In order to ascertain how accurately teachers prescribe read-aloud accommodations for math examinations and to create a profile of kids who benefit from such accommodations, this article details an investigation conducted among special education teachers and students. An achievement test in mathematics was given to elementary and middle school students in eight states, including general and special education. When it came to identifying which pupils might benefit from the accommodation, teachers were no more successful than chance. Pretest reading and math accomplishment results were utilized in supplemental analyses to try and create a profile of kids who preferred one or the other format. Student profiles did not always correspond with the results of accommodations.
Research on testing accommodations for children with disabilities is receiving more attention as a result of recent demands to include all students in large-scale testing. Despite this curiosity, opinions on when accommodations are warranted are divided. The verbatim oral explanation of mathematical problems is a frequently employed accommodation for pupils with inadequate reading proficiency. There is little evidence to support the claim that teachers are ineffective at making this accommodation. By investigating the accuracy of instructors’ assessments of the efficacy of read-aloud accommodations for students with disabilities, the current paper aims to contribute empirical evidence to the area. Additionally, we try to create a profile of students who could profit from this kind of housing.
ESSENTIAL DECISIONS ABOUT ACCOMODATION
A testing accommodation is any modification made to the format of the test or response that does not modify the construct being tested. The repercussions of bad judgments make it clear how important accommodations are. For instance, some forms of accommodations allow particular students to take tests that they would not otherwise be able to. The practice of reading math test items aloud to pupils who struggle with reading is one example of this. According to a number of studies, this method helps kids who struggle with reading differently than it does readers who are more proficient. However, in order for this accommodation to be effective, kids who would benefit must be accurately identified by special education teachers, members of the individualized education program (IEP) team, and others involved in assessment decisions. The study discussed in this article makes an effort to measure this effectiveness.
Some students may suffer if this accommodation is misused. According to a sizable portion of educators, reading test material out loud to children can be annoying and distracting for certain pupils. This hypothesis is supported by certain empirical data. In contrast to when items were read aloud to them, we discovered that more proficient readers did better on a regular administration of a mathematics examination. Similar outcomes were observed with certain students on a read-aloud accommodation of lengthy text segments. Although kids have different capacities for listening, remembering, and creating auditory vs visual schema, the reasons for this are unclear.
Additionally, some students may find oral presentations’ background noise disturbing if they prefer to read the material on their own. Research indicates that reading aloud to proficient readers reduces their comprehension. Teachers frequently over recommend accommodations for students with disabilities. This technique raises the possibility that an unnecessary accommodation would negatively impact students.
Another benefit of limiting the use of accommodations to kids who will benefit from them is that it saves money. The time and financial costs of administering nonstandard tests are usually higher. Districts must organize alternate testing locations and times for students who need this kind of accommodation, as well as train staff in test administration techniques, when test items are presented orally. Social implications swiftly enter the realm of measurement validity when states and schools are confronted with limited resources.
Lastly, the validity of conclusions drawn from test results is impacted by accommodation decisions. Although state-by-state policies differ, several modifications to test administration practices may cause scores to be separated from scores obtained under typical testing circumstances. Important policy decisions may be made based on insufficient knowledge if the findings of a sizable portion of students are excluded from data analysis due to needless changes made to their testing settings. Furthermore, because disaggregated scores may indicate different things than scores achieved under normal circumstances, individual children and their teachers are deprived of important comparative achievement data in these situations.
TEACHER EFFECTIVENESS AT ASSIGNING ACCOMMODATIONS
The accuracy of teachers’ assessments of the efficacy of read-aloud accommodations for math tests has been the subject of some new research. These provide contradictory outcomes. However, we discovered that when it came to identifying which children would gain from the accommodation, teachers performed no better than chance.
A group of general and special education teachers were given a copy of a standardized mathematics test, and they were asked to determine which of their pupils would benefit from having the items read aloud. This test was then given to the students twice, once with the items read aloud and once in the regular format. According to the results, students whose teachers had suggested an accommodation profited more from the read-aloud format than students whose teachers had not on concept/application problems with low reading demands. However, both recommended and nonrecommended students gained equally from the accommodation on problem-solving tasks that required extensive reading.
This latter study indicated that students could be sorted more efficiently for both concepts/applications and problem-solving tasks when information about the effectiveness of prior adjustments was supplied. Increasing the amount of information available to decision makers is the foundation of both systems.
