skills. HLE is multifaceted and involves several different factors:

  • The availability of reading and writing materials in the home;
  • The time that parents and caregivers spend reading to their children;
  • The instruction that parents and caregivers provide their children when their children are learning how to read and write; and
  • The value that parents and caregivers place on literacy, such as whether the parents are avid readers themselves.

Assessments

  • Direct observation of family
  • Questionnaires asking parents about their knowledge of children’s books and children’s book authors (see Foy & Mann, 2003)
  • Parent Questionnaires: Questions on number of books/picture books in the house, time spent reading to kids, and how often they read books and watch TV.
  • Home Observation for Measurement of the Environment (HOME): Inventory scored during 45-90 minute home visit
  • Home Literacy Checklist: Questionnaire that parents can use to determine whether they are providing an ideal home literacy environment for their children.

Learner Factor Connections

  • Alphabet Knowledge: Familiarity with letter names, forms, and corresponding sounds
    • Activities that promote a strong HLE (e.g., parents/caregivers reading to their children) are positively associated with growth in Alphabet Knowledge.
  • Morphological Awareness: Sensitivity to linguistic units (morphemes) including root words, prefixes, suffixes, intonations, and stress, which all convey meaning
    • The amount of time parents spend reading to their children is one important predictor of Morphological Awareness development. This is likely because language in books is often more complex than language used in spoken conversations.
  • Narrative Skills: The ability to tell stories requires the development and use of a complex set of skills, including properly forming and organizing sentences, understanding and using Vocabulary, and organizing the elements of a story (e.g., setting, main characters, etc.) in a logical manner.
    • A strong HLE enhances the development of strong Narrative Skills.
  • Phonological Awareness: The knowledge of and ability to manipulate and detect sounds in words
    • A strong HLE can aid in the development of Phonological Awareness skills.
  • Print Awareness: Understanding the forms, functions, and conventions of print
    • A strong HLE contributes to the development of Print Awareness skills.
  • Socioeconomic Status (SES): A combination of factors including education and income of a family compared to other families
    • The economic pressures that low income families face can negatively impact HLE. For example, parents may need to work multiple jobs resulting in less time for engaging in activities that can enhance HLE.
  • Syntax: The rules and principles that govern the structure and word order of sentences
    • Parent literacy and the amount of time spent engaging in shared reading with their children are correlated with Syntax comprehension in children.
  • Vocabulary: Includes both the lexical representations of stored sounds (word forms) and the semantic meaning associated with each of those stored sounds
    • A strong HLE helps promote Vocabulary development.

Research Findings

  • Multiple studies have found that active HLE variables (e.g., reading to a child) are more closely associated with Phonological Awareness, Vocabulary development, and early reading than passive HLE variables (e.g., seeing a parent read).
  • Knowledge that parents have about children’s book authors has been shown to be significantly correlated with Vocabulary knowledge, even when controlling for IQ and Working Memory (Davidse et al., 2011).
  • HLE significantly impacts Vocabulary and reading comprehension, even when controlling for SES and migration background (van Steensel, 2006).
  • HLE directly influences Phonological Awareness skills at the beginning of kindergarten (Niklas & Schneider, 2013).
  • Children from low-income (SES) homes who are entering kindergarten have weaker Print Awareness skills than those from middle-class or high-income homes (Justice & Ezell, 2002), which has been attributed to the HLE. Children from low-income homes often are raised with a weaker HLE, resulting in fewer opportunities to build Print Awareness at home (e.g., less time is spent reading books to children due to the economic pressures that low-income families face).
  • One study suggests that HLE acts as a mediator between SES and migration background; thus SES and migration background do not directly impact literacy, rather the influence of SES and migration background is mediated by the HLE (Niklas & Schneider, 2013).
  • Differences in children’s HLE has been associated with the acquisition of Alphabet Knowledge (Burgess, Hecht, & Lonigan, 2002). Specifically, active aspects of the HLE (e.g., time spent reading to the child) are positively associated with growth in Alphabet Knowledge.
  • Senechal and colleagues (2008) investigated the impact of shared reading between parents and their children on Narrative Skills, Morphological Awareness knowledge, Syntax comprehension, and expressive Vocabulary in a group of 4-year-olds. They found that time spent shared reading (indicative of HLE) was a significant predictor of morphological knowledge and expressive Vocabulary skills. They attributed their findings to the previous finding from Crain-Thoreson and colleagues (2001) who found that parents used longer MLUs (mean length of utterance) during shared reading activities. Their results also revealed that parents’ own print exposure was a predictor of their children’s Syntax comprehension. The authors explain this relationship is likely because parents who read more themselves tend to select books with more syntactically complex language than parents who read less or that parents who read more use more complex language when speaking to their children.

Home Literacy Interventions

  • Even non-intensive interventions to improve HLE (one session of educating families with young children on ways to improve their HLE and one session showing them the strategy of dialogic reading) are successful at significantly improving linguistic competencies in kindergarten students (Niklas & Schneider, 2015).
  • Zevenbergen and colleagues (2003) investigated the impact of a shared reading intervention program for 4-year-olds (n = 123 students) enrolled in Head Start. The intervention program involved training teachers and parents to use dialogic reading techniques (Whitehurst, 1994), where the adult engages the children while reading to them by prompting them with questions (e.g., asking wh-questions about the story, asking open-ended questions, using recall prompts that require the child to recall something that happened previously in the story). By the end of the school year, the children who participated in the program had significantly better Narrative Skills than children who did not participate. They found that children included significantly more evaluative devices in their narratives (they referenced the internal states of characters) relative to children who were not part of the intervention.

References

Burgess, S. R., & Lonigan, C. J. (1998). Bidirectional relations of phonological sensitivity and prereading abilities: Evidence from a preschool sample. Journal of Experimental Child Psychology, 70(2), 117-141.

Crain-Thoreson, C., Dahlin, M. P., & Powell, T. A. (2001). Parent-child interaction in three conversational contexts: Variations in style and strategy. In J. Brooks-Gunn & P. Rebello (Eds.), Sourcebook on emergent literacy (pp. 23–38). San Francisco: Jossey-Bass.

Davidse, N. J., de Jong, M. T., Bus, A. G., Huijbregts, S. C. J., & Swaab, H. (2011). Cognitive and environmental predictors of early literacy skills. Reading and Writing, 24(4), 395-412.

Foy, J. G., & Mann, V. (2003). Home literacy environment and phonological awareness in preschool children: Differential effects for rhyme and phoneme awareness. Applied Psycholinguistics, 24, 59-88.

Justice, L.M, & Ezell, H.K. (2002). Use of storybook reading to increase print awareness in at-risk children. American Journal of Speech-Language Pathology, 11(1), 17–29.

Niklas, F., & Schneider, W. (2013). Home literacy environment and the beginning of reading and spelling. Contemporary Educational Psychology, 38(1), 40-50.

Niklas, F., & Schneider, W. (2015). With a little help: Improving kindergarten children’s vocabulary by enhancing the home literacy environment. Reading and Writing, 28(4), 491-508.

Sénéchal, M., Pagan, S., Lever, R., & Ouellette, G. P. (2008). Relations among the frequency of shared reading and 4-year-old children’s vocabulary, morphological and syntax comprehension, and narrative skills. Early Education and Development, 19(1), 27-44.

van Steensel, R. (2006). Relations between socio-cultural factors, the home literacy environment and children’s literacy development in the first years of primary education. Journal of Research in Reading, 29(4), 367-382.

Whitehurst, G. J., Arnold, D. S., Epstein, J. N., Angell, A. L., Smith, M., & Fischel, J. E. (1994). A picture book reading intervention in day care and home for children from low-income families. Developmental Psychology, 30(5), 679.

Zevenbergen, A. A., Whitehurst, G. J., & Zevenbergen, J. A. (2003). Effects of a shared-reading intervention on the inclusion of evaluative devices in narratives of children from low-income families. Journal of Applied Developmental Psychology, 24(1), 1-15.

Physical Fitness

Students who lead healthy lifestyles and participate in higher levels of Physical Fitness often perform better academically, and this benefit extends to learning to read. The main constructs for understanding Physical Fitness are:

  • Physical Fitness refers to overall health and physical well-being and is dependent on several important factors, including proper nutrition, exercise, and an adequate amount of sleep.
  • Cognitive skills improve with increased participation in physical activities, and this leads to enhanced academic performance.

Learner Factor Connections

  • Attention: The ability to focus on a specific task without being distracted, as well as the ability to select relevant information while ignoring irrelevant information
    • Regular participation in physical activities enhances Attention skills, which contributes to enhanced academic performance.
  • Emotion: A complex psychological state that involves a subjective experience and can result in a physiological and behavioral response. Depression is a mood disorder causing feelings of sadness and hopelessness that have a significant negative impact on a student’s ability to participate in daily activities and succeed in school.
    • Children, and particularly girls, who are overweight are more likely to experience depression.
  • Safety: How physically and psychologically safe a child feels at home, school, and in their community
    • Children living in less safe neighborhoods have fewer opportunities to play outside, therefore fewer opportunities for regular exercise, than children living in safe neighborhoods.
  • Sleep: A naturally occurring state involving the suspension of consciousness during which the body and the brain rest. Both duration and quality contribute to obtaining sufficient Sleep.
    • Acquiring the right amount of quality Sleep is an essential component of maintaining Physical Fitness.
  • Trauma: Emotional distress resulting from experiencing violence, abuse, a disaster, or an accident. Interpersonal trauma refers to Trauma that has occurred between people (e.g., assault or abuse), and non-interpersonal Trauma refers to Trauma inflicted by some other source (e.g., a motor vehicle accident, a natural disaster).
    • Experiencing Trauma can have negative long-term impacts on health. Children who suffer Trauma (especially those who are exposed to violence and abuse) are at higher risk of developing issues with obesity, substance abuse, hallucinations, and higher rates of sexual promiscuity as adults.
  • Working Memory: The type of memory that allows a person to temporarily hold and manipulate information for use in many complex cognitive processes
    • Programs aimed at enhancing Physical Fitness in children have been found to also improve Working Memory processes.

Research Findings

Increased Physical Fitness is associated with higher levels of academic achievement. Also, obesity has been linked to short Sleep duration (Cappuccio et al., 2008), and being overweight is associated with significant physical and emotional health risks (Judge & Jahns, 2007).

