Preparation of an observation card to measure the developmental learning difficulties among primary school students in Sana’a City, Yemen

Developmental learning difficulties are among the prevalent exceptionalities school learners have today. In this regard, identification and placement are among the facilitators of later successful intervention for these groups of learners (WestOlatunji, Shure, Pringle, Adams, Lewis & Cholewa, 2010). However, there are not enough resources such as tools to measure the learners’ difficulties (Alim, Abdallah, Ramaroson, Sidikou & Van de Wiel, 2007) available. The tools, which objectively help a professional to identify a learner’s level of difficulty is an essential resource, however, they are scarce. With this study we aimed to develop an observation card to determine the prevalence of developmental learning difficulties among primary school students in Sana’a City, Yemen. A 24-item tool was used and analysed to test its psychometric properties. A total of 238 students with ages ranging from 6 to 13 years participated in the study. The findings of the study suggest the final formulation of the items to be included in the observation card that can measure the prevalence of this exceptionality through the use of observation scores. The observed raw score had been standardised by its deviation from the sample’s mean. Further, the findings reveal that there were statistically significant differences in the respondents’ level of difficulties in terms of their gender and grade. Recommendations of the study are presented in this article.


Introduction
At the policy development level, countries depend on human resources to improve their economy. Thus, they develop strategies and plans that are in line with individuals' abilities and qualifications to prepare and qualify them through an appropriate educational system. Like other countries, Yemen regards primary education as very important. The number of children who start school at the age of 6 has increased from 310,167 in 1991to 314,830 in 2000to 622,909 in 2008(Save the Children, 2016. Most countries are interested in identifying students with learning difficulties and conducting surveys to determine their level of developmental learning difficulties (DLDs) in order to take the necessary measures and to intervene to help these students to learn better (Cortiella & Horowitz, 2014).
In the United States of America (USA), as an example, the percentage of students with learning difficulties is 12% (Cortiella & Horowitz, 2014) whereas the number in the United Kingdom is about 21% (Emerson, Hatton, Robertson, Roberts, Baines, Evison & Glover, 2012).
Surveys to measure the prevalence of learning difficulties among students in the Arab world showed that 13 to 46% are suffering from these difficulties (Ahmad, 2015). Learning difficulties are very common among primary school students (Abosi, 2007), so they are in real need of care and attention since the learning difficulties could be recognised at this stage.
In 2013 the World Health Organization (WHO) stated that the number of Arabs with learning difficulties were over 53 million (Hadidi & Al Khateeb, 2015). With this estimation, it was important to refer to the efforts made by Arab countries like Kuwait and the Kingdom of Saudi Arabia. Kuwait, for instance, had the oldest and the largest centre, The Child Evaluation and Teaching Center, established in 1984, for the purpose of detecting students with learning difficulties and designing the appropriate programmes for these students (ALmenaye, 2009;Elbeheri, Everatt, Reid & Al Mannai, 2006;WHO, 2011). Likewise, Saudi Arabia created a programme at the King Saud University in 1992 to train teachers and familiarise them with learning difficulties. In 1995, a department was established by the General Secretarial of Special Education (GSSE) to manage and intensify the learning difficulties programmes in Saudi primary schools (Al-hano, 2006).
In a country like Yemen, with a high population density of 21 million of which about half are aged 15 or maybe less, no studies had been recorded to estimate the rates of learning difficulties in the country (Alyahri & Goodman, 2008).