STUDENT PROFILES
Regarding which kids benefit from read-aloud accommodations for arithmetic assessments, only broad information is available. Because different reference populations were employed in earlier studies, it is challenging to draw specific conclusions. These included low-skilled readers, children with reading and math skills combinations, students with special education needs, students with learning impairments (LDs), and students with reading IEPs. The fact that many students in the target groups did not benefit while many students in the control groups did complicates current grouping techniques.
Some hints about whether pupils may qualify for oral reading accommodations are provided by a few studies. We discovered that whereas competent readers and low readers with bad arithmetic skills did not benefit from a reading accommodation, sixth-grade pupils with low reading competency but average or above math skills did. According to some research, fourth-grade students with LD who performed better in math gained more from a read-aloud accommodation than their less successful peers. For fourth-grade students with impairments we discovered that there were substantial correlations between reading achievement and the impacts of a read-aloud accommodation, but not for other students. These results imply that there might be a math threshold below which pupils lack the skills required to benefit from the accommodation, as well as a reading proficiency threshold over which accommodations are no longer beneficial.
To sum up, testing accommodations are a useful instrument for guaranteeing the validity and fairness of test findings and their interpretations. However, improper use or denial of accommodations can raise expenses, invalidate test results, and deprive teachers and students of important data. It seems that teachers are frequently ineffective at identifying which pupils would benefit from having arithmetic problems read aloud. This effectiveness could be raised by organized systems. However, it seems that students’ understanding of their reading and arithmetic competence levels may be helpful in allocating adjustments in the absence of this kind of information regarding prior accommodations. In order to verify the findings of earlier studies, we first looked at how well teachers
predicted the effectiveness of accommodations for children with disabilities across four grade levels. In order to ascertain whether patterns of competency in these fundamental skill areas could be utilized to create a profile of students who would likely benefit from read-aloud accommodations, we next looked at the reading and math pretest accomplishment scores of the students.
METHOD
Eight states’ state departments of education were asked to find districts interested in taking part in an accommodations experiment as part of a wider study. One elementary school and one middle school were then found in each state. Two general education classrooms with 25–30 pupils and a common grade level (eighth or seventh grade in middle school or fourth or fifth grade in elementary school) were allowed to participate from each school. Additionally, all children at the selected grade level in each school who were receiving special education assistance and for whom extensive mathematics testing was a component of their academic program were included. Only these latter students were included in data analysis for the current study, unless otherwise indicated.
SUBJECTS
Students. 1,218 of the 1,550 students that participated in the project finished all the tasks. 245 kids enrolled in special education services had their primary data analyzed. It was determined that more than 70% of these pupils had learning difficulties. Mental retardation (5%), severe emotional disturbance (5%), and speech or language impairments (8%), in that order, were the next most prevalent disability. Males were 63% more numerous than females (37%). White students made up 59% of the student body, followed by Black students (28%), and Hispanic students (7%).
Educators. The teachers who taught mathematics to the kids mentioned above were included in this study. This was a general education teacher in some instances and a special education teacher in others. When students received instruction in more than one location, the person or people who knew the most about the students’ arithmetic achievement and skill levels filled out the survey.
If special education and general education teachers had different perspectives on a student’s ability, they may work together to create the survey questionnaire for that kid. It was impossible to pinpoint the precise identify of the teacher who answered any given survey question because of the way the data was collected. However, the 245 pupils who were the subject of the study were known to have come from 61 different classrooms.
MEASURE
Math Proficiency. A secured pool of roughly 100 items from a participating state’s seventh-grade item bank was used to generate two 30-question, multiple-choice mathematics achievement tests (Form A and Form B). The remaining seven states’ department of education officials examined each item to make sure it aligned with their state’s curriculum.
Items that used topics not included in the seventh-grade curricula of any state were removed from the pool. Based on data from field testing in the home state, the 30-item tests were matched for both content and difficulty. Algebraic relationships, measurement, statistics and probability, and geometry were among the many topics covered in each test.
PROCEDURES
The items had four answer choices and word problems ranging from seven to forty-five words. There were no simple calculation difficulties. The total number of successfully answered questions determined a student’s score on each version. All participants in the seventh and eighth grades took these assessments.
