Seeking Effective Policies and Practices for English Language Learners

A study by the Rennie Center for Education Research and Policy finds that English language learners (ELLs), a rapidly growing percentage of the Commonwealth's student population, are qualifying for transition into mainstream classrooms at a much slower pace than originally expected. The report examines the evolution of policies and practices affecting ELLs since the passage of Question 2 in November 2002. Question 2 mandated English immersion as the primary means of instruction for most ELLs and compelled schools to expedite the transition of students to mainstream classes. While Question 2 sought to limit English learners' immersion experience to a "period not normally intended to exceed one school year," federal Civil Rights legislation trumped Question 2 and mandated that students could not be re-classified out of ELL status until they can "participate meaningfully" in English-only classes.The Rennie Center's report examines whether expectations for an expedited transition process have been met and explores the ways in which the state Department of Education and schools and districts have tried to make sense of the conflicting mandates on what constitutes an adequate amount of time for a student to become proficient in English.Data from the Massachusetts English Proficiency Assessment (MEPA), a test designed to gauge the progress of English language learners, shows that after one year of English immersion only 17% of ELLs score at levels indicating they are ready to transition to mainstream classrooms. Among ELLs who have been in Massachusetts' schools for five or more years, only slightly more than half score at the transitioning level. The report also found that schools throughout Massachusetts have developed diverse ways of interpreting and implementing sheltered English immersion.At a time of national debate about the status of immigrants and sharp increases in the numbers of non-English speakers in cities and towns across the Commonwealth and nation, it is critical that public schools focus greater attention on the issue of how best to meet the needs of English language learners. The report cites that while ten years ago only slightly more than half the school districts in Massachusetts enrolled ELLs, today that proportion has soared to nearly three-quarters. The number of districts enrolling one hundred or more English language learners has risen 37% in the past decade.As the number of English language learners continues to rise, their performance persistently lags far behind that of native English speakers. According to the Rennie Center's report, ELLs scored below the median at every grade level in every subject on the Massachusetts Comprehensive Assessment System (MCAS). Further, ELLs are 57% less likely than their native English-speaking peers to earn the competency determination needed to graduate from high school. Both the No Child Left Behind legislation and the Massachusetts Education Reform Act require schools to ensure that ELLs meet the same performance standards as their native English-speaking counterparts. According to report authors, "That we are so woefully far from that goal should be cause for alarm and action."The Rennie Center's study seeks to shed light on this issue by providing an analysis of policies and practices affecting ELLs in Massachusetts over the past five years and examining the state role in promoting improved practice. The report includes case studies of three schools that are making significant strides with large populations of English language learners and highlights common elements that the three schools have utilized to successfully meet the needs of English language learners. For example, each school studied offered multiple types of programs to accommodate the needs of students at varying levels of English proficiency, rather than a one-size-fits-all approach. Case study schools also developed a staged transition process that provided vital support as students moved into mainstream classes.Next Steps at the State and District LevelsIn a series of recommended next steps, the report urges state policymakers to encourage flexibility and experimentation with innovative approaches to meet the needs of English language learners;offer opportunities for schools to share practices;get specific about when students should transition out of ELL status and to provide clear guidance to schools and districts;ensure a pipeline of leaders for ELL programs;require sheltered English immersion training in teacher preparation programs.And schools and districts to:consider staged transition processes;set goals and create incentives to get teachers trained;pool resources among districts with small ELL populations; andfocus more attention on reaching out to communicate with and provide guidance for the families of ELLs.The report, Seeking Effective Policies and Practices for English Language Learners, was released at a public event on May 31, 2007 in Marlborough, MA

Leveraging online user feedback to improve statistical machine translation

In this article we present a three-step methodology for dynamically improving a statistical machine translation (SMT) system by incorporating human feedback in the form of free edits on the system translations. We target at feedback provided by casual users, which is typically error-prone. Thus, we first propose a filtering step to automatically identify the better user-edited translations and discard the useless ones. A second step produces a pivot-based alignment between source and user-edited sentences, focusing on the errors made by the system. Finally, a third step produces a new translation model and combines it linearly with the one from the original system. We perform a thorough evaluation on a real-world dataset collected from the Reverso.net translation service and show that every step in our methodology contributes significantly to improve a general purpose SMT system. Interestingly, the quality improvement is not only due to the increase of lexical coverage, but to a better lexical selection, reordering, and morphology. Finally, we show the robustness of the methodology by applying it to a different scenario, in which the new examples come from an automatically Web-crawled parallel corpus. Using exactly the same architecture and models provides again a significant improvement of the translation quality of a general purpose baseline SMT system

Effects of Dual Language Protocol on Literacy Development of Yup\u27ik Language Students