Literature Review
Psychological and educational literature identify students with learning difficulties as those students who show differences between their expected performance (as measured with a mental capacity tests) (Van Luit & Toll, 2018;Visser, Korthagen & Schoonenboom, 2018) and their actual performance (as measured by achievement tests) in one or more academic areas due to difficulties in the basic psychological processes (perception, attention, solving problems, remembering) (Miciak, Taylor, Denton & Fletcher, 2015) and whether such difficulties occurred in the early stages (pre-school, primary school, preparatory school) or not.
In 1962 the American psychologist, Samuel Kirk, coined the term "learning disabilities" in a book on special education (Colker, 2011;Danforth, Slocum & Dunkle, 2010). After that, a conference was held in 1963 in which educators, psychologists, and parties interested in learning disabilities participated to discuss and investigate the difficulties of children suffering from mental retardation (Annamma, Ferri & Connor, 2018;Freedman & Ferri, 2017).
In 1983, Kirk illustrated that DLDs were considered to be one of the factors that explained the reason for low academic achievement, including disorders of memory efficiency, perception, attention, thinking, and language (Anderson, 2002). Consequently, such disorders lead to difficulties that impede academic progress as a result of an internal psychological or neurological process or a group of disorders that appear in the form of obvious disabilities in terms of acquiring reading, writing, spelling, and calculating skills (Keyes & Brandon, 2012;Thomas & Whitten, 2012).
It was important to note that the term "learning difficulties" was chosen rather than the term "learning disabilities." Learning difficulties could readily be alleviated through intensive educational intervention, while learning disabilities are lifelong and pervasive, and do not respond readily to intensive education intervention (Thomas & Whitten, 2012).
The causes of DLDs vary from student to student. There seems to be a great controversy on what the causes of DLDs are (Randall, 2006). Some scholars relate these difficulties to neurological factors while others relate them to environmental factors (Macdonald, 2010). McGuinness (2004) argues that students fail in school mainly because of environmental causes and not biological factors. This means that certain factors in the environment may cause developmental learning difficulty in some students. For instance, a lack of motivation at school or at home, or a lack of effective teaching methods could cause students to suffer from learning difficulties (Degener, 2016).
DLDs are related to brain functions and cognitive processes that students need for academic achievement such as sensory perception, hearing, thinking, language, and memory (Cortiella & Horowitz, 2014;Jacobs & Collair, 2017). These difficulties are due to functional tracings in the central nervous system. These can be divided into initial difficulties, which were related to the processes of attention, perception, memory, and secondary difficulties such as thinking, understanding, and oral language (Coladarci, 1992; López-Villalobos, Andrés-De Llano, López-Sánchez, Rodríguez-Molinero, Garrido-Redondo, Martínez-Rivera & Sacristán-Martín, 2015).
The following is an explanation of primary and secondary DLDs.

1) Primary DLDs:
• Attention difficulties. One of the factors that can have a substantial impact on a student's academic performance and his degree of motivation is attention disorder, which affects the student's ability to focus and control his behaviour. These two factors contribute most significantly to a child's daily progress and performance in the classroom. Three to 15% of students have attention difficulties; 50% of students are at risk and may suffer from school failure (Carpenter, Loo, Yang, Dang & Smalley, 2009;Perold, Louw & Kleynhans, 2010;Topkin, Roman & Mwaba, 2015). • Perception difficulties. These include impaired visual motor coordination, spatial and other cognitive factors (Ahmad, 2015). • Memory difficulties. The inability to recover what has been seen, heard, practiced or trained. Children with obvious visual or auditory problems may have trouble learning to read, spell, write and calculate (Gomez, Hafetz & Gomez, 2013). 2) Secondary DLDs: • Difficulties of thinking. This involves problems in mental processes including judgment, comparison, computation, verification, evaluation, reasoning, critical thinking, problem solving and decision-making (Moreno & Pelegrina del Rio, 2011).
• Verbal language difficulties. Language difficulties involve difficulty in understanding language and verbally expressing ideas (Mwanamukubi, 2013). Mahin, Haghdoost, Afsaneh and Hamideh (2014) investigated the prevalence of learning difficulties among primary school students. The study sample consisted of 793 primary students. A questionnaire of 40 items was developed. The results indicate that there was a significant difference between males and females. The research results of a study conducted by Abolhassanzadeh, Shafiee-Kandjani, Vaziri, Molavi, Sadeghi-Movahhed, Noorazar and Basharpoor (2016) to investigate the prevalence and risk factors of attention deficit hyperactivity disorder (ADHD) among elementary school students indicate that there was a relatively high prevalence of ADHD. Abdullah and Shehab (2013) studied the identifying non-adaptive behaviours of students with learning difficulties at the basic primary stage. The sample consisted of 303 students with learning difficulties and ordinary students. The study used the Walker measure. Means, t-tests and ANOVA were used for statistical analysis. The study found that there were statistically significant differences in the nonadaptive behaviour in favour of students with learning difficulties. There were differences in favour of male students. There were differences in favour of the first grade, fifth grade, and fourth grade students respectively.
Children in developing countries such as Yemen face many barriers to accessing better quality of education and cannot learn the basics of subjects like mathematics and language because of untrained teachers and a lack of learning tools (HLSP S.L., 2005).
Several studies have shown that more funds should be made available for the training of teachers, provision of tools to detect DLDs, and preparation of resource rooms with appropriate educational aids in order to help the large numbers of students suffering from DLDs to overcome those difficulties (O'Connor & Geiger 2009;Zimmerman & Smit, 2014).
Despite many studies on DLD, to the best of our knowledge, no independent research exists for standardisation studies which have established psychometric properties and utility as part of a comprehensive assessment or as a predictor of DLD.
Further evidence from teacher observation may contribute to a comprehensive screening, assessment, and prediction of DLD as described above because the teacher's observation is based on his or her experiences and direct interactions with students at different timesunlike tests which are performed at specific time segments.
Thus, if it is shown that the teacher's observation of students is adequate, then students can be accurately diagnosed and supported until standardised tools become available. This need is even more pressing in Sana'a City, where standardised tests for the assessment of students are scarce.
This makes a clear case for Sana'a City schools to secure a standardised tool for the assessment of students. In line with this, it was necessary to develop a measure which functions as an observation card to determine the DLD of the students and prepare programmes by specialists to overcome these difficulties.

