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The effects of computer technology in assisting thedevelopment of literacy in young struggling readersand spellersRolf B. Fasting & Solveig‐Alma Halaas Lystera University of Oslo , Norwayb Institute of Special Needs Education , 1170, Blindern, 0317 Oslo, Norway E-mail:Published online: 20 Jun 2007.

To cite this article: Rolf B. Fasting & Solveig‐Alma Halaas Lyster (2005) The effects of computer technology in assistingthe development of literacy in young struggling readers and spellers, European Journal of Special Needs Education, 20:1,21-40, DOI: 10.1080/0885625042000319061

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European Journal of Special Needs EducationVol. 20, No. 1, February 2005, pp. 21–40

ISSN 0885–6257 (print)/ISSN 1469–591X (online)/05/01/0021–20© 2005 Taylor & Francis Group LtdDOI: 10.1080/0885625042000319061

The effects of computer technology in assisting the development of literacy in young struggling readers and spellers

Rolf B. Fasting

*

and Solveig-Alma Halaas Lyster

University of Oslo, Norway

Taylor and Francis LtdREJS200102.sgm10.1080/0885625042000319061European Journal of Special Needs Education0885-6257 (print)/1469-591X (online)Original Article2005Taylor & Francis Ltd201000000February 2005RolfB.FastingInstitute of Special Needs Education1170Blindern 0317 OsloNorwayrolf.fasting@isp.uio.no

The aim of the present study is to evaluate the effect of MultiFunk, a computer program designedto assist reading, on the reading and spelling proficiency of struggling readers. Fifty-two below-average readers and spellers, in grades 5, 6 and 7, were randomly assigned as experimental and con-trol groups (

N

= 26 + 26). In addition, 114 classmates, who read normally, were included to com-pare changes in basic literacy development during the intervention. A pre-test, intervention, post-test, control-group design was used to evaluate the effects of the software, using texts to suit the pu-pils’ own choices and interests. The findings indicate that computerized assistive reading has thepotential to aid and support the development of basic literacy skills in a broad group of strugglingreaders and spellers. Issues concerning the MultiFunk text-to-speech technology are discussed.

Keywords:

Computer-assisted reading; Reading intervention; Remediation of reading problems

Introduction

Reading and writing are probably the most important skills learned at school. Successin reading and writing is of enormous importance to pupils’ motivation at school, totheir learning experience, and to their chances of succeeding academically andsocially. However, to some children the road towards literacy competence is an every-day struggle with words and letters. A recent survey by Skårbrevik (2002) shows thatproblems in reading and writing are one of the main reasons for the provision ofspecial education services in Norwegian primary and secondary schools.

Throughout the years a number of remedial programs and tools have beenproduced to support children’s basic literacy development. Over the past decade,

*Corresponding author. Institute of Special Needs Education, PO Box 1170, Blindern, 0317 Oslo,Norway. Email: rolf.fasting@isp.uio.no

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R. B. Fasting and S.-A. Halaas Lyster

computer technology has emerged as a new and interesting educational approach,and perhaps the technology can assist teachers’ interventions, so that pupils with diffi-culties in reading and spelling are supported in a suitable way.

The first part of this paper focuses on the possibilities of combining knowledge ofliteracy development and present computer technology in order to point out howsupporting software can be produced. The second part investigates the effects of acomputer program to assist reading development among struggling readers, includingdyslectic pupils, generally poor-readers, and pupils who for other reasons (for exam-ple, emotional problems) are retarded when it comes to reading skill.

Basic literacy development: reading and spelling

Frith (1985) provided a framework to explain the gradual changes in basic literacydevelopment in which both reading (word recognition) and writing (written wordproduction) were included. Frith focused on the interaction between the two types ofliteracy skills through a number of developmental stages. The development processfrom one stage to the next is seen as a gradual improvement in processing skills, whereboth reading and writing are responsible for triggering the developmental process atdifferent levels respectively.

Ehri (1997) also discusses the inextricable connection between reading and spellingin literacy development. In the early stages, the child’s basic knowledge of the alpha-betic system fuels the development. Such knowledge includes knowledge aboutphoneme–grapheme correspondences, and how letters can be combined into words.Throughout this analytic process, the child’s word-specific knowledge is emerging inmemory as specified orthographic units (Ehri, 1998). At this later phase of develop-ment, fluency reading is acquired.

Caravolas

et al

. (2001) added empirical support to the theories propounded byFrith and Ehri. Their findings underline the developmental connection between read-ing and spelling to make the memory retain orthographic representations. Theysuggest that interventional programs, to increase basic literacy, would be beneficial incombining both reading and spelling (see also Hatcher

et al

., 1994).Studies reported by Torgesen

et al

. (2001) show that inefficient word recognitioncan account for most of the differences in reading fluency between disabled andnormal readers. Their findings indicate developmental consequences. Due to enor-mous differences in reading praxis, disabled readers fall further and further behindtheir peers (Stanovich, 1986). Torgesen

et al

. advocate preventive programs, provid-ing accurate sight word reading strategies (i.e. recognizing words as orthographicunits at a single glance) for children at risk, to reduce the differences in cumulativereading praxis.

