Using computer-assisted instruction to enhanceachievement of English language learners

Jared Keengwe & Farhan Hussein

Published online: 26 September 2012# Springer Science+Business Media New York 2012

Abstract Computer-assisted instruction (CAI) in English-Language environmentsoffer practice time, motivates students, enhance student learning, increase authenticmaterials that students can study, and has the potential to encourage teamworkbetween students. The findings from this particular study suggested that studentswho used computer assisted program had a greater chance of closing achievementgap and meeting NCLB requirements than those students who did not use computer-assisted instruction. Additionally, the students that used computer-assisted classroominstruction gained scores in reading and math. Based on these findings, teachers,school administrators, and other educational stakeholder should explore strategies fortechnology integration to close the achievement gap.

Keywords Computer-assisted instruction (CAI) . Computer technology .

Charter schools . English language learners (ELL) . Student achievement

1 Introduction

The African refugees began coming to Minnesota in the mid-1990s. During the civilwar that broke out in Somalia in 1991, hundreds of thousands of Somali citizens fledto neighboring countries where majority received resettlement aid from othercountries, including the United States. Refugee camps such as those in Kenya becameflooded with Somali refugees fleeing the violence and famine. These refugees later

Educ Inf Technol (2014) 19:295–306DOI 10.1007/s10639-012-9214-z

J. Keengwe (*)Department of Teaching and Learning, University of North Dakota, STOP 7189, Grand Forks,ND 58201, USAe-mail: jared.keengwe@email.und.edu

F. HusseinLighthouse Academy of Nations, Columbia Heights, MN 55421, USAe-mail: fhussein@lighthouse.charter.k12.mn.us

moved to the United States where the majority of them settled in large cities such asMinneapolis. In 1997, Somali population was the largest group of immigrants inMinnesota. The largest Somali community in the U.S. lives in Minnesota, mainly inMinneapolis (Herrel et al. 2004).

There are over seventy thousand Somalis have established their homes inMinnesota. They are concentrated in Minneapolis, Saint Paul, Rochester,Owatonna, Eden Prairie, St. Cloud, Marshall, and Mankato. Somali parents opposethe social and cultural freedoms that their children encounter in the U.S. Some ofthem keep their original culture, some adopt new culture, and some maintain bothcultures. They are Muslim and African—a combination of a minority culture, reli-gion, and race that provides for a different type of immigration issue. Their percep-tions are reflected in the schools their children attend—the charter schools.

There are about 2000 Somali students attending public schools in Minneapolis(Minneapolis Public Schools 2009). More than 10 charter schools have been estab-lished in Minneapolis to address the issues related to refugee and immigrant childreneducation that supports their assimilation into American culture and values theirethnic heritage. The charter schools are governed by a board of directors of parents,teachers, and community members elected by school community and serve more than5,000 including Somali children. Students living throughout the metro area have achoice to attend any of these charter schools.

2 English-language learners

English-language learners (ELL) consist of the fastest growing percentage of theoverall student body (National Clearinghouse for English Language Acquisition andLanguage Instruction Education Programs (NCLEA) 2007). In 1979 to 2003, theELL students increased by 124 %, while other student populations increased by 19 %(National Center for Education Statistics 2004). Additionally, ELL students arespread all over other several states in the nation (Capps et al. 2005; Flynn and Hill2005). About 8 out of 10 ELL students speak Spanish, but some districts havestudents who represent more than 100 different language groups (NationalClearinghouse for English Language Acquisition and Language InstructionEducation Programs (NCLEA) 2007).

The ratio of computer use in United Stated Schools has declined dramaticallyevery year. The U.S. Department of Education (2005) reported that the ratio ofstudents using instructional computers with Internet declined to the ratio of 3.8 to 1in 2005 from 12.1 in 1998. Further, during the same time, Internet access increasedexponentially. Generally, many schools today have computer technology resources inthe classroom. However, having computer technology resources alone it is notenough. According to Clark (1983), “the media are mere vehicles that deliverinstruction but do not influence student achievement any more than the truck thatdelivers our groceries causes changes in our nutrition” (p. 445).

