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Information and Communication Technologies (ICT) and pupils with Attention Deficit Hyperactivity Disorder (ADHD) symptoms: do the software and the instruction method affect their behavior?

 The study investigated the effects of Information and
 Communication Technologies (ICT) use on pupils with Attention
 Deficit Hyperactivity Disorder (ADHD) symptoms. Nine Greek
 primary school pupils with ADHD symptoms and four others with
 no such deficit worked on a computer, either individually or
 collaboratively, once a week for a six-week period. The pupils
 worked on a series of activities especially developed for the
 study, with educational software and ICT environments of
 different types and features. It was found that specific
 characteristics of the educational software used by the pupils
 with ADHD symptoms stimulated their attention more than others
 did. Pupils with ADHD symptoms appeared to prefer reading short
 texts, watching short videos, and listening to short narration
 items when they work on the computer. Furthermore, significant
 differences were observed on those pupils' behavior and
 performance in learning tasks between individual and
 collaborative work.


The development of software applications that will meet the needs of pupils with various kinds of disabilities is a matter which appears to be compulsory today due to the necessity for universal access to information and communications services and for the development of software environments accessible to all (Shneiderman, 2000; Keates, Clarkson, & Robinson, 2002). Page (2002) referred to the positive effect that computers can have on "non-traditional" pupils, meaning all those who have been labeled as being learning disabled, low achieving, educationally disadvantaged, and so forth (p. 392). One of these groups of pupils at-risk for behavioral and academic problems is the group of children who exhibit attention deficit and/or hyperactivity-impulsivity symptoms.

Attention Deficit Hyperactivity Disorder (ADHD)

Attention Deficit Hyperactivity Disorder (ADHD) syndrome is a diagnostic category used to describe individuals who display developmentally inappropriate levels of inattention, impulsivity, and/or overactivity (DuPaul, Power, Anastopoulos, & Reid, 1998). It is a lifelong neurobiologically-based developmental disability which is estimated to affect 2-9.5% of the school age population, based on research evidence world-wide, with boys outnumbering girls at about a 2:1 to 5:1 ratio (Fowler, 1994; Barkley, 1998). Research evidence in Greece estimated that 12.4% of elementary school pupils exhibit ADHD symptoms (Zournatzis, Kakouros, Karamba, Papaeliou, & Badikian, 2001).

According to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (America Psychometric Association, 1994), the main symptoms of the syndrome are three:

1. Inattention. Individuals who have inattention problems display difficulties in focusing on a task, are easily distracted by extraneous stimuli, exhibit problems in organizing and completing their homework, often loose things necessary for tasks or activities (e.g., books, pencils), and so forth.

2. Hyperactivity. Hyperactive individuals have difficulty in remaining seated while being in the classroom, are often fidgety and talk excessively, run about or climb in situations in which it is inappropriate, and so forth.

3. Impulsivity. Impulsive individuals act before thinking, have difficulty in waiting turn, often interrupt or intrude on others, blurt out answers before questions have been completed, and so forth.

The DSM-IV categorizes these symptoms into three subtypes of the disorder: (a) predominantly inattentive, (b) predominantly hyperactive-impulsive, and (c) combination of the two types. For a child to be diagnosed as having ADHD, these symptoms must be present in the child's behavior before age seven and must persist for at least six months in two or more settings (at school and at home) (American Psychiatric Association [APA], 1994). In addition to the problems mentioned, pupils with ADHD characteristics very often experience academic difficulties and low learning motivation, poor self-esteem, behavioral problems, and social rejection (Fowler, 1994).

Computers and Pupils with ADHD Symptoms

Today, technology is incorporated in everyday life and computers could be seen as a useful educational tool in school settings to help pupils with attention deficits. Many aspects of technology appear to assist pupils with ADHD symptoms overcome their academic problems. In particular, it was found that computers allow pupils to learn at their own pace, have infinite patience and provide privacy, promote discovery learning and help them develop problem-solving skills, can excite and motivate pupils, provide instant reinforcement, corrective feedback and immediate praise (Ford, Poe, & Cox, 1993; Dailey & Rosemberg, 1994; Bender, & Bender, 1996; Xu, Reid, & Steckelberg, 2002). Furthermore, the way information is being presented on the computer (graphic objects, colors, sound, animation etc.) can be highly stimulating when it comes to individuals with attention problems and/or hyperactivity-impulsivity. All these features have been found to contribute to the improvement of ADHD pupils' academic performance (Barkley, 1998).

