Using tablet computers to teach preschool children to write letters: Exploring the impact of extrinsic and intrinsic feedback

Using tablet computers to teach preschool children to write

letters: Exploring the impact of extrinsic and intrinsic

feedback

Melissa M. Patchan, Cynthia S. Puranik

Georgia State University, 30 Pryor Street, Suite 850, Atlanta, GA 30303, USA

article info

Article history:

Received 13 November 2015

Received in revised form 28 July 2016

Accepted 30 July 2016

Available online 2 August 2016

Keywords:

Emergent writing

Handwriting

Tablet computers

Extrinsic feedback

Intrinsic feedback

abstract

With the increasing popularity of touchscreen devices, using technology to support young

children's learning has become more accessible. However, given the relative novelty of

tablet computers, the research regarding their effectiveness in education is limited. The

current study extends ﬁndings of current research demonstrating that tablet computers

helped students improve writing, reading, and math abilities of elementary students by

examining how tablet computers could support the development of preschool children's

writing ability. We explored the effects of two types of feedback afforded by tablet com-

puters: concurrent, extrinsic feedback (i.e., feedback provided by a tablet computer as soon

as an error was made) and intrinsic feedback (i.e., naturally occurring sensory information

resulting from practicing writing with one's ﬁnger). Preschool children (ages 41e65

months) learned to write eight uppercase letters in small groups three times a week for

eight weeks in one of three ways: paper and pencil, tablet computer and ﬁnger, or tablet

computer and stylus. The number of letters correctly written on a paper-and-pencil

posttest depended on the instructional condition. Those who practiced writing with a

stylus on a tablet computer wrote a similar number of letters correctly at posttest as those

who practiced using paper and pencil. This result suggests that concurrent, extrinsic

feedback did not provide an additional bene ﬁt over the visual feedback in this context.

More interestingly, those who practiced writing with their ﬁnger on a tablet computer

wrote more letters correctly at posttest than those who practiced using a stylus on a tablet

computer. This ﬁnding indicates that an enhanced tactile experience was more beneﬁcial

for learning to write on a tablet computer than increasing the similarity between the

practice tasks and the transfer task. However, whether the use of tablet computers is

superior to practicing with one's ﬁnger on paper worksheets remains an open question.

Several future directions are offered.

1. Introduction

Over the past three decades, more educators and researchers are recognizing the signiﬁcance of the preschool years for the

development of later academic skills. Alarmingly, as many as 35% of children in the United States enter public schools with

* Corresponding author.

E-mail addresses: [email protected] (M.M. Patchan), [email protected] (C.S. Puranik).

Contents lists available at ScienceDirect

Computers & Education

journal homepage: www.elsevier.com/locate/compedu

http://dx.doi.org/10.1016/j.compedu.2016.07.007

Computers & Education 102 (2016) 128e137

such low levels of skills and motivation that they are at substantial risk of early academic difﬁculties (Boyer, 1991; Zill & West,

2001). These early academic difﬁculties have serious, long-term consequences. For example, children who experience early

difﬁculties in learning to read and write are likely to continue experiencing problems with reading and writing throughout

their school years (Aram & Levin, 2004; Felton, 1998; Shatil, Share, & Levin, 2000), and these problems permeate into

adulthood (Bruck, 1998). Thus, the broad goal of the current study is to consider how the ways we provide support to young

children shape their development.

1.1. Supporting learning with technology

Many children are exposed to technology at an early age, and exposure to mobile devices in particular is growing across the

world. For example, access to mobile devices in the homes of US families with young children is increasingdmobile device

usage increased by 23% from 52% in 2011 to 75% in 2013, and speciﬁcally tablet computer usage increased by 32% from 8% in

2011 to 40% in 2013 (Rideout, 2013). Moreover, as reported by Rideout (2013), children were using mobile devices for longer

periods of time (45 min a day in 2011 to 67 min a day in 2013). Children have similar access to technology in schoolsd81% of

US PreK-12 teachers reported using personal computers or laptops in their classroom, 58% using interactive whiteboards, and

52% using tablet computers (PBS LearningMedia, 2015). Given the pervasiveness of technology in young children's lives, we

are particularly interested in how technology can support young children's developmentdand more speciﬁcally, emergent

writing.

Prior research on technology beneﬁts in preschool classrooms in the US, Australia, and Greece has demonstrated that

computers can be used to improve a variety of skills, including early literacy skills and early mathematical skills (Moxley,

Warash, Coffman, Brinton, & Concannon, 1997; Shute & Miksad, 1997; Vernadakis, 2005). These beneﬁts have been attrib-

uted to several features afforded by technology, including computer animations, immediate and targeted feedback, increased

locus of control, and increased engagement with the instructional material (R. Shute & Miksad, 1997).

With the introduction of Apple's iPad in 2010, the popularity of tablet computers in educational institutions has increased

in many countries including, the US, United Kingdom, Australia, New Zealand, and South Korea (W. Clark & Luckin, 2013;

Heinrich, 2012; Henderson & Yeow, 2012; Johnson, Adams Becker, Estrada, & Freeman, 2015; Neumann & Neumann, 2013,

2015; Plumb, Kautz, & Tootell, 2013; Saenz, 2011). However, as noted in these reviews, research regarding the effective-

ness of tablet computers in education is limited given the novelty of the technology.

Prior research has demonstrated how tablet computers could be used in the classroom (Beschorner & Hutchison, 2013;

Hutchison, Beschorner, & Schmidt-Crawford, 2012). For example, in Norway, preschool children used tablet computers to

create digital books, and teachers used tablet computers to check the weather during their opening routine (Sandvik,

Smerdal, & Osterud, 2012). Prior research also examined the usability of tablet computers with young children, ﬁnding

that children from a London nursery school interacted with the technology in ways that differed from the interactions with

traditional materials (Crescenzi, Jewitt, & Price, 2014). Although several gains and losses associated with tablet computers

were identiﬁed, tablet computers in general promoted an increase in mark making similar to traditional materials with

images (Price, Jewitt, & Crescenzi, 2015). Overall children from a primary school in the UK were able to easily execute a variety

of touch-screen gestures (e.g., ‘ click’, ‘slide’, ‘

swipe’), however they had some difﬁculty with others that typically involved

timing, like ‘select’, ‘long click’, and ‘double-click’ (McKnight & Fitton, 2010). These children also experienced problems with

unintentional movements and touches. Despite numerous technical issues, US children as young as preschool were not easily

frustrated, and many children commented that using the tablets was easier than using traditional materials (Couse & Chen,

2010).