There are many programs available that can assist students’ education, such asdiscrete educational software (DES), integrated learning systems (ILS), computer-assisted instruction (CAI) and computer-based instruction (CBI) (Murphy et al.2002). These tools have been in schools for more than two decades (Becker et al.

296 Educ Inf Technol (2014) 19:295–306

1999). With rapid technology advancement, educators have realized that technologycould help to develop second language learning pedagogy (Lai 2006). However, careshould be taken to ensure that technology tools do not undermine sound pedagogicalpractices (Keengwe 2007).

In a study to examine the effect of computer technology on learning and achieve-ment across all learning domains and all learner ages, Sivin-Kachala (1998) reportedthree major findings. First, that students in technology rich environments experiencedpositive effects on achievement in all major subject areas. Secondly, that students intechnology rich environments showed increased achievement in preschool throughhigher education for both regular and special needs children; and finally, that stu-dents’ attitude toward learning and their own self-concept improved consistentlywhen computers were used for instruction. However, he noted that specific studentpopulation, the software design, the educator’s role, and the level of student access tothe technology affected the level of effectiveness of educational technology tools.

Salaberry (2001) opposed technology-based pedagogy suggesting that it still notclear that any technology could provide similar pedagogical level of traditionallanguage learning instruction. As a result, school administrators should carefullymonitor technology expenditures (Beatty 2003; Cuban 2001). School leaders andsolid technology plan are the most important ingredients for implementing successfultechnology programs (Byrom and Bingham 2001). Computer technology availabilityand technology staff development has to go hand in hand (Sandholtz & Reilly 2004).Additionally, technology integration should focus on best practices in incorporatingtechnology into the curriculum as teaching tools (Keengwe and Onchwari 2008).

3 Computer-assisted instruction (CAI)

CAI generally refers to drill-and-practice, tutorials, simulation/interactive thinking,word processing, conferencing, and other activities (Fletcher-Flinn and Gravatt1995). Specifically, CAI consists of drill and practice, simulation tasks, instructionalgames, and tutorials; instruction can contain new material, and can be used alone oras an enhancement to traditional instructional methods (Bitter and Pierson 1999;Cotton 2001). CAI is one of the six best practices, which support literacy learning atthe elementary school level (Drake 2001). Proponents of CAI argue that there is apositive learning advantage for computer-assisted instruction when compared withtraditional instruction (Fletcher-Flinn and Gravatt 1995). Additionally, computertechnology makes learning easier, more efficient, and more motivating (Schacterand Fagnano 1999).

There are many reasons that educators should put computer technology in ELLenvironment: a) It gives a practice time, b) It motivates students, c) It enhance studentlearning, d) It increase authentic materials that students can study, and e) It encourageteam work between students (Lee 2000). In a meta-analysis of 500 studies, Kulik(1994) reported that CAI increased the positive attitudes of students toward learning,which resulted in increased learning. Similar to the findings of Niemiec and Walberg(1987), Kulik’s findings suggest that CAI is more effective in improving achievementof younger students and students with special learning needs. Students of lowersocio-economic status benefit more from CAI than do students who are from a more

Educ Inf Technol (2014) 19:295–306 297

advantaged environment (Cotton 2001). The findings from a comparison study inmotivation of elementary and intermediate level second-language students learningEnglish through print revealed that CAI increases motivation for learning English instudents whose primary language is not English (Garcia and Arias 2000).

Interactive visual media that computers provide allow language learners opportu-nity to enhance their problem solving and interpersonal communications skills(Kozma 1991). Further, computers can also enhance vocabulary development as wellas verbal language development. The computer-assisted language learning programscan also be wonderful stimuli for second language learning. Some studies suggestthat students learning increased up to 40 % faster through CAI instruction as thismode increases student time on task (Cotton 2001). Further, CAI boosts positiveattitudes of students toward learning. Many studies also suggest that CAI, when usedappropriately, can have enhance student learning (Tamim et al. 2011) especially onreading skills of pre-schoolers, elementary school students, at-risk students, and ELL(Chambers et al. 2008; Stetter and Hughs 2011).

