Summary descriptive statistics of the three content areas of ADHD
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It is considered to be the most common psychiatric disorder amongst children in the United States and Europe, with an estimated 3-10% of children being affected [1]. The situation in Africa does not appear to be much different and although there is a lack of knowledge with regards to ADHD on the African continent, it is believed that the disorder is as prevalent as it is in Western countries [1]. In South Africa specifically it is considered to be the most prevalent psychiatric disorder amongst children with a prevalence rate of approximately 10% [2]. As this has not been confirmed officially, it raises issues relating to possible over-identification of the disorder in South Africa. However, it is feasible that children present with comorbid attention difficulties, when taking into consideration the huge backlog in the education system and the high incidence of learning disorders and language difficulties as additional barriers to learning.
The South African education system is still struggling with the aftermath of Apartheid, which promoted exclusion in schools, not only based on race, gender, class, and ethnic background, but also on disability. This lead to the creation of a dual education system and learners, who did not meet the requirements of mainstream education, were placed in special education when educationalists considered it to be in the best interest of the learner [3]. With the abolition of Apartheid and the advent of the Constitution of the Republic of South Africa, Act No. 108 of 1996 [4], respect for the rights of all children regardless of variables such as race, gender, ethniticity, religion and ability was emphasised. This lead to the adaption of a new South African Education Policy, embedded in the philosophy of inclusive education and with its primary focus on “meeting the needs of all learners and actualising the full potential of all learners” [5, p.344].
Inclusive education is not uniquely South African and emerged as a key international policy when UNESCO’s Salamanca Statement was adopted in 1994, at the World Conference on Special Needs Education in Salamanca, Spain [6]. The emphasis at the Salamanca Conference was on the development of an inclusive education system that would
It was further noted that inclusive education systems, must not only recognise and respond to the diverse needs of learners, but also make room for different learning styles and rates. In addition, it is important that education systems ensure the quality of education through the design of appropriate curricula and teaching strategies, whilst also using and involving appropriate community and other resources. [7]
Although inclusive education therefore has a universal philosophy and universal practices, in the South African context it needed to be indigenised to meet the needs of the South African education system. This was done partially through the adoption of an eco-systemic framework in viewing barriers to learning and development.
Urie Bronfenbrenner is widely known for his development of the eco-systemic theory which looks at the manner in which different environments and social contexts, including political, socio-economical, and cultural patterns, produce distinct differences in the way in which children develop. He argues that to truly understand a child, as well as his/her developmental difficulties, one must view the child holistically within his/her context [9]. The eco-systemic theory, which forms part of the broader social ecological model to understanding learning barriers and more recently titled the bio-ecological perspective [10], amalgamates ecological and systems theories to exemplify how a person’s physical environment and the different levels of the person’s social context are linked in dynamic, interacting, and interdependent relationships.
Therefore, on the one hand the eco-systemic perspective emphasises the importance of the impact that a person’s physical environment can have on the development of the person. On the other hand, systems theory examines the multiple levels and groupings of a person’s social context that function interdependently so that the whole is reliant upon the interaction of the parts and can only be understood if the different parts are examined. Furthermore, as the different levels of a person’s social context is linked in every-changing, interacting and interdependent relationships; a shift in one system will impact the whole in a cyclical fashion.
Applied to ADHD within the South African context, the eco-systemic theory assists us in understanding how environmental factors such as lead poisoning [11], which are prevalent in the South African context [12-13], can have on the development of the disorder. Other environmental factors that are of particular importance in the development of ADHD [11] and prevalent in the South African context [14], include poverty and insufficient living conditions. In addition, the eco-systemic theory also assists us in understanding how the child’s micro-, meso-, exo-, macro-, and chronosystems [10] can have on the developmental course of ADHD. Here factors such as family discord, a maternal history of psychiatric disorders and a particular parenting style, are of importance [11]. Therefore, applied to ADHD, the eco-systemic perspective helps us to understand that children cannot be viewed in isolation, but as part of the bigger whole and in a reciprocal relationship with it. Taking this into consideration, one of the major challenges in effectively addressing ADHD within the South African context is to understand the complexity of the disorder as seen in a particular context and environment [9].
Although the predominant paradigm in understanding learning barriers such as ADHD, used to be the medical-deficit model, a more social-ecological approach is applicable when introducing inclusive education into an education system as it shifts attention from viewing psychiatric disorders as caused by or located within the individual, to viewing the child as being part of a broader system that contains many risk and protective factors that either contribute to the development and maintenance of a particular difficulty, or the prevention thereof. The World Health Organisation [15] defines environmental factors such as poor socio-economic status and high crime rates that can increase the risk of the developmental of externalising difficulties such as ADHD, as risk factors. In contrast, factors such as supportive parenting styles and educational support that moderate the effects of ADHD and assist in the appropriate adaptation of children with this to the school environment, are seen as protective factors.
In adopting a more socio-ecological paradigm, there will therefore be a shift from using labels such as special needs to applying terminology such as risk and protective factors, or as it is noted in the South African policy documentation; barriers to learning and development [16]. Barriers to learning and development are defined as all factors that can impact upon learning [17]. These barriers can occur within all levels of the eco-system and can be placed on a continuum; from intrinsic barriers that can be found within the individual, to extrinsic barriers which refer to factors outside the individual [17]. Some of the most prominent extrinsic barriers within the South African context include socio-economic barriers, negative attitudes towards difference and psychiatric disorders, inflexible curricula, inaccessible and unsafe building environments and schools, inappropriate and inadequate provision of support services, lack of enabling and protective legislation and policy, lack of parental recognition and involvement, and lack of human resource development strategies [16]. Some of the most prominent intrinsic barriers include language and communication difficulties, health difficulties such as HIV and tuberculosis, sensory impairments, intellectual and learning difficulties, and pervasive developmental disorders [17].
ADHD would be considered an intrinsic barrier as research has shown that genetic and biological factors such as an imbalance in the neurotransmitters noradrenalin and dopamine play an important role in the development of the disorder. It is however important to also take cognisance of the role that extrinsic barriers such as those noted above, as well as poor socio-economic circumstances, high crime rates, repeated trauma, parenting styles and parent-child interactions play in the maintenance and further developmental course of the disorder [15].
From an eco-systemic perspective, teachers can act as extrinsic barriers to learning and development when they act as risk factors in the developmental course of ADHD in particular learners in their classrooms. Likewise, teachers can also act as protective factors when their understanding of ADHD and support offered to the learners in their classrooms, positively impact on the developmental course of the disorder.
Teachers are often the primary source of identification and play a pivotal role in the diagnosis, management and intervention of ADHD. They have firsthand experience of the learner in the classroom situation; a setting which requires the learner to sit still, pay attention, adhere to instructions and interact with peers and adults in an appropriate manner. Teachers’ knowledge and understanding will determine how they engage with and manage learners experiencing ADHD. Furthermore, their attitudes towards different forms of ADHD intervention would affect their support of these treatment methods and the learners in their classrooms. Early identification and intervention by teachers is vital, especially as a large percentage of individuals continue to have symptoms in adolescence and adulthood [18], which can impede their future wellbeing. It is important to take cognisance of the manner in which teachers’ perceptions, knowledge and attitudes are influenced by contextual and socio-cultural factors, as shown in previous studies [1, 19-20].
It has however been found that teachers’ understanding of ADHD is often based on myths and false beliefs. It has been reported that some teachers believe that ADHD is a direct cause of the intake of certain food additives and eating too many sweets [21]. Others are of the idea that ADHD is mainly as a result of biological abnormalities [11], or as a direct result of bad parenting and a lack of parental supervision [22]. It is essential to understand that if teachers have an incorrect understanding of ADHD and its causes and symptoms, it may lead them to actually support the presence of behaviours associated with ADHD, which can lead to inaccurate diagnosis [23].
Over the past decade, many research studies have been done on teachers’ perceptions and knowledge of ADHD. In the United States, a sample of primary school teachers watched a video of a student displaying ADHD-like behaviours as well as those behaviours that are characteristic and unique to Oppositional Defiant Disorder (ODD). When examined, teachers were accurate in their evaluations of ADHD-like symptoms such as inattention and hyperactivity. However, when students displayed behaviours that belong solely to the domain of ODD, such as opposition and non-compliance, teachers automatically assumed that these behaviours were indicative of ADHD. Thus, teachers mistakenly assumed that children who displayed only ODD-like behaviours also exhibited ADHD-like behaviours [23]. A study conducted in Australia likewise revealed that teachers often provide parents and professionals with incorrect and inappropriate advice and information regarding the child who is displaying ADHD-like symptoms [21]. A study conducted in South Africa by [24] revealed that teachers are actually over identifying children with ADHD, as in the study 11.9% of the learners actually had ADHD, whilst teachers identified 15.4% of the learners to have ADHD. Thus, misunderstandings and misperceptions held by teachers may lead to inaccurate information being passed onto professionals, who carry out the task of making an actual ADHD diagnosis.
In support of these findings, further evidence reveals that teacher knowledge of ADHD tends to be very narrow and limited and even incorrect [21]. Three studies, as discussed in [21] were conducted in Australia over the last decade, which explored this area. One of the studies revealed that the teachers in the selected sample group were able to answer 60.7% of items in a questionnaire on ADHD. In a different study, the researchers administered the Knowledge of Attention Deficit Disorders Scale (KADDS) to a group of teachers. The findings of this study reflected that teachers knew more about the causes of ADHD, but possessed less information regarding treatment interventions for ADHD [21].
In South Africa, a study conducted in the peripheral areas of the Cape Town Metropole in the Western Cape, also employed the KADDS to assess 552 teachers’ knowledge of ADHD [2]. Their study revealed that the participants did not have an adequate understanding of ADHD. An overall score of correct responses of 42,6% was obtained. An overall percentage of 35.4% was gathered for “don’t know” responses, and 22% for incorrect responses [2].
These above results are consistent with a study conducted by [25]. In this South African study teachers’ perceptions of their ability to identify and manage learners diagnosed with ADHD were investigated. Four out of five teachers did not consider themselves able to adequately manage ADHD symptoms, and some of the teachers misidentified and misunderstood certain symptoms of this condition. In a further study, [26] revealed that teachers do not have a sound understanding of the symptoms of ADHD, and the majority of teachers in the sample were unable to distinguish between inattention and ADHD. According to Venter (2011, as cited in [27]), teachers from poor black communities that teach at rural South African schools are the ones who possess the most limited knowledge on the condition. Consequently, these children are physically and verbally punished as a result of their ADHD behaviour.
Conversely, a South African study conducted by [28], which included five schools situated in economically deprived areas and three school situated in economically affluent areas, showed different results to those yielded by [2]. It was revealed that the majority of teachers in this sample group in fact had in-depth knowledge and understanding of ADHD, and were acutely aware of the symptoms of ADHD. The teachers believed that their role in the classroom was crucial to the management of the condition. Furthermore, teachers in this study were very eager to learn and gain more information on the condition. However, this study consisted of a very small sample group and the results garnered appear to be more of an exception and stronger evidence exists for the fact that teachers generally have a poor understanding and lack of knowledge on the condition [2].
Research in the past decade, has explored if older teachers and those teachers who have had more years of teaching experience have better knowledge and understanding of ADHD. An Australian study conducted by [29], where 120 teachers completed a survey on what they thought and knew about ADHD, showed that teachers with more years of teaching experience perceived themselves to have greater knowledge on the condition than the less experienced teachers. However, the number of years of teaching experience of these teachers was not related to their actual levels of knowledge. The age of the teachers was also not linked to the teachers’ level of knowledge and understandings of the condition. These results are confirmed by the findings by [2].