Previous research relative to this subject is quite limited. However, a common finding among relevant studies is that computer use has positive effects on pupils with similar problems. In particular, Kleiman, Humphrey, and Lindsay (1981) found that pupils with ADHD symptoms worked for a longer period of time on solving Mathematics problems and solved twice as many problems on the computer compared similar paper-and-pencil tasks.

More recently, Ford et al. (1993) examined the impact of specific software packages on the attending behaviors of 21 primary school pupils with ADHD symptoms. Of those pupils, only five had been diagnosed by a specialist as having ADHD syndrome. The rest were either identified by their teachers as exhibiting nonattending behaviors (eight pupils), or scored within the required range on the Revised Conners' Questionnaire (eight pupils), that was filled in by their teachers. It was found that the pupils' attending behaviors are related to the type of software used, since their attention increased when they were using Mathematics software with a game format, which did not have animated graphics and where pupils had unlimited time to respond. On the other hand, when the same pupils used Reading tutorial and drill-and-practice software, they exhibited more nonattending behaviors.

In addition to the studies, in which educational software packages were used, psychologists conducted a series of other investigations, where it was found that computerized cognitive-training programs can contribute to the increase of attention and impulse control, and can, therefore, be effective tools for the reduction of ADHD symptoms of pupils with such difficulties (Slate, Meyer, Burns, & Montgomery, 1998; Navarro, Ruiz, Alcalde, Marchena, & Aguilar, 2001).

What must be stressed is the fact that the software used on these studies was either educational software in only two learning subjects (Mathematics and Reading) (Kleiman et al., 1981; Ford et al., 1993), or computerized cognitive-training programs developed by psychologists (Slate et al., 1998; Navarro et al., 2001).

Thus, the critical role of ICT use in various learning subjects, along with the specific characteristics that educational software used by pupils with ADHD problems should have to assist them overcome those symptoms have not yet been investigated. Furthermore, what should also be examined is the optimum way of working on the computer (alone or in collaboration), for those children to behave properly and achieve well.


The present study was designed to investigate:

1. The effects of using educational software of different types (drill-and-practice, multimedia applications, constructivist-type, open environments, Internet, the Web) and characteristics (text, narration, pictures, video, etc.) on the behavior of pupils with ADHD symptoms, in various school subjects and learning activities, and

2. The differences in the behavior and performance between pupils with ADHD symptoms working on the computer individually or collaboratively and pupils without attention problems.



To locate pupils with ADHD symptoms, the Greek adaptation of the American ADHD Rating Scale-IV: School Version (DuPaul et al., 1998) was used. The development of the original psychometric instrument was based on the DSM-IV criteria for ADHD (American Psychiatric Association [APA], 1994) while the Greek version is especially designed to be completed by teachers (Angeli, & Kalantzi-Azizi, 1999). According to DuPaul et al. (1998), the scale is highly accurate in predicting the absence of ADHD in the general population of children (p. 44). Though the scale itself is not capable of diagnosing children with ADHD syndrome, it can be used as a tool for the first screening of ADHD symptoms in children. The use of this kind of questionnaire to identify pupils with ADHD symptoms is a method well known (Ford et al., 1993). The questionnaire contains 18 items concerning respective ADHD symptoms, scored on a four-point scale: Never or rarely (0), Sometimes (1), Often (2) and Very often (3). The possible score that an individual can reach on the scale ranges from 0 to 54.

Fifteen Greek primary school teachers (10 male, 5 female) filled in the ADHD Rating Scale-IV, for a total of 281 5th and 6th grade pupils (143 boys, 138 girls). This process took place in February, which is almost 6 months after the beginning of the school year, so the teachers know their pupils and can assess their behavior. In the meantime, parents were informed about the forthcoming research by post and were asked permission for their children's participation in the study.

To be included in the study pupils had to score a mean of over 1.28 (Mean > 1.28) on each of the 18 items of the ADHD Rating Scale - IV, which is one standard deviation from the scale's mean (M= 0.6412, SD= 0.6496). Forty-four pupils (35 boys, 9 girls) reached the criterion set. However, only 9 pupils with high ADHD scores (6 boys, 3 girls) accepted to participate in the study. Furthermore, 4 other pupils (3 boys, 1 girl) without such deficit (see Tables 1a and 1b) were selected to take part in the research. It must be mentioned here that mostly the parents of pupils without ADHD symptoms were willing to give their permission.