4 Charter schools

There are about 500 charter schools nationwide in 40 states and the District ofColumbia, serving more than 1.6 million students. As a result, charter schools arefilling an educational gap that public schools cannot fill. Many educators believe thatcharter schools provide solutions for problems that public schools are facing. Manypublic school leaders admit to feeling pressure from angry parents as a result ofcompetition from charter schools. Public schools are facing competition becausemany parents feel that charter schools are viable alternatives to public schools fortheir children (Weil 2000).

The rationale behind charter schools is to create an alternative vision for schooling,to serve a specific population, to increase autonomy, to provide innovative publiceducation, and to be accountable to the public. The theory for chartering has fivecomponents: (a) adoption of charter school law; (b) creation of new or conversionschools; (c) creation of schools with more autonomy; (d) Accountability throughmarkets and governments; and (d) innovation and quality in charter schools (Bulkleyand Fisler 2002).

Finn et al. (2000) underscored the worry of many parents: that public schoolscannot meet the needs of their children that students are graduating from high schoolswithout the skills necessary for college and the work place. Evidently, there is a needfor the nation to reform the public education system as reflected in this study: “APublic Agenda Foundation study found that 61 % of Americans say academicstandards are too low in their own local schools. Parents routinely complain thattheir children are being allowed to ‘slide through’ without developing strong skills”(Nathan 1996, p. 12).

Many states have experienced dissatisfaction with public schools (Lazaridou andFris 2005). Further, many parents view public schools as bureaucratic and inefficientand the two authors suggested that public education should incorporate choices forthe parents, competition among schools, entrepreneurial opportunities, greater ac-countability, greater responsiveness to customers’ needs, decentralization of control,

298 Educ Inf Technol (2014) 19:295–306

and a dismantling of a monopoly. These ideas will surely generate vigorous debateabout reform in public schools. Additionally, the mission and vision of public schoolshave become more difficult since post-industrialization with the priorities being toeducate efficient employees who can work smart, and who have developed intellec-tual and problem-solving skills (Bond 2000).

Charter school funding is based on the number of students a school serves. Themore students a charter school can attract, the greater the likelihood that it will havesufficient operating funds to survive. In contrast, a charter school that fails to attractparents and students will lose money and, in all probability, it will not survive. Chubband Moe (1990) argued that efficiency, innovation, and student achievement are notthe only goals of charter schools, and proponents contend that charter schools willbreak down the monopoly that public schools have on education. If parents andstudents are seen as customers, as in a business model, they ought to have choice andthere should be competition.

Some charter schools have not lived up to their acclaimed potential. According tothe Minnesota Comprehensive Assessment of 2007, overall, charter schools inMinnesota have not performed academically as well as public schools (MinnesotaOffice of Legislative Auditory 2008). 50 % of charter schools made Adequate YearlyProgress (AYP) in 2007 while 68 % of district schools made AYP. In a studyconducted in Texas to compare the test scores of students at charter schools to thoseof students at public schools, Booker et al. (2005) found that charter school studentsperformed, on average, lower than the students at the public schools from which theyhad moved. Even so, in a study of Arizona’s charter schools, Solmon andGoldschmidt (2004) found that students entering charter schools got lower scoreson tests than did comparable students in public schools.

Charter schools in Minnesota have experienced high student mobility (MinnesotaOffice of Legislative Auditory 2008). For example, Lighthouse Academy of Nationsin Minneapolis had a 125 % mobility rate, and charter schools in Minneapolis had a23 % mobility rate, compared to Minneapolis public schools, which had a 2 % rate.Charter schools in the entire state had a 13 % mobility rate compared to the statewidepublic school mobility rate of less than 1 %. In addition, according to MPS (2009), inthe entire district of 1870 students, only 6 % were Somali speaking.