  • Coe and colleagues (2006) compared the academic achievement of 6th-graders who self-reported meeting vigorous activity recommendations of three or more days a week of 20+ minutes per session (above the level of activity achieved in physical education class offered at school) to those who either participated in moderate levels of activity or no activity. High levels of physical activity were correlated with higher grades. Moderate levels of activity were not associated with academic performance.
  • Eveland-Sayers and colleagues (2009) examined the link between academic achievement and Physical Fitness in a group of students in 3rd, 4th, and 5th grade. They collected measures of body mass index, one-mile run time, curl-up, and sit-and-reach data, and these were correlated with the results of an achievement test measuring math, reading, and language arts skills. They found that a lower one-mile run time was associated with higher math scores, and in girls, a lower run time was also associated with higher reading/language arts scores. Also, higher levels of muscular fitness were associated with higher math scores. Thus, higher levels of Physical Fitness were associated with academic performance.
  • Judge and Jahns (2007) examined data from 3rd-graders from the Early Childhood Longitudinal Study. They found that being overweight was associated with negative social and behavioral outcomes for girls. Also, while there was a correlation between being overweight and lower academic achievement, this relationship disappeared once SES and maternal education variables were removed. Overweight girls were more likely to engage in undesirable external behaviors such as fighting and to show undesirable internal behaviors indicating increased levels of loneliness and sadness. Overweight girls were also less likely to exhibit self-control relative to non-overweight girls. The authors stated that the association between being overweight and depressive symptoms in girls is a concern since depression (an aspect of Emotion) can often lead to impairments of social and behavioral skills.
  • Van der Niet and colleagues (2014) conducted a study where they modeled the relationship between Physical Fitness, academic achievement, and executive functioning in a group of 263 children between ages 7 to 12 living in the Netherlands. In order to assess executive functioning, they used the Tower of London test, which measures problem solving and planning abilities, and the Trailmaking text, which measures visual attention and task switching skills. Physical Fitness was measured using the European Physical Fitness test battery (EUROFIT), including standing broad jump, sit-ups, and running. Academic achievement was assessed using standardized test scores in math, spelling, and reading comprehension.Their resulting model suggested that Physical Fitness was related to both executive functioning and academic achievement. Moreover, executive functioning was a mediator in the relationship between Physical Fitness and academic achievement. Note that this was a cross-sectional study and not a longitudinal study, so the causality between these different variables needs to be further studied in order to make a stronger statement about the specific relationship between these three factors.
  • Kamijo and colleagues (2011) investigated whether a nine-month physical activity intervention designed to improve cardiorespiratory fitness would induce changes in Working Memory. Children (7- to 9-year-olds) were randomly assigned to a treatment or a control group. The physical activity program included a two-hour after school program. Working Memory was assessed using a modified Sternberg task, while electroencephalography (EEG) (measuring electromagnetic activity in the brain – brain waves) was recorded. From the EEG, event-related brain potentials (ERPs) were calculated to measure contingent negative variation (CNV) component. The Sternberg task required participants to encode an array of one, three, or five uppercase letters; then after a delay, they were presented with a single lowercase letter. Participants had to indicate via button press whether the lowercase letter appeared in its uppercase form in the array. The CNV is an ERP component measured in the interval between the array of uppercase letters and the presentation of the lowercase letter. The CNV is thought to be indicative of cognitive operations for maintaining goal-relevant information. Pre-intervention and post-intervention measures of ERP and behavioral (response time/ accuracy) measures on the Sternberg task, as well as measures of cardiorespiratory fitness (maximal oxygen consumption while walking/running on a treadmill), were collected. They found that children in the treatment group had significantly improved response accuracy for one and three letter arrays in the Sternberg task, but not for five letter arrays. This is possibly because the five letter arrays were too difficult for children in this age group. The effect size of improvement in the treatment group was largest in the three letter condition, whereas no effect was found in the control group. Additionally, at post-test, the intervention group had larger CNV amplitudes compared to the control group, even though no difference was found in CNV amplitudes at pre-test. The larger CNV amplitude suggests that cognitive control and Working Memory processes were enhanced as a result of the intervention. Cardiovascular fitness also improved in the treatment group.
  • Davis and colleagues (2011) recruited 171 children (7- to 11-year-olds) who were overweight and did not regularly participate in physical activities. The children were randomized to either a group who would receive a low dose of aerobic exercise (20 minutes/day), a high dose of exercise (40 minutes/day), or a control condition. The participants in the exercise groups participated every day after school for approximately three months. They also assessed executive functioning using the Cognitive Assessment System, which measures planning, Attention, simultaneous tasks (involving spatial and logical questions), and successive tasks (require analysis or recall of stimuli arranged in a sequence/order). Academic achievement was evaluated using the Woodcock-Johnson Tests of Achievement, which includes measures of math and reading. These skills were all assessed at baseline and posttest. Also, in a subset of 20 children (9 in control group and 11 in exercise group), functional magnetic resonance imaging (fMRI) was used to measure brain activity during an antisaccade task (which measures Inhibition). Overall, participation in regular aerobic exercise enhanced executive functioning on the Planning subtest. Any dose of exercise enhanced planning, but there was a dose response benefit as well. The fMRI results showed enhanced brain activity in prefrontal and parietal regions during the antisaccade task (Inhibition task).
  • Children who live in less safe neighborhoods have less opportunities to play outside than children living in safe neighborhoods. Thus, living in a less safe neighborhood limits opportunities for obtaining regular exercise (part of Physical Fitness) (Aikens & Barbarin, 2008; Franzini et al., 2010).
  • Anda and colleagues (2005) integrated findings from studies examining the neurobiological effects of childhood abuse and exposure to violence with data from the Adverse Childhood Experiences (ACE) study. The ACE Study was designed to assess the impact of adverse childhood experiences (that occurred between 0 to 18 years of age) on health behaviors and outcomes. Their results suggest that childhood abuse and exposure to violence results in long-term health, behavioral, and social problems. A higher ACE score (exposure to a higher number of abusive or violent events) was associated with higher rates of substance abuse, hallucinations, obesity, and sexual promiscuity as an adult. These results reveal that experiencing traumatic events as a child has long-term impacts on a person’s health.

References

Aikens, N. L., & Barbarin, O. (2008). Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts. Journal of Educational Psychology, 100(2), 235-251.

Anda, R. F., Felitti, V. J., Bremner, J. D., Walker, J. D., Whitfield, C. H., Perry, B. D., … Giles, W. H. (2006). The enduring effects of abuse and related adverse experiences in childhood. European Archives of Psychiatry and Clinical Neuroscience, 256(3), 174-186.

Cappuccio, F. P., Taggart, F. M., Kandala, N., Currie, A., Peile, E., Stranges, S., & Miller, M. A. (2008). Meta-analysis of short sleep duration and obesity in children and adults. Sleep, 31(5), 619-626.

Coe, D. P., Pivarnik, J. M., Womack, C. J., Reeves, M. J., & Malina, R. M. (2006). Effect of physical education and activity levels on academic achievement in children. Medicine and Science in Sports and Exercise, 38(8), 1515-1519.

Davis, C. L., Tomporowski, P. D., McDowell, J. E., Austin, B. P., Miller, P. H., Yanasak … J.D., Naglieri, J. A. (2011). Exercise improves executive function and achievement and alters brain activation in overweight children: a randomized, controlled trial. Health Psychology, 30(1), 91-98.

Eveland-Sayers, B. M., Farley, R. S., Fuller, D. K., Morgan, D. W., & Caputo, J. L. (2009). Physical fitness and academic achievement in elementary school children. Journal of Physical Activity & Health, 6(1), 99-104.

Franzini, L., Taylor, W., Elliott, M. N., Cuccaro, P., Tortolero, S. R., Gilliland, M. J., … & Schuster, M. A. (2010). Neighborhood characteristics favorable to outdoor physical activity: disparities by socioeconomic and racial/ethnic composition. Health & Place, 16(2), 267-274.

Judge, S., & Jahns, L. (2007). Association of overweight with academic performance and social and behavioral problems: An update from the early childhood longitudinal study. Journal of School Health, 77(10), 672-678.

Kamijo, K., Pontifex, M. B., O’Leary, K. C., Scudder, M. R., Wu, C. T., Castelli, D. M., & Hillman, C. H. (2011). The effects of an afterschool physical activity program on working memory in preadolescent children. Developmental Science, 14(5), 1046-1058.

Van der Niet, A. G., Hartman, E., Smith, J., & Visscher, C. (2014). Modeling relationships between physical fitness, executive functioning, and academic achievement in primary school children. Psychology of Sport and Exercise, 15(4), 319-325.

Primary Language

The number of students in the United States whose first language is not English is growing rapidly every year. These children will experience different language development trajectories than children from monolingual English homes (Hoff, 2013). English language learners come from a wide variety of home language environments. They may or may not have been exposed to English at home or in other environments prior to entering an English-speaking school. Thus, some bilingual or multilingual children will have English skills that are on par with their monolingual English-speaking peers; however many do not.

There are many benefits to growing up in a bilingual or multilingual home. However, for the purposes of discussing the acquisition of English literacy skills in U.S. public schools, many bilingual or multilingual children possess fewer English early literacy skills than their monolingual peers upon entering preschool or kindergarten.

The characteristics of children’s first languages relative to the language(s) they are using in school can significantly impact reading acquisition.The main constructs for understanding Primary Language are:

  • A Primary Language is the language they have been exposed to from birth.
  • The number of students who are learning more than one language is growing rapidly every year.
  • Children who are bilingual/multilingual experience different language development trajectories than their monolingual peers.
  • Simultaneous bi/multilingualism is when a child acquires two or more languages simultaneously from birth.
  • Sequential bi/multilingualism is when a child acquires a first language from birth and has meaningful exposure to additional language(s) (typically after the age of 3) after their first language has been established.

Learner Factor Connections

  • Attention: The ability to focus on a specific task without being distracted, as well as the ability to select relevant information while ignoring irrelevant information. Selective Attention is being able to select and focus on relevant information while filtering out other information.
    • Evidence suggests that children who are bilingual/multilingual develop enhanced selective Attention skills relative to their monolingual peers because they must constantly select the appropriate language to use according to situational context.
  • Background Knowledge: Information that is essential for fully understanding a situation, problem, story, etc.
    • When a student is reading a text at their reading skill level in a non-Primary Language, possessing the appropriate Background Knowledge can enhance reading comprehension.
  • Inhibition: The ability to suppress attention to irrelevant stimuli to focus on pertinent stimuli/information, both controlling responses and attention
    • Research suggests that being bilingual/multilingual enhances cognitive Inhibition skills because of the need to constantly inhibit the language not currently in use.
  • Morphological Awareness: Sensitivity to linguistic units (morphemes) including root words, prefixes, suffixes, intonations, and stress, which all convey meaning
    • Primary Language may impact Morphological Awareness because the types of morphemes can vary between languages. Therefore, if a student is learning a new language in school that uses different morphemes than their Primary Language, they may have less Morphological Awareness in this new language. Also, if similar morphemes are used in a child’s Primary and Secondary Language, Morphological Awareness skills can transfer from a child’s Primary to Secondary Language. Thus, the similarity or differences between the languages a child is learning can impact their language development in each language.
  • Sight Recognition: The ability to recognize a word by sight rather than needing to decode the word
    • Students attending school taught in a non-Primary Language have less exposure to this language and therefore have a lower rate of Sight Recognition and acquisition of sight words in this non-Primary language.
  • Socioeconomic Status (SES): A combination of factors including education and income of a family compared to other families
    • In the United States, a disproportionate number of bilingual children live in low SES homes, and bilingual children from low SES homes experience more difficulties when learning to read compared to their peers who come from middle class homes.
  • Vocabulary: Includes both the lexical representations of stored sounds (word forms) and the semantic meaning associated with each of those stored sounds
    • Bilingual/multilingual children often initially have lower expressive/receptive Vocabulary in each language when compared to monolingual peers because they are exposed to specific Vocabulary in one language but not the other (e.g., a child who speaks Spanish at home but attends an English-speaking school may know school-related words like “pencil” and “desk” in English but not Spanish).