A total 13 pupils formed the group of participants. Eleven (11) were 5th graders (8 boys, 3 girls) and 2 were 6th graders (1 boy, 1 girl). It should be mentioned that the 9 pupils with high ADHD mean scores will from now on be referred to as children with ADHD symptoms, since no professional diagnosis of the syndrome has been conducted for them, prior to this research.

After the sample was located, the pupils were divided into 2 groups (see Table 2) Group A was comprised of 5 pupils with ADHD symptoms who worked on the computer individually (3 boys, 2 girls) and b) Group B was comprised of 8 pupils (6 boys, 2 girls), 4 of whom had ADHD symptoms and 4 did not. Each pupil with ADHD symptoms worked on the computer in collaboration with a non-ADHD pupil of the same age and sex.

The two groups worked on the computer for 6 weeks and after that period their teachers filled in the ADHD Rating Scale-IV once more.

Software and Activities

Three commercial educational software items with topics on History, Geography and Mathematics, a constructivist-type software on Physics developed by the Universities of Athens and Thessaly in Greece, a HyperStudio (2) application created by one of the authors (3), Ms Excel, the Internet and a Greek site on the Web were used in six different activities especially developed for this study. The pupils had to follow the instructions set for each activity, fill in questionnaires and solve problems. To successfully perform each activity, they had to employ concentration and other skills such as using carefully and patiently the PC mouse and keyboard, reading short and long texts and paying attention to narration items and videos in order to find the correct answers. In particular, the six activities on the computer were the following:

1. Art: The pupils worked on the HyperStudio application concerning Cubism, the biographies and the paintings of four Cubist painters (Pablo Picasso, George Braque, Paul Klee, and Vassily Kandinsky). The application (stack) consisted of seven screen pages (cards):

a. Card 1: The pupils saw the title of the application, which was "Cubist Painters."

b. Card 2: They had to click on an interactive button to read a text (87 words) concerning Cubism.

c. Card 3: On this card, entitled "Pablo Picasso," there were two interactive buttons. The pupils had to click on the button "Biography" to read a text (34 words) about Picasso's life and afterwards click on the button "The three musicians" to view the corresponding Picasso painting.

d. Card 4: This card was entitled "George Braque." The pupils had to click on the button "Biography" to read a text (46 words) about Braque's life and then click on the button "Still life with violin and jug" to view this Braque painting.

e. Card 5: This card was about "Paul Klee." The pupils had to click on the button "Biography" to read a text (36 words) about Klee's life and then click on the button "The rose garden" to view the painting.

f. Card 6 (see Figure 1): This card's title was "Vassily Kandinsky." The pupils had to click on the button "Biography" to read a text (37 words) about Kandinsky's life and afterwards click on the button "Yellow, red, blue" to view his painting. In this card there was a third interactive button, which pupils had to click on so as to move to the last card and draw a painting of their own by using the same cubist style.

g. Card 7: In this last card, the pupils were given instructions on how they could create their own artifact by using the HyperStudio tools.

They had to draw only within the borders of a specific white frame on the screen.


2. History: The pupils worked on the topic "World War II" of the multimedia educational software "World History," which is a Greek translation of a software package created by Dorling Kindersley Multimedia. In this activity the pupils had to listen to 3 short narration items (narration item 1= 28 sec, item 2= 38 sec and item 3= 25 sec), to read a long text (580 words) and to watch 5 short documentary-type videos, which were in black-and-white and followed by narration. The duration of those videos was: video 1= 43 sec, video 2= 37 sec, video 3= 48 sec, video 4= 40 sec and video 5= 28 sec. While working on the computer the pupils had to fill in a 2-item-questionnaire. In particular, they had to answer "which countries declared the war against the Germans and when" and "where and when was the first atomic bomb dropped." The answer of the 1st question was in the long text and that of the 2nd question was in video 5.