Public schools are facing challenges; but so, too, are charter schools. The EdutrainCharter School in Los Angeles was the first charter school in the United States toclose amidst allegations of the misuse of public funds. Finn et al. (2000) noted thatthe school was $1 million in debt, while the principal was leasing a $39,000 sports carwith a $7,000 down payment. The Arizona Career and Technology High Schoolclosed its doors because of management issues. The Urban League Charter in SanDiego closed because of a dispute among its stakeholders, even though student test

Educ Inf Technol (2014) 19:295–306 299

Table 1 shows how six Minneapolis high schools are doing in math and readingscores. The first three are public schools while the last three are charter schools. Fromthe date, only one school is making Adequate Yearly Progress (AYP), as defined byfederal and state standards. Most of the students in the charter schools are Somalis—few Somali students attend the three public schools. Table 1 also shows how EnglishLanguage Learners (Somali students) are doing in charter schools. Of the three publicschools, only one is meeting AYP requirements, although even that school is signif-icantly below the state’s target index, which is 50 % or above.

scores were high. This downward trend reveals the problems of management incom-petence, as well as negative feedback from stakeholders.

Charter schools in Minnesota attract large numbers of minority students, studentswho are eligible for free and reduced-price lunch, and immigrant students (MinnesotaOffice of Legislative Auditory 2008). 52 % of students enrolled in charter schools areminorities as compared to 22 % in public schools. In the charter schools, 53 % of thestudents are eligible for free and reduced lunch. 21 % of charter school students havelimited English, whereas 7 % of public schools students have limited Englishproficiency. Somali students attend high schools that are among the lowestperforming schools in the state.

4.1 Purpose of study

CAI could increase the cost of education and affect education equity (Gips et al.2004). Even so, the challenge in technology investment is to review the relationshipbetween CAI and student learning in the light of current learning theories, andpedagogical practices. Therefore, the purpose of this study was to examine therelationship in achievement gap between ELL students utilizing computer-assistedinstruction (CAI) and English language Learners (ELL) students relying solely ontraditional classroom instruction in two charter schools in Minnesota.

4.2 Dugsi Academy

Dugsi Academy is a charter school located in St Paul, Minnesota. Dugsi Academyhas just completed six years (opened since 2005) giving education service to immi-grant students. The school primarily serves Somalia immigrants. The school runsfrom kindergarten to eight grades. The educational programs are intended especiallyfor students who may not have academic assistance at home. Most of the students areunable to find assistance through conventional school programming. The childrentypically have trouble adjusting to school; many are below grade level, have Englishlanguage and skill deficiencies, and need to close the gap between them and main-stream children. Dugsi Academy strives to assist students to integrate into theAmerican-educational system at a pace that takes into consideration their academicpreparation and English language barriers. According to Minnesota Department of

Table 1 Selected Minneapolis high schools math and reading scores

School name Type Math proficiency Reading proficiency AYP

Edison Senior High Public 0 % 6.80 % No

Washburn Senior High Public 8.19 % 26.19 Yes

Roosevelt Senior High Public 0 % 17 % No

Lighthouse Academy of Nations Charter 0 % 0 % No

Ubah Medical Academy Charter 4.80 % 6.81 % No

Lincoln International School Charter 0 % 0 % No

Minnesota Department of Education

300 Educ Inf Technol (2014) 19:295–306

Education, this school has not met the No Child Left Behind (NCLB) requirementsfor over two years.

4.3 Rochester Math and Science Academy (RMSA)

Rochester Math and Science Academy (RMSA) is a second charter school located inRochester, Minnesota. The school serves mainly Somali immigrants. The School hasalso been in operation for over six years (opened since 2005). Currently, the schoolruns K-8 grades. The School blends its curriculum technology where students use atleast one hour a day computer-assisted classroom curriculum (CAC). CAC instruc-tion supplements the traditional curriculum. The mission of Rochester Math andScience Academy (RMSA) is to maximize opportunities for children through educa-tional innovation that will ensure their full development as healthy and positivecontributors to the greater community. RMSA strives to create a supportive familyteaching community that utilizes shared ideals, goals and experiences as a major toolfor fostering a comprehensive and challenging education. RMSA places the student atthe center of a diverse and mutually respectful educational community of teachers,parents, inter-generational community volunteers, and experienced teachers who willall act as guidance counselors and student advocates. This school has met NCLBrequirements for over two years.