However, other research [30] reported that in fact younger teachers know more about ADHD than older ones, a finding which is confirmed by [31]. One explanation for this may be the fact that younger teachers notice the condition more in their classrooms compared to their older counterparts who have developed effective classroom behaviour management strategies. One researcher [32] believes that older teachers are much more rigid and set in their ways as compared to younger teachers, who are willing to be open, honest and adaptable to the needs of ADHD learners.
The question arises as to whether a teacher, who has obtained a more advanced level of education, consequently knows more about ADHD. A study [33] conducted in the United States, which aimed to investigate preschool teachers’ past educational practices and their knowledge and understanding of ADHD, revealed that those teachers that obtained higher levels of academic training, such as a university education, performed on a superior level and obtained higher scores on the administered questionnaire than those teachers that only obtained a high school level of education.
The study by [29] also indicated that having taught a student with ADHD is related to that teacher’s actual knowledge of the condition. Then the question arises as to whether training and exposure in the area, such as the reading of articles on the topic and the attendance of workshops, contributes to a teacher’s level of understanding and knowledge on ADHD. A study by [34], answers this question in the affirmative, and revealed that the attendance of workshops on ADHD has a positive relationship with teacher knowledge and understanding of ADHD. In the study by [2], teachers’ exposure to ADHD, which includes the number of workshops attended as well as the number of articles read was positively correlated to their overall knowledge and understanding of the condition.
In the study by [29] older teachers were more likely to attend workshops and engage in ADHD training than the younger teachers. Teaching experience and exposure to ADHD also increased the likelihood of teachers attending workshops. The more workshops the teachers attended, the more knowledge they had on the disorder, compared to the teachers who did not attend workshops. This was confirmed by the South African study conducted by [2]. Teachers’ confidence levels in their ability to teach and deal with a child with ADHD was positively related to their overall knowledge of this condition. As every teacher will experience at least one learner with ADHD per year, it may become essential for teachers to receive pre-service training in the area of ADHD [35].
Whilst understanding the pivotal role that teachers’ knowledge and perceptions play in the identification and treatment of ADHD, this chapter aims to integrate the information from the studies above, with one particular South African study [36] that focussed on the knowledge and perceptions held by a sample of South African Foundation Phase township teachers.
A range of mainstream and special education schools exist in South Africa, which include private and government funded schools. Of the government funded schools, formally white schools were better funded and resourced in comparison to the black township, rural and informal settlement schools. There is no previous documented research on township teachers’ perceptions of ADHD in South Africa, which prompted the current study. The study was conducted in Alexandra Township in Gauteng, which is one of the oldest townships in South Africa. It was proclaimed as a township for black persons in 1912, by the Apartheid regime which classified South Africans into four racial groups. Alexandra Township, with a population of about 350 000 people, covers an area of over 800 hectares of land. It consists of persons of different cultures and varying degrees of income and education and has a history of poverty, overcrowding as well as high levels of unemployment and crime.
The overall aim of this study was to explore and assess the knowledge and perceptions of ADHD held by a sample of Foundation Phase (Reception year to Grade 3) teachers within a township setting. More specifically, the research aimed at exploring the teachers’ general knowledge as well as their inadequate knowledge and misconceptions regarding ADHD, with emphasis paid to its’ associated features, symptoms/diagnosis and treatment. Teachers’ knowledge of ADHD was also investigated in relation to their demographic group.
In fulfilling the aim of the study, the following research questions were posed:
What is the teachers’ general knowledge of the content areas of ADHD in terms of:
Associated Features
Symptoms/Diagnosis
Treatment
What are teachers’ specific areas of inadequate knowledge and misconceptions in the content areas of:
Associated Features
Symptoms/Diagnosis
Treatment
Is teachers’ knowledge of the ADHD content areas different by demographic group in terms of:
Associated Features
Symptoms/Diagnosis
Treatment
This research was exploratory in nature as there is very limited documented research on ADHD in South Africa. The study garnered both qualitative and quantitative material which was analysed using numerical and descriptive statistics. For logistical and practical reasons, nine primary schools situated within the Alexandra Township were selected. Non probability, convenience sampling was employed as participation by the teachers depended on their availability and willingness to respond. As a result, the final sample of 100 female teachers who consented to participate in the study was not random in nature [37-38]. Foundation Phase teachers were chosen as the sample for this study due to the fact that they play an integral and primary role when it comes to the identification and recognition of ADHD-like symptoms [39]. Permission to undertake the investigation was sought from the Gauteng Department of Education and the ethics committee at the University of the Witwatersrand. A detailed information sheet detailing issues of anonymity and confidentiality regarding the particulars of the study was distributed to the principals of the schools and their teachers.
Clear instructions were given to the respondents during administration of the instrument and assistance was provided if they did not understand what was required. A questionnaire was chosen as the preferred instrument as it allowed for administration to a large group of subjects [38]. The questionnaire which was administered to the 100 participants was threefold in nature. It included; demographic/biographical questions, the Knowledge of Attention Deficit Disorders Scale (KADDS), as well as open-ended questions. Permission to use the KADDS measure was obtained from Professor Mark Sciutto.
In the first section of the questionnaire teachers were asked demographic questions such as their gender, age, educational level and number of years of teaching experience. Teachers were also asked to provide the number of hours of ADHD training that they had received (if any), as well as the number of evaluations and assessments that they had requested for children in their classes that they thought may have ADHD. Teachers were required to indicate the number of children that they had taught with a medical diagnosis of ADHD, how many workshops that they had attended on the topic as well as the number of articles that they had read on the condition. The teachers were also asked to rate their confidence levels to teach a child with ADHD. Lastly, teachers were required to indicate whether they had been asked for feedback by a professional, such as a doctor or psychologist, regarding a child in their class with ADHD in order to assess the child’s medication. These questions were based on a questionnaire that was administered in the previously reported South African study conducted by [2].
The second section of the questionnaire consisted of the Knowledge of Attention Deficit Disorder Scale (KADDS). This scale was developed by [31] and was previously used in similar studies in South Africa, see [2] and Australia, see [40]. It was designed and consequently published to assess teachers’ knowledge, of the symptoms, associated features and treatment of ADHD. The KADDS is a 39 item rating scale which elicits true and correct answers (T), false, incorrect and misperceived answers (F) and don’t know answers (DK). Previous research conducted on the internal consistency of the KADDS total score, based on the original 36 items that constituted this scale, revealed high internal consistency ranging from.81 to.86 [31,41-42]. A similarly high internal consistency for the KADDS was found in the present study, with the Cronbach’s alpha for the total score being.88. In terms of validity, KADDS scores are sensitive to teacher characteristics such as exposure to and interaction with a child with ADHD and prior training on this condition [31].
The last section of the questionnaire contained open- ended questions, where participants were given the opportunity to provide any additional comments or ideas that they had regarding ADHD. This information served to substantiate and support the quantitative results garnered by the research. In research terms, this method of using multiple sources of data to strengthen the trustworthiness of the data, is referred to as the triangulation of data [43].
Descriptive and inferential statistics and graphs were used to describe the sample respondents and the measurement scales, and to address the aims of the research study. In order to investigate the areas of inadequate knowledge and misconceptions held by teachers, summary statistics for the central tendency, variability and shape were computed at the item level of the KADDS subscales. These results were tabulated using a robot- type colour coding scheme whereby higher mean scores were shaded in deep green and shades of yellow through to red were used for relatively lower and low means respectively. Furthermore, the responses to each item were categorised as “don’t know”, incorrect responses or misconceptions, and correct responses, thereby enabling the examination of the extent of teachers’ misconceptions versus poor knowledge at the item level of each of the subscales. This analysis was depicted graphically in the form of a stacked bar graph for the items of each subscale of the KADDS. In order to address the teachers’ general knowledge of ADHD content areas in terms of their demographic group, a 1-way Analysis of Variance (ANOVA) was used. This was used to compare the mean responses of the respondents across the levels within each demographic variable on the three KADDS subscales. Line graphs were used to portray the differences between means in the case of significant ANOVA comparisons. Furthermore, the post hoc Scheffe test was used to indicate pairwise significances for significant analyses of demographic variables with more than two levels. In view of the non-normality of the score distributions, the parametric ANOVA tests were validated using the non-parametric equivalent Kruskal-Wallis test. Finally, the Chi squared test was used to compare the demographic characteristics of the respondents who opted versus those who did not opt for a future workshop on ADHD and profile line graphs were plotted to describe the two groups of these demographic variables. In addition, the t-test was used to compare the mean knowledge scores on the three KADDS subscales of these two groups. These analyses were complemented by the researcher’s thematic analysis of the qualitative responses.
All of the 100 respondents, who agreed to participate in this study, were female. The average learner to teacher ratio in the schools include in the schools, were 50:1. Almost two-thirds of the teachers in the sample were older than 40years, with a negligible number of them in the 20-25 year category. Consistent with the age distribution of the teacher respondents, the majority (60%) had more than 11 years of teaching experience, 20% had 6-10 years teaching experience and 20% had 5 years or less. Almost a quarter of the sample had a university level of education, while the remaining individuals had college level training. Over half of the respondents expressed no confidence in their ability to teach children with ADHD. Regarding their knowledge of ADHD, two thirds of the teachers had received no ADHD training. Over half of the respondents (52%) claimed that they had taught children diagnosed with ADHD and had assisted with ADHD evaluations (59%). Almost 40% claimed that they had been asked for feedback by a doctor regarding a child with ADHD in their classroom.
The overall results of the KADDS questionnaire revealed that there is a substantial lack of knowledge about ADHD amongst the participants. Based on the results of Table 1 the overall percentage of correct responses to the 39 KADDS items was 34.9%. Nine of the 100 educator respondents scored zero on all 39 items of the scale.
\n\t\t\t | \n\t\t\t\tMean\n\t\t\t | \n\t\t\t\n\t\t\t\t95% Confidence Interval for mean\n\t\t\t | \n\t\t\t\n\t\t\t\tMedian\n\t\t\t | \n\t\t\t\n\t\t\t\tStandard deviation\n\t\t\t | \n\t\t\tSkewNess | \n\t\t|
Associated features | \n\t\t\t30.4% | \n\t\t\t27.0% | \n\t\t\t33.8% | \n\t\t\t31.3% | \n\t\t\t17.2% | \n\t\t\t-0.21 | \n\t\t
Symptoms/ Diagnosis | \n\t\t\t47.9% | \n\t\t\t43.3% | \n\t\t\t52.5% | \n\t\t\t50.0% | \n\t\t\t23.3% | \n\t\t\t-0.51 | \n\t\t
Treatment | \n\t\t\t30.6% | \n\t\t\t26.5% | \n\t\t\t34.8% | \n\t\t\t30.8% | \n\t\t\t20.9% | \n\t\t\t0.10 | \n\t\t
Overall | \n\t\t\t34.9% | \n\t\t\t31.3% | \n\t\t\t38.6% | \n\t\t\t37.2% | \n\t\t\t18.2% | \n\t\t\t-0.33 | \n\t\t
Summary descriptive statistics of the three content areas of ADHD
Regarding the teachers’ knowledge in terms of the Associated Features subscale, a mean score of 30.4% was garnered which was lower than the overall scale score of 34.9%, and based on the median score reflected in Table 1, half of the respondents answered fewer than 31.3% of these items correctly. The minimum scores of zero on the Associated Features subscale show 10 teachers who either did not know and/or who answered all the items of the subscale incorrectly. Of the three subscales, the highest mean (percentage correctly answered items) is for Symptoms/Diagnosis (47.9%). Even on this subscale, the average respondent answered approximately half of the items incorrectly. Nine of the 100 teachers scored zero on this Symptoms/Diagnosis subscale. The mean score of 30.6% on the Treatment subscale is comparably low in relation to the mean score on the Associated Features subscale which was lower than the overall KADDS score of 34.9%. The minimum scores of zero on this subscale show 15 teachers who either did not know and/or who answered all the items of the subscale incorrectly.