This dissertation in teacher leadership represents original, independent research that investigated bilingual language instruction of an indigenous Alaskan group of students. Ethnographic research using qualitative and quantitative data was applied to develop an understanding of correlations between the value of English and Yup’ik language and dual language classroom protocol and pedagogy. This research included cultural insight into the history of language transition, influence of Westernized educational system, and teachers’ and community members’ attitudes toward bilingual instruction. Dual language enrichment model instruction and teacher efficacy in dual language pedagogy were assessed based upon 3rd grade student reading proficiency outcomes. Observational and interview data provided insight into factors affecting language instruction

Dual Language Elementary Teacher Supports in Rocky Mountain Resort Communities

Dual language (DL) programs have been proven to increase student achievement (Thomas & Collier, 2002; Thomas, Collier, & Collier, 2010) but a gap remains in how to support teachers in their instruction of Spanish to both English home language and Spanish home language students. This mixed methods, explanatory, sequential design study was conducted in two Rocky Mountain resort communities in two school districts. Participants were chosen based on the research criterion of being DL elementary teachers in rural amenity-based destinations. The Guiding Principles for Dual-language Education (Howard et al., 2018) was used as the conceptual framework. Data were obtained from three sources: an online survey using demographic data, the Guiding Principles for Dual-language Education, face-to-face interviews, and field notes. The online survey was sent to 116 elementary DL teachers in eight schools; 44 participants responded. In the follow-up face-to-face interviews, eight participants were interviewed. Data from the online survey were triangulated with transcripts from the interviews and field notes. The main results from this study revealed elementary dual language teachers in rural amenity destinations identified several important supports related to the implementation and maintenance of a successful DL: support through human interaction such as principals and coordinators, collaboration time, a collaborative culture, PTA/conferences, family, and community. Teachers recognized they would feel more supported if needed or desired supports were not lacking. A lack of Spanish resources and retaining qualified Spanish teachers were identified as having an impact on both English and Spanish DL elementary teachers. The implications of sharing the identified supports of this study could illuminate educators regarding the implementation or maintenance of DL programs

Cross-Lingual Link Discovery for Under-Resourced Languages

CC BY-NC 4.0In this paper, we provide an overview of current technologies for cross-lingual link discovery, and we discuss challenges, experiences and prospects of their application to under-resourced languages. We first introduce the goals of cross-lingual linking and associated technologies, and in particular, the role that the Linked Data paradigm (Bizer et al., 2011) applied to language data can play in this context. We define under-resourced languages with a specific focus on languages actively used on the internet, i.e., languages with a digitally versatile speaker community, but limited support in terms of language technology. We argue that languages for which considerable amounts of textual data and (at least) a bilingual word list are available, techniques for cross-lingual linking can be readily applied, and that these enable the implementation of downstream applications for under-resourced languages via the localisation and adaptation of existing technologies and resources

Unlocking the archives

The popular expression ‘locked in the archive’ suggests that items are impossible to find and access once they are archived. Benefiting from new technologies, digital language and music archives nowadays provide an increasing number of records online in and about the world’s small languages. Just six of these archives list between them over 31,000 items, representing something like 2,300 languages. We can certainly do better at making records more widely available—especially records from small, marginalised and sometimes isolated communities—but how do we build pathways for re-use? We discuss the practice of the Pacific and Regional Archive for Digital Sources in Endangered Cultures (PARADISEC) through the rubric provided by the FAIR principles. Building resources for learning and teaching language, history and culture, revitalising local performance traditions or reinforcing social identity through broadcasting are all possible pathways for future re-use of archival material. Ultimately, it is up to community members to decide on what they will do with archival materials once they have access; and it is up to language archives to listen and do our best to keep the pathways open to enable that.Endangered Archives Programme grant 693 (Preservation of Solomon Islands analogue recordings), Australian Research Council LIEF program (2003, 2004, 2006, 2011), ELDP LMG0009 Vanuatu Cultural Centre tape digitisation, ARC Centre of Excellence for the Dynamics of Language, ARC Future Fellowship FT140100214, Australian Research Council DP1096897, LP140100806, LP160100743

Leveraging online user feedback to improve statistical machine translation

In this article we present a three-step methodology for dynamically improving a statistical machine translation (SMT) system by incorporating human feedback in the form of free edits on the system translations. We target at feedback provided by casual users, which is typically error-prone. Thus, we first propose a filtering step to automatically identify the better user-edited translations and discard the useless ones. A second step produces a pivot-based alignment between source and user-edited sentences, focusing on the errors made by the system. Finally, a third step produces a new translation model and combines it linearly with the one from the original system. We perform a thorough evaluation on a real-world dataset collected from the Reverso.net translation service and show that every step in our methodology contributes significantly to improve a general purpose SMT system. Interestingly, the quality improvement is not only due to the increase of lexical coverage, but to a better lexical selection, reordering, and morphology. Finally, we show the robustness of the methodology by applying it to a different scenario, in which the new examples come from an automatically Web-crawled parallel corpus. Using exactly the same architecture and models provides again a significant improvement of the translation quality of a general purpose baseline SMT system.Peer ReviewedPostprint (author's final draft