Surprisingly, only two studies to date have empirically tested the effectiveness of using tablet computers for instruction. In

fourth through ninth grades located in the US, students with diagnosed speciﬁc learning disabilities signiﬁcantly improved

their handwriting, spelling, and syntax abilities after completing 36 h of writing lessons on tablet computer (Berninger, Nagy,

Tanimoto, Thompson, & Abbott, 2015). In ﬁrst and second grades located in the US, students showed greater improvement in

both reading and math when tablet computers were incorporated into their lessons (McKenna, 2012).

Although these initial results look promising, more research is needed to determine if and how tablet computers support

learning. In the current study, we explore two types of feedback that are likely to support learning to write letters with tablet

computers: 1) scaffolding and extrinsic feedback and 2) intrinsic feedback. Furthermore, we consider the importance of task

similarity for transfer to other classroom activities.

1.2. Scaffolding & extrinsic feedback

Scaffolding and feedback are often seen as critical components to the learning process (Chi & Wylie, 2014; Hattie &

Timperley, 2007; Kluger & DeNisi, 1996; Koedinger, Corbett, & Perfetti, 2012; Nelson & Schunn, 2009; Shute, 2008;

VanLehn, 2011; Wood, Bruner, & Ross, 1976). Despite the importance of scaffolding, this one-on-one instruction is often

impractical in classroom settings. Rather than adjusting the level of scaffolding to match an individual child, the teacher must

try to meet the needs of multiple children simultaneously. For example, preschool teachers tended to utilize low support

strategies that were less suitable for children who struggle with a task (Pentimonti & Justice, 2009).

Provided the continual advancements in technology, researchers have been investigating how technology in general can

be used in the classroom to support learning and deliver more individualized, one-on-one instruction (for a recent review, see

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137 129

Van der Kleij, Feskens, & Eggen, 2015). Using theories of learning and cognition as well as observations of human tutors,

computer tutors have been used to improve a variety of skills throughout the elementary grades, including mathematics

(Arroyo, Beck, Beal, Wing, & Woolf, 2001; Hwang, 2003; Rau, Aleven, & Rummel, 20 09, Rau, Aleven, & Rummel, 2012), literacy

(Kegel & Bus, 2012; Mayo, Mitrovic, & McKenzie, 2000; Steinhart, 2001), and science (Luckin & du Boulay, 1999).

Information provided by an external source (coming or operating from outside) during and after one performs a task, is

often referred to as extrinsic or augmented feedbackdhenceforth referred to as ‘ feedback’ (Schmidt & Wrisberg, 2008). This

type of feedback differs from visual feedback, which also derives from an external source. Unlike extrinsic feedback, visual

feedback occurs naturally, and it requires some internal processing before the learner detects an error. Therefore, visual

feedback is considered to be a form of intrinsic feedback rather than extrinsic feedback. The conditions that inﬂuence

feedback effectiveness are complex, and speciﬁc features of effective feedback have been largely disputed (for a review, see

Mory, 1996, 2004).

One such factor is the timing of feedback. From a reinforcement perspective, feedback that closely follows a response

would be most effective, however, it is unclear how closely the feedback should follow the response. Although several studies

have found that a delay in feedback was effective, these effects might be limited to special experimental circumstances

(Dempsey, Driscoll, & Swindell, 1993; Kulhavy, 1977; Kulik & Kulik, 1988). For the acquisition of motor skills, immediate

terminal feedback (i.e., feedback that is provided immediately after completing a task) can be effective, however, there is a risk

that learners will become dependent on the feedback and struggle when feedback is no longer available (Schmidt, Young,

Sinnen, & Shapiro, 1989). Similarly, concurrent feedback (i.e., feedback that is provided during the actual motor action) has

improved performance during the practice of motor skills and with computer tutors (Dyer, Stapleton, & Rodger, 2015;

Mononen, 2007; Schmidt, 1997; VanLehn, 2011). However, as with the immediate terminal feedback, a learner might

become overly dependent on the feedback and perform even worse on posttests than those who practiced without this

feedback (Schmidt, 1997). A recent review of the effects of concurrent feedback revealed that it was not possible to make any

general conclusions about the efﬁciency of concurrent feedback (Sigrist, Rauter, Riener, & Wolf, 2013). Although earlier

studies found that concurrent feedback was less helpful for simple tasks, more recent studies found that concurrent feedback

was more helpful for complex tasks, especially when provided earlier in the learning process.

Given the importance of scaffolding and extrinsic feedback in tutoring and for young children in particular, we wanted to

further examine how these supports provided by educational technology could shape preschool children's writing devel-

opment. The ﬁndings about concurrent, extrinsic feedback in particular inform our ﬁrst hypothesis.

Hypothesis 1.

Concurrent, extrinsic feedback will best support young children’s writing development, such that preschool children

who receive feedback from a tablet computer as soon as an error is made while practicing writing uppercase letters will write more

letters correctly on a paper and pencil, letter writing task at posttest than those who did not receive this concurrent, extrinsic

feedback (see Fig. 1-H1).

To make this comparison more robust, we compared students who practiced writing using a stylus versus pencil. Thus,

differences between these conditions could be attributed to the feedback provided by the tablet computers rather than the

utensils needed to perform the task s (Clark, 1983).

1.3. Intrinsic feedback

Learning how to write is unique from learning to read or learning math in that it includes a motor component. For

handwriting, success requires visual information about the letter (i.e., orthography), ﬁne motor control, as well as visual-

motor integration. Given the need to coordinate information from multiple senses while writing, intrinsic feedback is also

likely to be important. Intrinsic feedback refers to the naturally occurring sensory information resulting from movement

(Schmidt & Wrisberg, 2008). There are two types of intrinsic feedback. First, exteroception refers to feedback from sources

outside of the body or at a distance from the body. For example, visual feedback would result from seeing the product of one's

pencil stylus stylus finger stylus finger stylus finger

Extrinsic

Feedback

Intrinsic

Feedback

Tas k

Similarity

Both

# of letters correctly written

H2a H2b H2cH1

Fig. 1. Predictions for hypothesis 1 and hypothesis 2.

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137130

writing. Second, proprioception refers to feedback that occurs inside the body. For example, kinesthetic feedback would result

from feeling one's hand move in a particular direction while writing.

Evidence demonstrating how even expert writers rely on this intrinsic feedback can been seen in studies that varied paper

smoothness. For example, adults experienced difﬁculty writing on surfaces with low friction (e.g., coated paper), which

resulted in writing slower with more pressure (Chan & Lee, 2005; Wann & Nimmo-Smith, 1991). Similar difﬁculties could

occur when writing on tablet computersdthat is, using a plastic or rubber tipped stylus on the smooth surface would likely

produce very little friction. Indeed, legibility was reduced when writing with a stylus on a tablet computer compared to

writing with paper and paper (Alamargot & Morin, 2015). Moreover, the more experienced writers (i.e., ninth grade students)

adjusted for this difﬁculty by writing faster and using more pressure, while the less experienced writers (i.e., second grade

students) paused longer between strokes. How these adjustments might affect children just learning to write is still unclear.