In order to determine the specific areas of poor knowledge and misconceptions of the content areas of ADHD, the scores of the educator respondents were examined at the item level for the three KADDS subscales. The low internal consistency reliability and low average inter-item correlation for the Associated Features subscale (Table 2) imply that some items of the subscale were answered correctly by teachers who answered other items incorrectly, and thus some items would be expected to have vastly different means from others. To reflect the items on which low and poor correct responses were obtained, a robot-type colour coding system was used whereby lower means were shaded red and highest means were shaded dark green with shades of orange for items in between. Item 1, which suggests that ADHD occurs in approximately 15% of school age children, item 27, which states that children with ADHD generally experience more problems in novel situations rather than familiar ones, item 30, which states that the problem behaviours in children with ADHD are distinctly different from the behaviours of non-ADHD children and item 39, which states that children with ADHD display an inflexible adherence to routine, all have very low percentage correct responses with means between 4% and 12%. These percentages are particularly low compared to items 13, which states that it is possible for an adult to have ADHD, item 31, which refers to the idea that children with ADHD are more distinguishable from normal children in a classroom setting as opposed to a free play situation and item 32, which states that the majority of children with ADHD evidence some degree of poor school performance during their early school years, which all have relatively high percentage correct responses with means between 60% and 62%. Apart from these three items, the mean score on the rest of the items of this subscale were all below 42%, and thus the standard deviations were low on these items and as a result on the whole subscale. This low response variability would have impacted negatively on the internal consistency reliability as Cronbach’s alpha was dependent on the variability in the responses.
In order to investigate the low item scores, a distinction was made between misconceptions, i.e., incorrect responses, versus “don’t know” responses. This distinction is displayed graphically for the Associated Features items in Figure 1 where bars shaded in blue indicate the percentage of misconceptions and bars shaded in red indicate incorrect responses for each item. Figure 1 shows that teachers have the greatest extent of misconception of ADHD on items 27, 1, 39 and 24, which states that a diagnosis of ADHD by itself makes a child eligible for placement in special education. These items arranged in decreasing order of incorrect responses from 53% to 40% and the least extent on items 31, 13 and 32 (these items similarly arranged in decreasing order of incorrect responses from 14% to 11%).
\n\t\t\t\tItems\n\t\t\t | \n\t\t\t\n\t\t\t\tMean\n\t\t\t | \n\t\t\t\n\t\t\t\tMedian\n\t\t\t | \n\t\t\t\n\t\t\t\tStd.Dev\n\t\t\t | \n\t\t\t\n\t\t\t\t95% Confidence Interval for mean\n\t\t\t | \n\t\t\t\n\t\t\t\tSkewness\n\t\t\t | \n\t\t|
1: Most estimates suggest that ADHD occurs in approximately 15% of school age children. | \n\t\t\t4% | \n\t\t\t0% | \n\t\t\t20% | \n\t\t\t17% | \n\t\t\t23% | \n\t\t\t4.77 | \n\t\t
4: ADHD children are typically more compliant with their fathers than with their mothers. | \n\t\t\t22% | \n\t\t\t0% | \n\t\t\t42% | \n\t\t\t37% | \n\t\t\t48% | \n\t\t\t1.37 | \n\t\t
6: ADHD is more common in the 1st degree biological relatives (i.e. mother, father) of children with ADHD than in the general population. | \n\t\t\t34% | \n\t\t\t0% | \n\t\t\t48% | \n\t\t\t42% | \n\t\t\t55% | \n\t\t\t0.69 | \n\t\t
13: It is possible for an adult to be diagnosed with ADHD. | \n\t\t\t62% | \n\t\t\t100% | \n\t\t\t49% | \n\t\t\t43% | \n\t\t\t57% | \n\t\t\t-0.50 | \n\t\t
17: Symptoms of depression are found more frequently in ADHD children than in non- ADHD children. | \n\t\t\t41% | \n\t\t\t0% | \n\t\t\t49% | \n\t\t\t43% | \n\t\t\t57% | \n\t\t\t0.37 | \n\t\t
19: Most ADHD children "outgrow" their symptoms by the onset of puberty and subsequently function normally in adulthood. | \n\t\t\t25% | \n\t\t\t0% | \n\t\t\t44% | \n\t\t\t38% | \n\t\t\t51% | \n\t\t\t1.17 | \n\t\t
22: If an ADHD child is able to demonstrate sustained attention to video games or TV for over an hour, that child is also able to sustain attention for at least an hour of class or homework. | \n\t\t\t32% | \n\t\t\t0% | \n\t\t\t47% | \n\t\t\t41% | \n\t\t\t54% | \n\t\t\t0.78 | \n\t\t
24: A diagnosis of ADHD by itself makes a child eligible for placement in special education. | \n\t\t\t32% | \n\t\t\t0% | \n\t\t\t47% | \n\t\t\t41% | \n\t\t\t54% | \n\t\t\t0.78 | \n\t\t
27: ADHD children generally experience more problems in novel situations than in familiar situations. | \n\t\t\t5% | \n\t\t\t0% | \n\t\t\t22% | \n\t\t\t19% | \n\t\t\t25% | \n\t\t\t4.19 | \n\t\t
28: There are specific physical features which can be identified by medical doctors (e.g. paediatrician) in making a definitive diagnosis of ADHD. | \n\t\t\t20% | \n\t\t\t0% | \n\t\t\t40% | \n\t\t\t35% | \n\t\t\t47% | \n\t\t\t1.52 | \n\t\t
29: In school age children, the prevalence of ADHD in males and females is equivalent. | \n\t\t\t33% | \n\t\t\t0% | \n\t\t\t47% | \n\t\t\t41% | \n\t\t\t55% | \n\t\t\t0.73 | \n\t\t
30: In very young children (less than 4 years old), the problem behaviours of ADHD children are distinctly different from age-appropriate behaviours of non-ADHD children. | \n\t\t\t10% | \n\t\t\t0% | \n\t\t\t30% | \n\t\t\t26% | \n\t\t\t35% | \n\t\t\t2.71 | \n\t\t
31: Children with ADHD are more distinguishable from normal children in a classroom setting than in a free play situation. | \n\t\t\t60% | \n\t\t\t100% | \n\t\t\t49% | \n\t\t\t43% | \n\t\t\t57% | \n\t\t\t-0.41 | \n\t\t
32: The majority of ADHD children evidence some degree of poor school performance in the elementary school years. | \n\t\t\t66% | \n\t\t\t100% | \n\t\t\t48% | \n\t\t\t42% | \n\t\t\t55% | \n\t\t\t-0.69 | \n\t\t
33: Symptoms of ADHD are often seen in non-ADHD children who come from inadequate and chaotic home environments. | \n\t\t\t28% | \n\t\t\t0% | \n\t\t\t45% | \n\t\t\t40% | \n\t\t\t52% | \n\t\t\t0.99 | \n\t\t
39: Children with ADHD generally display an inflexible adherence to specific routines or rituals. | \n\t\t\t12% | \n\t\t\t0% | \n\t\t\t33% | \n\t\t\t29% | \n\t\t\t38% | \n\t\t\t2.37 | \n\t\t
Associated Features item statistics
Categorised responses to Associated Features items
In line with the relatively higher mean score of the Symptoms/Diagnosis subscale compared to the other subscales (Table 1), the item means presented in Table 3 for this subscale are generally higher than those of the Associated Features subscale. The items that the teachers found most difficult were 11, which state that it is common for ADHD children to have an inflated sense of self-esteem or grandiosity and 38, which states that if a child responds to stimulant medications then they probably have ADHD, as the mean correct responses obtained were 18% and 23%, respectively. More than two-thirds of the teachers scored the following items correctly: item 3, which states that ADHD children are frequently distracted by extraneous stimuli; item 9, which states that ADHD children often fidget or squirm in their seats; item 21, which states that a child must present with symptoms in two or more settings to obtain an ADHD diagnosis and item 26 which states that ADHD children often have difficulties organising tasks and activities.
Once again, in order to investigate the low item scores for Symptoms/Diagnosis, a distinction was made between misconceptions, that is, incorrect responses, versus “don’t know” responses. This distinction is displayed graphically for the Symptoms/Diagnosis items in Figure 2 where bars shaded in blue indicate the percentage of misconceptions and bars shaded in red indicate incorrect responses for each item. The figure shows that teachers have the greatest extent of misconceptions of ADHD Symptoms/ Diagnosis on item 7, which states that one of the symptoms displayed by ADHD children is that they are cruel to other people and item 14, which states that ADHD children often have a history of stealing or destroying other peoples’ things (48% and 47% misconceptions respectively). Figure 2 also shows that teachers have the least extent of misconceptions on items 21 and 16; which states that two clusters of symptoms exist for ADHD, and items 3, 9 and 26 have between 9% and 5% misconceptions.
\n\t\t\t\tItems\n\t\t\t | \n\t\t\t\n\t\t\t\tMean\n\t\t\t | \n\t\t\t\n\t\t\t\tMedian\n\t\t\t | \n\t\t\tStd.Dev. | \n\t\t\t\n\t\t\t\t95% Confidence Interval for mean\n\t\t\t | \n\t\t\t\n\t\t\t\tSkewness\n\t\t\t | \n\t\t|
3: ADHD children are frequently distracted by extraneous stimuli. | \n\t\t\t70% | \n\t\t\t100% | \n\t\t\t46% | \n\t\t\t40% | \n\t\t\t54% | \n\t\t\t-0.89 | \n\t\t
5: In order to be diagnosed with ADHD, the child\'s symptoms must have been present before age 7. | \n\t\t\t36% | \n\t\t\t0% | \n\t\t\t48% | \n\t\t\t42% | \n\t\t\t56% | \n\t\t\t0.59 | \n\t\t
7: One symptom of ADHD children is that they have been physically cruel to other people. | \n\t\t\t31% | \n\t\t\t0% | \n\t\t\t46% | \n\t\t\t41% | \n\t\t\t54% | \n\t\t\t0.83 | \n\t\t
9: ADHD children often fidget or squirm in their seats. | \n\t\t\t78% | \n\t\t\t100% | \n\t\t\t42% | \n\t\t\t37% | \n\t\t\t48% | \n\t\t\t-1.37 | \n\t\t
11: It is common for ADHD children to have an inflated sense of self-esteem or grandiosity. | \n\t\t\t18% | \n\t\t\t0% | \n\t\t\t39% | \n\t\t\t34% | \n\t\t\t45% | \n\t\t\t1.69 | \n\t\t
14: ADHD children often have a history of stealing or destroying other people\'s things | \n\t\t\t21% | \n\t\t\t0% | \n\t\t\t41% | \n\t\t\t36% | \n\t\t\t48% | \n\t\t\t1.45 | \n\t\t
16: Current wisdom about ADHD suggests two clusters of symptoms: One of inattention and another consisting of hyperactivity/impulsivity. | \n\t\t\t57% | \n\t\t\t100% | \n\t\t\t50% | \n\t\t\t44% | \n\t\t\t58% | \n\t\t\t-0.29 | \n\t\t
21: In order to be diagnosed as ADHD, a child must exhibit relevant symptoms in two or more settings (e.g., home, school). | \n\t\t\t68% | \n\t\t\t100% | \n\t\t\t47% | \n\t\t\t41% | \n\t\t\t54% | \n\t\t\t-0.78 | \n\t\t
26: ADHD children often have difficulties organizing tasks and activities. | \n\t\t\t77% | \n\t\t\t100% | \n\t\t\t42% | \n\t\t\t37% | \n\t\t\t49% | \n\t\t\t-1.30 | \n\t\t
38: If a child responds to stimulant medications (e.g., Ritalin), then they probably have ADHD. | \n\t\t\t23% | \n\t\t\t0% | \n\t\t\t42% | \n\t\t\t37% | \n\t\t\t49% | \n\t\t\t1.30 | \n\t\t
Symptoms/Diagnosis item statistics
Categorised responses to Symptoms/ Diagnosis items
As for the Associated Features subscale, the knowledge level on the treatment subscale was poor (Table 4), with 14% or fewer of the teachers responding correctly to item 23, which states that the reduction of sugar intake leads to the reduction of ADHD symptoms; item 34, which states that behavioural interventions for children with ADHD focus primarily on the child’s problems with inattention; item 35, which states that Electroconvulsive Therapy has been found to be an effective treatment for severe cases of ADHD and item 37, which states that research has shown that the prolonged use of medications leads to increased addiction in adulthood. Only on item 10, which states that parent and teacher training in managing an ADHD child are generally effective when combined with medication, did the majority of the teachers answer correctly.