Research Objectives
The objective of this study was to develop a diagnostic tool for DLD which would standardise student's raw scores during the evaluation process. Furthermore, it would also assist in standardising student scores based on the arithmetic mean of peers and analysing the degree of DLD according to gender and grade. This tool will further assist us to determine the levels of DLD among primary school students.

Methodology
The main focus of the study was to prepare an observation card to measure the DLD of students. The psychometric method was used through which the determined observation card was applied in this study. This design was deemed appropriate for this study because it enabled us to obtain information relating to the nature of DLD among primary school students in Sana'a City and determining the methods to assist the educators with the diagnosis of DLD.

Participants
The sample used in this study was chosen on the basis of official statistics which indicated that only five public schools in Sana'a City had resource rooms (Central Statistical Organization, 2016) serving a total number of 2,113 students (1,095 males and 1,018 females) who performed poorly. The five schools were from five educational districts according to the educational system in Yementhree schools for males and two for females. Only 15 teachers showed interest and volunteered to observe students under their supervision. Taking the variables of gender, age and grade into consideration, 238 students (120 males and 118 females) (11%) between the ages of 6 and 13 years from six different grades (M = 9.327, SD = 1.863) were involved in this study in the 2017/2018 academic year.

Measure
Based on a number of previous studies that measured the levels of DLDs among primary school students, the measured items were adapted to correspond to the Yemeni environment and included more items derived from literature on DLD (The Pupil Rating Scale) developed by Helmer Myklebust in the USA in 1981 (Rasugu, 2010). Myklebust's instrument is a behavioural checklist for classroom teachers to rate suspected students with cognitive and psychological abilities (e.g., attention, memory, perception, thinking, and verbal language) (Gregg, 2010;Pisoni, Kronenberger, Chandramouli & Conway, 2016;Rasugu, 2010).
The tool was developed in Arabic as it is the native language of the participants. The tool consisted of 24 items as initial formulation.
The observation card was presented to a panel of seven specialists and experts in the fields of psychology and education to confirm the face validity of the tool. After implementing the amendments proposed by the panel, it was agreed to modify, replace and improve some statements (e.g., "Learner's difficulty to complete the work assigned to him/her" instead of "Student doesn't do his homework"; "Learner's difficulty to use their hands" instead of "Student has shaky hands"; "Learner's difficulty to remember the word they heard before" instead of "Student's ability to memorise and recite words is extremely weak"; "Learner's difficulty to follow the teacher during the explanation" instead of "Student's attention is distracted by playing instead of listening to the teacher"; "Learner lacks the ability to distinguish between directions (right, left, up, down)" instead of "Student always mixes directions and walks to the opposite side").
We conducted a pilot test using the observation card with 30 students to verify the psychometric properties (validity and reliability) thereof. The results show Cronbach's Alpha of (α) = 0.771 and the square root of α = = 0.878 (Smits, Van der Ark & Conijn, 2018). As specified by Heale and Twycross (2015), the reliability and validity values were acceptable. The observation card included 24 items in two dimensions: Primary learning difficulties (attention, memory, and perception) and secondary developmental difficulties (thinking and verbal language).
After an observation of the student's behaviour and achievement, the teachers specified the student's level of agreement with the items on the scorecard in accordance with a five-level Likert scale (Always applicable, Almost applicable, Sometimes applicable, Seldom applicable and Not applicable at all) used in the observation card.