In reading research, computer technology has been used to explore different inter-ventional approaches. Wise

et al

. (2000) used two different computer-assisted condi-tions to remediate young pupils’ basic literacy skills. Pupils who used whole-wordfeedback got better results on tasks

with

time constraints. On the other hand, pupilswho received computerized phonological training achieved better results on tasks

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Reading remediation and computers

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without

any time limits. None of the conditions showed any advantage with regard tospelling. The results indicate that whole-word speech feedback in a contextual read-ing condition supports reading speed, and computerized phonological trainingsupports accurate decoding. To improve spelling, it seems that practising writing hasto be included as a training condition.

Computer technology easily combines both reading and writing. In addition, textscan be transformed and manipulated in a number of ways. The challenging task is tocreate a fruitful interaction between the computer and the child, so the struggling child’sdesire to learn is triggered in a suitable way. The computer software has to accountfor technological matters as well as educational and sociological issues, and it has tosupport both task-specific matters and the pupils’ needs and preferences (Grossen &Pochon, 1997). In the following paragraphs some of these aspects will be discussedin the light of pupils with reading difficulties and available computer technology.

Computer technology and reading

Screen readability

The topic in focus, the words, the syntax and the graphical layout all influence textreadability. The complexity of the text is more or less given by the author, and ismainly a pedagogical challenge for the teacher. However, it is possible to manipulatethe graphical layout on a computer screen. In a computer-reading context, screen-readability embraces how the readers perceive the layout of texts on screen.

From computer readability research we know that a range of graphical aspectsinfluence screen readability (Murphy

et al

., 2000; Walker & Reynolds, 2000; Dyson& Haselgrove, 2001; Wilkins

et al

., 2001), but some of the findings are difficult tointerpret. Dyson and Kipping (1998) argue that there might be a contrast betweenwhat the reader perceives as a good reading condition and what research finds as themore effective. They showed that longer lines were more effective for reading thanshorter lines in columns. On the other hand, the readers’ opinion was the other wayround! In this matter, Harrell (1999) suggests that the reader should be able to adjustthe screen layout in accordance with his or her preference. With respect to pupils withreading difficulties, the pupils’ own requests have to be given a great deal of impor-tance, and the computer software ought to be programmed such that the pupils caneasily adjust the screen-layout according to reading competence.

Another matter that makes reading difficult for novices and struggling readers is to‘keep-on-track’ while reading. Their lower reading skills and limited experience ofprint often result in accidental ‘jumps’. Computer software can alleviate this problem.Software can be programmed to highlight words or lines during reading by means ofsimple keystrokes, pointing out where and what to read at the request of the pupil.

Speech feedback

Computer research has shown that pupils with reading problems learn to decodewords more effectively when given speech feedback (Wise & Olson, 1994; Van Daal

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R. B. Fasting and S.-A. Halaas Lyster

& Reitsma, 2000). In addition, most pupils with reading difficulties need tostrengthen their text comprehension. Lundberg (1995) suggests that speech feedbackmay also strengthen the communicative aspect of reading, enhance a sense of masteryand trigger motivation.

Speech feedback and word highlighting co-occurrence can have an additionalpotential in strengthening the alphabetic-phonological coding process, since thewords highlighted are simultaneously read aloud (see Olofsson, 1992; Wise

et al

.,2000; Hecker

et al

., 2002) and, at the same time, this will support the establishmentof orthographical representations and sight word vocabulary in memory (Ehri, 1998;Torgesen

et al

., 2001).

Reading and motivation

Reading texts of current interest is of the same importance to pupils with reading diffi-culties as to others. Aspects of actuality and interest have to be validated by the readerhim/herself, but texts read by classmates (as books, reading exercises and homework)seem from a clinical perspective valid. The benefit of contextual reading has been thesource of some debate (Goodman, 1967; Nicholson, 1991; Levy, 2001). Martin-Chang and Levy (2003) found that poor readers in grade 4 and average readers ingrade 2, were more successful at the onset of a contextual reading program thanpupils reading columns of single words. Their findings advocate the benefit of usingcontextual reading based on pupils’ own choices. Additionally, asking pupils to writea short summary after reading may strengthen their understanding of the text, and,further, support the developmental process of basic literacy skills as learning ingeneral.

MultiFunk

Based on the above assumptions, a multifaceted computer-reading software support-ing Norwegian was developed. The goal was to make reading (and writing) an aidedtask, based on texts of pupils’ own choice and current interests. The present programwas given the name MultiFunk,

1

which is a Norwegian derivation of the words multi-media and multi-functionality.

The MultiFunk software is based on

individual adaptation

of text appearance onscreen and auditory-visual

reading support

. Each pupil creates his/her personal profileand, subsequently, all texts appear according to this profile. Texts can be importedfrom books or hard copies, using a scanner and optical character recognition soft-ware (OCR), from the Internet, from rtf-file format or simply by using the ‘copy–paste’ function between different computer programs. On the screen, modes of

wordhighlighting

can help the pupil to ‘keep-on-track’ while reading. A

text-to-speech

component is available to read aloud difficult words, lines or sentences at the pupils’request. While using the text-to-speech feature, each word is simultaneously high-lighted. Finally, a text editor is available to summarize or to write new texts. Writing

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in MultiFunk is supported by the same facilities as described above. A screenshot ofthe user interface that illustrates the MultiFunk software is shown in Appendix 1.