3. Physics: The pupils worked with the constructivist-type software MATHIMA (Solomonidou et al., 2000). The task was divided in two parts:

* Part 1: They had to read a text (66 words) which presented directions to "execute" a simulated experiment concerning "Propagation of light" (experiment 1) and then to fill in a 3-items written questionnaire relative to the rectilinear propagation of light. In Figures 2a and 2b one can see two different stages of this experiment, where the pupils had to find a way so that the light passes through both diaphragms and point at the little diamond on the wall. To do that, the pupils had firstly to find a way that the light passes through the 1st diaphragm, and that is changing the height of the lamp. After that they had to find a way so the light passes through both diaphragms. The solution was to change the height of the 2nd diaphragm so the light reaches the diamond on the wall.


* Part 2: They had to read a text (53 words) which presented directions to "execute" the second simulated experiment concerning "Shadow formation" (experiment 2). After this experiment too, they had to fill in a 3-items written questionnaire relative to the shadow formation phenomenon.


4. Geography 1: The pupils worked on the topic "Solar system" of the multimedia software "Streets of the Universe," created by Tessera Multimedia. In this task, the pupils had to listen to 4 narration items (narration item 1= 44 sec, item 2= 36 sec, item 3= 37 sec, and item 4= 43 sec), to read 2 long texts (text 1= 248 words and text 3= 270 words) and 2 shorter texts (text 2= 107 words and text 4= 131 words). Furthermore, they had to watch a video concerning planet Hermes, which was long (112 sec), black-and-white and not followed by narration, as well as a shorter (13 sec) colored video about the planet Mars. Finally, they had to see 10 black-and-white pictures of planet Hermes and 11 colored pictures of the planet Mars. During this task they had to fill in a 3-item-questionnaire. In particular they had to answer "how many and which are the planets of the solar system," "which is the smallest planet and the nearest to the Sun," and "which are the satellites of planet Mars." The answer to the 1st question was in narration 3 and the answers to the 2nd and the 3rd questions were in the 2 long texts.

5. Geography 2: They worked on the topic "The Greek mountains" using the Internet, the Web and Excel. First, they had to visit the Greek website, where, by following the written instructions given to them at the beginning of the task, they had to find and write down on a piece of paper the name and altimeter of the highest mountains in each of 8 geographic regions in Greece. Furthermore, they saw 38 colored pictures of those 8 mountains. Then they had to work on Excel to create a spreadsheet with the information previously collected. Afterwards, they had to follow the instructions so as to create a graphic image (diagram) of the spreadsheet and then to save the file on the computer's hard disk.

6. Mathematics: The pupils worked with "Math Town," a Greek drill-and-practice educational software, created by Inte*Learn company. In particular, the pupils worked on the topics "Fractions" and "Units of length conversion." They had to listen to a long narration item (83 sec) concerning the theory about equivalent fractions and to a shorter one (31 sec) about length units. Furthermore, they had to solve two problems about fractions and a more difficult one about conversion of length units. They also watched two videos (Mean duration= 120 sec) presenting Greek traditional dancers, as a reward for their success in solving the first two problems.


For a 6-week period, the 13 pupils visited the University of Thessaly once a week after arranged appointments and they worked on a computer activity. One of the authors (4) was present to assist them when needed. Each procedure was videotaped. Data analysis was comprised of careful observation of the videotaped activities, during which the behavior of each pupil was measured. Behavior components, such as reading the text carefully, fidgeting or being distracted while reading the text, fidgeting or being distracted while the partner is using the mouse or the keyboard (Table 3), were rated on a 3-point scale: Not at all (1), Moderately (2), and Very much (3). The term "fidgeting" describes behaviors such as being overactive, moving hands or feet, squirming in seat, talking too much, and so forth. Likewise, the term "inattentive" describes behaviors such as having difficulty paying attention to the task, not following instructions, avoiding tasks, being easily distracted by extraneous stimuli (looking out of the window, at the floor or the ceiling) and so forth.

In total, 598 measurements (46 for each pupil) were conducted concerning the processes of reading texts, watching videos and pictures, listening to narration items, solving problems, conducting experiments, drawing on HyperStudio and writing on Excel.

The pupils' performance on each activity was rated in a 4-point scale: Low (1), Moderate (2), Good (3), and Very Good (4). Pupils of Group B were assessed and scored as a team and not individually. The SPSS software package was used for the statistical analysis of the data.

