The Simple View of Reading (SVR; Gough & Tunmer, 1986; Hoover & Gough, 1990) has a longstanding history as a model of reading comprehension, but it has mostly been applied to native English speakers. The SVR posits reading comprehension is a function of the interaction between word-level reading skills and oral language skills. It has been useful in identifying subgroups of English monolinguals characterized by difficulties in word-level reading, oral language comprehension, or both (e.g. Catts, Adlof, & Weismer, 2006). However, applications investigating heterogeneous subgroups in samples of non-native English speakers are lacking. This study uses the SVR as a framework to explicitly model heterogeneity within a group of Spanish-speaking English language learners (ELLs). First, using latent profile analysis, this study empirically identified subgroups of ELLs based on reading and language skills in both Spanish and English. Three subgroups were identified, two based on relative language proficiency in Spanish and English. The first subgroup demonstrated the highest achievement across all measures, but was also characterized by relative strengths in Spanish compared to English. The second subgroup performed at the average level across most measures, but was also characterized by relative strengths in English compared to Spanish. The third group performed the lowest and did not show demonstrate substantial relative strengths in either language. Second, a regression mixture model was conducted to examine whether the SVR functioned differently across subgroups. Results demonstrated the predictive relationships posited in the SVR were moderated by membership in the subgroups and that Spanish-speaking ELLs should not be treated as a homogenous population in terms of reading comprehension and its component skills. This study is one of the first to treat Spanish-speaking ELLs as a heterogeneous group and sheds light on conflicting results found in previous research. Implications and directions for future research are discussed.

The goal of the present study was to examine how effective use of teaching strategies predict reading growth among a sample of English Language Learners. The study specifically examined whether the types of teaching strategies that predict growth in decoding skills also predict growth in comprehension skills. The sample consisted of students in 1st grade (n=115) and 2nd grade (n=95) who were identified as English Language Learners by their California English Language Development Test (CELDT) scores. Students were assessed with decoding and comprehension reading measures in the Fall of the first year of the study and in the Fall of the second year of the study. Classroom observations were conducted at three time points during the school year during language arts instruction. The English Language Learner Classroom Observation Instrument was completed to record objective measures of reading instruction during classroom activities. A total of 24 first-grade (n=14) and second-grade (n=10) classrooms were observed over the course of the first year of the study. Our findings suggest that teaching strategies are differentially effective for different reading skills and outcomes. This suggests that instructional intent is important to consider in the implementation of teaching strategies. Growth in beginning stages of reading such as sight-word reading might be associated primarily with strategies targeting engagement, while reading skills such as decoding and comprehension require strategies in which the teacher is focused on modeling skills and strategies and monitoring student comprehension. Our preliminary analyses suggest that there are different sets of strategies that are uniquely effective depending on the desired reading outcome.

The technological nature of the world we live in has produced a need for a workforce that is technologically savvy and possesses 21st century skills and abilities. Given that students with a learning disability (LD) may be an untapped source of science, technology, engineering, and mathematics (STEM) or career and technical education (CTE) potential, it is important to understand 1) whether LD students are capable of pursuing STEM and CTE fields and 2) what will aid them in successfully pursuing those fields. The two studies presented aim to answer those questions through a latent profile and latent class analysis. The results from the first study indicated that there are two STEM capable profiles of LD students: High-STEM and CTE Capability or Low-STEM Capability. It was found that female LD students were significantly more likely to be in the High-STEM and CTE Capability profile (.75, p < .05) by 2.11 times and that African-American LD students were significantly more likely to be found in the Low-STEM Capability profile (-1.31, p < .10). It was also more prevalent for LD students to pursue either STEM or CTE at the 2-year college regardless of what profile they resided in. Understanding a students’ STEM or CTE capability can play a role in how they prepare and plan for their future. For the second study it was found that LD students could be categorized into three engagement classes: Highly Engaged LD Students, Moderately Engaged LD Students, and Poorly Engaged LD Students. Again, gender played a role in students’ classification and it was found that female students were significantly more likely to be in the Moderately Engaged class (.22, p < .05). Results from this study also indicate that the 2-year pathway is the most traversed by LD students. LD students who were engaged in their IEP process, possess self-determination, and are able to utilize accommodations were more successful in pursuing a STEM and CTE field. Implications for postsecondary institutions will be discussed.

Community college transfer students often experience transfer shock at receiving four-year institutions, which includes a variety of academic, social, and institutional challenges associated with the first-year transfer experience. Research has demonstrated that first-year program interventions can facilitate the transition of first-year college students, and increase persistence and completion. To date, however, there is a dearth of literature on first-year transfer student program interventions and whether these programs would help transfer students acclimate to four-year research institutions. Furthermore, extant literature on the post-transfer experience often groups all transfer students into a single homogeneous student population, which ignores the heterogeneity of this population. Therefore, the purpose of this study is to fill a gap in the literature by using a latent class analysis (LCA) to examine whether meaningful subgroups of transfer students emerged based on their response patterns to academic and social adjustment items. Three covariates (i.e., race and ethnicity, participation in a first-year Transfer Student Success Course, and major) were also added into the LCA model to determine the student characteristics of each of the subgroups. The distal outcome, drop in GPA, was also included in the LCA model to determine whether the subgroups varied on this measure. Data from a newly developed survey, the Transfer Student Transition Survey (TSTS), were used for this study. This survey was distributed to three cohorts of first-year transfer students at a large selective public research university in California. The results of this study indicated the emergence of four transfer student subgroups. Additionally, participants who enrolled in a first-year Transfer Student Success Course were more likely to be in the ideal class, Higher Level of Academic and Social Adjustment (HighA/HighS), which had a higher probability of endorsement on both the academic and social adjustment items. This class also had the smallest drop in GPA across classes. Furthermore, STEM majors were most likely to belong in the lowest class, Lower Level of Academic Adjustment and Social Adjustment (LowA/LowS), which had lowest probability of endorsement on most of the academic and social adjustment items. This study is one of the first to examine community college transfer students as a heterogeneous group and empirical support for first-year transfer student program interventions. Implications for practice, policy and future research are discussed.