In response to federal policy and the COVID-19 pandemic, schools and districts are using technology to support students designated as English learners (ELs). However, school leaders and teachers have little guidance about how to implement technology effectively to foster these students’ language development and content instruction. To address this need, Jennifer Altavilla raises three concerns specific to technology use with ELs: (1) Technology accessibility and use are equally important, (2) Technologies have baked-in biases, (3) Technology should promote authentic social interaction.
AhnT. Y.LeeS. M. (2016). User experience of a mobile speaking application with automatic speech recognition for EFL learning. British Journal of Educational Technology, 47(4), 778–786.
2.
AndreiE. (2017). Technology in teaching English language learners: The case of three middle school teachers. TESOL Journal, 8 (2), 409–431.
3.
AshwellT.ElamJ. R. (2017). How accurately can the Google Web Speech API recognize and transcribe Japanese L2 English learners’ oral production?Jalt Call Journal, 13(1), 59–76.
4.
AttewellP. (2001). Comment: The first and second digital divides. Sociology of Education, 252–259.
5.
AttewellP. (1999). Home computers and school performance. The Information Society, 15 (1), 1–10.
6.
ConiamD. (1999). Voice recognition software accuracy with second language speakers of English. System, 27 (1), 49–64.
7.
CucchiariniC.StrikH. (2018). Second language learners’ spoken discourse: Practice and corrective feedback through automatic speech recognition. In Smart Technologies: Breakthroughs in Research and Practice (pp. 367–389). IGI Global.
8.
DeaneP. (2013). On the relation between automated essay scoring and modern views of the writing construct. Assessing Writing, 18 (1), 7–24.
9.
DerwingT.M.MunroM.J.CarbonaroM. (2000). Does popular speech recognition software work with ESL speech?. TESOL Quarterly, 34 (3), 592–603.
10.
FirthA.WagnerJ. (1997). On discourse, communication and (some) fundamental concepts in SLA research. Modern Language Journal, 91, 285–300.
11.
FloresN.RosaJ. (2015). Undoing appropriateness: Raciolinguistic ideologies and language diversity in education. Harvard Educational Review, 85(2), 149–171.
12.
FreemanB. (2012). Using digital technologies to redress inequities for English language learners in the English speaking mathematics classroom. Computers & Education, 59 (1), 50–62.
13.
HananiA.RussellM.J.CareyM.J. (2013). Human and computer recognition of regional accents and ethnic groups from British English speech. Computer Speech & Language, 27 (1), 59–74.
14.
HargittaiE. (2002). Second-level digital divide: Differences in people’s online skills. First Monday, 7 (4).
15.
HoangG.T.L.KunnanA.J. (2016). Automated essay evaluation for English language learners: A case study of MY Access. Language Assessment Quarterly, 13 (4), 359–376.
IsaacsT. (2018). Shifting sands in second language pronunciation teaching and assessment research and practice. Language Assessment Quarterly, 15(3), 273–293.
18.
KewalRamaniA.ZhangJ.WangX.RathbunA.CorcoranL.DilibertiM.ZhangJ. (2018). Student access to digital learning resources outside of the classroom (NCES 2017-098). Washington, DC: National Center for Education Statistics.
19.
Kukulska-HulmeA.ShieldL. (2008). An overview of mobile assisted language learning: From content delivery to supported collaboration and interaction. ReCALL, 20 (3), 271–289.
20.
LevyM. (2009). Technologies in use for second language learning. The Modern Language Journal, 93, 769–782.
21.
LiJ.CumminsJ.DengQ. (2017). The effectiveness of texting to enhance academic vocabulary learning: English language learners’ perspective. Computer Assisted Language Learning, 30 (8), 816–843.
22.
LitmanD.StrikH.LimG. S. (2018). Speech technologies and the assessment of second language speaking: Approaches, challenges, and opportunities. Language Assessment Quarterly, 15(3), 294–309.
23.
LiuM.MooreZ.GrahamL.LeeS. (2002). A look at the research on computer-based technology use in second language learning: A review of the literature from 1990–2000. Journal of Research on Technology in Education, 34 (3), 250–273.
24.