The assessment of the pupils' performance in each task was conducted as follows:

* Art: The pupils were assessed according to their performance on the drawing task. To get a higher grade they had to use geometric shapes in their drawing and draw only within the white frame of the screen.

* History, Physics, and Geography 1: The pupils were assessed according to their performance on the written questionnaires, in which they had to give correct and complete answers.

* Geography 2: The pupils were assessed according to their performance on the creation of the spreadsheet and the diagram on Excel. To get a higher grade they had to write the names of the mountains on Excel carefully with no mistakes.

* Mathematics: The pupils were assessed according to the mistakes they made while solving the three mathematical problems.


The research data concerning the effect of software characteristics and the working method on the behavior of pupils with and without ADHD symptoms are presented next.

Impact of Software Characteristics on Pupils' Behavior

Following the assessment procedure, a total of 598 tables were plotted, regarding pupils' behavior during the activities on the computer. The study of those tables allowed us to draw several conclusions regarding the variations among pupils with and without behavioral problems. The most important difference was detected on the activity levels between pupils with and without ADHD symptoms while reading the longest text in History (580 words) and while listening to the longest narration item in Mathematics (83 seconds) (Table 4).

In both cases, pupils with attention deficit and/or hyperactivity-impulsivity symptoms were more kinetic than pupils with no such behavioral problems. In particular, while reading the long text, most of the pupils with ADHD symptoms seamed bored, they asked "if they had to read it all" and complained that the text "was too long." Similarly, when those pupils listened to the long narration item, they seemed to be bored and complained, "they do not need to listen to that because they already know all those things." On the other hand, pupils without ADHD symptoms concentrated in both situations and did not complain in any of those cases.

No other differences were found between pupils with and without ADHD symptoms concerning their behavior while reading texts, watching pictures, or attending to videos and narration items. Yet, it was observed that pupils of Group A, who worked alone, watched the long video in Geography 1 (112 sec, black-and-white, no narration) much more carefully and less inattentively than pupils with or without ADHD symptoms in Group B who worked in pairs (Table 5). Specifically, while pupils in Group B were watching this long video, they were talking to each other about irrelative subjects (e.g., football, the weather, etc.), they were looking out of the window, the ceiling or the floor, being completely inattentive.

Impact of the Instruction Method on Pupils' Behavior

Regarding collaborative work, our data revealed that pupils with ADHD symptoms in Group B were attentive and less kinetic only when they had control of the computer, in other words when they used the PC mouse or the keyboard. On the contrary, when their partner used the computer, they were inattentive and fidgety. Examination and analysis of inattention and activity levels in eight tasks, where pupils of Group B had to use the PC mouse (or the keyboard) in turns with their collaborator, indicate that those with ADHD symptoms were, in most cases, significantly more fidgety and inattentive while they did not use the computer themselves (Table 6). In particular, when they did not use the computer themselves, they were squirming in their seat, moving their feet or hands and were quite talkative. Furthermore, in some cases they were disturbing their partners by talking to them or touching them.

However, as observed in Table 6, in Physics experiment 1 ("Propagation of light"), where the users had to highly interact with the software program so as to carry out the procedure, no significant difference was observed in the activity and the inattention levels between pupils with and without ADHD symptoms. Moreover, no important difference was detected on the inattention levels between the two categories of pupils while executing experiment 2 in Physics ("Shadow formation") and while solving problem 3 in Mathematics ("Units of length conversion"), which was more difficult than the previous two ("Fractions"). As mentioned before, in order to execute the simulated experiments in Physics, the pupils had to engage themselves in problem solving situations, which seemed to interest them and keep them focused. Furthermore, solving problem 3 in Mathematics, which was the most difficult among the three, appeared to be more attractive, since it was more demanding.

Pupils' Performance on the Activities

Differences were detected concerning the performance in the activities between pupils who worked alone (Group A) and those who collaborated (Group B). Based on the four-point scale used to measure their performance, the latter obtained generally higher marks than the former (with the exception of Art, in which Group B grades were marginally lower, and Physics, in which there were no differences) (Table 7). The greatest differences were observed in Geography 2 and in Mathematics. However, further in-group examination regarding the performance of pupils with and without ADHD symptoms who worked in pairs indicated important differences.