5 Method

5.1 Sample selection

The researchers selected two charter schools because these schools have similarstudent demographics and are located in Minnesota, home to the largest Somalicommunity in the United States with an estimated population of more than 50,000.

Table 2 Descriptive statistics of the two schools

Descriptive statistics RMSA Dugsi Academy

Ethnicity-black 99 % 100 %

Free/reduced lunch 98 % 99 %

Special education 2 % 4 %

Number of students enrolled 250 280

Table 3 The percentage of students meeting NWEA Goal for fall 2009 to 2010

NWEA—Fall to Spring Test—2009 to 2010

Reading Percent Meeting NWEA Goal-RMSA Percent Meeting NWEA Goal-Dugsi

Math 69 % 28 %

Reading 61 % 27 %

Educ Inf Technol (2014) 19:295–306 301

These two schools are the only ones very similar in terms of the grades served (K-12)and the years of operation (about 6 years). 99 % of both schools are eligible for freeand reduced-price lunches. More than 60 % of the students at these charter schoolsare Somali speaking and, therefore, English Language Learners. One school imple-mented CIA to supplement traditional classroom instruction while the second schoolprimary uses traditional classroom lectures. Table 2 provides a summary of thecharter schools.

5.2 Procedure

The researchers collected data (state scores for math and readings) for two yearsfor the two schools to assess the achievement gap between English languagelearners (ELLs) utilizing computer-assisted instruction (CAI) in the classroom,and ELLs relying solely on traditional classroom instruction. Participating stu-dents in both schools also completed a brief survey before the intervention thatrevealed that the student populations in both schools were quite similar. Forinstance, almost 95 % of the students in both schools indicated that they didn’tget “homework” assistance at home and that their parents were not knowledge-able on basic computer skills.

6 Findings

NWEA adapts to each student’s instructional level, giving more information about thestudent’s specific skills, and also making it more engaging for the student; provides astable measure of growth, which can be tracked within the school year, and from yearto year; and helps students set individual learning goals, thus motivating their ownlearning. In the fall of 2010 to spring 2011, 80 % of students who had valid test score

Table 4 The percentage of students meeting NWEA Goal for fall 2010 to 2011

WEA—Fall to Spring Test—2010 to 2011

Reading Percent Meeting NWEA Goal-RMSA Percent Meeting NWEA Goal-Dugsi

Math 80 % 34 %

Reading 61 % 33 %

Table 5 2010–2011 MCATest Results

Rochester Math and Science Academy Dugsi Academy

Test Proficient Not proficient Number tested Proficient Not proficient Number tested

Reading 63.04 % 36.95 % 138 34.66 %% 65.33 % 150

Math 57.55 % 42.44 % 139 11.97 % 88.02 % 167

Minnesota Department of Education

302 Educ Inf Technol (2014) 19:295–306

met RMSA’s math target goal. During the same year, 61 % of students who had validtest score met MAP Northwest Evaluation Association (NWEA) goal. On other hand,Dugsi, 34 % of students met the math goal while 33 % of students met the readinggoal.

The findings indicated that students who used computer-assisted classroom tosupplement learning did better than the students who relied solely on traditionalclassroom lectures. Additionally, the computer-assisted classrooms were signifi-cantly close to the achievement gap more than the class that did not usecomputers. The school that implemented computer aid curriculum had alsohigher means in reading, language arts, and math. A summary of this informationis provided in Tables 3 and 4.

