View in EDS HTML Full Text PDF Full Text

The Use of Touch Devices for Enhancing Academic Achievement: A Meta-Analysis

Saved in:
Bibliographic Details
Title: The Use of Touch Devices for Enhancing Academic Achievement: A Meta-Analysis
Language: English
Authors: Petersen-Brown, Shawna M. (ORCID 0000-0002-1509-165X), Henze, Erin E. C., Klingbeil, David A. (ORCID 0000-0003-2571-4424), Reynolds, Jennifer L. (ORCID 0000-0002-5115-3547), Weber, Rachel C., Codding, Robin S.
Source: Psychology in the Schools. Jul 2019 56(7):1187-1206.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 20
Publication Date: 2019
Document Type: Journal Articles
Information Analyses
Descriptors: Technology Uses in Education, Handheld Devices, Academic Achievement, Instructional Effectiveness, Program Implementation, Intervention, Outcomes of Education
DOI: 10.1002/pits.22225
ISSN: 0033-3085
Abstract: Touch devices such as tablets and smartphones are widely adopted in educational settings and have many desirable features. However, research supporting the use of touch devices to improve academic achievement is emergent and has not been evaluated through a meta-analysis. We conducted a meta-analysis of 65 group and single case design research studies, published 2010-2018, to evaluate the effects of touch device implementation on academic achievement. The overall mean effect sizes were moderate for group design and single case design studies. Participant, intervention, and study attributes were also evaluated to describe the research and how these attributes may moderate the results. Overall, results suggest that touch devices may be an effective tool for enhancing academic achievement. The need to conduct additional, rigorous research on the use of touch devices as well as implications for researchers and practitioners are discussed.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1221125
Database: ERIC
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
    Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwHP89X-ZWJ8oL13iZxQ5bCzAAAA4jCB3wYJKoZIhvcNAQcGoIHRMIHOAgEAMIHIBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDEUDFv6bcetbfNV2lQIBEICBmtVwMrX59BDknI9Ijj1MT8zKioV5SEbo8xaBMRA-PIPbQ784oDwU2XQuz53mWvg3bMTM9uFfe23DUMEWf5SbGPUJ1pQ6pIZMwcCunxlH-KpmCYgbh5b9I6rkSGF1daYGuLJAcKaM5DJ23RoSiw4b7AKUlJy5iCrGGzD8VWfIlFSb2kqH9GcFFZKkbyZ0kutnzzeWWaGfM7hCYwQ=
Text:
  Availability: 1
  Value: <anid>AN0137323259;pis01jul.19;2019Jul06.05:17;v2.2.500</anid> <title id="AN0137323259-1">The use of touch devices for enhancing academic achievement: A meta‐analysis </title> <p>Touch devices such as tablets and smartphones are widely adopted in educational settings and have many desirable features. However, research supporting the use of touch devices to improve academic achievement is emergent and has not been evaluated through a meta‐analysis. We conducted a meta‐analysis of 65 group and single case design research studies, published 2010–2018, to evaluate the effects of touch device implementation on academic achievement. The overall mean effect sizes were moderate for group design and single case design studies. Participant, intervention, and study attributes were also evaluated to describe the research and how these attributes may moderate the results. Overall, results suggest that touch devices may be an effective tool for enhancing academic achievement. The need to conduct additional, rigorous research on the use of touch devices as well as implications for researchers and practitioners are discussed.</p> <p>Keywords: academic intervention; iPad; meta‐analysis; technology</p> <hd id="AN0137323259-2">1 INTRODUCTION</hd> <p>The Use of Touch Devices for Enhancing Academic Achievement: A Meta‐Analysis Technology has enjoyed widespread use in educational settings and comes in many forms (Cheung & Slavin, [<reflink idref="bib74" id="ref1">74</reflink>]). Beginning over 30 years ago, the use of computers (through computer‐assisted instruction, or CAI) has led to changes in the way students of all ages and ability levels learn. As the number of computers available for instructional purposes nearly tripled from 1995 to 2008 (from 5.6 million to 15.4 million), the ratio of students to instructional computers with Internet access decreased from 6.6 to 3.1 between 2000 and 2008 (U.S. Department of Education, National Center for Education Statistics, [<reflink idref="bib108" id="ref2">108</reflink>]). The importance of technology in schools is reflected in the Common Core State Standards which describes the necessity of technical skills such as typing, accessing the internet, and using digital tools (CCSS; National Governors Association Center for Best Practices & Council of Chief State School Officers, [<reflink idref="bib96" id="ref3">96</reflink>]).</p> <p>More recently, touch devices have garnered significant attention for their instructional potential. Touch devices, devices with a touch‐sensitive screen, include the iPad and other tablets, iPod touch, smartphones, internet‐enabled e‐readers, and touch screen computers. Adoption and use of touch devices, especially tablets, have skyrocketed in recent years (Kagohara et al., [<reflink idref="bib90" id="ref4">90</reflink>]), often on a large scale (e.g., Lapowsky, [<reflink idref="bib94" id="ref5">94</reflink>]). Although touch devices have been described as a way to transform education (Ferenstein, [<reflink idref="bib79" id="ref6">79</reflink>]), there is limited research regarding the use of touch devices in educational settings (Bebell et al., [<reflink idref="bib69" id="ref7">69</reflink>]; Kucirkova, [<reflink idref="bib93" id="ref8">93</reflink>]; Larabee, Burns, & Mccomas, [<reflink idref="bib30" id="ref9">30</reflink>]).</p> <hd id="AN0137323259-3">2 ADOPTION OF TOUCH DEVICES IN SCHOOLS</hd> <p>Those adopting touch devices may find several characteristics particularly appealing Touch devices may be more affordable than traditional computers. They are also accessible, promoting equitable access to technology across student populations (Melhuish & Falloon, [<reflink idref="bib95" id="ref10">95</reflink>]). In terms of their physical properties, touch devices have an intuitive design and are portable, lightweight, and eliminate the need for accessories, such as a mouse and keyboard, which can be cumbersome and limit accessibility for individuals with fine motor deficits (Melhuish & Falloon, [<reflink idref="bib95" id="ref11">95</reflink>]). With regard to functionality, touch devices can provide access to the internet; instant turn on/off ability; and video, camera, and audio capture features. Touch devices can accommodate a wide variety of applications and uses and also allow for independent and adaptive instruction, potentially requiring fewer staff resources, and allowing students to access instruction at their own level of performance (Melhuish & Falloon, [<reflink idref="bib95" id="ref12">95</reflink>]).</p> <p>Given the appeal of touch devices in education, it is not surprising that they have been widely adopted. According to a 2014 survey, an estimated 88% of school districts have adopted touch devices in schools, and an additional 9% reported that their district was very likely to adopt touch technology within 2 years (Interactive Educational Systems Design, Inc, [<reflink idref="bib71" id="ref13">71</reflink>]). Twenty percent of districts reported that classrooms had a 1:1 ratio of touch devices to students, whereas an additional 62% of districts reported interest in implementing or expanding a 1:1 touch device program. The most commonly cited expected benefits of touch devices were increasing student engagement (47.3%) and increasing student achievement (40.1%). The most commonly cited challenges in adopting touch technology were a lack of professional development and other supports (70%), managing the mobile devices (60%), and infrastructure issues like bandwidth management (55%). Given the widespread adoption and ubiquity of touch devices, understanding their impact on student achievement is critical.</p> <hd id="AN0137323259-4">3 PREVIOUS SYSTEMATIC REVIEWS OF TOUCH DEVICE RESEARCH</hd> <p>Several reviews have summarized and evaluated the emerging research on touch devices in educational settings. Each of these reviews focused on specific student populations, generally students with disabilities. Therefore, the findings of these reviews are not generalizable to a universal student population or to other student populations. Kagohara et al. ([<reflink idref="bib90" id="ref14">90</reflink>]) conducted a systematic review of touch devices on the performance of students ranging from 4 to 27 years of age with developmental disabilities. Researchers evaluated studies that covered the domains of academic skills, communication, employment, leisure, and transitioning across settings. The results were largely positive and suggested that students with developmental disabilities can be taught to use operate touch devices for a variety of purposes and positive impacts on functioning in each domain were observed in the research. However, only 15 articles met inclusion criteria, and the effects of interventions delivered via touch device were not systematically quantified. A majority of the studies (53%) addressed communication, whereas only one study (7%) addressed academic skills. Because the researchers were primarily interested in examining interventions delivered via touch device to students with developmental disabilities, the findings cannot be generalized to students with other disabilities, students at‐risk for disabilities, or universal student populations.</p> <p>Alzrayer, Banda, and Koul ([<reflink idref="bib67" id="ref15">67</reflink>]) conducted a review of the effects of touch devices on the communication skills of students with autism spectrum disorder (ASD) and/or developmental disabilities. Specifically, researchers analyzed studies that implemented augmentative alternative communication (AAC) applications (apps) with students with autism or other developmental disabilities, targeted communication skills (i.e., verbal behavior), and used a single‐case design (SCD). Their analysis included data from 13 studies (consisting of 46 participants), and data were analyzed using the Percentage of Nonoverlapping Data (PND; Scruggs, Mastropieri, Cook, & Escobar, [<reflink idref="bib54" id="ref16">54</reflink>]). Results showed that interventions delivered via touch device were highly effective (i.e., PND ranging from 91% to 100%) for 23 (50%) participants, moderately effective (PND ranging from 73% to 90%) for 12 (26%) participants, minimally effective (i.e., PND ranging from 50% to 70%) for six (13%) participants and had no effect on the communication skills of five (11%) participants. These results, like those of Kagohara et al. ([<reflink idref="bib90" id="ref17">90</reflink>]), are largely positive. However, this analysis included a small number of studies, represented only three of the many AAC apps, and focused on the use of touch devices in one domain (communication) with a specific population (students with autism and developmental disabilities). Thus, these findings also have limited generalizability to the use of touch devices in other domains or with other student populations.</p> <p>Ok and Kim ([<reflink idref="bib97" id="ref18">97</reflink>]) review by examining academic skills. They conducted a systematic review of 20 studies, published between 2011 and 2015 that examined the effects of interventions delivered via iPads and iPods on the academic performance and engagement of students with disabilities. They examined 20 SCD studies including 69 students with disabilities (e.g., autism spectrum disorder, learning disability, emotional impairment). Their synthesis included eight studies targeting literacy, seven targeting math, two targeting science, and one targeting various subjects. Overall, effect sizes (as measured by nonoverlap of all pairs, NAP) ranged from small to large with most studies demonstrating a strong positive effect on academic skills. Although results of this research were promising, their review was limited to students with disabilities, included only SCD studies, and did not synthesize the overall results or examine potential moderators.</p> <p>Kim, Park, and Coleman ([<reflink idref="bib91" id="ref19">91</reflink>]) examined the research on the effects of tablet‐assisted instruction on the academic skills of students with disabilities. A primary purpose of their research was to examine the quality of research on tablet‐assisted instruction. Their review included 3 quasi‐experimental/experimental and 14 SCD studies that included students with disabilities or at‐risk students (i.e., English learners, students with learning difficulties). Researchers coded descriptive information and evaluated each study according to a set of Quality Indicators (QI; Gersten et al., [<reflink idref="bib81" id="ref20">81</reflink>]; Horner et al., [<reflink idref="bib88" id="ref21">88</reflink>]; Jitendra, Burgess, & Gajria, [<reflink idref="bib89" id="ref22">89</reflink>]). Overall, the SCD studies showed positive effects (mean PND = 84.3%, range 34%–100%); although three studies were excluded from this calculation based on a lack of baseline condition. The results must be interpreted cautiously because only four (28.6%) SCD studies and none of the experimental/quasi‐experimetnal studies met minimum QI criteria. Therefore, the authors posited that tablet‐assisted intervention cannot be considered an evidence‐based practice for at‐risk students or students with disabilities based on the research evaluated.