Two versions of each form (A and B) were produced. The first used a standard structure, with multiple things per page in a test booklet that had written items. Additionally, a movie was made for each test form that displayed the problem’s text on one part of the screen and the face of an actor reading each item on the other. This style came with a test booklet that had one item on each of the two facing pages. Students bubbled their responses on a different answer sheet for both versions.
A beginning pool of roughly 100 things selected from the fourth-grade item bank in the same state underwent the same process. All primary school pupils took the two resulting tests. The domains covered were the same as those previously mentioned. These tests have from 7 and 69 words per item, including response choices.
Ratings of teachers. The relevant teacher (as previously mentioned) filled out a survey for each student, rating their reading and arithmetic skills on a 5-point Likert scale from extremely poor proficiency to very high proficiency. “How important is the accommodation (video version) for this student in generating successful performance?” was another question asked in the poll.
Test of Basic Math Skills. Every student took a math skills test. 16 of the 21 items on this middle school test were basic skills computations that included addition, subtraction, multiplication, and division of whole numbers, fractions, and decimals. Three tasks required converting fractions, decimals, and percentages into various formats. The last two tasks were one-step word problems with 20 words or fewer. Every item was a response to production. The total number of correct answers on this test and a 60-item multiple-choice problem-solving test that was a part of a southwestern state’s statewide math assessment program showed a correlation of .75 in a prior field test that involved 240 middle school students.
Students in the fourth and fifth grades took a math abilities test that included 17 addition, subtraction, multiplication, and division problems involving fractions and whole integers. Students had to convert or add units of measure for two more problems that used fewer than seven words. This activity and the 60-item elementary version of the standardized math achievement exam utilized in this study had a correlation of .60 in a field test. Both the primary and middle school versions of this test prohibited the use of calculators.
Maze reading. Reading proficiency was assessed using two labyrinth tasks: one for elementary school pupils and one for middle schoolers. These included roughly 200-word paragraphs, 25 of which had blank spaces in them. Students were instructed to choose the deleted word from five options for each blank. Words deemed significant to the plot were selected, in contrast to standard maze puzzles that eliminate every nth word. These were nouns, verbs, adjectives, or adverbs in every instance. According to earlier field studies, there were connections between these mazes and the overall results of 60-item reading comprehension exams that were utilized as part of a statewide assessment program of .68 (elementary) and .76 (middle school). Correlation coefficients between the math problems and the labyrinth in the current study varied from .41 to .46 in the middle school and from .55 to .60 in the primary school.
METHODS
Classrooms of pupils in elementary and middle school were split into two groups at random. Each of the test’s forms (A and B) was administered to both groups one to four days apart. Form B was taken in video format, and Form A was taken in conventional format by Group 1. Form B was taken in conventional format, and Form A was taken in video format by Group 2. The administration order (Forms A and B) was counterbalanced within each group. Every test was given in a group.
Students were handed a test booklet and told to read each item, select the best response from the list of options, and finish the test at their own pace when taking the normal edition. There was no time restriction. Students had two options for the video presentation: either follow along with the reader as they silently read from their booklet, or observe and listen to the contents read and shown on the video monitor.
The visual display was managed by test administrators. Depending on the type of difficulty, the video was paused for a predefined amount of time after each item had finished being read. Students worked on each problem’s solution during this time, marking their selections. Students were told to turn the page after the allotted pause, at which point another difficulty appeared. Students were given textbooks so they may review material or scan it for important details. Pupils were told not to flip through their booklets until the next issue was displayed on the screen. Groups of students took the video tests in classrooms where the seats were placed so that everyone could see the monitor.
The recommended stop periods between issues were set between 15 and 60 seconds and were deemed liberal based on field testing. Test administrators were advised to exercise discretion if they believed certain students would be unable to finish a problem in the allotted time as an extra precaution. More time was allowed in these situations.
In addition to ensuring that our administrator-paced style would more closely resemble the student-paced structure that is characteristic of most testing accommodations of this sort, this precaution was intended to relieve students of the time pressure to finish tasks. Even if it seemed like every student had finished an activity, pause periods could never be decreased.