Once again, the categorised responses of “don’t know” versus misconceptions and correct responses are displayed in Figure 3 for Treatment items. This figure shows greatest misconceptions for items 23 and 34, which relate to dietary intake and ADHD and behavioural/psychological interventions for children with ADHD (53% and 47% incorrect responses respectively), and fewest misconceptions on item 35; which relates to electroconvulsive therapy as a treatment approach for ADHD and item 20, which states that medication is often used before other behaviour modification techniques are attempted.
\n\t\t\t\tItems\n\t\t\t | \n\t\t\t\n\t\t\t\tMean\n\t\t\t | \n\t\t\t\n\t\t\t\tMedian\n\t\t\t | \n\t\t\tStd.Dev. | \n\t\t\t\n\t\t\t\t95% Confidence Interval for mean\n\t\t\t | \n\t\t\t\n\t\t\t\tSkewness\n\t\t\t | \n\t\t|
2: Current research suggests that ADHD is largely the result of ineffective parenting skills. | \n\t\t\t37% | \n\t\t\t0% | \n\t\t\t49% | \n\t\t\t43% | \n\t\t\t56% | \n\t\t\t0.55 | \n\t\t
8: Antidepressant drugs have been effective in reducing symptoms for many ADHD | \n\t\t\t46% | \n\t\t\t0% | \n\t\t\t50% | \n\t\t\t44% | \n\t\t\t58% | \n\t\t\t0.16 | \n\t\t
10: Parent and teacher training in managing an ADHD child are generally effective when combined with medication treatment. | \n\t\t\t65% | \n\t\t\t100% | \n\t\t\t48% | \n\t\t\t42% | \n\t\t\t56% | \n\t\t\t-0.64 | \n\t\t
12: When treatment of an ADHD child is terminated, it is rare for the child\'s symptoms to return. | \n\t\t\t26% | \n\t\t\t0% | \n\t\t\t44% | \n\t\t\t39% | \n\t\t\t51% | \n\t\t\t1.11 | \n\t\t
15: Side effects of stimulant drugs used for treatment of ADHD may include mild insomnia and appetite reduction. | \n\t\t\t43% | \n\t\t\t0% | \n\t\t\t50% | \n\t\t\t44% | \n\t\t\t58% | \n\t\t\t0.29 | \n\t\t
18: Individual psychotherapy is usually sufficient for the treatment of most ADHD children. | \n\t\t\t19% | \n\t\t\t0% | \n\t\t\t39% | \n\t\t\t35% | \n\t\t\t46% | \n\t\t\t1.60 | \n\t\t
20: In severe cases of ADHD, medication is often used before other behavior modification techniques are attempted. | \n\t\t\t36% | \n\t\t\t0% | \n\t\t\t48% | \n\t\t\t42% | \n\t\t\t56% | \n\t\t\t0.59 | \n\t\t
23: Reducing dietary intake of sugar or food additives is generally effective in reducing the symptoms of ADHD. | \n\t\t\t7% | \n\t\t\t0% | \n\t\t\t26% | \n\t\t\t23% | \n\t\t\t30% | \n\t\t\t3.42 | \n\t\t
25: Stimulant drugs are the most common type of drug used to treat children with ADHD | \n\t\t\t34% | \n\t\t\t0% | \n\t\t\t48% | \n\t\t\t42% | \n\t\t\t55% | \n\t\t\t0.69 | \n\t\t
34: Behavioral/Psychological interventions for children with ADHD focus primarily on the child\'s problems with inattention. | \n\t\t\t12% | \n\t\t\t0% | \n\t\t\t33% | \n\t\t\t29% | \n\t\t\t38% | \n\t\t\t2.37 | \n\t\t
35: Electroconvulsive Therapy (i.e. shock treatment) has been found to be an effective treatment for severe cases of ADHD. | \n\t\t\t14% | \n\t\t\t0% | \n\t\t\t35% | \n\t\t\t31% | \n\t\t\t41% | \n\t\t\t2.11 | \n\t\t
36: Treatments for ADHD which focus primarily on punishment have been found to be the most effective in reducing the symptoms of ADHD. | \n\t\t\t47% | \n\t\t\t0% | \n\t\t\t50% | \n\t\t\t44% | \n\t\t\t58% | \n\t\t\t0.12 | \n\t\t
37: Research has shown that prolonged use of stimulant medications leads to increased addiction (i.e., drug, alcohol) in adulthood. | \n\t\t\t12% | \n\t\t\t0% | \n\t\t\t33% | \n\t\t\t29% | \n\t\t\t38% | \n\t\t\t2.37 | \n\t\t
Treatment item statistics
Categorised responses to Treatment items
In order to investigate whether the teachers’ general knowledge of the content areas of ADHD differed in terms of their demographic group,their scores on the three ADHD content areas were compared across the levels of each of the demographic variables (Table 5) using 1- way Analysis of Variance (ANOVA).
\n\t\t\t\t\n\t\t\t | \n\t\t\t\n\t\t\t\tdf\n\t\t\t | \n\t\t\t\n\t\t\t\tAssociated Features – F\n\t\t\t | \n\t\t\t\n\t\t\t\tAssociated Features - p\n\t\t\t | \n\t\t\t\n\t\t\t\tSymptoms/Diagnosis - F\n\t\t\t | \n\t\t\t\n\t\t\t\tSymptoms/Diagnosis – p\n\t\t\t | \n\t\t\t\n\t\t\t\tTreatment - F\n\t\t\t | \n\t\t\t\n\t\t\t\tTreatment – p\n\t\t\t | \n\t\t
2. Age group | \n\t\t\t2 | \n\t\t\t2.114 | \n\t\t\t\n\t\t\t | 2.126 | \n\t\t\t\n\t\t\t | 2.674 | \n\t\t\t\n\t\t |
3. Education level | \n\t\t\t1 | \n\t\t\t15.780 | \n\t\t\t*** | \n\t\t\t13.919 | \n\t\t\t*** | \n\t\t\t6.409 | \n\t\t\t* | \n\t\t
4. Number of years of teaching experience | \n\t\t\t2 | \n\t\t\t1.485 | \n\t\t\t\n\t\t\t | 1.174 | \n\t\t\t\n\t\t\t | 0.092 | \n\t\t\t\n\t\t |
5. Hours of ADHD training received | \n\t\t\t2 | \n\t\t\t9.035 | \n\t\t\t*** | \n\t\t\t8.521 | \n\t\t\t*** | \n\t\t\t15.924 | \n\t\t\t*** | \n\t\t
6. Evaluations/ assessments of children you thought may be ADHD | \n\t\t\t1 | \n\t\t\t0.071 | \n\t\t\t\n\t\t\t | 0.432 | \n\t\t\t\n\t\t\t | 0.059 | \n\t\t\t\n\t\t |
7. Number of children taught with a medical diagnosis of ADHD | \n\t\t\t1 | \n\t\t\t0.347 | \n\t\t\t\n\t\t\t | 0.919 | \n\t\t\t\n\t\t\t | 1.431 | \n\t\t\t\n\t\t |
8. Number of workshops attended on ADHD | \n\t\t\t1 | \n\t\t\t11.508 | \n\t\t\t** | \n\t\t\t13.928 | \n\t\t\t*** | \n\t\t\t20.087 | \n\t\t\t*** | \n\t\t
9. Number of articles read on ADHD | \n\t\t\t2 | \n\t\t\t6.538 | \n\t\t\t** | \n\t\t\t18.290 | \n\t\t\t*** | \n\t\t\t20.170 | \n\t\t\t*** | \n\t\t
10. Confidence to teach a child with ADHD | \n\t\t\t3 | \n\t\t\t3.275 | \n\t\t\t* | \n\t\t\t8.298 | \n\t\t\t*** | \n\t\t\t5.629 | \n\t\t\t** | \n\t\t
11. Teachers asked by a DR to assess the medication of a child with ADHD | \n\t\t\t1 | \n\t\t\t12.506 | \n\t\t\t*** | \n\t\t\t21.961 | \n\t\t\t*** | \n\t\t\t16.809 | \n\t\t\t*** | \n\t\t
ADHD content areas compared across levels of demographic variables
Education and training is the common theme underlying these items reflecting significant differences on knowledge levels of the three ADHD content areas. Based on the direction of the means and the Scheffe post hoc tests for the significant ANOVA comparisons, the general trend of the means is that the more educated and trained teachers are more knowledgeable in each of the three ADHD content areas than are the less educated and trained teachers. Specifically, teachers with a university education score significantly higher than those with a college education [F (1;93) = 15. 780, p < 0.001; F(1; 93) = 13.919, p < 0.001; and F (1;93) = 6.409, p < 0.05], teachers with more than ten hours of ADHD training score higher than teachers with none or few hours, [(F (1; 93) = 9. 035, p < 0.001; F (1; 93) = 8.521, p< 0.001; and F (1; 93) = 15. 924, p <0.05]. Those teachers that have attended ADHD workshops score higher than those who have not [(F (2; 93) = 11. 508, p < 0.001; F (2; 93) = 13. 928, p< 0.001; and F (1; 93) = 20. 087, p <0.05]. Those teachers who have read more than five ADHD articles score higher than those who have not read any ADHD articles [(F (2; 93) = 6. 538, p < 0.001; F (2; 93) = 18. 290, p< 0.001; and F (2; 93) = 20. 170, p <0.05]. In addition, those teachers who have been asked by a doctor to assess medication of a child with ADHD, and those who feel more confident to teach children with ADHD have significantly higher scores on the three ADHD content areas than other teachers (F (3; 93)= 3.275, p < 0.001; F (3; 93) = 8.298, p < 0.001 and F(3; 93) = 5.629, p< 0.05) and (F (1; 93)= 12. 506, p < 0.001; F (1; 93) = 21. 961, p < 0.001 and F(1; 93) = 16. 809, p< 0.05). Finally, it should be noted for all the significant comparisons of the demographic variables, knowledge levels on the Symptoms/ Diagnosis content area were significantly higher than on the Associated Features and Treatment content areas. The qualitative results from the questionnaire revealed that teachers are willing and eager to participate in workshops on ADHD, substantiated by 73% of the sample group indicating that they were in favour of this. Interestingly, the 27% of teachers who did not opt to attend the workshop tended to be older, less confident (Pearson Chi-square(3) = 6.41, p<0.10), tended to have attended fewer ADHD workshops, read fewer ADHD articles and had been less often asked by a doctor to assess the medication of a child with ADHD (Pearson Chi-square(1) = 5.00, p<0.05). However, although the mean scores on the three content areas of ADHD of the respondents who opted for the workshops were marginally higher than those who did not opt to attend, these differences were not significant.