</p> <p>Hong et al. ([<reflink idref="bib87" id="ref23">87</reflink>]) conducted a meta‐analysis on the effects of tablet‐based interventions on the skills of students with ASD. They reviewed a total of 36 SCDs targeting eight dependent variables (including various adaptive skills, social/communication skills, and academic skills) and found promising effects for tablet‐assisted interventions. Higher‐functioning students showed greater improvements than students with intellectual disability or lower‐functioning ASD. The authors found large to very large effect sizes for interventions targeting academic skills, although only four (11%) studies included an academic dependent variable. In addition, the research investigating academic skills did not meet What Works Clearinghouse (WWC) standards. This study was consistent with previous reviews in identifying promising effects of tablet‐assisted interventions and systematically examined these effects using meta‐analytic techniques. However, this review was limited to students with disabilities and included only SCD studies.</p> <p>Existing efforts to evaluate research on interventions delivered via touch devices have generally found positive results, suggesting some benefits across age groups (Alzrayer et al., [<reflink idref="bib67" id="ref24">67</reflink>]; Kagohara et al., [<reflink idref="bib90" id="ref25">90</reflink>]) and domains such as communication (e.g., Alzrayer et al., [<reflink idref="bib67" id="ref26">67</reflink>]), adaptive skills (e.g., Hong et al., [<reflink idref="bib87" id="ref27">87</reflink>]), and academic skills (Hong et al., [<reflink idref="bib87" id="ref28">87</reflink>]; Ok & Kim, [<reflink idref="bib97" id="ref29">97</reflink>]). However, these analyses generally sampled specific types of research conducted with specific student populations, signifying gaps in the literature. First, these analyses evaluated a total of 69 unique studies (103 total) that were published between 2006 and 2017. Nearly all of these studies used SCDs and three used experimental/quasi‐experimental designs. Second, aside from two studies in the Kim et al. ([<reflink idref="bib91" id="ref30">91</reflink>]) review that targeted students with reading difficulties, these analyses included only students with disabilities (e.g., autism, learning disabilities, emotional impairment, intellectual disability). The specific populations and generally small sample sizes represented suggest that these results are not generalizable to other student populations. This contrasts the widespread adoption of touch devices, often at a universal level, and suggests the need for a review that includes the use of touch devices with universal student populations. Finally, with the exception of Hong et al. ([<reflink idref="bib87" id="ref31">87</reflink>]), researchers who have conducted detailed reviews of the literature have approached the task as a systematic review, rather than a meta‐analysis. Systematic, nonquantitative reviews are prone to a variety of issues including subjective or misleading interpretations of overall findings and a failure to examine potential moderating variables (Wolf, [<reflink idref="bib110" id="ref32">110</reflink>]). Meta‐analyses utilize more systematic and quantitative procedures that facilitate more accurate and credible findings and can be used to systematically examine potential moderators (Rosenthal & DiMatteo, [<reflink idref="bib102" id="ref33">102</reflink>]). Given that supporting student achievement is one of the primary reasons that touch devices are adopted in schools (Interactive Educational Systems Design, Inc, [<reflink idref="bib71" id="ref34">71</reflink>]), it is critical to build upon the scope the current literature to evaluate the research investigating touch devices in an academic domain with all students.</p> <hd id="AN0137323259-5">4 PURPOSE</hd> <p>Research evaluating the use of touch devices in schools is insufficient for indicating the overall effectiveness of their implementation, particularly on the academic skills of universal and at‐risk populations. The current meta‐analysis was conducted to address the gap in the existing literature and to evaluate the research on the implementation of touch devices in schools to impact academic achievement. This analysis focused on the impact of interventions delivered via touch devices and the circumstances surrounding implementation, rather than the instructional procedures used within touch device apps. Specifically, this meta‐analysis addressed the following research questions:</p> <p></p> <p>• 1.</p> <p></p> <ulist> <item> What are the descriptive characteristics of the research investigating the implementation of touch devices, in terms of academic skills targeted; age/grade levels of participants; status of participants as universal, at‐risk, or students with disabilities; interventionists implementing touch devices; and study design and rigor?</item> <p></p> </ulist> <p>• 2.</p> <p></p> <ulist> <item> What is the impact of implementing touch devices on academic achievement?</item> <p></p> </ulist> <p>• 3.</p> <p></p> <ulist> <item> Is the impact of implementing touch devices moderated by the descriptive variables investigated?</item> </ulist> <hd id="AN0137323259-6">5 METHOD</hd> <p></p> <hd id="AN0137323259-7">5.1 Literature search procedures and selection of studies</hd> <p>We systematically searched the Academic Search Premier, ERIC, and PsycINFO in September 2018 to identify studies published from 2000 through 2018 that investigated the implementation of touch devices. The year 2000 was selected because the first tablets were released in 2002, and the first iPods were released in 2001. Search terms included academic subject areas ("math," "reading," "writing," and "spelling") and common names for touch devices ("iPad," "iPod," "tablet," "mobile device," and "touch device"). Notably, although we did not specifically search for touch‐screen laptops or computers, studies conducted with those devices would have been considered for inclusion. In addition, among studies utilizing an iPod, only those using an iPod touch would have been considered for inclusion. Each subject area was combined with each common touch device name using the "AND" specifier to yield an initial set of peer‐reviewed journal articles for consideration, resulting in 20 separate searches. We also conducted a hand search of articles from four related reviews (Alzrayer et al., [<reflink idref="bib67" id="ref35">67</reflink>]; Kim et al., [<reflink idref="bib91" id="ref36">91</reflink>]; Kagohara et al., [<reflink idref="bib90" id="ref37">90</reflink>]; Ok & Kim, [<reflink idref="bib97" id="ref38">97</reflink>]). After duplicates were eliminated within each subject area as well as across subject areas, the initial search resulted in 888 journal articles for consideration. Articles were reviewed two additional times to determine whether each met the following inclusionary criteria:</p> <p></p> <p>• 1.</p> <p></p> <ulist> <item> The article was published in English in a peer‐reviewed journal.</item> <p></p> </ulist> <p>• 2.</p> <p></p> <ulist> <item> The article presented the results of a study or studies as original research.</item> <p></p> </ulist> <p>• 3.</p> <p></p> <ulist> <item> The article included sufficient data to compute an effect.</item> <p></p> </ulist> <p>• 4.</p> <p></p> <ulist> <item> Students were the recipients of the intervention.</item> <p></p> </ulist> <p>• 5.</p> <p></p> <ulist> <item> Students were in preschool through 12th grade (or were adults up to age 26 receiving transition services through a school district).</item> <p></p> </ulist> <p>• 6.</p> <p></p> <ulist> <item> The study investigated an intervention that included the use of a touch device, and this intervention was compared to either a no‐treatment control condition or to an intervention that did not include the use of a touch device. Studies using a variety of comparison conditions were included, in keeping with previous reviews (e.g., Kim et al., [<reflink idref="bib91" id="ref39">91</reflink>]; Ok & Kim, [<reflink idref="bib97" id="ref40">97</reflink>]); the type of baseline condition was descriptively and quantitatively evaluated through this study.</item> <p></p> </ulist> <p>• 7.</p> <p></p> <ulist> <item> The intervention targeted an academic skill, and at least one dependent variable represented an academic skill (e.g., math, reading, spelling, or writing).</item> <p></p> </ulist> <p>• 8.</p> <p></p> <ulist> <item> If a group design, the study used a between‐group, rather than within‐subjects, design due to the multiple threats to validity present in pre‐post only designs.</item> </ulist> <p>Of the 888 journal articles identified for consideration, 65 met all inclusion criteria and were included in this meta‐analysis.</p> <hd id="AN0137323259-8">5.2 Coding procedures</hd> <p></p> <hd id="AN0137323259-9">5.2.1 Training and reliability</hd> <p>The first and second authors individually coded four studies (two group design and two SCD) for training purposes. Results were compared, disagreements were resolved, and adjustments to the coding system were made. Next, the first and second authors held two 1‐hr training sessions to instruct the fourth and fifth authors on the coding system and extraction of SCD data. The fourth and fifth authors individually coded studies, one group design study and one SCD study (from the original set coded by the first and second authors). Results were compared to the coding agreed upon by the first and second authors, and coding continued until 100% agreement was achieved among all four raters.</p> <p>Next, each rater coded an initial assigned set of studies, with the first and second authors responsible for coding each study and the fourth and fifth authors responsible for coding studies to collect reliability data. Interrater reliability was calculated for all qualitative coding variables for 22 studies (34%). The total number of agreements between the two sets of raters was divided by the total number of coding opportunities (i.e., agreements plus disagreements) and multiplied by 100, which resulted in mean interrater reliability of 89%. Disagreements were discussed between the two raters and a consensus reached before conducting analyses.</p> <hd id="AN0137323259-10">5.2.2 Variables coded</hd> <p>Each study was coded according to variables related to the purposes of the study described above. Information collected included moderator variables described below, as well as additional qualitative and quantitative information allowing for a more comprehensive understanding of the research. The authors developed the coding system used in this study.</p> <hd id="AN0137323259-11">Participants and setting</hd> <p>For each study, we recorded the number of participants, their age, and grade placements, and their educational status (i.e., general education, at‐risk, or special education). General education was recorded when all students were included (e.g., whole‐class practices) as well as when some or all students with disabilities were not included. We also recorded information regarding the setting in which the intervention was delivered (i.e., general education classroom, special education resource classroom, self‐contained special education classroom, instructional specialist setting, other educational setting, home, or other).</p> <hd id="AN0137323259-12">Intervention and skill targeted</hd> <p>Regarding intervention‐related variables, we recorded the overall skill targeted by the intervention (i.e., reading, math, writing, spelling). The specific device used was recorded (e.g., iPad, other tablets, iPod Touch, e‐reader, smartphone, personal digital assistant [PDA], or other, such as a touch‐screen laptop). We recorded whether participants were learning in their primary language or learning a foreign language. Next, we recorded the format of the intervention as large group (defined as more than eight participants in a group; Gagne, Wager, Golas, & Keller, [<reflink idref="bib80" id="ref41">80</reflink>]), small group (defined as 2–8 participants in a group), or individual. We recorded the type of support provided by the intervention agent according to whether it was guided (they actively provided instruction during the intervention, with instruction defined as teaching, modeling, facilitation, and/or elaborative feedback to directly enhance knowledge, understanding, or skills) or if participants were independent (with the exception of prompting, answering student‐generated questions, or managing behavior). We recorded whether the intervention agent was a classroom teacher, special education teacher, other educator, researcher, volunteer, or parent. Finally, we recorded the dosage, in total minutes, of the touch device intervention. The dosage was included if authors reported any of the following: total minutes of touch device intervention; session length and number of sessions; or session length, number of sessions per week, and number of weeks of intervention. Within SCD studies, each participant's dosage was calculated separately and then averaged.