Statistical Analysis
Validity of the scale was established by using Pearson's correlation coefficient to determine the correlation between each item and the overall observation tool. The items in the observation card are presented in Table 1: items 1 to 9 for attention difficulties, items 10 to 15 for memory difficulties, items 16 to 18 for perception difficulties, items 19 to 22 for thinking difficulties and items 23 and 24 for verbal language difficulties. The validity of the observation card is also presented in Table 1, and it is clear that all the items were statistically significant at 0.01. The highest correlation was with the third item (0.869) (Learner's difficulty to complete the work assigned to him/her), while the lowest correlation was with the sixth item (0.549) (Learner has difficulty to use his/her hands). According to Heale and Twycross (2015), a correlation coefficient of less than 0.3 signifies a weak correlation, 0.3 to 0.5 moderate, and greater than 0.5, a strong correlation. Learner frequently moves from one task to another or from one job to another. 0.735** 0.00 10 Learner has difficulty to distinguish sound stimuli. 0.647** 0.00 11 Learner has difficulty to remember. 0.779** 0.00 12 Learner has difficulty to remember the alphabet or numbers that he/she has heard . Learner has difficulty to connect facts and ideas. 0.737** 0.00 Note. **ρ ≤ 0.01. Criterion-related validity was also investigated to determine the correlation between a student's achievement score for the last year (as a criterion) and the observation card's score (of the current scale). The negative sign indicates that the increase of learning difficulties has led to the lowest educational achievement (see Table 2). In order to determine the reliability, Cronbach's Alpha (α) and the Guttman Split-half coefficients were employed to assess the reliability of the total scale. The values were 0.919 and 0.881 respectively (see Table 3), which indicated a suitable reliability for this measure. These results were in line with the findings of Cho and Kim (2015).

Results
The level of DLD among students had been determined by calculating the range, Range = maximum(xi )minimum(xi) (CK-12 Foundation, 2009), where (xi) represents the set of values 114 -24 = 90. The observation card contained five options. The range had been divided into five categories to determine the length of the category: (L) = 90/5 = 18 As presented in Table 4, 76 of 238 students (32%) had a moderate level of DLD, 72 students (30%) had a low level of DLD, while 46 students (19%) had a very low level of DLD. Thirty-two students (14%) had a high level of DLD and only 12 students (5%) were suffering from a very high level of DLDs. From the observation card scores it is clear that attention as a primary developmental learning difficulty was the most common among the primary school students observed (M = 21.48, SD = 8.89, variance = 79.03 and range = 35), followed by memory difficulties (M = 14.17, SD = 6.07, variance = 36.85 and range = 24) and perception difficulties (M = 7.17, SD = 3.57, variance = 12.75 and range = 12). Thinking as a secondary developmental learning difficulty was the most common among the primary school students observed (M = 8.53, SD = 4.02, variance = 16.16 and range = 16) while verbal language were the least common (M = 5.37, SD = 2.53, variance = 6.41 and range = 8). As shown in Table 5, the values of the total arithmetic mean, standard deviation, variation and the range were used to find the z-score, t-score and scaled score for each raw score where the students' raw scores were compared to the t-score and scaled score. In order to standardise the raw score of DLD, the following equations were used: Standard score (z-score) = raw scoremean / standard deviation, transformed score (t-score) = 50+ 10Z and scaled score = 10 + 3Z To determine the observation scores of the students, the transformed score (t-score) and scaled score for each raw score were calculated. The raw score was classified under the transformed score (tscore). To remove the decimals, we used the transformed score (t-score) instead of the standard score (z-score) (Test Partnership, 2017). We also used the scaled score to standardise the observation score of the students (see Table 6) and standardise the raw score according to the grades (Standards and Testing Agency, 2016) (see Table 11). By comparing the means that examined whether students' DLD differed by gender, it was indicated that male students had the highest mean score (M = 60.65, SD = 24.18) while female students scored (M = 52.73, SD = 21.41) (see Table  7).  Table 8 shows the arithmetic means differences according to grade. Grade 1 students scored the highest arithmetic mean (M = 61.45, SD = 29.94), while Grade 6 students scored the lowest arithmetic mean (M = 51.09, SD = 19.47).  Figure 1 shows the arithmetic means differences according to grade. Grade 1 students scored the highest arithmetic mean, while Grade 6 students scored the lowest arithmetic mean. There was a difference in the mean score between grades.