Teachers were given the opportunity to provide additional comments at the end of the questionnaire. Four teachers commented that there exists a lack of resources at the disposal of teachers and that schools should have special classes for children with ADHD, and that schools have a dire need for psychologists to help identify the children who are displaying ADHD -like symptoms as soon and early on as possible. Some of the teachers explained that there is often a misdiagnosis of ADHD; and often an over diagnosis made by teachers of this condition. Teachers expressed that they would like to learn more about the identification, treatment and possible classroom interventions for learners with ADHD children.
This study sought to investigate the knowledge and perceptions of ADHD held by Foundation Phase teachers within a township setting in South Africa. The results of the study suggested that there exists a substantial lack of knowledge about ADHD among this sample group. These findings are consistent with the body of literature which states that teachers generally lack knowledge and hold certain misconceptions in the area of ADHD [21]. Teachers in the present study were the most knowledgeable about the symptoms of ADHD, less knowledgeable about the associated features and the least knowledgeable about treatment for this condition; which supported the results reported in an Australian study [21].
Teachers’ generally good understanding of the symptoms of ADHD which was shown in this research study, is supported by several other South African studies which were conducted using a range of different teacher and school samples [2, 26, 28, 44]. Even though teachers in this study obtained the highest percentage of correct responses for the symptoms/diagnosis subscale of the KADDS, there were two specific items which resulted in the greatest extent of teacher misperception. Physical cruelty to other people and a history of stealing and destroying other people’s things were perceived by the teachers as features of ADHD. The behaviours included in these two items are those that are characteristic of a Conduct Disorder and suggestive of an Oppositional Defiant Disorder [45], which the teachers in the present study may not have been aware of. These findings are consistent with the results of a study that was conducted in America [23].
In the present study, teachers were less knowledgeable about the associated features of ADHD, than they were about the symptoms, as half of the respondents answered less than 31% of the items on this subscale correctly. However, teachers obtained the lowest scores on the treatment subscale. Teachers in the present study possessed very poor and even incorrect knowledge regarding the treatment of ADHD. This finding has an important implication for teacher pre-service and in-service training, as teachers play an important role in the identification, management and treatment of ADHD [21]. Teachers in this study seemed to possess limited and even incorrect knowledge on the after effects of medication, and many of them believed that stimulant medications lead to drug and alcohol addictions in adulthood. Nevertheless, the majority of the teachers in the current study were aware that parent and teacher training in managing a child diagnosed with ADHD combined with medical treatment, was generally an effective and preferable method of treatment for this condition.
In line with the results of a number of other studies [2, 46], a large number of teachers in the present study incorrectly believed that the alteration of diet and the reduction of sugars and food additives would lead to the alleviation of ADHD symptoms. Few studies have supported the idea that the alteration of one’s diet alleviates symptoms of ADHD, and in fact labels this belief as a common myth [15].
Among the sample group in this study, there existed a clear lack of knowledge on the epidemiology of ADHD, as a very low percentage of correct responses was obtained for the item which stated that most estimates suggest that ADHD occurs in approximately 15% of school age children. As pointed out by the study conducted by [23], if teachers are unaware of how many students in their classrooms have ADHD, it may lead to the condition being overlooked and unidentified, or conversely, it may lead to the teacher attributing many of a child’s unruly and uncharacteristic behaviours to ADHD resulting in incorrect referrals [2].
Poor academic performance is often considered as one of the most prominent factors associated with ADHD, and students with ADHD are at an increased risk for grade retention and school failure [15]. Teachers in the present study seemed to be aware of this, and results revealed a large number of correct responses for the questionnaire item which looked at the idea that the majority of ADHD children evidence some degree of poor school performance in the elementary school years.
In this study, while the age of the teachers was unrelated to their overall level of ADHD knowledge, their educational level was positively related to this variable. The higher their level of education, the more knowledge they possessed on ADHD, possibly as a result greater exposure to this condition. Unlike the findings of [31], teachers’ knowledge of ADHD was unrelated to their number of years of teaching experience in this study. An important finding for school administrators is the result that teachers who previously attended training programmes and workshops and those that were exposed to ADHD by means of written articles, all knew more about the condition than those teachers with less training and exposure in the area. Furthermore, teachers who felt more confident to teach a child with ADHD obtained higher scores on the KADDS, and thus knew more about the condition. This finding supports the results of studies conducted by [2, 31], where the more confident teachers had more knowledge on ADHD.
It was noted in this study, that it was the younger, more confident, more experienced teachers who wanted to participate in workshops on ADHD. The teachers also suggested that the workshops include a section on treatment, which is an area where knowledge is seemingly lacking. The older, more inexperienced teachers were those who were reluctant and disinterested to partake in workshops. One reason for this may be because the older teachers are more set in their ways, and are thus more reluctant to engage in and learn new material.
The finding may be related to what Martin Seligman calls learned helplessness. This is once an “individual learns that he or she is not in control, the motivation to seek control may be shut down, even when control later becomes possible [47, p.252]. Due to the lack of resources within the townships in South Africa and the possible lack of options that some of these teachers are faced with, they may have come to learn that they are not in control of the situation, and often what they do is to no avail. Thus, when a workshop is offered to them, they may have learned that they are not in control, and consequently they do not believe that the workshop will be of assistance and benefit to them.
Results of the study imply that South African Foundation Phase teachers do not have adequate knowledge or sufficient understanding of ADHD. Teachers seem to have some information on the symptoms of ADHD, and less on the associated features and treatment for the condition. It is therefore important that training programmes or workshops address these gaps in the teachers’ knowledge regarding the condition. Overall, the majority of teachers in this study expressed willingness to participate in workshops and training programmes on ADHD. Teachers also indicated that there is a lack of resources at the township schools to aid in the recognition and management of the condition. It is essential that the South African Department of Education becomes aware of these issues and provides teachers with the necessary training and ongoing support to facilitate the learning and schooling experience and holistic development of children with ADHD. This is of particular importance if inclusive education is to be implemented successfully.
The following were some of the limitations of the present research study:
The sample for the study was obtained on a strict voluntary basis; using a purposive, non probability sampling method. The current sample is not representative of the entire population of Foundation Phase township teachers. Responses to the questionnaire were very much dependent on the teachers’ availability and willingness to participate in the study. A sample of 100 teachers from a specific geographic location was obtained, and there were no male participants. Thus, the sample used in the study was small and narrow. For these reasons, issues with generalisability arose and therefore widespread conclusions from the results cannot be drawn.
English is not a first language for many of the teachers that participated in the research study. It is unknown to what extent the teachers’ responses to the questionnaire were hampered by language related issues, which similar research studies conducted in the future would have to consider. The construct validity of the measuring instrument used was therefore a possible limitation of the study.
There is limited local literature and research on ADHD. Further work is necessary to develop and contextualize international developments in relation to the unique South African context.
The following suggestions are made for future research:
The majority of teachers in this study were willing to participate in workshops related to ADHD training. Future researchers could focus on creating and providing training programmes that would bridge the gaps in knowledge about ADHD and its causes, symptoms and treatment.
After the implementation of teacher training and workshops, follow up programme evaluation studies and longitudinal research would be beneficial. This research could serve as a springboard for future workshops and educational programs to be implemented at schools at a national level.
Broader teacher samples from public, private, rural and township schools need to be considered in future ADHD studies.
Future research could focus on creating awareness and gathering resources to aid in the recognition and management of the condition at schools. It is essential that teachers receive the necessary training and ongoing support to facilitate the learning and schooling experience of children with ADHD.
This chapter primarily focused on one particular South African study [36] that sought to investigate the knowledge and perceptions of ADHD held by Foundation Phase teachers in a township in Gauteng. The results of the study were compared to local and international research conducted in the last decade. After an in depth analysis of the results of the study and other research conducted, the chapter highlighted that the lack of knowledge that teachers has, as well as the misperceptions they hold regarding ADHD, need to be addressed as teachers play a vital role in the identification, diagnosis, referral and treatment process of ADHD. Inaccurate information about ADHD can lead to inaccurate referrals, resulting in the incorrect information being relayed to parents and doctors, which in itself has negative effects and consequences for individuals’ diagnosed with the condition. In addition the chapter also noted the need for more workshops and programmes to become available to teachers to aid them in the recognition and management of ADHD in their classrooms. Overall, the chapter highlighted the need for more research to be conducted in the area of ADHD in South Africa, in order for every learner to maximise his or her potential and to succeed within the South African inclusive education classroom environment.
In the context of this chapter, a satellite is a spacecraft (SC) that orbits around a celestial body such as the earth. A spacecraft has several design constraints placed upon it before it can be placed in an orbit around the intended celestial body. First, satellite designs are limited in their mass and volume to fit on the launch vehicle that places them into orbit. Secondly, the mass and volume limits affect the size of the power system on the spacecraft; therefore, the amount of power available to the satellite is also limited. In addition, the space environment (thermal, radiation, atomic oxygen, space debris, micrometeoroids, etc.) imposes constraints on the design such as parts and material selection.
A spacecraft is consisted of two parts: the spacecraft bus and the payload (PL) [1, 2]. The spacecraft bus provides control of the satellite and support services to the mission payload, while the mission payload provides the mission part of the satellite including payload control, mission data processing, and mission data downlink dissemination. Examples of mission payloads (or payloads or PLs) are: scientific instruments, remote sensing instruments, navigation service transmitters, or communications equipment. A satellite may have one type of PL or a combination of payload types to accomplish its mission such as navigation, remote sensing, and communications. Shown below in Figure 1 is a typical imaging satellite used for the remote sensing mission. Note the clear separation between the spacecraft bus that provides solar power and maneuvering capability via thruster, while the payload consisting of the camera and supporting communication devices such as antennas and guidance devices such as star trackers.
A typical satellite with bus and payload separation.
Regardless of the mission type1 and the payload that a spacecraft carries, a subsystem that must exist in all satellites is the communication subsystem that enables the spacecraft to communicate with the ground stations that control the satellite and to deliver the data that the mission requires. This chapter focuses on architecture and functionalities of the communications subsystem that usually resides on the satellite.
There are three specific segments shown in Figure 2 below that must work together for the larger overall system to provide communication, navigation, or any other type of missions:
The space segment consisting of all satellites and associated equipment required for the mission applications and the launch vehicles used to deliver those satellites to orbit.
The satellite control (or control) segment consisting of all the personnel, facilities, and equipment that are used to monitor and control all the assets in space. Practically, the control segment is also referred to as satellite ground segment because it is usually located on the ground.
The user segment consisting of all the individuals and groups who use and benefit from the data and services provided by the payloads of the satellite and the equipment that allows this use.
The three main segments for satellite system.
In general, the space mission dictates the type of orbit2, satellite design and its expected life cycle, and its operational scenarios. The PL design includes dimensions, interfaces, weight, physical characteristics, and basic utility needs (e.g., power consumption), which usually influences spacecraft (SC) bus design. The PL is often a unique and one-of-a-kind design tailored to meet specific mission requirements, frequently relying heavily on newer technology, while the satellite bus has the supporting function, and as such relies largely on existing or modified hardware such as batteries, inertial devices, and star trackers. Since PLs and their missions vary widely, so is this satellite bus supporting role.