</p> <hd id="AN0137323259-13">Study design and rigor</hd> <p>Each group design study was coded as a: (a) randomized control trial (RCT) or (b) quasi‐experimental design (QED) study. SCD studies were coded as a: (a) ABAB design, (b) alternating treatments design (ATD), (c) multiple baseline design, or (d) changing criterion design. We recorded the type of comparison utilized, whether touch device intervention was compared with a no‐treatment baseline or assessment only condition (i.e., the baseline or comparison condition required only the completion of applicable assessment measures), a business‐as‐usual (BAU) instructional practice (i.e., the baseline or comparison condition included existing instructional practices, regardless of their similarity to the touch device intervention), or a similar intervention delivered through a traditional medium (i.e., the baseline or comparison condition was developed to have the same skill targets and instructional features as the touch device intervention). The rigor of each study was evaluated using the WWC criteria (U.S. Department of Education, Institute of Education Sciences, What Works Clearinghouse, [<reflink idref="bib107" id="ref42">107</reflink>]). Each study was given an overall rating: meets evidence standards, meets evidence standards with reservations, or does not meet evidence standards.</p> <p>We also collected qualitative information on study procedures. Specifically, we recorded whether social validity, treatment integrity, and interobserver agreement data were collected and described the overall results.</p> <hd id="AN0137323259-14">5.3 Moderator categories</hd> <p>Moderators were selected based on their relevance for school‐based use of touch devices and were linked directly with our research questions. Moderator analysis occurred across each of three broad categories (participants and setting, intervention, comparison condition, and study rigor). Moderator variable categories were modified from the original coding scheme (e.g., writing and spelling were initially separate categories but were combined as "written expression") so that a sufficient number of studies were included in each group to maximize power.</p> <hd id="AN0137323259-15">5.3.1 Participants and setting</hd> <p>Participants' grade was coded as a categorical moderator variable. Treatment effects were compared between preschool through 2nd grade, 3rd through 5th grade, and 6th through 12th grade. The setting could not be analyzed given the lack of variability between studies within research designs. For example, the SCD studies included participants receiving special education almost exclusively, whereas group design studies were conducted primarily with general education participants.</p> <hd id="AN0137323259-16">5.3.2 Intervention</hd> <p>The targeted skill was coded as reading, mathematics, written expression or other. Reading included global reading achievement, various reading subskills (e.g., fluency, word identification, phoneme identification). Written expression included measures of writing fluency, written expression, and spelling outcomes. Math outcomes included broad measures of math achievement and several different subskills (e.g., early numeracy skills, multiplication, fractions knowledge, line estimation, and math communication). Other included measures of broad academic skills and content‐area measures (e.g., social studies, science). The delivery format was analyzed as a large group, small group, or individual. Support was coded as either guided (the interventionist actively provided instruction) or independent (the interventionist provided only logistical and behavioral support). Finally, the interventionist was coded as school staff or researcher. Only two studies (Kosko & Ferdig, [<reflink idref="bib28" id="ref43">28</reflink>]; Masataka, [<reflink idref="bib34" id="ref44">34</reflink>]) used parents as interventionists; these were excluded from the analysis.</p> <hd id="AN0137323259-17">5.3.3 Comparison condition</hd> <p>Comparison condition was coded as a dichotomous variable. Effects were compared between studies that compared touch device implementation to no‐treatment, assessment only, or BAU condition, and those that compared touch device implementation to a similar analog condition.</p> <hd id="AN0137323259-18">5.3.4 Study rigor</hd> <p>The methodological rigor of each study was rated using the U.S. Department of Education, Institute of Education Sciences, What Works Clearinghouse ([<reflink idref="bib107" id="ref45">107</reflink>]) standards as described above. Studies were coded as follows: did not meet standards, met standards with reservations, or met standards. Only RCTs and well‐designed SCDs were eligible for the <emph>met standards</emph> designation.</p> <hd id="AN0137323259-19">5.4 Data extraction</hd> <p>Raw data from the included SCD studies were extracted using GraphClick (Arizona Software, [<reflink idref="bib68" id="ref46">68</reflink>]). More specifically, <emph>x</emph> and <emph>y</emph> coordinates for each data point were estimated for each participant in all phases in the design. Irrational values (i.e., percentages >100 or <0) were fixed before analysis.</p> <hd id="AN0137323259-20">5.5 Effect size estimation</hd> <p></p> <hd id="AN0137323259-21">5.5.1 Group designs</hd> <p>Effect sizes (<emph>g</emph>; Hedges, [<reflink idref="bib83" id="ref47">83</reflink>]) were calculated for each group design study using the Comprehensive Meta‐Analysis program (Borenstein, Hedges, Higgins, & Rothstein, [<reflink idref="bib73" id="ref48">73</reflink>]). Positive effect sizes represent results that favored instruction using touch devices over control conditions. We used means and standard deviations to calculate Hedges' <emph>g</emph> whenever possible; otherwise, we used various combinations of information (e.g., <emph>t</emph> or <emph>F</emph> statistics, <emph>p</emph> values, sample sizes) to calculate effect sizes.</p> <hd id="AN0137323259-22">5.5.2 SCD studies</hd> <p>Raw data were used to estimate two different effect sizes for SCD studies. The first effect size was baseline corrected Tau (Tarlow, [<reflink idref="bib104" id="ref49">104</reflink>]). Baseline corrected Tau represents the nonparametric correlation between phase and outcome data, and allows for monotonic control of baseline‐trend. Baseline‐corrected Tau was computed using an online calculator (Tarlow, [<reflink idref="bib105" id="ref50">105</reflink>]), with a correction for baseline trend made if the baseline trend significance test was <emph>p</emph> < 0.05.</p> <p>We also estimated the effect of interventions delivered via touch devices using a design‐comparable, between‐case standardized mean difference (BC‐SMD) for SCD studies. After correcting for small sample bias, the corresponding standardized mean difference is equivalent to Hedges' g ([<reflink idref="bib83" id="ref51">83</reflink>]) for between‐group experiments (Pustejovsky, Hedges, & Shadish, [<reflink idref="bib100" id="ref52">100</reflink>]). Three participants are required to estimate between‐case variance. The BC‐SMD extended the first attempts to create a standardized mean difference for SCD studies (e.g., Hedges, Pustejovsky, & Shadish, [<reflink idref="bib85" id="ref53">85</reflink>]) by allowing for between‐case variation in levels and trends in the data (Pustejovsky et al., [<reflink idref="bib100" id="ref54">100</reflink>]). Within‐case errors are assumed to follow an AR(<reflink idref="bib1" id="ref55">1</reflink>) autocorrelation structure and be normally distributed. To date, the BC‐SMD can be estimated for reversal (Hedges, Pustejovsky, & Shadish, [<reflink idref="bib84" id="ref56">84</reflink>]) and multiple‐baseline (or multiple‐probe) across participant designs (Pustejovsky et al., [<reflink idref="bib100" id="ref57">100</reflink>]). Therefore, we only estimated the BC‐SMD for studies using a multiple‐baseline (<emph>k</emph> = 3) or multiple‐probe (<emph>k</emph> = 6) across participants design with three or more participants. We used raw data from SCD studies using a multiple‐baseline across participants design to estimate the BC‐SMD in R (R Core Team, [<reflink idref="bib43" id="ref58">43</reflink>]) using the scdhlm package (Pustejovsky, [<reflink idref="bib101" id="ref59">101</reflink>]).</p> <hd id="AN0137323259-23">5.6 Effect size syntheses</hd> <p>We conducted the meta‐analytic analyses using the robumeta (Fisher & Tipton, [<reflink idref="bib19" id="ref60">19</reflink>]) and metafor (Viechtbauer [<reflink idref="bib109" id="ref61">109</reflink>]) packages in R (R Core Team, [<reflink idref="bib43" id="ref62">43</reflink>]). Models estimated using robust variance estimation were fit using the correlated effects model (rho = 0.8) and adjustments for small sample sizes (Tipton, 2014). More conventional meta‐analytic syntheses, estimated using an unweighted average effect size for each study, used random‐effects models with the respective variances estimated using restricted maximum‐likelihood estimation with adjusted standard errors (Knapp & Hartung, [<reflink idref="bib92" id="ref63">92</reflink>]). We report between‐study heterogeneity (<emph>T</emph><sups>2</sups>) and <emph>I</emph><sups>2</sups> values, which indicate the proportion of variance resulting from by true between‐study differences in effect sizes rather than sampling error (Borenstein, Hedges, Higgins, & Rothstein, [<reflink idref="bib72" id="ref64">72</reflink>]). <emph>I</emph><sups>2</sups> values of 25%, 50%, and 75% represent low, moderate, and high ratios of variance, respectively (Higgins, Thompson, Deeks, & Altman, [<reflink idref="bib86" id="ref65">86</reflink>]). Due to the number of comparisons made, the criterion for statistical significance was <emph>p</emph> < 0.008. This criterion resulted from a Bonferroni correction with six comparisons.</p> <hd id="AN0137323259-24">5.6.1 Overall treatment effect</hd> <p>We estimated the overall treatment effects for all academic outcomes. We did not include any effect sizes related to treatment acceptability, engagement with the program, task engagement, or other nonlearning outcomes. Thus, the resulting effect size represents the overall effect of the implementation of touch devices on learning outcomes. Positive effect sizes indicated the benefit of touch device implementation compared with other approaches (between‐group studies) or baseline conditions (SCD studies).</p> <p>We estimated treatment effects for two different groups of studies. First, we calculated the overall treatment effects for controlled designs combined with SCDs for which we could estimate a design comparable effect size (Pustejovsky et al., [<reflink idref="bib100" id="ref66">100</reflink>]) using robust variance estimation. Second, we estimated a separate overall treatment effect for all SCDs using conventional meta‐analysis techniques. The unweighted average effect size was used for all SCDs in which more than one effect size was presented (<emph>k</emph> = 9) as the use of baseline‐corrected Tau.</p> <hd id="AN0137323259-25">5.6.2 Moderator analyses</hd> <p>The impact of the moderators described above was investigated using a series of mixed‐effect regression models. The criterion for statistical significance was adjusted for the number of comparisons. We used a series of comparisons rather than meta‐regression due to the small number of studies included in the analysis. Moderators were analyzed for between‐group designs and SCDs in which we could estimate the BC‐SMD (<emph>k</emph> = 35) and all SCD studies (<emph>k</emph> = 27), separately.</p> <hd id="AN0137323259-26">5.6.3 Publication bias</hd> <p>We evaluated the potential of publication bias for the treatment effects obtained from the between‐group studies only (<emph>k</emph> = 35). We did not evaluate whether publication bias existed for the SCD effects estimated using between‐case Tau because research has yet to evaluate these methods for effect sizes such as Tau (Shadish, Zelinsky, Vevea, & Kratochwill, [<reflink idref="bib103" id="ref67">103</reflink>]). Methods for evaluating publication bias in robust variance estimation models have not been established. Therefore, we calculated an unweighted effect size for each study (<emph>k</emph> = 35) and fit a random‐effects model to estimate the overall treatment effect. Potential publication bias was examined through visual inspection of the funnel plot and statistical testing the asymmetry using rank‐correlation (Begg & Mazumdar, [<reflink idref="bib70" id="ref68">70</reflink>]) and linear regression tests (Egger, Smith, Schneider, & Minder, [<reflink idref="bib77" id="ref69">77</reflink>]). We used the trim and fill method (Duvall & Tweedie, [<reflink idref="bib76" id="ref70">76</reflink>]), which estimates the number of missing studies and adjusted effect size, to assess the potential impact of publication bias on the overall treatment effect.