Present study and research questions

The remainder of this article will present and discuss a study of the MultiFunkcomputer software used by poor readers and spellers, in grades 5–7, to enhance theirbasic literacy performance. The study can be viewed as a multifaceted approach tostudy the effect of the MultiFunk software. For theoretical and practical reasons,however, it would be highly desirable to do a closer evaluation of each of the includedcomponents. In the investigation of the effects of the integrated use of the MultiFunksoftware, the following research questions were generally focused on:

1. Does the MultiFunk computer software show effects on reading and spellingdevelopment in a group of struggling readers and spellers?

2. Does the included synthetic-speech component, with simultaneous word high-lighting, make any significant impact on the pupils’ reading and spelling develop-ment?

3. Does the MultiFunk intervention help struggling pupils to keep up with the devel-opmental growth of their classmates during the intervention (the Matthew effect)?

An experimental study in the field was designed to explore these basic questionsusing the MultiFunk software in every-day classroom settings.

Method

A total of 52 young Norwegian struggling readers and spellers were advised by theirclassroom teachers or school reading therapists to attend the MultiFunk study. Thesample of 25 girls and 27 boys, in grades 5–7 (age,

M

= 11:02,

st.d

9 months, range09:08–12:06) were recruited from six schools in the Municipal Authority Area ofSarpsborg (in the following referred to as struggling readers and spellers). All pupilshad Norwegian as their first language. Compared to classmates, the strugglingpupils’ reading skills were

z

=

−

1.05 (

SD

= 0.722) and spelling skills were

z

=

−

1.50(

SD

= 0.740).After receipt of parental consent, all the struggling pupils’ cognitive abilities were

screened, using the Vocabulary subtest from the Wisc-R (Wechsler, 1974; Undheim,1978) and Raven S.P.M. (Raven

et al

.,1983). Exploring pupils’ cognitive abilities, theanalyses showed decreasing abilities by grade, across cognitive tests. The pupils werestratified by grade and gender, and randomly assigned as MultiFunk experimentals(26) and controls (26). Subjects’ characteristics are reported in Table 1.

The table shows that grade and gender were well balanced in the MultiFunk exper-imental group and the control group. On the other hand, cognitive differences indi-cated decreasing abilities by grade. The teachers’ selection of pupils may explainsome of the findings. It can be argued that among the older pupils, the teacher hadselected pupils with more severe learning problems. In the case of these children, the

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R. B. Fasting and S.-A. Halaas Lyster

teachers had worked for years to remediate the pupils’ reading and spelling problems,without adequate results. This matter can interfere with the conclusions to be drawnfrom the study, as skilled reading involves an ongoing adaptation of multiple cognitiveprocesses (NRP, 2000).

In addition to the groups of struggling readers and spellers, a selection of

classmates,normal readers and spellers

(

N

= 114) was included to compare changes in reading andspelling skills during the experimental intervention. Eight of the classmates wereexcluded on account of not having Norwegian as their first language, of severe cogni-tive disorders or of behavioural problems. The

classmates, normal readers and spellers

(later referred to as classmates), were a random selection of one-fourth of the strug-gling readers’ and spellers’ home classes. The relative proportion of the grade amongthe struggling pupils was maintained during the selection of classmates.

Apparatus

The MultiFunk software was installed on IBM compatible Pentium computers withSound-Blaster compatible soundboard and Internet connection. In addition, theTeleNor Talsmann® synthetic-speech synthesizer was installed. The MultiFunk soft-ware was also supported by a scanner and the ScanSoft Optical Character Recogni-tion software, DevKit 2000®, to process scanned texts.

General design of the study

An experimental pre-test–intervention–post-test design was used. The battery ofreading and spelling tests was given at pre- and post-test, and 11 weeks after the inter-vention (follow-up). The interval between pre- and post-tests (seven weeks) andbetween post-test and follow-up (11 weeks) was balanced according to Christmaspreparations and a two-week Christmas holiday.

Table 1. Subject characteristics at pre-test: means, standard deviation (in parentheses) of pre-test

measures

MultiFunk experimentals Controls

Variables Grade 5 Grade 6 Grade 7 Grade 5 Grade 6 Grade 7

Gender (

N

=) 2M/2F 8M/8F 3M/3F 2M/2F 7M/8F 5M/2FRaven S.P.M.(PS) 59.0 38.5 42.0 49.25 41.3 30.0

(28.0) (23.7) (18.6) (28.2) (23.8) (11.0)Vocabulary (SS) 9.0 7.7 7.0 9.0 8.0 7.1

(0.8) (2.3) (3.0) (2.0) (1.9) (1.8)

N

= 26

N

= 26

Note

: M = male, F = female, PS = percentiles score, SS = standard scores.

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The MultiFunk experimental pupils were to use the MultiFunk software for at least20 minutes every day for seven weeks. The software was used in classroom settings orin computer-rooms reserved for pupils’ use. The control group received no specialtreatment, but had individual or group-based lessons as usual, including access toother relevant computer software. The control-group members were told that theywere to have a turn at using the MultiFunk software the next term in common withscheduled school activities in Norway. All the pupils received a session of daily liter-acy-related instruction via teacher-led classroom activities.