There were 138 and 139 students who were eligible to take MCA reading andMCA math in RMSA respectively. On other hand, there were 150 and 167 studentswho eligible to take MCA reading and MCA math in Dugsi Academy respectively. Asummary of this information is provided in Table 5.

A total of 127 students in RMSA were eligible to take state tests in reading andmath called MCA. A summary of this information is provided in Table 6.

7 Conclusion

Students that used technology as curriculum supplementary were more likely toachieve than students who did not use computer assisted classroom. In other words,students who had computer assisted program had a greater chance of closing achieve-ment gap and meeting NCLB requirements than students who did not use computeraid curriculum. The students that used computer assist classroom instruction gainedscores in reading and math. These findings support previous studies that documentedsignificant gains in computer based programs in ESL setting (Kang and Dennis 1995;Liaw 1997). This study shows that there is correlation between students’ achieve-ments and using computer-assisted instruction. However, technology tools must beused selectively and appropriately to supplement teaching (Wachira and Keengwe2011).

In some cases, school districts are investing more on computers (Cuban 2001) thatare not adequately utilized. Consequently, investment focus should be on facultyrather than on existing technology resources (Keengwe 2007). Planning for technol-ogy initiatives requires schools to focus on reasonable timelines. Staff training and

Table 6 2009–2010 MCATest Results

Rochester Math and Science Academy Dugsi Academy

Test Proficient Not proficient Number tested Proficient Not proficient Number tested

Reading 62.99 % 37.00 % 127 35.45 % 64.54 % 110

Math 66.92 % 33.07 % 127 26.16 % 73.83 % 107

Minnesota Department of Education

Educ Inf Technol (2014) 19:295–306 303

commitment to school’s learning goals also need to be part of this process. Given thatmany schools continue to spend thousands of dollars each year on technologyinvestments without any evidence of its impact on student learning, it is necessaryto have some technology audit to help a school or district make decisions onappropriate and cost-effective professional development, curriculum alignment andstaffing needs for the staff and students (Hubbell 2011).

School administrators should explore strategies for technology integration to closethe achievement gap. One possibility is the implementation of various 1:1 laptopcomputer initiatives. However, implementing a 1:1 laptop initiative requires muchmore than purchasing hardware and software; 1:1 laptop initiative requires generalknowledge of various tools that help students collaborate on projects and communi-cate with others, and teachers who are willing to lead students to learn with technol-ogy (Hubbell 2011). Teachers should embrace and incorporate new technology skillsto support student learning. Finally, schools must also allow ample time for teachersto learn, understand, and model sound pedagogical practices as well as innovativecomputer technology integration models (Bebell and O’Dwyer 2010).

References

Beatty, K. (2003). Teaching and researching computer-assisted language learning. Essex: Pearson Edu-cation Limited.

Bebell, D., & O’Dwyer, L. M. (2010). Special edition: Educational outcomes and research from 1:1computing settings. The Journal of Technology, Learning, and Assessment, 9(1). Retrieved fromhttp://escholarship.bc.edu/cgi/viewcontent.cgi?article01236&context0jtla

Becker, H. J., Ravitz, J. L., & Wong, Y. T. (1999). Teacher and teacher-directed student use of computers.Teaching, learning and computing national survey (Report no. 3). Irvine, California, USA: Center forResearch on Information Technology and Organizations at the University of California. Retrieved fromhttp://www.crito.uci.edu/tlc/findings/computeruse/

Bitter, G. G., & Pierson, M. E. (1999). Using technology in the classroom (4th ed.). Needham Heights:Allyn & Bacon.

Bond, W. L. (2000). The “R’s of schools reform” and the politics of reforming or replacing public schools.Journal of Educational Change, 1, 225–252.

Booker, K., Zimmer, R., & Buddin, R. (2005). The effect of charter schools on school peer composition.Santa Monica: Rand Corporation.