</p> <hd id="AN0137323259-27">6 RESULTS</hd> <p>There were 64 articles included in the analysis. Musti‐Rao, Lo, and Plati ([<reflink idref="bib39" id="ref71">39</reflink>]) included two separate studies, resulting in 65 studies total. Among 35 controlled studies, there were more QED studies (<emph>k</emph> = 24; 37%) than RCTs (<emph>k</emph> = 11; 17%). There were a total of 30 SCD studies (from 29 articles) included in the analysis. Among SCD studies, 22 (73%) used a multiple‐baseline design. There were fewer ATDs (<emph>k</emph> = 8; 27%).</p> <hd id="AN0137323259-28">6.1 Descriptive overview of included articles</hd> <p>We conducted a descriptive analysis to provide a more complete picture of how touch devices are being used to target academic skills and address the first research question. A summary of academic skill targeted, participant characteristics, intervention, intervention agent, study design, and rigor by study is included in online supplemental materials.</p> <hd id="AN0137323259-29">6.1.1 Academic skill targeted</hd> <p>A plurality of studies within this sample targeted reading skills (<emph>k</emph> = 27, 42%), although a sizeable number of studies targeted math skills (<emph>k</emph> = 24, 37%). Within the area of written language, three studies (5%) targeted spelling, and five studies (8%) targeted writing. Four studies (6%) targeted learning a foreign language, with three focusing on reading and one focusing on writing. Five studies (8%) target other subjects such as science and social studies, and one study (2%) targeted both reading and math.</p> <hd id="AN0137323259-30">6.1.2 Participant characteristics</hd> <p>A wide range of grade levels was represented in this sample. Twenty‐five (38%) included participants in preschool through 2nd grade, 17 (26%) included participants in 3rd through 5th grade, and 19 (29%) included students in 6th grade through high school. Within these broader categories, there were seven studies that included preschool students (11%). Adults were sparsely represented in the current sample, comprising the samples of two (3%) studies (Kellems et al., [<reflink idref="bib26" id="ref72">26</reflink>]; Purazella & Mechling, [<reflink idref="bib48" id="ref73">48</reflink>]). Participants' grade levels were not specified in one (2%) study and spanned multiple age ranges in three (5%) studies.</p> <p>General education students comprised the sample in over half of the included studies (<emph>k</emph> = 33, 51%). Special education students were included in 26 studies (40%), and 6 studies (9%) included an at‐risk sample. All of the studies that included special education students and half of the studies that included an at‐risk student population (<emph>k</emph> = 3, 5%) used an SCD, whereas nearly all (<emph>k</emph> = 32, 49%) of the studies with a general education sample used a group design. Among studies with special education students, participants included students with ASD (<emph>k</emph> = 9, 35%), students with specific learning disabilities (<emph>k</emph> = 4, 15%), students with a developmental delay (<emph>k</emph> = 4, 15%), students with an intellectual disability (<emph>k</emph> = 2, 8%), students with an emotional disturbance (<emph>k</emph> = 2, 8%), students with a visual impairment (<emph>k</emph> = 1, 4%), students with a speech or language impairment (<emph>k</emph> = 1, 4%), and students with multiple disabilities (<emph>k</emph> = 3, 11%).</p> <hd id="AN0137323259-31">6.1.3 Intervention</hd> <p>iPads were the most commonly used touch device in this sample (<emph>k</emph> = 41, 63%). Other tablets were also utilized, with no specific models predominating (<emph>k</emph> = 16, 25%). Other touch devices included iPod Touches (<emph>k</emph> = 3, 5%), PDAs (<emph>k</emph> = 2, 3%), e‐readers (<emph>k</emph> = 1, 2%), and smartphones (<emph>k</emph> = 1, 2%). One study used a large touchscreen tabletop.</p> <p>The majority of the studies consisted of intervention within the general education classroom (<emph>k</emph> = 38, 58%). Fifteen studies (23%) were conducted within a special education classroom, four (6%) in a resource room and 11 (17%) in a self‐contained special education classroom. Six studies (9%) described intervention delivered in another educational setting. The remaining studies either did not describe the setting (<emph>k</emph> = 3, 5%) or provided intervention at home (<emph>k</emph> = 1, 2%) or in a research setting (e.g., clinic or university classroom, <emph>k</emph> = 2, 3%).</p> <p>The majority of the studies in the sample used interventionists to provide guided intervention support (<emph>k</emph> = 33, 51%), whereas a minority of the studies consisted of students working independently (i.e., interventionists provided only logistical and behavioral support; <emph>k</emph> = 28, 43%). Four studies (6%) provided insufficient information on the role of interventionists. Participants used touch devices individually in 30 studies (46%), in small groups in 16 studies (25%), and in large groups in 15 studies (23%). Four studies (6%) did not provide sufficient information to determine participant group size.</p> <p>Dosage data were included for 38 studies (57%); 27 studies did not include adequate information to compute dosage. The average dosage was 374 min but varied widely (<emph>SD</emph> = 362.05). Dosage ranged from one 15‐min session (Piatt, Coret, Choi, Volden, & Bisanz, [<reflink idref="bib45" id="ref74">45</reflink>]) to an average of 1,698 min of training occurring in 20‐min sessions (Hallstedt, Klingberg, & Ghaderi, [<reflink idref="bib21" id="ref75">21</reflink>]). Due to the relatively incomplete reporting, dosage was not used in a moderator analysis.</p> <hd id="AN0137323259-32">6.1.4 Intervention agent</hd> <p>The most common intervention agent was the classroom teacher (<emph>k</emph> = 32, 49%). The second most common intervention agent was the researcher (<emph>k</emph> = 21, 32%), and in 19 (90%) of these cases, an SCD was used. Six studies (9%) utilized a special education teacher and each of these was an SCD study. Other educators (e.g., occupational therapist, paraprofessional) served as interventionists in four studies (6%) and two studies (3%) included parents as interventionists.</p> <hd id="AN0137323259-33">6.1.5 Study design and rigor</hd> <p>The studies varied with regard to the nature of the comparison condition. A number of studies (<emph>k</emph> = 21, 32%) compared touch device delivered the intervention to a no‐treatment control or assessment‐only condition. However, other studies compared touch device intervention to BAU (<emph>k</emph> = 24, 37%) or to similar instruction delivered through another medium (<emph>k</emph> = 20, 31%).</p> <p>Study quality was evaluated based on methodological rigor per WWC criteria and the inclusion of treatment integrity, IOA, and social validity data. The majority of studies in this sample did not meet research design standards per WWC criteria (<emph>k</emph> = 39, 60%). However, 17 studies (26%) did meet standards, whereas 9 (14%) met standards with reservations. Treatment integrity data were presented for 30 studies (46%). IOA was presented for 28 studies (43%). Twenty‐seven studies (42%) presented both treatment integrity and IOA. Social validity data were collected in 37 (57%) studies.</p> <hd id="AN0137323259-34">6.2 Overall treatment effects</hd> <p>The second research question examined the overall effect of intervention delivered via touch device across all learning outcomes. We estimated the overall effect from 24 QED studies, 11 RCT studies, and the 9 SCDs for which we could estimate the BC‐SMD statistic (<emph>n</emph> = 4,017). The average treatment effect in these 44 studies (137 effect sizes) was <emph>g</emph> = 0.731, 95% CI [0.514, 0.947], <emph>p</emph> < 0.001. The estimated between‐study heterogeneity <emph>T</emph><sups>2</sups> = 0.350 and a substantial amount of the between‐study variance (<emph>I</emph><sups>2</sups> = 87.949) was systematic rather than random error. There were no studies identified as outliers based on visual inspection of the studentized residuals. Average effect sizes obtained from each design type, along with a forest plot of Hedge's <emph>g</emph> effect sizes by study is included in the online supplemental materials.</p> <hd id="AN0137323259-35">6.2.1 SCD studies</hd> <p>There were 27 SCD studies included in the meta‐analysis (<emph>n</emph> = 100). Across all 27 studies, the average baseline‐corrected Tau = 0.608, 95% CI [0.512, 0.705], <emph>p</emph> < 0.001. The estimated between‐study heterogeneity, <emph>T</emph><sups>2</sups> = 0.034 (<emph>SE</emph> = 0.016) was small and statistically significant <emph>Q</emph>(<reflink idref="bib26" id="ref76">26</reflink>) = 62.929, <emph>p</emph> < 0.001. Bryant, Ok et al. ([<reflink idref="bib6" id="ref77">6</reflink>]) was identified as an outlier upon visual inspection, and outside of being the only study where touch devices were associated with a negative effect, there was no other substantive reason to exclude it from the analysis. A forest plot of baseline‐corrected Tau values for SCD studies is included in the online supplemental materials.</p> <hd id="AN0137323259-36">6.3 Potential moderators of overall treatment effects</hd> <p>Results from the moderator analyses are shown in Tables and. For the between‐group and nine SCD studies for which we could estimate the BC‐SMD, effects from studies comparing touch devices to similar, analog treatments were much smaller than effects found in studies where the counterfactual was a no‐treatment or baseline as usual condition (Table). It is important to note that the counterfactual in the SCD studies, which had much larger effect size estimates than those found in the between‐group studies, was universally a no‐treatment or business as usual condition. The effects of touch devices in the SCD studies (<emph>k</emph> = 27), measured using baseline corrected Tau, were significantly lower when touch devices were implemented in a small group setting, compared with individually (Table).</p> <p>1 Moderator results for between‐group and BC‐SMD effect sizes</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Moderators</th><th>Level</th><th><italic>k</italic></th><th align="char" char="("><italic>g</italic> (<italic>SE</italic>)</th><th>95% CI</th><th><italic>t</italic></th><th><italic>df</italic></th><th><italic>p</italic><sup>a</sup></th><th><italic>I</italic><sup><italic>2</italic></sup></th><th><italic>T</italic><sup><italic>2</italic></sup></th></tr><tr valign="bottom"><th><italic>LL</italic></th><th><italic>UL</italic></th></tr></thead><tbody valign="top"><tr><td>Grade</td><td>Intercept (Preschool through second)</td><td>17</td><td>0.601 (0.151)</td><td>0.281</td><td>0.921</td><td>3.988</td><td>15.60</td><td>0.001</td><td>87.699</td><td>0.352</td></tr><tr><td /><td>Third through fifth</td><td>13</td><td>0.033 (0.210)</td><td>−0.405</td><td>0.472</td><td>0.158</td><td>19.80</td><td>0.876</td><td>–</td><td>–</td></tr><tr><td /><td>Sixth through twelfth</td><td>13</td><td>0.390 (0.312)</td><td>−0.267</td><td>1.047</td><td>1.249</td><td>17.80</td><td>0.228</td><td>–</td><td>–</td></tr><tr><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Skill</td><td>Intercept (reading)</td><td>17</td><td>0.724 (0.215)</td><td>0.263</td><td>1.186</td><td>3.374</td><td>13.60</td><td>0.005</td><td>87.336</td><td>0.413</td></tr><tr><td /><td>Math</td><td>20</td><td>0.088 (0.276)</td><td>−0.476</td><td>0.653</td><td>0.320</td><td>28.08</td><td>0.751</td><td>–</td><td>–</td></tr><tr><td /><td>Other</td><td>4</td><td>−0.214 (0.310)</td><td>−1.008</td><td>0.579</td><td>−0.691</td><td>5.09</td><td>0.520</td><td>–</td><td>–</td></tr><tr><td /><td>Writing</td><td>4</td><td>0.184 (0.418)</td><td>−1.094</td><td>1.463</td><td>0.441</td><td>3.23</td><td>0.687</td><td>–</td><td>–</td></tr><tr><td>Delivery Format</td><td>Intercept (individual)</td><td>18</td><td>1.086 (0.331)</td><td>0.359</td><td>1.813</td><td>3.28</td><td>11.3</td><td>0.007</td><td>88.275</td><td>0.464</td></tr><tr><td /><td>Small group</td><td>15</td><td>−0.589 (0.494)</td><td>−1.659</td><td>0.482</td><td>−1.19</td><td>12.6</td><td>0.255</td><td>–</td><td>–</td></tr><tr><td /><td>Large group</td><td>7</td><td>−0.346 (0.345)</td><td>−1.057</td><td>0.366</td><td>−1.000</td><td>23.70</td><td>0.326</td><td>–</td><td>–</td></tr><tr><td>Support</td><td>Intercept (guided)</td><td>23</td><td>1.033 (0.203)</td><td>0.604</td><td>1.461</td><td>5.09</td><td>16.7</td><td><0.001</td><td>88.346</td><td>0.395</td></tr><tr><td /><td>Independent</td><td>17</td><td>−0.493</td><td>−1.003</td><td>0.017</td><td>−1.97</td><td>31.8</td><td>0.058</td><td>–</td><td>–</td></tr><tr><td>Rigor (WWC rating)</td><td>Intercept (does not meet)</td><td>32</td><td>0.715 (0.113)</td><td>0.480</td><td>0.949</td><td>6.245</td><td>27.78</td><td><0.001</td><td>88.299</td><td>0.417</td></tr><tr><td /><td>Meets with reservations</td><td>5</td><td>0.906 (1.235)</td><td>−4.080</td><td>5.889</td><td>0.734</td><td>2.14</td><td>0.535</td><td>–</td><td>–</td></tr><tr><td /><td>Meets</td><td>7</td><td>−0.108 (0.294)</td><td>−0.790</td><td>0.573</td><td>−0.369</td><td>7.81</td><td>0.722</td><td>–</td><td>–</td></tr><tr><td>Counterfactual</td><td>Intercept (No treatment or BAU)</td><td>30</td><td>0.957 (0.155)</td><td>0.635</td><td>1.278</td><td>6.16</td><td>22.6</td><td><0.001</td><td>86.832</td><td>0.349</td></tr><tr><td /><td>Similar analog/traditional</td><td>14</td><td>−0.595 (0.194)</td><td>−0.993</td><td>−0.196</td><td>−3.06</td><td>27.6</td><td>0.005</td><td>–</td><td>–</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>. Results from mixed effects models robust variance estimation. Significance values for tests when <emph>df</emph> < 4 should not be trusted (Tipton, 2014). Models were fit with an intercept and the parameter estimates for the nonintercept moderator levels represent changes from the intercept value. <sups>a</sups>Significance level set at <emph>p</emph> < .008 due to the number of comparisons. BAU: Business as usual; BC‐SMD: between‐case standardized mean difference CI: confidence interval; <emph>k</emph>: number of studies; LL: lower limit; <emph>m</emph>: number of effects; SE: standard error; UL: upper limit.