Traditionally, the PL is considered a subsystem of the satellite bus that is designed to generally satisfy the corresponding mission requirements. The PL operational requirements sometimes impose specific requirements on the satellite bus that must be satisfied for the PL to accomplish its mission. This interdependence between satellite bus and PL subsystems has historically resulted in many nonstandard interfaces developed and implemented by the incumbent spacecraft builders. As a result, the aerospace industry has been moving toward a more standardized and commodity satellite bus framework that can potentially result in a tremendous cost saving approach.
As shown in Figure 3 below, a satellite bus typically consists of the following subsystems: command and data handling subsystem (C&DHS); communications subsystem (CS); electrical power subsystem (EPS); propulsion subsystem (PS); thermal control subsystem (TCS); attitude control subsystem (ACS) also known as guidance, navigation and control (GNC) subsystem; structures and mechanics subsystem (S&MS); and life support subsystem for manned missions if required. The C&DHS will be described in detail below. The CS provides the satellite bus with the necessary communication functionalities to connect the user and ground segments to different satellite subsystems. The EPS provides the electrical power generation and distribution for various spacecraft subsystems. The PS provides maneuvers necessary for altitude, inclination adjustment, and momentum management adjustments. The TCS provides active thermal control from electrical heaters and actuators to control temperature ranges of equipment within specific ranges. The ACS provides proper pointing directions for the satellite subsystems, such as sun pointing for EPS to the solar arrays and earth pointing for CS. The S&MS provides the necessary mechanical structure to withstand launch loads by the launch vehicle, during orbital maneuvers, as well as loads imparted by entry into the atmosphere of earth or another planetary body.
A typical satellite bus and payload subsystem.
On the other hand, a PL is tailored to a specific mission type. For example, a remote sensing satellite can have as its payload an electro-optical (EO) camera to take day-time pictures of the earth and then convert them to electrical signals that can be captured. Alternatively, the camera may also have infra-red (IR) sensors that enable the PL to see the earth at night, or microwave sensors that will let the PL “see” radio frequency (RF) signals from the earth at several radio frequencies (RFs). These sensors can be classified as passive or active, and each of them can be further classified as imaging or sounding3. Figure 4 below illustrates a generic imaging PL that will convert the sensor analog data into electrical signals that can be captured and transmitted to a ground station. Note the existence of a communication subsystem as part of this imaging payload.
A typical and generic sensor payload.
In this section, the different typical modules of a satellite communication subsystem are discussed. In addition, the command and data handling subsystem, and command, telemetry and mission data processing subsystem will also be described in detail.
At the physical layer, the communications subsystem starts with an antenna and the RF front-end transceiver. The antenna is the most important component of the communications subsystem where the electromagnetic (EM) signals are originated or received. The RF front-end/back-end is where the EM signal is being down/up-converted to baseband/RF signal to be demodulated/modulated for baseband signal recovery or downlink transmission, respectively. Figure 5 below depicts a typical transmitter and receiver (transceiver) chain with the modulation and demodulation (MODEM), followed by the RF front-end and the antennas. The baseband communications function is carried out by the MODEM, whereas the RF portion is handled in the transceiver, RF front-end, and antenna sections.
Typical RF front-end chain.
Modulation is the name given to the process of impressing the wanted signal to be transported onto a radio frequency (RF) carrier, which is then conveyed over the satellite link and demodulated at the receiving terminal to extract the wanted signal from the carrier. Thus, modulation translates a baseband spectrum (at zero frequency) to a carrier spectrum (at RF range) and demodulation is the process of recovering the data at the receiver end of the link. Thus, the process requires a modulator and a demodulator, collectively known as a MODEM. The input to the modulator may require some initial processing such as filtering and amplitude limiting.
Before the RF signal is sent to the antenna, a traveling wave tube amplifier (TWTA) or solid-state power amplifier (SSPA) is needed to amplify the RF signal to a desired level for transmission. Conversely, after the RF signal is received by the antenna, a low noise amplifier (LNA) is needed to ensure that the received signal is brought up to the desired signal level with minimum noise before demodulation.
In addition to being lighter than TWTA, the achievable power efficiency for SSPAs is a major factor to support transmit phased arrays. Currently, the tube-based TWTA implementations are still the most cost-effective design, even though both options might be viable for lower power systems.
In increasing technical maturation over the years, the following types of spacecraft antennas have been used for satellite communications:
Low-gain omni and squinted-beam antennas for large earth coverage.
Increased gain types of satellite antennas (horn type and helix antennas) for medium earth coverage.
Parabolic reflectors, including multi-beam antennas with multiple feed systems for multiple user and small area coverage.
Deployable antennas, particularly to achieve more highly focused beams and support much high-gain multi-beam antennas.
Phased array feed and phased array antennas for scanning and hopping beams.
Optical communications systems, which have been used for intersatellite links and interplanetary communications, and increasingly being considered for earth-to-space systems.
In general, there are many different types of antennas, but the one most commonly associated with satellite communications is the parabolic dish antenna. These dish antennas have a narrow beam width, concentrating the energy of the radiated main beam into a smaller solid angle. This means more of the radiated energy reaches, or “illuminates,” the satellite when using a dish antenna as compared to an omnidirectional, or “omni” for short, antenna. An example of dish antenna used on satellite is shown below in Figure 6 for a Ku-band space to ground antenna (SGANT) mounted on the external stowage platform of the International Space Station (ISS).
Example of a satellite dish antenna.
There are several factors driving the design and development of satellite antennas. These include the need to reuse frequency bands because of limited spectrum allocations; the need to have antennas that can operate at higher frequencies with higher bandwidth; and the desire to deploy higher gain antennas at the same time minimizing the required size, weight, and power (SWAP) constrains. In practice, there are substantially more SWAP constrains for satellite antennas than on the ground stations, and this results in several design trade-offs between the space and control/user segments.
For example, the GEO orbit allows a high gain antenna to be pointed at a satellite with a minimum of tracking. Thus, a large dish can be used and remain virtually stationary without tracking a satellite as it moves around in its orbit. On the other hand, a low earth orbit (LEO) satellite that can cross from horizon to horizon in a few seconds can result in ground antenna installations that can be quite complex and expensive. Consequently, trade-offs need to be made to support the mission parameters of the whole satellite network.
The term “command and data handling subsystem” (C&DHS) was referred to as “On-board Computer” (OBC), which is a legacy of the past in which many satellite functions were performed by analog circuits with the help of an OBC. With the current shift toward the digital domain, the term OBC does not fully cover the topic anymore thus C&DHS is being used instead. An appropriate analogy to describe the C&DHS subsystem is to regard it as the brain and nervous system of the spacecraft.
The function of a C&DHS subsystem is to perform onboard processing and operations and internal communication [3, 4]. The task of managing the operations of the spacecraft subsystems is nowadays performed mostly by software in an autonomous manner and is generally categorized as onboard operations. The software is also responsible for preparing the data to be downlinked and handling any commands that are received from satellite operators on the ground. Lastly, the C&DHS facilitates and controls all internal communications (consisting of commands, telemetry, and tracking data) between the different satellite subsystems. The basic functions of the C&DHS can be summarized below:
Receives commands from the command or user segment through the telemetry, tracking, and control (TT&C) subsystem.
Decodes, executes, and/or distributes those commands to/from the onboard computer.
Collects and formats telemetry data from all space vehicle (SV) units.
Distributes telemetry for downlinking. Provides a platform for bus flight software (FSW).
Additional functions include ranging processing for satellite tracking purpose, satellite timekeeping, computer health monitoring (watchdog), and security interfaces.
An overview of the architecture of C&DHS in a typical satellite is provided in Figure 7 below. In this figure, all components are connected to each other via a common low-speed data bus in red color, typically compliant with MIL-STD 1553 or other standards. Also shown is the data connection in blue from the C&DHS to other components, which is more customized and high-speed in nature depending on the design.
Block diagram of a typical command and data handling subsystem.
The heart of the system is the C&DHS’ onboard computer (or OBC) that runs the software responsible for managing the onboard operations. The OBC is tightly linked to the electrical power subsystem (EPS). The main reason is the importance of the available and consumed power for managing onboard spacecraft operations. For instance, by continuously querying the EPS on the available power, the OBC can decide to turn off non-critical subsystems to prevent vital systems from shutting down from lack of power. Secondly, the OBC must be able to command the EPS to disable or enable different subsystems throughout the various phases of the mission. Since the amount of transmitted data between these two subsystems is small, a low-speed data link is sufficient, although there is a new trend to incorporate high-speed standard link such as SpaceWire4 to satisfy increasing demand for data volume.
The OBC is also responsible for receiving, interpreting, and executing commands from ground operators via the radio receiver. Using low-speed radio transmitters, the OBC also sends packets of housekeeping data, or telemetry, to the ground station. The purpose of the housekeeping data is to give the operators on the ground an overview of the spacecraft health and its general condition.
Some small satellites only have a single low-speed transmitter, so the housekeeping and payload data are combined over the same link. For larger satellites with payloads capable of producing vast amounts of data, a dedicated high-speed data link is used to store the data on an onboard storage system. When the satellites pass over a ground station, the OBC commands the high-speed radio transmitter to retrieve and transmit the previously stored payload data through another dedicated high-speed link from the onboard storage system. This approach frees the OBC from having to process large amounts of data and allows it to devote its internal resources for time critical operations and communicates with the PL and all other subsystems through the low-speed data links. This would include the requirements to retrieve information on the health, perform critical interventions as well as to command these subsystems to perform various actions according to the operational arrangement of the mission.
The telemetry, tracking, and control (TT&C) subsystem of a satellite provides a connection between the satellite (space segment) and the ground facilities (control or user segment). The purpose of the TT&C function is to ensure the satellite performs correctly. As part of the satellite bus, the TT&C subsystem is required for all satellites regardless of the mission type. The TT&C subsystem has three specific tasks that must be performed to ensure a successful mission:
Telemetry: the collection, processing of health, and status data of all spacecraft subsystems, and the transmission of these data to the control segment on the ground. This requires not only a telemetry system on the spacecraft but also a global network of ground stations around the world, unless the satellite space network includes intersatellite links that can relay the data to designated satellite and downlink to the appropriate ground station. Figure 8 below illustrates the processing of telemetry data by the C&DHS. Here the different health information and status information sent from various subsystems are collected by the telemetry input interface, fed to the C&DHS processor, buffered, encrypted, and sent down to the ground station.
Tracking: the determination of the satellite’s exact location by the control segment and where it is going via the reception, processing, and transmitting of ranging signals. This requires a ranging system on the spacecraft and a data collection ground network for this tracking function to work.
Command and control: the reception and processing of commands for continuous operation of the satellite. Usually a ground system is required, although advanced spacecraft designs have evolved toward “autonomous operations” so that many of the control functions can be automated onboard and do not require ground intervention except under emergency conditions. A typical command processing scenario is illustrated in Figure 9 where serial command bit stream from the command receiver is received by the command input interface, where the relevant commands are extracted and sent to the appropriate subsystems via a serial or parallel interface.
Telemetry processing by C&DHS.
Command and control message processing by C&DHS.
For communications payload, the onboard switching systems are designed to make more efficient use of a satellite communication network, especially those that employ multi-beam technology that entails onboard switching to interconnect uplink and downlink beams with a high degree of efficiency.