Some of the teachers were teaching both the MultiFunk experimentals andcontrols. This reduced the influence of teacher differences on the outcome of theexperiment. On the other hand, the teachers’ educational preferences and style couldnot be separated from school and socio-economic factors. As a consequence, therewas no control for carry-over effects of fruitful teaching strategies in either of thegroups (see also Hatcher

et al

., 1994, Wise

et al

., 2000). With both experimentals andcontrols in the same class and school, unique usernames and passwords were used tocontrol pupils’ use of MultiFunk. Teachers were also present most of the time, eithersupporting the experimental pupils or teaching in the next-door classroom.

All the teachers involved attended the MultiFunk study voluntarily. They receivedinformation about the MultiFunk software and the training conditions during thespring term. The week before the intervention started, all the teachers joined a Multi-Funk training session. Later they administered the pupils’ use of the program, guidedby the author. The teachers supported the pupils’ choice of texts, helped them toscan/correct mistakes in the scanned passages, and guided their MultiFunk readingand writing. The schools and teachers were visited regularly in order to solve prob-lems, answer questions, and to encourage teachers and pupils to use the MultiFunksoftware as scheduled.

Pre- and post-tests

The goal of the intervention was to explore possible effects of the MultiFunk softwarein pupils’ overall reading and spelling performance. All instruments used were paper-and-pencil tasks. Two reading tests and a spelling test are reported in this context.

OS400 (Søegård & Bording Petersen, 1974), a silent, single word-decoding test,was used to assess word-decoding speed and comprehension. OS400 has 400 items.Columns of words, each word accompanied by four pictures, were presented. Thepupils’ task is to mark one of the pictures illustrating the given word, and the score isthe number of correctly identified words; time limit: 10 minutes. Olofsson (1985)found test–retest reliability (alpha) to be 0.87.

The LS60 (Nielsen

et al

., 1986), a sentence-reading test, was included to assesssilent sentence reading and comprehension. The LS60 consists of 60 sentences/blocks of text with increasing complexity, and the pupils’ task is to mark out oneamong five pictures, corresponding to the given sentence. The score is the number ofcorrectly identified sentences; time limit: 5 minutes, test–retest reliability (alpha),0.93.

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A Spelling Test was composed of Sivertsen’s (1983) 20-word spelling test with theaddition of 12 selected words, all items contextually given. The test consists of amixture of regularly and irregularly spelled words. The regularly spelled wordsinclude more complex words, such as

straks

(immediately) and

elektrisk

(electric). Theirregularly spelled words are based on rules that are common in Norwegian spelling,such as

hvorfor

(why)/

skøyter

(skates), and morphologically derived words such as

uheldig

(unlucky) and

trygt

(safely). The score is the number of correctly spelledwords. Obtained inter-item reliability (alpha) was 0.92.

Vocabulary from the Wisc-R (Wechsler, 1974; Undheim, 1978) and Raven S.P.M.(1983) were used to screen the pupils’ cognitive abilities and included as control vari-ables.

Administration

In the group of struggling readers and spellers, the cognitive tests were given threemonths before the MultiFunk intervention and administered according to manualrecommendations. The reading and spelling tests were given just before and after theintervention, and at follow-up. Classmates were given the OS400 word reading testand the spelling test on pre- and post-test occasions. The tests were administered inblocks of 45 minutes (normal lesson duration in Norwegian schools), and all thepupils were assessed within six days. The order of the tests was the same on all occa-sions: OS400, Spelling and LS60. In addition to the test battery, information wascollected about the struggling pupils’ school motivation, their computer knowledgeand experience of using the MultiFunk software.

Results

The MultiFunk software generated a log file at the end of every session. The log filerecorded pupils’ use of MultiFunk and the program components

screen-adaptations

and

synthetic-speech

. The log files showed on average 26 of 33 days’ use. In spite of theprevious arrangements for the intervention period, some pupils missed MultiFunksessions as a result of interruptions caused by school and classroom projects andprivate holidays. To compensate for pupils’ loss of MultiFunk time, some teachersincreased the length of the sessions. In total, the pupil use was recorded as 96% of theprescheduled time during the intervention (

M

= 11 h 09 min,

st.d

= 1 h 58 min),which has to be considered an optimal outcome in an experimental study in the field.Analyses showed no gender or grade differences on

days

or

minutes of use

, use of

synthetic speech

or

screen adaptations

, recorded by the MultiFunk log files.

Descriptive statistics

The pre-tests were taken just after eight weeks of summer vacation, and showedsignificant differences between the struggling readers and spellers and classmates, onall reading and spelling tests. On the OS400 silent word-reading test, 90% of the

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struggling pupils showed word-reading skills equivalent to the bottom 30% of theclass. The same pattern was observed on the spelling task; 90% of the strugglingpupils spelled less than 18 words correctly, and showed results equivalent to thebottom 20% spellers in the class. No gender or experimental/control group differ-ences showed up on pre-tests, but the mean score showed higher values for thecontrol group on all measured variables. Table 2 reports descriptive statistics at pre-test, and growth scores at post-test and at follow-up.