Research Findings

  • English language learners in the United States who speak Spanish as their first language have significantly lower rates of reading achievement relative to other minorities and Caucasian children (McCardle, Keller-Allen, & Shuy, 2008; Lesaux et al., 2010).
  • In the United States, bilingual homes are disproportionately low SES homes, and thus these families often must cope with the challenges that come with living in poverty (Haskins, Greenberg, & Fremstad, 2004). Because SES is often confounded with bilingual/multilingual status, it can be difficult to tease apart the impact of poverty and Primary Language on language development.
  • Studies of preschool children who are acquiring two languages have found that they often possess lower levels of skill in each language relative to monolingual peers (Marchman, Fernald, & Hurtado, 2010), and this is true even when the two groups are matched for SES (Hoff et al., 2011). While there are many advantages to being bilingual and multilingual, educators should be aware that dual and multiple language learners follow different learning trajectories than monolingual peers.
  • Gonzalez and colleagues (2016) examined a group of Spanish-speaking English language learners in preschool from low-income (SES) homes. They identified distinct profiles revealing four patterns of strengths and weaknesses in early literacy (letter recognition/Alphabet Knowledge and Phonological Awareness) and language-related measures in English and Spanish (e.g., expressive/receptive Vocabulary, auditory comprehension, repeating simple sentences, story recall). The authors concluded that the individual strengths and weaknesses of dual language learners should be considered when teaching literacy skills in the classroom. They also recommend the assessment of a broad range of skills in order to identify the specific needs of individual students rather than focusing on one factor (such as Vocabulary). They found that early literacy skills (letter recognition and Phonological Awareness), as well as language skills, varied significantly across dual language learners.
    • They identified four distinct profiles: (1) Low English Language, Average Spanish Language, and Mixed Spanish Code-Related, (2) Average English Language, Strengths in Spanish Language, and Spanish Code-Related, (3) Mixed English and Spanish Language and Low Spanish Code-Related, and (4) high English Language, Average Spanish Language, and Mixed Spanish Code-Related.
  • Ramirez and colleagues (2010) investigated the effects of Morphological Awareness in Spanish-speaking English language learners. They found that Spanish Morphological Awareness was related to word reading skills in Spanish. Moreover, they found evidence of cross-linguistic transfer of Morphological Awareness skills from Spanish to English, but not vice versa. This is an example of a language skill in one language impacting outcomes in the second language.
  • Mancilla-Martinez and Lesaux (2010) conducted a longitudinal study examining the contributions of initial status (at age 4.5) and rate of growth in both Vocabulary (measured in both Spanish and English using a picture-naming task) and word reading skills to English reading comprehension in low-achieving Spanish-speaking children. The participants were followed between ages 4.5 to 8, and a portion of these students were recruited to investigate reading comprehension skills at the age of 11. Word reading and English Vocabulary were found to influence English reading comprehension at age 11, but word reading had a greater impact. Also, the average English reading comprehension of these fifth grade students was at the second grade level, and their Vocabulary skills plateaued at the level equivalent to an 8.5- to 9-year-old monolingual English speaker. Yet, their word reading skills were in the average range. The authors suggest that it might be possible to identify poor comprehenders on the basis of a profile of low Vocabulary and average age-appropriate word level reading skills. They also suggest that an emphasis be placed on boosting Vocabulary knowledge in language learners, which will in turn enhance their ability to gain Vocabulary and word knowledge from their own independent reading.
  • Swanson, Orosco, and Lussier (2015) examined visual-spatial Working Memory, verbal Working Memory, and phonological Short-term Memory in a group of 410 children in the 1st to 3rd grades whose first language was Spanish. The measures were administered at baseline, one year post, and two years post baseline. They discovered that growth in Working Memory skills underlies growth in second language skills.
  • Many studies have found that bilingual/multilingual children have certain cognitive advantages relative to their monolingual peers (Morton & Harper, 2007; Bialystok & Senman, 2004; Foy & Mann, 2015). Specifically, these studies have found that bi/multilinguals have better cognitive control abilities. Cognitive control is the ability to consciously act according to goals and resolve interference. It is achieved through a combination of cognitive skills including Inhibition and Attention. This is likely because children are required to actively inhibit the language(s) that is/are not currently in use in order to use the desired language at that point in time. They also must monitor contextual cues and selectively attend to the appropriate language according to the particular situation. This constant monitoring, Inhibition, and selective Attention all serve to boost these cognitive skills. Further research is required to fully understand the details of this bilingual cognitive advantage (see Barac et al., 2014 for a review).
  • Burns and Helman (2009) examined the relationship between English oral language proficiency and acquisition rate of sight words (part of Sight Recognition) among a population of 2nd-grade dual language learners from Hmong-speaking households. Students were grouped into low, middle, and high English proficiency groups. A significant correlation was found between oral proficiency in English and acquisition rate where students in the low proficiency group demonstrated a significantly smaller acquisition rate relative to the students in the middle and high proficiency groups. The authors proposed that children with limited English proficiency have less experience with the sight words and thus had more difficulty learning at the same rate as students with better English proficiency.
  • Droop and Verhoeen (1998) examined and compared the role of Background Knowledge in reading comprehension in Dutch, Turkish and Moroccan children living in the Netherlands. Dutch was the native language of the Dutch children, and it was the second language for the Turkish and Moroccan children. The students were given three types of texts, including texts referring to Dutch culture, texts referring to Turkish and Moroccan cultures, and neutral texts. Their results revealed that possessing Background Knowledge provides children with a significant benefit in the areas of reading comprehension (measured by accuracy on recall task) and reading efficiency (as measured by number of words read correctly per minute). They also found that when texts are presented in a child’s secondary language, the benefit of Background Knowledge disappears if the linguistic (syntactic and semantic) complexity of the text is beyond the child’s current reading skill level.

References

Barac, R., Bialystok, E., Castro, D. C., & Sanchez, M. (2014). The cognitive development of young dual language learners: A critical review. Early Childhood Research Quarterly, 29(4), 699-714.

Bialystok, E., & Senman, L. (2004). Executive processes in appearance–reality tasks: The role of inhibition of attention and symbolic representation. Child Development, 75(2), 562-579.

Burns, M. K., & Helman, L. A. (2009). Relationship between language skills and acquisition rate of sight words among English language learners. Literacy Research and Instruction, 48(3), 221-232.

Droop, M., & Verhoeven, L. (1998). Background knowledge, linguistic complexity, and second-language reading comprehension. Journal of Literacy Research, 30(2), 253-271.

Foy, J. G., & Mann, V. A. (2013). Bilingual children show advantages in nonverbal auditory executive function task. International Journal of Bilingualism, 18(6), 717-729.

Gonzalez, J., Pollard-Durodola, S., Saenz, L., Soares, D., Davis, H., Resendez, N., & Zhu, L. (2016). Spanish and English early literacy profiles of preschool Latino English language learner children. Early Education and Development, 27(4), 513-531.

Haskins, R., Greenberg, M., & Fremstad, S. (2004). Federal policy for immigrant children: Room for common ground? (Policy Brief). The Future of Children, 14(2), 2-6.

Hoff, E. (2013). Interpreting the early language trajectories of children from low-SES and language minority homes: Implications for closing achievement gaps. Developmental Psychology, 49(1), 4-14.

Hoff, E., Core, C., Place, S., Rumiche, R., Señor, M., & Parra, M. (2012). Dual language exposure and early bilingual development. Journal of Child Language, 39(1), 1-27.

Lesaux, N. K., Crosson, A. C., Kieffer, M. J., & Pierce, M. (2010). Uneven profiles: Language minority learners’ word reading, vocabulary, and reading comprehension skills. Journal of Applied Developmental Psychology, 31(6), 475-483.

Mancilla‐Martinez, J., & Lesaux, N. K. (2011). The gap between Spanish speakers’ word reading and word knowledge: A longitudinal study. Child Development, 82(5), 1544-1560.

Marchman, V. A., Fernald, A., & Hurtado, N. (2010). How vocabulary size in two languages relates to efficiency in spoken word recognition by young Spanish–English bilinguals. Journal of Child Language, 37(04), 817-840.

McCardle, P., Keller-Allen, C., & Shuy, T. (2008). Learning disability identification. In E. Grigorenko (Ed.), Educating individuals with disabilities (pp. 137–164). New York, NY: Springer.

Morton, J. B., & Harper, S. N. (2007). What did Simon say? Revisiting the bilingual advantage. Developmental Science, 10(6), 719-726.

Ramirez, G., Chen, X., Geva, E., & Kiefer, H. (2010). Morphological awareness in Spanish-speaking English language learners: Within and cross-language effects on word reading. Reading and Writing, 23, 337-358.

Swanson, H. L., Orosco, M. J., & Lussier, C. M. (2015). Growth in literacy, cognition, and working memory in English language learners. Journal of Experimental Child Psychology, 132, 155-188.

 

Safety

Safety is an important factor when considering how well students can learn at school. Students who attend safe schools where they feel protected are better able to focus on learning, whereas students in unsafe schools are more likely to miss school and, when they are at school, tend to participate less often in classroom discussions/activities (Boyd, 2004; Hernandez & Seem, 2004). Research has demonstrated that children who are bullied experience higher levels of depression, anxiety (part of Emotion), and other mental health disorders, which can all result in lower levels of academic achievement (Hymel, Schonert-Reichl, & Miller, 2006; Rivers et al., 2009; Schwartz et al., 2005; Whitted & Dupper, 2005). Thus, feeling safe both at school and at home can have a significant impact on a child’s ability to succeed academically.

Assessments

  • Physical Safety can be assessed using self-report on a Likert scale. For example, parents may be asked to rate the Safety of their neighborhood on a scale from 1 to 3, where 1 = not at all safe, 2 = somewhat safe, and 3 = very safe.
  • Student perceptions of school Safety can be assessed using a survey on a Likert scale. Questionnaires may ask questions about how safe students feel at school, how comfortable they feel participating in classroom discussions and activities, and how often students are bullied or teased.
  • The Classroom Victimization Observation System (CVOS) (see Reuland & Mikami, 2014 for details): A tool that can be used to document and code peer victimization incidents in the classroom, as well as the teacher’s response to victimization. Observers are trained on the specific coding system, which includes definitions of verbal, physical, covert, and relational aggression, as well as exclusion.
    • Verbal aggression is defined as name-calling, laughing at a rejected child, or criticism.
    • Physical aggression includes pushing, hitting, or kicking.
    • Covert aggression is defined as stealing or hiding a child’s possessions.
    • Relational aggression involves spreading rumors or lies about a child.
    • Exclusion is defined as leaving a child out or not wanting to be the child’s partner or playmate.
  • The Peer Victimization Scale (Austin & Joseph, 1996): An assessment of bullying behavior at school for children between ages 8 to 11.
  • The Neighborhood Safety Subscale (NSS) (Posner & Vandell, 1994): A subscale of the Self-Care Checklist – Parent questionnaire that measures perceived neighborhood safety.

Learner Factor Connections

  • Emotion: A complex psychological state that involve a subjective experience and can result in a physiological and behavioral response. Anxiety is intense worry or fear and in individuals with an anxiety disorder, these feelings will not subside over time. While, depression is a mood disorder causing feelings of sadness and hopelessness that have a significant negative impact on a student’s ability to participate in daily activities and succeed in school.
    • Children who are bullied at school are at risk for developing anxiety and depressive disorders.
  • Physical Fitness: Overall health and physical well-being that is dependent on several important factors including proper nutrition, regular exercise, and an adequate amount of Sleep
    • Children living in less safe neighborhoods have fewer opportunities to play outside than children living in safe neighborhoods. Thus, living in a less safe neighborhood limits opportunities for obtaining regular exercise (Aikens & Barbarin, 2008; Franzini et al., 2010).
  • Socioeconomic Status (SES): A combination of factors including education and income of a family compared to other families
    • Poorer neighborhoods are often less safe, due to higher crime rates, than more affluent neighborhoods (Franzini et al., 2010).
  • Trauma: Emotional distress resulting from experiencing violence, abuse, a disaster, or an accident. Interpersonal trauma refers to Trauma that has occurred between people (e.g., assault or abuse), whereas non-interpersonal Trauma refers to Trauma inflicted by some other source (e.g., a motor vehicle accident, a natural disaster).
    • Experiencing Trauma, and especially interpersonal Trauma, will cause children to feel less safe in their environment.