Figure 10 below summarizes the functional block diagram of a channelized transponder processor assuming a digital implementation of the channelized transponder filtering and switching function. Any signal within the receiver bandwidth is down-converted to an intermediate frequency (IF) or baseband and digitally sampled. These samples are digitally filtered, stored, and routed to the switch port corresponding to the desired downlink beam. This routing is achieved by a simple readdressing of the stored digital samples within a common output buffer memory or by a more traditional digital switch implementation.
Channelized processor for communications payload.
For most sensing payload and as shown in Figure 4 above, the sensor analog data are collected onboard, digitized, buffered if necessary, and transmitted down to ground station for processing. This is due to the complexity of sensing mission data processing and the lack of onboard computational power to accomplish these tasks. An example of onboard PL processing for passive electro-optical (EO) remote sensing is shown in Figure 11 below, where the reflected light from earth is passing through a combination of optical lenses and charge coupled device5 (CCD) whose output is an analog signal that would be conditioned by analog filters before being digitized, compressed, and sent down via a mission data downlink to the ground station for processing. There, the data are decompressed, and image is enhanced by appropriate algorithms and displayed for users.
Onboard image processing for an EO application.
Typical data volume collected by sensing payload is large, and peak rates can produce data at much higher speeds than TT&C; thus, a separate downlink for mission data is needed. Depending on the system, this mission data downlink to a ground station can either be performed using a dedicated mission direct downlink, or indirectly via a relay broadband communications satellite. Sensing satellite can be positioned in GEO, MEO, or LEO orbits, and can have many possible mission data downlink architectures based on mission requirements. For example, a LEO sensing satellite can either buffer its mission data until within view of a dedicated ground station for downlink, or it can forward its mission data to a relay satellite that can ensure that the mission data can be downlinked to a designated ground station.
Another example of active remote sensing is a synthetic aperture radar (SAR) mission, where returned radar signals are collected onboard and sent to the ground to be correlated and form an image of the ground surface. This type of remote sensing does not heavily depend on sun light and other weather affects. Applications for SAR include agriculture, geology, geohazards, ice, oil spills, and flood monitoring. Several emerging applications such as forestry, ship detection, and others are possible [1]. An example of a SAR mission is the NASA-ISRO Synthetic Aperture Radar (NISAR) [17], which is a collaborative earth-science mission between NASA and the Indian Space Research Organization (ISRO). The sensing payload features an L-band SAR instrument and an S-band SAR instrument. The simultaneous dual-frequency radar system at peak rates will produce data at gigabit-per second speeds, which drives the data-volume requirements at a minimum of 35 Terabits per day of radar science data to the ground. This is a direct mission downlink system with three designated ground stations. The payload communication system uses a 70-cm high-gain antenna with two synchronized transmitters in a dual-polarization configuration with each transmitter providing 2.4 Gbps of coded data with an aggregate rate of 4.8 Gbps.
Traditional communications systems are designed for and constrained to a specific waveform(s) operating over predetermined frequencies, bandwidths, and signal modulation types. This paradigm works well when the requirements and constraints of the communication link and network protocol are well understood prior to design.
As a result, most radios in today’s world have very dedicated uses. A car key fob is designed only to unlock or lock your car door, while a smart phone radio connects to the Internet through various wireless communication protocols. Although these examples vary in complexity of the hardware, they both cannot operate outside the confines of their physical layer implementation. Consequently, RF hardware with a narrow focus is not suitable for applications with a broader communication scope.
A single software defined radio (SDR) with a flexible RF front-end combined with modern computing power can be used for the above applications plus more. In addition, a radio with a flexible hardware and software architecture can also lead to more innovation in the communications industry. Because of the rapid development nature of software, an engineer or researcher can experiment with novel ideas and SDR waveforms that would not be achievable with a traditional radio.
SDR in the satellite communications industry has become a growing trend, particularly in the commercial and defense industries. In the following section, an overview of SDR will be given and applications of SDR in satellite communications will be discussed.
Before going into SDR basics, some of the SDR advantages are [8]:
Interoperability: an SDR can seamlessly communicate with incompatible radios, or work as a bridge between them. For example, different branches of the military and law enforcement can use many incompatible radios, thus hindering communications during joint operations. A single multichannel SDR can work with all these different radios and provide interoperability.
Efficient use of resources under varying conditions: for example, a low-power waveform can be selected if the radio is running low on battery, while a high-throughput waveform can be used to quickly download a file. This flexibility is one of the first reasons why SDR became popular.
Opportunistic frequency reuse in SDR using cognitive radio6 (CR) technology: if the “owner” (or primary user) of a spectrum band is not using it, an SDR-CR can “borrow” the spectrum until the owner comes back. This technique has the potential to dramatically increase efficient use of radio frequency spectrum.
Reduced obsolescence: an SDR can be field upgraded to support the latest communications standards. This capability is especially important to radio with long life cycles such as those in satellite communications.
Lower cost: a single SDR can be adapted for use in multiple markets and for multiple applications. For example, a single radio can be sold to cell phone and automobile manufacturers to significantly reduce cost.
Research and development: SDR can be used to implement many different advanced waveforms, e.g., code division multiplexing access (CDMA) or orthogonal frequency division multiplexing (OFDM), for real-time performance analysis. Performance studies can be conducted much faster and often with higher fidelity than simulations.
On the other hand, some of the disadvantages for SDR are:
Cost is the most common argument against SDR. A single key fob is based on a very inexpensive ASIC7; however SDR is heavily reliant on FPGA,8 which is much more expensive. This is even more significant for high-volume, low-margin consumer products.
The second most common argument against SDR is increased power consumption with increased DSP complexity and higher mixed-signal/RF bandwidth. Power consumption in an FPGA or GPP for flexible signal processing can easily be 10 times higher than in ASIC. Also, wideband analog-to-digital converters (ADCs), digital-to-analog converters (DACs), and RF front-ends consume more power than their narrowband equivalents.
Increased time and cost to implement the radio: it can take much more engineering effort to develop software/firmware for multiple waveforms than for one, especially if it must be compliant with a military standard such as JTRS9.
Changing specifications and requirements: this usually happens when the SDR design must support not only a set of baseline waveforms but also anticipate additional waveforms.
Increased schedule risks: since SDR is still a relatively new technology, it is more difficult to anticipate schedule problems. Also, it is difficult to thoroughly test the radio in all the supported and anticipated modes.
Limited technical scope: SDR only addresses the physical layer and will require cooperation from upper layers for throughput improvements.
The general definition for a SDR is a radio with some or all its physical layer behavior defined through means of software [9, 11]. SDRs are incredibly valuable devices as they allow the end user the ability to traverse the RF spectrum at variable sampling rates. The fundamental qualities that make up an SDR are the flexible specifications and the ability to transform the analog signal using digital signal processing (DSP).
A radio can be categorically separated into receivers and transmitters. For this section, the receiver implementation will be considered as it is generally more interesting and complex. A block diagram of an SDR receiver is shown below in Figure 12. The following sections will present the anatomy of the SDR that differentiates it from a traditionally designed radio.
A block diagram of an SDR.
The purpose of the RF front-end (RFFE) is to isolate the desired signal received by the antenna from interference signals. To achieve this, the signal of interest must be brought down to lower frequency for digital conversion while mitigating the side effects from filtering during the frequency conversion process. A flexible RFFE for SDR must be designed so that the frequency and bandwidth are controllable by software. Depending on the system requirements and the available RF component specifications, there are several ways to achieve this.
One of the most common RFFE designs for analog radios is the heterodyne receiver. A heterodyne receiver, shown in Figure 13 below, works by mixing down the received signal from its carrier frequency to a lower intermediate frequency (IF). The signal at IF can now be more conveniently filtered, amplified, and processed. A super-heterodyne receiver uses a fixed IF that is lower than the carrier frequency but higher than the signal bandwidth and often uses two stages of down conversion to reduce the filtering requirements at each stage.
Heterodyne receiver.
Another popular RF front-end architecture generally used for low-power applications is called zero-IF. A zero-IF receiver, shown in Figure 14 below, uses a single mixing stage with the local oscillator (LO) set directly to the desired carrier frequency to convert directly to baseband in-phase and quadrature signals. Because mixers tend to have high power consumption and only low-pass filters are required, the simpler zero-IF provides improved power efficiency over a heterodyne architecture. However, the zero-IF implementation is more susceptible to IQ imbalances of the in-phase and quadrature oscillators, which will produce anomalies in the signal constellation. LO leakage may also self-mix through the RF ports creating a large DC bias. Both issues can be corrected using digital signal processing.
Zero-IF receiver.
The analog-to-digital converter (ADC) is responsible for converting a continuous-time signal to a discrete-time one. To translate signals from the analog to digital domain, an ADC must perform two fundamental steps: sampling and quantization. Sampling is the process of reading voltages at discrete-time intervals. Quantization is the process of converting these voltage readings into binary outputs. ADC performance can be evaluated based on various parameters, such as: signal-to-noise ratio (SNR), dynamic range, bit resolution, sampling rate, and power dissipation. The ADC dictates the DSP limitations of the SDR. Generally, the sampling rate should be at least twice the desired bandwidth of your signal. The ADC should be chosen to match the capability of your processor and specifications of the signals of interest.
The two main functions of a digital front-end are sample rate conversion (SRC) and channelization. Once a signal has become digitally converted, the samples need to be further primed for digital processing. Operating the ADC at a fixed rate simplifies its clock generation; however, it may be necessary to convert the sampling rate to match the sampling rate required to demodulate certain waveforms. Most wireless signals generally operate with specific symbol or chip rates that are specified by their respective standard. Depending on the RFFE design and signal type, channelization may be required to select the channel of interest.
SRC represents a classic sampling theorem problem. Converting sampling rates can introduce undesirable effects such as aliasing, an effect that causes frequency components to overlap. SRC can be achieved digitally through the processes of decimation and interpolation. To mitigate aliasing, decimation is performed by using an anti-aliasing filter followed by subsampling, which is essentially removing samples at certain intervals. Interpolation is a method of calculating values to add values in between samples. Channelization works by using digital down conversion, the process of digitally mixing down a signal to baseband with a numerically controlled oscillator.
SDRs have an array of devices to choose from for the required DSP application, each with their own strengths and weaknesses. An SDR may integrate multiple processor types and partition the signal processing chain to optimize each processor. The following criteria should be considered when evaluating the various processor types: flexibility, modularity, and performance. The three digital hardware choices this section will consider are the general-purpose processor (GPP), digital signal processor (DSP), and the field programmable gate array (FPGA).
A GPP is the typical microprocessor designed to handle a wide variety of generic tasks that can be found in your everyday personal computer. They are generally designed to have large instruction sets and highly capable of implementing and performing complex arithmetic tasks such as modulation/demodulation, filtering, fixed/floating point math, and encoding/decoding. Some commonly used GPP architectures are x86/64 and Advanced RISC Machine (ARM). The advantage of using a GPP is the wide availability, flexibility, and ease of programmability. Several GPP-based SDRs, such as Universal Software Radio Peripheral (USRP) and the LimeSDR, operate by digitizing the baseband signal and performing the required digital signal processing on computers. These types of SDRs are popular among university researchers and hobbyists due to the relative ease of obtaining and developing their applications.
Because the GPP was designed with such a broad focus, latency, speed, and power efficiency may be a limiting factor depending on the application. Many wireless communication standards have strict real-time and large processing bandwidth requirements that most modern CPUs cannot meet due to processor architecture and operating system design. .