These studies inform our hypothesis that young children's writing development may be best supported while using their

ﬁnger on tablet computersdthat is, children using their ﬁnger on tablet computers will not only experience similar visual and

kinesthetic feedback as those writing with a pencil on paper, but they will also have an enriched tactile experience. The

additional proprioception information (i.e., haptic feedback) resulting from direct contact of one's ﬁnger while writing is also

expected to strengthen one's memory of the letter in comparison to the sensation that would be mediated by a pencil or

stylus. Moreover, using one's ﬁnger rather than a stylus would likely result in more friction, and thus change the intrinsic

information available while writing. For young children, using a stylus could result in longer pauses between strokes and

possibly disrupt connections between the visual and haptic information.

One possible limitation to practicing writing with a ﬁnger would be how well the skill transfers to other writing activities

that involve writing with a utensil, such as a pencil. The success of transfer often depends on the overlapping units between

the learning task and the transfer task (Anderson & Singley, 1993; Kieras & Bovair, 1986; Taatgen, 2013; Thorndike &

Woodworth, 1901). For novel and complex situations, both adults and children tend to focus on surface similarities, which

leads to poor transfer on tasks that have a similar underlying structure but differ on the surface (Anderson,1987; Brown,1988;

Chi, Feltovich, & Glaser, 1981). Although explicit training or instruction that encourages reﬂection upon relational similarities

can improve the probability of transfer, this training is often less successful with young children (Bransford, Brown, & Cocking,

2003; Chen & Klahr, 2008). These ﬁndings inform our hypothesis that young children's development of handwriting may best

be supported while using a stylus on tablet computers.

We therefore contrasted ways to use tablet computers: one that emphasized an enriched tactile experience (i.e., using a

ﬁnger) and one that emphasized the similarity to other classroom writing activities (i.e., using a stylus). Three hypotheses

emerged from this prior research:

Hypothesis 2a.

Intrinsic feedback (i.e., enriched tactile experience resulting from direct contact of one’s ﬁnger while writing) is

more important to young children’s development than task similarity, such that preschool children who practice writing uppercase

letters using their ﬁnger will write more letters correctly on a paper and pencil, letter writing task at posttest than those who

practice writing using a stylus (see Fig. 1-H2a).

Hypothesis 2b.

Task similarity is more important to young children’s development than intrinsic feedback, such that preschool

children who practice writing uppercase letters using a stylus will write more letters correctly on a paper and pencil, letter writing

task at posttest than those who practice writing using their ﬁnger (see Fig. 1-H2b).

Hypothesis 2c.

Both intrinsic feedback and task similarity are equally important to young children’s development, such that

preschool children who practice writing uppercase letters using their ﬁnger will write the same number of letters correctly on a

paper and pencil, letter writing task at posttest as those who practice writing using a stylus (see Fig. 1-H2c).

2. Method

2.1. Participants

Participants were recruited from 10 classes in six preschools. A range of socioeconomic status (SES) backgrounds was

represented. Two preschools were low-SES with more than 75% of the students receiving subsidiaries, one preschool was

mid-SES with 25e4 9% of the students receiving subsidiaries, and three preschools were high-SES with less than 25% of the

students receiving subsidiaries.

As part of the screening process, a pretest assessing children's letter knowledge was administered to all the children in

attendance. To be eligible for participation, children had to demonstrate that they were just beginning to write using con-

ventional letters, which was determined using two criteria. First, since instruction involved teaching children to write eight

target letters, children who were able to write most of the letters at pretest (i.e., more than 18 letters) were not eligible to

participate. Out of the 113 preschool students who were screened, 84 students met this requirement. Second, children should

be able to write at least three letters at pretest or correctly name at least 17 letters at pretest. A total of 65 students met both

requirements. Because instruction was provided in small group format, groups of two or three children were formed from

these potentially eligible children. Children from the same preschool were matched with other children who had no prior

writing knowledge of the same eight target letters. Children whose writing knowledge did not overlap with any of the other

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137 131

eligible children in their school were excluded from the study. This selection process resulted in a total of 54 participants in 21

small groups.

Each small group was randomly assigned to one of the three conditions: iPad ﬁnger, iPad stylus, and paper and pencil.

During the eight weeks of instruction, eight children moveddfour from the iPad ﬁnger condition, two from the iPad stylus

condition, and two from the paper and pencil condition. Thus, of the 46 participants who completed the study, 16 children

practiced writing with an iPad and their ﬁnger, 14 children practiced writing with an iPad and a stylus, and 16 children

practiced writing with paper and pencil. These participants ranged in age from 41 months to 65 months (M ¼ 51.9, SD ¼ 5.4)

with 57% of the children being female. The sample included 4 8% Caucasians, 46% African-Americans, 4% Hispanic, and 2%

Asian.

2.2. Measures & coding process

Prior to and following the instruction period, all participants completed two individual assessments: letter naming and

letter writing. Assessments were conducted in the students' classroom using paper and pencil and took approximately 15 min

per child. The assessments were administered and scored by trained research assistants (RAs).

2.2.1 Letter naming. To measure children's letter naming knowledge, they were asked to name all 26 letters of the al-

phabet presented individually in a random order. The letter naming score was the number of correct responses out of 26.

2.2.2 Letter writing. To measure children's letter writing knowledge, they were asked to write the uppercase form of each

letter presented verbally in a random order. The letter writing score was the number of correctly written letters. A letter was

considered correct if it demonstrated complete or partial knowledge (e.g., reversal or inverted letters, missing or extra

strokes) of the letter. To examine scoring ﬁdelity, 15% of the writing assessments were double-coded. Inter-rater reliability

was high (90% agreement).

2.3. Procedure

Trained RAs provided instruction to the children three times a week for eight weeks. A different letter was taught each

week for a total of eight target letters. Each of the 21 small groups was taught a different set of eight letters depending on the

letter writing knowledge of the children in the group. Across the small groups, all 26 letters of the alphabet were taught. To

conﬁrm that this variation was not confounded by condition, the average letter writing difﬁculty was calculated for each

participant using the difﬁculty parameter (i.e., higher values represent more difﬁcult letters) estimated by Puranik, Petscher,

and Lonigan (2012). A one-way, between-subjects ANOVA revealed that there was a signiﬁcant difference between the

conditions, F (2, 32) ¼ 7.22, p ¼ 0.002. Least Signiﬁcant Difference (LSD) post-hoc tests conﬁrmed that children in the paper

and pencil condition were taught easier letters than the iPad stylus condition (see Fig. 2). This difference only sets a high bar

for the experimental conditions.