Research Findings

Neighborhood Safety

  • Aikens and Barbarin (2008) investigated how school and neighborhood factors, including neighborhood Safety, interact with other variables, like family and school, to account for the impact that SES has on children’s early literacy skills. Neighborhood Safety and neighborhood conditions were assessed using parent reports on a questionnaire. The data in this study were from the Early Childhood Longitudinal Study, Kindergarten Cohort of 1998-1999 where data was gathered from a nationally representative sample of American children. A sample of 17,401 students was used in the current study assessing school and neighborhood factors on reading development. They found that neighborhood Safety was an important factor in reading skill acquisition rates. Students living in unsafe neighborhoods experienced a slower rate of reading skill acquisition. This difference between students living in unsafe vs. safe neighborhoods was most obvious between the spring of kindergarten and the spring of 1st grade, which is the most rapid time period of reading skill growth. Thus, it was concluded that neighborhood Safety can account for some of the impact that SES has on reading skill development, with Home Literacy Environment (HLE) also an important factor. Children from homes with a stronger HLE began kindergarten with better reading skills than children from a weaker HLE. Children from homes with a stronger HLE also experienced a faster rate of growth.
  • Children who live in less safe neighborhoods have fewer opportunities to play outside than children living in safe neighborhoods. Thus, living in a less safe neighborhood limits opportunities for obtaining regular exercise (part of Physical Fitness) (Aikens & Barbarin, 2008; Franzini et al., 2010).

School Safety and Bullying

  • Gietz and McIntosh (2014) examined how student perceptions of school Safety and experiences being bullied (while controlling for school-level poverty) impacted their academic performance. This study included participants from 969 elementary and 73 middle schools in Canada. Academic performance in reading comprehension and numeracy skills was investigated in grades 4 and 7. The researchers found that bullying/victimization at school and school Safety (as perceived by the students) was a significant predictor of reading comprehension skills measured in the 4th grade. Victimization at school was the strongest predictor of 4th grade literacy (and numeracy). Moreover, a stronger relationship between student victimization and academic achievement existed in grade 4 relative to grade 7. Students were more likely to be victims of bullying in the 4th relative to the 7th grade.
  • Reuland and Mikami (2014) examined victimization in the classroom and its relationship with reading achievement scores. Trained observers reviewed 28 elementary classrooms from three schools in Virginia using the CVOS (see above section on assessments). Academic achievement was measured by achievement tests that were administered in the fall, winter, and spring over the course of one school year. They found that even under teacher supervision, peer victimization is very common in elementary classrooms. Bullying incidents in the classroom primarily consist of verbal aggression and exclusion behaviors. Also, teachers only responded to victimization incidents approximately 50% of the time. Additionally, lower victimization was a predictor of higher average reading achievement scores.
  • Alisic and colleagues (2014) conducted a literature review of 72 peer-reviewed articles to investigate the factors that can lead to post-traumatic stress disorder (PTSD) when children and adolescents have been exposed to Trauma. Overall, 15.9% of youth exposed to Trauma experienced PTSD; however, the rates varied based on gender and type of trauma. Girls exposed to interpersonal Trauma (Trauma between people such as abuse) are at the highest risk of developing PTSD, with 32.9% PTSD rate. Boys exposed to non-interpersonal Trauma (Trauma that is not between people) were at the lowest risk of developing PTSD (8.4% PTSD rate). The authors explained that interpersonal Trauma is more likely to lead to PTSD because it is often more chronic and leads to self-blame more often than non-interpersonal Trauma. Moreover, interpersonal Trauma can destroy Social Supports and make children feel less safe, particularly when a family member is the perpetrator, which also represents a serious betrayal of trust in a way that severely negatively impacts a child’s ability to function normally.

References

Aikens, N. L., & Barbarin, O. (2008). Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts. Journal of Educational Psychology, 100(2), 235-251.

Alisic, E., Zalta, A. K., Van Wesel, F., Larsen, S. E., Hafstad, G. S., Hassanpour, K., & Smid, G. E. (2014). Rates of post-traumatic stress disorder in trauma-exposed children and adolescents: meta-analysis. The British Journal of Psychiatry, 204(5), 335-340.

Austin, S., & Joseph, S. (1996). Assessment of bully/victim problems in 8–11 year-olds. British Journal of Educational Psychology, 66, 447-456.

Boyd, K. S. (2004). The association between student perceptions of safety and academic achievement: The mediating effects of absenteeism. Paper presented at the annual meeting of the American Sociological Association, San Francisco, CA.

Franzini, L., Taylor, W., Elliott, M. N., Cuccaro, P., Tortolero, S. R., Gilliland, M.J., … Schuster, M. A. (2010). Neighborhood characteristics favorable to outdoor physical activity: Disparities by socioeconomic and racial/ethnic composition. Health & Place, 16(2), 267-274.

Gietz, C., & McIntosh, K. (2014). Relations between student perceptions of their school environment and academic achievement. Canadian Journal of School Psychology, 29(3), 161-176.

Hernandez, T. J., & Seem, S. R. (2004). A safe school climate: A systems approach and the school counselor. Professional School Counseling, 7, 256-262.

Hymel, S., Schonert-Reichl, K. A., & Miller, L. (2006). Reading, ‘riting, ‘rithmetic and relationships: Considering the social side of education. Exceptionality Education Canada, 16(3), 1-44.

Posner, J. K., & Vandell, D. L. (1994). Low-income children’s after-school care: are there beneficial effects of after-school programs? Child Development, 65, 440-456.

Reuland, M. M., & Mikami, A. Y. (2014). Classroom victimization: Consequences for social and academic adjustment in elementary school. Psychology in the Schools, 51(6), 591-607.

Rivers, I., Poteat, V. P., Noret, N., & Ashurst, N. (2009). Observing bullying at school: The mental health implications of witness status. School Psychology Quarterly, 24, 211-223.

Schwartz, D., Gorman, A. H., Nakamoto, J., & Toblin, R. L. (2005). Victimization in the peer group and children’s academic functioning. Journal of Educational Psychology, 97(3), 425-435.

Whitted, K. S., & Dupper, D. R. (2005). Best practices for preventing or reducing bullying in schools. Children & Schools, 27(3), 167-173.

 

Sleep

Obtaining the right amount (quantity) and good quality of Sleep is important for a variety of cognitive and language skills that are essential for academic success, including learning to read. The main constructs for understanding Sleep are:

  • Sleep is a naturally occurring state involving the suspension of consciousness during which the body and the brain rest.
  • The National Sleep Foundation recommends that toddlers receive between 11 to 14 hours of Sleep, preschoolers between 10 to 13 hours, school-aged children between 9 to 11 hours, and teenagers between 8 to 10 hours (Hirschkowitz, 2015).
  • It is becoming progressively more common for children to receive less Sleep than they need (Matricciani, 2012); many children regularly fail to achieve their recommended minimum Sleep duration (National Sleep Foundation).
  • Sleep can be divided into nonrapid eye movement (NREM) and rapid eye movement (REM). NREM Sleep can be further divided into four distinct stages. Typically NREM Sleep constitutes 75-90% of Sleep, and REM Sleep accounts for the remainder. NREM and REM occur in alternating cycles, which each last about 90 minutes on average.

Assessments

  • Actigraph Sensor: Worn on the wrist to measure Sleep patterns and circadian rhythms.
  • Electroencephalogram (EEG): Measures and records the brain’s electrical activity and allows researchers to distinguish the stage of Sleep.
  • Children’s Sleep Habits Questionnaire (Owens et al., 2000): A parent questionnaire that measures Sleep behaviors in children between ages 4 to 12.

Learner Factor Connections

  • Attention: The ability to focus on a specific task without being distracted, as well as the ability to select relevant information while ignoring irrelevant information. Sustained Attention, the ability to maintain focus
    • Insufficient Sleep can lead to impairments in sustained Attention abilities.
  • Inhibition: The ability to suppress attention to irrelevant stimuli to focus on pertinent stimuli/information, both controlling responses and attention
    • Behavioral Inhibition declines when students do not obtain the optimal amount and quality of Sleep.
  • Physical Fitness: A state of overall health and physical well-being
    • Acquiring the right amount of quality Sleep is an essential component of maintaining Physical Fitness.
  • Sensory Integration: The process of receiving, processing, and organizing multiple sources of sensory information from the environment
    • Children with Sensory Integration difficulties (and particularly children with sensitivity to touch) often experience Sleep disturbances.
  • Working Memory: The type of memory that allows a person to temporarily hold and manipulate information for use in many complex cognitive processes
    • Sleep, and especially the quality of Sleep, that a child receives is important for Working Memory processes to operate accurately and efficiently.

Research Findings

Sleep restriction in children is associated with cognitive impairments particularly on more demanding cognitive tasks:

  • Randazzo and colleagues (1998) examined performance on a battery of psychomotor and cognitive tests in a group of children (age range = 10 to 14 years) assigned to sleep restriction (5 hours in bed) relative to a control group (11 hours in bed). They found that the sleep-deprived group of children performed significantly worse on a task of learning abstract concepts and verbal creativity. However, memory was not affected, which the authors attributed to Motivation overcoming sleepiness on some tasks.
  • Steenari and colleagues (2003) examined how Sleep quality and quantity (measured using actigraphy) would impact performance on auditory and visual Working Memory tasks (n-back tasks) in a group of 6- to 13-year-olds. Children with lower Sleep quality (less efficient and longer time before going to Sleep) performed worse on almost all memory load levels. Lower Sleep quantity was also associated with worse performance on some measures. Overall their findings suggest that Sleep quality was more important than Sleep quantity on the performance on Working Memory tasks. The authors suggest that measures of Sleep, and especially Sleep quality, be considered when children are experience academic difficulties.
  • Sadeh and colleagues (2002) measured Sleep activity (using actigraphy) for five consecutive nights in a group of school-age children (age range = 7.2 to 12.7 years). The children were identified as either poor sleepers (more fragmented Sleep or reduced Sleep efficiency) or good sleepers. The good sleepers performed significantly better than the poor sleepers on a declarative memory task (serial digit learning test) in a morning but not noon testing session. Performance on more complex tasks was correlated with poor Sleep. Also, they found a stronger correlation between Sleep and neurobehavioral functioning in younger children. Overall, they found that poor Sleep was associated with difficulty sustaining Attention and behavioral Inhibition.
  • In a review paper, Koenig and Rudney (2010) reviewed papers that examined Sensory Integration and its impact on Sleep, activities of daily living, social participation, and education in children and adolescents. This review suggests that children with tactile sensitivity exhibited a high rate of Sleep disturbances. Also, children with Sensory Integration difficulties show decreased quality/quantity of play skills and lower ratings of Social Awareness. Those with high sensory overresponsivity possess the weakest social skills. Moreover, children with these difficulties display lower participation in school activities. Thus, difficulty with Sensory Integration and processing can lead to difficulties with social participation, Sleep, and participating in classroom activities.
  • Short Sleep duration has been linked to increased risk of obesity (Cappuccio et al., 2008), likely because Sleep loss leads to metabolic and hormonal changes that can impact weight gain (Beccuti & Pannain, 2011).