More specifically, in a total of 11 items in three written questionnaires (History, Physics, and Geography 1), pupils with ADHD symptoms answered fewer questions (M= 2,5, SD= 1,73) than nonADHD pupils (M= 8, SD= 0,82). Furthermore, in the Geography 2 task, where they had to take notes on a piece of paper concerning eight Greek mountains, pupils with ADHD symptoms took far less notes (M= 0,5, SD= 1,00) than the other ones (M= 7,50, SD= 1,00). Some of the pupils with ADHD symptoms even refused to take part in these procedures and assigned this "job" to their working partner.

These data clearly indicate that pupils with ADHD symptoms intensively tend to avoid involving themselves in tasks they apparently dislike, such as writing down on a piece of paper, or working on tasks unrelated to the use of the computer (PC mouse and keyboard). Furthermore, it appears as though they were not concerned about their performance, since they counted on their working partner to perform well and complete the task.

After the intervention the ADHD Rating Scale-IV: School Version (DuPaul et al., 1998) was again filled in by the teachers of the nine pupils with ADHD symptoms. Results show a significant reduction in the younger (5th grade) pupils' ADHD total scale scores and a slight increase in the older (6th grade) pupils' total scale scores (Figure 3). Those data suggest that despite the small number of the participating pupils and the limited number of their working sessions, the computer indeed seems to be effective, primarily to the younger pupils with ADHD symptoms.


The present study indicates that specific characteristics of a software program, used by pupils with ADHD symptoms, can affect their behavior while working on the computer. In particular, pupils with ADHD symptoms paid more attention when they watched videos and pictures or listened to short narration items, but they showed great difficulty in reading long texts or watching long videos with no narration. As a general remark our findings appear to lend support to the literature suggesting that ICT can indeed have a positive effect on users with attention deficit and/or hyperactivity-impulsivity problems (Kleiman et al, 1981; Ford et al., 1993; Dailey & Rosemberg, 1994; Bender & Bender, 1996; Xu et al., 2002). However, they strongly suggested that this effect is succeeded and expanded if the appropriate software environment is used.


The increase of ADHD scores in the older pupils may indicate that younger pupils are, the more effective than older ones working on the computer with appropriate software environments. As to the question regarding which is the most effective computer instruction method with pupils with ADHD symptoms, it appears that our results support the individualistic way, since ADHD pupils displayed disruptive behavior when working with a partner.

As previously noted, in all the tasks where pupils had to do something not related to the use of the computer (mouse or keyboard), those with ADHD symptoms appeared extremely reluctant to participate. As a result, their partner did the work, which they deliberately avoided (e.g., filling in the written questionnaires). Furthermore, as observed in the study, pupils with ADHD symptoms who worked collaboratively were attentive and less fidgety only when they had control of the computer. On the contrary, they were inattentive and hyperactive, when their working partner had control of the computer, especially during less interactive and demanding tasks. However, when they used highly interactive constructivist-type software in Physics or were engaged in a difficult Mathematics task (problem 3), the pupils with ADHD symptoms exhibited no or less inattentive or hyperactive symptoms, when they did not have control over the computer.

In conclusion, it appears that pupils with such deficits should use multimedia environments containing short videos followed by narration, pictures, short texts and narration items and constructivist-type software, to allow them to interact as much as possible with the environment. Moreover, working on the computer might be more effective for pupils with ADHD symptoms when they work individually and are, therefore, responsible for their own achievement. Finally, there are two obvious limitations in the study described in this article: the small number of the participating pupils and the fact that it was their teachers who assessed those pupils' ADHD symptoms, and therefore the raters could be biased. The limited number of the participants was due to the fact that only the parents of 9 pupils, from a total of 44, who had been identified as having ADHD symptoms, agreed to their child's participation in the study. Regarding the ratings given by the teachers in the ADHD Rating Scale, it must be stressed that they were all acquainted with their pupils for the last six months before filling-in the scale and that the ADHD Rating Scale is a reliable psychometric instrument especially developed for teachers. Although this measurement may be considered as subjective, because is taken from the teachers, it nevertheless is based on a questionnaire especially developed for teachers, which is tested worldwide and, thus, widely accepted.