LiuM.NavarreteC.C.WivaggJ. (2014). Potentials of mobile technology for K-12 education: An investigation of iPod touch use for English language learners in the United States. Journal of Educational Technology & Society, 17 (2), 115–126.
25.
LucasT.VillegasA. M.Freedson-GonzalezM. (2008). Linguistically responsive teacher education: Preparing classroom teachers to teach English language learners. Journal of Teacher Education, 59 (4), 361–373.
26.
McSweeneyM. (2017). I text English to everyone: Links between second-language texting and academic proficiency. Languages, 2 (3), 7.
27.
National Center for Education Statistics (2018). Student access to digital learning resources outside the classroom. Washington, DC: Author. nces.ed.gov/pubs2017/2017098/guide.asp
28.
National Center for Education Statistics. (2019). English language learners in public schools. Washington, DC: Author. nces.ed.gov/programs/coe/indicator_cgf.asp.
29.
National Science Board. (2018). Science and engineering indicators 2018. Arlington, VA: National Science Foundation. www.nsf.gov/statistics/2018/nsb20181
30.
NeriA.CucchiariniC.StrikH. (2003, January). Automatic speech recognition for second language learning: How and why it actually works. In SoleM.J.RecasensD.RomeroJ. (Eds), Proceedings of the 15th International Congress of Phonetic Sciences (pp. 1157–1160), Barcelona.
31.
PiersonM.E. (2001). Technology integration practice as a function of pedagogical expertise. Journal of Research on Computing in Education, 33 (4), 413–430.
32.
RanalliJ.LinkS.Chukharev-HudilainenE. (2017). Automated writing evaluation for formative assessment of second language writing: investigating the accuracy and usefulness of feedback as part of argument-based validation. Educational Psychology, 37 (1), 8–25.
33.
RotermundS.DeRocheJ.OttemR. (2017). Teacher professional development by selected teacher and school characteristics: 2011-12(NCES 2017-200). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
34.
SchmidE.C. (2008). Potential pedagogical benefits and drawbacks of multimedia use in the English language classroom equipped with interactive whiteboard technology. Computers & Education, 51 (4), 1553–1568.
35.
Solano-FloresG.TrumbullE. (2008). In what language should English language learners be tested? In KoprivaR.J. (Ed.), Improving testing for English language learners. New York, NY: Routledge.
StevensonM.PhakitiA. (2019). Automated feedback and second language writing. In HylandK.HylandF. (Eds.), Feedback in second language writing: Contexts and issues (pp. 125–142). New York, NY: Cambridge University Press.
U.S. Department of Education. (2017b). Reimagining the role of technology in education: 2017 national education technology plan update. Washington, DC: U.S. Department of Education, Office of Educational Technology. tech.ed.gov/files/2017/01/NETP17.pdf.
ValadézJ.R.DuránR.P. (2007). Redefining the digital divide: Beyond access to computers and the internet. The High School Journal, 90 (3), 31–44
43.
WalquiA.van LierL. (2010). Scaffolding the academic success of adolescent English language learners: A pedagogy of promise. San Francisco, CA: WestEd.
44.
WarschauerM. (2012). The digital divide and social inclusion. Americas Quarterly, 6 (2), 131–135.
45.
WarschauerM.KnobelM.StoneL. (2004). Technology and equity in schooling: Deconstructing the digital divide. Educational Policy, 18 (4), 562–588.
46.
WatsonJ.PapeL.MurinA.GeminB.VashawL. (2015). Keeping pace with K–12 digital learning: An annual review of policy and practice. Durango, CO: Evergreen Education Group.
47.
WeigleS.C. (2013). English language learners and automated scoring of essays: Critical considerations. Assessing Writing, 18 (1), 85–99.
48.
WittS.M.YoungS.J. (2000). Phone-level pronunciation scoring and assessment for interactive language learning. Speech Communication, 30 (2-3), 95–108.
49.
ZhaoY.Alvarez-TorresM.J.SmithB.TanH. S. (2004). The non-neutrality of technology: A theoretical analysis and empirical study of computer mediated communication technologies. Journal of Educational Computing Research, 30 (1-2), 23–55.