Each lesson lasted approximately 20 min. The lesson began with the RA introducing or reviewing the letter of the week,

including the name, sound (along with several words that begin with the letter sound), and how to write the letter. The RA

modeled writing the letter three times while verbally describing the strokes. To model writing for all three conditions, the RA

used a dry erase marker and a large laminated poster that was propped up on an easel.

Then the children practiced writing the letter for 5 min. Participants in the iPad conditions used the Writing Wizard app by

L'Escapadou. After the appropriate letter was selected, the app ﬁrst modeled how to write the letter, and then the child

attempted to write the letter. If the child strayed too far from the model, the app stopped the child and provided scaffolding by

placing an arrow where the student should restart. Upon successful completion of the letter, the child touched the refresh

button to try again. The app also provided the option to hide the model so that the children could practice writing freehand.

Those in the iPad ﬁnger condition practiced writing with their ﬁnger, while those in the iPad stylus condition practiced

writing with a chunky stylus that resembled a fat pencil commonly used with preschoolers. Participants in the paper and

0.0

0.1

0.2

0.3

0.4

0.5

paper and pencil iPad stylus iPad finger

letter difficulty

p < .001; d = 1.14

p = .06; d = 1.27

p = .06; d = 0.63

Fig. 2. Average letter instruction difﬁculty by condition.

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137132

pencil condition practiced writing the letter using worksheets typical of preschool writing instruction that were created using

an add-on feature of the Alphabet Tracing app by FunLittleApps. Practice involved both tracing model letters as well as writing

the letter freehand. During this practice, the RA spent most of her time keeping the children focused on the task. For example,

children in the paper and pencil condition needed encouragement to continue writing, whereas children in the iPad con-

ditions needed reminders to push the refresh button after completing the letter. Occasionally, children needed help with

forming the letters, and the RA was careful to provide similar support across the conditions. This support typically involved

repeating the verbal instructions that described the strokes in the letter and pointing where to start.

After the children ﬁnished the ﬁrst writing session, they completed a supplemental activity that either focused on the

letter name (e.g., identifying the target letter among foil letters by tapping it with a ﬂy swatter), the letter sound (e.g., creating

‘My Alphabet Books’ by pasting pictures that started with each target letter sound), or the letter shape (e.g., using bingo

daubers to ﬁll in the letter on a worksheet). Then the children practiced writing for ﬁve more minutes. At the conclusion of the

lesson, the RA reviewed the letter name, letter sound, and verbal instructions describing how to form the letter.

Within one week of the last writing lesson, the children again completed the letter naming task and the letter writing task.

These posttests were conducted individually in the students' classroom using paper and pencil.

3. Results

A series of one-way, between-subjects ANOVAs revealed no preexisting differences between the instructional conditions

on any of the pretest measures nor were there differences in age or gender. Chi-Square tests also revealed no differences in

SES or ethnicity. The only variables signiﬁcantly correlated with the posttest letter writing scores were the pretest letter

naming scores, r (44) ¼ 0.42, p < 0.001, and the pretest letter writing scores, r (44) ¼ 0.33, p < 0.001. Therefore, we included

these measures of pretest as covariates.

A between-subjects ANCOVA revealed that there was a signiﬁcant difference between the conditions for the posttest letter

writing score, F (2, 41) ¼ 7.07, p ¼ 0.002. LSD post-hoc tests were used to test our hypotheses. Hypothesis 1 was not sup-

porteddchildren in the stylus condition wrote a similar number of letters correctly as children in the paper and pencil

condition (see Fig. 3-H1). Hypothesis 2a was supporteddchildren in the iPad ﬁnger condition wrote more letters correctly

than children in the iPad stylus condition (see Fig. 3-H2). This pattern of results was also consistent when analyzed without

the covariates. A between-subjects ANCOVA revealed that there was no signiﬁcant differences between the conditions for the

posttest letter naming score (M ¼ 5.9; SD ¼ 2.3), F (2, 41) ¼ 1.55, p ¼ 0.22.

A one-way, between-subjects ANOVA of the average number of practice trials per letter conﬁrmed that these differences

were not just the result of more practice (see Fig. 4). The children in the paper and pencil group practiced writing each letter

more often than children in both iPad conditions, and there was not a signiﬁcant difference between the iPad conditions, F (2,

43) ¼ 42.9, p < 0.001.

4. Discussion

The goal of the current study was to consider how technology could support young children's emergent writing skills. In

particular, only a few prior studies empirically tested the effectiveness of using tablet computers for instruction and found a

beneﬁt for students in ﬁrst through ninth grades in writing, reading, and math (Berninger et al., 2015; McKenna, 2012). The

current study provides additional support for using tablet computers to teach preschool children how to write their up-

percase letters. We further examined the inﬂuence of two factors afforded by tablet computers (i.e., extrinsic and intrinsic

feedback) on the development of children's writing ability.

First, we expected that the concurrent, extrinsic feedback provided by a tablet computer would best support preschool

children learning to write uppercase letters because it was provided while the child was still thinking about the form of the

paper and pencil iPad stylus iPad finger

# of letters correctly written

H1: d = .29

H2: d = .98

Fig. 3. Average number of correctly written letters by condition for hypothesis 1 (H1) and hypothesis 2 (H2).

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137 133

letter. As suggested by recent research on motor learning, correcting errors as they occur could help a child adjust his or her

mental representation of that letter and support performance during the early learning process (Sigrist et al., 2013). Sur-

prisingly, this hypothesis was not supporteddthe children in the iPad stylus condition wrote a similar number of letters

correctly at posttest as the children in the paper and pencil condition. Perhaps, additional extrinsic feedback might not be

necessary to support the development of writing skillsdthat is, the visual feedback the children experienced when they saw

that their letters strayed from the model while tracing might be sufﬁcient. Additionally, by providing feedback as soon as an

error was made, the tablet computer could have disrupted the encoding process. Therefore, although the feedback might have

corrected formation errors, it might have also caused inefﬁcient learning. Perhaps, receiving feedback after completely

writing a letter would have been more helpful than being interrupted as soon as a mistake was made.