DATA ANALYSES
We computed standard (z) scores for the 30-item oral presentation and 30-item paper-and-pencil examinations for all Group 1 primary pupils (general and special education). We calculated the amount of the difference (Diff) in relative performance between the two forms in standard deviation units by subtracting the paper-and-pencil z-score from the accommodated z-score. A positive score meant that the oral presentation had been the student’s best comparable performance. Every student whose difference exceeded or was equivalent to the absolute value of .5 was noted. As a result, we got a list of every Group 1 student who saw a change between the standard and accommodating test formats of at least half a standard deviation, either way. We considered this to be a discernible change with real-world applications. These pupils were classified as either “Favor Standard” or “Favor Oral.” We went through the same process with middle school pupils and Group 2 members. Only special education students that experienced this .5 magnitude shift are included in the majority of the data analysis included in this paper.
We divided students into four groups according to (a) their best test performance (standard or video) and (b) their teachers’ perception of the necessity of a test accommodation in order to examine the accuracy with which teachers awarded read-aloud accommodations. Teachers’ answers to our survey served as the basis for this last criterion. If the teacher indicated that the accommodation was of high or very high relevance, we took that into consideration when recommending it to a student. If the teacher marked the accommodation as low priority or extremely low importance, we deemed the student not recommended for the accommodation. Those who fared better in the video format were recommended by their teachers, whereas those who performed better in the regular version were not. These two groups reflected students whose teachers’ predictions had come true. The other two groups—recommended students who did better on the conventional format and non-recommended students who did better on the video version—represented incorrect predictions. The accuracy of the teachers was gauged by the proportion of accurate predictions.
We compared the maze and basic math skill scores of the Favor Standard and Favor Oral groups using t-tests in order to create a profile of kids who benefited from read-aloud accommodations. In addition, we separated students into four groups based on reading proficiency (using a Maze z-score of -0.5 as the boundary between poor and satisfactory reading) and basic math proficiency (using a math skill z-score of -0.5 as the dividing line) in order to examine whether math and reading skills were related. As a result, we were able to identify both proficient and poor readers who had both suitable and insufficient mathematical abilities. For two reasons, a relatively low bar was established to distinguish between high and low achievers. First, we believed that testing accommodations would not typically be given to kids whose reading and math accomplishment scores were close to z-score = 0. As a result, our use of the terms high and low is related to our particular goal rather than being normative. Second, we were able to include enough students in each category to conduct significant statistical analyses thanks to the criteria we selected. After the students were divided into groups, we compared the Diff scores of each group using analysis of variance.
RESULTS
For 1,218 of the 1,550 initial pupils, complete data sets (survey information, maze, basic math skills exam, and both variants of the mathematics achievement test) were gathered. On every measure across all grade levels, unpaired t-tests revealed a significant difference (p <.01) between general education and special education students. About 56% of special education pupils assessed the significance of an accommodation as high or very high. On the other hand, just 9% of these pupils were rated as having low or very low importance.
The difference between the video and paper-and-pencil versions of the math achievement test was at least half a standard deviation for nearly 600 (46%) of the kids. These were divided between the two testing formats about equally. Of the 122 special education children who were subjected to such a shift, 60 preferred the video version and 62 preferred the normal version.
TEACHER ACCURACY
Teachers’ evaluations of the significance of accommodations for special education students who were classified as either in need of (rating 4 or 5) or not in need of (rating 1 or 2) an accommodation is displayed here. These are categorized by the actual performance preferences of the students. Fourth and fifth graders, as well as seventh and eighth graders, were merged to create elementary and middle school divisions in order to expand the cell size for data analysis. A significant majority (81%) of the 122 students who preferred one or the other testing forms were classified as needing an accommodation, with 80 of them receiving ratings at the extremes (ratings of 3 were deleted).
52% of elementary school pupils whose teachers thought it was crucial that they be given a test accommodation did better in regular classroom settings. The recommendations made by these pupils were erroneous. Fifty percent of middle school students made the wrong recommendations. While 88% of middle school students whose teachers believed that accommodations were not significant did better on the video test, 14% of primary school students whose teachers believed that accommodations were of low priority did better. Inaccurate recommendations are also represented by these students. Overall, teachers gave inaccurate recommendations to 57% of middle school pupils and 45% of primary school students.
PROFILE
The maze and basic math scores for the Favor Standard and Favor Oral groups are interesting. When comparing students who performed better on the standard test to those who performed better on the accommodated version, there were three notable variations in the scores of these variables. Both the math abilities exam and the maze pretest scores were considerably higher for fourth-grade kids who performed better in the modified format. But we discovered the opposite outcome in the fifth grade.