A correlation exists between dyslexia and Sleep disturbances:

  • Carotenuto and colleagues (2016) evaluated the prevalence of Sleep disturbances in children with developmental dyslexia relative to a group of healthy controls. They found that Sleep disorders, and particularly those associated with initiating and maintaining Sleep, were significantly more frequently in the group of children with dyslexia.
  • Bruni and colleagues (2009) used EEG to measure non-rapid eye movement (NREM) Sleep activity in a group of children with dyslexia (mean age = 10.1 years) relative to a group of healthy controls. They found differences in Sleep spindle activity (which indicates repeated activation of thalamocortical or hippocampo-cortical networks) in the group of children with dyslexia that was correlated with the degree of impairment (as measured by the Word Reading test). They conclude that differences in Sleep patterns between children with dyslexia and controls point to an overactivation of thalamocortical and hippocampal circuitry in order to overcome reading difficulties.

References

Beccuti, G., & Pannain, S. (2011). Sleep and obesity. Current Opinion in Clinical Nutrition and Metabolic Care, 14(4), 402-412.

Bruni, O., Ferri, R., Novelli, L., Terribili, M., Troianiello, M., Finotti, E., … Curatolo, P. (2009). Sleep spindle activity is correlated with reading abilities in developmental dyslexia. Sleep, 32(10), 1333-1340.

Cappuccio, F. P., Taggart, F. M., Kandala, N., Currie, A., Peile, E., Stranges, S., & Miller, M. A. (2008). Meta-analysis of short sleep duration and obesity in children and adults. Sleep, 31(5), 619-626.

Carotenuto, M., Esposito, M., Cortese, S., Laino, D., & Verrotti, A. (2016). Children with developmental dyslexia showed greater sleep disturbances than controls, including problems initiating and maintaining sleep. Acta Paediatrica, 105, 1079-1082.

Hirshkowitz, M., Whiton, K., Albert, S., Alessi, C., Bruni, O., DonCarlos, L., … Katz, E.S. (2015). National Sleep Foundation’s sleep time duration recommendations: Methodology and results summary. Sleep Health, 1(1), 40-43.

Koenig, K. P., & Rudney, S. G. (2010). Performance challenges for children and adolescents with difficulty processing and integrating sensory information: A systematic review. American Journal of Occupational Therapy, 64(3), 430-442.

Matricciani, L., Olds, T., & Petkov, J. (2012). In search of lost sleep: Secular trends in the sleep time of school-aged children and adolescents. Sleep Medicine Reviews, 16(3), 203-211.

National Sleep Foundation. 2014 Sleep in America Poll – Sleep in the Modern Family: Summary of Findings (2014). Retrieved from: https://sleepfoundation.org/sleep-polls-data/2014-sleep-the-modern-family

Owens, J. A., Spirito, A., & McGuinn, M. (2000). The Children’s Sleep Habits Questionnaire (CSHQ): Psychometric properties of a survey instrument for school-aged children. Sleep, 23(8), 1043-1052.

Randazzo, A. C., Muehlbach, M. J., Schweitzer, P. K., & Walsh, J. K. (1998). Cognitive function following acute sleep restriction in children ages 10-14. Sleep, 21(8), 861-868.

Sadeh, A., Gruber, R., & Raviv, A. (2002). Sleep, neurobehavioral functioning, and behavior problems in school‐age children. Child Development, 73(2), 405-417.

Steenari, M. R., Vuontela, V., Paavonen, E. J., Carlson, S., Fjällberg, M., & Aronen, E. T. (2003). Working memory and sleep in 6-to 13-year-old schoolchildren. Journal of the American Academy of Child & Adolescent Psychiatry, 42(1), 85-92.

 

Social Supports

Social Supports are the perception of the support network, including parents, friends, and teachers, that is available to help if needed. Two key aspects of Social Supports are peer relationships and external supports, including parents, teachers, and other family members. The quality of peer relationships depends upon Social Awareness and Relationship Skills.

Social Supports can include (Malecki & Demaray, 2007):

  • Emotional support: Refers to caring behaviors;
  • Appraisal support: Involves receiving feedback from others;
  • Instrumental support: Can be providing resources like time and money; and
  • Information support: Refers to information/advice.

Social Supports can be beneficial even when students do not take advantage of all forms of support; rather, it is important that children perceive these Social Supports are available to them.

Assessments

  • Child and Adolescent Social Support Scale (CASSS) (Malecki et al., 2000): 60 items rating a child’s perceived support from five sources: parents, teachers, classmates, close friends, and the school. Students rate the items on a six point Likert scale, and support from these five sources are rated.
  • Social Support Scale for Children (SSSC) (Harter, 1985): 24-items that assess social support from parents, teachers, classmates, and friends.
  • Penn Interactive Peer Play Scale (PIPPS) (Fantuzzo & Hampton, 2000): Assesses whether a child has positive and successful relationships with their peers. It consists of 32 items that are each answered with a 4-point Likert scale. A teacher or a parent can fill out the questionnaire that evaluates behaviors observed by the teacher/parent between the child and their peers. This assessment has three dimensions: (1) Play Interaction which indicates the child’s strengths during play, (2) Play Disruption which describes any aggressive or antisocial behaviors, and (3) Play Disconnection which describes withdrawing behaviors or the lack of participation in peer play.
  • Strength and Difficulties Questionnaire (SDQ) (Goodman, Meltzer, & Bailey, 1998): 25 items that are scored with a 3-point Likert scale. This questionnaire contains five subscales that measure peer relationships (e.g., how often the child plays alone) and prosocial behavior (e.g., whether the child is considerate of others), in addition to other factors such as conduct problems, hyperactivity and inattention, and emotional regulation difficulties. The student, the student’s teachers, or the student’s parents can answer the questionnaire items.

Learner Factor Connections

  • Alphabet Knowledge: Familiarity with letter names, forms, and corresponding sounds
    • Students with positive relationships with their peers often have better Alphabet Knowledge than students who do not have these strong relationships. This may be because positive peer relationships are a key factor in a student’s engagement at school. Another possibility is peer relationship skills partially depend upon language and literacy skills. Thus, stronger language and literacy skills, including Alphabet Knowledge, contribute to forming stronger peer relationships.
  • Emotion: A complex psychological state that involves a subjective experience and can result in a physiological and behavioral response. Anxiety is intense worry or fear, and in individuals with an anxiety disorder, these feelings will not subside over time. Depression is a mood disorder causing feelings of sadness and hopelessness that have a significant negative impact on a student’s ability to participate in daily activities and succeed in school. Emotion regulation is the ability to control emotional arousal in order to facilitate adaptive functioning.
    • Students who are rejected by their peers or are bullied at school have poor peer relationships, which are essential to Social Supports, and are at risk for developing anxiety and depressive disorders. Also, students who have better Emotion regulation skills experience higher levels of acceptance by their peers, which results in better peer Social Supports.
  • Phonological Awareness: The knowledge of and ability to manipulate and detect sounds in words
    • Students with better peer relationships also tend to have better Phonological Awareness skills. This is possibly because positive peer relationships contribute to a student’s engagement in the classroom. Another possibility is that peer relationships skills partially depend on language comprehension and production skills. Thus, stronger language skills, such as Phonological Awareness, contribute to the formation of stronger peer relationships.
  • Social Awareness & Relationship Skills: Understanding social norms for behavior and understanding the perspective of others contributes to interpersonal skills
    • The quality of peer relationships, which are vital to Social Supports, depend on a student’s Social Awareness & Relationship Skills.
  • Socioeconomic Status (SES): A combination of factors including education and income of a family compared to other families
    • Children who live in poverty have less Instrumental Supports than children living in middle- or high-income homes.
  • Trauma: Emotional distress resulting from experiencing violence, abuse, a disaster, or an accident. Interpersonal trauma refers to Trauma that has occurred between people (e.g., assault or abuse), whereas non-interpersonal Trauma refers to Trauma inflicted by some other source (e.g., a motor vehicle accident, a natural disaster).
    • Social Supports can erode when a child experiences Trauma, particularly interpersonal Trauma and even more specifically when a child’s family members or members of the community are involved in inflicting violence and abuse.

Research Findings

  • Malecki and Demaray (2006) examined Social Supports (using the CASSS) and academic performance (measured by GPA) in a group of 164 middle school students. The students were classified as low or higher SES in order to investigate the relationship between SES and Social Supports. No correlation was revealed between academic performance and Social Supports in children from higher SES homes. However, moderate associations between academic performance and Social Supports were discovered in children from low SES homes. Their research suggested that the relationship between poverty and academic performance may be partially moderated by Social Supports.
  • Rueger, Malecki, and Demaray (2008) examined the impact of Social Supports from parents, teachers, classmates, friends, and school (measured using the CASSS) and the impact of gender on academic performance (GPA) and psychological adjustment (self-esteem and depressive and anxiety symptoms) in 636 middle school students. These areas were assessed at two time points, one at the beginning of the academic year and one in the spring near the end of the year. Support from classmates was a unique predictor of academic performance and adjustment for boys. Support from parents was a unique predictor of academic performance and adjustment for both boys and girls. While boys and girls rated parental support similarly, girls rated all other forms of support as higher than boys. Also, parental support was a predictor of higher self-esteem, lower level of depressive symptoms, and a higher GPA in boys. All forms of support were correlated with measures of academic performance and psychological adjustment.
  • Gooren and colleagues (2011) examined the relationship between conduct problems and depression (part of Emotion) in kindergarteners (n = 323) over the course of two years. They found that the development of conduct problems led to higher rates of peer rejection, which subsequently led to depressive symptoms.
  • Kim and Cicchetti (2010) conducted a longitudinal study to examine how child maltreatment interacted with Emotion regulation, peer acceptance/rejection, and psychopathology in a group of 215 maltreated and 206 nonmaltreated children between ages 6 to 12. Children who experienced Trauma were identified through the County Department of Social Services, and the nonmaltreated children were recruited from families who required temporary assistance because most of the members of maltreated families also required income assistance. Children who were maltreated were more likely to experience difficulties with Emotion regulation, which led to more aggressive and delinquent behaviors. These conduct problems subsequently led to higher rates of peer rejection. In this way, experiencing Trauma can lead to higher rates of peer rejection and poor peer Social Supports.
  • Rouse and Fantuzzo (2006) investigated the relationship between early literacy skills (measured by DIBELS subtests) and peer relationships (as measured by the PIPPS) in a group of kindergarten students in a district that primarily educates low-income minority students. They found that peer interactions during free play were significantly correlated with scores on Letter Naming (Alphabet Knowledge), Nonsense Words (Alphabet Knowledge), and Phoneme Segmentation (Phonological Awareness).
  • Johnson (2014) examined whether and how hyperactivity (difficulties with Attention) and peer relationships (as measured by the SDQ) impact academic performance in a group of 129 students in 1st to 6th grades in an urban school district in the Northeast. The results indicated that difficulties with peer relationships were correlated with lower reading comprehension scores. Overall students who had the highest reading comprehension scores also were in the “low peer problems,” “low conduct problems,” and “low hyperactivity” group.
  • Hartas (2012) investigated the relationship between prosocial behavior (part of Social Awareness and Relationship Skills factor), hyperactivity, emotional difficulties, and language and literacy abilities in a cohort of children from the Millennium Cohort Study (MCS) who were ages 3, 5, and 7. Prosocial behavior and hyperactivity were measured using both parent and teacher ratings on the SDQ. They found that prosocial behaviors were correlated with language and literacy skills. The author discussed that a child’s receptive/expressive language skills may impact teacher and parent perceptions of a child’s behavior. They explain that the relationship between behavior (which contributes to parent and teacher ratings of peer relationships), peer relationships, and language/literacy skills is very complex. Yet, there is clearly a relationship between positive peer relationships, Phonological Awareness, and Alphabet Knowledge. Also, difficulties with prosocial behavior and hyperactivity decreased over the three to seven year period, whereas ratings of emotional difficulties remained stable.
  • Alisic and colleagues (2014) conducted a literature review of 72 peer-reviewed articles to investigate the factors that can lead to post-traumatic stress disorder (PTSD) after children and adolescents have been exposed to Trauma. Overall, 15.9% of youth exposed to Trauma experienced PTSD; however the rates varied based on gender and type of trauma. Girls exposed to interpersonal Trauma (Trauma between people such as abuse) are at the highest risk of developing PTSD, with 32.9% PTSD rate. Boys exposed to non-interpersonal Trauma (Trauma that is not between people) were at the lowest risk of developing PTSD (8.4% PTSD rate). The authors explained that interpersonal Trauma is more likely to lead to PTSD because it is often more chronic and leads to self-blame more often than non-interpersonal Trauma. Moreover, interpersonal Trauma can destroy Social Supports and make children feel less safe, particularly when a family member is the perpetrator, which also represents a serious betrayal of trust in a way that severely negatively impacts a child’s ability to function normally.