</p> <p>2 Moderator results for all single‐case design studies</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Moderators</th><th>Level</th><th align="char" char="("><italic>k</italic></th><th align="char" char="("><italic>bcTau</italic> (<italic>SE</italic>)</th><th>95% CI</th><th><italic>t</italic></th><th><italic>p</italic></th><th><italic>Q</italic><sup><italic>e</italic></sup></th><th><italic>p</italic></th><th><italic>I</italic><sup><italic>2</italic></sup></th><th><italic>T</italic><sup><italic>2</italic></sup></th></tr><tr valign="bottom"><th><italic>LL</italic></th><th><italic>UL</italic></th></tr></thead><tbody valign="top"><tr><td>Grade</td><td>Intercept (Preschool through second)</td><td>8</td><td>0.619 (0.094)</td><td>0.424</td><td>0.815</td><td>6.607</td><td><0.001</td><td>54.289</td><td><0.001</td><td>64.34</td><td>.044</td></tr><tr><td /><td>Third through Fifth</td><td>7</td><td>− 0.147 (0.136)</td><td>−0.431</td><td>0.136</td><td>−1.084</td><td>0.291</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td /><td>Sixth through twelfth</td><td>8</td><td>0.042 (0.133)</td><td>−0.235</td><td>0.318</td><td>0.315</td><td>0.756</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>Skill</td><td>Intercept (reading)</td><td>13</td><td>0.581 (0.070)</td><td>0.436</td><td>0.725</td><td>8.335</td><td><0.001</td><td>58.487</td><td><0.001</td><td>63.03</td><td>0.038</td></tr><tr><td /><td>Math</td><td>8</td><td>−0.011 (0.114)</td><td>− 0.246</td><td>0.224</td><td>−0.097</td><td>0.924</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td /><td>Writing</td><td>5</td><td>0.130 (0.131)</td><td>−0.140</td><td>0.400</td><td>0.998</td><td>0.329</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>Delivery Format</td><td>Intercept (individual)</td><td>19</td><td>0.693 (0.043)</td><td>0.604</td><td>0.783</td><td>15.999</td><td><0.001</td><td>40.393</td><td>0.027</td><td>37.57</td><td>0.013</td></tr><tr><td /><td>Small group</td><td>8</td><td>−0.326 (0.089)</td><td>−0.509</td><td>−0.143</td><td>−3.671</td><td><0.001</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>Support</td><td>Intercept (guided)</td><td>16</td><td>0.660 (0.058)</td><td>0.539</td><td>0.780</td><td>11.303</td><td><0.001</td><td>57.779</td><td><0.001</td><td>58.47</td><td>0.031</td></tr><tr><td /><td>Independent</td><td>11</td><td>−0.133 (0.095)</td><td>0.329</td><td>0.062</td><td>−1.406</td><td>0.172</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>Rigor (WWC rating)</td><td>Intercept (does not meet)</td><td>12</td><td>0.566 (0.070)</td><td>0.421</td><td>0.710</td><td>8.064</td><td><0.001</td><td>61.841</td><td><0.001</td><td>63.07</td><td>0.038</td></tr><tr><td /><td>Meets with reservations</td><td>6</td><td>0.074 (0.127)</td><td>−0.188</td><td>0.335</td><td>0.582</td><td>0.566</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td /><td>meets</td><td>9</td><td>0.084 (0.111)</td><td>−0.145</td><td>0.312</td><td>0.756</td><td>0.457</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>Interventionist</td><td>Intercept (researcher)</td><td>18</td><td>0.576 (0.057)</td><td>0.459</td><td>0.692</td><td>10.184</td><td><0.001</td><td>59.448</td><td><0.001</td><td>60.29</td><td>0.033</td></tr><tr><td /><td>School staff</td><td>9</td><td>0.105 (0.101)</td><td>−0.102</td><td>0.313</td><td>1.044</td><td>0.306</td><td>–</td><td>–</td><td>–</td><td>–</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>. Results from mixed effects models using restricted maximum likelihood estimation and the Knapp and Hartung method for calculating between‐study variance. The <emph>Q</emph><subs><emph>e</emph></subs> statistic is used to test whether remaining between‐group heterogeneity is significant. Significance level set at <emph>p</emph> < 0.008 due to the number of comparisons. Models were fit with an intercept and the parameter estimates for the nonintercept levels represent changes from the intercept value. CI: confidence interval; <emph>k</emph> = number of studies; LL: lower limit; SE: standard error; UL: upper limit.</p> <hd id="AN0137323259-37">6.4 Publication bias</hd> <p>For the between‐group designs, the potential of publication bias was evaluated by inspecting funnel plots and using two statistical tests. Results from the multiple methods were not indicative of publication bias. Nonsignificant results were obtained from the rank‐test, tau = 0.052, <emph>p</emph> = 0.672, and linear regression test, <emph>t</emph>(<reflink idref="bib33" id="ref78">33</reflink>) = −1.145, <emph>p</emph> = 0.260. Results from the trim‐fill analysis did not indicate any studies were missing from the left side of the funnel plot.</p> <hd id="AN0137323259-38">7 DISCUSSION</hd> <p>It is critical to evaluate the research on the implementation of touch devices for enhancing academic achievement. This is especially true as the adoption of touch devices is widespread and increasing, and a primary perceived benefit to touch devices is enhancing academic achievement. However, research in this area is emergent, and this is the first known meta‐analysis to evaluate the body of research on implementing touch devices to enhance academic achievement. Most past systematic literature reviews did not use meta‐analytic techniques; only Hong et al. ([<reflink idref="bib87" id="ref79">87</reflink>]) conducted a meta‐analysis. Past reviews have largely examined the use of touch devices with students with disabilities, and most have not exclusively focused on their use for enhancing academic achievement (Alzrayer et al., [<reflink idref="bib67" id="ref80">67</reflink>]; Hong et al., [<reflink idref="bib87" id="ref81">87</reflink>]; Kagohara et al., [<reflink idref="bib90" id="ref82">90</reflink>]; Kim et al., [<reflink idref="bib91" id="ref83">91</reflink>]; Ok & Kim, [<reflink idref="bib97" id="ref84">97</reflink>]). Thus, the current review is important for understanding the nature and results of research investigating the impact of touch device implementation on the academic achievement of universal populations.</p> <p>Several important findings emerged from our meta‐analysis. Intervention and instruction delivered via touch device appear to be effective overall, with average effect sizes exceeding the 0.40 "hinge point" (Hattie, [<reflink idref="bib82" id="ref85">82</reflink>]). SCD and controlled studies showed moderate effects overall (Cohen, [<reflink idref="bib75" id="ref86">75</reflink>]; Parker, Vannest, & Davis, [<reflink idref="bib98" id="ref87">98</reflink>]). This finding provides evidence for the overall effectiveness of touch device‐based intervention. However, effect sizes for various moderator values fell below 0.40 and were not always significantly greater than zero. Because this meta‐analysis is the first of its kind, the general lack of significant moderating effects is an important finding in itself; although the use of touch devices in academic settings is increasing, our results demonstrate that there is still not an understanding of how and when interventions delivered via touch devices are most effective. Although the moderator analyses included in this study were underpowered due to the small sample size, some differences were statistically significant and others were clinically significant. These differences may suggest important considerations and areas for future research.</p> <p>With respect to academic skills, reading skills were most commonly investigated, followed closely by math skills. A smaller number of studies addressed written expression. There were negligible and nonsignificant differences in the effectiveness of touch device implementation by academic skill.</p> <p>Students in a variety of age groups were represented in the research. Less research was available investigating the impact of interventions delivered via touch devices among very young children (preschoolers) and adults who continued to receive special education services. Moderator analyses did not identify significant differences in effectiveness based on grade level. Nearly half of studies targeted general education students, with fewer studies targeting at‐risk students and students receiving special education services. This is an interesting finding because previous reviews of touch device research focused almost exclusively on students with disabilities (Alzrayer et al., [<reflink idref="bib67" id="ref88">67</reflink>]; Hong et al., [<reflink idref="bib87" id="ref89">87</reflink>]; Kagohara et al., [<reflink idref="bib90" id="ref90">90</reflink>]; Kim et al., [<reflink idref="bib91" id="ref91">91</reflink>]; Ok & Kim, [<reflink idref="bib97" id="ref92">97</reflink>]). Therefore, our findings provide initial support for the implementation of touch devices with general education and at‐risk students, although moderator analyses based on student placement were not possible due to the propensity for group design studies to include a general education sample.</p> <p>Not surprisingly, iPads were the most commonly used touch device in this analysis. Touch devices are most commonly used in a general education classroom, consistent with the student populations who have participated in this research. Touch devices have been utilized both with direct instructional support and with only logistical and behavioral support. Moderator analyses found effect sizes that were not significant differences between these two types of support. However, guided instruction was found to be much more effective than students working independently in the between‐group and 9 SCD studies with BC‐SMDs; this clinically significant difference may warrant additional future investigation. In addition, most studies examined the effects of touch devices implemented individually, and a smaller number of studies investigated touch devices implemented in either small or large groups. Moderator analyses suggested that interventions delivered via touch device were more effective when delivered individually; the difference between individual and small group implementation was statistically significant in SCD studies. This finding suggests that touch devices may be most beneficial when implemented individually and/or with guided instruction and counters one of the suggested affordances of touch devices, which is the ability to provide individualized instruction while utilizing fewer staff resources (Malhuish & Falloon, [<reflink idref="bib95" id="ref93">95</reflink>]). Regardless of the level of the support they provided (i.e., instruction or logistical/behavioral support), most interventionists were school staff and were most often a general education teacher. Moderator analyses suggested no significant differences based on interventionist, which supports the effective implementation of touch devices by school staff.</p> <p>The studies included in this analysis varied with regard to methods and quality. The majority of studies evaluated touch device interventions to an active comparison, either typical classroom instruction or a similar traditional intervention. Active comparisons, particularly those comparing to a similar traditional intervention, are potentially more informative than a comparison to a no‐treatment baseline, as touch device intervention is likely occurring within a finite school day, and these interventions are likely to displace other instructional activities. Active comparisons that are as similar as possible to touch device interventions are particularly important to facilitate appropriate conclusions by establishing credible and rigorous comparison conditions that are as controlled and well operationalized as treatment conditions (e.g., Pressley & Harris, [<reflink idref="bib99" id="ref94">99</reflink>]). Within this meta‐analysis, studies utilizing a no‐treatment or BAU comparison had a smaller average effect size than studies utilizing similar analog comparisons, and this finding was statistically significant. This finding reinforces the importance of active comparisons that are as similar as possible to touch device interventions.