The summer vacation may have affected the pre-test results, especially in thesample of young struggling readers and spellers, with lower reading skills and reducedinitiative with regard to literacy activities (Cunningham & Stanovich, 1998).

To analyse the effects of the intervention, individuals’ growth scores at post-testand at follow-up were computed by subtracting the pre-test scores from the post-testscores, on the criterion variables. Two different growth scores were computed: G-1;growth in performance at post-test (post-test minus pre-test) and G-2; growth inperformance at follow-up (follow-up minus post-test).

Analyses

The data analyses procedure consisted of several univariate hierarchical multipleregressions, to test the effects of the MultiFunk experimental intervention and thecomponents in the MultiFunk software. Three basic models were made according tothe research questions and available data. The first model was made to examine

Table 2. Descriptive statistics in experimental, Control and classmates comparisons: pretests,

and growth at post-test (G-1), and at follow-up (G-2)

Pre-test Growth

Variables: Experimental Control Classmates comparison

Experimental Control Classmates comparison

OS400:Pre-test 152,2 (35,0) 164,0 (43,1) 225,2 (48,1) — — —

Growth at post-test (G-1) — — — 40,9 (16,0) 24,7 (15,5) 44,4 (21,7)

Growth at follow-up (G-2) — — — 17,5 (17,8) 17,0 (10,7) —

SL60:

Pre-test 30,0 (6,6) 32,7 (8,7) — — — —

Growth at post-test (G-1) — — — 6,5 (3,8) 3,1 (3,5) —

Growth at follow-up (G-2) — — — 4,9 (4,6) 3,2 (2,5) —

Spelling:

Pre-test 10,5 (4,5) 13,2 (5,2) 23,9 (4,9) — — —

Growth at post-test (G-1) — — — 3,0 (1,9) 0,6 (1,9) 0,7 (3,4)

Growth at follow-up (G-2) — — — 1,2 (1,7) 1,5 (2,1) —

(

N

= 26) (

N

= 26) (

N

= 114) (N = 26) (

N

= 26) (

N

= 114)

Note

: Standard deviations in parentheses.

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R. B. Fasting and S.-A. Halaas Lyster

changes in reading and spelling performance as an effect of the MultiFunk experi-mental intervention. The second model was made to evaluate the effect of thesynthetic-speech component. A third model was made to contrast changes in skills inMultiFunk experimentals and controls with classmates, normal readers and spellers.

In the analyses, variables theoretically prior were given a higher priority of entry, topull out adjoining variance due to correlation in covariates, pre-test and the pupils’growth in performance. The beta coefficient (

β

) indicates the direction of the relation,and the squared semipartial regressions coefficients (

R

2

), the proportion of variancecaptured by the predictor after controlling for other components in the model. Theraw regression coefficient (

B

) is used to show differences where it is appropriate. Inall statistical analyses an alpha level of 0.05 was used.

Initial analyses of statistical assumptions were carried out by examining the regres-sions’ residual scatter plots (Tabachnick & Fidell, 2001). No cases tended to be outli-ers or had missing data (

N

= 52).

Analyses of covariates and interactions

Series of regression analyses were conducted to examine the effects of the MultiFunkintervention. To account for gender differences and cognitive variation, gender andthe sub-test Vocabulary Wisc-R (Wechsler, 1974; Undheim, 1978) were used ascovariates. Interactions were analysed by multiplying actual variables (Tabachnick &Fidell, 2001). The present data indicated no reliable effects of covariates or covariateinteractions on any of the computed reading growth scores at post-tests (

p

>0.385).As noted earlier, small sample sizes and skewness in regard to grade reduces powerand, consequently, interactions may have been suppressed.

Main effects in groups of struggling readers and spellers

The main effects of the MultiFunk intervention were analysed through series of hier-archical regressions, using OS400, LS60 and Spelling growth scores as dependentvariables. The first series of analyses examined the growth scores obtained at post-test, G-1. In the model, gender and the cognitive variable were entered in the firststep, then the pre-test measure on the criterion variable and as the third step theMultiFunk experimental/control predictor (i.e. effect of the MultiFunk intervention).The analyses are reported in Table 3.

The analyses showed significant effect of the experimental/control predictor,

p

<0.001, on all measures of growth at post-test (G-1). The covariates obtained nosignificant part of the variance in any of the equations (p>0.138). The analyses indi-cate that the MultiFunk experimental group increased their reading and spelling skillssignificantly more than the control group. Follow-up analyses in the experimentalgroup indicated that the boys showed significantly more progress on the spelling vari-able than the girls, M = 1.5, p = 0.046.

A second series of analyses examined post-experimental effects, using the growthscores obtained at follow-up (G-2). In the regression model, the post-test measure

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Reading remediation and computers 31

on the criterion variable was entered as the second step, to pull out variance due toinitial differences after the intervention, before entering the experimental grouppredictor (step 3). The analyses indicated a significant impact of the control vari-ables, gender and Vocabulary Wisc-R, on the spelling test, p = 0.030. No otherpredictor showed up significantly at follow-up on any tested variable (R2<0.049,

Table 3. Analyses of experimental effects at end-of-intervention and at follow-up: F-values and

obtained variance for relevant predictors

Post-test outcomes Follow-up outcomes

Dependent variables F change R2 change β p F change R2 change β p

OS4001Step 1: Gender and cognitive variables

(2,49) 0.30 0.012 — n.s. 1.81 0.069 — n.s.