Bulkley, K., & Fisler, J. (2002). A review of the research on charter schools. Philadelphia, PA: Consortiumfor Policy Research in Education. (ERIC Document Reproduction Services No. ED477 868)

Byrom, E., & Bingham, M. (2001). Factors influencing the effective use of technology for teaching andlearning: Lessons learned from the SEIR-TEC intensive site schools. Retrieved from http://www.serve.org/seir-tec/publications/lessons.pdf

Capps, R., Fix, M., Murray, J., Ost, J., Passel, J. S., & Herwantoro, S. (2005). The New Demography ofAmerica’s Schools: Immigration and the No Child Left Behind Act. Retrieved from http://eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage _01/0000019b/80/1b/c5/24.pdf

Chambers, B., Abrami, P., Tucker, B., Slavin, R., Madden, N., Cheung, A., et al. (2008). Computer-assistedtutoring in success for all: reading outcomes for first graders. Journal of Research on EducationalEffectiveness, 1, 120–137.

Chubb, J. E., & Moe, T. M. (1990). Politics, markets, and America’s schools. Washington, DC: TheBrookings Institution. (ERIC Document Reproduction Services, ED336851)

Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53,4445–4460.

Cotton, K. (2001, August). Computer-assisted instruction. Northwest Regional Educational Library: SchoolImprovement Research Series, 10. Retrieved from http://www.nwrel.org/scpd/sirs/5/cu10.html

304 Educ Inf Technol (2014) 19:295–306

Cuban, L. (2001). Oversold and underused: Computers in schools 1980–2000. Cambridge: HarvardUniversity Press.

Drake, K. B. (2001). A study of technology-based best practices which support literacy learning inelementary schools. Unpublished doctoral dissertation, Pepperdine University, CA. Retrieved fromProQuest Digital Dissertations database.

Finn, J. R., Manno, B. V., & Vanourek, G. (2000). Renewing public education: Charter schools in action.Princeton: Princeton University Press.

Fletcher-Flinn, C. M., & Gravatt, B. (1995). The efficacy of computer assisted instruction (CAI): a meta-analysis. Journal of Educational Computing Research, 12(3), 219–242.

Flynn, K. & Hill, J. (2005). English Language Learners: A growing Population. Retrieved from the Mid-continent Research for Education and Learning Web Site http://www.mcrel.org/pdf/policybriefs/5052pi_pbenglishlanguagelearners.pdf

Garcia, M. R., & Arias, F. V. (2000). A comparative study in motivation and learning through print-orientedand computer-oriented tests. Computer Assisted Language Learning, 13(4–5), 457–465. Retrievedfrom Academic Search Premier database.

Gips, A., DiMattia, P., & Gips, J. (2004). The effect of assistive technology on Educational costs: Two casestudies”, in K. Miesenberger, J. Klaus, W. Zagler, D. Burger (eds.), Computers Helping People withSpecial Needs, Springer, 2004, pp. 206–213.

Herrel, N., Olevitch, L., DuBois, D. K., Terry, P., Thor, D., Kind, E., et al. (2004). Somali refugee womenspeak out about their needs for care during pregnancy and delivery. Journal of Midwifery & Women’sHealth, 49(4), 345–349.

Hubbell, E.R. (2011). Before Adopting a Laptop Initiative. The School Administrator, 68(2), 36–37.Retrieved from http://www.aasa.org/SchoolAdministratorArticle.aspx?id017830

Kang, S. H., & Dennis, J. R. (1995). The effects of computer-enhanced vocabulary lessons on achievementof ESL grade school children. Computers in the Schools, 11(3), 25–35.

Keengwe, J. (2007). Faculty Integration of Technology into instruction and students’ perceptions ofcomputer technology to improve student learning. Journal of Information Technology Education, 6,169–180.

Keengwe, J., & Onchwari, G. (2008). Constructivism, technology, and meaningful learning. In T. Kidd &H. Song (Eds.), Handbook of Research on Instructional Systems and Technology (pp. 51–64). Hershey:Information Science Reference.

Kozma, R. B. (1991). Learning with media. Review of Educational Research, 61(2), 179–211.Kulik, J. (1994). Meta-analytic studies of findings on computer-based instruction. In E. L. Baker & H. F.