This evidence could influence the design of educational software and the development of digital environments suitable to the needs and abilities of pupils with ADHD symptoms on the one hand, and on the other, to the educators who use the computer as a learning tool. A perspective of this research could also be the thorough examination of pupils' (with and without ADHD symptoms) individual performance, while working on the computer in groups, so that a comparison of pupils with different behaviors can be done.
Table 1a

Participants of the Study

 ADHD-Scale ADHD-Scale
 Score Score

Participants n Mean SD

Pupils with ADHD 9 1,845 0,394

Pupils without ADHD 4 0,708 0,1720

Table 1b

Participants of the Study

 ADHD-Scale ADHD-Scale

Participants n Total Score Total Score
 Mean SD

Pupils with ADHD symptoms 9 33,56 7,04

Pupils without ADHD symptoms 4 12,000 3,83

Table 2

Groups of the pupils of the study

Pupils n With ADHD Without ADHD 5thGrade
 symptoms symptoms


A (individualistic 5 5 - 3

B (collaborative 8 4 4 8

Total 13 9 4 11

Pupils 6thGrade Boys Girls


A (individualistic 2 3 2

B (collaborative - 6 2

Total 2 9 4

Table 3

Example of an Observation Form of Pupils' Behavior While Reading a

Behavior Components Rate

 Not at Moderately Very
 all much

Is he/she reading the text 1 2 3

Is he/she fidgeting while reading 1 2 3
the text?

Is he/she inattentive while reading 1 2 3
the text?

Is he/she inattentive while his/her 1 2 3
partner is using the mouse or the

Is he/she fidgeting while his/her 1 2 3
partner is using the mouse or the

Table 4

Activity Levels of Pupils with and without ADHD Symptoms While Reading
the Longest Text and Listening to the Longest Narration Item

 Text (580 words) Narration item (83 sec)

 n Mean (SD) Mean (SD)

Pupils with ADHD 9 2,56 (0,73) 1,67 (0,50)

Pupils without ADHD 4 1,25 (0,50) 1 (0,00)

Table 5

Inattention Levels of Pupils of Groups A and B While Watching the Long
Video in Geography 1

 Geography 1: Video (112 sec)

 n Mean (SD) (5)

Group A 5 1,00 (0,50)
Group B 8 1,75 (0,46)

Table 6

Differences in Fidgeting and Inattention Levels Between Students with
and without ADHD Symptoms in Group B (collaborative work)

Is he/she fidgeting while his/her Is he/she distracted while his/her
partner is using the mouse or the partner is using the mouse or the
keyboard? keyboard?

 Mean (SD) Mean (SD)

Art: Drawing ADHD= 3,00 (0,00) Art: Drawing ADHD= 2,50 (0,58)

 Non-ADHD= 1,75 (0,50) Physics: Non-ADHD= 1,50 (0,58)

Physics: ADHD= 1,25 (0,50) Executing ADHD= 1,25 (0,50)

Executing Non-ADHD= 1,00 (0,00) experiment 1 Non-ADHD= 1,00 (0,00)

experiment 1

Physics: ADHD= 1,75 (0,50) Physics: ADHD= 1,50 (0,58)

Executing Non-ADHD= 1,00 (0,00) Executing Non-ADHD= 1,00 (0,00)

experiment 2 experiment 2

Geography 2: ADHD= 2,50 (0,58) Geography 2: ADHD= 2,00 (0,00)

Writing on Non-ADHD= 1,25 (0,50) Writing on Non-ADHD= 1,25 (0,50)
Ms Excel the Ms Excel the
mountains' mountains'
names names

Geography 2: ADHD= 2,25 (0,50) Geography 2: ADHD= 1,75 (0,50)

Writing on Non-ADHD= 1,00 (0,00) Writing on Non-ADHD= 1,00 (0,00)
Ms Excel the Ms Excel the
mountains' mountains'
altimeter altimeter

Mathematics: ADHD= 2,25 (0,50) Mathematics: ADHD= 2,00 (0,00)

Solving Non-ADHD= 1,00 (0,00) Solving Non-ADHD= 1,00 (0,00)

problem 1 problem 1

Mathematics: ADHD= 2,25 (0,50) Mathematics: ADHD= 1,75 (0,50)

Solving Non-ADHD= 1,00 (0,00) Solving Non-ADHD= 1,00 (0,00)

problem 2 problem 2

Mathematics: ADHD= 1,75 (0,50) Mathematics: ADHD= 1,50 (0,58)