1Step 2: Pre-test scores (3,48) 2.27 0.045 0.22 n.s. — — — —1Step 3: Experimental predictor

(4,47) 15.98 0.239 0.50 0.000 — — — —

2Step 2: Post-test scores (3,48) — — — — 0.01 0.000 0.01 n.s.2Step 3: Experimental predictor

(4,47) — — — — 0.00 0.000 0.00 n.s.

Total R2: 0.296 0.69

SL601Step 1: Gender and cognitive variables

(2,49) 1.70 0.065 — n.s. 0.23 0.009 — n.s.

1Step 2: Pre-test scores (3,48) 0.96 0.018 −0.14 n.s. — — — —1Step 3: Experimental predictor

(4,47) 12.19 0.189 0.44 0.001 — — — —

2Step 2: Post-test scores (3,48) — — — — 2.54 0.050 −0.23 n.s.2Step 3: Experimental predictor

(4,47) — — — — 2.60 0.049 0.22 n.s.

Total R2: 0.266 0.109

Spelling1Step 1: Gender and cognitive variables

(2,49) 0.59 0.023 — n.s. 3.77 0.133 — 0.030

1Step 2: Pre-test scores (3,48) 0.57 0.011 −0.12 n.s. — — — —1Step 3: Experimental predictor

(4,47) 20.55 0.294 0.57 0.000 — — — —

2Step 2: Post-test scores (3,48) — — — — 1.53 0.027 −0.18 n.s.2Step 3: Experimental predictor

(4,47) — — — — 0.71 0.012 −0.11 n.s.

Total R2: 0.346 0.172

Note: Total R2 refers to the total proportion of unique variance in growth scores obtained at post-test and growth scores obtained at follow-up, captured by included predictors.1Dependent variable: growth scores obtained at post-test (G-1).2Dependent variable: growth scores obtained at follow-up (G-2).

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32 R. B. Fasting and S.-A. Halaas Lyster

p>0.114). In a follow-up regression, gender and the cognitive covariate were analy-sed in a forward selection, and Vocabulary turned out to be significant, F(1,50) =4.73, R2 = 0.086, p<0.034.

The findings indicate that the intervention had no post-effect on the experimentalpupils’ reading and spelling skills; however, the results showed that the differencesobtained after the intervention were maintained 11 weeks after the interventionended. Only vocabulary had any significant impact on the pupils’ literacy develop-ment between post-test and follow-up.

Detailed analyses of the MultiFunk synthetic-speech program component’simpact on pupils’ growth in reading and spelling were carried out in the experimen-tal group (n = 26). A regression model was made by entering gender and cognitivemeasures in the first step, pre-test scores in the second, Minutes of use in the thirdand pupils’ Use of synthetic-speech as the fourth. In addition, relevant interactioncomponents were included in a forward selection based on gender differences andobserved variation in use (discussed above). The post-test growth scores were usedas dependent variables.

The analyses showed a unique impact of the synthetic-speech program componenton the sentence reading task (SL60), F(5, 20) = 9.56, R2 = 0.254, p = 0.006 and onSpelling F(5, 20) = 8.49, R2 = 0.245, p = 0.009. The beta coefficients indicated thatthe poorest struggling readers and spellers enjoyed using the synthetic-speech featuremore. The findings indicate a significant impact on the poorer struggling pupils’reading and spelling development, by the synthetic-speech program component. Aninteraction component Minutes of use by Synthetic-speech showed up significantly onthe word-reading task OS400, F(6,19) = 6.07, R2 = 0.182, p = 0.023. Follow-upanalyses indicated that pupils, who spent least time with the software used synthetic-speech more than pupils with more time at the computers. No other interactionswere discovered.

The MultiFunk intervention and the Matthew effect

The third research question was addressed to the ‘Matthew’ effect, usually experi-enced by struggling readers and spellers in falling further and further behind theirpeers (Stanovich, 1986). Would the MultiFunk intervention make it possible for theexperimental pupils to keep up with the growth in reading and spelling achievementof their classmates? To examine this developmental issue, two predictor variableswere ‘dummy coded’ (Cohen et al., 2003) to contrast changes in reading and spellingdevelopment in MultiFunk experimentals and controls with classmates. In thismatter, only the pre-test–post-test scores on OS400 and Spelling were available. Inthe regression model, gender and the pre-test variable were entered as the first twosteps, then the contrast variables in the third. The analyses indicated significant influ-ence of the contrast variables on OS400, F(4,161) = 6.16, p = 0.003, and on Spelling,F(4,161) = 3,59, p = 0.030. The slopes of the regression lines in the MultiFunkexperimentals, the controls and the selection of classmates have been plotted inFigure 1.Figure 1. Please supply caption.

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Reading remediation and computers 33

The analyses showed no significant differences in gains between the MultiFunkexperimentals and classmates (p>0.524), but a reliable difference between thecontrols and classmates on OS400, B = –14.61, p = 0.003. A similar trend was foundbetween controls and classmates on the Spelling variable, B = –1.50, p = 0.066. Theanalyses indicated that during the MultiFunk intervention, the control groupobtained significantly lower growth in their reading development, compared to Multi-Funk experimentals and to classmates. A comparable trend showed up on the spellingvariable.