O’Neil Jr. (Eds.), Technology assessment in education and training. Hillsdale: Lawrence Erlbaum.Lai, C. (2006). The advantages and disadvantages of computer technology in second language acquisition.

National Journal for Publishing and Mentoring Doctoral Student Research, 3(1), 1–6.Lazaridou, A., & Fris, J. (2005). Charter schools: a matter of values. Managerial Models and Choice in

Schooling, 23(3), 47–67.Lee, K.W. (2000). English teachers’ barriers to the use of Computer assisted language learning. The Internet

TESL journal, Retrieved from http://www.4english.cn/englishstudy/xz/thesis/barrirLiaw, M. L. (1997). An analysis of ESL children’s verbal interaction during computer book reading.

Computers in the Schools, 13(3/4), 55–73.Minneapolis Public School. (2009). Somali language spoken in Minneapolis public school. Retrieved from

http://ell.mpls.k12.mn.us/uploads/Languages_Spoken_in_Mpls_Public_Schools_2.pdfMurphy, R. F., Panuel, W. R., Means, B., Korbak, C., Whaley, A., & Allen, J. E. (2002, April). E-DESK: A

review of recent evidence on the effectiveness of discrete educational software. Menlo Park, CA: SRIInternational. Retrieved from http://ctl.sri.com/publications/downloads/task3_finalreport3.pdf

Nathan, J. (1996). Charter schools: Creating hope and opportunity for American education. San Francisco:Jossey-Bass.

National Center for Education Statistics. (2004). English Language Learner Students in U.S. PublicSchools: 1994 and 2000. Retrieved from the NCES web site http://nces.ed.gov/pubs2004/2004035.pd

National Clearinghouse for English Language Acquisition and Language Instruction Educational Programs(NCELA), 2007. Retrieved from www.ncela.gwu.edu/expert/

Niemiec, R., & Walberg, H. J. (1987). Comparative effects of computer-assisted instruction: a synthesis ofreviews. Journal of Educational Computing Research, 3, 19–37.

Salaberry, M. R. (2001). The use of technology for second language learning and teaching: a retrospective.Modern Language Journal, 85(1), 39–56.

Sandholtz, J. H., & Reilly, B. (2004). Teachers, not technicians: rethinking technical expectations forteachers. Teachers College Record, 106(3), 487–512.

Educ Inf Technol (2014) 19:295–306 305

Schacter, J., & Fagnano, C. (1999). Does computer technology improve student learning and achievement?How, when, and under what conditions? Journal of Educational Computing Research, 20(4), 329–343.

Sivin-Kachala, J. (1998). Report on the effectiveness of technology in schools, 1990–1997. Washington,DC: Software Publisher’s Association.

Solomon, L., & Goldschmidt, P. (2004). Comparison of traditional public schools and charter schools onretention, school switching, and achievement growth. Phoenix, AZ: The Goldwater Institute. Retrievedfrom http://www.goldwaterinstitute.org/file/3285/download/3285

Stetter, M., & Hughs, M. (2011). Computer assisted instruction to promote comprehension in students withlearning special needs. International Journal of Special Education, 26(1), 88–100.

Tamim, R., Bernard, R., Borokhovski, E., Abrami, P., & Schmid, R. (2011). What forty years of researchsays about the impact of technology on learning: a second-order meta-analysis and validation study.Review of Educational Research, 81(4), 4–28.

U.S. Department of Education. (2005, April). Internet access in U.S. public schools and classroom: 1994–2003; and unpublished tabulations. Retrieved from http://nces.ed.gov/pgrograms/digest/d05/tables/dt05_416.asp

Wachira, P., & Keengwe, J. (2011). Technology Integration Barriers: Urban School Mathematics TeachersPerspectives. Journal of Science Education and Technology, 20(1), 17–25.

Weil, D. (2000). Charter schools: A reference handbook. Santa Barbara: ABCCLIO.

306 Educ Inf Technol (2014) 19:295–306