References

Alisic, E., Zalta, A. K., Van Wesel, F., Larsen, S. E., Hafstad, G. S., Hassanpour, K., & Smid, G. E. (2014). Rates of post-traumatic stress disorder in trauma-exposed children and adolescents: meta-analysis. The British Journal of Psychiatry, 204(5), 335-340.

Fantuzzo, J. W., & Hampton, V. R. (2000). Penn Interactive Peer Play Scale: A parent and teacher rating system for young children. In K. Gitlin-Weiner, A. Sandgrund, & C. Schaefer (Eds.), Play diagnosis and assessment (2nd edition) (pp. 599-620). New York: Wiley.

Goodman, R., Meltzer, H., & Bailey, V. (1998). The Strengths and Difficulties Questionnaire: A pilot study on the validity of the self-report version. European Child & Adolescent Psychiatry, 7(3), 125-130.

Gooren, E. M., van Lier, P. A., Stegge, H., Terwogt, M. M., & Koot, H. M. (2011). The development of conduct problems and depressive symptoms in early elementary school children: The role of peer rejection. Journal of Clinical Child & Adolescent Psychology, 40(2), 245-253.

Hartas, D. (2012). Children’s social behaviour, language and literacy in early years. Oxford Review of Education, 38(3), 357-376.

Harter, S. (1985). Manual for the social support scale for children. Denver: University of Denver.

Johnson, K. F. (2013). The cumulative effect of hyperactivity and peer relationships on reading comprehension. Journal of Education and Training Studies, 2(1), 98-102.

Kim, J., & Cicchetti, D. (2010). Longitudinal pathways linking child maltreatment, emotion regulation, peer relations, and psychopathology. Journal of Child Psychology and Psychiatry, 51(6), 706-716.

Malecki, C. K., & Demaray, M. K. (2006). Social support as a buffer in the relationship between socioeconomic status and academic performance. School Psychology Quarterly, 21(4), 375-395.

Malecki, C. K., Demaray, M. K., & Elliott, S. N. (2000). The Child and Adolescent Social Support Scale. DeKalb, IL: Northern Illinois University.

Rouse, H. L., & Fantuzzo, J. W. (2006). Validity of the dynamic indicators for basic early literacy skills as an indicator of early literacy for urban kindergarten children. School Psychology Review, 35(3), 341-355.

Rueger, S. Y., Malecki, C. K., & Demaray, M. K. (2008). Gender differences in the relationship between perceived social support and student adjustment during early adolescence. School Psychology Quarterly, 23(4), 496-514.

 

Socioeconomic Status (SES)

In the United States, 22% of children live in households where the income is below the poverty level. Being raised in an economically disadvantaged home can impact children’s literacy skills for a variety of reasons (Hart & Risley, 2003). Children from economically advantaged homes may know up to 15,000 more words than children from less advantaged homes by the time they enter kindergarten (Moats, 2001). Also, being raised in a more economically advantaged home is associated with enhanced oral language comprehension skills, including Vocabulary knowledge (Kaefer, Neuman, & Pinkham, 2015). The resulting language gap often persists into the high school years (Biemiller, 2001).

Assessments

  • Parental income and parental education
  • Researchers can either choose to use individual student’s SES or an aggregated SES based on the school that the child attends (Sirin, 2005).

Learner Factor Connections

  • Background Knowledge: Information that is essential for fully understanding a situation, problem, story, etc.
    • Children with low-income backgrounds often have less Background Knowledge than children raised in middle- and high-income households. This may be because children gain Background Knowledge from books and educational materials, and children from low-income backgrounds often have less access to these in their homes and schools compared to children from middle- and high-income backgrounds.
  • Home Literacy Environment (HLE): The environment the family provides to help a child gain precursors of reading/ spelling skills including access to reading materials and exposure to reading/literacy concepts
    • The economic pressures that low income families face can negatively impact HLE. For example, parents may need to work multiple jobs resulting in less time for engaging in activities that can enhance HLE.
  • Narrative Skills: The ability to tell stories requires the development and use of a complex set of skills, including properly forming and organizing sentences, understanding and using Vocabulary, and organizing the elements of a story (e.g., setting, main characters, etc.) in a logical manner.
    • Children with low-income backgrounds often have weaker Narrative Skills than peers from middle- and high-income backgrounds. This can be changed by enhancing HLE (see above and strategies below).
  • Primary Language: The child’s language they have been exposed to from birth
    • In the United States, a disproportionate number of bilingual children live in low SES homes, and bilingual children from low SES homes experience more difficulties when learning to read compared to their peers who come from middle class homes.
  • Print Awareness: Understanding the forms, functions, and conventions of print
    • Children from low-income homes often have weaker Print Awareness skills entering kindergarten compared to children from higher income homes, likely due to interaction of SES and HLE (see above).
  • Safety: How physically and psychologically safe a child feels at home, school, and in their community
    • Poorer neighborhoods tend to be less safe due to higher crime rates than more affluent neighborhoods.
  • Social Supports: The perception of the support network, including parents, friends, and teachers, that is available to help if needed. Instrumental support refers to Social Supports that contribute resources such as time and money.
    • Children who live in poverty have less instrumental support than children living in middle- or high-income homes.
  • Syntax: The rules and principles that govern the structure and word order of sentences
    • Children raised in low SES homes tend to be exposed to less complex Syntax due to less interactions with their parents, who may need to work several jobs thus spend less time speaking with and reading to their children. Also, parent literacy skills influence their children’s literacy, possibly because parents who read more produce more complex Syntax during interactions with their children. Less exposure to complex Syntax negatively impacts syntactic development.
  • Vocabulary: Includes both the lexical representations of stored sounds (word forms) and the semantic meaning associated with each of those stored sounds. Receptive Vocabulary refers to words that a student understands and expressive Vocabulary refers to words a student can successfully produce during speech.
    • Distinct differences in productive/expressive Vocabulary emerge by age 3 between children from low SES households and those from middle-class homes. Some of these differences may occur because maternal education and literacy skills are a strong predictor of a child’s expressive Vocabulary and because children in low SES homes are exposed to significantly less Vocabulary than children from middle and high SES homes.
  • Working Memory: The type of memory that allows a person to temporarily hold and manipulate information for use in many complex cognitive processes
    • Children who are raised in low SES homes tend to have weaker Working Memory skills compared to children who live in middle or high SES homes.

Research Findings

  • Differences in Vocabulary and comprehension skills between children from high and low SES households can be partly explained by differences in Background Knowledge (Kaefer et al., 2015). Children from low SES homes have significantly less pre-existing Background Knowledge relative to children from more economically advantaged homes. No differences in word learning, comprehension, or inference making abilities were found between children from low and high SES households when Background Knowledge was held constant by introducing an unknown topic.
  • Children from low SES households are exposed to one-third of the verbiage that children from high SES are exposed to (Hart & Risley, 1995).
  • Upon entering school, children from low SES households may know half (or fewer) of the words (Vocabulary) known by typical children from middle class households and even fewer than more privileged children (Hart & Risley, 1995).
  • Studies have also shown that children from low SES homes tend to have weaker oral language and Narrative Skills than those from middle class and high SES homes (Hoff, 2013; Gardner-Neblatt, 2015).
  • Parents in low SES homes tend to have less education than those in middle or high SES homes, and when communicating with their children, parents with less education tend to use less complicated Syntax, fewer words (a smaller Vocabulary), and make fewer references to events that are not in the present (Hart & Risley, 1995).
  • Children from low-income homes who are entering kindergarten tend to have weaker Print Awareness skills than those from middle-class or high-income homes (Justice & Ezell, 2002), which has been attributed to the Home Literacy Environment (HLE). Children from low-income homes often are raised with a weaker HLE, resulting in fewer opportunities to build Print Awareness at home (e.g., less time is spent reading books to children due to the economic pressures that low-income families face).
  • Being raised in a low SES household is associated with reduced Working Memory and executive functioning abilities in 5- to 7-year-olds (Noble et al., 2005; Noble et al., 2007) and 10- to 13-year-olds (Farah et al., 2006).
  • One study suggests that HLE acts as a mediator between SES and migration background; thus SES and migration background do not directly impact literacy, but rather the influence of SES and migration background is mediated by HLE (Niklas & Schneider, 2013).
  • Aikens and Barbarin (2008) investigated how school and neighborhood factors, including neighborhood Safety, interact with other variables, like family and school, to account for the impact that SES has on children’s early literacy skills. Neighborhood Safety and conditions were assessed using parent reports on a questionnaire. The data in this study were from the Early Childhood Longitudinal Study, Kindergarten Cohort of 1998-1999 where data was gathered from a nationally representative sample of American children. A sample of 17,401 students was used in the current study assessing school and neighborhood factors on reading development. They found that neighborhood Safety was an important factor in reading skill acquisition rates. Students living in unsafe neighborhoods experienced a slower rate of reading skill acquisition. This difference between students living in unsafe vs. safe neighborhoods was most obvious between the spring of kindergarten and the spring of 1st grade, which is the most rapid time period of reading skill growth. Thus, it was concluded that neighborhood Safety can account for some of the impact that SES has on reading skill development. HLE was also an important factor. Children from homes with a strong HLE began kindergarten with better reading skills than children from a weaker HLE. Children from homes with a stronger HLE also experienced a faster rate of growth.
  • Noble and colleagues (2006) used functional magnetic resonance imaging (fMRI), a brain imaging technique, to examine brain activation during reading in 38 children between the 1st to 3rd grades. Specifically, they investigated the relationship between Phonological Awareness skills and SES in the left-hemisphere fusiform and left-hemisphere perisylvian regions (brain regions important for reading development). They found a strong relationship between individual phonological skills and brain activation in children from low SES homes, but this relationship did not exist in children from middle and high SES homes. This suggests that SES has an important impact on brain-behavior relationships.
  • Many of the negative effects of poverty on language development can be mediated by enhancing parental language usage as an aspect of HLE (e.g., increasing number of words used, using more complex Syntax) (Perkins et al., 2013).
  • Malecki and Demaray (2006) examined Social Supports (using the CASSS) and academic performance (measured by GPA) in a group of 164 middle school students. The students were classified as low or higher SES in order to investigate the relationship between SES and Social Supports. No correlation was revealed between academic performance and Social Supports in children from higher SES homes. However, moderate associations between academic performance and Social Supports were discovered in children from low SES homes. Their research suggested that the relationship between poverty and academic performance may partially be moderated by Social Supports.