A DSP is a microprocessor optimized for digital signal processing applications with the ability to be programmed with high-level languages. Although a GPP can contain much of the same functionality, the DSP performs the same digital signal processing operations more quickly and efficiently due to its reduced instruction set computer (RISC) architecture and parallel processing. The reduced instruction set limits the essentials but contains optimizations for common DSP operations such as multiply accumulate (MAC), filtering, matrix operations, and fast Fourier transform (FFT). DSPs are commonly sold in two variants: optimized for power efficiency and optimized for performance; and are used in applications such as base stations and edge devices. Power consumption is also minimized by reducing the silicon footprint that would be in GPPs sophisticated cache and peripheral subsystems.
Although DSPs have been commonly deployed in the past decades, they serve as a middle ground between GPPs and FPGAs with regard to flexibility, performance and efficiency. Field-programmable gate array (FPGA) offers more parallelism, higher data rates, and better power efficiency than DSP, but is not well suited for control applications, such as implementing the network/protocol stack. This is due to the limited amount of memory in FPGA and for this reason it is often paired with GPP.
A FPGA is an array of programmable hardware logic blocks, such as general logic, memory, and multiplier blocks, that are wired together via a reconfigurable interconnect to generate an integrated circuit for several designs with the ability to quickly switch between configurations. FPGA configurations are programmed using hardware description language (HDL), which is also used for ASIC. Because a FPGA functionality is defined at the hardware level and can be implemented using parallelism, it can perform DSP algorithms at much higher rates than DSPs and GPPs. FPGA consumes more power and requires more space than ASICs but provides more programmability and flexibility than ASIC. A big consideration for using FPGAs for SDR is the domain knowledge requirement for developers. Developing on FPGAs can be time consuming and require an extensive understanding of the target hardware architecture.
When the system requirements exceed the capabilities of a singular processor type, a comprehensive solution may include a combination of the above processor types. A common processing architecture in the defense industry comprises of a FPGA, DSP, and GPP. In this paradigm, the FPGA is responsible for high data rate signal processing tasks, such as sampling and filtering, the DSP handles demodulation and protocol, and the GPP performs control-related tasks, such as the user interface and algorithmic processing. Implementing such a system can become a complex management task to coordinate the processing flow; however, the system can benefit greatly by optimizing overall performance based on the strength of each processor.
For space applications, SDR has unique challenges such as extreme radiation and temperature environment, autonomous operational requirements, limitations on size, weight and power (SWAP), and the need for reduced development time and increased reliability in agile prototyping. In this section, recent applications of software defined radio to satellite, as well as the current status of radiation-hardened SDR components, are presented.
Recognizing early on that a standard and open architecture is needed to encourage reuse and portability of software, NASA developed an open architecture specification for space and ground SDRs called the Space Telecommunications Radio System (STRS) [12]. From this standard, several compliant systems have been built and demonstrated in radios on the International Space Station (ISS) and several ground stations. It was also the intention of NASA that the STRS architecture should be used as baseline for many future NASA space communications technologies.
In a nutshell, the STRS standard consists of hardware, configurable hardware design, and software architectures with accompanying description, guidance, and requirements. The three main hardware functionalities are connected by the Hardware Interface Description10 (HID) and described and shown in Figure 15 below:
General processing module (GPM) consists of the general-purpose processor; appropriate memory; spacecraft bus (e.g., MILSTD-1553, Space Wire); interconnection bus (e.g., PCI); and the components to support the configuration of the radio.
Signal processing module (SPM) where signal processing is used to handle the transformation of digital signals into data packets. Its components include ASICs, FPGAs, DSPs, memory, and connection fabric/bus (e.g., PCI, flex-fabric).
RF module (RFM) handles the RF functionality to transmit/receive the appropriate digital signal. Its components include RF switches, digital-to-analog converter (DAC), analog-to-digital converter (ADC), diplexer, filters, low-noise amplifiers (LNAs), and power amplifiers (PAs).
NASA STRS’ three main hardware functionalities.
In STRS terminology, software includes source code, object code, executables, etc. implemented on a processor. As shown in Figure 16, the STRS software architecture uses three primary interfaces: the STRS APIs, STRS hardware abstraction layer11 (HAL) specification, and the Portable Operating System Interface12 (POSIX®). The STRS APIs provide the interfaces that allow applications to be instantiated and use platform services.
STRS software architecture layers.
Configurable hardware designs are the items and designs, such as hardware description language (HDL) source, loadable files, data tables, etc., implemented in a configurable hardware device such as a FPGA.
STRS encourages the development of applications that are modular, portable, reconfigurable, and reusable. The STRS software, configurable hardware design, metadata, documentation for STRS applications, STRS devices, and operating environments (OEs) are submitted to NASA STRS Application Repository to allow applications to be reused in the future with appropriate release agreements.
CubeSats13 are increasingly popular spacecraft platforms for mission-oriented experiments that can be accomplished via quick prototyping and launches [13, 14, 15]. This short development timeline is due to the use of commercial-off-the-shelf (COTS) technology that typically has limited resilience to the space environment. Therefore, CubeSat usage has largely been limited to experiments or applications where high availability is not the main objective.
In general, SDR technology will allow for on-orbit flexibility via reconfigurability of data management, protocols, multiple access methods, waveforms, and data protection. SDR processing requirements are inherently scaled to the application. The availability of modular, high-performance sequential and parallel processors that are resilient to radiation upsets allows the tailoring of hardware architectures to the application and to the CubeSat platform. This is especially suitable for missions that require the flexibility to support multiple TT&C and mission data from multiple satellites and ground stations [5, 6, 7].
Given the provided mission flexibility, implementing an SDR on a CubeSat could significantly increase the required processing capacity and thus the size, weight, power and cost (SWAP-C) of the SDR implementation. Consequently, most current CubeSat SDR design and implementation are still customized depending on the mission requirements. In [10], some of the current COTS SDR hardware and software platforms such as GomSpace, Ettus Research USRP, EPIQ Solutions, Lime Microsystems, FunCube, and RTL SDR are described and categorized in decreasing cost and mass to illustrate the heterogeneous nature of SDR in CubeSat applications. Also described are a number of space and ground segment systems built to be (or have been) launched using these COTS SDRs or components thereof. What would be needed is a standard for CubeSat SDR similar to NASA STRS to ensure that hardware and software reuse can be incorporated into future CubeSat developments.
A pioneering commercial application of SDR in space is the HawkEye 360 (HE360) system [16] that was launched on 3 December 2018. HE360 system consists of three identical spacecrafts and their primary payload is a SDR with custom RF front-end along with VHF Ku-band antennas. This Pathfinder mission14 was to enable onboard reception and geolocation of different types of terrestrial RF signals using signal processing technique to combine received data from all three payloads15.
One commercial application of this mission is the detection and geolocation of a maritime vessel’s automatic identification system (AIS), which broadcasts the locations generated by GPS-enabled receiver. The locations generated by AIS can be disabled or spoofed, therefore not reliable. Another application would be to allow regulators, telecommunications companies, and broadcasters to globally monitor spectrum usage and identify areas of interference. The system can also be used to help large area search and rescue operations by quickly locating activated emergency beacons.
The SDR developed for the Pathfinder payload consists of an embedded processor system and three baseband processors. The baseband processor was built around the Analog Devices 9361 (AD9361) System on Chip (SoC) product, which is a highly integrated RF transceiver that combines high-speed ADCs and DACs, RF amplifiers, filtering, switching plus more. The HE360 payload supported up to three receiver channels (one AD9361 per channel) that can be simultaneously processed on separate frequencies. In addition, the signal processing subsystem takes advantage of open-source software and firmware code to allow system development to proceed without knowing the final space hardware. GNURadio16 was selected for being a free and open-source toolkit for SDR and widely used in small space projects for ground software processing.
In space, most semiconductor electronic components are susceptible to radiation damage, thus radiation-hardened (or rad-hard) components are required and normally developed based on their COTS equivalents with variations in design and manufacturing17 to reduce the susceptibility to radiation. Consequently, rad-hard components tend to lag behind most recent COTS developments. Depending on mission requirements, rad-hard products are typically selected and tested using popular metrics such as total ionizing dose18 (TID), and single event effects19 (SEEs).
Per US DoD MIL-PRF-38535 J standard [18], an ideal integrated circuit for space applications is the qualified manufacturing line20 (QML) Class V with radiation hardness assurance21 (RHA) level identified in the part specification. From the perspective of payload designer and developer, only Class V is space quality and should be the main factor for selecting SDR hardware components.
The FPGA is perhaps the most important component of an SDR and has a long history for manufactured QML class V parts where rad-hard Xilinx and Actel (now Microsemi) FPGAs were studied [19]. Currently, Xilinx is the major player for space-qualified QML level V products used in actual payloads with many more devices under development. The rad-hard DSP products also follow the QML process, with Texas Instrument (TI) currently taking the lead for in-flight payloads with many offerings in space-qualified RF components in addition to DSP. Similarly, space-qualified GPP follows the same QML path as FPGA and DSP, and the current on-flight rad-hard GPPs based on the following architecture are [20].
RISC PowerPC: RAD750, RAD5500.
RISC MIPS: RH-32, Mongoose-V, KOMDIV-32.
Motorola 68,000 Series: Coldfire M5208
ARM Microcontroller: Vorago VA10820
In the first section of this chapter, an overview of the satellite bus and payload subsystems are presented for command and data handling subsystem (C&DHS); communications subsystem (CS); electrical power subsystem (EPS); propulsion subsystem (PS); thermal control subsystem (TCS); attitude control subsystem (ACS) also known as guidance, navigation and control (GNC) subsystem; and structures and mechanics subsystem (S&MS). A significant portion is spent on describing the C&DHS and CS with much details on how they are related to other satellite subsystems for continuous operation.
There are distinctive functional separations between the satellite bus and payload that are discussed at a high level with some examples given; however, there are currently no existing standard on their interfaces due to legacy satellite design and development. Examples were given for mission-specific sensing and communications payloads, showing that pretty much all mission payloads are very customized in design in legacy systems.
The second section of this chapter covers software defined radio (SDR) as a new technology with an overview and how SDR is being applied to satellite design and development in both space and ground segments. There has been a NASA standard for SDR that has been used for traditional and large satellites and shown to have some advantages over non-SDR approach.
However, recent rapid developments of Small Satellites (SmallSats), which CubeSat is a subset of, have resulted in an explosion of SDR applications to build Pathfinder missions that can lead to successful follow-on projects. There remains to be a standard to be defined for SDR for this CubeSat application. Regardless, SDR is providing a path forward to a common framework that may enable a more generic building block for a future concept called Software Defined Satellite that will change missions based on a software upload.
Since SDR is becoming an important part of a satellite, radiation hardening of the relevant SDR components is described in some detail. The area is evolving slowly despite fast changing technology due to the additional design and manufacturing steps taken to ensure minimum effects of radiation on microelectronics. The selection of the appropriate rad-hard FPGA, DSP, and GPP components should be an important factor in design trade-offs when SDR is being considered for future missions.
The first author, Dr. Hung H. Nguyen, would like to express bountiful appreciation for his wife, Thuy Le Nguyen, for her constant support during this effort.
IntechOpen’s Academic Editors and Authors have received funding for their work through many well-known funders, including: the European Commission, Bill and Melinda Gates Foundation, Wellcome Trust, Chinese Academy of Sciences, Natural Science Foundation of China (NSFC), CGIAR Consortium of International Agricultural Research Centers, National Institute of Health (NIH), National Science Foundation (NSF), National Aeronautics and Space Administration (NASA), National Institute of Standards and Technology (NIST), German Research Foundation (DFG), Research Councils United Kingdom (RCUK), Oswaldo Cruz Foundation, Austrian Science Fund (FWF), Foundation for Science and Technology (FCT), Australian Research Council (ARC).
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