</p> <p>A concerning finding is that a majority of the studies reviewed did not meet WWC standards, suggesting that the methodological rigor of this research is lacking. Effect sizes did not differ significantly between studies that met standards and those that did not. Researchers who attempt to further validate the implementation of touch devices to improve academic skills must be diligent about using rigorous methods and designs to ensure that conclusions can be confidently made based on the data. It is also disconcerting that a minority of studies provided treatment integrity and/or IOA data. Over half of the included studies provided social validity data; these data are important as one of the perceived benefits of touch devices is enhancing student engagement (Interactive Educational Systems Design, Inc, [<reflink idref="bib71" id="ref95">71</reflink>]).</p> <hd id="AN0137323259-39">7.1 Limitations</hd> <p>The findings of this meta‐analysis must be considered in context with its limitations. First, this meta‐analysis included a small number of studies (65 of 888 articles initially identified for consideration), despite the inclusion of both group and SCD studies. This limited sample resulted in limited power and may have made some effects difficult to detect. In addition, the design of a subset of SCD studies prevented calculation of some effect sizes. Thus, the studies on which effect size calculations and moderator analyses were based may not be representative of the larger sample of studies. Second, it is possible that not all relevant research was included, despite the authors' search efforts. Some of the research was excluded intentionally, such as dissertations, to ensure there was no duplication and that only peer‐reviewed research was included. This may have impacted the results. However, publication bias results were favorable, indicating no significant bias in group and SCD studies. Third, this analysis may not have investigated all relevant variables. Some information (i.e., specifics regarding critical components of the applications used) was not available in a substantial portion of the research and thus was not able to be included in coding procedures. In addition, the ability to investigate all potential moderator variables was limited, due to the small number of studies. Additional analyses may be possible as researchers better understand variables impacting the effectiveness of touch device implementation. Finally, studies utilizing a variety of comparison conditions, including both inactive and active comparison groups, were included in this meta‐analysis. Effect sizes when comparing with a similar traditional intervention were significantly smaller than effect sizes comparing with a no‐treatment or BAU condition. Thus, future meta‐analyses should consider including only studies with active comparison conditions, as these are more informative and rigorous.</p> <hd id="AN0137323259-40">7.2 Implications for research and practice</hd> <p>The results of the present study suggest that touch devices may be an effective tool for enhancing academic achievement. However, there is a need for additional research in this area to more effectively draw conclusions about the effectiveness of interventions delivered via touch devices. Researchers should ensure that their research is rigorous and meets WWC criteria, in addition to collecting treatment integrity, IOA, and social validity data, which are important in school‐based intervention research. Future research may target areas where research is currently lacking. Research on the role of touch devices in spelling and writing is limited. In addition, research including preschool children and adults receiving academic support through the public school system is lacking. Researchers should consider comparing interventions delivered via touch device to a similar intervention delivered using traditional methods, ensuring that instructional time is equivalent. These comparisons are stronger than no intervention comparison conditions and also more accurately reflect how touch devices are utilized in schools. Finally, researchers must continue to monitor and evaluate the usage and effects of newer technologies in the classroom. As technology evolves, newer devices (e.g., Chromebooks) are becoming widely used in school settings and may be used for many of the same purposes as the touch devices examined in this study.</p> <p>These findings also have implications for practice. These results suggest school‐based professionals can effectively implement touch devices. In addition, this analysis suggests that touch devices are likely to be more effective when implemented individually. However, the circumstances under which this is true require additional investigation. In addition, school staff is urged to carefully evaluate the specific apps used. Apps used should have a direct research base supporting their effectiveness or should use research‐based instructional practices. With careful consideration and evaluation, touch devices may be an effective and efficient complement to traditional instructional mediums.</p> <p>References marked with an asterisk indicate studies included in the meta‐analysis.</p> <p>GRAPH: Supporting Information</p> <ref id="AN0137323259-41"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref55" type="bt">1</bibl> <bibtext> *Al‐Mashaqbeh, I., & Al Shurman, M. (2015). The adoption of tablet and e‐textbooks: First grade core curriculum and school administration attitude. Journal of Education and Practice, 6, 188 – 194.</bibtext> </blist> <blist> <bibl id="bib2" type="bt">2</bibl> <bibtext> *Billings, E. S., & Mathison, C. (2012). I get to use an iPod in school? Using technology‐based advance organizers to support the academic success of English learners. Journal of Science Education & Technology, 21, 494 – 503.</bibtext> </blist> <blist> <bibl id="bib3" type="bt">3</bibl> <bibtext> *Boyle, S., McCoy, A., McNaughton, D., & Light, J. (2017). Using digital texts in interactive reading activities for children with language delays and disorders: A review of the research literature and pilot study. Seminars in Speech and Language, 38, 263 – 275.</bibtext> </blist> <blist> <bibl id="bib4" type="bt">4</bibl> <bibtext> *Browder, D. M., Root, J. R., Wood, L., & Allison, C. (2017). Effects of story‐mapping procedure using the iPad on the comprehension of narrative texts by students with autism spectrum disorder. Focus on Autism and Other Developmental Disabilities, 32, 243 – 255.</bibtext> </blist> <blist> <bibl id="bib5" type="bt">5</bibl> <bibtext> *Brown, H. Q. (2016). Examining the effects of school‐provided e‐readers on middle school students' reading ability. Journal of Educational Technology Systems, 44, 404 – 410.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref77" type="bt">6</bibl> <bibtext> *Bryant, B. R., Ok, M., Kang, E. Y., Kim, M. K., Lang, R., Bryant, D. P., & Pfannestiel, K. (2015). Performance of fourth‐grade students with learning disabilities on multiplication facts comparing teacher‐mediated and technology‐mediated interventions: A preliminary investigation. Journal of Behavioral Education, 24, 255 – 272.</bibtext> </blist> <blist> <bibl id="bib7" type="bt">7</bibl> <bibtext> *Bryant, B. R., Kim, M. K., Ok, M. W., Kang, E. Y., Bryant, D. P., Lang, R., & Son, S. H. (2015). A comparison of the effects of reading interventions on engagement and performance for fourth‐grade students with learning disabilities. Behavior Modification, 39, 167 – 190.</bibtext> </blist> <blist> <bibl id="bib8" type="bt">8</bibl> <bibtext> *Burton, C. E., Anderson, D. H., Prater, M. A., & Dyches, T. T. (2013). Video self‐modeling on an iPad to teach functional math skills to adolescents with Autism and Intellectual Disability. Focus on Autism and Other Developmental Disabilities, 28, 67 – 77.</bibtext> </blist> <blist> <bibl id="bib9" type="bt">9</bibl> <bibtext> *Caron, J., Light, J., Holyfield, C., & McNaughton, D. (2018). Effects of dynamic text in an AAC app on sight word reading for individuals with autism spectrum disorder. Augmentative and Alternative Communication, 32, 143 – 154.</bibtext> </blist> <blist> <bibtext> *Carr, J. M. (2012). Does math achievement h'APP'en when iPads and game‐based learning are incorporated into fifth‐grade mathematics instruction? Journal of Information Technology Education: Research, 11, 269 – 285.</bibtext> </blist> <blist> <bibtext> *Chai, Z. (2017). Improving early reading skills in young children through an iPad app: Small‐group instruction and observational learning. Rural Special Education Quarterly, 36, 101 – 111.</bibtext> </blist> <blist> <bibtext> *Chai, Z., Vail, C. O., & Ayres, K. M. (2015). Using an iPad application to promote early literacy development in young children with disabilities. The Journal of Special Education, 48, 268 – 278.</bibtext> </blist> <blist> <bibtext> *Chang, K. E., Lan, Y. J., Chang, C. M., & Sung, Y. T. (2010). Mobile‐device‐supported strategy for Chinese reading comprehension. Innovations in Education and Teaching International, 47, 69 – 84.</bibtext> </blist> <blist> <bibtext> *Creech‐Galloway, C., Collins, B. C., Knight, V., & Bausch, M. (2013). Using a simultaneous prompting procedure with an iPad to teach the Pythagorean Theorem to adolescents with moderate Intellectual Disability. Research and Practice for Persons with Severe Disabilities, 38, 222 – 232.</bibtext> </blist> <blist> <bibtext> *Crowley, K., McLaughlin, T., & Kahn, R. (2013). Using direct instruction flashcards and reading racetracks to improve sight word recognition of two elementary students with autism. Journal of Developmental and Physical Disabilities, 25, 297 – 311.</bibtext> </blist> <blist> <bibtext> *D'Agostino, J. V., Rodgers, E., Harmey, S., & Brownfield, K. (2016). Introducing an iPad app into literacy instruction for struggling readers: Teacher perceptions and student outcomes. Journal of Early Childhood Literacy, 16, 522 – 548.</bibtext> </blist> <blist> <bibtext> *El Zein, F., Gevarter, C., Bryant, B., Son, S. H., Bryant, D., Kim, M., & Solis, M. (2015). A comparison between ipad‐assisted and teacher‐directed reading instruction for students with autism spectrum disorder (ASD). Journal of Developmental and Physical Disabilities, 28, 195 – 215.</bibtext> </blist> <blist> <bibtext> *Fabian, K., Topping, K. J., & Barron, I. G. (2018). Using mobile technologies for mathematics: Effects on student attitudes and achievement. Education Technology Research & Development, 66, 1119 – 1139.</bibtext> </blist> <blist> <bibtext> Fisher, Z., & Tipton, E. (2015). Robumeta: An R‐package for robust variance estimation in meta‐analysis (R package version 1.6). http://CRAN.R‐project.org/package=robumeta</bibtext> </blist> <blist> <bibtext> *Halloluwa, T., Vyas, D., Usoof, H., & Hewagamage, K. P. (2018). Gamification for development: A case of collaborative learning in Sri Lankan primary schools. Personal & Ubiquitous Computing, 22, 391 – 407.</bibtext> </blist> <blist> <bibtext> *Hallstedt, M. H., Klingberg, T., & Ghaderi, A. (2018). Short and long‐term effects of a mathematics tablet intervention for low performing second graders. Journal of Educational Psychology. Advance online publication. https://doi.org/10.1037/edu0000264</bibtext> </blist> <blist> <bibtext> *Haydon, T., Hawkins, R., Denune, H., Kimener, L., McCoy, D., & Basham, J. (2012). A comparison of iPads and worksheets on math skills of high school students with emotional disturbance. Behavioral Disorders, 37, 232 – 243.</bibtext> </blist> <blist> <bibtext> *Hung, C. Y., Sun, J. C. Y., & Yu, P. T. (2015). The benefits of a challenge: Student motivation and flow experience in tablet‐PC‐game‐based learning. Interactive Learning Environments, 23, 172 – 190.</bibtext> </blist> <blist> <bibtext> *Hwang, W. Y., Chen, H. S. L., Shadiev, R., Huang, R. Y. M., & Chen, C. Y. (2014). Improving English as a foreign language writing in elementary schools using mobile devices in familiar situational contexts. Computer Assisted Language Learning, 27, 359 – 378.</bibtext> </blist> <blist> <bibtext> *Jackson, A. T., Brummel, B. J., Pollet, C. L., & Greer, D. D. (2013). An evaluation of interactive tabletops in elementary mathematics education. Educational Technology Research and Development, 61, 311 – 332.</bibtext> </blist> <blist> <bibtext> *Kellems, R. O., Frandsen, K., Hansen, B., Gabrielsen, T., Clarke, B., Simons, K., & Clements, K. (2016). Teaching multi‐step math skills to adults with disabilities via video prompting. Research in Developmental Disabilities, 58, 31 – 44.</bibtext> </blist> <blist> <bibtext> *Kiger, D., Herro, D., & Prunty, D. (2012). Examining the influence of a mobile learning intervention on third grade math achievement. Journal of Research on Technology in Education, 45, 61 – 82.</bibtext> </blist> <blist> <bibtext> *Kosko, K. W., & Ferdig, R. E. (2016). Effects of a tablet‐based mathematics application for pre‐school children. Journal of Computers in Mathematics and Science Teaching, 35, 61 – 79.</bibtext> </blist> <blist> <bibtext> *Lan, Y. J., Sung, Y. T., & Chang, K. E. (2009). Let us read together: Development and evaluation of a computer‐assisted reciprocal early English reading system. Computers & Education, 53, 1188 – 1198.</bibtext> </blist> <blist> <bibtext> *Larabee, K. M., Burns, M. K., & Mccomas, J. J. (2014). Effects of an iPad‐supported phonics intervention on decoding performance and time on‐task. Journal of Behavioral Education, 23, 449 – 469.