In Figure 1, initial differences between the classmates and the MultiFunk experi-mentals and controls are shown on the y-axis. During the intervention, all groups hadsignificant growth in their reading and spelling skills. The lines indicate parallelgrowth in MultiFunk experimental and classmate comparisons during the interven-tion. On the other hand, the MultiFunk controls had significantly lower growth onpost-tests. The fact that the experimental group initially had a lower mean score onpre-tests may have influenced the outcome, and indicates that the results have to beinterpreted carefully.

Figure 1. Slopes in regression lines in experimental, controls and classmates comparisons.

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34 R. B. Fasting and S.-A. Halaas Lyster

Discussion

The aim of the reported study was to evaluate the MultiFunk assistive reading soft-ware using a field-experimental, pre-test–intervention–post-test design. A group of 26Norwegian poor readers and spellers, in grades 5, 6 and 7, used the MultiFunk soft-ware for seven weeks. Test results were contrasted with control peers and a selectionof classmates, normal readers. The analyses indicated that the present computer tech-nology has the potential to enhance word reading rate and reading comprehension,as well as it seems to support spelling in making orthographic units be retained inmemory, compared to controls.

Research has shown that reading and spelling problems can be observed in a broadrange of pupils (Siegel, 1992). In most pupils with reading problems, well-knowncharacteristics are difficulties in single-word decoding, frequently combined withproblems in writing and spelling (Lyon, 1995; British Dyslexia Association, 1998). Itis suggested that speed and fluency are the core problem for most children with read-ing difficulties (Torgesen et al., 2001), including pupils using ‘semi-shallow’ orthog-raphies such as German (Wimmer et al., 2000) and Norwegian.

In this study, the angle of incidence was to give struggling readers and spellersaccess to texts of current interest, supported by the MultiFunk software technology.It was expected that the MultiFunk software would increase the pupils’ amount ofreading; subsequently, the pupils’ extended experiences with texts would increasetheir reading speed and fluency. In most comparable studies, texts and tasks havebeen carefully selected, pre-programmed and introduced to the pupils in well-designed exercises (Olofsson, 1992; Wise & Olson, 1994; Van Daal & Reitsma, 2000;Wise et al., 2000). In the present study, the struggling readers and spellers chose textsby themselves or on teachers’ recommendations, and the texts were given in anadapted computerized environment. The findings suggest that computerized assistivereading has the potential to improve the basic literacy skills of struggling readers.

Writing text passages in MultiFunk was a supplementary task for pupils who foundbenefit in it, and some used the MultiFunk text editor to summarize texts, and towrite passages with teachers’ feedback. Other pupils simply made some attempts atwriting. The pupils used the synthetic-speech component to read aloud and correctthe text passages. No other spelling feature was included in the software. On post-test,the experimental group had a significantly higher gain on the spelling test than thecontrol group, and the boys showed more progress than the girls (M = 1.5 correctspelled word). This optimistic finding with regard to the male pupils may suggest thatthe technology matched the males’ educational needs, and made it a preventive factorin later reading and spelling failure (for a discussion see Skårbrevik, 2002). A simplesuggestion is that the MultiFunk software activated the males’ general interest intechnology, and made writing (and reading) a more attractive task by the use of thetechnology. A similar trend was found in the Norwegian sample in the OECD–PISAreading study. On texts about technology and science, the male Norwegian pupilsshowed significantly better reading results than on texts concerning literacy experi-ence (Lie et al., 2001).

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Reading remediation and computers 35

The gains obtained on the spelling test do not suggest that computer reading alonesupports the developmental process of spelling, but that the integrated software tech-nology can be a supporting tool in the remediation of pupils’ spelling problems.

The analyses of the synthetic-speech component showed that the more the experi-mental pupils increased their reading skills, the less they were in need of synthetic-speech assistance. On the other hand, the pupils with poorer growth in their abilitiesseemed to benefit from the use of synthetic-speech in spite of its limitations (discussedbelow).

In the evaluation of remedial software or training conditions, a critical matter is toestimate magnitude and length of the intervention. Wise et al. (2000) suggest 250–300 hours, over one to three years, to make significant and lasting growth in below-average readers and spellers (see also Torgesen et al., 1997). Whether all poor readersand spellers need this much training to reach and to maintain adequate skills remainsto be examined. In the present study, the MultiFunk software was used at schools inevery-day sessions for seven weeks. If no positive effects had been experienced duringthe scheduled period of time, it is questionable whether the pupils and teachers wouldhave kept on using the MultiFunk software.

It was expected that the experimental pupils after some training would use theMultiFunk software alone because of its user-friendly interface. This was a falseassumption in the case of most of the pupils. Olofsson, among others, emphasizesreading-impaired pupils’ difficulties in monitoring their own reading (Olofsson,1992; Lundberg, 1995), and the teachers learned that the struggling readers andspellers needed a supporting dialogue to be aware of their reading strategies. Conse-quently, the findings do not suggest that the present computer technology is effectivewithout any supporting teacher.