References

Aikens, N. L., & Barbarin, O. (2008). Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts. Journal of Educational Psychology, 100(2), 235-251.

Biemiller, A. (2001). Teaching vocabulary: Early direct, and sequential. American Educator, 25(1), 24-28.

Farah, M. J., Shera, D. M., Savage, J. H., Betancourt, L., Giannetta, J. M., Brodsky, N., … E.K., Hurt, H. (2006). Childhood poverty: specific associations with neurocognitive development. Brain Research, 1110, 166-174.

Gardner-Neblett, N., & Iruka, I. U. (2015). Oral narrative skills: Explaining the language-emergent literacy link by race/ethnicity and SES. Developmental Psychology, 51(7), 889-904.

Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experience of young American children. Baltimore, MD: Paul H. Brookes Publishing.

Hart, B., & Risley, T. R. (2003). The early catastrophe: The 30 million word gap. American Educator, 27(1), 4-9.

Hirsch, E.D., & Moats, L. C. (2001). Overcoming the language gap. American Educator, 25(2), 8-9.

Hoff, E. (2013). Interpreting the early language trajectories of children from low-SES and language minority homes: Implications for closing achievement gaps. Developmental Psychology, 49(1), 4-14.

Justice, L.M., & Ezell, H.K. (2002). Use of storybook reading to increase print awareness in at-risk children. American Journal of Speech-Language Pathology, 11(1), 17–29.

Kaefer, T., Neuman, S. B., & Pinkham, A. M. (2015). Pre-existing background knowledge influences socioeconomic differences in preschoolers’ word learning and comprehension. Reading Psychology, 36(3), 203-231.

Malecki, C. K., & Demaray, M. K. (2006). Social support as a buffer in the relationship between socioeconomic status and academic performance. School Psychology Quarterly, 21(4), 375.

Noble, K. G., Norman, M. F., & Farah, M. J. (2005). Neurocognitive correlates of socioeconomic status in kindergarten children. Developmental Science, 8(1), 74-87.

Noble, K. G., McCandliss, B. D., & Farah, M. J. (2007). Socioeconomic gradients predict individual differences in neurocognitive abilities. Developmental Science, 10, 464-480.

Noble, K. G., Wolmetz, M. E., Ochs, L. G., Farah, M. J., & McCandliss, B. D. (2006). Brain–behavior relationships in reading acquisition are modulated by socioeconomic factors. Developmental Science, 9(6), 642-654.

Perkins, S. C., Finegood, E. D., & Swain, J. E. (2013). Poverty and language development: Roles of parenting and stress. Innovations in Clinical Neuroscience, 10(4), 10-19.

Pressley, M., Wharton-McDonald, R., Allington, R., Block, C. C., Morrow, L., Tracey, D., … Woo, D. (2001). A study of effective first-grade instruction. Scientific Study of Reading, 5(1), 35-58.

Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417-453.

Taylor, B. M., Pearson, D. P., Clark, K., & Walpole, S. (2000). Effective schools and accomplished teachers: Lessons about primary-grade reading instruction in low-income schools. The Elementary School Journal, 101(2), 121-165.

Trauma

Experiencing Trauma in childhood can result in long-term changes to health, behavioral and social functioning, and brain structure and functioning that have a far-reaching, negative impacts on academic outcomes, including learning to read. Trauma refers to emotional distress resulting from experiencing violence, abuse, or an accident.

Trauma is divided into two categories:

  • Interpersonal Trauma refers to Trauma that has occurred between people (e.g., assault, abuse).
  • Non-interpersonal Trauma refers to Trauma inflicted by some other source (e.g., a motor vehicle accident, a natural disaster).

According to the 2014 National Survey of Children’s Exposure to Violence, within the year preceding the study:

  • 37.3% of youth experienced a physical assault, most often by siblings and peers, and 9.3% of youth experienced an injury resulting from an assault;
  • 15.2% of children were maltreated by a caregiver; and
  • 2% of girls had experienced a serious sexual assault (the rate increased to 4.6% for girls between ages 14 to 17).

Experiencing chronic Trauma in childhood causes stress hormones to be released during a critical time of brain development, which leads to permanent changes to the brain.

Assessment

  • The Traumatic Events Screening Inventory for Children (TESI-C) (Ippen et al., 2002): Evaluates a child’s exposure to traumatic events such as injuries, hospitalizations, accidents, disasters, domestic violence, community violence, physical abuse, and sexual abuse. There are parent-report and child-report versions of the scale.

Learner Factor Connections

  • Emotion: A complex psychological state that involve a subjective experience and can result in a physiological and behavioral response. Anxiety is intense worry or fear, and in individuals with an anxiety disorder, these feelings will not subside over time. Depression is a mood disorder causing feelings of sadness and hopelessness that have a significant negative impact on a student’s ability to participate in daily activities and succeed in school. Finally, Post Traumatic Stress Disorder (PTSD) is a psychiatric disorder that causes extreme anxiety and distress as the result of Trauma.
    • Children who experience Trauma are at risk for developing anxiety and depressive disorders and PTSD. Experiencing interpersonal Trauma puts children at more risk for developing PTSD than non-interpersonal Trauma.
  • Inhibition: The ability to suppress attention to irrelevant stimuli to focus on pertinent stimuli/information, both controlling responses and attention
    • Children who experience Trauma, particularly those who are abused or witness abuse at home, are at risk for executive functioning impairments, including deficits to Inhibition.
  • Long-term Memory: The ability to hold information for a long period of time, and possibly indefinitely
    • Childhood Trauma and maltreatment have been linked with reductions in adult brain structure involved in the consolidation of memories from Short- to Long-term Memory.
  • Physical Fitness: Overall health and physical well-being that is dependent on several important factors including proper nutrition, regular exercise, and an adequate amount of Sleep
    • Children living in less safe neighborhoods have fewer opportunities to play outside than children living in safe neighborhoods. Thus, living in a less safe neighborhood limits opportunities for obtaining regular exercise (Aikens & Barbarin, 2008; Franzini et al., 2010).
  • Safety: How physically and psychologically safe a child feels at home, school, and in their community
    • Experiencing Trauma, and especially interpersonal Trauma, will cause children to feel less Safe.
  • Social Supports: The perception of the support network, including parents, friends, and teachers, that is available to help if needed
    • Social Supports can erode when a child experiences Trauma, particularly interpersonal Trauma. This is particularly true when a child’s family members or members of the community are involved in inflicting violence and abuse.
  • Working Memory: The type of memory that allows a person to temporarily hold and manipulate information for use in many complex cognitive processes
    • Children who are abused or witness abuse in their homes are at greater risk for having Working Memory deficits.

Research Findings

Trauma in childhood can result in long-term negative changes to health, brain structure, and function:

  • Anda and colleagues (2005) integrated findings from studies examining the neurobiological effects of childhood abuse and exposure to violence with data from the Adverse Childhood Experiences (ACE) study. The ACE Study was designed to assess the impact of adverse childhood experiences (that occurred between ages 0 to 18) on health behaviors and outcomes. Their results suggest that childhood abuse and exposure to violence results in long-term health, behavioral, and social problems. A higher ACE score (exposure to a higher number of abusive or violent events) was associated with higher rates of substance abuse, hallucinations, obesity, and sexual promiscuity as an adult. These results reveal that experiencing traumatic events as a child has long-term impacts on a person’s health.
  • Several studies have found reductions in hippocampus (a brain structure involved in the consolidation of information from Short-term to Long-term Memory) and amygdala (involved in mood, emotional, and cognitive responses) volumes in adults who experienced childhood Trauma (Bremner, 2003; Samplin et al., 2013; Stein, 1997; Teicher et al., 2012).
    • For example, Samplin and colleagues examined structural MRI scans in a group of adults with a history of childhood abuse compared to those without. They compared the hippocampal volume, as well as measures of general cognitive ability (IQ, digit span etc.) and subclinical psychopathology between both groups. They found reduced hippocampal volumes in males but not in females. However, both males and females experienced higher rates of subclinical psychiatric symptoms resulting from childhood maltreatment.
  • Barber and colleagues (2014) examined how traumatic events can lead to acute stress disorder in children and adolescents between ages 8 to 17 (n = 479). The researchers interviewed and administered self-report questionnaires to children and their caregivers within one month following a traumatic event. 71% of children in the study experienced an unintentional injury (e.g., a broken bone, motor vehicle accident), 21% of the children experienced a medical event, and 8% either witnessed or were victims of violence. They found that children who experienced greater symptoms of acute stress immediately after a traumatic event also experienced greater depression and anxiety (part of Emotion) rates. This is important to consider because depression and acute stress following a traumatic event can lead to long-term post-traumatic stress symptoms (Pailler et al., 2007). These findings converge on past research finding that children who experience Trauma will experience almost twice as many psychiatric disorders (including anxiety and depression) compared to children who do not experience any traumatic events (Copeland et al., 2007).
  • Research has demonstrated that children who are bullied (part of Safety) experience higher levels of depression, anxiety (part of Emotion), and other mental health disorders, which can all result in lower levels of academic achievement (Hymel, Schonert-Reichl, & Miller, 2006; Rivers et al., 2009; Schwartz et al., 2005; Whitted & Dupper, 2005). Thus, experiencing Trauma at school can have a significant impact on a child’s ability to succeed academically.
  • Alisic and colleagues (2014) conducted a literature review of 72 peer-reviewed articles to investigate the factors that can lead to post-traumatic stress disorder (PTSD) after children and adolescents have been exposed to Trauma. Overall 15.9% of youth exposed to Trauma experienced PTSD; however the rates varied based on gender and type of Trauma. Girls exposed to interpersonal Trauma (Trauma between people such as abuse) are at the highest risk of developing PTSD, with 32.9% PTSD rate. Boys exposed to non-interpersonal Trauma (Trauma that is not between people) were at the lowest risk of developing PTSD (8.4% PTSD rate). The authors explained that interpersonal Trauma is more likely to lead to PTSD because it is often more chronic and leads to self-blame more often than non-interpersonal Trauma. Moreover, interpersonal Trauma can destroy Social Supports, particularly when a family member or trusted member of the community is the perpetrator, which also represents a serious betrayal of trust in a way that severely negatively impacts a child’s ability to function normally.
  • Kim and Cicchetti (2010) conducted a longitudinal study to examine how child maltreatment interacted with Emotion regulation, peer acceptance/rejection, and psychopathology in a group of 215 maltreated and 206 nonmaltreated children between ages 6 to 12. Children who experienced Trauma were identified through the County Department of Social Services, and the nonmaltreated children were recruited from families who required temporary assistance because most of the members of maltreated families also required income assistance. Children who were maltreated were more likely to experience difficulties with Emotion regulation, which led to more aggressive and delinquent behaviors. These conduct problems subsequently led to higher rates of peer rejection. In this way, experiencing Trauma can lead to higher rates of peer rejection and poor peer Social Supports.

Children exposed to violence are at risk for exhibiting neurological changes leading to problems in executive functioning, Self-Regulation, language development (Vocabulary growth), and memory (Choi et al., 2009; DePrince, Weinzierl, & Combs, 2009; Perkins & Graham-Berman, 2012).