Second, we examined whether intrinsic feedback or the task similarity better supported children's learning. The results

supported hypothesis 2adchildren in the iPad ﬁnger condition wrote more letters correctly at posttest than the children in

the iPad stylus condition. This result suggests that enhancing a child's tactile experience during learning was more beneﬁcial

than increasing the similarity between the practice tasks and the transfer task . The success of transferring knowledge or skills

from the learning task to a transfer task often depends on the overlapping units between the two tasks (Anderson & Singley,

1993; Kieras & Bovair,1986; Taatgen, 2013; Thorndike & Woodworth, 1901). However, in this context, task similarity was not a

critical factordthat is, using a stylus, which is more similar to the other writing utensils used in the classroom (e.g., pencils,

crayons, markers), did not help children write more letters correctly on a posttest that involved paper and pencil. This ﬁnding

suggests that the critical component for handwriting is something different than the particular motor movement differences

between using a stylus and ﬁnger.

More important for this context was the child's tactile experience. This ﬁnding relates to theories of embodied cognition,

also known as ‘grounded’ or ‘situated’ cognition, which postulate that knowledge stored in memory contains rich, multimodal

representations, and all of these representations are reactivated when a particular concept is retrieved (Barsalou, 2008;

Barsalou, Simmons, Barbey, & Wilson, 2003). Several studies have supported this embodiment of writing knowledge

(Kiefer & Trumpp, 2012). Recent research has supported the use of multisensory letter training for improving handwriting

(Bara & Gentaz, 2011; Labat, Ecalle, Baldy, & Magnan, 2014; Vinter & Chartrel, 2010). In addition, children made greater gains

from learning to write using paper and pencil than typing on a keyboard (Kiefer et al., 2015; Longcamp, Zerbato-Poudou, &

Velay, 2005). These studies suggest that haptic or kinesthetic perception has an effect on learning to write. Indeed, Yu, Howe,

and Hinojosa (2012) found that haptic perception (i.e., sense of touch) inﬂuenced children's handwriting speed, while

kinesthetic perception (i.e., sense of movement and position) inﬂuenced children's handwriting legibility.

Further evidence was provided in several fMRI studies. Although children were equally likely to recognize a letter after

either practicing writing the letter or observing a teacher write the letter, connections to sensori-motor networks only

developed after active motor experiences in which children practiced writing (Kersey & James, 2013). Similarly, activation in

brain regions associated only with reading occurred after handwriting training but not after typing or tracing (James &

Engelhardt, 2012). In these multi-sensory tasks, additional sensory-motor information is likely to be encoded along with

the visual form information, and these multiple types of information can strengthen one's memory of the letter (Guan, Liu,

Chan, Ye, & Perfetti, 2011).

However, in the current study, there is only a subtle difference between using a stylus and using a ﬁnger. Both conditions

have similar visual and kinesthetic input as well as some form of tactile input. With the stylus, input is collected by pushing or

pulling the stylus in a particular direction, whereas with the ﬁnger, input is collected through friction. Perhaps this input from

the ﬁnger is richer than the input from the stylus. Alternatively, surfaces with low friction can make writing more difﬁcult for

even more experienced writers (Alamargot & Morin, 2015; Chan & Lee, 2005; Wann & Nimmo-Smith, 1991). As indicated by

past research with second grade students, when using a stylus, children are more likely to pause longer between strokes,

which may have disrupted the connection between the visual and haptic information. The visual information might be better

combined with the haptic information when the ﬁnger directly touches and follows the letter's shape rather than indirectly

with the stylus. Thus, the richer information and better connection between the visual and haptic information from using

one's ﬁnger while practicing writing could strengthen one's memory of the letter (Guan et al., 2011).

100

120

140

160

180

paper and pencil iPad stylus iPad finger

number of practice trials per letter

n.s.

d = 2.5

Fig. 4. Average number of practice trials per letters by condition.

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137134

4.1. Limitations & future directions

One limitation to the current study is the relatively small sample size (i.e., 46 participants across three conditions). Despite

this lower sample size, signiﬁcant differences between the conditions were observed. However, signiﬁcant effects may also

have been missed. For example, although the difference between the iPad stylus condition and the paper and pencil condition

was not statistically signiﬁcant (indicating that concurrent, extrinsic feedback was not helpful in this context), the effect size

indicated a small effect, which might be practically important. Perhaps a larger sample would reveal a signiﬁcant difference.

Furthermore, a lower sample size limited our ability to examine whether SES moderated the effects. Given that lower SES

students tend to perform at lower levels than higher SES students, these students might beneﬁt more from concurrent,

extrinsic feedback. Similarly, the beneﬁt of using one's ﬁnger while practicing writing may be stronger for the lower SES

students. We also did not collect data on the students' phonological awareness at pre-test which has been shown to positively

contribute to letter writing (Puranik, Lonigan, & Kim, 2011).

Additionally, in the current study, participants were not screened for learning disabilities, or attention deﬁcit hyperactivity

disorder, which could be factors that inﬂuence potential learning gains. Because the participants were randomly assigned to

conditions, the likelihood that these factors confounded the ﬁndings is minimal. Future research should examine these

populations speciﬁcally.

Finally, the current study did not examine the effects of writing practice that involves an enriched tactile experience without

the concurrent, extrinsic feedback (e.g., tracing letters in colorful substances or writing in sand). To further isolate the impor-

tance of the tactile experience from the additional beneﬁts of the tablet computers, future research could incorporate a tactile

handwriting task that does not involve technology. For example, similar writing instruction could involve worksheets rather

than a tablet computer, and if the tactile experience continues to be an important factor, we would expect similar differences for

those children who traced letters with their ﬁnger versus those who used a pencil. Furthermore, the amount or quality of the

tactile sensation could be manipulated by using different materials (e.g., paper vs. sandpaper) to better understand the degree to

which haptic perception supports learning. Future research could also explore the beneﬁts of multisensory learning. Are other

senses just as supportive as the sense of touch (e.g., sound vs. touch)? Is there an additive effect to multisensory instruction (e.g.,

sound þ touch vs. touch only)? Do these beneﬁts depend on the nature of the task or skill being learned?

The ﬁnding that children who received concurrent, extrinsic feedback did not write more letters correctly than those who

did not receive this type of feedback was somewhat surprising. Although early research has found that the beneﬁt of con-

current, extrinsic feedback did not extend to tasks without that feedback (Schmidt, 1997), more recent research suggests that

concurrent, extrinsic feedback could be more bene ﬁ cial earlier in the learning process compared to later in the learning

process (Sigrist et al., 2013). For preschool children who are just learning to write, concurrent feedback could guide their

movements, help minimize errors, and possibly prevent cognitive overload. However, future research should further examine

how to best fade this type of feedback so that children are able to successfully write without continuous support (e.g., when

should concurrent feedback transition to terminal feedback?). Given the advances in technology, tablet computers could

easily support this adaptive learning environment.

Future research should examine how technology, and tablet computers in particular, supports learning among other

populations. For example, given that technology can increase students' motivation and help sustain their attention, in-

struction utilizing tablet computers could be especially useful for teaching children with disabilities.