Another factor that called for the presence of the teachers was some technical weak-nesses in the evaluated software. The scanning component was most sensitive to textrotation and, subsequently, the pupils needed supervising during text scanning.Accordingly, most of the pupils were guided on a group basis during the interventionby preparing and correcting scanned text passages. Initially, a program defect alsoshowed up on some of the computers. After scanning, the synthetic-speech compo-nent read aloud some invisible text-formatting signs, and it took some time before theprogram defect was corrected. The teacher also remarked on the lack of intonation inthe synthetic-speech component, stating for example: ‘The voice has an inanimate,metallic sound’, but the pupils’ comments on the matter were ‘That’s how acomputer ought to speak!’. In addition, every-day matters, such as restrictions atschools, interruptions caused by school and classroom projects, absence and holidays,had an impact on the pupils’ presence in the MultiFunk sessions. All these consider-ations were clearly put forward by the teachers who administered the intervention,and may have reduced the influence of the software. It also calls attention to the diffi-culty in conducting experimental studies in the field involving prototypes andcomputer-based technology.

These technical problems, however, did not overrun the spirit and enthusiasm amongpupils and teachers. The experimental pupils participated in discussions about texts

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36 R. B. Fasting and S.-A. Halaas Lyster

and about how to use the MultiFunk software. And in so doing, they played an activepart in the learning process, and moved to a higher level of learning and knowledgewhen it came to how to understand texts and to solve present problems (Mercer, 1995).A potential Hawthorne effect (Gall et al., 1996) cannot be ruled out, but which of theuncontrolled factors made most impact on the result, the enthusiasm among experi-mental pupils and teachers or the weaknesses in the program, is an unsolved question.

It is also important to underline the individual differences among the strugglingpupils, across teachers, classes and schools, both in gains after the intervention and inmotivation. Some of the pupils were very keen on using MultiFunk even after theintervention was ended, other pupils did not show this enthusiasm. Pupils’ post-inter-views pointed to the classroom teacher as an important factor. It seemed crucial howteachers integrated the use of the MultiFunk software in the pupils’ normal schooland homework. In post-interviews, several of the pupils stressed this aspect as themost motivating factor: ‘I could do my ordinary school work/homework in the Multi-Funk sessions.’ This statement emphasizes the benefit of using reading material ofcurrent interest as the point of departure in resolving struggling pupils’ reading andspelling problems.

To some teachers, the MultiFunk software became an educational tool in theirinteractions with the pupils, and in so doing, the technology became a remedial tutor-ing artefact, guiding the pupils’ construction of knowledge (Mercer, 1995; Leong,1995). This general concept of using computer technology as scaffolding to assist theprocess of learning can be traced to Vygotsky’s notions (1986, 1978) ‘zone of proxi-mal development’ and ‘social reconstruction of knowledge’.

The present technology, however, does not seem to have the same benefit for allpupils. The poorest readers, with severe problems on the basic levels of decoding,may have problems in integrating auditory and visual information given on the screen.In these cases, the technology has to be supported by special selection of texts, guidedby a reading therapist. In pupils who improve their reading performance towardsnormal speed and fluency, the technology will at some point become redundant.Pupils with both these characteristics were present in the study.

In our exploring of the benefit of computer technology, further research has torefine and evaluate the significance of each of the included components, using care-fully selected samples of pupils. Developing computer software to support pupils withdisabilities when it comes to reading and spelling, a synonym vocabulary and anadapted spelling tool, would be highly desirable. Having a suitable range of carefullyselected integrated components available, the hope is that the reading-impairedpupils can turn their focus towards the content of the text. And then, as Olofsson(1992) puts it: ‘perhaps for the first time engage in reading for meaning and thus getthe personal experience of what reading really is about’ (p. 166).

Acknowledgements

This work was supported by the Norwegian Research Council, 2001–4, grant no.138543/220. The authors wish to thank G. Kampsrud, Norwegian Computer Center,

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B. G. Saltnes, Publishing House Aschehoug and A-L. Rygvold, Department ofSpecial Needs Education, University of Oslo, for their valuable contributions to thisstudy. Without the participation of pupils, teachers and principals in six schools inSarpsborg, Norway, the study could not have been conducted. Thanks are extendedto all.

Note

1. The MultiFunk research group is presented in Appendix 1.

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Appendix 1. The MultiFunk computer program

A collaborating research group, financed by the Norwegian Research Council (NorskForskningsråd), developed the MultiFunk computer software. Collaborating partnerswere the publishing house Aschehoug, Education, Norwegian Computing Centreand Department of Special Needs Education, University of Oslo. The Department ofSpecial Needs Education was invited to conduct the evaluation of the MultiFunkcomputer software. The different partners’ unique interests in the MultiFunkresearch project can be summarized as follows:

1. Inquiries from schools and teachers for remedial products and software, support-ing dyslectics and struggling readers’ needs.

2. Interests in exploring the possibilities of computer technology to aid and supportpupils with reading and spelling problems.

3. Interests in developing a range of teaching material and software, supportingdifferent educational levels and groups of pupils.

MultiFunk computer software

The MultiFunk computer software is shown in the screenshot below. All texts aresaved in rtf-file format, and texts are compatible with most word processors.

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