Figure 1 Differences in developmental learning difficulties for grades
A comparison of DLD between the six grades illustrated that there were no significant differences between Grades 1 and 2 (ρ = 0.552) and Grades 1 and 3 students (ρ = 0.101). However, there were significant differences between Grades 1 and 4 (ρ = 0.053) and Grades 5 (ρ = 0.049) and 6 students (ρ = 0.041) (see Table 9). A one-way ANOVA analysis was conducted to find whether the differences seen among arithmetic means in Table 8 were statistically significant. The results of the analysis are presented in Table 10 and shows that there was a significant difference based on the grade F-value 2.267, ρ = 0.051 at the 0.05 level. For a fair evaluation, the observation of the DLD for each student was compared to the mean of the same grade, because it was not realistic to compare the general mean for all grades as there were significant statistical differences between grades.
The mean and deviation for each grade's z-score, t-score and scaled score for each raw score had been calculated depending on the arithmetic mean and the standard deviation (see Table 8) and as illustrated in Table 11 and Appendix A. In order to compare the means and to classify the difficulties for each grade, each grade was standardised separately as shown in Table 11 and Appendix A. We observed the degree of DLD for students as follows: For Grade 1 students the deviation of z-score on the negative side was -1.251, t-score = 37, scaled score = 6 and on the positive side +1.588, t-score = 66, scaled score = 15. For Grade 2 students the deviation on the negative side was -1.515, t-score = 35, scaled score = 6 and on the positive side 2.166, t-score = 72, scaled score = 16. For Grade 3 students the deviation on the negative side was -1.461, t-score = 35, scaled score = 6 and on the positive side 1.647, t-score = 66, scaled score = 15. For Grade 4 students the deviation on the negative side was -1.313, t-score = 37, scaled score = 6 and in the positive side 1.928, t-score = 69, scaled score = 16. For Grade 5 students the deviation on the negative side was -2.187, t-score = 28, scaled score = 3 and on the positive side 2.000, t-score = 70, scaled score = 16. For Grade 6 students the deviation on the negative side was -1.391, t-score = 36, scaled score = 6 and on the positive side 2.512, t-score = 75, scaled score = 17. Scaled scores are standard scores with a mean of 10 points; scaled scores also have a standard deviation of three points (Von Davier, 2011). Regarding the tested scaled score, the values 7 and below are classified as below average, values 8 to 12 are classified as average and values 13 and above are classified as above average (Rubin, A 2009).