4.2. Conclusion

The current study explored two aspects of tablet computers that could support young children's developmentdthat is,

providing concurrent, extrinsic feedback as well as intrinsic feedback through an enriched tactile experience. In the context of

learning to write uppercase letters, the concurrent, extrinsic feedback did not provide an additional beneﬁt. There was no general

beneﬁt of tablet computer-based training. However, the intrinsic feedback made salient by the enriched tactile experience did

enhance children's learning. There was a beneﬁt of practicing writing with one's ﬁnger on a tablet computer. Whether the use of

tablet computers is superior to ﬁnger writing on paper worksheets remains an open question. Importantly, more practice was not

necessarily better. Although children who practiced with a paper and pencil wrote each letter almost three times more than

children who practiced with the tablet computers (i.e., 142 vs. 48), they did not perform better at posttest. Clearly more work is

warranted in understanding how tablet computers can be used effectively to enhance instruction.

Acknowledgements

Support for this research was provided by the Central Research Development Fund at the University of Pittsburgh. The

opinions expressed are those of the authors. We would like to thank Sarah Jacobson, Brittany Kachline, Mary Sears, and Kelly

Stasik for their help with this project.

References

Alamargot, D., & Morin, M. F. (2015). Does handwriting on a tablet screen affect students' graphomotor execution? A comparison between Grades Two and

Nine. Human Movement Science, 44,32e41. http://dx.doi.org/10.1016/j.humov.2015.08.011.

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137 135

Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem solutions. Psychological Review, 94(2), 192e210. http://dx.doi.org/10.1037/

0033-295X.94.2.192.

Anderson, J. R., & Singley, M. K. (1993). The identical elements theory of transfer. In J. R. Anderson (Ed.), Rules of the mind (pp. 183e204). Hillsdale, NJ:

Lawrence Erlbaum Associates, Inc.

Aram, D., & Levin, I. (2004). The role of maternal mediation of writing to kindergarteners in promoting literacy in school: A longitudinal perspective.

Reading & Writing, 17(4), 387e409. http://dx.doi.org/10.1023/B: READ.0000032665.14437.e0.

Arroyo, I., Beck, J. E., Beal, C. R., Wing, R., & Woolf, B. P. (2001, May). Analyzing students' response to help provision in an elementary mathematics intelligent

tutoring system. Paper presented at the 10th International Conference on Artiﬁcial Intelligence in Education (AIED), San Antonio.

Bara, F., & Gentaz, E. (2011). Haptics in teaching handwriting: The role of perceptual and visuo-motor skills. Human Movement Science, 30(4), 745e759.

http://dx.doi.org/10.1016/j.humov.2010.05.015.

Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59,617e645. http://dx.doi.org/10.1146/annurev.psych.59.103006.093639.

Barsalou, L. W., Simmons, W. K., Barbey, A. K., & Wilson, C. D. (2003). Grounding conceptual knowledge in modality-speciﬁc systems. TRENDS in Cognitive

Science, 7(2), 84e91. http://dx.doi.org/10.1016/S1364-6613(02)00029-3.

Berninger, V. W., Nagy, W., Tanimoto, S., Thompson, R., & Abbott, R. D. (2015). Computer instruction in handwriting, spelling, and composing for students

with speciﬁc learning disabilities in grades 4 to 9. Computers & Education, 81,154e168. http://dx.doi.org/10.1016/j.compedu.2014.10.005.

Beschorner, B., & Hutchison, A. (2013). iPads as a literacy teaching tool in early childhood. International Journal of Education in Mathematics, Science and

Technology, 1(1), 16e24.

Boyer, E. L. (1991). Ready to learn: A mandate for the nation. Princeton, NJ: Carnegie Foundation for the Advancement of Teaching.

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2003). How people learn: Brain, mind, experience, and school. Washington D.C: National Academy Press.

Brown, A . L. (1988). Preschool children can learn to transfer: Learning to learn and learning from example. Cognitive Psychology, 20(4), 493e523. http://dx.

doi.org/10.1016/0010-0285(88)90 014-X.

Bruck, M. (1998). Outcomes of adults with childhood histories of dyslexia. In C. Hulme, & J. R. Malatesha (Eds.), Reading and spelling: Development and

disorders (pp. 179e200). Mahwah, NJ: Erlbaum.

Chan, A. H., & Lee, P. S. (2005). Effects of different task factors on speed and preferences in Chinese handwriting. Ergonomics, 48

(1), 38e54. http://dx.doi.org/

10.1080/00140130412331303902.

Chen, Z., & Klahr, D. (2008). Remote transfer of scientiﬁc reasoning and problem solving strategies in children. In R. V. Kail (Ed.), Advances in child

development and behavior (Vol. 36, pp. 419e470). Amsterdam: Elsevier.

Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Psychology, 5(2),

121e152. http://dx.doi.org/10.1207/s15516709cog0502_2.

Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219e243.

http://dx.doi.org/10.1080/00461520.2014.965823.

Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53(4), 445e 459. http://dx.doi.org/10.3102/

00346543053004445.

Clark, W., & Luckin, R. (2013). What the research says: iPads in the classroom. Retrieved from London Knowledge Lab website: http://

digitalteachingandlearning.ﬁles.wordpress.com/2013/03/iPads-in-the-classroom-report-lkl.pdf.

Couse, L. J., & Chen, D. W. (2010). A tablet computer for young children? Exploring its viability for early childhood education. Journal of Research on

Technology in Education, 43(1), 75e98. http://dx.doi.org/10.1080/15391523.2010.10782562.

Crescenzi, L., Jewitt, C., & Price, S. (2014). The role of touch in preschool children's learning using iPad versus paper interaction. Australian Journal of

Language and Literacy, 37(2), 86e95.

Dempsey, J. V., Driscoll, M. P., & Swindell, L. K. (1993). Text-based feedback. In J. V. Dempsey, & G. C. Sales (Eds.), Interactive instruction and feedback.

Englewood Cliffs, NJ: Educational Technology Publications.

Dyer, J. F., Stapleton, P., & Rodger, M. W. M. (2015). Soniﬁcation as concurrent augmented feedback for motor skill learning and the importance of mapping

design. The Open Psychology Journal, 8(Suppl. 3: M4), 192e202. http://dx.doi.org/10.2174/1874350101508010192.

Felton, R. H. (1998). The development of reading skills in poor readers: Educational implications. In C. Hulme, & R. M. Joshi (Eds.), Reading and spelling:

Development and disorders (pp. 219e233). Mahwah, NJ: Lawrence Erlbaum Assoicates, Inc.