</bibtext> </blist> <blist> <bibtext> *Lin, C. (2017). Learning English with electronic textbooks on tablet PCs. Interactive Learning Environments, 25, 1035 – 1047.</bibtext> </blist> <blist> <bibtext> *Lin, C. C. (2014). Learning English reading in a mobile‐assisted extensive reading program. Computers & Education, 78, 48 – 59.</bibtext> </blist> <blist> <bibtext> *Lorah, E. R., & Parnell, A. (2014). The acquisition of letter writing using a portable multi‐media player in young children with developmental disabilities. Journal of Developmental and Physical Disabilities, 26, 655 – 666.</bibtext> </blist> <blist> <bibtext> *Masataka, N. (2014). Development of reading ability is facilitated by intensive exposure to a digital children's picture book. Frontiers in Psychology, 5, 1 – 4. https://doi.org/10.3389/fpsyg.2014.00396</bibtext> </blist> <blist> <bibtext> *McKeown, D., Kimball, K., & Ledford, J. (2015). Effects of asynchronous audio feedback on the story revision practices of students with emotional/behavioral disorders. Education and Treatment of Children, 38, 541 – 564.</bibtext> </blist> <blist> <bibtext> *McLaughlin, R., & Kamei‐Hannan, C. (2018). Paper or digital text: Which reading medium is best for students with visual impairments? Journal of Visual Impairment & Blindness, 112, 337 – 350.</bibtext> </blist> <blist> <bibtext> *Moser, G. P., Morrison, T. G., & Wilcox, B. (2017). Supporting fourth‐grade students' word identification using application software. Reading Psychology, 38, 349 – 368.</bibtext> </blist> <blist> <bibtext> *Musti‐Rao, S., & Plati, E. (2015). Comparing two classwide interventions: Implications of using technology for increasing multiplication fact fluency. Journal of Behavioral Education, 24, 418 – 437.</bibtext> </blist> <blist> <bibtext> *Musti‐Rao, S., Lo, Y., & Plati, E. (2015). Using an iPad app to improve sight word reading fluency for at‐risk first graders. Remedial and Special Education, 36, 154 – 166.</bibtext> </blist> <blist> <bibtext> *Nicholas, M., McKenzie, S., & Wells, M. A. (2017). Using digital devices in a first year classroom: A focus on design and use of phonics software applications. Journal of Education and Learning, 6, 267 – 282.</bibtext> </blist> <blist> <bibtext> *Nordness, P. D., Haverkost, A., & Volberding, A. (2011). An examination of hand‐held computer‐assisted instruction on subtraction skills for second grade students with learning and behavioral difficulties. Journal of Special Education Technology, 26, 15 – 24.</bibtext> </blist> <blist> <bibtext> *Ok, M. W., & Bryant, D. P. (2016). Effects of a strategic intervention with iPad practice on the multiplication fact performance of fifth‐grade students with learning disabilities. Learning Disability Quarterly, 39, 146 – 158.</bibtext> </blist> <blist> <bibtext> R Core Team (2016). R: A language and environment for statistical computing. Vienna, Austria : R Foundation for Statistical Computing. Retrieved from. https://www.R‐project.org/</bibtext> </blist> <blist> <bibtext> *Ozbek, A. B., & Girli, A. (2017). The effectiveness of a tablet computer‐aided intervrenton program for improving reading fluency. Universal Journal of Educational Research, 5, 757 – 764.</bibtext> </blist> <blist> <bibtext> *Piatt, C., Coret, M., Choi, M., Volden, J., & Bisanz, J. (2015). Comparing children's performance on and preference for a number‐line estimation task: Tablet versus paper and pencil. Journal of Psychoeducational Assessment, 34, 244 – 255.</bibtext> </blist> <blist> <bibtext> *Piper, B., Zuilkowski, S. S., Kwayumba, D., & Strigel, C. (2016). Does technology improve reading outcomes? Comparing the effectiveness and cost‐effectiveness of ICT interventions for early grade reading in Kenya. International Journal of Educational Development, 49, 204 – 214.</bibtext> </blist> <blist> <bibtext> *Pitchford, N. J. (2015). Development of early mathematical skills with a tablet intervention: A randomized control trial in Malawi. Frontiers in Psychology, 6, 1 – 12.</bibtext> </blist> <blist> <bibtext> *Purazella, K., & Mechling, L. C. (2013). Evaluation of manual spelling, observational and incidental learning using computer‐based instruction with a tablet PC, large screen projection, and a forward chaining procedure. Education and Training in Autism and Developmental Disabilities, 48, 218 – 235.</bibtext> </blist> <blist> <bibtext> *Redcay, J. D., & Preston, S. M. (2016). Improving second grade student's reading fluency and comprehension using teacher‐guided iPad app instruction. Interactive Technology and Smart Education, 13, 218 – 228.</bibtext> </blist> <blist> <bibtext> *Reeves, J. L., Gunter, G. A., & Lacey, C. (2017). Mobile learning in pre‐kindergarten: Using student feedback to inform practice. Educational Technology & Society, 20, 37 – 44.</bibtext> </blist> <blist> <bibtext> *Regan, K., Evmenova, A. S., Good, K., Legget, A., Ahn, S. Y., Gafurov, B., & Mastropieri, M. (2018). Persuasive writing with mobile‐based graphic organizers in inclusive classrooms across the curriculum. Journal of Special Education Technology, 33, 3 – 14.</bibtext> </blist> <blist> <bibtext> *Riconscente, M. M. (2013). Results from a controlled study of the iPad fractions game Motion Math. Games and Culture, 8, 186 – 214.</bibtext> </blist> <blist> <bibtext> *Schacter, J., & Jo, B. (2016). Improving low‐income preschoolers mathematics achievement with Math Shelf, a preschool tablet computer curriculum. Computers in Human Behavior, 55, 223 – 229.</bibtext> </blist> <blist> <bibtext> Scruggs, T. E., Mastropieri, M. A., Cook, S. B., & Escobar, C. (1986). Early intervention for children with conduct disorders: a quantitative synthesis of single‐subject research. Behavioral Disorders, 11, 260 – 271.</bibtext> </blist> <blist> <bibtext> *Seok, S., DaCosta, B., & Yu, B. M. (2015). Spelling practice intervention: A comparison of tablet PC and picture cards as spelling practice methods for students with developmental disabilities. Education and Training in Autism and Developmental Disabilities, 50, 84 – 94.</bibtext> </blist> <blist> <bibtext> *Smith, B. R., Spooner, F., & Wood, C. L. (2013). Using embedded computer‐assisted explicit instruction to teach science to students with autism spectrum disorder. Research in Autism Spectrum Disorders, 7, 433 – 443.</bibtext> </blist> <blist> <bibtext> *Spooner, F., Ahlgrim‐Delzell, L., Kemp‐Inman, A., & Wood, L. A. (2014). Using an iPad2® with systematic instruction to teach shared stories for elementary‐aged students with autism. Research and Practice for Persons with Severe Disabilities, 39, 30 – 46.</bibtext> </blist> <blist> <bibtext> *Spooner, F., Kemp‐Inman, A., Ahlgrim‐Delzell, L., Wood, L., & Ley davis, L. (2015). Generalization of literacy skills through portable technology for students with severe disabilities. Research and Practice for Persons with Severe Disabilities, 40, 52 – 70.</bibtext> </blist> <blist> <bibtext> *van der Ven, F., Segers, E., Takashima, A., & Verhoeven, L. (2017). Effects of a tablet game intervention on simple additiona and subtraction fluency in first graders. Computers in Human Behavior, 72, 200 – 207.</bibtext> </blist> <blist> <bibtext> *Van Gorp, K., Segers, E., & Verhoeven, L. (2017). Enhancing decoding efficiency in poor readers via a word identification game. Reading Research Quarterly, 52, 105 – 123.</bibtext> </blist> <blist> <bibtext> *Volk, M., Cotic, M., Zajc, M., & Starcic, A. I. (2017). Tablet‐based cross‐curricular maths vs. traditional maths classroom practice for higher‐order learning outcomes. Computers & Education, 114, 1 – 23.</bibtext> </blist> <blist> <bibtext> *Walczak, S., & Taylor, N. G. (2018). Geography learning in primary school: Comparing face‐to‐face tablet‐based instruction methods. Computers & Education, 117, 188 – 198.</bibtext> </blist> <blist> <bibtext> *Wollscheid, S., Sjaastad, J., Tomte, C., & Lover, N. (2016). The effect of pen and paper or tablet computer on early writing – A pilot study. Computers & Education, 98, 70 – 80.</bibtext> </blist> <blist> <bibtext> *Yakubova, G., Hughes, E. M., & Hornberger, E. (2015). Video‐based intervention in teaching fraction problem‐solving to students with Autism Spectrum Disorder. Journal of Autism and Developmental Disorders, 45, 2865 – 2875.</bibtext> </blist> <blist> <bibtext> *Yang, C. C., Hwang, G. J., Hung, C. M., & Tseng, S. S. (2013). A n evaluation of the leraning effectiveness of concept map‐based science book reading via mobile devices. Journal of Educational Technology & Society, 16, 167 – 178.</bibtext> </blist> <blist> <bibtext> *Yang, E. F. Y., Chang, B., Cheng, H. N. H., & Chan, T. W. (2016). I mproving pupils' mathematical communication abilities through computer‐supported reciprocal peer tutoring. Educational Technology & Society, 19, 157 – 169.</bibtext> </blist> <blist> <bibtext> Alzrayer, N., Banda, D. R., & Koul, R. K. (2014). Use of iPad/iPods with individuals with Autism and other developmental disabilities: A meta‐analysis of communication interventions. Review Journal of Autism and Developmental Disorders, 1, 179 – 191.</bibtext> </blist> <blist> <bibtext> Arizona Software (2012). GraphClick 3.0.3. (http://www.arizona‐software.ch/graphclick/)</bibtext> </blist> <blist> <bibtext> Bebell, L. M., Ngonzi, Siedner, M. J., Muyindike, W. R., Bwana, B. M., Riley, L. E., ..., Bassett, I. V. (2010). One to one computing: A summary of the quantitative results from the Berkshire Wireless Learning Initiative. The Journal of Technology, Learning, and Assessment, 9, 5 – 59.</bibtext> </blist> <blist> <bibtext> Begg, C. B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics, 50, 1088 – 1101. https://doi.org/10.2307/2533446</bibtext> </blist> <blist> <bibtext> Interactive Educational Systems Design, Inc (2014). Educator Edition: 2014 National Survey on Mobile Technology for Education. New York, NY : Amplify.</bibtext> </blist> <blist> <bibtext> Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta‐analysis. New York : Wiley</bibtext> </blist> <blist> <bibtext> Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2015). Comprehensive meta‐analysis (v. 3.3.070), Englewood, NJ : Biostat.</bibtext> </blist> <blist> <bibtext> Cheung, A. C. K., & Slavin, R. E. (2012). How features of educational technology applications affect student reading outcomes: A meta‐analysis. Educational Research Review, 7, 198 – 215.</bibtext> </blist> <blist> <bibtext> Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ : Lawrence Earlbaum Associates.</bibtext> </blist> <blist> <bibtext> Duval, S., & Tweedie, R. (2000). A nonparametric "trim and fill" method of accounting for publication bias in meta‐analysis. Journal of the American Statistical Association, 95, 89 – 98. https://doi.org/10.1080/01621459.2000.10473905</bibtext> </blist> <blist> <bibtext> Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta‐analysis detected by a simple, graphical test. British Medical Journal, 315, 629 – 635. https://doi.org/10.1136/bmj.315.7109.629</bibtext> </blist> <blist> <bibtext> ESSA (2015). Every Student Succeeds Act of 2015, Pub. L. No. 114‐95 § 114 Stat. 1177 (2015‐2016).</bibtext> </blist> <blist> <bibtext> Ferenstein, G. (2011). How the iPad 2 will revolutionize education. Fast Company. Retrieved from. <ulink href="http://www.fastcompany.com/1733662/how‐ipad‐2‐will‐revolutionize‐education">http://www.fastcompany.com/1733662/how‐ipad‐2‐will‐revolutionize‐education</ulink></bibtext> </blist> <blist> <bibtext> Gagne, R. M., Wager, W. W., Golas, K. C., & Keller, J. M. (2004). Principles of instructional design (5th ed.). Belmont, CA : Wadsworth Publishing.</bibtext> </blist> <blist> <bibtext> Gersten, R., Fuchs, L. S., Compton, D., Coyne, M., Greenwood, C., & Innocenti, M. S. (2005). Quality indicators for group experimental and quasi‐experimental research in special education. Exceptional Children, 71, 149 – 164.</bibtext> </blist> <blist> <bibtext> Hattie, J. (2009). Visible learning: A synthesis of over 800 meta‐analyses relating to achievement. London : Routledge.</bibtext> </blist> <blist> <bibtext> Hedges, L. V. (1981). Distribution theory for Glass's estimator of effect size and related estimators. Journal of Educational and Behavior Statistics, 6, 107 – 128. https://doi.org/10.3102/10769986006002107</bibtext> </blist> <blist> <bibtext> Hedges, L. V., Pustejovsky, J. E., & Shadish, W. R. (2012). A standardized mean difference effect size for single case designs. Research Synthesis Methods, 3, 224 – 239.</bibtext> </blist> <blist> <bibtext> Hedges, L. V., Pustejovsky, J. E., & Shadish, W. R. (2013). A standardized mean difference effect size for multiple baseline designs across individuals. Research Synthesis Methods, 4, 324 – 341. https://doi.org/10.1002/jrsm.1086</bibtext> </blist> <blist> <bibtext> Higgins, J. P., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta‐analyses. British Medical Journal, 327, 557 – 560. https://doi.org/10.1136/bmj.327.7414.557</bibtext> </blist> <blist> <bibtext> Hong, E. R., Gong, L., Ninci, J., Morin, K., Davis, J. L., Kawaminami, S., ..., Noro, F. (2017). A meta‐analysis of single‐case research on the use of tablet‐mediated interventions for persons with ASD. Research in Developmental Disabilities, 70, 198 – 214.