Solving Non-ADHD= 1,00 (0,00) Solving Non-ADHD= 1,00 (0,00)

problem 3 problem 3

Table 7

Differences in Performance on the Activities Between the Two Working

Activities Performance (Means and Standard Deviations)

 Group A Group B
 (individualistic work) (collaborative work)

Art 2,20 (0,84) > 2,00 (1,31)
History 2,20 (0,84) < 3,00 (1,07)
Physics 3,00 (0,71) = 3,00 (0,76)
Geography 1 3,20 (1,30) < 3,50 (0,93)
Geography 2 2,60 (0,55) < 3,25 (0,46)
Mathematics 2,20 (1,10) < 3,00 (0,00)


(1.) The Revised Conners' Questionnaire is an instrument used for the detection of ADHD symptoms on someone's behavior.

(2.) HyperStudio is an authoring system for designing multimedia and hypermedia applications (, suitable for teachers and pupils since it is quite easy to learn to use.

(3.) Garagouni-Areou Fotini.

(4.) Garagouni-Areou Fotini

(5.) The children's behavior was rated on a 3-pont scale: Not at all (1), Moderately (2), and Very Much (3).


American Psychiatric Association (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

Angeli, K., & Kalantzi-Azizi, A. (1999, September). Screening of children with ADHD in a sample of primary school students and investigation of their coping strategies, 9th European Conference on Developmental Psychology. Spetses, Greece.

Barkley, R. (1998). ADHD: A handbook for diagnosis and treatment. New York: The Guilford Press.

Bender, R., & Bender, W. (1996). Computer-assisted instruction for students at risk for ADHD, mild disabilities or academic problems. Boston: Allyn and Bacon.

Dailey, E., & Rosemberg, M (1994). ADD, computers and learning: Using computers to help children with ADD become efficient learners. Attention!, 1(2), 8-16.

DuPaul, G., Power, T., Anastopoulos, A., & Reid, R. (1998). ADHD rating scale-IV. New York: The Guilford Press.

Ford, M.J., Poe, V., & Cox, J. (1993). Attending behaviors of ADHD children in math and reading using various types of software. Journal of Computing in Childhood Education, 4, 183-196.

Fowler, M. (1994). Attention-deficit/hyperactivity disorder, fact sheet 19, (pp. 1-16). National Information Center for Children and Youth with Disabilities (NICHCY).

Keates, S., Clarkson, P.J., & Robinson, P. (2002). Developing a practical inclusive interface approach. Interacting With Computers, 14, 271-299.

Kleiman, G., Humphrey, M., & Lindsay, P.H. (1981). Microcomputers and hyperactive children. Creative Computing, 7, 93-94.

Navarro, J., Ruiz, G., Alcalde, C., Marchena, E., & Aguilar, M. (2001, May). How to increase attention using a computer assisted teaching procedure. Paper presented at the International Conference on Education and Technology, Tallahassee, Florida.

Page, M. (2002). Technology-enriched classrooms: Effects on students of low socio-economic status. Journal of Research on Technology in Education, 34(4), 389-409.

Shneiderman, B. (2000). Universal usability: Pushing human-computer interaction research to empower every citizen. Communications of the ACM, 43(5), 84-91.

Slate, S.E., Meyer, T., Burns, W., & Montgomery, D. (1998). Computerized cognitive training for severely disturbed children with ADHD. Behavior Modification, 22, 415-437.

Solomonidou, C., Stavridou, E., Grigoriadou, M., Mitropoulos, D., Rigoutsos, A., & Samarakou, M. (2000, November). Light and colors: Design and development of educational software to study geometric optics. In D. Meimaridou (Ed.) CD-ROM conference proceedings "Informatics in Education." Thessaloniki, Greece: University of Thessaloniki, Association of Informatics Teachers of Northern Greece (6 pages, in Greek).

Xu, C., Reid, R., & Steckelberg, A. (2002). Technology applications for children with ADHD: Assessing the empirical support. Education and Treatment of Children, 25, 224-248.

Zournatzis, E., Kakouros, E., Karamba, O., Papaeliou, X., & Badikian, M. (2001). The performance of children with ADHD on the basic academic sections. Paper presented at the 1st Panhellenic Conference on Educational Psychology, Athens, Greece. [Online]. Available:


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Author:Zafiropoulou, Maria
Publication:Journal of Educational Multimedia and Hypermedia
Date:Jun 22, 2004
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