Guan, C. Q., Liu, Y., Chan, D. H. L., Ye, F. F., & Perfetti, C. A. (2011). Writing strengthens orthography and alphabetic-coding strengthens phonology in learning

to read Chinese. Journal of Educational Psychology, 103(3), 509e522. http://dx.doi.org/10.1037/0033-295X.94.2.192.

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81e112. http://dx.doi.org/10.3102/003465430298487.

Heinrich, P. (2012). The iPad as a tool for education: A study of the introduction of iPads at long

ﬁeld academy, Kent. Retrieved from: http://www.e-

learningfoundation.com/Websites/elearningfoundation/images/PDF_Documents/Longﬁeld-The_iPad_as_a_Tool_for_Education.pdf.

Henderson, S., & Yeow, J. (2012, January). iPad in education: A case study of iPad adoption and use in a primary school. Paper presented at the 45th Hawaii

international conference on system sciences (HICSS), Maui, HI.

Hutchison, A., Beschorner, B., & Schmidt-Crawford, D. (2012). Exploring the use of the iPad for literacy learning. The Reading Teacher, 66(1), 15e23. http://dx.

doi.org/10.1002/TRTR.01090.

Hwang, G.-J. (2003). A conceptual map model for developing intelligent tutoring systems. Computers & Education, 40(3), 217e235. http://dx.doi.org/10.1016/

S0360-1315(02)00121-5.

James, K. H., & Engelhardt, L. (2012). The effects of handwriting experience on functional brain development in pre-literate children. Trends Neuroscience

and Education, 1(1), 32e42. http://dx.doi.org/10.1016/j.tine.2012.08.001.

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2015). NMC horizon report: 2015 K-12 edition. Retrieved from Austin, TX: The New Media Con-

sortium http://cdn.nmc.org/media/2015-nmc-horizon-report-k12-EN.pdf.

Kegel, C. A. T., & Bus, A. G. (2012). Online tutoring as a pivotal quality of web-based early literacy programs. Journal of Educational Psychology, 104(1),

182e192. http://dx.doi.org/10.1037/a0025849.

Kersey, A. J., & James, K. H. (2013). Brain activation patterns resulting from learning letter forms through active self-production and passive observation in

young children. Frontiers in Psychology, 4(567), 1e15. http://dx.doi.org/10.3389/fpsyg.2013.00567.

Kiefer, M., Schuler, S., Mayer, C., Trumpp, N. M., Kille, K., & Sachse, S. (2015). Handwriting or typewriting? the inﬂuence of pen- or keyboard-based writing training

on reading and writing performance in preschool children. Advances in Cognitive Psychology, 11(4), 136e146. http://dx.doi.org/10.5709/acp-0178-7.

Kiefer, M., & Trumpp, N. M. (2012). Embodiment theory and education: The foundations of cognition in perception and action. Trends in Neuroscience and

Education, 1(1), 15e20. http://dx.doi.org/10.1016/j.tine.2012.07.002.

Kieras, D. E., & Bovair, S. (1986). The acquisition of procedures from text: A production system analysis of transfer of training. Journal of Memory and

Language, 25(5), 507e524. http://dx.doi.org/10.1016/0749-596X(86)90008-2.

Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback

intervention theory. Psychological Bulletin, 119(2), 254e284. http://dx.doi.org/10.1037/0033-2909.119.2.254.

Koedinger, K. R., Corbett, A. T., & Perfetti, C. (2012). The knowledge-learning-instruction framework: Bridging the science-practice chasm to enhance robust

student learning. Cognitive Science, 36

(5), 757e798. http://dx.doi.org/10.1111/j.1551-6709.2012.01245.x.

Kulhavy, R. W. (1977). Feedback in written instruction. Review of Educational Research, 47(2), 211e232. http://dx.doi.org/10.3102/00346543047002211.

Kulik, J. A., & Kulik, C. C. (1988). Timing of feedback and verbal learning. Review of Educational Research, 58(1), 79e97. http://dx.doi.org/10.3102/

00346543058001079.

Labat, H., Ecalle, J., Baldy, R., & Magnan, A . (2014). How can low-skilled 5-year-old children beneﬁt from multisensory training on the acquisition of the

alphabetic principle? Learning and Individual Differences, 29,106e113. http://dx.doi.org/10.1016/j.lindif.2013.09.016.

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137136

Longcamp, M., Zerbato-Poudou, M. T., & Velay, J. L. (2005). The inﬂuence of writing practice on letter recognition in preschool children: A comparison

between handwriting and typing. Acta Psychologica, 119(1), 67e79. http://dx.doi.org/10.1016/j.actpsy.2004.10.019.

Luckin, R., & du Boulay, B. (1999). Ecolab: The development and evaluation of a Vygotskian design framework. International Journal of Artiﬁcial Intelligence in

Education, 10(2), 198e220.

Mayo, M., Mitrovic, A., & McKenzie, J. (2000, December). CAPIT: An intelligent tutoring system for capitalisation and punctuation. Paper presented at the

International Workshop on Advance Learning Technologies (IWALT), Palmerston North, New Zealand.

McKenna, C. (2012). There's an app for that: How two elementary classrooms used iPads to enhance student learning and achievement. Education, 2(5),

136e142. http://dx.doi.org/10.5923/j.edu.20120205.05.

McKnight, L., & Fitton, D. (2010, June). Touch-screen technology for children: Giving the right instructions and getting the right responses. Paper presented at the

9th International Conference on Interaction Design and Children, Barcelona, Spain.

Mononen, K. (2007). The effects of augmented feedback on motor skill learning in shooting: A feedback training intervention among inexperienced riﬂe shooters.

Unpublished doctoral dissertation. Jyv

€

askyl

€

a, Finland: University of Jyv

€

askyl

€

Mory, E. H. (1996). Feedback research. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 919e956). New York:

Simon & Schuster Macmillan.

Mory, E. H. (2004). Feedback research revisited. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology, second edition

(pp. 745e783). Mahwah, New Jersey: Lawrence Erlbaum Associates.

Moxley, R. A., Warash, B., Coffman, G., Brinton, K., & Concannon, K. R. (1997). Writing development using computers in a class of three-year-olds. Journal of

Computing in Childhood Education, 8(2e3), 133e164.

Nelson, M. M., & Schunn, C. D. (2009). The nature of feedback: How different types of peer feedback affect writing performance. Instructional Science, 37(4),

375e401. http://dx.doi.org/10.1007/s11251-008-9053-x.

Neumann, M. M., & Neumann, D. L. (2013). Touch screen tablets and emergent literacy. Early Childhood Education Journal, 42(4), 231e239. http://dx.doi.org/

10.10 07/s10643-013-0608-3.

Neumann, M. M., & Neumann, D. L. (2015). The use of touch-screen tablets at home and pre-school to foster emergent literacy. Journal of Early Childhood

Literacy. http://dx.doi.org/10.1177/1468798415619773.