</bibtext> </blist> <blist> <bibtext> Horner, R. H., Carr, E. G., Halle, J., McGee, G., Odom, S., & Wolery, M. (2005). The use of single subject research to identify evidence‐based practice in special education. Exceptional Children, 71, 165 – 179.</bibtext> </blist> <blist> <bibtext> Jitendra, A. K., Burgess, C., & Gajria, M. (2011). Cognitive strategy instruction for improving expository text comprehension of students with learning disabilities: The quality of evidence. Exceptional Children, 77, 135 – 159.</bibtext> </blist> <blist> <bibtext> Kagohara, D. M., van der Meer, L., Ramdoss, S., O'Reilly, M. F., Lancioni, G. E., Davis, T. N., ..., Sigafoos, J. (2013). Using iPods and iPads in teaching programs for individuals with developmental disabilities: A systematic review. Research in Developmental Disabilities, 34, 147 – 156.</bibtext> </blist> <blist> <bibtext> Kim, M. K., Park, Y., & Coleman, M. B. (2017). The quality of evidence in tablet‐assisted interventions for students with disabilities. Journal of Computer Assisted Learning, 33, 547 – 561.</bibtext> </blist> <blist> <bibtext> Knapp, G., & Hartung, J. (2003). Improved tests for a random effects meta‐regression with a single covariate. Statistics in Medicine, 22, 2693 – 2710. https://doi.org/10.1002/sim.1482</bibtext> </blist> <blist> <bibtext> Kucirkova, N. (2014). iPads in early education: Separating assumptions and evidence. Frontiers in Psychology, 5, 1 – 3. https://doi.org/10.3389/fpsyg.2014.00715</bibtext> </blist> <blist> <bibtext> Lapowsky, I. (2015). What schools must learn from LA's iPad debacle. Wired. Retrieved from. https://<ulink href="http://www.wired.com/2015/05/los‐angeles‐edtech/">www.wired.com/2015/05/los‐angeles‐edtech/</ulink></bibtext> </blist> <blist> <bibtext> Melhuish, K., & Falloon, G. (2010). Looking to the future: M‐learning with the iPad. Computers in New Zealand Schools: Learning, Leading, Technology, 22, 1 – 16.</bibtext> </blist> <blist> <bibtext> National Governors Association Center for Best Practices & Council of Chief State School Officers (2010). Common Core State Standards. Retrieved from <ulink href="http://www.corestandards.org">http://www.corestandards.org</ulink></bibtext> </blist> <blist> <bibtext> Ok, M. W., & Kim, W. (2017). Use of iPads and iPods for academic performance and engagement of Prek‐12 students with disabilities: A research synthesis. Exceptionality, 25, 54 – 75. https://doi.org/10.1080/09362835.2016.1196446</bibtext> </blist> <blist> <bibtext> Parker, R. I., Vannest, K. J., & Davis, J. L. (2014). Non‐overlap analysis for single‐case research. In Kratochwill, T. R., & Levin, J. R. (Eds.), Single‐case intervention research: methodological and statistical advances (pp. 127 – 152). Washington DC : American Psychological Association.</bibtext> </blist> <blist> <bibtext> Pressley, M., & Harris, K. R. (1994). Increasing the quality of educational intervention research. Educational Psychology Review, 6, 191 – 208.</bibtext> </blist> <blist> <bibtext> Pustejovsky, J. E., Hedges, L. V., & Shadish, W. R. (2014). Design‐comparable effect sizes in multiple baseline designs: A general modeling framework. Journal of Educational and Behavioral Statistics, 39, 368 – 393. https://doi.org/10.3102/1076998614547577</bibtext> </blist> <blist> <bibtext> Pustejovsky, J.E. (2016). scdhlm: Estimating hierarchical linear models for single‐case designs (Version 0.3.1). Retrived from: https://github.com/jepusto/scdhlm</bibtext> </blist> <blist> <bibtext> Rosenthal, R., & DiMatteo, M. R. (2001). Meta‐analysis: Recent developments in quantitative methods for literature reviews. Annual Review of Psychology, 52, 59 – 82.</bibtext> </blist> <blist> <bibtext> Shadish, W. R., Zelinsky, N. A. M., Vevea, J. L., & Kratochwill, T. R. (2016). A survey of publication practices of single‐case design researchers when treatments have small or large effects. Journal of Applied Behavior Analysis, 49, 656 – 673. https://doi.org/10.1002/jaba.308</bibtext> </blist> <blist> <bibtext> Tarlow, K. R. (2017). An improved rank correlation effect size statistic for single‐case designs: Baseline corrected Tau. Behavior Modification, 41, 427 – 467. https://doi.org/10.1177/0145445516676750</bibtext> </blist> <blist> <bibtext> Tarlow, K.R. (2018). Baseline Corrected Tau Calculator. Retreived from: <ulink href="http://ktarlow.com/stats/tau/">http://ktarlow.com/stats/tau/</ulink></bibtext> </blist> <blist> <bibtext> Tipton, E. (2015). Small sample adjustments for robust variance estimation with meta‐regression. Psychological Methods, 20, 375 – 393. https://doi.org/10.1037/met0000011</bibtext> </blist> <blist> <bibtext> U.S. Department of Education, Institute of Education Sciences, What Works Clearinghouse. (2016, September). What Works Clearinghouse: Procedures and Standards Handbook (Version 3.0). Retrieved from <ulink href="http://whatworks.ed.gov">http://whatworks.ed.gov</ulink></bibtext> </blist> <blist> <bibtext> U.S. Department of Education, National Center for Education Statistics. (2016). Digest of Education Statistics, 2015 (NCES 2016‐014), Chapter 7. Retrieved from https://nces.ed.gov/fastfacts</bibtext> </blist> <blist> <bibtext> Viechtbauer, W. (2010). Conducting meta‐analyses in R with the metafor package. Journal of Statistical Software, 36, 1 – 48.</bibtext> </blist> <blist> <bibtext> Wolf, F. M. (1986). Meta‐analysis: Quantitative Methods for Research Synthesis, Sage. Newbury Park, CA.</bibtext> </blist> </ref> <aug> <p>By Shawna M. Petersen‐Brown; Erin E. C. Henze; David A. Klingbeil; Jennifer L. Reynolds; Rachel C. Weber and Robin S. Codding</p> <p>Reported by Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib74" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib108" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib96" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib90" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib94" firstref="ref5"></nolink> <nolink nlid="nl6" bibid="bib79" firstref="ref6"></nolink> <nolink nlid="nl7" bibid="bib69" firstref="ref7"></nolink> <nolink nlid="nl8" bibid="bib93" firstref="ref8"></nolink> <nolink nlid="nl9" bibid="bib30" firstref="ref9"></nolink> <nolink nlid="nl10" bibid="bib95" firstref="ref10"></nolink> <nolink nlid="nl11" bibid="bib71" firstref="ref13"></nolink> <nolink nlid="nl12" bibid="bib67" firstref="ref15"></nolink> <nolink nlid="nl13" bibid="bib54" firstref="ref16"></nolink> <nolink nlid="nl14" bibid="bib97" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib91" firstref="ref19"></nolink> <nolink nlid="nl16" bibid="bib81" firstref="ref20"></nolink> <nolink nlid="nl17" bibid="bib88" firstref="ref21"></nolink> <nolink nlid="nl18" bibid="bib89" firstref="ref22"></nolink> <nolink nlid="nl19" bibid="bib87" firstref="ref23"></nolink> <nolink nlid="nl20" bibid="bib110" firstref="ref32"></nolink> <nolink nlid="nl21" bibid="bib102" firstref="ref33"></nolink> <nolink nlid="nl22" bibid="bib80" firstref="ref41"></nolink> <nolink nlid="nl23" bibid="bib107" firstref="ref42"></nolink> <nolink nlid="nl24" bibid="bib28" firstref="ref43"></nolink> <nolink nlid="nl25" bibid="bib34" firstref="ref44"></nolink> <nolink nlid="nl26" bibid="bib68" firstref="ref46"></nolink> <nolink nlid="nl27" bibid="bib83" firstref="ref47"></nolink> <nolink nlid="nl28" bibid="bib73" firstref="ref48"></nolink> <nolink nlid="nl29" bibid="bib104" firstref="ref49"></nolink> <nolink nlid="nl30" bibid="bib105" firstref="ref50"></nolink> <nolink nlid="nl31" bibid="bib100" firstref="ref52"></nolink> <nolink nlid="nl32" bibid="bib85" firstref="ref53"></nolink> <nolink nlid="nl33" bibid="bib84" firstref="ref56"></nolink> <nolink nlid="nl34" bibid="bib43" firstref="ref58"></nolink> <nolink nlid="nl35" bibid="bib101" firstref="ref59"></nolink> <nolink nlid="nl36" bibid="bib19" firstref="ref60"></nolink> <nolink nlid="nl37" bibid="bib109" firstref="ref61"></nolink> <nolink nlid="nl38" bibid="bib92" firstref="ref63"></nolink> <nolink nlid="nl39" bibid="bib72" firstref="ref64"></nolink> <nolink nlid="nl40" bibid="bib86" firstref="ref65"></nolink> <nolink nlid="nl41" bibid="bib103" firstref="ref67"></nolink> <nolink nlid="nl42" bibid="bib70" firstref="ref68"></nolink> <nolink nlid="nl43" bibid="bib77" firstref="ref69"></nolink> <nolink nlid="nl44" bibid="bib76" firstref="ref70"></nolink> <nolink nlid="nl45" bibid="bib39" firstref="ref71"></nolink> <nolink nlid="nl46" bibid="bib26" firstref="ref72"></nolink> <nolink nlid="nl47" bibid="bib48" firstref="ref73"></nolink> <nolink nlid="nl48" bibid="bib45" firstref="ref74"></nolink> <nolink nlid="nl49" bibid="bib21" firstref="ref75"></nolink> <nolink nlid="nl50" bibid="bib33" firstref="ref78"></nolink> <nolink nlid="nl51" bibid="bib82" firstref="ref85"></nolink> <nolink nlid="nl52" bibid="bib75" firstref="ref86"></nolink> <nolink nlid="nl53" bibid="bib98" firstref="ref87"></nolink> <nolink nlid="nl54" bibid="bib99" firstref="ref94"></nolink>
Header DbId: eric
DbLabel: ERIC
An: EJ1221125
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Use of Touch Devices for Enhancing Academic Achievement: A Meta-Analysis
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Petersen-Brown%2C+Shawna+M%2E%22">Petersen-Brown, Shawna M.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-1509-165X">0000-0002-1509-165X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Henze%2C+Erin+E%2E+C%2E%22">Henze, Erin E. C.</searchLink><br /><searchLink fieldCode="AR" term="%22Klingbeil%2C+David+A%2E%22">Klingbeil, David A.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-2571-4424">0000-0003-2571-4424</externalLink>)<br /><searchLink fieldCode="AR" term="%22Reynolds%2C+Jennifer+L%2E%22">Reynolds, Jennifer L.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-5115-3547">0000-0002-5115-3547</externalLink>)<br /><searchLink fieldCode="AR" term="%22Weber%2C+Rachel+C%2E%22">Weber, Rachel C.</searchLink><br /><searchLink fieldCode="AR" term="%22Codding%2C+Robin+S%2E%22">Codding, Robin S.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Psychology+in+the+Schools%22"><i>Psychology in the Schools</i></searchLink>. Jul 2019 56(7):1187-1206.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 20
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2019
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Information Analyses
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Handheld+Devices%22">Handheld Devices</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Implementation%22">Program Implementation</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Outcomes+of+Education%22">Outcomes of Education</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/pits.22225
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0033-3085
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Touch devices such as tablets and smartphones are widely adopted in educational settings and have many desirable features. However, research supporting the use of touch devices to improve academic achievement is emergent and has not been evaluated through a meta-analysis. We conducted a meta-analysis of 65 group and single case design research studies, published 2010-2018, to evaluate the effects of touch device implementation on academic achievement. The overall mean effect sizes were moderate for group design and single case design studies. Participant, intervention, and study attributes were also evaluated to describe the research and how these attributes may moderate the results. Overall, results suggest that touch devices may be an effective tool for enhancing academic achievement. The need to conduct additional, rigorous research on the use of touch devices as well as implications for researchers and practitioners are discussed.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2019
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1221125
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1221125
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/pits.22225
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 1187
    Subjects:
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Handheld Devices
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Instructional Effectiveness
        Type: general
      – SubjectFull: Program Implementation
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Outcomes of Education
        Type: general
    Titles:
      – TitleFull: The Use of Touch Devices for Enhancing Academic Achievement: A Meta-Analysis
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Petersen-Brown, Shawna M.
      – PersonEntity:
          Name:
            NameFull: Henze, Erin E. C.
      – PersonEntity:
          Name:
            NameFull: Klingbeil, David A.
      – PersonEntity:
          Name:
            NameFull: Reynolds, Jennifer L.
      – PersonEntity:
          Name:
            NameFull: Weber, Rachel C.
      – PersonEntity:
          Name:
            NameFull: Codding, Robin S.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-print
              Value: 0033-3085
          Numbering:
            – Type: volume
              Value: 56
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Psychology in the Schools
              Type: main
ResultId 1