Discussion
In this study we calculated the psychometric properties of the scale (validity and reliability) to be practical in assisting specialists to evaluate the prevalence of DLD among primary school students. The scale's validity analyses used the requisite content and criterion of the observation card. The value -0.636 indicated that academic achievement tends to fall with increasing DLD. The reliability calculated using Cronbach's Alpha coefficient (α) and Guttman's Split-half with the values of 0.919 and 0.881 respectively, indicated high reliability for the observation card (Cho & Kim, 2015;Heale & Twycross, 2015).
The evidence in the literature review suggests that developmental learning difficulty is one of the basic difficulties that many students suffer from (Angelka & Goran, 2018;Rubin, IL, Merrick, Greydanus & Patel, 2016).
DLDs are considered to be one of the factors responsible for academic difficulties later on in life and hinders the child's academic progress (Jacobs & Collair, 2017;Kavale, Kauffman, Bachmeier & LeFever, 2008). The difficulty prevalence rates reported by countries in a study of the Economic and Social Commission For Western Asia ([ESCWA], 2014), were as follows: 0.6% in Egypt, 4.8% in the Sudan and 1.9% in Yemen.
In our study, to investigate the prevalence of DLD among primary school students and analysis of socio-demographic characteristics, 238 students were tested of which 76 (32%) students represented with a moderate level of DLD. This prevalence can be considered low when compared with other studies (Dhanda & Jagawat, 2013;Dilshad, 2006). Mazzocco and Myers (2003) report that about 6% of primary students had different types of learning difficulties. The explanations for these differences might be in the use of different measurement instruments. We did not use a single instrument to estimate learning difficulties. Furthermore, we found that attention difficulties were more prevalent than perception, memory, thinking and verbal language difficulties. Abolhassanzadeh et al. (2016) and Bener, Al Qahtani and Abdelaal (2006) also found that attention was one of the most prevalent psychiatric disorders among children and adolescents, which may lead to negative consequences such as dysfunction in education, personal, and social relationships. Weiss and Hechitman (1993) report that attention difficulty is a chronic, debilitating disorder that may affect many aspects of an individual's life, including academic difficulties, social skills problems, and disturbance in parent-child relationships (Bener et al., 2006).
The findings also indicate that the rate of prevalence of DLD among male students was more than among female students. Gender was a contradictable variable in the prevalence of learning difficulties. Researchers say that the reason for that was due to the psychological differences. Lerner (2000) and Rasugu (2010), explain that due to biological causes, males may be more vulnerable to learning difficulties due to cultural factors (i.e., males tend to exhibit more disruptive behaviour that is troublesome to adults), and expectation pressures for success in school, which may be greater for males than for females. The studies of Dilshad (2006) and Mahin et al. (2014) showed similar results.
In addition, the findings of our study revealed that there were significant differences according to the grade, in which Grade 1 students scored the highest arithmetic mean. These results can be clarified as follows: DLDs are directly affected by age. Therefore, when growing up, the abilities to focus, perceive and think increase. These findings are in agreement with the findings of Ameer and Singh (2013) who found that students in higher grades performed better than students in lower grades. But in a study by Talepasand and Vahed (2012), prevalence of difficulties did not differ significantly by grade.

Conclusion
In this study we developed the observation card's psychometric properties to assist educationists responsible for developing therapeutic programmes that help students with learning difficulties. The findings reveal a tangible correlation between the observation card's overall value and each item's value. Criterion validity analysis proved a sizeable correlation between academic achievement levels and DLDs. The Guttman Split-half and Cronbach's Alpha coefficients were used for assessing overall reliability of this scale.
The results show that around 76 of the 238 students were vulnerable to moderate DLDs. DLD was identified as the most prevalent learning difficulty among students at primary school level. Results varied significantly based on gender, as males scored the highest arithmetic means on average. The grade level also displayed a similar effect, with students from the lowest grade level (Grade 1) observed to have scored the highest arithmetic means.
With this study we shed light on developmental learning difficulty programmes necessary to counter gender and grade level related performance issues. Similarly, our study lends credence to the necessity for resource rooms in primary schools to evaluate students with learning difficulties and to help specialists and teachers implement the programmes according to the students' needs in order to overcome learning difficulties, and to enable these students to keep up with their peers in terms of academic development.
In conclusion, we recommend the creation of special programmes for children with DLDs, taking into consideration the different categories and variables covered in this study. Additionally, we also suggest that future studies should consider expanding the constructs for measuring the characteristics of the students suffering from DLDs.