THE EFFECT OF BALANCED STRATEGY INSTRUCTION ON ENGLISH LANGUAGE LEARNER LITERACY

English Language Learner (ELL) achievement on standardized testing in a second language (L2; English) has been shown to be compromised due to L2 literacy deficits demonstrated by many of these students (Cheng, Fox, & Zheng, 2007; Solorzano, 2008; Zheng, Cheng, & Klinger, 2007). ELL achievement results on the Ontario Secondary School Diploma (OSSD) literacy requirement, the Ontario Secondary School Literacy Test (OSSLT), have remained consistently a minimum of 10% below that of students whose first language (L1) is English (Education Quality and Accountability Office, 2015a). The focus of this quasi-experimental study was to improve ELL L2 literacy, specifically achievement of reading skills, using a targeted intervention which consisted of a series of balanced strategy literacy sessions. This explicitly instructed balanced strategy literacy program was delivered in an after school format to secondary school ELL students who were randomly assigned to treatment (use of L1 and L2) and sub-treatment groups (use of L2 only). Balanced strategy instruction utilized the construction-integration model of reading comprehension (Kintsch, 1988) as a direct application of social-cognitive constructivist theory to engage students in the building of L2 literacy skills through choral reading, guided reading, independent reading, peer discussions and high interest vocabulary development. Research results indicated that the treatment method used did not have a significant effect on ELL achievement of reading skills in L2, as measured by the 2014 OSSLT in comparison to pre-intervention achievement on the 2010 OSSLT. Research results also indicated higher achievement levels on the 2014 OSSLT for ELL students who had greater exposure to L2 development (e.g., prior courses, daily practice). Following the study, the ELL students’ development of L2 literacy skills continued within the context of secondary school credit courses towards successful completion of the OSSD. These findings suggest that more research is needed to determine the effective implementation of balanced strategy literacy programming as a support to ELL demonstration of graduation diploma requirements

When Reading Goes Digital: Conceptual and Methodological Reviews on Technology and L2 Vocabulary Learning

Existing research syntheses on technology and second language acquisition have called for further systematic investigation of the theoretical frameworks and methodologies used in research of this field. Additionally, although vocabulary has been one of the most popular areas in technology-integrated second language acquisition research, a majority of the previous studies have examined college students or other adult populations. To fill these gaps, this dissertation systematically reviewed the theoretical and methodological trends in research on technology-integrated L2 vocabulary learning for PreK-12 learners of English. A total of 60 studies published between 2008 and 2018 were selected for analysis. The types of vocabulary knowledge, affordances of technology, and major theoretical frameworks were analyzed to uncover conceptual and theoretical trends; study context, participant demographics, research design, and outcome measures were analyzed for the methodological characteristics of the selected studies. The theoretical review showed that the current research on technology-integrated L2 vocabulary learning for young learners was mostly guided by information/cognitive processing theories, social constructivism, and sociocognitive theories. However, a large body of the studies indicated a lack of direct reference to a theoretical framework, which demonstrated a need to strengthen the connections among theory, research, and practice in this field. The analysis of methodological characteristics has revealed several areas for further improvement, such as more complete reporting of the participant’s English proficiency level, consistent reporting of study duration and length of treatment, and more research in English as second language contexts

Time to Act: An Agenda for Advancing Adolescent Literacy for College and Career Success

Presents a vision for literacy instruction from fourth through twelfth grade; examines the challenges; outlines the elements of success, including professional development and use of data; and lays out a national agenda for change based on case studies

Annotated Bibliography of Research in the Teaching of English (2009)

This is the publisher's version, also found at http://search.proquest.com/docview/215343848/13E80C2B60056B43EE4/5?accountid=1455

Finding the Right Fit: Exploring ESL Teachers and Students’ Perceptions of iLit ELL, a Technology-based Literacy Program’s Use with High School English Language Learners

The purpose of this interpretative phenomenological study was to explore the lived experiences ESL secondary teachers and their perceptions towards the use, effects and integration of iLit ELL, a technology-based language program designed for English Language Learners, as well as, the perceived effects the program had on students’ motivation and attitudes towards learning English. Data were collected using teacher interviews, student focus groups and final reflections, as well as my observations and field notes. The collected data were analyzed through the steps of Interpretive Phenomenological Analysis (IPA) to broaden the breadth and depth of the content and complexity of each narrative independently. Data were then compared across individual experiences and interpreted in a dynamic and active process, that involved double hermeneutics, which focuses on two interpretations: first, the participants’ interpretations of their own experience, followed by the researcher’s interpretation of the participants’ interpretations (Smith, Flowers & Larkin, 2009). Based on the data collected over the course of the study, major findings indicated that technology integration is affected by teachers’ adaptability to change; teacher mindset effects teachers’ acceptance, integration and effective use of technology; when applied purposefully, technology and differentiated instruction increases student motivation and teachers’ efficiency; and, technology with embedded scaffolds can enhance student autonomy and motivate student learning. From the emerging themes, the following recommendations are suggested for stakeholders and future research: differentiated professional development for teachers; applying consistent school and system-wide supports and beliefs on technology; adopting a universal designs method to teaching; further exploring teacher perceived efficacy and actual performance of technology integration; and a comparative study exploring best instructional models