Math skill scores were significantly higher for students who performed better on the conventional version, and their higher maze scores were close to significance (p =.09). In middle school, no notable differences were observed.
The Diff scores (z-score disparities between standard and accommodating formats) of the four achievement groups (LowRead/LowMath, HiRead/LowMath, LowRead/HiMath, and HiRead/Hi-Math) were compared in our final analysis. The LowRead/HiMath group had the highest value across both levels.
The average performance in each instance was around half a standard deviation better when the standard test was administered. In both elementary school (F [3,100] = 4.36) and middle school (F [3,137] = 6.08), showed a main effect for the group. Follow-up contrasts for primary school pupils showed a substantial difference between HiRead/LowMath and LowRead/HiMath. LowRead/HiMath versus HiRead/Low-Math and LowRead/HiMath versus LowRead/LowMath were two noteworthy contrasts in middle school.
DISCUSSION
Two questions were raised by this study. How reliable are the read-aloud accommodations suggested by teachers for arithmetic tests? And what characteristics distinguish a student who gains from this kind of accommodation? Regretfully, we could only come up with a provisional response to one of these questions.
TEACHER PREDICTION ACCURACY
When it came to recommending which children would benefit from having arithmetic test items read aloud, the teachers in our study didn’t seem to be very successful. Only about half of the time did teachers’ assessments of their students’ need for testing accommodations match the students’ actual performance. This result is no better than what a simple random guess would have predicted.
We discovered that teachers frequently suggest too many accommodations, which is in line with the research of Fuchs and associates. This is not shocking. It stands to reason that hearing the text read aloud to pupils who struggle with independent reading would be beneficial. This view was shared by all of the teachers in a brand-new study. However, when test items were read aloud, only about half of the children in our study saw an improvement in their relative performance, and only about half of these kids saw an increase in performance of at least half a standard deviation. This applied to both regular education and special education pupils. In general, teachers’ strong feelings on students’ accommodations were unaffected by this.
The benefits that kids really received had little to do with teachers’ opinions about how important it was to make concessions for specific pupils.
Our study’s deliberate exclusion of students who did not see a performance shift of at least half a standard deviation between the standard and adapted formats is one of its limitations. About half of the kids who were tested are represented by this. Because of this, we might have disregarded a lot of good teacher advice, which would have led to a more negative assessment of teacher accuracy than we otherwise would have. Despite this possibility, we support our analysis techniques with two arguments.
First, it makes sense that we originally concentrated on the pupils who stood to benefit the most, as there isn’t much work in this area. It is obviously useful to find out how accurately teachers believe that reading test items aloud to students greatly improved or hampered their performance. Examining teacher accuracy in relation to pupils who alter their relative performance just slightly has little practical significance. Second, teachers were able to forecast performance more accurately because to our method. Teachers who are aware of how pupils will fare with exam accommodations should undoubtedly be more aware of those who are at the extremes. It is evident that if the pool consisted solely of subjects with distinct preferences, it would be simpler to determine which format a student would favor. Even for pupils at the extremes, the fact that teachers’ forecasts were ineffective speaks something about their perceptions.
STUDENT PROFILE
However, we take care to avoid criticizing teachers for seemingly lacking awareness of their students’ read-aloud accommodations needs. We couldn’t have done much better, even with the advantages of post facto data and statistical analytic methods. By comparing the reading and basic math success levels of kids who scored better on the normal format of the test with those who did better, we tried to create a profile of those students who benefit from read-aloud accommodations. We discovered surprisingly few differences between the two groups. Out of the 14 comparisons we did, only three were significant and provided contradicting data. Students in the fourth grade who preferred the modified format performed better on reading and arithmetic assessments. However, similar high performers in the fifth grade preferred the conventional style. We did not find any correlation between kids’ preference for a specific assessment method and their achievement in reading or math in middle school.
We divided people into four groups on the basis of the theory that reading and math abilities could interact to affect how effective an accommodation is. Even though we discovered some noteworthy variations, they did not go in the expected direction. We anticipated that the pupils most likely to benefit from a read-aloud accommodation would be those with low reading proficiency but strong math abilities. Although their math accomplishment scores suggested that they would have the mathematical tools required to solve many of the issues once they understood the problem statement, these students seemed to be the ones who would struggle to extract meaning from text.