PBS LearningMedia. (2015). The future of digital learning

. Retrieved from website: http://gpb.pbslearningmedia.org/resource/26524f73-498a-4607-ae61-

66d6a8903e1f/the-future-of-digital-learning/.

Pentimonti, J. M., & Justice, L. M. (2009). Teachers' use of scaffolding strategies during read alouds in the preschool classroom. Early Childhood Education

Journal, 37(4), 241e248. http://dx.doi.org/10.1007/s10643-009-0348-6.

Plumb, M., Kautz, K., & Tootell, H. (2013, December). Touch screen technology adoption and utilisation by educators in early childhood educational institutions.

Paper presented at the 24th Australasian Conference on Information Systems (ACIS), Melbourne, Australia.

Price, S., Jewitt, C., & Crescenzi, L. (2015). The role of iPads in pre-school children's mark making development. Computers & Education, 87,131e141. http://

dx.doi.org/10.1016/j.compedu.2015.04.003.

Puranik, C., Lonigan, C., & Kim, Y.-S. (2011). Contributions of emergent literacy skills to name writing, letter writing, and spelling in preschool children. Early

Childhood Research Quarterly, 26, 465e474. http://dx.doi.org/10.1016/j.ecresq.2011.03.002.

Puranik, C. S., Petscher, Y., & Lonigan, C. J. (2012). Dimensionality and reliability of letter writing in 3- to 5-year-old preschool children. Learning and In-

dividual Differences, 28,133e141. http://dx.doi.org/10.1016/j.lindif.2012.06.011.

Rau, M. A ., Aleven, V., & Rummel, N. (2009). Intelligent tutoring systems with multiple representations and self-explanation prompts support learning of

fractions. Paper presented at the 14th International Conference on Artiﬁcial Intelligence in Education (AIED), Amsterdam, the Netherlands.

Rau, M. A., Aleven, V., & Rummel, N. (2012, July). How to schedule multiple graphical representations? A classroom experiment with an intelligent tutoring

system for fractions. Paper presented at the 10th International Conference of the Learning Sciences (ICLS), Sydney, Australia.

Rideout, V. (2013). Zero to eight: Children's media use in America 2013. Retrieved from Common Sense Media website: https://www.commonsensemedia.org/

ﬁle/zero-to-eight-2013pdf-0/download.

Saenz, A. (2011). South Korea: We're spending $2 billion to put our textbooks on tablet PCs by 2015. What are you doing? SingularityHUB. Retrieved from: http://

singularityhub.com/2011/07/06/south-korea-were-spending-2-billion-to-put-our-textbooks-on-tablet-pcs-by-2015-what-are-you-doing/.

Sandvik, M., Smerdal, O., & Osterud, S. (2012). Exploring iPads in practitioners' repertoires for language learning and literacy practices in kindergarten.

Nordic Journal of Digital Literacy, 7(3), 204e220.

Schmidt, R. A. (1997). Continuous concurrent feedback degrades skill learning: Implications for training and simulation. Human Factors, 39(4), 509e525.

Schmidt, R. A., & Wrisberg, C. A. (2008). Motor learning and performance. A situation-based learning approach, Fourth Edition. Champaign, IL: Human Kinetics.

Schmidt, R. A., Young, D. E., Sinnen, S., & Shapiro, D. C. (1989). Summary knowledge of results for skill acquisition: Support for the guidance hypothesis.

Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(2), 352e359. http://dx.doi.org/10.1037/0278-7393.15.2.352.

Shatil, E., Share, D., & Levin, I. (2000). On the contribution of kindergarten writing to grade 1 literacy: A longitudinal study in Hebrew. Applied Psycho-

linguistics, 21(1), 1e21 .

http://dx.doi.org/10.1017/S0142716400001016 .

Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153e189. http://dx.doi.org/10.3102/0034654307313795.

Shute, R., & Miksad, J. (1997). Computer-assisted instruction and cognitive development in preschoolers. Child Study Journal, 27(3), 237e253.

Sigrist, R., Rauter, G., Riener, R., & Wolf, P. (2013). Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychonomic

Bulletin & Review, 20(1), 21e53. http://dx.doi.org/10.3758/s13423-012-0333-8.

Steinhart, D. J. (2001). Summary Street: An intelligent tutoring system for improving student writing through the use of latent semantic analysis. Doctoral

dissertation. Boulder, CO: University of Colorado.

Taatgen, N. A. (2013). The nature and transfer of cognitive skills. Psychological Review, 120(3), 439e471. http://dx.doi.org/10.1037/a0033138.

Thorndike, E. L., & Woodworth, R. S. (1901). The inﬂuence of improvement in one mental function upon the efﬁciency of other functions. Psychological

Review, 8(3), 247e261. http://dx.doi.org/10.1037/h0074898.

Van der Kleij, F. M., Feskens, R. C. W., & Eggen, T. J. H. M. (2015). Effects of feedback in a computer-based learning environment on students' learning

outcomes: A meta-analysis. Review of Educational Research, 85(4), 475e51 1. http://dx.doi.org/10.3102/0034654314564881.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4),

197e221. http://dx.doi.org/10.1080/00461520.2011.611369.

Vernadakis, N. (20 05). The use of computer assisted instruction in preschool education: Making teaching meaningful. Early Childhood Education Journal,

33(2), 99e104. http://dx.doi.org/10.1007/s10643-005-0026-2.

Vinter, A., & Chartrel, E. (2010). Effects of different types of learning on handwriting movements in young children. Learning and Instruction, 20(6), 476e486.

http://dx.doi.org/10.1016/j.learninstruc.2009.07.001.

Wann, J., & Nimmo-Smith, I. (1991). The control of pen pressure in handwriting: A subtle point. Human Movement Science, 10(2e3), 223e246. http://dx.doi.

org/10.1016/0167-9457(91)900 05-I.

Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology & Psychiatry, 17(2), 89e100. http://dx.doi.org/10.

1111/j.1469-7610.1976.tb00381.x.

Yu, T.-Y., Howe, T.-H., & Hinojosa, J. (2012). Contributions of haptic and kinesthetic perceptions on handwriting speed and legibility for

ﬁrst and second

grade children. Journal of Occupational Therapy, Schools, & Early Intervention, 5(1), 43e60. http://dx.doi.org/10.1080/19411243.2012.673320.

Zill, N., & West, J. (2001). Entering kindergarten: A portrait of american children when they begin school. Findings from the condition of education, 2000.

Washington, DC: National Center for Education Statistics.

M.M. Patchan, C.S. Puranik / Computers & Education 102 (2016) 128e137 137