The Smartpen as a Mediational Tool for Learning Language and Content Areas: The Case of English Learners in Mainstream Classrooms

The use of mobile devices for supporting the instruction of second language (L2) learners is an emerging and rapidly growing area of inquiry. Previous research on mobile assisted language learning (MALL) has concentrated on the development of isolated linguistic skills through a common set of mobile technologies, such as PDAs and iPods, with limited attention given to alternative mobile devices or situations of L2 learning that require the simultaneous learning of language and academic content (Wu, Jim Wu, Chen, Kao, Lin, & Huang, 2012; Viberg & Grönlund, 2012; 2013). In particular, little is understood about how English Learners (ELs) educated within mainstream classrooms choose to appropriate mobile technologies to meet their learning needs, with respect to both their development linguistically and across academic course disciplines. To inform this gap in research, this study used a quasi-ethnographic, instrumental case study design to explore how a group of middle school ELs used an understudied mobile device, the Echo Smartpen, to mediate their learning of language skills (e.g., speaking, reading, writing, listening, vocabulary) and of academic content areas (e.g., math, science, social studies). It also sought to examine how the Smartpen could assist ELs\u27 learning processes with respect to individual learner characteristics (e.g., affective, cognitive, metacognitive). To accomplish this purpose, multiple sources of data were collected from seven student participants, their English as a Second Language (ESL) specialist, and primary mainstream teacher. These sources consisted of technologically-mediated digital data, such as the students\u27 digitized notebooks, as well as traditional methods qualitative data collection, including individual and focus group interviews, and learning artifacts. The overall theoretical framework guiding the data analysis was Vygotskian sociocultural theory (SCT), complemented by grounded theory and the constant comparison coding method (Strauss & Corbin, 1990; 1998). Key principles for the analysis were the Vygotskian notions of mediated learning through physical and psychological tool use (Lantolf, 2000). Findings from this study provide insights about the process of mediated language and content learning with the Smartpen for ELs clustered around three major themes: 1) extended opportunities for language learning through self-constructed artifacts; (2) extended opportunities for content learning through co-constructed artifacts; and (3) extended learning self with the Smartpen. In addition to the main emergent themes, research findings incorporate the participant-based metaphorical concept of time travel as an important sub-thematic element in tracing ELs\u27 use of the Smartpen across temporal and educational contexts (e.g., school and home). Finally, this study concludes with a discussion of theoretical and pedagogical implications for the integration of mobile devices for ELs in mainstream settings, as well as with recommendations for future research deriving from this research

Improved collaborative filtering using clustering and association rule mining on implicit data

The recommender systems are recently becoming more significant due to their ability in making decisions on appropriate choices. Collaborative Filtering (CF) is the most successful and most applied technique in the design of a recommender system where items to an active user will be recommended based on the past rating records from like-minded users. Unfortunately, CF may lead to poor recommendation when user ratings on items are very sparse (insufficient number of ratings) in comparison with the huge number of users and items in user-item matrix. In the case of a lack of user rating on items, implicit feedback is used to profile a user’s item preferences. Implicit feedback can indicate users’ preferences by providing more evidences and information through observations made on users’ behaviors. Data mining technique, which is the focus of this research, can predict a user’s future behavior without item evaluation and can too, analyze his preferences. In order to investigate the states of research in CF and implicit feedback, a systematic literature review has been conducted on the published studies related to topic areas in CF and implicit feedback. To investigate users’ activities that influence the recommender system developed based on the CF technique, a critical observation on the public recommendation datasets has been carried out. To overcome data sparsity problem, this research applies users’ implicit interaction records with items to efficiently process massive data by employing association rules mining (Apriori algorithm). It uses item repetition within a transaction as an input for association rules mining, in which can achieve high recommendation accuracy. To do this, a modified preprocessing has been employed to discover similar interest patterns among users. In addition, the clustering technique (Hierarchical clustering) has been used to reduce the size of data and dimensionality of the item space as the performance of association rules mining. Then, similarities between items based on their features have been computed to make recommendations. Experiments have been conducted and the results have been compared with basic CF and other extended version of CF techniques including K-Means Clustering, Hybrid Representation, and Probabilistic Learning by using public dataset, namely, Million Song dataset. The experimental results demonstrate that the proposed technique exhibits improvements of an average of 20% in terms of Precision, Recall and Fmeasure metrics when compared to the basic CF technique. Our technique achieves even better performance (an average of 15% improvement in terms of Precision and Recall metrics) when compared to the other extended version of CF techniques, even when the data is very sparse