In contrast to what we expected, low readers with sufficient arithmetic skills outperformed the conventional version by an average of half a standard deviation in both elementary and middle school. In addition to being paradoxical, this is remarkable because we discovered that these students were the only group who preferred a read-aloud accommodation. The effect that these researchers saw may be explained by the fact that they restricted their analysis to six test items that satisfied intricate linguistic requirements. Generally speaking, the items used in this earlier study were easier to read than those used in this one. It should come as no surprise that read-aloud accommodations assist pupils more when the items are of a high readability level than when the language is relatively plain.
It’s possible that a sizable portion of students were able to identify the type of problem or obtain enough hints about the solution method from key terms without having to read an item through to the end. However, this does not account for the fact that we discovered that students’ performance improved when they were required to read the items themselves. It would seem most likely that proficient readers would be the ones who were distracted by our video presentation.
Another surprising discovery was that the HiRead/LowMath group (Favor Oral) performed substantially better than the LowRead/HiMath group (Favor Standard) in both elementary and middle school. We didn’t think that this later group of proficient readers with poor math skills would benefit in any way from our accommodation. This is the exact group that is least likely to apply the knowledge (low math competence) and to gain from having stuff read aloud (high reading skill). To ascertain whether these trends apply to other groups, replication research is required.
CONSEQUENCES FOR PRACTICE
Our study supports other researchers’ conclusions that teachers make inaccurate adjustments assignments. However, given the requirement for test validity and federal demands to include all children in extensive testing programs, the significance of accommodations for special education students does not diminish. It is the responsibility of researchers to create strategies to improve teacher efficiency rather than circumventing them in the decision-making process, as instructors are the ones who deal directly with students and have the best understanding of their skills.
Our tentative advice is supported by promising systems which target kids for accommodations based on the outcomes of prior accommodations. However, the great majority of teachers are forced to use alternative approaches because they lack access to these kinds of technology. According to earlier studies, screening for reading and math skills may be helpful in determining if a person qualifies for read-aloud accommodations. Regretfully, this was not confirmed by the current study. However, we do not entirely give up on this approach. This approach appears to have drawbacks when used as the main method of identification. As an alternative, it’s possible that teachers or testing coordinators may improve decision-making efficiency by combining their in-depth knowledge of students—which we don’t have—with reading and math profiles. For instance, we used the results of accomplishment tests to determine the competence levels in reading and math. However, reading problems can take many different shapes. There are kids who have both low fluency and strong reading comprehension (one of the qualities assessed by maze tests), despite our temptation to avoid suggesting a read-aloud accommodation to someone who scored highly on a reading maze screener. Even though the reading screener indicated that a read-aloud accommodation was not required, it could be wise to use one if direct instructor experience of a student in this group indicated that the student felt easily frustrated when reading challenging texts.
Students are also likely to gain from the use of an accommodation in the classroom before tests. An assessment/instruction relationship is not necessary in many states; however, it is in some of them. Information from screenings for reading and math skills as well as actual instructor experience may suggest that a certain student would benefit from test items being read aloud. Nevertheless, the novelty of this testing method can be distracting or perplexing enough to offset any potential benefits. Implementing an accommodation that pupils have never seen before may introduce another irrelevant testing criteria in an attempt to remove the first one (reading ability). This could be one reason why the two approaches we looked at were ineffectual. By incorporating modifications into regular classroom activities, a novelty effect can be eliminated, perhaps improving the accuracy of teacher assessments.
Teachers should nevertheless assign this kind of accommodation while taking the necessary safeguards, even when we are unable to confirm an effective identification system. There is little evidence to support the idea that giving pupils too many read-aloud accommodations is bad for them. Furthermore, kids who are not normally targeted for accommodations—like high-ability readers—are probably most at risk. Teachers and IEP team members should rely on their understanding of students’ reading and math proficiency, learning preferences, classroom experiences, and testing habits until empirical research confirms a workable system for allocating read-aloud accommodations. Teachers should be able to target children for accommodations more precisely if they have up-to-date and pertinent information in each of these areas.
Jeff Palmer is a teacher, success coach, trainer, Certified Master of Web Copywriting and founder of https://Ebookscheaper.com. Jeff is a prolific writer, Senior Research Associate and Infopreneur having written many eBooks, articles and special reports.