  • DePrince and colleagues (2009) tested executive functioning in 114 school-age children divided into three groups: those who had been exposed to familial Trauma (e.g., sexual abuse, physical abuse, or witnessing domestic violence), those exposed to non-familial Trauma, and those with no exposure to Trauma. Specifically, they measured Working Memory, Inhibition, auditory Attention, and interference control. Working Memory was measured using arithmetic, letter-number sequencing, and digit span subscales of the Wechsler Intelligence Scale for Children (WISC-IV) (Wechsler, 2003). Inhibition was measured using the Gordon Diagnostic System where children are asked to look at strings of numbers and press a key whenever they see a certain sequence of numbers in the center of the number string. Auditory Attention was measured using the Brief Test of Attention where the children are asked to listen to a series of letters and numbers, then are asked to indicate how many numbers were presented without counting on their fingers. Finally, interference control was assessed using the Stroop task. They found a significant correlation (medium effect size) between experiencing familial Trauma to a composite score of executive functioning, even when controlling for SES, traumatic brain injury, and anxiety. They did not find this association in children who had been exposed to non-familial Trauma. They concluded that executive functioning impairments may contribute to the academic, psychological, and behavior problems often seen in children who have suffered abuse.
  • Choi and colleagues (2009) used diffusion tensor imaging (DTI) to examine white matter tracts in 16 young adults (mean age = 21.9 years) who had been exposed to high levels of parental verbal abuse relative to 16 healthy controls (mean age = 21.0 years) who had not been exposed to parental verbal abuse. They found that three white matter tracts associated with language development had significantly reduced fractional anisotropy values (used to compare white matter tracts) in the participants who had been exposed to parental verbal abuse, but not physical abuse. These findings show that even experiencing verbal abuse can lead to significant changes in neural pathways.

References

Alisic, E., Zalta, A. K., Van Wesel, F., Larsen, S. E., Hafstad, G. S., Hassanpour, K., & Smid, G. E. (2014). Rates of post-traumatic stress disorder in trauma-exposed children and adolescents: Meta-analysis. The British Journal of Psychiatry, 204(5), 335-340.

Anda, R. F., Felitti, V. J., Bremner, J. D., Walker, J. D., Whitfield, C. H., Perry, B. D., … Giles, W. H. (2006). The enduring effects of abuse and related adverse experiences in childhood. European Archives of Psychiatry and Clinical Neuroscience, 256(3), 174-186.

Bremner, J. D. (2003). Long-term effects of childhood abuse on brain and neurobiology. Child and Adolescent Psychiatric Clinics of North America, 12(2), 271-292.

Choi, J., Jeong, B., Rohan, M. L., Polcari, A. M., & Teicher, M. H. (2009). Preliminary evidence for white matter tract abnormalities in young adults exposed to parental verbal abuse. Biological Psychiatry, 65(3), 227-234.

Copeland, W.E., Keeler, G., Angold, A., & Costello, E.J. (2007). Traumatic events and posttraumatic stress in childhood. Archives of General Psychiatry, 64(5), 577–584.

DePrince, A. P., Weinzierl, K. M., & Combs, M. D. (2009). Executive function performance and trauma exposure in a community sample of children. Child Abuse & Neglect, 33(6), 353-361.

Finkelhor, D., Turner, H. A., Shattuck, A., & Hamby, S. L. (2015). Prevalence of childhood exposure to violence, crime, and abuse: Results from the National Survey of Children’s Exposure to Violence. JAMA Pediatrics, 169(8), 746-754.

Hymel, S., Schonert-Reichl, K. A., & Miller, L. (2006). Reading, ‘riting, ‘rithmetic and relationships: Considering the social side of education. Exceptionality Education Canada, 16(3), 1-44.

Ippen, C. G., Ford, J., Racusin, R., Acker, M., Bosquet, M., Rogers, K., … Edwards, J. (2002). Traumatic Events Screening Inventory – Parent Report Revised.

Kim, J., & Cicchetti, D. (2010). Longitudinal pathways linking child maltreatment, emotion regulation, peer relations, and psychopathology. Journal of Child Psychology and Psychiatry, 51(6), 706-716.

Pailler, M.E., Kassam-Adams, N., Datner, E.M., & Fein, J.A. (2007). Depression, acute stress and behavioral risk factors in violently injured adolescents. General Hospital Psychiatry, 29(4), 357–363.

Perkins, S., & Graham-Bermann, S. (2012). Violence exposure and the development of school-related functioning: Mental health, neurocognition, and learning. Aggression and Violent Behavior, 17(1), 89-98.

Rivers, I., Poteat, V. P., Noret, N., & Ashurst, N. (2009). Observing bullying at school: The mental health implications of witness status. School Psychology Quarterly, 24(4), 211-223.

Samplin, E., Ikuta, T., Malhotra, A. K., Szeszko, P. R., & DeRosse, P. (2013). Sex differences in resilience to childhood maltreatment: Effects of trauma history on hippocampal volume, general cognition and subclinical psychosis in healthy adults. Journal of Psychiatric Research, 47(9), 1174-1179.

Schwartz, D., Gorman, A. H., Nakamoto, J., & Toblin, R. L. (2005). Victimization in the peer group and children’s academic functioning. Journal of Educational Psychology, 97(3), 425 – 435.

Stein, M. B., Koverola, C., Hanna, C., Torchia, M. G., & McClarty, B. (1997). Hippocampal volume in women victimized by childhood sexual abuse. Psychological Medicine, 27(4), 951-959.

Teicher, M. H., Anderson, C. M., & Polcari, A. (2012). Childhood maltreatment is associated with reduced volume in the hippocampal subfields CA3, dentate gyrus, and subiculum. Proceedings of the National Academy of Sciences, 109(9), E563-E572.

Whitted, K. S., & Dupper, D. R. (2005). Best practices for preventing or reducing bullying in schools. Children & Schools, 27(3), 167-173.

Vision

Reading requires being able to see the detailed features of text clearly. Students with uncorrected Vision issues can have difficulty distinguishing letters and reading at the same rate as peers with normal or corrected Vision. The main constructs for understanding Vision are:

  • Vision is the ability to use eyesight to perceive information about the world.
  • Reading encompasses several different Vision characteristics and skills including:
    • Visual acuity: The ability to see objects clearly at a given distance
    • Visual fixation: The ability to maintain gaze on one location
    • Visual field: The entire area that a child can see, including peripheral and central vision
    • Binocular fusion: The brain’s ability to form one image from visual input received from two eyes
    • Convergence: Moving eyes toward each other to focus on a nearby object
    • Accommodation: Maintaining focus on an object as the distance to the object changes
  • Early identification of Vision problems is critical for preventing academic difficulties later. However, Vision screenings at school typically only assess visual acuity, so it is possible for a child to have a Vision problem in other areas even though they pass the screening. Thus, if a child is at risk for having Vision problems, they should receive an extensive eye examination regardless of screening results (American Optometric Association).

Assessments

  • Vision Screening: Screening for difficulties with Visual Acuity in children typically involves an eye chart using shapes and symbols rather than letters. The child is asked to identify symbols on the chart with both eyes and with each eye individually at varying distances from the chart. If the child displays difficulties here, they will be referred for an extensive visual examination.
  • More comprehensive Vision evaluations may include tests of visual field, binocular vision, convergence, and accommodation (Verweyan, 2004). For example, Visual Field can be evaluated using a test where a white spot is projected on a screen and the patient indicates when the spot disappears from their Visual Field. Convergence and Accommodation can be tested by evaluating how a child’s eyes move while tracking a moving object.

Learner Factor Connections

  • Attention: The ability to focus on a specific task without being distracted, as well as the ability to select relevant information while ignoring irrelevant information. Visual Selective Attention is the ability to focus on relevant information in a cluttered visual scene.
    • Vision skills are necessary for Visual Selective Attention.
  • Visual Processing: The process of interpreting visual stimuli as meaningful input
    • Vision allows visual information to enter the brain and be interpreted as meaningful input via Visual Processing.

Research Findings

Vision

  • Many economically disadvantaged students in rural areas of China who would benefit from eyeglasses do not have access to affordable eyeglasses through public or private organizations. Glewwe, Park, and Zhao (2016) examined the impact of providing free eyeglasses to students with Vision problems in rural Chinese schools. They found that in students with poor Vision, wearing eyeglasses for one year significantly increased average test scores. Students who were under-performing academically benefitted the most from the intervention. They also found that student’s nutritional status and parental education both explained heterogeneity in the impact of wearing eyeglasses. Also, approximately one-third of parents/children who were offered free eyeglasses refused the offer, which was likely due to parents believing that their children’s eyesight was adequate.

Visual-motor Integration

Visual-motor integration skills allow eyes and hands to work together in an organized and coordinated manner, and they rely on both visual spatial discrimination and motor skills. Many studies have found a relationship between visual perception and academic performance (Feagans & Merriwether, 1990; Kulp, 1999; Rosner & Rosner, 1987). However, it should be noted that the field of research examining the relationship between visual function and academic performance is controversial (see Lack, 2010, for a review). Yet since a good amount of research exists suggesting Vision is an important factor in academic performance, that literature will be discussed briefly here.

  • Several researchers have found that visual-motor integration (VMI) is a predictor of academic performance. For example, Kulp (1999) examined VMI in children in kindergarten to 3rd grade and found a significant correlation between VMI and scores in reading, writing, spelling, and math. Also, Sortor and Kulp (2003) found that lower VMI scores were associated with poor performance in both math and reading. These associations were maintained after controlling for intelligence.
  • Goldstand, Koslowe, and Parush (2005) examined visual and visual-information processing skills in 7th grade students who were considered to either be proficient or nonproficient readers. The students were tested using the Modified Clinical Technique (MCT), an optometric vision screening task (Blum, Peters, & Bettman, 1959), which measured several aspects of Vision (e.g., visual acuity near/far, color vision, visual tracking, etc.). Half of the students failed the MCT vision screening in both the proficient and nonproficient reader groups. However, nonproficient readers had significantly poorer scores on the visual screening.

References

American Optometric Association. Limitations of Vision Screening Programs.

Feagans, L. V., & Merriwether, A. (1990). Visual discrimination of letter-like forms and its relationship to achievement over time in children with learning disabilities. Journal of Learning Disabilities, 23(7), 417-425.

Glewwe, P., Park, A., & Zhao, M. (2016). A better vision for development: Eyeglasses and academic performance in rural primary schools in China. Journal of Development Economics, 122, 170-182.

Goldstand, S., Koslowe, K. C., & Parush, S. (2005). Vision, visual-information processing, and academic performance among seventh-grade schoolchildren: A more significant relationship than we thought? American Journal of Occupational Therapy, 59(4), 377-389.

Kulp, M. T. (1999). Relationship between visual motor integration skill and academic performance in kindergarten through third grade. Optometry & Vision Science, 76(3), 159-163.

Lack, D. (2010). Another joint statement regarding learning disabilities, dyslexia, and vision – A rebuttal. Optometry-Journal of the American Optometric Association, 81(10), 533-543.

Rosner, J., & Rosner, J. (1987). Comparison of visual characteristics in children with and without learning difficulties. Optometry & Vision Science, 64(7), 531-533.

Sortor, J. M., & KULP, M. T. (2003). Are the results of the Beery-Buktenica Developmental Test of Visual-Motor Integration and its subtests related to achievement test scores? Optometry & Vision Science, 80(11), 758-763.

Verweyen, P. (2004). Measuring vision in children. Community Eye Health, 17(50), 27-29.

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